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©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Role of intelligent/interactive qualitative and quantitative analysis-three-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation
Han Ding, Zhi-Guo Ding, Wen-Jing Xiao, Xu-Nan Mao, Qi Wang, Yi-Chi Zhang, Hao Cai, Wei Gong
Han Ding, Yi-Chi Zhang, Hao Cai, 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
Wei Gong, Department of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
Wei Gong, Shanghai Key Laboratory of Biliary Tract Disease Research, Shanghai, 200092, China
Co-first authors: Zhi-Guo Ding and Wen-Jing Xiao.
Co-corresponding authors: Hao Cai and Yi-Chi Zhang.
Author contributions: Gong W, Cai H and Zhang YC contributed to the study conception and design; Material preparation and data collection were performed by Ding H, Ding ZG and Wang Q; Data analysis was performed by Xiao WJ and Mao XN; The first draft of the manuscript was written by Ding H and all authors commented on previous versions of the manuscript; All authors read and approved the final manuscript. Ding ZG and Xiao WJ contributed equally to this work as co-first authors. The follow-up and data collection of 133 patients included in this study were all completed by Ding ZG, which is a time-consuming and difficult task. Therefore, it is reasonable to list him as a co-first author. The data analysis and figure drawing involved in this article were mostly completed by Xiao WJ. She maintained the rigorous principle and ensured data authenticity in the process of data analysis, which justifies her as a qualified co-first author. Cai H and Zhang YC contributed equally to this work as co-corresponding authors. Cai H consulted a large amount of relevant literature and designed this study together with Gong Wei and Zhang YC. The details of the study (such as primary outcomes, secondary outcomes, influencing factors, etc.) were determined by Cai H, which makes it reasonable for him to become a co-corresponding author. Zhang YC also participated in the design of the study, and as an experienced surgeon, he was mainly responsible for calculating eTLV using IQQA-3D and carrying out further amendments if necessary. In addition, he was mainly committed to revising the manuscript, which makes it reasonable for him to become a co-corresponding author.
Supported by National Natural Science Foundation of China, No. 82172628.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of Xinhua Hospital Affifiliated to Shanghai Jiao Tong University School of Medicine (No. XHEC-D-2023-076).
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: The authors have no relevant financial or non-financial interests to disclose.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at gongwei@xinhuamed.com.cn.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
https://creativecommons.org/Licenses/by-nc/4.0/ Corresponding author: Wei Gong, Doctor, MD, PhD, Doctor, Professor, Surgeon, Department of General Surgery, Xinhua Hospital, Affiliated to Shanghai Jiaotong University School of Medicine, No.1665 Kongjiang Road, Shanghai 200092, China. gongwei@xinhuamed.com.cn
Received: August 18, 2023
Peer-review started: August 18, 2023
First decision: November 3, 2023
Revised: November 10, 2023
Accepted: November 14, 2023
Article in press: November 14, 2023
Published online: November 28, 2023
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.
Core Tip: This is a retrospective study to identify benefits of intelligent/interactive qualitative and quantitative analysis-three-dimensional (IQQA-3D) liver volumetry in deceased donor liver transplantation and establish an estimation model to guide perioperative management. Patients with estimation total liver volume index (eTLVi) ≥ 1.24 have an increased risk of massive intraoperative blood loss and patients with eTLVi ≤ 0.85 or eTLVi ≥ 1.32 have an increased risk of early allograft dysfunction. To improve the overall survival of patients, we should follow the guidance of the IQQA-3D eTLVi model either for organ allocation or perioperative management.
