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Yang X, Park S, Lee S, Han K, Lee MR, Song JS, Yu HC, Do Yang J. Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry. Sci Rep 2023; 13:17746. [PMID: 37853228 PMCID: PMC10584880 DOI: 10.1038/s41598-023-45140-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 10/16/2023] [Indexed: 10/20/2023] Open
Abstract
This study aimed at developing a fully automatic technique for right lobe graft weight estimation using deep learning algorithms. The proposed method consists of segmentation of the full liver region from computed tomography (CT) images, classification of the entire liver region into the right and left lobes, and estimation of the right lobe graft weight from the CT-measured right lobe graft volume using a volume-to-weight conversion formula. The first two steps were performed with a transformer-based deep learning model. To train and evaluate the model, a total of 248 CT datasets (188 for training, 40 for validation, and 20 for testing and clinical evaluation) were used. The Dice similarity coefficient (DSC), mean surface distance (MSD), and the 95th percentile Hausdorff distance (HD95) were used for evaluating the segmentation accuracy of the full liver region and the right liver lobe. The correlation coefficient (CC), percentage error (PE), and percentage absolute error (PAE) were used for the clinical evaluation of the estimated right lobe graft weight. The proposed method achieved high accuracy in segmentation for DSC, MSD, and HD95 (95.9% ± 1.0%, 1.2 ± 0.4 mm, and 5.2 ± 1.9 mm for the entire liver region; 92.4% ± 2.7%, 2.0 ± 0.7 mm, and 8.8 ± 2.9 mm for the right lobe) and in clinical evaluation for CC, PE, and PAE (0.859, - 1.8% ± 9.6%, and 8.6% ± 4.7%). For the right lobe graft weight estimation, the present study underestimated the graft weight by - 1.8% on average. A mean difference of - 21.3 g (95% confidence interval: - 55.7 to 13.1, p = 0.211) between the estimated graft weight and the actual graft weight was achieved in this study. The proposed method is effective for clinical application.
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Affiliation(s)
- Xiaopeng Yang
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Seonyeong Park
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Seungyoo Lee
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Kyujin Han
- School of Global Entrepreneurship and Information Communication Technology, Handong Global University, Pohang, 37554, Republic of Korea
| | - Mi Rin Lee
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea
| | - Ji Soo Song
- Department of Radiology, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
| | - Hee Chul Yu
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea
| | - Jae Do Yang
- Department of Surgery, Jeonbuk National University Medical School and Hospital, Jeonju, 54907, Republic of Korea.
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju, 54907, Republic of Korea.
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju, 54907, Republic of Korea.
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Tamulevicius M, Oezcelik A, Koitka S, Theysohn JM, Hoyer DP, Farzaliyev F, Haubold J, Nensa F, Treckmann J, Malamutmann E. Preoperative Computed Tomography Volumetry and Graft Weight Estimation of Left Lateral Segment in Pediatric Living Donor Liver Transplant. EXP CLIN TRANSPLANT 2023; 21:831-836. [PMID: 37965959 DOI: 10.6002/ect.2023.0176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
OBJECTIVES Liver volumetry based on a computed tomography scan is widely used to estimate liver volume before any liver resection, especially before living donorliver donation. The 1-to-1 conversion rule for liver volume to liver weight has been widely adopted; however, debate continues regarding this approach. Therefore, we analyzed the relationship between the left-lateral lobe liver graft volume and actual graft weight. MATERIALS AND METHODS This study retrospectively included consecutive donors who underwent left lateral hepatectomy for pediatric living donor liver transplant from December 2008 to September 2020. All donors were healthy adults who met the evaluation criteria for pediatric living donor liver transplant and underwent a preoperative contrast-enhanced computed tomography scan. Manual segmentation of the leftlateral liverlobe for graft volume estimation and intraoperative measurement of an actual graft weight were performed. The relationship between estimated graft volume and actual graft weight was analyzed. RESULTS Ninety-four living liver donors were included in the study. The mean actual graft weight was ~283.4 ± 68.5 g, and the mean graft volume was 244.9 ± 63.86 mL. A strong correlation was shown between graft volume and actual graft weight (r = 0.804; P < .001). Bland-Altman analysis revealed an interobserver agreement of 38.0 ± 97.25, and intraclass correlation coefficient showed almost perfect agreement(r = 0.840; P < .001). The conversion formula for calculating graft weight based on computed tomography volumetry was determined based on regression analysis: 0.88 × graft volume + 41.63. CONCLUSIONS The estimation of left liver graft weight using only the 1-to-1 rule is subject to measurable variability in calculated graft weights and tends to underestimate the true graft weight. Instead, a different, improved conversion formula should be used to calculate graft weight to more accurately determine donor graft weight-to-recipient body weightratio and reduce the risk of underestimation of liver graft weightin the donor selection process before pediatric living donor liver transplant.
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Affiliation(s)
- Martynas Tamulevicius
- From the University Hospital Essen, Department of General, Visceral and Transplantation Surgery, Essen, Germany
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Kalshabay Y, Zholdybay Z, Di Martino M, Medeubekov U, Baiguissova D, Ainakulova A, Doskhanov M, Baimakhanov B. CT volume analysis in living donor liver transplantation: accuracy of three different approaches. Insights Imaging 2023; 14:82. [PMID: 37184628 DOI: 10.1186/s13244-023-01431-8] [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: 09/18/2022] [Accepted: 04/09/2023] [Indexed: 05/16/2023] Open
Abstract
OBJECTIVES The aim of this retrospective study is to compare and evaluate accuracy of three different approaches of liver volume quantification in living donor transplantations. METHODS This is a single-center, retrospective study of 60 donors. The total and right lobe liver volumes were analyzed in the portal-venous phase by two independent radiologists who estimated the volumes using manual, semi-automated and automated segmentation methods. The measured right lobe liver volume was compared to the real weight of the graft after back-table examinations. RESULTS The mean estimated overall liver volume was 1164.4 ± 137.0 mL for manual, 1277.4 ± 190.4 mL for semi-automated and 1240.1 ± 108.5 mL for automated segmentation. The mean estimated right lobe volume was 762.0 ± 122.4 mL for manual, 792.9 ± 139.9 mL for semi-automated and 765.4 ± 132.7 mL for automated segmentation. The mean graft weight was 711.2 ± 142.9 g. The manual method better correlated with the graft weight (r = 0.730) in comparison with the semi-automated (r = 0.685) and the automated (r = 0.699) methods (p < 0.001). The mean error ratio in volume estimation by each application was 12.7 ± 16.6% for manual, 17.1 ± 17.3% for semi-automated, 14.7 ± 16.8% for automated methods. There was a statistically significant difference between the mean error ratio of the manual and the semi-automated segmentations (p = 0.017), and no statistically significant difference between the manual and the automated applications (p = 0.199). CONCLUSION Volume analysis application better correlates with graft weight, but there is no obvious difference between correlation coefficients of all three methods. All three modalities had an error ratio, of which the semi-automated method showed the highest value. CRITICAL RELEVANCE STATEMENT Volume analysis application was more accurate, but there is no drastic difference between correlation coefficients of all three methods.
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Affiliation(s)
- Yerkezhan Kalshabay
- Kazakh National Medical University Named After S.D. Asfendiyarov, Almaty, Republic of Kazakhstan.
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan.
| | - Zhamilya Zholdybay
- Kazakh National Medical University Named After S.D. Asfendiyarov, Almaty, Republic of Kazakhstan
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan
| | - Michele Di Martino
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy
| | - Ulykbek Medeubekov
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan
| | - Dinara Baiguissova
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan
| | - Akmaral Ainakulova
- Kazakh National Medical University Named After S.D. Asfendiyarov, Almaty, Republic of Kazakhstan
| | - Maksat Doskhanov
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan
| | - Bolatbek Baimakhanov
- National Scientific Center of Surgery Named After A.N. Syzganov, 51 Zheltoksan Street, A05F0D2, Almaty, Republic of Kazakhstan
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Bozkurt B, Emek E, Arikan T, Ceyhan O, Yazici P, Sahin T, Mammadov E, Serin A, Gurcan NI, Yuzer Y, Tokat Y. Liver Graft Volume Estimation by Manual Volumetry and Software-Aided Interactive Volumetry: Which is Better? Transplant Proc 2019; 51:2387-2390. [DOI: 10.1016/j.transproceed.2019.01.152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 01/21/2019] [Indexed: 02/07/2023]
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Yang X, Yang JD, Lee S, Hwang HP, Ahn S, Yu HC, You H. Estimation of Standard Liver Volume Using CT Volume, Body Composition, and Abdominal Geometry Measurements. Yonsei Med J 2018; 59:546-553. [PMID: 29749138 PMCID: PMC5949297 DOI: 10.3349/ymj.2018.59.4.546] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 03/27/2018] [Indexed: 02/07/2023] Open
Abstract
PURPOSE The present study developed formulas for estimation of standard liver volume (SLV) with high accuracy for the Korean population. MATERIALS AND METHODS SLV estimation formulas were established using gender-balanced and gender-unbalanced measurements of anthropometric variables, body composition variables, and abdominal geometry of healthy Koreans (n=790). Total liver volume excluding blood volume, was measured based on CT volumetry. RESULTS SLV estimation formulas as preferred in various conditions of data availability were suggested in the present study. The suggested SLV estimation formulas in the present study were found superior to existing formulas, with an increased accuracy of 4.0-217.5 mL for absolute error and 0.2-18.7% for percentage of absolute error. CONCLUSION SLV estimation formulas using gender-balanced measurements showed better performance than those using gender-unbalanced measurements. Inclusion of body composition and abdominal geometry variables contributed to improved performance of SLV estimation.
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Affiliation(s)
- Xiaopeng Yang
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea
| | - Jae Do Yang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Seunghoon Lee
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea
| | - Hong Pil Hwang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Sungwoo Ahn
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea
| | - Hee Chul Yu
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Korea
- Research Institute for Endocrine Sciences, Chonbuk National University, Jeonju, Korea.
| | - Heecheon You
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Korea.
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Yang X, Yang JD, Yu HC, Choi Y, Yang K, Lee TB, Hwang HP, Ahn S, You H. Dr. Liver: A preoperative planning system of liver graft volumetry for living donor liver transplantation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 158:11-19. [PMID: 29544776 DOI: 10.1016/j.cmpb.2018.01.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 01/11/2018] [Accepted: 01/24/2018] [Indexed: 05/28/2023]
Abstract
BACKGROUND AND OBJECTIVE Manual tracing of the right and left liver lobes from computed tomography (CT) images for graft volumetry in preoperative surgery planning of living donor liver transplantation (LDLT) is common at most medical centers. This study aims to develop an automatic system with advanced image processing algorithms and user-friendly interfaces for liver graft volumetry and evaluate its accuracy and efficiency in comparison with a manual tracing method. METHODS The proposed system provides a sequential procedure consisting of (1) liver segmentation, (2) blood vessel segmentation, and (3) virtual liver resection for liver graft volumetry. Automatic segmentation algorithms using histogram analysis, hybrid level-set methods, and a customized region growing method were developed. User-friendly interfaces such as sequential and hierarchical user menus, context-sensitive on-screen hotkey menus, and real-time sound and visual feedback were implemented. Blood vessels were excluded from the liver for accurate liver graft volumetry. A large sphere-based interactive method was developed for dividing the liver into left and right lobes with a customized cutting plane. The proposed system was evaluated using 50 CT datasets in terms of graft weight estimation accuracy and task completion time through comparison to the manual tracing method. The accuracy of liver graft weight estimation was assessed by absolute difference (AD) and percentage of AD (%AD) between preoperatively estimated graft weight and intraoperatively measured graft weight. Intra- and inter-observer agreements of liver graft weight estimation were assessed by intraclass correlation coefficients (ICCs) using ten cases randomly selected. RESULTS The proposed system showed significantly higher accuracy and efficiency in liver graft weight estimation (AD = 21.0 ± 18.4 g; %AD = 3.1% ± 2.8%; percentage of %AD > 10% = none; task completion time = 7.3 ± 1.4 min) than the manual tracing method (AD = 70.5 ± 52.1 g; %AD = 10.2% ± 7.5%; percentage of %AD > 10% = 46%; task completion time = 37.9 ± 7.0 min). The proposed system showed slightly higher intra- and inter-observer agreements (ICC = 0.996 to 0.998) than the manual tracing method (ICC = 0.979 to 0.999). CONCLUSIONS The proposed system was proved accurate and efficient in liver graft volumetry for preoperative planning of LDLT.
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Affiliation(s)
- Xiaopeng Yang
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Jae Do Yang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Hee Chul Yu
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea.
| | - Younggeun Choi
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
| | - Kwangho Yang
- Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Tae Beom Lee
- Department of Surgery, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Hong Pil Hwang
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Sungwoo Ahn
- Department of Surgery, Chonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Chonbuk National University, Jeonju, Republic of Korea; Biomedical Research Institute of Chonbuk University Hospital, Jeonju, Republic of Korea
| | - Heecheon You
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea
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