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Tartari C, Porões F, Schmidt S, Abler D, Vetterli T, Depeursinge A, Dromain C, Violi NV, Jreige M. MRI and CT radiomics for the diagnosis of acute pancreatitis. Eur J Radiol Open 2025; 14:100636. [PMID: 39967811 PMCID: PMC11833635 DOI: 10.1016/j.ejro.2025.100636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2024] [Revised: 01/17/2025] [Accepted: 01/22/2025] [Indexed: 02/20/2025] Open
Abstract
Purpose To evaluate the single and combined diagnostic performances of CT and MRI radiomics for diagnosis of acute pancreatitis (AP). Materials and methods We prospectively enrolled 78 patients (mean age 55.7 ± 17 years, 48.7 % male) diagnosed with AP between 2020 and 2022. Patients underwent contrast-enhanced CT (CECT) within 48-72 h of symptoms and MRI ≤ 24 h after CECT. The entire pancreas was manually segmented tridimensionally by two operators on portal venous phase (PVP) CECT images, T2-weighted imaging (WI) MR sequence and non-enhanced and PVP T1-WI MR sequences. A matched control group (n = 77) with normal pancreas was used. Dataset was randomly split into training and test, and various machine learning algorithms were compared. Receiver operating curve analysis was performed. Results The T2WI model exhibited significantly better diagnostic performance than CECT and non-enhanced and venous T1WI, with sensitivity, specificity and AUC of 73.3 % (95 % CI: 71.5-74.7), 80.1 % (78.2-83.2), and 0.834 (0.819-0.844) for T2WI (p = 0.001), 74.4 % (71.5-76.4), 58.7 % (56.3-61.1), and 0.654 (0.630-0.677) for non-enhanced T1WI, 62.1 % (60.1-64.2), 78.7 % (77.1-81), and 0.787 (0.771-0.810) for venous T1WI, and 66.4 % (64.8-50.9), 48.4 % (46-50.9), and 0.610 (0.586-0.626) for CECT, respectively.The combination of T2WI with CECT enhanced diagnostic performance compared to T2WI, achieving sensitivity, specificity and AUC of 81.4 % (80-80.3), 78.1 % (75.9-80.2), and 0.911 (0.902-0.920) (p = 0.001). Conclusion The MRI radiomics outperformed the CT radiomics model to detect diagnosis of AP and the combination of MRI with CECT showed better performance than single models. The translation of radiomics into clinical practice may improve detection of AP, particularly MRI radiomics.
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Affiliation(s)
- Caterina Tartari
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Fabio Porões
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sabine Schmidt
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Daniel Abler
- Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland
- Department of Oncology, Geneva University Hospitals, Geneva, Switzerland
| | - Thomas Vetterli
- Institute of Informatics, School of Management, HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland
| | - Adrien Depeursinge
- Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland
- Department of Oncology, Geneva University Hospitals, Geneva, Switzerland
| | - Clarisse Dromain
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Naïk Vietti Violi
- Department of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mario Jreige
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Ma Y, Yue P, Zhang J, Yuan J, Liu Z, Chen Z, Zhang H, Zhang C, Zhang Y, Dong C, Lin Y, Liu Y, Li S, Meng W. Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform. Ann Med 2024; 56:2357354. [PMID: 38813815 PMCID: PMC11141304 DOI: 10.1080/07853890.2024.2357354] [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: 08/17/2023] [Accepted: 04/26/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity. METHODS We retrospectively recruited GSP patients who underwent CT imaging within 48 h of admission from tertiary referral centre. Radiomics and CT features were extracted from CT scans. The clinical and CT features were selected by the random forest algorithm to develop the ML GSP model for the identification of severity of GSP (mild or severe), and its predictive efficacy was compared with radiomics model. The predictive performance was assessed by the area under operating characteristic curve. Calibration curve and decision curve analysis were performed to demonstrate the classification performance and clinical efficacy. Furthermore, we built a web-based open access GSP severity calculator. The study was registered with ClinicalTrials.gov (NCT05498961). RESULTS A total of 301 patients were enrolled. They were randomly assigned into the training (n = 210) and validation (n = 91) cohorts at a ratio of 7:3. The random forest algorithm identified the level of calcium ions, WBC count, urea level, combined cholecystitis, gallbladder wall thickening, gallstones, and hydrothorax as the seven predictive factors for severity of GSP. In the validation cohort, the areas under the curve for the radiomics model and ML GSP model were 0.841 (0.757-0.926) and 0.914 (0.851-0.978), respectively. The calibration plot shows that the ML GSP model has good consistency between the prediction probability and the observation probability. Decision curve analysis showed that the ML GSP model had high clinical utility. CONCLUSIONS We built the ML GSP model based on clinical and CT image features and distributed it as a free web-based calculator. Our results indicated that the ML GSP model is useful for predicting the severity of GSP.
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Affiliation(s)
- Yuhu Ma
- Department of Anesthesiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Ping Yue
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Jinduo Zhang
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Jinqiu Yuan
- Clinical Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China
| | - Zhaoqing Liu
- School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Zixian Chen
- Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Hengwei Zhang
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Chao Zhang
- Department of Orthopedics, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Yong Zhang
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Chunlu Dong
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Yanyan Lin
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Yatao Liu
- Department of Anesthesiology, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Shuyan Li
- School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Wenbo Meng
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
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Qi M, Lu C, Dai R, Zhang J, Hu H, Shan X. Prediction of acute pancreatitis severity based on early CT radiomics. BMC Med Imaging 2024; 24:321. [PMID: 39604925 PMCID: PMC11603661 DOI: 10.1186/s12880-024-01509-9] [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: 10/01/2024] [Accepted: 11/21/2024] [Indexed: 11/29/2024] Open
Abstract
BACKGROUND This study aims to develop and validate an integrated predictive model combining CT radiomics and clinical parameters for early assessment of acute pancreatitis severity. METHODS A retrospective cohort of 246 patients with acute pancreatitis was analyzed, with a 70%-30% split for training and validation groups. CT image segmentation was performed using ITK-SNAP, followed by the extraction of radiomics features. The stability of the radiomics features was assessed through inter-observer Intraclass Correlation Coefficient analysis. Feature selection was carried out using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation. A radiomics model was constructed through logistic regression to compute the radiomics score. Concurrently, univariate and multivariate logistic regression were employed to identify independent clinical risk factors for the clinical model. The radiomics score and clinical variables were integrated into a combined model, which was visualized with a nomogram. Model performance and net clinical benefit were evaluated through the area under the receiver operating characteristic curve (AUC), the DeLong test, and decision curve analysis. RESULTS A total of 913 radiomics features demonstrated satisfactory consistency. Eight features were selected for the radiomics model. Serum calcium, C-reactive protein, and white blood cell count were identified as independent clinical predictors. The AUC of the radiomics model was 0.871 (95% CI, 0.793-0.949) in the training cohort and 0.859 (95% CI, 0.751-0.967) in the validation cohort. The clinical model achieved AUCs of 0.833 (95% CI, 0.756-0.910) and 0.810 (95% CI, 0.692-0.929) for the training and validation cohorts, respectively. The combined model outperformed both the radiomics and clinical models, with an AUC of 0.905 (95% CI, 0.837-0.973) in the training cohort and 0.908 (95% CI, 0.824-0.992) in the validation cohort. The DeLong test confirmed superior predictive performance of the combined model over both the radiomics and clinical models in the training cohort, and over the clinical model in the validation cohort. Decision curve analysis further demonstrated that the combined model provided greater net clinical benefit than the radiomics or clinical models alone. CONCLUSION The clinical-radiomics model offers a novel tool for the early prediction of acute pancreatitis severity, providing valuable support for clinical decision-making.
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Affiliation(s)
- Mingyao Qi
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, No. 8 Dianli Road, Zhenjiang, Jiangsu, P. R. China
| | - Chao Lu
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, No. 8 Dianli Road, Zhenjiang, Jiangsu, P. R. China
| | - Rao Dai
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, No. 8 Dianli Road, Zhenjiang, Jiangsu, P. R. China
| | - Jiulou Zhang
- Artificial Intelligence Imaging Laboratory, Nanjing Medical University, No.101 Longmian Avenue, Nanjing, Jiangsu, P. R. China
| | - Hui Hu
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing, Jiangsu, P. R. China.
| | - Xiuhong Shan
- Department of Radiology, Affiliated People's Hospital of Jiangsu University, No. 8 Dianli Road, Zhenjiang, Jiangsu, P. R. China.
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Yao J, Chu LC, Patlas M. Applications of Artificial Intelligence in Acute Abdominal Imaging. Can Assoc Radiol J 2024; 75:761-770. [PMID: 38715249 DOI: 10.1177/08465371241250197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024] Open
Abstract
Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology. Acute abdominal pain is a common clinical presentation that can range from benign conditions to life-threatening emergencies. The critical nature of these situations renders emergent abdominal imaging an ideal candidate for AI applications. CT, radiographs, and ultrasound are the most common modalities for imaging evaluation of these patients. For each modality, numerous studies have assessed the performance of AI models for detecting common pathologies, such as appendicitis, bowel obstruction, and cholecystitis. The capabilities of these models range from simple classification to detailed severity assessment. This narrative review explores the evolution, trends, and challenges in AI applications for evaluating acute abdominal pathologies. We review implementations of AI for non-traumatic and traumatic abdominal pathologies, with discussion of potential clinical impact, challenges, and future directions for the technology.
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Affiliation(s)
- Jason Yao
- Department of Radiology, McMaster University, Hamilton, ON, Canada
| | - Linda C Chu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael Patlas
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
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Zhang C, Peng J, Wang L, Wang Y, Chen W, Sun MW, Jiang H. A deep learning-powered diagnostic model for acute pancreatitis. BMC Med Imaging 2024; 24:154. [PMID: 38902660 PMCID: PMC11188273 DOI: 10.1186/s12880-024-01339-9] [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: 03/08/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND Acute pancreatitis is one of the most common diseases requiring emergency surgery. Rapid and accurate recognition of acute pancreatitis can help improve clinical outcomes. This study aimed to develop a deep learning-powered diagnostic model for acute pancreatitis. MATERIALS AND METHODS In this investigation, we enrolled a cohort of 190 patients with acute pancreatitis who were admitted to Sichuan Provincial People's Hospital between January 2020 and December 2021. Abdominal computed tomography (CT) scans were obtained from both patients with acute pancreatitis and healthy individuals. Our model was constructed using two modules: (1) the acute pancreatitis classifier module; (2) the pancreatitis lesion segmentation module. Each model's performance was assessed based on precision, recall rate, F1-score, Area Under the Curve (AUC), loss rate, frequency-weighted accuracy (fwavacc), and Mean Intersection over Union (MIOU). RESULTS Upon admission, significant variations were observed between patients with mild and severe acute pancreatitis in inflammatory indexes, liver, and kidney function indicators, as well as coagulation parameters. The acute pancreatitis classifier module exhibited commendable diagnostic efficacy, showing an impressive AUC of 0.993 (95%CI: 0.978-0.999) in the test set (comprising healthy examination patients vs. those with acute pancreatitis, P < 0.001) and an AUC of 0.850 (95%CI: 0.790-0.898) in the external validation set (healthy examination patients vs. patients with acute pancreatitis, P < 0.001). Furthermore, the acute pancreatitis lesion segmentation module demonstrated exceptional performance in the validation set. For pancreas segmentation, peripancreatic inflammatory exudation, peripancreatic effusion, and peripancreatic abscess necrosis, the MIOU values were 86.02 (84.52, 87.20), 61.81 (56.25, 64.83), 57.73 (49.90, 68.23), and 66.36 (55.08, 72.12), respectively. These findings underscore the robustness and reliability of the developed models in accurately characterizing and assessing acute pancreatitis. CONCLUSION The diagnostic model for acute pancreatitis, driven by deep learning, exhibits excellent efficacy in accurately evaluating the severity of the condition. TRIAL REGISTRATION This is a retrospective study.
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Affiliation(s)
- Chi Zhang
- Department of Intensive Care Medicine, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, Chengdu, China
| | - Jin Peng
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Histology and Neuroscience, Sichuan University, Chengdu, China
| | - Lu Wang
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Department of Emergency Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Wang
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Beijing, China
| | - Wei Chen
- Department of Clinical Nutrition, Peking Union Medical College Hospital, Beijing, China
| | - Ming-Wei Sun
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Hua Jiang
- Institute for Emergency and Disaster Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
- Department of Emergency Medicine, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
- Sichuan Provincial Clinical Research Center for Emergency and Critical Care, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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Hu JX, Zhao CF, Wang SL, Tu XY, Huang WB, Chen JN, Xie Y, Chen CR. Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence. World J Gastroenterol 2023; 29:5268-5291. [PMID: 37899784 PMCID: PMC10600804 DOI: 10.3748/wjg.v29.i37.5268] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/31/2023] [Accepted: 09/14/2023] [Indexed: 09/25/2023] Open
Abstract
Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease of the pancreas, with clinical management determined by the severity of the disease. Diagnosis, severity prediction, and prognosis assessment of AP typically involve the use of imaging technologies, such as computed tomography, magnetic resonance imaging, and ultrasound, and scoring systems, including Ranson, Acute Physiology and Chronic Health Evaluation II, and Bedside Index for Severity in AP scores. Computed tomography is considered the gold standard imaging modality for AP due to its high sensitivity and specificity, while magnetic resonance imaging and ultrasound can provide additional information on biliary obstruction and vascular complications. Scoring systems utilize clinical and laboratory parameters to classify AP patients into mild, moderate, or severe categories, guiding treatment decisions, such as intensive care unit admission, early enteral feeding, and antibiotic use. Despite the central role of imaging technologies and scoring systems in AP management, these methods have limitations in terms of accuracy, reproducibility, practicality and economics. Recent advancements of artificial intelligence (AI) provide new opportunities to enhance their performance by analyzing vast amounts of clinical and imaging data. AI algorithms can analyze large amounts of clinical and imaging data, identify scoring system patterns, and predict the clinical course of disease. AI-based models have shown promising results in predicting the severity and mortality of AP, but further validation and standardization are required before widespread clinical application. In addition, understanding the correlation between these three technologies will aid in developing new methods that can accurately, sensitively, and specifically be used in the diagnosis, severity prediction, and prognosis assessment of AP through complementary advantages.
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Affiliation(s)
- Jian-Xiong Hu
- Intensive Care Unit, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
| | - Cheng-Fei Zhao
- School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China
- Key Laboratory of Pharmaceutical Analysis and Laboratory Medicine, Putian University, Putian 351100, Fujian Province, China
| | - Shu-Ling Wang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Xiao-Yan Tu
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Wei-Bin Huang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Jun-Nian Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Ying Xie
- School of Mechanical, Electrical and Information Engineering, Putian University, Putian 351100, Fujian Province, China
| | - Cun-Rong Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
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Kjelle E, Andersen ER, Krokeide AM, Soril LJJ, van Bodegom-Vos L, Clement FM, Hofmann BM. Characterizing and quantifying low-value diagnostic imaging internationally: a scoping review. BMC Med Imaging 2022; 22:73. [PMID: 35448987 PMCID: PMC9022417 DOI: 10.1186/s12880-022-00798-2] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 04/12/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Inappropriate and wasteful use of health care resources is a common problem, constituting 10-34% of health services spending in the western world. Even though diagnostic imaging is vital for identifying correct diagnoses and administrating the right treatment, low-value imaging-in which the diagnostic test confers little to no clinical benefit-is common and contributes to inappropriate and wasteful use of health care resources. There is a lack of knowledge on the types and extent of low-value imaging. Accordingly, the objective of this study was to identify, characterize, and quantify the extent of low-value diagnostic imaging examinations for adults and children. METHODS A scoping review of the published literature was performed. Medline-Ovid, Embase-Ovid, Scopus, and Cochrane Library were searched for studies published from 2010 to September 2020. The search strategy was built from medical subject headings (Mesh) for Diagnostic imaging/Radiology OR Health service misuse/Medical overuse OR Procedures and Techniques Utilization/Facilities and Services Utilization. Articles in English, German, Dutch, Swedish, Danish, or Norwegian were included. RESULTS A total of 39,986 records were identified and, of these, 370 studies were included in the final synthesis. Eighty-four low-value imaging examinations were identified. Imaging of atraumatic pain, routine imaging in minor head injury, trauma, thrombosis, urolithiasis, after thoracic interventions, fracture follow-up and cancer staging/follow-up were the most frequently identified low-value imaging examinations. The proportion of low-value imaging varied between 2 and 100% inappropriate or unnecessary examinations. CONCLUSIONS A comprehensive list of identified low-value radiological examinations for both adults and children are presented. Future research should focus on reasons for low-value imaging utilization and interventions to reduce the use of low-value imaging internationally. SYSTEMATIC REVIEW REGISTRATION PROSPERO: CRD42020208072.
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Affiliation(s)
- Elin Kjelle
- Institute for the Health Sciences, The Norwegian University of Science and Technology (NTNU) at Gjøvik, NTNU Gjøvik, Postbox 191, 2802 Gjøvik, Norway
| | - Eivind Richter Andersen
- Institute for the Health Sciences, The Norwegian University of Science and Technology (NTNU) at Gjøvik, NTNU Gjøvik, Postbox 191, 2802 Gjøvik, Norway
| | - Arne Magnus Krokeide
- Institute for the Health Sciences, The Norwegian University of Science and Technology (NTNU) at Gjøvik, NTNU Gjøvik, Postbox 191, 2802 Gjøvik, Norway
| | - Lesley J. J. Soril
- Department of Community Health Sciences and The Health Technology Assessment Unit, O’Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6 Canada
| | - Leti van Bodegom-Vos
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Fiona M. Clement
- Department of Community Health Sciences and The Health Technology Assessment Unit, O’Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6 Canada
| | - Bjørn Morten Hofmann
- Institute for the Health Sciences, The Norwegian University of Science and Technology (NTNU) at Gjøvik, NTNU Gjøvik, Postbox 191, 2802 Gjøvik, Norway
- Centre of Medical Ethics, The University of Oslo, Blindern, Postbox 1130, 0318 Oslo, Norway
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Utilization of computerized tomography scan in the management of acute pancreatitis at a large tertiary institution. Pancreatology 2022; 22:83-84. [PMID: 34863610 DOI: 10.1016/j.pan.2021.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 12/11/2022]
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9
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Yang E, Nguyen NH, Kwong WT. Abdominal free fluid in acute pancreatitis predicts necrotizing pancreatitis and organ failure. Ann Gastroenterol 2021; 34:872-878. [PMID: 34815654 PMCID: PMC8596223 DOI: 10.20524/aog.2021.0666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/07/2021] [Indexed: 11/16/2022] Open
Abstract
Background Abdominal free fluid is frequently encountered on cross-sectional imaging for acute pancreatitis and may be a sign of increased severity and complications. This study examines the ability of free fluid to predict necrotizing pancreatitis and other adverse outcomes. Methods We conducted a single-center retrospective study of patients with acute pancreatitis and multiple cross-sectional imaging studies. Patients were divided into those who demonstrated free fluid on initial imaging and those without free fluid. The primary outcome was developing necrotizing pancreatitis. Logistic regression analysis assessed the performance of several predictors. Results A total of 245 acute pancreatitis patients were included. Pancreatic necrosis occurred more frequently in the free fluid group (31.3 vs. 1.3%, P<0.001). The free fluid group also had higher rates of transient organ failure (17.7 vs. 3.4%, P<0.001), persistent organ failure (17.7 vs. 2.0%, P<0.001), in-hospital mortality (7.3 vs. 1.3%, P=0.016), length of stay (16.2 vs. 5.5 days, P<0.001), and intensive care unit admission (30.2 vs. 4.7%, P<0.001). On multivariate logistic regression, free fluid was the strongest predictor (adjusted odds ratio 17.11, 95% confidence interval 3.68-79.65; P<0.001) for necrotizing pancreatitis, with an excellent performance (area under the curve 0.92). When neither fluid on initial imaging nor persistent systemic inflammatory response syndrome was present, the negative predictive value for developing pancreatic necrosis was 100%. Conclusions Free fluid in acute pancreatitis is a strong predictor for necrotizing pancreatitis, organ failure and mortality, and outperformed current predictors. Patients who lacked both free fluid on imaging and persistent systemic inflammatory response syndrome are at low risk for adverse outcomes and may be considered for early discharge.
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Affiliation(s)
- Edward Yang
- Division of Gastroenterology, Department of Medicine, UC San Diego, La Jolla, California, USA
| | - Nghia H Nguyen
- Division of Gastroenterology, Department of Medicine, UC San Diego, La Jolla, California, USA
| | - Wilson T Kwong
- Division of Gastroenterology, Department of Medicine, UC San Diego, La Jolla, California, USA
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10
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Glazer DI, Cochon LR, Raja AS, Jin DX, Banks PA, Sodickson AD, Khorasani R. Prevalence of imaging findings of acute pancreatitis in emergency department patients with elevated serum lipase. Am J Emerg Med 2021; 50:10-13. [PMID: 34271230 DOI: 10.1016/j.ajem.2021.07.015] [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: 04/26/2021] [Revised: 06/24/2021] [Accepted: 07/02/2021] [Indexed: 10/20/2022] Open
Abstract
PURPOSE To assess the association of imaging features of acute pancreatitis (AP) with the magnitude of lipase elevation in Emergency Department (ED) patients. METHODS This Institutional Review Board-approved retrospective study included 509 consecutive patients presenting from 9/1/13-8/31/15 to a large academic ED with serum lipase levels ≥3× the upper limit of normal (ULN) (≥180 U/L). Patients were excluded if they did not have imaging (n = 131) or had a history of trauma, abdominal metastases, altered mental status, or transfer from an outside hospital (n = 190); the final study population was 188 patients. Imaging exams were retrospectively evaluated, and a consensus opinion of two subspecialty-trained abdominal radiologists was used to diagnose AP. Primary outcome was presence of imaging features of AP stratified by lipase level (≥3×-10× ULN and > 10× ULN). Secondary outcome was rate of discordant consensus evaluation compared to original radiologist's report. RESULTS 25.0% of patients (47/188) had imaging features of AP. When lipase was >10× ULN (n = 94), patients were more likely to have imaging features of AP (34%) vs. those with mild elevation (16%) (p = 0.0042). There was moderately strong correlation between lipase level and presence of imaging features of AP (r = 0.48, p < 0.0001). Consensus review of CT and MRI images was discordant with the original report in 14.9% (28/188) of cases. CONCLUSION Prevalence of imaging signs of AP in an ED population with lipase ≥3× ULN undergoing imaging is low. However, the probability of imaging features of AP increases as lipase value increases.
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Affiliation(s)
- Daniel I Glazer
- Division of Abdominal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America; Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 20 Kent Street, Brookline, MA 02445, United States of America.
| | - Lailah R Cochon
- Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 20 Kent Street, Brookline, MA 02445, United States of America
| | - Ali S Raja
- Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 20 Kent Street, Brookline, MA 02445, United States of America; Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, United States of America
| | - David X Jin
- Center for Pancreatic Disease, Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America
| | - Peter A Banks
- Center for Pancreatic Disease, Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America
| | - Aaron D Sodickson
- Division of Emergency Radiology, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America
| | - Ramin Khorasani
- Division of Abdominal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, United States of America; Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 20 Kent Street, Brookline, MA 02445, United States of America
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11
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Lohse MR, Ullah K, Seda J, Thode HC, Singer AJ, Morley EJ. The role of emergency department computed tomography in early acute pancreatitis. Am J Emerg Med 2021; 48:92-95. [PMID: 33866269 DOI: 10.1016/j.ajem.2021.04.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/31/2021] [Accepted: 04/10/2021] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Computed tomography (CT) is often ordered for patients in whom the diagnosis of acute pancreatitis (AP) has already been established via elevated lipase levels and typical abdominal pain. We investigated whether early CT imaging performed in the ED altered the diagnosis or management. METHODS A retrospective chart review was performed on patients presenting to a large, academic ED between the years 2013-2015 with AP who received CT imaging. Relevant history, laboratory, imaging data, and hospital course were abstracted from the medical record and analyzed by three independent reviewers, with 100% agreement among reviewers on 30 randomly selected cases. The primary outcome was whether the CT led to a change in diagnosis or management above and beyond the ultrasound. Univariate and multivariate analyses were performed to determine association between predictor variables and outcomes. RESULTS The electronic health record query yielded 458 patients. Of those, 174 met the American College of Gastroenterology criteria for AP and were included in the study. 145 patients (83%) had abdominal CT during their hospital course, 125 (86%) of which were performed in the ED. Of these 145 patients, 57 (39%) had imaging evidence of AP. 107 patients had abdominal ultrasound (US) during their hospital course. Of 84 patients who had both CT and US, 31 (37%) patients were diagnosed with gallstones by US versus 19 (23%) by CT. Biliary dilation/obstruction was diagnosed by US in 5 (6%) patients versus 4 (5%) by CT. CT led to the correct diagnosis or change in management in 21 (14.5%) patients. CONCLUSION Early CT may alter the diagnosis or management in up to 15% of patients presenting to the ED with AP, especially older patients with prior episodes of pancreatitis and biliary interventions, however abdominal US may be a more sensitive screening study for biliary etiologies and thereby better direct further management.
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Affiliation(s)
- Matthew R Lohse
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America
| | - Kazi Ullah
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America
| | - Jesus Seda
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America
| | - Henry C Thode
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America
| | - Adam J Singer
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America.
| | - Eric J Morley
- Department of Emergency Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States of America
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12
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Shah J, Nwogu C, Vivian E, John ES, Kedia P, Sellers B, Cler L, Acharya P, Tarnasky P. The Value of Managing Acute Pancreatitis With Standardized Order Sets to Achieve "Perfect Care". Pancreas 2021; 50:293-299. [PMID: 33835958 DOI: 10.1097/mpa.0000000000001758] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVES We aimed to define perfect care index (PCI) metrics and to evaluate whether implementation of standardized order sets would improve outcomes without increasing hospital-based charges in patients with acute pancreatitis (AP). METHODS This is a retrospective, pre-post, observational study measuring clinical quality, processes of care, and hospital-based charges at a single tertiary care center. The first data set included AP patients from August 2011 to December 2014 (n = 219) before the implementation of a standardized order set (Methodist Acute Pancreatitis Protocol [MAPP]) and AP patients after MAPP implementation from January 2015 to September 2018 (n = 417). The second data set included AP patients (n = 150 in each group) from January 2013 to September 2014 (pre-MAPP) and January 2018 to September 2019 (post-MAPP) to evaluate perfect care between the 2 cohorts after controlling for systemic inflammatory response syndrome at baseline. Length of stay, PCI, and hospital-based charges were measured. RESULTS The post-MAPP cohort had a significantly shorter length of stay (median, 3 days vs 4 days; P = 0.01). In the second data set, PCI significantly increased after implementation of MAPP order sets (5.3%-35.3%, P < 0.0001). CONCLUSIONS The MAPP order sets increased the value of care by improving clinical outcomes without increasing hospital-based charges.
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Affiliation(s)
- Jimmy Shah
- From the Methodist Digestive Institute, Methodist Dallas Medical Center, Dallas
| | - Christiana Nwogu
- From the Methodist Digestive Institute, Methodist Dallas Medical Center, Dallas
| | - Elaina Vivian
- From the Methodist Digestive Institute, Methodist Dallas Medical Center, Dallas
| | - Elizabeth S John
- From the Methodist Digestive Institute, Methodist Dallas Medical Center, Dallas
| | | | | | - Leslie Cler
- Internal Medicine and Hospital Administration, Methodist Dallas Medical Center
| | - Priyanka Acharya
- Clinical Research Institute, Methodist Health System, Dallas, TX
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13
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Liao WC, Tu TC, Lee KC, Tseng JH, Chen MJ, Sun CK, Wang SY, Chang WK, Chang PY, Wu MS, Lin TJ, Lee HL, Chen JH, Yuan KC, Liu NJ, Wu HC, Liang PC, Wang HP, Hwang TL, Lee CL. Taiwanese consensus recommendations for acute pancreatitis. J Formos Med Assoc 2020; 119:1343-1352. [PMID: 31395463 DOI: 10.1016/j.jfma.2019.07.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/11/2019] [Accepted: 07/17/2019] [Indexed: 12/12/2022] Open
Abstract
The incidence of acute pancreatitis and related health care utilization are increasing. Acute pancreatitis may result in organ failure and various local complications with risks of morbidity and even mortality. Recent advances in research have provided novel insights into the assessment and management for acute pancreatitis. This consensus is developed by Taiwan Pancreas Society to provide an updated, evidence-based framework for managing acute pancreatitis.
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Affiliation(s)
- Wei-Chih Liao
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan; Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tien-Chien Tu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Cathay General Hospital, Taipei, Taiwan
| | - Kuei-Chuan Lee
- Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Jseng-Hwei Tseng
- Department of Imaging & Intervention, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Ming-Jen Chen
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, MacKay Memorial Hospital, Taipei, Taiwan
| | - Cheuk-Kay Sun
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
| | - Shang-Yu Wang
- Division of Trauma and Emergency Surgery, Department of Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Wei-Kuo Chang
- Division of Gastroenterology, Department of Internal Medicine, Tri-Service General Hospital, Taiwan
| | - Pi-Yi Chang
- Department of Radiology, Taichung Veterans General Hospital, Taiwan
| | - Ming-Shun Wu
- Division of Gastroenterology, Department of Internal Medicine, Wan Fang Hospital, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Tsung-Jung Lin
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei City Hospital, Ren-Ai Branch, Taipei, Taiwan
| | - Hsiang-Lin Lee
- Department of Surgery, Chung Shan Medical University Hospital, Institute of Medicine4, Chung Shan Medical University, Taichung, Taiwan
| | - Jiann-Hwa Chen
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Tzu Chi Hospital, Taipei, Taiwan
| | - Kuo-Ching Yuan
- Division of Acute Care Surgery and Trauma, Department of Surgery, Taipei Medical University Hospital, Taiwan
| | - Nai-Jen Liu
- Department of Gastroenterology and Hepatology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Hsing-Chien Wu
- Department of Internal Medicine, Taipei Hospital, Ministry of Health and Welfare, Taiwan
| | - Po-Chin Liang
- Department of Medical Imaging, National Taiwan University Hospital, Taiwan
| | - Hsiu-Po Wang
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan; Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tsann-Long Hwang
- Department of Surgery, Chang Gung Memorial Hospital, Chang Gung University, Lin-Kou, Taiwan
| | - Chia-Long Lee
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Cathay General Hospital, Taipei, Taiwan.
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14
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Colvin SD, Smith EN, Morgan DE, Porter KK. Acute pancreatitis: an update on the revised Atlanta classification. Abdom Radiol (NY) 2020; 45:1222-1231. [PMID: 31494708 DOI: 10.1007/s00261-019-02214-w] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Acute pancreatitis (AP) is the most common gastrointestinal disease resulting in hospitalization in the United States with reports of over 270,000 hospitalizations and costs up to 2.6 billion dollars per year. AP is highly variable in disease course and outcome. Established in 1992, the original Atlanta classification system aimed to categorize the wide spectrum of AP by creating consensus-based terminology for AP types, severity, and complications. Though the original system standardized terminology, certain terms and definitions (i.e. pancreatic abscess) were unclear and often misused. The 2012 revised Atlanta classification (RAC) system updated terms, clarified definitions, and incorporated the medical community's improved understanding of the physiology of AP. The resulting RAC effectively defined the morphologic types of pancreatitis, provided a more standardized system for disease severity grading, further classified the local retroperitoneal complications, and established objective measures to describe this highly variable but common disease. This review provides an update on the recent literature evaluating the RAC, discusses both the strengths and shortcomings of the RAC system (including problematic interobserver agreement), and considers improvements for future classification systems.
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Affiliation(s)
| | - Elainea N Smith
- Department of Radiology, University of Alabama at Birmingham, 619 19th Street South, Birmingham, AL, 35294, USA
| | - Desiree E Morgan
- Department of Radiology, University of Alabama at Birmingham, 619 19th Street South, Birmingham, AL, 35294, USA
| | - Kristin K Porter
- Department of Radiology, University of Alabama at Birmingham, 619 19th Street South, Birmingham, AL, 35294, USA.
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15
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Lin Q, Ji YF, Chen Y, Sun H, Yang DD, Chen AL, Chen TW, Zhang XM. Radiomics model of contrast-enhanced MRI for early prediction of acute pancreatitis severity. J Magn Reson Imaging 2020; 51:397-406. [PMID: 31132207 DOI: 10.1002/jmri.26798] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 05/09/2019] [Accepted: 05/10/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Computed tomography (CT) or MR images may cause the severity of early acute pancreatitis (AP) to be underestimated. As an innovative image analysis method, radiomics may have potential clinical value in early prediction of AP severity. PURPOSE To develop a contrast-enhanced (CE) MRI-based radiomics model for the early prediction of AP severity. STUDY TYPE Retrospective. SUBJECTS A total of 259 early AP patients were divided into two cohorts, a training cohort (99 nonsevere, 81 severe), and a validation cohort (43 nonsevere, 36 severe). FIELD STRENGTH/SEQUENCE 3.0T, T1 -weighted CE-MRI. ASSESSMENT Radiomics features were extracted from the portal venous-phase images. The "Boruta" algorithm was used for feature selection and a support vector machine model was established with optimal features. The MR severity index (MRSI), the Acute Physiology and Chronic Health Evaluation (APACHE) II, and the bedside index for severity in acute pancreatitis (BISAP) were calculated to predict the severity of AP. STATISTICAL TESTS Independent t-test, Mann-Whitney U-test, chi-square test, Fisher's exact tests, Boruta algorithm, receiver operating characteristic analysis, DeLong test. RESULTS Eleven potential features were chosen to develop the radiomics model. In the training cohort, the area under the curve (AUC) of the radiomics model, APACHE II, BISAP, and MRSI were 0.917, 0.750, 0.744, and 0.749, and the P value of AUC comparisons between the radiomics model and scoring systems were all less than 0.001. In the validation cohort, the AUC of the radiomics model, APACHE II, BISAP, and MRSI were 0.848, 0.725, 0.708, and 0.719, respectively, and the P value of AUC comparisons were 0.96 (radiomics vs. APACHE II), 0.40 (radiomics vs. BISAP), and 0.46 (radiomics vs. MRSI). DATA CONCLUSION The radiomics model had good performance in the early prediction of AP severity. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:397-406.
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Affiliation(s)
- Qiao Lin
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
- Medical Imaging and Department of Radiology, Gaoping District People's Hospital of Nanchong, Nanchong, Sichuan, China
| | - Yi-Fan Ji
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Yong Chen
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Huan Sun
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Dan-Dan Yang
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Ai-Li Chen
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Tian-Wu Chen
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Xiao Ming Zhang
- Sichuan Key Laboratory of Medical Imaging and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
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16
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Gallyamov EA, Agapov MA, Busyrev YB, Gallyamov EE, Kakotkin VV, Allakhverdieva AR. [Comparison of minimal invasive technologies for treatment of infected pancreatic necrosis]. Khirurgiia (Mosk) 2020:22-28. [PMID: 32271733 DOI: 10.17116/hirurgia202003122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
AIM the assessment of the role of minimally invasive interventional procedures in the treatment of patients with infected pancreatic necrosis and their safety, as well as comparison of the results of the most common modern minimally invasive techniques among themselves. METHODS The results of treatment of 310 patients are presented with infected destructive pancreatitis from 2013 to 2018 on the basis of the city clinical hospital named after I.V. Davydovsky. The patients were divided into three groups: in the first one (n=170) patients underwent puncture followed by drainage of necrotic foci under ultrasound and CT control, in the second (n=98) patients underwent sanation of foci completely by laparoscopic access, in the third (n=42) a series of retroperitoneoscopy was used for the same purpose. RESULTS In 114 (67.1%) cases, patients from the first group did not require further surgical intervention. The results of percutaneous drainage were successful. The average length of hospital stay in the first group was 27 days, in the second and third groups - 31 days (the ratio in the 2nd and 3rd groups was 1.03 (95% CI 0.97-1.08; p<0.05)). In the course of treatment, complications were identified in 35 (35.7%) patients in the 2nd and 17 (40.4%) patients in the 3rd group (ratio 0.88 (95% CI 0.82-0.94)). There were 22 (7.1%) deaths. The causes of death were: 1 (0.3%) of the patient had arrosive bleeding, 2 (0.7%) had duodenal fistulas, 19 (6.1%) multiple organ failure against the background of widespread retroperitoneal phlegmon. CONCLUSION The efficacy of treatment of infected pancreatic necrosis depends on the possibility of full drainage of the necrotic focus, regardless of approach. Minimally invasive techniques can reduce intraoperative trauma by reducing the wound surface, which contribute to develop systemic inflammatory response syndrome.
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Affiliation(s)
- E A Gallyamov
- Sechenov First Moscow State Medical University of the Ministry of Health of Russia, Moscow, Russia
| | - M A Agapov
- Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russia
| | - Yu B Busyrev
- Sechenov First Moscow State Medical University of the Ministry of Health of Russia, Moscow, Russia
| | - E E Gallyamov
- Federal Medical and Biological Agency of Russia, Moscow, Russia
| | - V V Kakotkin
- Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russia
| | - A R Allakhverdieva
- Sechenov First Moscow State Medical University of the Ministry of Health of Russia, Moscow, Russia
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17
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Porter KK, Zaheer A, Kamel IR, Horowitz JM, Arif-Tiwari H, Bartel TB, Bashir MR, Camacho MA, Cash BD, Chernyak V, Goldstein A, Grajo JR, Gupta S, Hindman NM, Kamaya A, McNamara MM, Carucci LR. ACR Appropriateness Criteria® Acute Pancreatitis. J Am Coll Radiol 2019; 16:S316-S330. [DOI: 10.1016/j.jacr.2019.05.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 05/14/2019] [Indexed: 12/19/2022]
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18
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Can Disturbed Liver Perfusion Revealed in p-CT on the First Day of Acute Pancreatitis Provide Information about the Expected Severity of the Disease? Gastroenterol Res Pract 2019; 2019:6590729. [PMID: 31485219 PMCID: PMC6710743 DOI: 10.1155/2019/6590729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Revised: 04/24/2019] [Accepted: 07/26/2019] [Indexed: 02/06/2023] Open
Abstract
Background The aim of the study was to evaluate the prognostic properties of perfusion parameters of liver parenchyma based on computed tomography (CT) of patients with acute pancreatitis (AP) made on the first day of onset of symptoms, to assess their usefulness in identifying patients with increased risk of the development of severe AP. Methods 79 patients with clinical symptoms and biochemical criteria indicative of AP underwent perfusion computed tomography (p-CT) within 24 hours after onset of the symptoms. Perfusion parameters in 41 people who developed a severe form of AP were compared with parameters in 38 patients in whom the course of AP was mild. Results Statistical differences in the liver perfusion parameters between the group of patients with mild and severe AP were shown. The permeability-surface area product was significantly lower, and the hepatic arterial fraction was significantly higher in the group of patients with progression of AP. Conclusions Based on the results, it seems that p-CT performed on the first day from the onset of AP is a method that, by revealing disturbances in hepatic perfusion, can help in identifying patients with increased risk of the development of severe AP.
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Kothari S, Kalinowski M, Kobeszko M, Almouradi T. Computed tomography scan imaging in diagnosing acute uncomplicated pancreatitis: Usefulness vs cost. World J Gastroenterol 2019; 25:1080-1087. [PMID: 30862996 PMCID: PMC6406186 DOI: 10.3748/wjg.v25.i9.1080] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/10/2019] [Accepted: 01/26/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Literature has suggested that imaging is over-utilized in the diagnosis of pancreatitis. If the diagnosis of acute pancreatitis (AP) is established with abdominal pain and increased serum amylase or lipase activity without systemic signs of severe disease, computed tomography (CT) imaging may not be necessary. We hypothesize that among patients with uncomplicated acute pancreatitis (AUP), there is a significant number of unwarranted CT imaging studies. This imposes increased expenditure and cost in our healthcare system and does not improve hospital stay or management of AUP.
AIM To assess the overutilization and associated cost of CT imaging among patients meeting diagnostic criteria for AUP.
METHODS In this Institutional Review Board-approved retrospective, single-center study, we identified all adult patients admitted with AP from January 1, 2012 through October 1, 2017. Patients were identified via International Classification of Diseases (ICD-9) code for AP (577.0) and ICD-10 codes for different etiological AP (K85.9 unspecified, K85.0 idiopathic, K85.1 biliary, K85.2 alcohol-induced, K85.3 drug-induced, and K85.8 other). Diagnosis was confirmed by chart review using established non-imaging diagnostic criteria (presence of typical abdominal pain and elevated lipase or amylase greater than 3 times upper limit of normal). Ranson criteria and BISAP scores on presentation were calculated and patients that met scores less than or equal to 2 for both were included to suggest AUP. The utilization and cost of imaging in these patients were recorded.
RESULTS Between January 2012 and October 2017, 1305 patients presented to the emergency department with AP, and 405 patients (31%) met our inclusion criteria for AUP (201 males, 204 females; mean age 49 years, range 18-98). Of those, 210 patients (51.85%) underwent CT imaging. One patient (0.47%) had evidence of pancreatic necrosis, one patient had cyst formation (0.47%), and the remaining 208 patients (99.05%) had either normal CT scan imaging or findings consistent with mild AP without necrosis. The average cost of CT scan imaging was $4510 with a total cost of $947056. Median length of hospitalization stay was 3 d among both groups. Combining Ranson’s Criteria and BISAP score identified AUP in our patient population with an accuracy of 99.5%.
CONCLUSION CT imaging is unnecessary when AUP is diagnosed clinically and biochemically. Reducing overuse of diagnostic CT scans will decrease healthcare expenditure and radiation exposure to patients.
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Affiliation(s)
- Shana Kothari
- Department of Internal Medicine, University of Illinois at Chicago - Advocate Christ Medical Center, Oak Lawn, IL 60453, United States
| | - Michael Kalinowski
- Department of Internal Medicine, University of Illinois at Chicago - Advocate Christ Medical Center, Oak Lawn, IL 60453, United States
| | - Matthew Kobeszko
- Department of Internal Medicine, University of Illinois at Chicago - Advocate Christ Medical Center, Oak Lawn, IL 60453, United States
| | - Tarek Almouradi
- Department of Gastroenterology, Advocate Christ Medical Center, Oak Lawn, IL 60453, United States
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20
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Choi HW, Park HJ, Choi SY, Do JH, Yoon NY, Ko A, Lee ES. Early Prediction of the Severity of Acute Pancreatitis Using Radiologic and Clinical Scoring Systems With Classification Tree Analysis. AJR Am J Roentgenol 2018; 211:1035-1043. [PMID: 30160978 DOI: 10.2214/ajr.18.19545] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2024]
Abstract
OBJECTIVE The objective of our study was to develop a decision tree model for the early prediction of the severity of acute pancreatitis (AP) using clinical and radiologic scoring systems. MATERIALS AND METHODS For this retrospective study, 192 patients with AP who underwent CT 72 hours or less after symptom onset were divided into two cohorts: a training cohort (n = 115) and a validation cohort (n = 77). Univariate analysis was performed to identify significant parameters for the prediction of severe AP in the training cohort. For early prediction of disease severity, a classification tree analysis (CTA) model was constructed using significant scoring systems shown by univariate analysis. To assess the diagnostic performance of the model, we compared the area under the ROC curve (AUC) with each selected single parameter. We also evaluated the diagnostic performance in the validation cohort. RESULTS The Acute Physiology and Chronic Health Evaluation (APACHE)-II score, bedside index for severity in acute pancreatitis (BISAP) score, extrapancreatic inflammation on CT (EPIC) score, and Balthazar grade were included in the CTA model. In the training cohort, our CTA model showed a trend of a higher AUC (0.853) than the AUC of each single parameter (APACHE-II score, 0.835; BISAP score, 0.842; EPIC score, 0.739; Balthazar grade, 0.700) (all, p > 0.0125) while achieving specificity (100%) higher than and accuracy (94.8%) comparable to each single parameter (both, p < 0.0125). In the validation cohort, the CTA model achieved diagnostic performance similar to the training cohort with an AUC of 0.833. CONCLUSION Our CTA model consisted of clinical (i.e., APACHE-II and BISAP scores) and radiologic (i.e., Balthazar grade and EPIC score) scoring systems and may be useful for the early prediction of the severity of AP and identification of high-risk patients who require close surveillance.
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Affiliation(s)
- Hye Won Choi
- 1 Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul 06973, Republic of Korea
| | - Hyun Jeong Park
- 1 Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul 06973, Republic of Korea
| | - Seo-Youn Choi
- 2 Department of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon, Republic of Korea
| | - Jae Hyuk Do
- 3 Department of Internal Medicine, College of Medicine, Chung-Ang University, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Na Young Yoon
- 4 College of Business, Korea Advanced Institute of Science and Technology, Seoul, Republic of Korea
| | - Ara Ko
- 1 Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul 06973, Republic of Korea
| | - Eun Sun Lee
- 1 Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul 06973, Republic of Korea
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The Use of International Classification of Diseases Codes to Identify Patients with Pancreatitis: A Systematic Review and Meta-analysis of Diagnostic Accuracy Studies. Clin Transl Gastroenterol 2018; 9:191. [PMID: 30287807 PMCID: PMC6172207 DOI: 10.1038/s41424-018-0060-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Accepted: 09/06/2018] [Indexed: 02/06/2023] Open
Abstract
Background Hospital discharge codes are increasingly used in gastroenterology research, but their accuracy in the setting of acute pancreatitis (AP) and chronic pancreatitis (CP), one of the most frequent digestive diseases, has never been assessed systematically. The aim was to conduct a systematic literature review and determine accuracy of diagnostic codes for AP and CP, as well as the effect of covariates. Methods Three databases (Pubmed, EMBASE and Scopus) were searched by two independent reviewers for relevant studies that used International Classification of Disease (ICD) codes. Summary estimates of sensitivity, specificity and positive predictive value were obtained from bivariate random-effects regression models. Sensitivity and subgroup analyses according to recurrence of AP and age of the study population were performed. Results A total of 24 cohorts encompassing 18,106 patients were included. The pooled estimates of sensitivity and specificity of ICD codes for AP were 0.85 and 0.96, respectively. The pooled estimates of sensitivity and specificity of ICD codes for CP were 0.75 and 0.94, respectively. The positive predictive value of ICD codes was 0.71 for either AP or CP. It increased to 0.78 when applied to incident episode of AP only. The positive predictive value decreased to 0.68 when the ICD codes were applied to paediatric patients. Conclusion Nearly three out of ten patients are misidentified as having either AP or CP with the indiscriminate use of ICD codes. Limiting the use of ICD codes to adult patients with incident episode of AP may improve identification of patients with pancreatitis in administrative databases.
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Abstract
OBJECTIVE This study aimed to develop a diagnostic model that predicts acute pancreatitis (AP) risk before imaging. METHODS Emergency department patients with serum lipase elevated to 3 times the upper limit of normal or greater were identified retrospectively (September 1, 2013-August 31, 2015). An AP diagnosis was established by expert review of full hospitalization records. Candidate predictors included demographic and clinical characteristics at presentation. Using a derivation set, a multivariable logistic regression model and corresponding point-based scoring system was developed to predict AP. Discrimination accuracy and calibration were assessed in a separate validation set. RESULTS In 319 eligible patients, 182 (57%) had AP. The final model (area under curve, 0.92) included 8 predictors: number of prior AP episodes; history of cholelithiasis; no abdominal surgery (prior 2 months); time elapsed from symptom onset; pain localized to epigastrium, of progressively worsening severity, and severity level at presentation; and extent of lipase elevation. At a diagnostic risk threshold of 8 points or higher (≥99%), the model identified AP with a sensitivity of 45%, and a specificity and a positive predictive value of 100%. CONCLUSIONS In emergency department patients with lipase elevated to 3 times the upper limit of normal or greater, this model helps identify AP risk before imaging. Prospective validation studies are needed to confirm diagnostic accuracy.
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McNabb-Baltar J, Chang MS, Suleiman SL, Banks PA, de Silva DPS. A time trend analysis of CT and MRI scan imaging in acute pancreatitis patients presenting to US emergency departments. Am J Emerg Med 2018; 36:1709-1710. [PMID: 29395766 DOI: 10.1016/j.ajem.2018.01.069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 01/22/2018] [Accepted: 01/23/2018] [Indexed: 12/12/2022] Open
Affiliation(s)
- Julia McNabb-Baltar
- Division of Gastroenterology, Hepatology, and Endoscopy, Center for Pancreatic Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Matthew S Chang
- Division of Gastroenterology, Hepatology, and Endoscopy, Center for Pancreatic Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shadeah L Suleiman
- Division of Gastroenterology, Hepatology, and Endoscopy, Center for Pancreatic Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter A Banks
- Division of Gastroenterology, Hepatology, and Endoscopy, Center for Pancreatic Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - D Punyanganie S de Silva
- Division of Gastroenterology, Hepatology, and Endoscopy, Center for Pancreatic Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Ariffin AC, Ngadiron H. Acute pancreatitis: is early CT necessary? Eur J Trauma Emerg Surg 2017; 43:883-884. [PMID: 28936579 DOI: 10.1007/s00068-017-0843-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 09/14/2017] [Indexed: 11/29/2022]
Affiliation(s)
- A C Ariffin
- Surgery Department, Universiti Sains Islam Malaysia, Tingkat 13, Persiaran MPAJ, Jalan Pandan Utama, 55100, Kuala Lumpur, Malaysia.
| | - H Ngadiron
- Emergency and Trauma Department, Universiti Sains Islam Malaysia, Jalan Pandan Utama, 55100, Kuala Lumpur, Malaysia
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Abstract
Once considered uncommon, pancreatic diseases are increasingly recognized in the pediatric age group. Acute pancreatitis, acute recurrent pancreatitis, and chronic pancreatitis occur in children with an incidence approaching that of adults. Risk factors are broad, prompting the need for a completely different diagnostic and therapeutic approach in children. Although cystic fibrosis remains the most common cause of exocrine pancreatic insufficiency, other causes such as chronic pancreatitis may be as common as Shwachman Diamond syndrome. Long-term effects of pancreatic diseases may be staggering, as children suffer from significant disease burden, high economic cost, nutritional deficiencies, pancreatogenic diabetes, and potentially pancreatic cancer.
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Affiliation(s)
- Aliye Uc
- Division of Pediatric Gastroenterology, Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, BT 1120-C, 200 Hawkins Drive, Iowa City, IA 52242, USA.
| | - Douglas S. Fishman
- Texas Children’s Hospital; Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Baylor College of Medicine
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Shi Y, Liu Y, Liu YQ, Gao F, Li JH, Li QJ, Guo QY. Early diagnosis and severity assessment of acute pancreatitis (AP) using MR elastography (MRE) with spin-echo echo-planar imaging. J Magn Reson Imaging 2017; 46:1311-1319. [PMID: 28252868 DOI: 10.1002/jmri.25679] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 02/03/2017] [Indexed: 01/21/2023] Open
Affiliation(s)
- Yu Shi
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Ying Liu
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Yan-qing Liu
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Feng Gao
- Department of Hepato-pancreato-biliary Tumour Surgery; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Jia-hui Li
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Qiu-ju Li
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
| | - Qi-yong Guo
- Department of Radiology; Shengjing Hospital of China Medical University; Shenyang P.R. China
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Gibbons EK, Le Roux P, Vasanawala SS, Pauly JM, Kerr AB. Body Diffusion Weighted Imaging Using Non-CPMG Fast Spin Echo. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:549-559. [PMID: 27810802 PMCID: PMC5492898 DOI: 10.1109/tmi.2016.2622238] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
SS-FSE is a fast technique that does not suffer from off-resonance distortions to the degree that EPI does. Unlike EPI, SS-FSE is ill-suited to diffusion weighted imaging (DWI) due to the Carr-Purcell-Meiboom-Geill (CPMG) condition. Non-CPMG phase cycling does accommodate SS-FSE and DWI but places constraints on reconstruction, which are resolved here through parallel imaging. Additionally, improved echo stability can be achieved by using short duration and highly selective DIVERSE radiofrequency pulses. Here, signal-to-noise ratio (SNR) comparisons between EPI and nCPMG SS-FSE acquisitions and reconstruction techniques give similar values. Diffusion imaging with nCPMG SS-FSE gives similar SNR to an EPI acquisition, though apparent diffusion coefficient values are higher than seen with EPI. In vivo images have good image quality with little distortion. This method has the ability to capture distortion-free DWI images near areas of significant off-resonance as well as preserve adequate SNR. Parallel imaging and DIVERSE refocusing RF pulses allow shorter ETL compared to previous implementations and thus reduces phase encode direction blur and SAR accumulation.
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29
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[Acute pancreatitis in intensive care medicine : Which risk score is useful?]. Med Klin Intensivmed Notfmed 2017; 112:717-723. [PMID: 28144728 DOI: 10.1007/s00063-017-0260-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 11/13/2016] [Accepted: 12/13/2016] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Acute pancreatitis is a disease with an increasing incidence in the Western countries associated with a high mortality depending on severity of disease. Etiology is often biliary or due to alcoholism. Incidence of etiology varies between regions depending on risk-factor prevalence. Several risk scores are available to estimate mortality. The aim of the study is to identify the risk factors most relevant for patients being treated for severe acute pancreatitis in an ICU of a tertiary medical center. PATIENTS AND METHODS The retrospective cohort study included 91 patients (61.2% men, mean age 52 years) with severe acute pancreatitis who were treated between 2002 and 2013 at the medical ICU of a tertiary medical center. Risk factors were identified using COX regression analysis and associations were assessed with the χ2 test. RESULTS Pulmonary failure necessitating ventilator support, renal failure requiring renal replacement therapy, need for vasopressor therapy, positive blood cultures, and bleeding complications were identified as risk factors for high mortality in severe acute pancreatitis. Low calcium and high lactate levels are independent risk factors for mortality. CONCLUSION Critically ill patients with severe pancreatitis have high mortality rates that can be estimated using risk scores. Weighting of risk factors may differ depending on region and severity of disease. For patients included in our study, the Ranson Criteria and the APACHE II Score may be most applicable.
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The ability of emergency physicians to diagnose and score acute pancreatitis on computed tomography. Eur J Trauma Emerg Surg 2016; 43:287-292. [PMID: 27913839 DOI: 10.1007/s00068-016-0743-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 11/15/2016] [Indexed: 10/20/2022]
Abstract
PURPOSE The aim of this study is to determine the ability of emergency physicians' (EP) interpreting contrast-enhanced computed tomographies (CECTs) performed in patients diagnosed or suspected acute pancreatitis (AP), using the modified computed tomography severity index (MCTSI) scoring system. METHODS This study was conducted in Training and Research Hospital's Emergency Department. From January 1, 2013 to April 30, 2016, patients whom performed CECT within 24 h of admission with diagnosis or suspicion of AP were reviewed retrospectively. One hundred eighteen patients were included in the study. Three-third-year EPs received education about CECT interpretation and MCTSI criteria. Each EP interpreted CECTs in a blinded manner. The EPs' performance of determining the CECTs with or without AP and scoring the CECTs with CTSI scoring system was investigated. RESULTS The agreement (weighted kappa) between the EPs and the radiologists for determining CECTs positive for AP was 0.932 (p < 0.001), 0.864 (p < 0.001) and 0.949 (p < 0.001) for EP1, EP2 and EP3, respectively. The agreement for MCTSI scores was 0.649 (p < 0.001), 0.588 (p < 0.001) and 0.734 (p < 0.001). These values showed a significant relationship between the EPs and radiologists. CONCLUSIONS EPs can diagnose the AP on CECTs and score CECTs with MCTSI scoring system correctly.
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Abstract
The goal of a diagnostic imaging examination is to provide the referring provider with an actionable imaging report that can be used to impart information to determine optimal clinical management for the patient. An actionable imaging report not only conveys the findings of the examination accurately, but does so in a timely and safe manner for an imaging examination that was performed appropriately and using the correct technique. The use of information technology tools has been paramount in improving the value of the imaging report and continues to play a prominent role in this process. The diversity of abdominal imaging, in both the variety of imaging modalities available and the organ systems evaluated, makes it well-suited to adopt these information technology solutions to improve report quality, including increased consistency in reports and in follow-up recommendations. This review discusses the components of the imaging chain involved in optimizing the imaging report with specific emphasis on the role of information technology applications to address the challenges that are frequently encountered. Specific abdominal imaging examples are presented to provide practical guidance and clinical context.
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32
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Pieńkowska J, Gwoździewicz K, Skrobisz-Balandowska K, Marek I, Kostro J, Szurowska E, Studniarek M. Perfusion-CT--Can We Predict Acute Pancreatitis Outcome within the First 24 Hours from the Onset of Symptoms? PLoS One 2016; 11:e0146965. [PMID: 26784348 PMCID: PMC4718557 DOI: 10.1371/journal.pone.0146965] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2015] [Accepted: 12/23/2015] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Severe acute pancreatitis (AP) is still a significant clinical problem which is associated with a highly mortality. The aim of this study was the evaluation of prognostic value of CT regional perfusion measurement performed on the first day of onset of symptoms of AP, in assessing the risk of developing severe form of acute pancreatitis. MATERIAL AND METHODS 79 patients with clinical symptoms and biochemical criteria indicative of acute pancreatitis (acute upper abdominal pain, elevated levels of serum amylase and lipase) underwent perfusion CT within 24 hours after onset of symptoms. The follow-up examinations were performed after 4-6 days to detect progression of the disease. Perfusion parameters were compared in 41 people who developed severe form of AP (pancreatic and/or peripancreatic tissue necrosis) with parameters in 38 consecutive patients in whom course of AP was mild. Blood flow, blood volume, mean transit time and permeability surface area product were calculated in the three anatomic pancreatic subdivisions (head, body and tail). At the same time the patient's clinical status was assessed by APACHE II score and laboratory parameters such as CRP, serum lipase and amylase, AST, ALT, GGT, ALP and bilirubin were compared. RESULTS Statistical differences in the perfusion parameters between the group of patients with mild and severe AP were shown. Blood flow, blood volume and mean transit time were significantly lower and permeability surface area product was significantly higher in patients who develop severe acute pancreatitis and presence of pancreatic and/or peripancreatic necrosis due to pancreatic ischemia. There were no statistically significant differences between the two groups in terms of evaluated on admission severity of pancreatitis assessed using APACHE II score and laboratory tests. CONCLUSIONS CT perfusion is a very useful indicator for prediction and selection patients in early stages of acute pancreatitis who are at risk of developing pancreatic and/or peripancreatic necrosis already on the first day of the onset of symptoms and can be used for treatment planning and monitoring of therapy of acute pancreatitis. Early suspicion of possible pancreatic necrosis both on the basis of scores based on clinical status and laboratory tests have low predictive value.
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Affiliation(s)
- Joanna Pieńkowska
- II Department of Radiology–Faculty of Health Sciences, Medical University of Gdansk, Gdansk, Poland
| | - Katarzyna Gwoździewicz
- I Department of Radiology–Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
- * E-mail:
| | | | - Iwona Marek
- Department of Gastroenterology and Hepatology, Medical University of Gdansk, Gdansk, Poland
| | - Justyna Kostro
- Department of General Endocrine and Transplant Surgery, Medical University of Gdansk, Gdansk, Poland
| | - Edyta Szurowska
- II Department of Radiology–Faculty of Health Sciences, Medical University of Gdansk, Gdansk, Poland
| | - Michał Studniarek
- I Department of Radiology–Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland
- Department of Diagnostic Imaging, Medical University of Warsaw, Warsaw, Poland
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Abstract
The medical treatment of acute pancreatitis continues to focus on supportive care, including fluid therapy, nutrition, and antibiotics, all of which will be critically reviewed. Pharmacologic agents that were previously studied were found to be ineffective likely due to a combination of their targets and flaws in trial design. Potential future pharmacologic agents, particularly those that target intracellular calcium signaling, as well as considerations for trial design will be discussed. As the incidence of acute pancreatitis continues to increase, greater efforts will be needed to prevent hospitalization, readmission and excessive imaging in order to reduce overall healthcare costs. Primary prevention continues to focus on post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis and secondary prevention on cholecystectomy for biliary pancreatitis as well as alcohol and smoking abstinence.
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Affiliation(s)
- Vikesh K Singh
- Pancreatitis Center, Division of Gastroenterology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Kuo DC, Rider AC, Estrada P, Kim D, Pillow MT. Acute Pancreatitis: What's the Score? J Emerg Med 2015; 48:762-70. [DOI: 10.1016/j.jemermed.2015.02.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Revised: 01/30/2015] [Accepted: 02/21/2015] [Indexed: 02/07/2023]
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