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Law JH, Kow AWC. Prediction and management of small-for-size syndrome in living donor liver transplantation. Clin Mol Hepatol 2025; 31:S301-S326. [PMID: 39657750 PMCID: PMC11925445 DOI: 10.3350/cmh.2024.0870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Revised: 11/19/2024] [Accepted: 12/09/2024] [Indexed: 12/12/2024] Open
Abstract
Small-for-size syndrome (SFSS) remains a critical challenge in living donor liver transplantation (LDLT), characterized by graft insufficiency due to inadequate liver volume, leading to significant postoperative morbidity and mortality. As the global adoption of LDLT increases, the ability to predict and manage SFSS has become paramount in optimizing recipient outcomes. This review provides a comprehensive examination of the pathophysiology, risk factors, and strategies for managing SFSS across the pre-, intra-, and postoperative phases. The pathophysiology of SFSS has evolved from being solely volume-based to incorporating portal hemodynamics, now recognized as small-for-flow syndrome. Key risk factors include donor-related parameters like age and graft volume, recipient-related factors such as MELD score and portal hypertension, and intraoperative factors related to venous outflow and portal inflow modulation. Current strategies to mitigate SFSS include careful graft selection based on graft-to-recipient weight ratio and liver volumetry, surgical techniques to optimize portal hemodynamics, and novel interventions such as splenic artery ligation and hemiportocaval shunts. Pharmacological agents like somatostatin and terlipressin have also shown promise in modulating portal pressure. Advances in 3D imaging and artificial intelligence-based volumetry further aid in preoperative planning. This review emphasizes the importance of a multifaceted approach to prevent and manage SFSS, advocating for standardized definitions and grading systems. Through an integrated approach to surgical techniques, hemodynamic monitoring, and perioperative management, significant strides can be made in improving the outcomes of LDLT recipients. Further research is necessary to refine these strategies and expand the application of LDLT, especially in challenging cases involving small-for-size grafts.
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Affiliation(s)
- Jia-hao Law
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, National University Hospital, Singapore
| | - Alfred Wei-Chieh Kow
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, National University Hospital, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- National University Center for Organ Transplantation (NUCOT), National University Health System, Singapore
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Cebula M, Biernacka A, Bożek O, Kokoszka B, Kazibut S, Kujszczyk A, Kulig-Kulesza M, Modlińska S, Kufel J, Azierski M, Szydło F, Winder M, Pilch-Kowalczyk J, Gruszczyńska K. Evaluation of Various Methods of Liver Measurement in Comparison to Volumetric Segmentation Based on Computed Tomography. J Clin Med 2024; 13:3634. [PMID: 38999200 PMCID: PMC11242708 DOI: 10.3390/jcm13133634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/17/2024] [Accepted: 06/17/2024] [Indexed: 07/14/2024] Open
Abstract
Background: A reliable assessment of liver volume, necessary before transplantation, remains a challenge. Our work aimed to assess the differences in the evaluation and measurements of the liver between independent observers and compare different formulas calculating its volume in relation to volumetric segmentation. Methods: Eight researchers measured standard liver dimensions based on 105 abdominal computed tomography (CT) scans. Based on the results obtained, the volume of the liver was calculated using twelve different methods. An independent observer performed a volumetric segmentation of the livers based on the same CT examinations. Results: Significant differences were found between the formulas and in relation to volumetric segmentation, with the closest results obtained for the Heinemann et al. method. The measurements of individual observers differed significantly from one another. The observers also rated different numbers of livers as enlarged. Conclusions: Due to significant differences, despite its time-consuming nature, the use of volumetric liver segmentation in the daily assessment of liver volume seems to be the most accurate method.
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Affiliation(s)
- Maciej Cebula
- Individual Medical Practice, 40-754 Katowice, Poland
| | - Angelika Biernacka
- Department of Radiodiagnostics and Invasive Radiology, University Clinical Center Prof. Kornel Gibiński of the Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Oskar Bożek
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Bartosz Kokoszka
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Sylwia Kazibut
- Department of Radiodiagnostics and Invasive Radiology, University Clinical Center Prof. Kornel Gibiński of the Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Anna Kujszczyk
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Monika Kulig-Kulesza
- Department of Radiology and Radiodiagnostics in Zabrze, Medical University of Silesia, 41-800 Katowice, Poland
| | - Sandra Modlińska
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Jakub Kufel
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Michał Azierski
- Students’ Scientific Association of MedTech, Medical University of Silesia, 40-055 Katowice, Poland
- Students’ Scientific Association of Computer Analysis and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Medical University of Silesia, 40-752 Katowice, Poland
| | - Filip Szydło
- Department of Radiodiagnostics and Invasive Radiology, University Clinical Center Prof. Kornel Gibiński of the Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Mateusz Winder
- Department of Radiodiagnostics, Invasive Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Joanna Pilch-Kowalczyk
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
| | - Katarzyna Gruszczyńska
- Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences, Medical University of Silesia, 40-752 Katowice, Poland
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Ding H, Ding ZG, Xiao WJ, Mao XN, Wang Q, Zhang YC, Cai H, Gong W. Role of intelligent/interactive qualitative and quantitative analysis-three-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation. World J Gastroenterol 2023; 29:5894-5906. [PMID: 38111507 PMCID: PMC10725563 DOI: 10.3748/wjg.v29.i44.5894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 11/10/2023] [Accepted: 11/14/2023] [Indexed: 11/27/2023] Open
Abstract
BACKGROUND Donor-recipient size mismatch (DRSM) is considered a crucial factor for poor outcomes in liver transplantation (LT) because of complications, such as massive intraoperative blood loss (IBL) and early allograft dysfunction (EAD). Liver volumetry is performed routinely in living donor LT, but rarely in deceased donor LT (DDLT), which amplifies the adverse effects of DRSM in DDLT. Due to the various shortcomings of traditional manual liver volumetry and formula methods, a feasible model based on intelligent/interactive qualitative and quantitative analysis-three-dimensional (IQQA-3D) for estimating the degree of DRSM is needed. AIM To identify benefits of IQQA-3D liver volumetry in DDLT and establish an estimation model to guide perioperative management. METHODS We retrospectively determined the accuracy of IQQA-3D liver volumetry for standard total liver volume (TLV) (sTLV) and established an estimation TLV (eTLV) index (eTLVi) model. Receiver operating characteristic (ROC) curves were drawn to detect the optimal cut-off values for predicting massive IBL and EAD in DDLT using donor sTLV to recipient sTLV (called sTLVi). The factors influencing the occurrence of massive IBL and EAD were explored through logistic regression analysis. Finally, the eTLVi model was compared with the sTLVi model through the ROC curve for verification. RESULTS A total of 133 patients were included in the analysis. The Changzheng formula was accurate for calculating donor sTLV (P = 0.083) but not for recipient sTLV (P = 0.036). Recipient eTLV calculated using IQQA-3D highly matched with recipient sTLV (P = 0.221). Alcoholic liver disease, gastrointestinal bleeding, and sTLVi > 1.24 were independent risk factors for massive IBL, and drug-induced liver failure was an independent protective factor for massive IBL. Male donor-female recipient combination, model for end-stage liver disease score, sTLVi ≤ 0.85, and sTLVi ≥ 1.32 were independent risk factors for EAD, and viral hepatitis was an independent protective factor for EAD. The overall survival of patients in the 0.85 < sTLVi < 1.32 group was better compared to the sTLVi ≤ 0.85 group and sTLVi ≥ 1.32 group (P < 0.001). There was no statistically significant difference in the area under the curve of the sTLVi model and IQQA-3D eTLVi model in the detection of massive IBL and EAD (all P > 0.05). CONCLUSION IQQA-3D eTLVi model has high accuracy in predicting massive IBL and EAD in DDLT. We should follow the guidance of the IQQA-3D eTLVi model in perioperative management.
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Affiliation(s)
- Han Ding
- Department of Transplantation, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Zhi-Guo Ding
- Department of General Surgery, The Third People’s Hospital of Yangzhou, Yangzhou 225126, Jiangsu Province, China
| | - Wen-Jing Xiao
- Department of Tuberculosis Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Xu-Nan Mao
- Department of Biliary-Pancreatic Surgery, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai 200003, China
| | - Qi Wang
- Department of Pathology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Yi-Chi Zhang
- Department of Transplantation, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Hao Cai
- Department of Transplantation, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Wei Gong
- Department of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
- Shanghai Key Laboratory of Biliary Tract Disease Research, Shanghai, 200092, China
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Yang X, Park S, Lee S, Han K, Lee MR, Song JS, Yu HC, Do Yang J. Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry. Sci Rep 2023; 13:17746. [PMID: 37853228 PMCID: PMC10584880 DOI: 10.1038/s41598-023-45140-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/16/2023] [Indexed: 10/20/2023] Open
Abstract
This study aimed at developing a fully automatic technique for right lobe graft weight estimation using deep learning algorithms. The proposed method consists of segmentation of the full liver region from computed tomography (CT) images, classification of the entire liver region into the right and left lobes, and estimation of the right lobe graft weight from the CT-measured right lobe graft volume using a volume-to-weight conversion formula. The first two steps were performed with a transformer-based deep learning model. To train and evaluate the model, a total of 248 CT datasets (188 for training, 40 for validation, and 20 for testing and clinical evaluation) were used. The Dice similarity coefficient (DSC), mean surface distance (MSD), and the 95th percentile Hausdorff distance (HD95) were used for evaluating the segmentation accuracy of the full liver region and the right liver lobe. The correlation coefficient (CC), percentage error (PE), and percentage absolute error (PAE) were used for the clinical evaluation of the estimated right lobe graft weight. The proposed method achieved high accuracy in segmentation for DSC, MSD, and HD95 (95.9% ± 1.0%, 1.2 ± 0.4 mm, and 5.2 ± 1.9 mm for the entire liver region; 92.4% ± 2.7%, 2.0 ± 0.7 mm, and 8.8 ± 2.9 mm for the right lobe) and in clinical evaluation for CC, PE, and PAE (0.859, - 1.8% ± 9.6%, and 8.6% ± 4.7%). For the right lobe graft weight estimation, the present study underestimated the graft weight by - 1.8% on average. A mean difference of - 21.3 g (95% confidence interval: - 55.7 to 13.1, p = 0.211) between the estimated graft weight and the actual graft weight was achieved in this study. The proposed method is effective for clinical application.
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Affiliation(s)
- Xiaopeng Yang
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Seonyeong Park
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Seungyoo Lee
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Kyujin Han
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Mi Rin Lee
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea
| | - Ji Soo Song
- Department of Radiology, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
| | - Hee Chul Yu
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea
| | - Jae Do Yang
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea.
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea.
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea.
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5
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Kow AWC, Liu J, Patel MS, De Martin E, Reddy MS, Soejima Y, Syn N, Watt K, Xia Q, Saraf N, Kamel R, Nasralla D, McKenna G, Srinvasan P, Elsabbagh AM, Pamecha V, Palaniappan K, Mas V, Tokat Y, Asthana S, Cherukuru R, Egawa H, Lerut J, Broering D, Berenguer M, Cattral M, Clavien PA, Chen CL, Shah S, Zhu ZJ, Emond J, Ascher N, Rammohan A, Bhangui P, Rela M, Kim DS, Ikegami T. Post Living Donor Liver Transplantation Small-for-size Syndrome: Definitions, Timelines, Biochemical, and Clinical Factors for Diagnosis: Guidelines From the ILTS-iLDLT-LTSI Consensus Conference. Transplantation 2023; 107:2226-2237. [PMID: 37749812 DOI: 10.1097/tp.0000000000004770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
BACKGROUND When a partial liver graft is unable to meet the demands of the recipient, a clinical phenomenon, small-for-size syndrome (SFSS), may ensue. Clear definition, diagnosis, and management are needed to optimize transplant outcomes. METHODS A Consensus Scientific committee (106 members from 21 countries) performed an extensive literature review on specific aspects of SFSS, recommendations underwent blinded review by an independent panel, and discussion/voting on the recommendations occurred at the Consensus Conference. RESULTS The ideal graft-to-recipient weight ratio of ≥0.8% (or graft volume standard liver volume ratio of ≥40%) is recommended. It is also recommended to measure portal pressure or portal blood flow during living donor liver transplantation and maintain a postreperfusion portal pressure of <15 mm Hg and/or portal blood flow of <250 mL/min/100 g graft weight to optimize outcomes. The typical time point to diagnose SFSS is the postoperative day 7 to facilitate treatment and intervention. An objective 3-grade stratification of severity for protocolized management of SFSS is proposed. CONCLUSIONS The proposed grading system based on clinical and biochemical factors will help clinicians in the early identification of patients at risk of developing SFSS and institute timely therapeutic measures. The validity of this newly created grading system should be evaluated in future prospective studies.
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Affiliation(s)
- Alfred Wei Chieh Kow
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, National University of Singapore, Singapore
- Liver Transplantation, National University Center for Organ Transplantation (NUCOT), National University Health System Singapore, Singapore
| | - Jiang Liu
- Department of Surgery, Hepato-pancreato-biliary Center, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
- Department of Surgery, LKS Faculty of Medicine, HKU-Shenzhen Hospital, University of Hong Kong, Hong Kong/Special Administrative Region (SAR), China
| | - Madhukar S Patel
- Division of Surgical Transplantation, University of Texas Southwestern Medical Center, Dallas, TX
| | - Eleonora De Martin
- Department of Hepatology, APHP, Hospital Paul Brousse, Centre Hépato-Biliaire, INSERM Unit 1193, FHU Hepatinov, Villejuif, France
| | - Mettu Srinivas Reddy
- Institute of Liver Disease and Transplantation, Gleneagles Global Health City, Chennai, India
| | - Yuji Soejima
- Department of Surgery, Shinshu University, Japan
| | - Nicholas Syn
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, National University of Singapore, Singapore
- Liver Transplantation, National University Center for Organ Transplantation (NUCOT), National University Health System Singapore, Singapore
| | - Kymberly Watt
- Division of Gastroenterology/Hepatology, Mayo Clinic, Rochester, MN
| | - Qiang Xia
- Department of Surgery, Division of Liver Transplantation, Renji Hospital, Renji Hospital affiliated to Shanghai Jiao Tong University School of Medicine, China
| | - Neeraj Saraf
- Institute of Liver Transplantation and Regenerative Medicine, Medanta-the Medicity, New Delhi, India
| | - Refaat Kamel
- Department of Surgery, Ain Shams University, Cairo, Egypt
| | - David Nasralla
- Department of HPB Surgery and Liver Transplantation, Royal Free London, Royal Free London NHS Foundation Trust, London, United Kingdom
| | - Greg McKenna
- Department of Surgery, Simmons Transplant Institute, Baylor University Medical Center, Dallas, TX
| | - Parthi Srinvasan
- Institute of Liver Studies, King's College Hospital NHS Foundation Trust, London, United Kingdom
| | - Ahmed M Elsabbagh
- Gastroenterology Surgical Center, Department of Surgery, Mansoura University, Mansoura, Egypt
| | - Vinayendra Pamecha
- Department of Liver Transplant and Hepato-Pancreato-Biliary Surgery, Institute of Liver and Biliary Sciences, Vasant Kunj, New Delhi, India
| | - Kumar Palaniappan
- The Institute of Liver Disease and Transplantation, Dr Rela Institute, and Medical Centre, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Valeria Mas
- Department of Surgery, School of Medicine, University of Maryland, Baltimore, MD
| | - Yaman Tokat
- International Liver Center, Acibadem Healthcare Hospitals, Turkey
| | - Sonal Asthana
- Department of Surgery, Integrated Liver Care Aster CMI Hospital, Bangalore, India
| | - Ramkiran Cherukuru
- The Institute of Liver Disease and Transplantation, Dr Rela Institute, and Medical Centre, Chennai, Tamil Nadu, India
| | - Hiroto Egawa
- Hamamatsu Rosai Hospital, Hamamatsu, Shizuoka, Japan
| | - Jan Lerut
- Pôle de chirurgie expérimentale et transplantation, Université Catholique De Louvain, Louvain, Belgium
| | - Dieter Broering
- King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Marina Berenguer
- Hepatology and Liver Transplant Unit, Fundación Para La Investigación Del Hospital Universitario La Fe De La CCVV, IIS La Fe, Ciberehd, University of Valencia, Valencia, Spain
| | - Mark Cattral
- Department of Surgery, University Health Network, Toronto General Hospital, Toronto, ON, Canada
| | | | - Chao-Long Chen
- Department of Surgery, Chang Gung Memorial Hospital Kaoshiung, Taiwan
| | - Samir Shah
- Institute of Liver Disease, HPB Surgery and Rransplant, Global Hospitals, Mumbai, India
| | - Zhi-Jun Zhu
- Department of HPB Surgery and Liver Transplantation, Beijing Friendship Hospital, Beijing, China
| | - Jean Emond
- Department of Surgery, Columbia University Medical Center, New York, NY
| | - Nancy Ascher
- Division of Transplant Surgery, University of California San Francisco, San Francisco, CA
| | - Ashwin Rammohan
- The Institute of Liver Disease and Transplantation, Dr Rela Institute, and Medical Centre, Chennai, Tamil Nadu, India
| | - Prashant Bhangui
- Institute of Liver Transplantation and Regenerative Medicine, Medanta-the Medicity, New Delhi, India
| | - Mohamed Rela
- The Institute of Liver Disease and Transplantation, Dr Rela Institute, and Medical Centre, Chennai, Tamil Nadu, India
| | - Dong-Sik Kim
- Department of Surgery, Korea University Medical Center, Anam Hospital, Seoul, South Korea
| | - Toru Ikegami
- Department of Surgery, Centennial Hall Kyushu University School of Medicine, Kyushu, Japan
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McRae MP, Helmke SM, Burton JR, Everson GT. Compartmental model describing the physiological basis for the HepQuant SHUNT test. Transl Res 2023; 252:53-63. [PMID: 35948199 DOI: 10.1016/j.trsl.2022.08.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/22/2022] [Accepted: 08/03/2022] [Indexed: 01/14/2023]
Abstract
The HepQuant SHUNT test quantifies hepatic functional impairment from the simultaneous clearance of cholate from the systemic and portal circulations for the purpose of monitoring treatment effects or for predicting risk for clinical outcome. Compartmental models are defined by distribution volumes and transfer rates between volumes to estimate parameters not defined by noncompartmental analyses. Previously, a noncompartmental analysis method, called the minimal model (MM), demonstrated reproducible and reliable measures of liver function (Translational Research 2021). The aim of this study was to compare the reproducibility and reliability of a new physiologically based compartmental model (CM) vs the MM. Data were analyzed from 16 control, 16 nonalcoholic steatohepatitis (NASH), and 16 hepatitis C virus (HCV) subjects, each with 3 replicate tests conducted on 3 separate days. The CM describes transfer of cholates between systemic, portal, and liver compartments with assumptions from measured or literature-derived values and unknown parameters estimated by nonlinear least-squares regression. The CM was compared to the MM for 6 key indices of hepatic disease in terms of intraclass correlation coefficient (ICC) with a lower acceptable limit of 0.7. The CM correlated well with the MM for disease severity index (DSI) with R2 (95% confidence interval) of 0.96 (0.94-0.98, P < 0.001). Acceptable reproducibility (ICC > 0.7) was observed for 6/6 and 5/6 hepatic disease indices for CM and MM, respectively. SHUNT, a measure of the absolute bioavailability, had ICC of 0.73 (0.60-0.83, P = 0.3095) for MM and 0.84 (0.76-0.90, P = 0.0012) for CM. The CM, but not the MM, allowed determination of anatomic shunt and hepatic extraction and improved the within individual reproducibility.
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Affiliation(s)
| | | | - James R Burton
- Division of Gastroenterology and Hepatology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
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Ichihara N, Sato N, Marubashi S, Miyata H, Eguchi S, Ohdan H, Umeshita K, Gotoh M. Achieving clinically optimal balance between accuracy and simplicity of a formula for manual use: Development of a simple formula for estimating liver graft weight with donor anthropometrics. PLoS One 2023; 18:e0280569. [PMID: 36662814 PMCID: PMC9858735 DOI: 10.1371/journal.pone.0280569] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 01/03/2023] [Indexed: 01/21/2023] Open
Abstract
In developing a formula for manual use in clinical settings, simplicity is as important as accuracy. Whole-liver (WL) mass is often estimated using demographic and anthropometric information to calculate the standard liver volume or recommended graft volume in liver transplantation. Multiple formulas for estimating WL mass have been reported, including those with multiple independent variables. However, it is unknown whether multivariable models lead to clinically meaningful improvements in accuracy over univariable models. Our goal was to quantitatively define clinically meaningful improvements in accuracy, which justifies an additional independent variable, and to identify an estimation formula for WL graft weight that best balances accuracy and simplicity given the criterion. From the Japanese Liver Transplantation Society registry, which contains data on all liver transplant cases in Japan, 129 WL donor-graft pairs were extracted. Among the candidate models, those with the smallest cross-validation (CV) root-mean-square error (RMSE) were selected, penalizing model complexity by requiring more complex models to yield a ≥5% decrease in CV RMSE. The winning model by voting with random subsets was fitted to the entire dataset to obtain the final formula. External validity was assessed using CV. A simple univariable linear regression formula using body weight (BW) was obtained as follows: WL graft weight [g] = 14.8 × BW [kg] + 439.2. The CV RMSE (g) and coefficient of determination (R2) were 195.2 and 0.548, respectively. In summary, in the development of a simple formula for manually estimating WL weight using demographic and anthropometric variables, a clinically acceptable trade-off between accuracy and simplicity was quantitatively defined, and the best model was selected using this criterion. A univariable linear model using BW achieved a clinically optimal balance between simplicity and accuracy, while one using body surface area performed similarly.
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Affiliation(s)
- Nao Ichihara
- Department of Healthcare Quality Assessment, University of Tokyo, Bunkyo, Tokyo, Japan
| | - Naoya Sato
- Department of Hepato-Biliary-Pancreatic and Transplant Surgery, Fukushima Medical University, Fukushima, Fukushima, Japan
| | - Shigeru Marubashi
- Department of Hepato-Biliary-Pancreatic and Transplant Surgery, Fukushima Medical University, Fukushima, Fukushima, Japan
| | - Hiroaki Miyata
- Department of Healthcare Quality Assessment, University of Tokyo, Bunkyo, Tokyo, Japan
| | - Susumu Eguchi
- Department of Surgery, Nagasaki University Graduate School of Biomedical Science, Sakamoto, Nagasaki, Japan
- Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hideki Ohdan
- Japanese Liver Transplant Society, Suita, Osaka, Japan
- Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Koji Umeshita
- Department of Gastroenterological and Transplant Surgery, Applied Life Sciences, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Hiroshima, Japan
- Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
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8
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Shulan Estimation Model: A New Formula for Estimation of Standard Liver Volume In Chinese Adults. Transplant Proc 2022; 54:2236-2242. [PMID: 36114045 DOI: 10.1016/j.transproceed.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 07/07/2022] [Accepted: 08/02/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND To establish a new and accurate model for standard liver volume (SLV) estimation and graft size prediction in liver transplantation for Chinese adults. METHODS In this study, the data of morphologic indices and liver volume (LV) were retrospectively obtained on 507 cadaveric liver transplantation donors between June 2017 and September 2020 in Shulan (Hangzhou) Hospital. Linear regression analysis was performed to evaluate the impact of each parameter and develop a new SLV formula. The new formula was then validated prospectively on 97 donors between October 2020 and June 2021, and the prediction accuracy was compared with previous formulas. RESULTS The average LV in all subjects was 1445.68 ± 309.94 mL. Body weight (BW) showing the strongest correlation (r = 0.453, P < .001). By stepwise multiple linear regression analysis, BW and age were the only 2 independent correlation factors for LV. Shulan estimation model derived: SLV (mL) = 13.266 × BW (kg) - 4.693 × age + 797.16 (R2 = 0.236, P < .001). In the validation cohort, our new model achieved no significant differences between the estimated SLV and the actual LV (P > .05), and showed the lowest mean percentage error of 0.33%. The proportions of estimated SLV within the actual LV ± 20%, ± 15%, and ± 10% percentage errors were 69.1%, 55.7%, and 40.2%, respectively. DISCUSSION The Shulan SLV estimation model predicted LV more accurately than previous formulas on Chinese adults, which could serve as a simple screening tool during the initial assessment of graft volume for potential donors.
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Pettit RW, Marlatt BB, Corr SJ, Havelka J, Rana A. nnU-Net Deep Learning Method for Segmenting Parenchyma and Determining Liver Volume From Computed Tomography Images. ANNALS OF SURGERY OPEN 2022; 3:e155. [PMID: 36275876 PMCID: PMC9585534 DOI: 10.1097/as9.0000000000000155] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 03/15/2022] [Indexed: 11/26/2022] Open
Abstract
Background Recipient donor matching in liver transplantation can require precise estimations of liver volume. Currently utilized demographic-based organ volume estimates are imprecise and nonspecific. Manual image organ annotation from medical imaging is effective; however, this process is cumbersome, often taking an undesirable length of time to complete. Additionally, manual organ segmentation and volume measurement incurs additional direct costs to payers for either a clinician or trained technician to complete. Deep learning-based image automatic segmentation tools are well positioned to address this clinical need. Objectives To build a deep learning model that could accurately estimate liver volumes and create 3D organ renderings from computed tomography (CT) medical images. Methods We trained a nnU-Net deep learning model to identify liver borders in images of the abdominal cavity. We used 151 publicly available CT scans. For each CT scan, a board-certified radiologist annotated the liver margins (ground truth annotations). We split our image dataset into training, validation, and test sets. We trained our nnU-Net model on these data to identify liver borders in 3D voxels and integrated these to reconstruct a total organ volume estimate. Results The nnU-Net model accurately identified the border of the liver with a mean overlap accuracy of 97.5% compared with ground truth annotations. Our calculated volume estimates achieved a mean percent error of 1.92% + 1.54% on the test set. Conclusions Precise volume estimation of livers from CT scans is accurate using a nnU-Net deep learning architecture. Appropriately deployed, a nnU-Net algorithm is accurate and quick, making it suitable for incorporation into the pretransplant clinical decision-making workflow.
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Affiliation(s)
- Rowland W. Pettit
- From the Department of Medicine, Baylor College of Medicine, Houston, TX
| | | | - Stuart J. Corr
- Department of Innovation Systems Engineering, Houston Methodist, Houston, TX
- Department of Cardiovascular Surgery, Houston Methodist Hospital, Houston, TX
- Department of Bioengineering, Rice University, Houston, TX
- Department of Biomedical Engineering, University of Houston, Houston, TX
- Swansea University Medical School, Wales, United Kingdom
| | | | - Abbas Rana
- Department of Surgery, Division of Abdominal Transplantation, Baylor College of Medicine, Houston, TX
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10
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Yang X, Lee MR, Yang JD. A new formula for estimation of standard liver volume using liver height and thoracic width. Ann Surg Treat Res 2022; 103:47-52. [PMID: 35919114 PMCID: PMC9300442 DOI: 10.4174/astr.2022.103.1.47] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 05/12/2022] [Accepted: 06/20/2022] [Indexed: 12/04/2022] Open
Abstract
Purpose Precise estimation of the standard liver volume (SLV) is crucial in decision making regarding major hepatectomy and living donor liver transplantation. This study aimed to propose an accurate and efficient formula for estimating the SLV in the Korean population. Methods We created a regression model for SLV estimation using a data set of 230 Korean patients with healthy livers. The proposed model was cross validated using a different data set of 37 patients with healthy livers. The total liver volume (TLV), except for the volume of liver blood vessels, was measured through computed tomography volumetry as the dependent variable. Various anthropometric variables, liver height (LH), thoracic width (TW), age, and sex (0, female and 1, male) were considered as candidates for independent variables. We conducted stepwise regression analysis to identify variables to be included in the proposed model. Results A new formula was established; SLV = −1,275 + 9.85 × body weight (BW, kg) + 19.95 × TW (cm) + 7.401 × LH (mm). The proposed formula showed the best performance among existing formulas over the cross-validation data set. Conclusion The proposed formula derived using BW, TW, and LH estimated the TLV in the cross-validation data set more accurately than existing formulas.
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Affiliation(s)
- Xiaopeng Yang
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, Korea
| | - Mi Rin Lee
- Department of Surgery, Jeonbuk National University Medical School, Jeonju, Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University, Jeonju, Korea
| | - Jae Do Yang
- Department of Surgery, Jeonbuk National University Medical School, Jeonju, Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University, Jeonju, Korea
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11
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Hagen F, Mair A, Bösmüller H, Horger M. Correlation between liver volume and liver weight in a cohort with chronic liver disease: a semiautomated CT-volumetry study. Quant Imaging Med Surg 2022; 12:376-383. [PMID: 34993086 DOI: 10.21037/qims-21-299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/15/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND To estimate the optimal density coefficient for conversion of liver volume into liver weight in patients with chronic liver disease based on semiautomated CT-liver volumetry data and the histologic Ishak score of explanted liver. METHODS A total of 114 patients (39 female; age, 46±20 years) with chronic liver diseases who underwent liver transplantation between January 2010 and September 2020 were identified over a patient chart search at our institution and subsequently analyzed in retrospect. All patients had contrast-enhanced CT-examinations (mean, 24 days) to liver transplantation. Liver volume was calculated by a semiautomated software and results compared with the liver weight registered by the pathologist. Each explanted liver was histologically scored into six classes according to the Ishak classification where the categories were subgrouped based on recommendation of the pathologists into the following categories 0-3, 4-5 and 6. RESULTS Mean liver volume was 1,870±1,195, 1,162±679 and 1,278±510 mL for the categories 0-3, 4-5 and 6, respectively. Mean liver weight was 1,624±999, 1,082±669 and 1,346±559 g for the categories 0-3, 4-5 and 6, respectively. A coefficient of 0.92±0.22, 0.98±0.28 and 1.06±0.20 g/mL was found at best for conversion of liver volume into liver weight in these subgroups. Differences between Ishak-subgroups proved significant (0.002). In 4 patients with cystic liver disease, density coefficients varied significantly and were found generally lower compared to the other liver disorders. CONCLUSIONS Our results yielded significant differences between the density coefficients calculated along with the Ishak score and also for the subgroup with cystic liver disease.
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Affiliation(s)
- Florian Hagen
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
| | - Antonia Mair
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
| | - Hans Bösmüller
- Department of Pathology and Neuropathology, Eberhard-Karls-University, Tübingen, Germany
| | - Marius Horger
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
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12
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Harada K, Ishinuki T, Ohashi Y, Tanaka T, Chiba A, Numasawa K, Imai T, Hayasaka S, Tsugiki T, Miyanishi K, Nagayama M, Takemasa I, Kato J, Mizuguchi T. Nature of the liver volume depending on the gender and age assessing volumetry from a reconstruction of the computed tomography. PLoS One 2021; 16:e0261094. [PMID: 34879120 PMCID: PMC8654223 DOI: 10.1371/journal.pone.0261094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 11/23/2021] [Indexed: 11/18/2022] Open
Abstract
Although the liver is a regenerating organ, excessive loss of liver volume (LV) can cause fatal liver failure. It is unclear whether LV is correlated with age; however, it is known that liver function decreases with age. In addition, the gender-related role of LV remains unclear. This study aimed to investigate the changes in LV by age and gender. Between January and December 2018, 374 consecutive patients who underwent abdominal multidetector computed tomography (MDCT) for any abdominal examinations were enrolled. LV was evaluated using MDCT. The relationship between the LV and body mass index (BMI), body surface area (BSA), age, and gender was investigated. The modified LV (mLV) was calculated by a formula measured LV × 1.5/BSA. LV correlated to BSA more than to BMI in both the males (R: 0.559 vs. 0.416) and females (R: 0.479 vs. 0.300) in our study. Age was negatively correlated to LV and BSA, and correlated to LV more than to BSA in males (R: 0.546 vs. 0.393) and females (R: 0.506 vs. 0.385). In addition, the absolute slope between age and LV in the males was higher than that in the females (14.1 vs. 10.2, respectively). Furthermore, the absolute slope of age and mLV in the males was slightly higher than in the females (9.1 vs. 7.3, respectively). In conclusion, LV in the normal liver is correlated to age rather than the one in the diseased liver. Liver volume in the males decreased more with age than LV in the females.
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Affiliation(s)
- Kohei Harada
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Tomohiro Ishinuki
- Postgraduate School of Health Science and Medicine, Sapporo Medical University, Sapporo, Hokkaido, Japan
| | - Yoshiya Ohashi
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Takeo Tanaka
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Ayaka Chiba
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Kanako Numasawa
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Tatsuya Imai
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Shun Hayasaka
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Takahito Tsugiki
- Division of Radiology, Sapporo Medical University Hospital, Sapporo, Hokkaido, Japan
| | - Koji Miyanishi
- Department of Medical Oncology, Sapporo Medical University, Sapporo, Hokkaido, Japan
| | - Minoru Nagayama
- Departments of Surgery, Surgical Science and Oncology, Sapporo Medical University, Sapporo, Hokkaido, Japan
| | - Ichiro Takemasa
- Departments of Surgery, Surgical Science and Oncology, Sapporo Medical University, Sapporo, Hokkaido, Japan
| | - Junji Kato
- Department of Medical Oncology, Sapporo Medical University, Sapporo, Hokkaido, Japan
| | - Toru Mizuguchi
- Postgraduate School of Health Science and Medicine, Sapporo Medical University, Sapporo, Hokkaido, Japan
- Departments of Surgery, Surgical Science and Oncology, Sapporo Medical University, Sapporo, Hokkaido, Japan
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Jung EH, Cho CK, Kang P, Park HJ, Lee YJ, Bae JW, Choi CI, Jang CG, Lee SY. Physiologically based pharmacokinetic modeling of candesartan related to CYP2C9 genetic polymorphism in adult and pediatric patients. Arch Pharm Res 2021; 44:1109-1119. [PMID: 34817825 DOI: 10.1007/s12272-021-01363-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 11/06/2021] [Indexed: 12/18/2022]
Abstract
Candesartan cilexetil is an angiotensin II receptor blocker and it is widely used to treat hypertension and heart failure. This drug is a prodrug that rapidly converts to candesartan after oral administration. Candesartan is metabolized by cytochrome P450 2C9 (CYP2C9) enzyme or uridine diphosphate glucurinosyltransferase 1A3, or excreted in an unchanged form through urine, biliary tract and feces. We investigated the effect of genetic polymorphism of CYP2C9 enzyme on drug pharmacokinetics using physiologically based pharmacokinetic (PBPK) modeling. In addition, by introducing the age and ethnicity into the model, we developed a model that can propose an appropriate dosage regimen taking into account the individual characteristics of each patient. To evaluate the suitability of the model, the results of a clinical trial on twenty-two healthy Korean subjects and their CYP2C9 genetic polymorphism data was applied. In this study, PK-Sim® was used to develop the PBPK model of candesartan.
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Affiliation(s)
- Eui Hyun Jung
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Chang-Keun Cho
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Pureum Kang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Hye-Jung Park
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Yun Jeong Lee
- College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea.
| | - Jung-Woo Bae
- College of Pharmacy, Keimyung University, Daegu, 42601, Republic of Korea
| | - Chang-Ik Choi
- College of Pharmacy, Dongguk University-Seoul, Goyang, 10326, Republic of Korea
| | - Choon-Gon Jang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seok-Yong Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
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14
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Sosna J. Deep Learning for Automated Normal Liver Volume Estimation. Radiology 2021; 302:343-344. [PMID: 34698573 DOI: 10.1148/radiol.2021212010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Jacob Sosna
- From the Department of Radiology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel 91120
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15
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Li B, Chen PY, Tan YF, Huang H, Jiang M, Wu ZR, Jiang CH, Zheng DF, He D, Shi YJ, Luo Y, Yang JY. Standard liver weight model in adult deceased donors with fatty liver: A prospective cohort study. World J Gastroenterol 2021; 27:6701-6714. [PMID: 34754162 PMCID: PMC8554397 DOI: 10.3748/wjg.v27.i39.6701] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 08/22/2021] [Accepted: 09/16/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Standard liver weight (SLW) is frequently used in deceased donor liver transplantation to avoid size mismatches with the recipient. However, some deceased donors (DDs) have fatty liver (FL). A few studies have reported that FL could impact liver size. To the best of our knowledge, there are no relevant SLW models for predicting liver size. AIM To demonstrate the relationship between FL and total liver weight (TLW) in detail and present a related SLW formula. METHODS We prospectively enrolled 212 adult DDs from West China Hospital of Sichuan University from June 2019 to February 2021, recorded their basic information, such as sex, age, body height (BH) and body weight (BW), and performed abdominal ultrasound (US) and pathological biopsy (PB). The chi-square test and kappa consistency score were used to assess the consistency in terms of FL diagnosed by US relative to PB. Simple linear regression analysis was used to explore the variables related to TLW. Multiple linear regression analysis was used to formulate SLW models, and the root mean standard error and interclass correlation coefficient were used to test the fitting efficiency and accuracy of the model, respectively. Furthermore, the optimal formula was compared with previous formulas. RESULTS Approximately 28.8% of DDs had FL. US had a high diagnostic ability (sensitivity and specificity were 86.2% and 92.9%, respectively; kappa value was 0.70, P < 0.001) for livers with more than a 5% fatty change. Simple linear regression analysis showed that sex (R2, 0.226; P < 0.001), BH (R2, 0.241; P < 0.001), BW (R2, 0.441; P < 0.001), BMI (R2, 0.224; P < 0.001), BSA (R2, 0.454; P < 0.001) and FL (R2, 0.130; P < 0.001) significantly impacted TLW. In addition, multiple linear regression analysis showed that there was no significant difference in liver weight between the DDs with no steatosis and those with steatosis within 5%. Furthermore, in the context of hepatic steatosis, TLW increased positively (non-linear); compared with the TLW of the non-FL group, the TLW of the groups with hepatic steatosis within 5%, between 5% and 20% and more than 20% increased by 0 g, 90 g, and 340 g, respectively. A novel formula, namely, -348.6 + (110.7 x Sex [0 = Female, 1 = Male]) + 958.0 x BSA + (179.8 x FLUS [0 = No, 1 = Yes]), where FL was diagnosed by US, was more convenient and accurate than any other formula for predicting SLW. CONCLUSION FL is positively correlated with TLW. The novel formula deduced using sex, BSA and FLUS is the optimal formula for predicting SLW in adult DDs.
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Affiliation(s)
- Bo Li
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Pan-Yu Chen
- Operating Room, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Yi-Fei Tan
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - He Huang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Min Jiang
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Zhen-Ru Wu
- Laboratory of Pathology, Key Laboratory of Transplant Immunology and Engineering, National Health Commission, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Chen-Hao Jiang
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Dao-Feng Zheng
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Diao He
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Yu-Jun Shi
- Laboratory of Pathology, Key Laboratory of Transplant Immunology and Engineering, National Health Commission, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Yan Luo
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Jia-Yin Yang
- Department of Liver Surgery, Liver Transplantation Centre, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
- Laboratory of Liver Transplantation, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
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Kim DW, Ha J, Lee SS, Kwon JH, Kim NY, Sung YS, Yoon JS, Suk HI, Lee Y, Kang BK. Population-based and Personalized Reference Intervals for Liver and Spleen Volumes in Healthy Individuals and Those with Viral Hepatitis. Radiology 2021; 301:339-347. [PMID: 34402668 DOI: 10.1148/radiol.2021204183] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background Reference intervals guiding volumetric assessment of the liver and spleen have yet to be established. Purpose To establish population-based and personalized reference intervals for liver volume, spleen volume, and liver-to-spleen volume ratio (LSVR). Materials and Methods This retrospective study consecutively included healthy adult liver donors from 2001 to 2013 (reference group) and from 2014 to 2016 (healthy validation group) and patients with viral hepatitis from 2007 to 2017. Liver volume, spleen volume, and LSVR were measured with CT by using a deep learning algorithm. In the reference group, the reference intervals for the volume indexes were determined by using the population-based (ranges encompassing the central 95% of donors) and personalized (quantile regression modeling of the 2.5th and 97.5th percentiles as a function of age, sex, height, and weight) approaches. The validity of the reference intervals was evaluated in the healthy validation group and the viral hepatitis group. Results The reference and healthy validation groups had 2989 donors (mean age ± standard deviation, 30 years ± 9; 1828 men) and 472 donors (mean age, 30 years ± 9; 334 men), respectively. The viral hepatitis group had 158 patients (mean age, 48 years ± 12; 95 men). The population-based reference intervals were 824.5-1700.0 cm3 for liver volume, 81.1-322.0 cm3 for spleen volume, and 3.96-13.78 for LSVR. Formulae and a web calculator (https://i-pacs.com/calculators) were presented to calculate the personalized reference intervals. In the healthy validation group, both the population-based and personalized reference intervals were used to classify the volume indexes of 94%-96% of the donors as falling within the reference interval. In the viral hepatitis group, when compared with the population-based reference intervals, the personalized reference intervals helped identify more patients with volume indexes outside the reference interval (liver volume, 21.5% [34 of 158] vs 13.3% [21 of 158], P = .01; spleen volume, 29.1% [46 of 158] vs 22.2% [35 of 158], P = .01; LSVR, 35.4% [56 of 158] vs 26.6% [42 of 158], P < .001). Conclusion Reference intervals derived from a deep learning approach in healthy adults may enable evidence-based assessments of liver and spleen volume in clinical practice. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Ringl in this issue.
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Affiliation(s)
- Dong Wook Kim
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Jiyeon Ha
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Seung Soo Lee
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Ji Hye Kwon
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Na Young Kim
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Yu Sub Sung
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Jee Seok Yoon
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Heung-Il Suk
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Yedaun Lee
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
| | - Bo-Kyeong Kang
- From the Department of Radiology and Research Institute of Radiology (D.W.K., J.H., S.S.L., J.H.K., Y.S.S.) and Department of Clinical Epidemiology and Biostatistics (N.Y.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea; Department of Brain and Cognitive Engineering (J.S.Y., H.I.S.) and Department of Artificial Intelligence (H.I.S.), Korea University, Seoul, Republic of Korea; Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea (Y.L.); and Department of Radiology, Hanyang University Medical Center, Hanyang University School of Medicine, Seoul, Republic of Korea (B.K.K.)
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Addeo P, Naegel B, Terrone A, Faitot F, Schaaf C, Bachellier P, Noblet V. Analysis of factors associated with discrepancies between predicted and observed liver weight in liver transplantation. Liver Int 2021; 41:1379-1388. [PMID: 33555130 DOI: 10.1111/liv.14819] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 01/24/2021] [Accepted: 01/29/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Even using predictive formulas based on anthropometrics in about 30% of subjects, liver weight (LW) cannot be predicted with a ≤20% margin of error. We aimed to identify factors associated with discrepancies between predicted and observed LW. METHODS In 500 consecutive liver grafts, we tested LW predictive performance using 17 formulas based on anthropometric characteristics. Hashimoto's formula (961.3 × BSA_D-404.8) was associated with the lowest mean absolute error and used to predict LW for the entire cohort. Clinical factors associated with a ≥20% margin of error were identified in a multivariable analysis after propensity score matching (PSM) of donors with similar anthropometric characteristics. RESULTS The total LW was underestimated with a ≥20% margin of error in 53/500 (10.6%) donors and overestimated in 62/500 (12%) donors. After PSM analysis, ages ≥ 65, (OR = 3.21; CI95% = 1.63-6.31; P = .0007), age ≤ 30 years, (OR = 2.92; CI95% = 1.15-7.40; P = .02), and elevated gamma-glutamyltransferase (GGT) levels (OR = 0.98; CI95% = 0.97-0.99; P = .006), influenced the risk of LW overestimation. Age ≥ 65 years, (OR = 5.98; CI95% = 2.28-15.6; P = .0002), intensive care unit (ICU) stay with ventilation > 7 days, (OR = 0.32; CI95% = 0.12-0.85; P = .02) and waist circumference increase (OR = 1.02; CI95% = 1.00-1.04; P = .04) were factors associated with LW underestimation. CONCLUSIONS Increased waist circumference, age, prolonged ICU stay with ventilation, elevated GGT were associated with an increase in the margin of error in LW prediction. These factors and anthropometric characteristics could help transplant surgeons during the donor-recipient matching process.
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Affiliation(s)
- Pietro Addeo
- Hepato-Pancreato-Biliary Surgery and Liver transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France.,ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
| | | | - Alfonso Terrone
- Hepato-Pancreato-Biliary Surgery and Liver transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - François Faitot
- Hepato-Pancreato-Biliary Surgery and Liver transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France.,ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
| | - Caroline Schaaf
- Hepato-Pancreato-Biliary Surgery and Liver transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Philippe Bachellier
- Hepato-Pancreato-Biliary Surgery and Liver transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Vincent Noblet
- ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
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18
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Population Pharmacokinetics of Primaquine in the Korean Population. Pharmaceutics 2021; 13:pharmaceutics13050652. [PMID: 34063671 PMCID: PMC8147617 DOI: 10.3390/pharmaceutics13050652] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/28/2021] [Accepted: 04/30/2021] [Indexed: 11/17/2022] Open
Abstract
While primaquine has long been used for malaria treatment, treatment failure is common. This study aims to develop a population pharmacokinetic model of primaquine and its metabolite, carboxyprimaquine, and examine factors influencing pharmacokinetic variability. The data was obtained from a clinical study in 24 Korean subjects randomly assigned to normal and obese groups. The participants received primaquine 15 mg daily for 4 days and blood samples were collected at day 4. Pharmacokinetic modeling was performed with NONMEM and using simulations; the influences of doses and covariates on drug exposure were examined. A minimal physiology-based pharmacokinetic model connected with a liver compartment comprehensively described the data, with CYP450 mediated clearance being positively correlated with the body weight and CYP2D6 activity score (p < 0.05). In the simulation, while the weight-normalized area under drug concentration for primaquine in the obese group decreased by 29% at the current recommended dose of 15 mg, it became similar to the normal weight group at a weight-normalized dose of 3.5 mg/kg. This study has demonstrated that the body weight and CYP2D6 activity score significantly influence the pharmacokinetics of primaquine. The developed model is expected to be used as a basis for optimal malaria treatment in Korean patients.
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19
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Addeo P, Naegel B, De Mathelin P, Paul C, Faitot F, Schaaf C, Terrone A, Serfaty L, Bachellier P, Noblet V. Predicting the available space for liver transplantation in cirrhotic patients: a computed tomography-based volumetric study. Hepatol Int 2021; 15:780-790. [PMID: 33851323 DOI: 10.1007/s12072-021-10187-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 03/31/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Anthropometric parameters (weight, height) are usually used for quick matching between two individuals (donor and recipient) in liver transplantation (LT). This study aimed to evaluate clinical factors influencing the overall available space for implanting a liver graft in cirrhotic patients. METHODS In a cohort of 275 cirrhotic patients undergoing LT, we calculated the liver volume (LV), cavity volume (CV), which is considered the additional space between the liver and the right hypocondrium, and the overall volume (OV = LV + CV) using a computed tomography (CT)-based volumetric system. We then chose the formula based on anthropometric parameters that showed the best predictive value for LV. This formula was used to predict the OV in the same population. Factors influencing OV variations were identified by multivariable logistic analysis. RESULTS The Hashimoto formula (961.3 × BSA_D-404.8) yielded the lowest median absolute percentage error (21.7%) in predicting the LV. The median LV was 1531 ml. One-hundred eighty-five patients (67.2%) had a median CV of 1156 ml (range: 70-7006), and the median OV was 2240 ml (range: 592-8537). Forty-nine patients (17%) had an OV lower than that predicted by the Hashimoto formula. Independent factors influencing the OV included the number of portosystemic shunts, right anteroposterior abdominal diameter, model for end-stage liver disease (MELD) score > 25, high albumin value, and BMI > 30. CONCLUSIONS Additional anthropometric characteristics (right anteroposterior diameter, body mass index) clinical (number of portosystemic shunts), and biological (MELD, albumin) factors might influence the overall volume available for liver graft implantation. Knowledge of these factors might be helpful during the donor-recipient matching.
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Affiliation(s)
- Pietro Addeo
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France. .,ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France.
| | - Benoit Naegel
- ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
| | - Pierre De Mathelin
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France
| | - Chloe Paul
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France
| | - François Faitot
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France.,ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
| | - Caroline Schaaf
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France
| | - Alfonso Terrone
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France
| | - Lawrence Serfaty
- Hepatology Department, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Philippe Bachellier
- Hepato-Pancreato-Biliary Surgery and Liver Transplantation, Pôle des Pathologies Digestives, Hépatiques et de la Transplantation, Hôpital de Hautepierre-Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, 1, Avenue Moliere, 67098, Strasbourg, France
| | - Vincent Noblet
- ICube, Université de Strasbourg, CNRS UMR 7357, Illkirch, France
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21
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Kim Y, Hatley O, Rhee SJ, Yi S, Lee HA, Yoon S, Chung JY, Yu KS, Lee H. Development of a Korean-specific virtual population for physiologically based pharmacokinetic modelling and simulation. Biopharm Drug Dispos 2019; 40:135-150. [PMID: 30921829 DOI: 10.1002/bdd.2178] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 03/07/2019] [Accepted: 03/21/2019] [Indexed: 01/19/2023]
Abstract
Physiologically based pharmacokinetic (PBPK) modelling and simulation is a useful tool in predicting the PK profiles of a drug, assessing the effects of covariates such as demographics, ethnicity, genetic polymorphisms and disease status on the PK, and evaluating the potential of drug-drug interactions. We developed a Korean-specific virtual population for the SimCYP® Simulator (version 15 used) and evaluated the population's predictive performance using six substrate drugs (midazolam, S-warfarin, metoprolol, omeprazole, lorazepam and rosuvastatin) of five major drug metabolizing enzymes (DMEs) and two transporters. Forty-three parameters including the proportion of phenotypes in DMEs and transporters were incorporated into the Korean-specific virtual population. The simulated concentration-time profiles in Koreans were overlapped with most of the observed concentrations for the selected substrate drugs with a < 2-fold difference in clearance. Furthermore, we found some drug models within the SimCYP® library can be improved, e.g., the minor allele frequency of ABCG2 and the fraction metabolized by UGT2B15 should be incorporated for rosuvastatin and lorazepam, respectively. The Korean-specific population can be used to evaluate the impact of ethnicity on the PKs of a drug, particularly in various stages of drug development.
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Affiliation(s)
- Yun Kim
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea
| | | | - Su-Jin Rhee
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea
| | - Sojeong Yi
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea
| | - Hyun A Lee
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea.,Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - Sumin Yoon
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea
| | - Jae-Yong Chung
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Bundang Hospital, Seongnam, South Korea
| | - Kyung-Sang Yu
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea
| | - Howard Lee
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, South Korea.,Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
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22
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Olthof PB, van Dam R, Jovine E, Campos RR, de Santibañes E, Oldhafer K, Malago M, Abdalla EK, Schadde E. Accuracy of estimated total liver volume formulas before liver resection. Surgery 2019; 166:247-253. [PMID: 31204072 DOI: 10.1016/j.surg.2019.05.003] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 05/06/2019] [Accepted: 05/06/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Future remnant liver volume is used to predict the risk for liver failure in patients who will undergo major liver resection. Formulas to estimate total liver volume based on biometric data are widely used to calculate future remnant liver volume; however, it remains unclear which formula is most accurate. This study evaluated published estimate total liver volume formulas to determine which formula best predicts the actual future remnant liver volume based on measurements in a large number of patients who underwent associating liver partition and portal vein ligation for staged hepatectomy surgery. METHODS All patients with complete liver volume data in the associating liver partition and portal vein ligation for staged hepatectomy registry were included in this study. Estimate total liver volume and estimated future remnant liver volume were calculated for 16 published formulas. The median over- or underestimation compared with actual measured volumes were determined for estimate total liver volume and future remnant liver volume. The proportion of patients with an under- or overestimated future remnant liver volume for each formula were compared with each other using a 25% cut-off for each formula. RESULTS Among 529 studied patients, the formulas ranged from a 19% underestimation to a 63% overestimation of estimate total liver volume. Estimation of future remnant liver volume lead to a 10% underestimation to a 5% overestimation among the formulas. Of all studied formulas, the Vauthey1 formula was the most accurate, generating underestimation of future remnant liver volume in 20% and overestimation of future remnant liver volume in 6% of patients. CONCLUSION Validation of 16 published total liver volume formulas in a multicenter international cohort of 529 patients that underwent staged hepatectomy revealed that the Vauthey formula (estimate total liver volume = 18.51 × body weight + 191.8) provides the most accurate prediction of the actual future remnant liver volume.
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Affiliation(s)
- Pim B Olthof
- Department of Surgery, Reinier de Graaf Gasthuis, Delft, the Netherlands; Department of Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
| | - Ronald van Dam
- Department of Surgery, Maastricht University Medical Center, Maastricht, the Netherlands, and Universitätsklinikum Aachen, Aachen, Germany
| | - Elio Jovine
- Department of Surgery, C. A. Pizzardi Maggiore Hospital, Bologna, Italy
| | | | | | - Karl Oldhafer
- Department of General, Visceral and Oncological Surgery, Asklepios Klinik Barmbek, Hamburg, Germany
| | - Massimo Malago
- Department of HPB and Liver Transplant Surgery, Royal Free Hospital, University College London, London, UK
| | - Eddie K Abdalla
- Department of Hepato-Pancreato-Biliary Surgery, Northside Hospital Cancer Institute, Atlanta, GA
| | - Erik Schadde
- Institute of Physiology, Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland; Department of Surgery, Cantonal Hospital Winterthur, Winterthur, Switzerland; Department of Surgery, Rush University Medical Center, Chicago, IL
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23
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Harada K, Nagayama M, Ohashi Y, Chiba A, Numasawa K, Meguro M, Kimura Y, Yamaguchi H, Kobayashi M, Miyanishi K, Kato J, Mizuguchi T. Scoring criteria for determining the safety of liver resection for malignant liver tumors. World J Meta-Anal 2019; 7:234-248. [DOI: 10.13105/wjma.v7.i5.234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 05/20/2019] [Accepted: 05/22/2019] [Indexed: 02/06/2023] Open
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Abstract
Introduction: Liver volumetry is a routine procedure performed before major hepatectomy or living donor liver transplantation (LDLT) to anticipate the remnant liver volume and prevent liver failure. However, many parameters may impact its accuracy and no large-scale studies have evaluated inter-rater variabilities. We aimed to determine the reliability of volumetric assessments for whole organs in deceased-donor liver transplantations (DDLT) and partial organs in LDLT settings. Patients & Methods: Eight operators (four surgeons + four radiologists) analysed 30 preoperative CT scans (15 whole cirrhotic livers in the DDLT group + 15 partial healthy grafts in the LDLT group), using five software systems. The computed volumes were compared with liver weight; liver density being considered as1. Results: Inter-rater and inter-software concordances were excellent with coefficients of correlation >0.9. However, calculations overestimated the real volumes in 25 cases by a mean of 249 ± 206 [14-771] cc in the DDLT group and 138 ± 92cc [39-375] in the LDLT group. The mean calculations were significantly higher than liver weights in the LDLT group only (p=0.04). The radiologists overestimated the surgeons’ assessment in 24 cases, the differences exceeding 6% in some cases. The type of software used significantly impacted results in the DDLTgroup. Conclusions: Despite its unanimously recognised utility, we highlight significant discrepancies between estimated and real liver volumes. The global overestimation may lead to leave of too small remnant liver, with potentially dramatic consequences. In case of border-line estimations, we recommend a repetition of the evaluation by another operator (surgeon + radiologist working in concert).
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25
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Haberal KM, Kural Rahatlı F, Turnaoğlu H, Özgün G, Coşkun M. Use of Computed Tomography Volumetry to Assess Liver Weight in Patients With Cirrhosis During Evaluation Before Living-Donor Liver Transplant. EXP CLIN TRANSPLANT 2018; 19:149-153. [PMID: 30398100 DOI: 10.6002/ect.2018.0008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVES Computed tomography liver volumetry has been widely used to detect total and segmental liver volume in living-donor liver transplantation. However, use of this technique to evaluate the cirrhotic liver remains unclear. In this study, we evaluated the accuracy of freehand computed tomography volumetry to assess total liver volume by comparing weights of total hepatectomy specimens in patients with cirrhosis. For our analyses, we considered the density of a cirrhotic liver to be 1.1 kg/L. MATERIALS AND METHODS Liver volume was measured using a freehand computed tomography technique in 52 patients with cirrhosis from different causes and who had no solid lesions before transplant. Measurements were made with a 16-slice multidetector computed tomography scanner (Siemens Somatom Sensation 16, Erlangen, Germany). For volumetric measurements, 10-mm-thick slices with 10-mm reconstruction intervals were preferred. Total hepatectomy weights of explant livers and computed tomography volumetry data were compared. RESULTS We excluded 3 cirrhotic patients with Budd-Chiari syndrome due to wide variations in scatterplot results. In the 49 patients included in the final analyses, average estimated liver volume by computed tomography was 721 ± 398 mL and actual cirrhotic liver weight was 727.8 ± 415 g. No significant differences were shown between these measurements. A simple regression analysis used to analyze correlations between estimated liver volume by computed tomography and real cirrhotic liver weight showed correlation of 0.957 (P < .001). When computed tomography liver volumetry as the independent variable and cirrhotic liver weight as dependent variable were considered, regression analyses showed R2 = 0.915. CONCLUSIONS Freehand computed tomography liver volumetry can be confidently used to evaluate liver volume in cirrhotic liver patients similar to use of this technique to estimate actual weights in normal livers. This technique can also be valuable during pretransplant and liver resection evaluations to ensure a more successful outcome.
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Affiliation(s)
- Kemal Murat Haberal
- From the Department of Radiology, Baskent University Faculty of Medicine, Ankara, Turkey
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26
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Imbault M, Dioguardi Burgio M, Faccinetto A, Ronot M, Bendjador H, Deffieux T, Triquet EO, Rautou PE, Castera L, Gennisson JL, Vilgrain V, Tanter M. Ultrasonic fat fraction quantification using in vivo adaptive sound speed estimation. ACTA ACUST UNITED AC 2018; 63:215013. [DOI: 10.1088/1361-6560/aae661] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Marion Imbault
- Institut Langevin, ESPCI Paris, PSL Research University, CNRS UMR 7587, INSERM U979, Paris, France. Author to whom any correspondence should be addressed
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27
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Donadon M, Mimmo A, Costa G, Cimino M, Viganò L, Palmisano A, Torzilli G. Measurement of Total Liver Volume Using the Energy Expenditure: A New Formula. World J Surg 2018; 42:3350-3356. [PMID: 29691622 DOI: 10.1007/s00268-018-4632-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND The assessment of liver volume (LV) is important before surgical resection or transplantation to reduce the risk of hepatic insufficiency. LV is usually measured using computed tomography or with some formulas. The aim of this study was to develop a new dynamic formula to predict LV. METHODS Using computed tomography, LV was calculated in 101 patients without liver disease. LV was correlated with patient metabolic status, calculated with the Harris-Benedict equation for basal energy expenditure (BEE). Activity energy expenditure (AEE) was also calculated. Using linear regression analysis, a new formula was derived and was compared with Heinmann's, Urata's, Emre's, Vauthey's, Yoshizumi's, Yu's, and Hashimoto's formulas. RESULTS A new basal formula was established: LV = (0.789 × BEE) + 272. It was found to be the most accurate (R2 = 0.39, p < 0.001). Heinmann's, Emre's, and Vauthey's formulas tend to overestimate LV, while Urata's, Yoshizumi's, Yu's, and Hashimoto's formulas tend to underestimate LV. A new AEE formula was also established: LV = (0.789 × AEE) + 272. CONCLUSIONS These formulas give a dynamic perspective of LV, which may be influenced by the patient's actual clinical status. Using these formulas, it is possible to estimate an increased value of LV, which may contribute to a reduction in the risk of postoperative hepatic insufficiency.
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Affiliation(s)
- Matteo Donadon
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy.
| | - Antonio Mimmo
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
| | - Guido Costa
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
| | - Matteo Cimino
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
| | - Luca Viganò
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
| | - Angela Palmisano
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
| | - Guido Torzilli
- Department of Hepatobiliary and General Surgery, Humanitas Clinical and Research Center, Humanitas University, Via Manzoni, 56, 20089, Rozzano, Milan, Italy
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Shen YN, Zheng ML, Guo CX, Bai XL, Pan Y, Yao WY, Liang TB. The role of imaging in prediction of post-hepatectomy liver failure. Clin Imaging 2018; 52:137-145. [PMID: 30059953 DOI: 10.1016/j.clinimag.2018.07.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 07/11/2018] [Accepted: 07/23/2018] [Indexed: 02/08/2023]
Abstract
Post-hepatectomy liver failure (PHLF) is not only a leading cause of mortality but also a leading cause of life-threatening complications in patients undergoing liver resection. The ability to accurately detect the emergence of PHLF represents a crucially important step. Currently, PHLF can be predicted by a comprehensive evaluation of biological, clinical, and anatomical parameters. With the development of new technologies, imaging methods including elastography, diffusion-weighted magnetic resonance imaging, and gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid-enhanced MRI play a more significant role in the pre-operative prediction and assessment of PHLF. In this review, we summarize the mainstream studies, with the aim of evaluating the role of imaging and improving the clinical value of existing scoring systems for predicting PHLF.
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Affiliation(s)
- Yi-Nan Shen
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China
| | - Meng-Lin Zheng
- Department of Ultrasound, Huashan Hospital of Fudan University, Shanghai, China
| | - Cheng-Xiang Guo
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China
| | - Xue-Li Bai
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China
| | - Yao Pan
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wei-Yun Yao
- Department of General Surgery, The People's Hospital of Changxing County, Huzhou, China
| | - Ting-Bo Liang
- Department of Hepatobiliary and Pancreatic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Zhejiang Provincial Key Laboratory of Pancreatic Disease, Hangzhou, China.
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Yang X, Yang JD, Lee S, Hwang HP, Ahn S, Yu HC, You H. Estimation of Standard Liver Volume Using CT Volume, Body Composition, and Abdominal Geometry Measurements. Yonsei Med J 2018; 59:546-553. [PMID: 29749138 PMCID: PMC5949297 DOI: 10.3349/ymj.2018.59.4.546] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 03/27/2018] [Indexed: 02/07/2023] Open
Abstract
PURPOSE The present study developed formulas for estimation of standard liver volume (SLV) with high accuracy for the Korean population. MATERIALS AND METHODS SLV estimation formulas were established using gender-balanced and gender-unbalanced measurements of anthropometric variables, body composition variables, and abdominal geometry of healthy Koreans (n=790). Total liver volume excluding blood volume, was measured based on CT volumetry. RESULTS SLV estimation formulas as preferred in various conditions of data availability were suggested in the present study. The suggested SLV estimation formulas in the present study were found superior to existing formulas, with an increased accuracy of 4.0-217.5 mL for absolute error and 0.2-18.7% for percentage of absolute error. CONCLUSION SLV estimation formulas using gender-balanced measurements showed better performance than those using gender-unbalanced measurements. Inclusion of body composition and abdominal geometry variables contributed to improved performance of SLV estimation.
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Affiliation(s)
- Xiaopeng Yang
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea
| | - Jae Do Yang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Seunghoon Lee
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea
| | - Hong Pil Hwang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Sungwoo Ahn
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Hee Chul Yu
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea.
| | - Heecheon You
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea.
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Yang X, Yang JD, Hwang HP, Yu HC, Ahn S, Kim BW, You H. Segmentation of liver and vessels from CT images and classification of liver segments for preoperative liver surgical planning in living donor liver transplantation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 158:41-52. [PMID: 29544789 DOI: 10.1016/j.cmpb.2017.12.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 11/13/2017] [Accepted: 12/11/2017] [Indexed: 06/08/2023]
Abstract
BACKGROUND AND OBJECTIVE The present study developed an effective surgical planning method consisting of a liver extraction stage, a vessel extraction stage, and a liver segment classification stage based on abdominal computerized tomography (CT) images. METHODS An automatic seed point identification method, customized level set methods, and an automated thresholding method were applied in this study to extraction of the liver, portal vein (PV), and hepatic vein (HV) from CT images. Then, a semi-automatic method was developed to separate PV and HV. Lastly, a local searching method was proposed for identification of PV branches and the nearest neighbor approximation method was applied to classifying liver segments. RESULTS Onsite evaluation of liver segmentation provided by the SLIVER07 website showed that the liver segmentation method achieved an average volumetric overlap accuracy of 95.2%. An expert radiologist evaluation of vessel segmentation showed no false positive errors or misconnections between PV and HV in the extracted vessel trees. Clinical evaluation of liver segment classification using 43 CT datasets from two medical centers showed that the proposed method achieved high accuracy in liver graft volumetry (absolute error, AE = 45.2 ± 20.9 ml; percentage of AE, %AE = 6.8% ± 3.2%; percentage of %AE > 10% = 16.3%; percentage of %AE > 20% = none) and the classified segment boundaries agreed with the intraoperative surgical cutting boundaries by visual inspection. CONCLUSIONS The method in this study is effective in segmentation of liver and vessels and classification of liver segments and can be applied to preoperative liver surgical planning in living donor liver transplantation.
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Affiliation(s)
- Xiaopeng Yang
- Department of Industrial Management and Engineering, Pohang University of Science and Technology, Pohang, 37673, South Korea
| | - Jae Do Yang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, 54907, South Korea; Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, 54907, South Korea; Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, 54907, South Korea
| | - Hong Pil Hwang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, 54907, South Korea; Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, 54907, South Korea; Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, 54907, South Korea
| | - Hee Chul Yu
- Department of Surgery, Chonbuk National University Medical School, Jeonju, 54907, South Korea; Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, 54907, South Korea; Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, 54907, South Korea.
| | - Sungwoo Ahn
- Department of Surgery, Chonbuk National University Medical School, Jeonju, 54907, South Korea; Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, 54907, South Korea; Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, 54907, South Korea
| | - Bong-Wan Kim
- Department of Liver Transplantation and Hepatobiliary Surgery, Ajou University School of Medicine, Suwon, 16499, South Korea
| | - Heecheon You
- Department of Industrial Management and Engineering, Pohang University of Science and Technology, Pohang, 37673, South Korea
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Yang X, Yang JD, Yu HC, Choi Y, Yang K, Lee TB, Hwang HP, Ahn S, You H. Dr. Liver: A preoperative planning system of liver graft volumetry for living donor liver transplantation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 158:11-19. [PMID: 29544776 DOI: 10.1016/j.cmpb.2018.01.024] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 01/11/2018] [Accepted: 01/24/2018] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND OBJECTIVE Manual tracing of the right and left liver lobes from computed tomography (CT) images for graft volumetry in preoperative surgery planning of living donor liver transplantation (LDLT) is common at most medical centers. This study aims to develop an automatic system with advanced image processing algorithms and user-friendly interfaces for liver graft volumetry and evaluate its accuracy and efficiency in comparison with a manual tracing method. METHODS The proposed system provides a sequential procedure consisting of (1) liver segmentation, (2) blood vessel segmentation, and (3) virtual liver resection for liver graft volumetry. Automatic segmentation algorithms using histogram analysis, hybrid level-set methods, and a customized region growing method were developed. User-friendly interfaces such as sequential and hierarchical user menus, context-sensitive on-screen hotkey menus, and real-time sound and visual feedback were implemented. Blood vessels were excluded from the liver for accurate liver graft volumetry. A large sphere-based interactive method was developed for dividing the liver into left and right lobes with a customized cutting plane. The proposed system was evaluated using 50 CT datasets in terms of graft weight estimation accuracy and task completion time through comparison to the manual tracing method. The accuracy of liver graft weight estimation was assessed by absolute difference (AD) and percentage of AD (%AD) between preoperatively estimated graft weight and intraoperatively measured graft weight. Intra- and inter-observer agreements of liver graft weight estimation were assessed by intraclass correlation coefficients (ICCs) using ten cases randomly selected. RESULTS The proposed system showed significantly higher accuracy and efficiency in liver graft weight estimation (AD = 21.0 ± 18.4 g; %AD = 3.1% ± 2.8%; percentage of %AD > 10% = none; task completion time = 7.3 ± 1.4 min) than the manual tracing method (AD = 70.5 ± 52.1 g; %AD = 10.2% ± 7.5%; percentage of %AD > 10% = 46%; task completion time = 37.9 ± 7.0 min). The proposed system showed slightly higher intra- and inter-observer agreements (ICC = 0.996 to 0.998) than the manual tracing method (ICC = 0.979 to 0.999). CONCLUSIONS The proposed system was proved accurate and efficient in liver graft volumetry for preoperative planning of LDLT.
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Affiliation(s)
- Xiaopeng Yang
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Jae Do Yang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Hee Chul Yu
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea.
| | - Younggeun Choi
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Kwangho Yang
- Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Tae Beom Lee
- Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Hong Pil Hwang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Sungwoo Ahn
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Heecheon You
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
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Abstract
Background With the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates. Methods LDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression. Results The optimal formula using TAC was determined to be SLV = (TAC × 3.5816) − (Age × 3.9844) − (Sex × 109.7386) − 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025). Conclusion We report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts.
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Ma KW, Chok KSH, Chan ACY, Tam HSC, Dai WC, Cheung TT, Fung JYY, Lo CM. A new formula for estimation of standard liver volume using computed tomography-measured body thickness. Liver Transpl 2017; 23:1113-1122. [PMID: 28650089 DOI: 10.1002/lt.24807] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2017] [Revised: 05/06/2017] [Accepted: 06/13/2017] [Indexed: 12/24/2022]
Abstract
The objective of this article is to derive a more accurate and easy-to-use formula for finding estimated standard liver volume (ESLV) using novel computed tomography (CT) measurement parameters. New formulas for ESLV have been emerging that aim to improve the accuracy of estimation. However, many of these formulas contain body surface area measurements and logarithms in the equations that lead to a more complicated calculation. In addition, substantial errors in ESLV using these old formulas have been shown. An improved version of the formula for ESLV is needed. This is a retrospective cohort of consecutive living donor liver transplantations from 2005 to 2016. Donors were randomly assigned to either the formula derivation or validation groups. Total liver volume (TLV) measured by CT was used as the reference for a linear regression analysis against various patient factors. The derived formula was compared with the existing formulas. There were 722 patients (197 from the derivation group, 164 from the validation group, and 361 from the recipient group) involved in the study. The donor's body weight (odds ratio [OR], 10.42; 95% confidence interval [CI], 7.25-13.60; P < 0.01) and body thickness (OR, 2.00; 95% CI, 0.36-3.65; P = 0.02) were found to be independent factors for the TLV calculation. A formula for TLV (cm3 ) was derived: 2 × thickness (mm) + 10 × weight (kg) + 190 with R2 0.48, which was the highest when compared with the 4 other most often cited formulas. This formula remained superior to other published formulas in the validation set analysis (R2 , 5.37; interclass correlation coefficient, 0.74). Graft weight/ESLV values calculated by the new formula were shown to have the highest correlation with delayed graft function (C-statistic, 0.79; 95% CI, 0.69-0.90; P < 0.01). The new formula (2 × thickness + 10 × weight + 190) represents the first study proposing the use of CT-measured body thickness which is novel, easy to use, and the most accurate for ESLV. Liver Transplantation 23 1113-1122 2017 AASLD.
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Affiliation(s)
- Ka Wing Ma
- Department of Surgery, The University of Hong Kong, Hong Kong, China
| | - Kenneth S H Chok
- Department of Surgery, The University of Hong Kong, Hong Kong, China
- State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
| | - Albert C Y Chan
- Department of Surgery, The University of Hong Kong, Hong Kong, China
- State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
| | - Henry S C Tam
- Department of Surgery, The University of Hong Kong, Hong Kong, China
| | - Wing Chiu Dai
- Department of Surgery, The University of Hong Kong, Hong Kong, China
| | - Tan To Cheung
- Department of Surgery, The University of Hong Kong, Hong Kong, China
- State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
| | - James Y Y Fung
- State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
- Department of Medicine, The University of Hong Kong, Hong Kong, China
| | - Chung Mau Lo
- Department of Surgery, The University of Hong Kong, Hong Kong, China
- State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
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Feng LM, Wang PQ, Yu H, Chen RT, Wang J, Sheng X, Yuan ZL, Shi PM, Xie WF, Zeng X. New formula for predicting standard liver volume in Chinese adults. World J Gastroenterol 2017; 23:4968-4977. [PMID: 28785151 PMCID: PMC5526767 DOI: 10.3748/wjg.v23.i27.4968] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 04/17/2017] [Accepted: 06/12/2017] [Indexed: 02/06/2023] Open
Abstract
AIM To obtain a reference range of morphological indices and establish a formula to accurately predict standard liver volume (SLV) in Chinese adults.
METHODS Computed tomography (CT)-estimated total liver volume (CTLV) was determined in 369 Chinese adults. Age, sex, body weight, body height, body mass index, and body surface area (BSA) were recorded using CT. Total splenic volume, portal venous diameter (PVD), splenic venous diameter (SVD), and portal venous cross-sectional area (PVCSA) were also measured by CT. Stepwise multiple linear regression analysis was performed to evaluate the impact of each parameter on CTLV and to develop a new SLV formula. The accuracy of the new formula was compared with the existing formulas in a validation group.
RESULTS The average CTLV was 1205.41 ± 257.53 cm3 (range, 593.80-2250.10 cm3). The average of PVD, SVD and PVCSA was 9.34 ± 1.51 mm, 7.40 ± 1.31 mm and 173.22 ± 48.11 mm2, respectively. The CT-estimated splenic volume of healthy adults varied markedly (range, 46.60-2892.30 cm3). Sex, age, body height, body weight, body mass index, and BSA were significantly correlated with CTLV. BSA showed the strongest correlation (r = 0.546, P < 0.001), and was used to establish a new model for calculating SLV: SLV (cm3) = 758.259 × BSA (m2)-124.272 (R2 = 0.299, P < 0.001). This formula also predicted CTLV more accurately than the existing formulas, but overestimated CTLV in elderly subjects > 70 years of age, and underestimated liver volume when CTLV was > 1800 cm3.
CONCLUSION Our new BSA-based formula is more accurate than other formulas in estimating SLV in Chinese adults.
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Allard MA, Baillié G, Castro-Benitez C, Faron M, Blandin F, Cherqui D, Castaing D, Cunha AS, Adam R, Vibert É. Prediction of the Total Liver Weight using anthropological clinical parameters: does complexity result in better accuracy? HPB (Oxford) 2017; 19:338-344. [PMID: 28043763 DOI: 10.1016/j.hpb.2016.11.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 10/07/2016] [Accepted: 11/30/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND The performance of linear models predicting Total Liver Weight (TLW) remains moderate. The use of more complex models such as Artificial Neural Network (ANN) and Generalized Additive Model (GAM) or including the variable "steatosis" may improve TLW prediction. This study aimed to assess the value of ANN and GAM and the influence of steatosis for predicting TLW. METHODS Basic clinical and morphological variables of 1560 cadaveric donors for liver transplantation were randomly split into a training (2/3) and validation set (1/3). Linear models, ANN and GAM were built by using the training cohort and evaluated with the validation cohort. RESULTS The TLW is subject to major variations among donors with similar morphological parameters. The performance of ANN and GAM were moderate and similar to that of linear models (concordance coefficient from 0.36 to 0.44). In 28-30% of cases, TLW cannot be predicted with a margin of error ≤20%. The addition of the variable "steatosis" to each model did not improve their performance. CONCLUSION TLW prediction based on anthropological parameters carry a significant risk of error despite the use of more complex models. Others determinants of TLW need to be identified and imaging-based volumetric measurements should be preferred when feasible.
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Affiliation(s)
- Marc-Antoine Allard
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France; INSERM, Unit UMRS776, Villejuif, F-94800, France.
| | - Gaëlle Baillié
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Carlos Castro-Benitez
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France
| | - Matthieu Faron
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Frédérique Blandin
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Daniel Cherqui
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - Denis Castaing
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - Antonio Sa Cunha
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - René Adam
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France; INSERM, Unit UMRS776, Villejuif, F-94800, France
| | - Éric Vibert
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
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Small BG, Wendt B, Jamei M, Johnson TN. Prediction of liver volume - a population-based approach to meta-analysis of paediatric, adult and geriatric populations - an update. Biopharm Drug Dispos 2017; 38:290-300. [PMID: 28084034 DOI: 10.1002/bdd.2063] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 12/12/2016] [Accepted: 12/27/2016] [Indexed: 12/12/2022]
Abstract
Liver volume is a critical scaling factor for predicting drug clearance in physiologically based pharmacokinetic modelling and for both donor/recipient graft size estimation in liver transplantation. The accurate and precise estimation of liver volume is therefore essential. The objective here was to extend an existing meta-analysis using a non-linear mixed effects modelling approach for the estimation of liver volume to other race groups and paediatric and geriatric populations. Interrogation of the PubMed® database was undertaken using a text string query to ensure as objective a retrieval of liver volume data for the modelling exercise as possible. Missing body size parameters were estimated using simulations from the Simcyp Simulator V13R1 for an age and ethnically appropriate population. Non-linear mixed effect modelling was undertaken in Phoenix 1.3 (Certara) utilizing backward deletion and forward inclusion of covariates from fully parameterized models. Existing liver volume models based on body surface area (BSA) and body weight and height were implemented for comparison. The extension of a structural model using a BSA equation and incorporating the Japanese race and age as covariates and exponents on LV0 (θBaseline ) and body surface area (θBSA ), respectively, delivered a comparatively low objective function value. Bootstrapping of the original dataset revealed that the confidence intervals (2.5-97.5%) for the fitted (theta) parameter estimates were bounded by the bootstrapped estimates of the same. In conclusion, extension and re-parameterization of the existing Johnson model adequately describes changes in liver volume using the body surface area in all investigated populations. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- Ben G Small
- Simcyp (a Certara company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK
| | - Bernd Wendt
- Certara Munich, Martin-Kollar-Strasse 17, Munich, D-81829, Germany
| | - Masoud Jamei
- Simcyp (a Certara company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK
| | - Trevor N Johnson
- Simcyp (a Certara company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK
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Yang X, Chu C, Yang J, Yang K, Yu H, Cho B, You H. Estimation of Right-Lobe Graft Weight From Computed Tomographic Volumetry for Living Donor Liver Transplantation. Transplant Proc 2017; 49:303-308. [DOI: 10.1016/j.transproceed.2016.12.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 12/13/2016] [Indexed: 02/07/2023]
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Lee CH, Kim IH, Moon JC, Seo SY, Kim SH, Kim SW, Lee SO, Lee ST, Kim DG, Yang JD, Yu HC. 3-Dimensional liver volume assessment in patients with hepatitis B virus-related liver cirrhosis during long-term oral nucleos(t)ide analogues therapy. World J Gastroenterol 2017; 23:297-305. [PMID: 28127203 PMCID: PMC5236509 DOI: 10.3748/wjg.v23.i2.297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 11/22/2016] [Accepted: 12/08/2016] [Indexed: 02/06/2023] Open
Abstract
AIM To assess the effect of long-term oral nucleos(t)ide analogues (NUCs) therapy on liver volume change in patients with suppress hepatitis B virus (HBV)-related liver cirrhosis. METHODS We reviewed the data of naïve patients with HBV-related liver cirrhosis, who had taken oral NUCs therapy, between 2003 and 2007 at Chonbuk University Hospital. We analyzed two consecutive sets of abdominal computerized tomography scans-one at the time of treatment initiation and another at the second-year follow-up. Liver volume was calculated by 3-dimensional liver extraction volumetry program. RESULTS A total of 55 patients (34 males) were included. There was 114.3 mL ± 167.8 mL (12.9% ± 17.9%) of increase in liver volume during the two years of NUCs therapy (993.8 mL ± 242.8 mL at baseline vs 1108.1 mL ± 263.3 mL at two-year follow-up, P < 0.001). The ratio of the measured baseline liver volume to the estimated standard liver volume was improved from 70.8% to 78.0%. An increase in liver volume was shown not only in patients with compensated cirrhosis (P = 0.046) but also in those with decompensated cirrhosis (P < 0.001). Significant factors for volume increases were Child-Turcotte-Pugh grade and model for end-stage liver disease score improvement without virological breakthrough. In multiple linear regression analysis, delta albumin and delta alanine aminotransferase levels showed a significant association with the increase in liver volume (P = 0.002 and 0.005, respectively). CONCLUSION Long-term oral NUCs therapy in patients with HBV-related liver cirrhosis lead to significant increase in liver volume assessed with 3-dimensional liver extraction volumetry program.
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Estimation of liver volume in the western Indian population. Indian J Gastroenterol 2016; 35:274-9. [PMID: 27316699 DOI: 10.1007/s12664-016-0662-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Accepted: 04/28/2016] [Indexed: 02/04/2023]
Abstract
BACKGROUND A number of formulae to estimate standard liver volume (SLV) exist. However, studies have shown that only certain formulae are applicable to a particular patient population, whereas the other formulae have not been accurate in estimating the SLV. Aim of this study was to assess which formula is most accurate in estimating SLV in the western Indian population. METHODS Data for donors of living donor liver transplantation from September 2014 to July 2015 was analyzed. Liver volumes were measured using computed tomography volumetry (CTV). SLV was calculated using formulae by the currently existing formulae. The mean SLV and CTV, percentage error in the SLV, and the correlation between SLV and CTV were calculated. RESULTS Fifty-nine healthy subjects underwent donor hepatectomy [28 (47.5 %) males]. The mean age, mean body mass index (BMI), and mean body surface area (BSA) were 31.8 ± 8.8 years, 23.8 ± 3.7 kg/m(2), and 1.6 ± 0.4, respectively. Mean CTV was 1178 ± 246.8 mL. Difference between mean SLV and mean CTV ranged from -133.5 (±189) mL to 632.2 (±190.2) mL. Mean SLV was significantly different from CTV by all the formulae except Urata. Percentage of population whose SLV was within 15 % of the mean CTV ranged from 1.7 % to 67.8 %, with the highest percentage obtained by using Fu-Gui's formula. However, there was wide inter-individual variation on scatter plots between SLV and CTV by both these formulae. CONCLUSION Currently existing formulae were not accurate in estimating SLV in our population.
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Kim H, Park HC, Ryu H, Kim K, Kim HS, Oh KH, Yu SJ, Chung JW, Cho JY, Kim SH, Cheong HI, Lee K, Park JH, Pei Y, Hwang YH, Ahn C. Clinical Correlates of Mass Effect in Autosomal Dominant Polycystic Kidney Disease. PLoS One 2015; 10:e0144526. [PMID: 26641645 PMCID: PMC4671651 DOI: 10.1371/journal.pone.0144526] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Accepted: 11/19/2015] [Indexed: 11/18/2022] Open
Abstract
Mass effect from polycystic kidney and liver enlargement can result in significant clinical complications and symptoms in autosomal dominant polycystic kidney disease (ADPKD). In this single-center study, we examined the correlation of height-adjusted total liver volume (htTLV) and total kidney volume (htTKV) by CT imaging with hepatic complications (n = 461) and abdominal symptoms (n = 253) in patients with ADPKD. “Mass-effect” complications were assessed by review of medical records and abdominal symptoms, by a standardized research questionnaire. Overall, 91.8% of patients had 4 or more liver cysts on CT scans. Polycystic liver disease (PLD) was classified as none or mild (htTLV < 1,600 mL/m); moderate (1,600 ≤ htTLV <3,200 mL/m); and severe (htTLV ≥ 3,200 mL/m). The prevalence of moderate and severe PLD in our patient cohort was 11.7% (n = 54/461) and 4.8% (n = 22/461), respectively, with a female predominance in both the moderate (61.1%) and severe (95.5%) PLD groups. Pressure-related complications such as leg edema (20.4%), ascites (16.6%), and hernia (3.6%) were common, and patients with moderate to severe PLD exhibited a 6-fold increased risk (compared to no or mild PLD) for these complications in multivariate analysis. Similarly, abdominal symptoms including back pain (58.8%), flank pain (53.1%), abdominal fullness (46.5%), and dyspnea/chest-discomfort (44.3%) were very common, and patients with moderate to severe PLD exhibited a 5-fold increased risk for these symptoms. Moderate to severe PLD is a common and clinically important problem in ~16% of patients with ADPKD who may benefit from referral to specialized centers for further management.
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Affiliation(s)
- Hyunsuk Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Hayne Cho Park
- Department of Internal Medicine, Armed Forces Capital Hospital, Seongnam-si, Gyeonggi-do, Korea
| | - Hyunjin Ryu
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Kiwon Kim
- Nephrology Clinic, National Cancer Center, Goyang-si, Gyeonggi-do, Korea
| | - Hyo Sang Kim
- Department of Internal Medicine, Asan Medical Center, University of Ulsan, Seoul, Korea
| | - Kook-Hwan Oh
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Su Jong Yu
- Division of Hepatology, Seoul National University Hospital, Seoul, Korea
| | - Jin Wook Chung
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jeong Yeon Cho
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Seung Hyup Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Hae Il Cheong
- Department of Pediatrics, Seoul National University Children's Hospital, Seoul, Korea.,Research Coordination Center for Rare Diseases, Seoul National University Hospital, Seoul, Korea
| | - Kyubeck Lee
- Department of Internal Medicine, Kangbuk Samsung Medical Center, Seoul, Korea
| | - Jong Hoon Park
- Department of Biological Science, Sookmyoung Women's University, Seoul, Korea
| | - York Pei
- Division of Nephrology, Department of Internal Medicine, University Health Network and University of Toronto, Ontario, Canada
| | - Young-Hwan Hwang
- Research Coordination Center for Rare Diseases, Seoul National University Hospital, Seoul, Korea.,Department of Internal Medicine, Eulji General Hospital, Seoul, Korea
| | - Curie Ahn
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.,Research Coordination Center for Rare Diseases, Seoul National University Hospital, Seoul, Korea
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Sonnemans LJP, Hol JC, Monshouwer R, Prokop M, Klein WM. Correlation Between Liver Volumetric Computed Tomography Results and Measured Liver Weight: A Tool for Preoperative Planning of Liver Transplant. EXP CLIN TRANSPLANT 2015; 14:72-8. [PMID: 26643225 DOI: 10.6002/ect.2015.0142] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVES Before liver transplant, it is necessary to know the size of the organ in advance of the procedure. We studied the correlation between liver volumetric computed tomography results and liver weight. MATERIALS AND METHODS Postmortem volumetric computed tomography was conducted on cadavers before autopsy, and 3-dimensional liver volume was estimated with semiautomated software. Liver weight was then determined at autopsy. Linear regression and univariate analysis of variance results were used to determine the accuracy of volumetric 3-dimensional computed tomography in estimating liver weight. We also used 2-dimensional liver sizes to design a 2-dimensional formula to estimate liver volume. RESULTS We found that 3-dimensional volumetric computed tomography was able to accurately estimate liver weight (standard error = 157 g) with a liver density of 0.99 g/mL. Intraobserver and interobserver variabilities were small. The 2-dimensional formula estimated liver weight slightly less accurately (standard error = 212 g). CONCLUSIONS We conclude that liver weight can be estimated accurately with 3-dimensional volumetric computed tomography; estimates were more precise than with the 2-dimensional formula-based liver volume estimation. Volumetric computed tomography can be an important tool during preoperative workup before transplant surgery.
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Affiliation(s)
- Lianne J P Sonnemans
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
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Um EH, Hwang S, Song GW, Jung DH, Ahn CS, Kim KH, Moon DB, Park GC, Lee SG. Calculation of standard liver volume in Korean adults with analysis of confounding variables. KOREAN JOURNAL OF HEPATO-BILIARY-PANCREATIC SURGERY 2015; 19:133-8. [PMID: 26693231 PMCID: PMC4683924 DOI: 10.14701/kjhbps.2015.19.4.133] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 09/10/2015] [Accepted: 09/15/2015] [Indexed: 02/07/2023]
Abstract
Backgrounds/Aims Standard liver volume (SLV) is an important parameter that has been used as a reference value to estimate the graft matching in living donor liver transplantation (LDLT). This study aimed to determine a reliable SLV formula for Korean adult patients as compared with the 15 SLV formulae from other studies and further estimate SLV formula by gender and body mass index (BMI). Methods Computed tomography liver volumetry was performed in 1,000 living donors for LDLT and regression formulae for SLV was calculated. Individual donor data were applied to the 15 previously published SLV formulae, as compared with the SLV formula derived in this study. Analysis for confounding variables of BMI and gender was also performed. Results Two formulae, "SLV (ml)=908.204×BSA-464.728" with DuBois body surface area (BSA) formula and "SLV (ml)=893.485×BSA-439.169" with Monsteller BSA formula, were derived by using the profiles of the 1,000 living donors included in the study. Comparison with other 15 other formulae, all except for Chouker formula showed the mean volume percentage errors of 4.8-5.4%. The gender showed no significant effect on total liver volume (TLV), but there was a significant increase in TLV as BMI increased. Conclusions Our study suggested that most SLV formulae showed a crudely applicable range of SLV estimation for Korean adults. Considering the volume error in estimating SLV, further SLV studies with larger population from multiple centers should be performed to enhance its predictability. Our results suggested that classifying SLV formulae by BMI and gender is unnecessary.
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Affiliation(s)
- Eun Hae Um
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Shin Hwang
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Gi-Won Song
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Dong-Hwan Jung
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Chul-Soo Ahn
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Ki-Hun Kim
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Deok-Bog Moon
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Gil-Chun Park
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sung-Gyu Lee
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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Kokudo T, Hasegawa K, Uldry E, Matsuyama Y, Kaneko J, Akamatsu N, Aoki T, Sakamoto Y, Demartines N, Sugawara Y, Kokudo N, Halkic N. A new formula for calculating standard liver volume for living donor liver transplantation without using body weight. J Hepatol 2015; 63:848-854. [PMID: 26057995 DOI: 10.1016/j.jhep.2015.05.026] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2014] [Revised: 04/17/2015] [Accepted: 05/19/2015] [Indexed: 12/13/2022]
Abstract
BACKGROUND & AIMS The standard liver volume (SLV) is widely used in liver surgery, especially for living donor liver transplantation (LDLT). All the reported formulas for SLV use body surface area or body weight, which can be influenced strongly by the general condition of the patient. METHODS We analyzed the liver volumes of 180 Japanese donor candidates and 160 Swiss patients with normal livers to develop a new formula. The dataset was randomly divided into two subsets, the test and validation sample, stratified by race. The new formula was validated using 50 LDLT recipients. RESULTS Without using body weight-related variables, age, thoracic width measured using computed tomography, and race independently predicted the total liver volume (TLV). A new formula: 203.3-(3.61×age)+(58.7×thoracic width)-(463.7×race [1=Asian, 0=Caucasian]), most accurately predicted the TLV in the validation dataset as compared with any other formulas. The graft volume for LDLT was correlated with the postoperative prothrombin time, and the graft volume/SLV ratio calculated using the new formula was significantly better correlated with the postoperative prothrombin time than the graft volume/SLV ratio calculated using the other formulas or the graft volume/body weight ratio. CONCLUSIONS The new formula derived using the age, thoracic width and race predicted both the TLV in the healthy patient group and the SLV in LDLT recipients more accurately than any other previously reported formulas.
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Affiliation(s)
- Takashi Kokudo
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kiyoshi Hasegawa
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Emilie Uldry
- Department of Visceral Surgery, University Hospital Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Yutaka Matsuyama
- Department of Biostatistics, School of Public Health, The University of Tokyo, Tokyo, Japan
| | - Junichi Kaneko
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nobuhisa Akamatsu
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Taku Aoki
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoshihiro Sakamoto
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nicolas Demartines
- Department of Visceral Surgery, University Hospital Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Yasuhiko Sugawara
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Norihiro Kokudo
- Hepato-Biliary-Pancreatic Surgery Division and Artificial Organ and Transplantation Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
| | - Nermin Halkic
- Department of Visceral Surgery, University Hospital Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
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Truant S, Boleslawski E, Sergent G, Leteurtre E, Duhamel A, Hebbar M, Pruvot FR. Liver function following extended hepatectomy can be accurately predicted using remnant liver volume to body weight ratio. World J Surg 2015; 39:1193-201. [PMID: 25561196 DOI: 10.1007/s00268-014-2929-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Standardised measurement of remnant liver volume (RLV), where total liver volume (TLV) is calculated from patients' body surface area (RLV-sTLV), has been advocated. Extrapolating the model of living donor liver transplantation, we showed in a pilot study that the simplified RLV/body weight ratio (RLVBWR) was accurate in assessing the functional limit of hepatectomy. The aim of the study was to compare in a prospective series of extended right hepatectomy the predictive value of the RLVBWR and the RLV-sTLV at a cut-off of 0.5% (RLVBWR0.5%) and 20% (RLV-sTLV20%), respectively. METHODS We studied the impact of RLVBWR0.5% and of RLV-sTLV20% on three months morbidity and mortality in 74 non-cirrhotic patients operated on for malignant tumours. Of these, 47 patients who were not included in the initial pilot study were enrolled in a prospective validation cohort to reappraise the predictive value of each method. RESULTS RLVBWR and RLV-sTLV were highly correlated (Pearson correlation coefficient, 0.966). Three months overall and severe morbidity (grade 3b-5) and mortality were significantly increased in groups RLVBWR ≤ 0.5% and RLV-sTLVs ≤ 20% compared to groups >0.5% and >20%, respectively. The sensitivity and specificity in predicting death from liver failure were 100 and 84.1% for RLVBWR0.5% and 60 and 94.2% for RLV-sTLV20%, respectively. Similar results were observed in the validation cohort for the RLVBWR0.5% (lack of statistical power for RLV-sTLV as only 2 patients showed a RLV-sTLV ≤ 20%). CONCLUSIONS The RLVBWR0.5% is a method of assessing the remnant liver that is simple and as reliable as the standardised RLV-sTLV20%.
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Affiliation(s)
- Stéphanie Truant
- Service de Chirurgie Digestive et Transplantation, Hôpital HURIEZ, Rue M. Polonovski, CHU, Univ Nord de France, 59000, Lille, France,
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Kim HJ, Kim CY, Park EK, Hur YH, Koh YS, Kim HJ, Cho CK. Volumetric analysis and indocyanine green retention rate at 15 min as predictors of post-hepatectomy liver failure. HPB (Oxford) 2015; 17:159-67. [PMID: 24964188 PMCID: PMC4299390 DOI: 10.1111/hpb.12295] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Accepted: 05/15/2014] [Indexed: 12/12/2022]
Abstract
OBJECTIVES The actual future liver remnant (aFLR) is calculated as the ratio of remnant liver volume (RLV) to total functional liver volume (TFLV). The standardized future liver remnant (sFLR) is calculated as the ratio of RLV to standard liver volume (SLV). The aims of this study were to compare the aFLR with the sFLR and to determine criteria for safe hepatectomy using computed tomography volumetry and indocyanine green retention rate at 15 min (ICG R15). METHODS Medical records and volumetric measurements were obtained retrospectively for 81 patients who underwent right hemi-hepatectomy for malignant hepatic tumours from January 2010 to November 2013. The sFLR was compared with the aFLR, and a ratio of sFLR to ICG R15 as a predictor of postoperative hepatic function was established. RESULTS In patients without cirrhosis, the sFLR showed a stronger correlation with the total serum bilirubin level than the aFLR (R(2) = 0.499 versus R(2) = 0.239). Post-hepatectomy liver failure developed only in the group with an sFLR of <25%, regardless of ICG R15. In patients with cirrhosis, the aFLR and sFLR had no correlation with postoperative total serum bilirubin. An sFLR : ICG R15 ratio of >1.9 showed 66.7% sensitivity and 100% specificity. CONCLUSIONS Regardless of ICG R15, an sFLR of ≥ 25% in patients without cirrhosis, and an sFLR of ≥ 25% with an sFLR : ICG R15 ratio of >1.9 in patients with cirrhosis indicate acceptable levels of safety in major hepatectomy.
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Affiliation(s)
- Hee Joon Kim
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Choong Young Kim
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Eun Kyu Park
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Young Hoe Hur
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Yang Seok Koh
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Hyun Jong Kim
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea
| | - Chol Kyoon Cho
- Department of Surgery, Chonnam National University Medical SchoolGwangju, South Korea,Correspondence, Chol Kyoon Cho, Division of Hepato-Pancreato-Biliary Surgery, Department of Surgery, Chonnam National University Hwasun Hospital, 322 Seoyang-ro, Hwasun-eup, Hwasun-gun, Jeollanam-do 519-763, South Korea. Tel: +82 61 379 7646. Fax: +82 61 379 7661. E-mail:
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Goumard C, Perdigao F, Cazejust J, Zalinski S, Soubrane O, Scatton O. Is computed tomography volumetric assessment of the liver reliable in patients with cirrhosis? HPB (Oxford) 2014; 16:188-94. [PMID: 23679861 PMCID: PMC3921016 DOI: 10.1111/hpb.12110] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Accepted: 03/11/2013] [Indexed: 02/07/2023]
Abstract
OBJECTIVES The estimation of liver volume (LV) has been widely studied in normal liver, the density of which is considered to be equivalent to 1 kg/l. In cirrhosis, volumetric evaluation and its correlation to liver mass remain unclear. The aim of this study was to evaluate the accuracy of computed tomography (CT) scanning to assess LV in patients with cirrhosis. METHODS Liver volume was evaluated by CT (CTLV) and correlated to the explanted liver weight (LW) in 49 patients. Liver density (LD) and its association with clinical features were analysed. Commonly used formulae for estimating LV were also evaluated. The real density of cirrhotic liver was prospectively measured in explant specimens. RESULTS Wide variations between CTLV (in ml) and LW (in g) were found (range: 3-748). Cirrhotic livers in patients with hepatitis B virus infection presented significantly increased LD (P = 0.001) with lower CTLV (P = 0.005). Liver volume as measured by CT was also decreased in patients with Model for End-stage Liver Disease scores of >15 (P = 0.023). Formulae estimating LV correlated poorly with CTLV and LW. The density of cirrhotic liver measured prospectively in 15 patients was 1.1 kg/l. CONCLUSIONS In cirrhotic liver, LV assessed by CT did not correspond to real LW. Liver density changed according to the aetiology and severity of liver disease. Commonly used formulae did not accurately assess LV.
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Affiliation(s)
- Claire Goumard
- Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France
| | - Fabiano Perdigao
- Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France
| | - Julien Cazejust
- Department of Radiology, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France
| | - Stéphane Zalinski
- Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France
| | - Olivier Soubrane
- Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France
| | - Olivier Scatton
- Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital Assistance Publique–Hôpitaux (AP-HP)Paris, France,University Pierre and Marie Curie (UPMC, University of Paris 06)Paris, France,Correspondence Olivier Scatton, Department of Hepatobiliary and Transplant Surgery, Saint Antoine Hospital, 184 Rue du Faubourg Saint Antoine, Paris 75012, France. Tel: + 33 1 49 28 25 61. Fax: + 33 1 71 97 01 57. E-mail:
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Kim HJ, Kim CY, Hur YH, Koh YS, Kim JC, Cho CK, Kim HJ. Comparison of remnant to total functional liver volume ratio and remnant to standard liver volume ratio as a predictor of postoperative liver function after liver resection. KOREAN JOURNAL OF HEPATO-BILIARY-PANCREATIC SURGERY 2013; 17:143-51. [PMID: 26155230 PMCID: PMC4304515 DOI: 10.14701/kjhbps.2013.17.4.143] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Revised: 09/18/2013] [Accepted: 09/30/2013] [Indexed: 12/22/2022]
Abstract
BACKGROUNDS/AIMS The future liver remnant (FLR) is usually calculated as a ratio of the remnant liver volume (RLV) to the total functional liver volume (RLV/TFLV). In liver transplantation, it is generally accepted that the ratio of the graft volume to standard liver volume (SLV) needs to be at least 30% to 40% to fit the hepatic metabolic demands of the recipient. The aim of this study was to compare RLV/TFLV versus RLV/SLV as a predictor of postoperative liver function and liver failure. METHODS CT volumetric measurements of RLV were obtained retrospectively in 74 patients who underwent right hemihepatectomy for a malignant tumor from January 2010 to May 2013. RLV and TFLV were obtained using CT volumetry, and SLV was calculated using Yu's formula: SLV (ml)=21.585×body weight (kg)(0.732)×height (cm)(0.225). The RLV/SLV ratio was compared with the RLV/TFLV as a predictor of postoperative hepatic function. RESULTS Postheptectomy liver failure (PHLF), morbidity, and serum total bilirubin level at postoperative day 5 (POD 5) were increased significantly in the group with the RLV/SLV ≤30% compared with the group with the RLV/SLV >30% (p=0.002, p=0.004, and p<0.001, respectively). But RLV/TFLV was not correlated with PHLF and morbidity (p=1.000 and 0.798, respectively). RLV/SLV showed a stronger correlation with serum total bilirubin level than RLV/TFLV (RLV/SLV vs. RLV/TFLV, R=0.706 vs. 0.499, R(2)=0.499 vs. 0.239). CONCLUSIONS RLV/SLV was more specific than RLV/TFLV in predicting the postoperative course after right hemihepatectomy. To determine the safe limit of hepatic resection, a larger-scaled prospective study is needed.
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Affiliation(s)
- Hee Joon Kim
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Choong Young Kim
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Young Hoe Hur
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Yang Seok Koh
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Jung Chul Kim
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Chol Kyoon Cho
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
| | - Hyun Jong Kim
- Department of Surgery, Chonnam National University College of Medicine, Gwangju, Korea
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Yang X, Yu HC, Choi Y, Lee W, Wang B, Yang J, Hwang H, Kim JH, Song J, Cho BH, You H. A hybrid semi-automatic method for liver segmentation based on level-set methods using multiple seed points. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2013; 113:69-79. [PMID: 24113421 DOI: 10.1016/j.cmpb.2013.08.019] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Revised: 08/27/2013] [Accepted: 08/29/2013] [Indexed: 06/02/2023]
Abstract
The present study developed a hybrid semi-automatic method to extract the liver from abdominal computerized tomography (CT) images. The proposed hybrid method consists of a customized fast-marching level-set method for detection of an optimal initial liver region from multiple seed points selected by the user and a threshold-based level-set method for extraction of the actual liver region based on the initial liver region. The performance of the hybrid method was compared with those of the 2D region growing method implemented in OsiriX using abdominal CT datasets of 15 patients. The hybrid method showed a significantly higher accuracy in liver extraction (similarity index, SI=97.6 ± 0.5%; false positive error, FPE = 2.2 ± 0.7%; false negative error, FNE=2.5 ± 0.8%; average symmetric surface distance, ASD=1.4 ± 0.5mm) than the 2D (SI=94.0 ± 1.9%; FPE = 5.3 ± 1.1%; FNE=6.5 ± 3.7%; ASD=6.7 ± 3.8mm) region growing method. The total liver extraction time per CT dataset of the hybrid method (77 ± 10 s) is significantly less than the 2D region growing method (575 ± 136 s). The interaction time per CT dataset between the user and a computer of the hybrid method (28 ± 4 s) is significantly shorter than the 2D region growing method (484 ± 126 s). The proposed hybrid method was found preferred for liver segmentation in preoperative virtual liver surgery planning.
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Affiliation(s)
- Xiaopeng Yang
- Pohang University of Science and Technology, Pohang 790-784, South Korea
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Vijay K, Naidu C, Godara R, Rao P, Sharma S, Vijayvergia V. Standard liver volume estimation in Indian population: Need for an accurate formula. INDIAN JOURNAL OF TRANSPLANTATION 2013. [DOI: 10.1016/j.ijt.2013.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
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Gunay–Aygun M, Font–Montgomery E, Lukose L, Gerstein MT, Piwnica–Worms K, Choyke P, Daryanani KT, Turkbey B, Fischer R, Bernardini I, Sincan M, Zhao X, Sandler NG, Roque A, Douek DC, Graf J, Huizing M, Bryant JC, Mohan P, Gahl WA, Heller T. Characteristics of congenital hepatic fibrosis in a large cohort of patients with autosomal recessive polycystic kidney disease. Gastroenterology 2013; 144:112-121.e2. [PMID: 23041322 PMCID: PMC4162098 DOI: 10.1053/j.gastro.2012.09.056] [Citation(s) in RCA: 108] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Revised: 09/22/2012] [Accepted: 09/25/2012] [Indexed: 02/06/2023]
Abstract
BACKGROUND & AIMS Autosomal recessive polycystic kidney disease (ARPKD), the most common ciliopathy of childhood, is characterized by congenital hepatic fibrosis and progressive cystic degeneration of kidneys. We aimed to describe congenital hepatic fibrosis in patients with ARPKD, confirmed by detection of mutations in PKHD1. METHODS Patients with ARPKD and congenital hepatic fibrosis were evaluated at the National Institutes of Health from 2003 to 2009. We analyzed clinical, molecular, and imaging data from 73 patients (age, 1-56 years; average, 12.7 ± 13.1 years) with kidney and liver involvement (based on clinical, imaging, or biopsy analyses) and mutations in PKHD1. RESULTS Initial symptoms were liver related in 26% of patients, and others presented with kidney disease. One patient underwent liver and kidney transplantation, and 10 others received kidney transplants. Four presented with cholangitis and one with variceal bleeding. Sixty-nine percent of patients had enlarged left lobes on magnetic resonance imaging, 92% had increased liver echogenicity on ultrasonography, and 65% had splenomegaly. Splenomegaly started early in life; 60% of children younger than 5 years had enlarged spleens. Spleen volume had an inverse correlation with platelet count and prothrombin time but not with serum albumin level. Platelet count was the best predictor of spleen volume (area under the curve of 0.88905), and spleen length corrected for patient's height correlated inversely with platelet count (R(2) = 0.42, P < .0001). Spleen volume did not correlate with renal function or type of PKHD1 mutation. Twenty-two of 31 patients who underwent endoscopy were found to have varices. Five had variceal bleeding, and 2 had portosystemic shunts. Forty-percent had Caroli syndrome, and 30% had an isolated dilated common bile duct. CONCLUSIONS Platelet count is the best predictor of the severity of portal hypertension, which has early onset but is underdiagnosed in patients with ARPKD. Seventy percent of patients with ARPKD have biliary abnormalities. Kidney and liver disease are independent, and variability in severity is not explainable by type of PKHD1 mutation; ClinicalTrials.gov number, NCT00068224.
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Affiliation(s)
- Meral Gunay–Aygun
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland,The Intramural Program of the Office of Rare Diseases, Bethesda, Maryland
| | | | - Linda Lukose
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Maya Tuchman Gerstein
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Katie Piwnica–Worms
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Peter Choyke
- Molecular Imaging Program, National Cancer Institute, Bethesda, Maryland
| | | | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, Bethesda, Maryland
| | - Roxanne Fischer
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Isa Bernardini
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Murat Sincan
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Xiongce Zhao
- Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
| | - Netanya G. Sandler
- Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Annelys Roque
- Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Daniel C. Douek
- Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Jennifer Graf
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Marjan Huizing
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Joy C. Bryant
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland
| | - Parvathi Mohan
- Department of Pediatric Gastroenterology, George Washington University, Washington, DC
| | - William A. Gahl
- Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland,The Intramural Program of the Office of Rare Diseases, Bethesda, Maryland
| | - Theo Heller
- Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland
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