The influence of the middle hepatic vein and its impact on outcomes in right lobe living donor liver transplantation

AI-Based 3D Liver Segmentation and Volumetric Analysis in Living Donor Data

This study investigated the application of deep learning for 3-dimensional (3D) liver segmentation and volumetric analysis in living donor liver transplantation. Using abdominal computed tomography data from 55 donors, this study aimed to evaluate the liver segmentation performance of various U-Net-based models, including 3D U-Net, RU-Net, DU-Net, and RDU-Net, before and after hepatectomy. Accurate liver volume measurement is critical in liver transplantation to ensure adequate functional recovery and minimize postoperative complications. The models were trained and validated using a fivefold cross-validation approach. Performance metrics such as Dice similarity coefficient (DSC), recall, specificity, precision, and accuracy were used to assess the segmentation results. The highest segmentation accuracy was achieved in preoperative images with a DSC of 95.73 ± 1.08%, while postoperative day 7 images showed the lowest performance with a DSC of 93.14 ± 2.10%. A volumetric analysis conducted to measure hepatic resection and regeneration rates revealed an average liver resection rate of 40.52 ± 8.89% and a regeneration rate of 13.50 ± 8.95% by postoperative day 63. A regression analysis was performed on the volumetric results of the artificial intelligence model's liver resection rate and regeneration rate, and all results were statistically significant at p < 0.0001. The results indicate high reliability and clinical applicability of deep learning models in accurately measuring liver volume and assessing regenerative capacity, thus enhancing the management and recovery of liver donors.

Prediction and management of small-for-size syndrome in living donor liver transplantation

Small-for-size syndrome (SFSS) remains a critical challenge in living donor liver transplantation (LDLT), characterized by graft insufficiency due to inadequate liver volume, leading to significant postoperative morbidity and mortality. As the global adoption of LDLT increases, the ability to predict and manage SFSS has become paramount in optimizing recipient outcomes. This review provides a comprehensive examination of the pathophysiology, risk factors, and strategies for managing SFSS across the pre-, intra-, and postoperative phases. The pathophysiology of SFSS has evolved from being solely volume-based to incorporating portal hemodynamics, now recognized as small-for-flow syndrome. Key risk factors include donor-related parameters like age and graft volume, recipient-related factors such as MELD score and portal hypertension, and intraoperative factors related to venous outflow and portal inflow modulation. Current strategies to mitigate SFSS include careful graft selection based on graft-to-recipient weight ratio and liver volumetry, surgical techniques to optimize portal hemodynamics, and novel interventions such as splenic artery ligation and hemiportocaval shunts. Pharmacological agents like somatostatin and terlipressin have also shown promise in modulating portal pressure. Advances in 3D imaging and artificial intelligence-based volumetry further aid in preoperative planning. This review emphasizes the importance of a multifaceted approach to prevent and manage SFSS, advocating for standardized definitions and grading systems. Through an integrated approach to surgical techniques, hemodynamic monitoring, and perioperative management, significant strides can be made in improving the outcomes of LDLT recipients. Further research is necessary to refine these strategies and expand the application of LDLT, especially in challenging cases involving small-for-size grafts.

Technical challenges in LDLT - Overcoming small for size syndrome and venous outflow reconstruction

Living Donor Liver Transplantation (LDLT) emerged as an alternative treatment option for patients with end-stage liver disease waiting for an organ from a deceased donor. In addition to allowing for a faster access to transplantation, LDLT provides improved recipient outcomes when compared to deceased donor LT. However, it represents a more complex and demanding procedure for the transplant surgeon. In addition to a comprehensive preoperative donor assessment and stringent technical considerations during the donor hepatectomy to ensure upmost donor safety, the recipient procedure also comes with intrinsic challenges during LDLT. A proper approach during both procedures will result in favorable donor and recipient's outcomes. Hence, it is critical for the transplant surgeon to know how to overcome such technical challenges and avoid deleterious complications. One of the most feared complications following LDLT is small-for-size syndrome (SFSS). Although, surgical advances and deeper understanding of the pathophysiology behind SFSS has allowed for a safer implementation of LDLT, there is currently no consensus on the best strategy to prevent or manage this complication. Therefore, we aim to review current practices in technically challenging situations during LDLT, with a particular focus on management of small grafts and venous outflow reconstructions, as they possess one of the biggest technical challenges faced during LDLT.

Textbook outcome among voluntary donors undergoing major living donor hepatectomy

PURPOSE

Textbook outcome (TO) is a composite measure of outcome and provides superior assessment of quality of care after surgery. TO after major living donor hepatectomy (MLDH) has not been assessed. The objective of this study was to determine the rate of TO and its associated factors, after MLDH.

METHODS

This was a single center retrospective review of living liver donors who underwent MLDH between 2012 and 2021 (n = 1022). The rate of TO and its associated factors was determined.

RESULTS

Among 1022 living donors (of whom 693 [67.8%] were males, median age 26 [range, 18-54] years), TO was achieved in 714 (69.9%) with no donor mortality. Majority of donors met the cutoffs for individual outcome measures: 908 (88.8%) for no major complications, 904 (88.5%) for ICU stay ≤ 2 days, 900 (88.1%) for hospital stay ≤ 10 days, 990 (96.9%) for no perioperative blood transfusion, 1004 (98.2%) for no 30-day re-admission, and 1014 (99.2%) for no post-hepatectomy liver failure. Early donation era (before streamlining of donor operative pathways) was associated with failure to achieve TO [OR 1.4, CI 1.1-1.9, P = 0.006]. TO was achieved in 506/755 (67%) donors in the early donation era versus 208/267 (77.9%) in the later period (P = 0.001).

CONCLUSION

Despite zero mortality and low complication rate, TO was achieved in approximately 70% donors. TO was modifiable and improved with changes in donor operative pathway.

Living donor hepatectomy in medium volume liver transplant centre has comparable outcomes to high volume centres: validation of donabedian quality assurance framework

BACKGROUND

Given the complexity of living donor hepatectomy, it is expected that high hospital volume will better outcomes. This study aims to evaluate post-operative outcomes for living donor hepatectomy in a medium volume liver transplant centre and compare to outcomes in high volume centres. Also, it serves as a validation tool for framework of structure-process-outcome model for safe living donor hepatectomy program.

METHODS

204 donors who underwent donor hepatectomy between June 1996 to September 2019 were reviewed retrospectively and compared to outcomes in high volume centres.

RESULTS

At 6 months, overall donor morbidity rate was 20/204 (9.8%). Wound complications were most common at 5/204 (2.5%). Majority of complications were either Clavien grade 1 or 2 and only 3 donors had Clavien grade 3 complications. There was zero donor mortality.

DISCUSSION

Our centre's donor morbidity rate of 9.8% is the one of the lowest reported in the published literature. With increased experience, stringent donor selection and enhanced perioperative care by a multi-disciplinary team, outcomes in a medium volume centre can match the outcomes reported in high volume centres. The framework for quality in terms of structure, process and outcomes is presented which can be adopted for developing programs.

Evaluation of Adult Living Donor Liver Transplantation in Largest Southeast Asian Transplantation Center: Benchmarking With Adult-to-Adult Living Donor Liver Transplantation (A2ALL) Experience

BACKGROUND

The volume-outcome relation for complex surgical procedures such as living donor liver transplantation (LDLT) generally favors high volume (HV) centers. It is important for low to medium volume (MV) centers to evaluate their centers' performance against HV centers to allow early detection and correction of potential systemic issues. There is a dearth of national and international comprehensive registries for LDLT that may allow reasonable risk-adjusted comparisons for benchmarking. This study aims to evaluate the LDLT program by comparing our center's performance against HV centers of the Adult-to-Adult Living Donor Liver Transplantation cohort.

STUDY DESIGN

Patient outcomes from a MV transplant center were compared with 11 HV transplant centers from the Adult-to-Adult Living Donor Liver Transplantation cohort. Outcomes evaluated included length of hospital stay, same admission mortality, 90-day mortality, and overall survival.

RESULTS

A total of 1381 patients were analzyed. HV 1 to 4, 6, 8, 9, and 11 centers had a shorter median length of hospital stay compared with the MV center (All Dunnett corrected P values all less than .05). HV 9 and 11 centers had lower same admission mortality compared with the MV center (Dunnett corrected P = .023 and .015). After adjusting for other significant predictors, the MV center had comparable 90-day mortality rates and overall survival rates to all HV centers.

CONCLUSION

This benchmarking exercise has demonstrated that the limitation of low institutional case volume can be overcome with a protocol-based framework to implement a safe LDLT program. This framework presented can be adopted for developing programs.