Innovations and perspectives in liver transplantation

Liver transplantation is a rapidly developing field. Advanced technologies, like AI, will improve access, outcomes, and offer more personalized care.

Global statistics and access to liver transplantation

Although liver transplantation is available in over 100 countries, many people with severe liver diseases do not have access to this therapy. The issue is not just the lack of transplant centers or donors. In the United States, for example, racial disparities, poverty, rural residency, and lack of health insurance limit access.

In 2022, more than 39.000 liver transplants were performed worldwide. The United States accounted for over 10.000 liver transplants, while Europe recorded about 9.800 transplants. Spain stands out for its donation model, with the highest deceased donor rate in the world, also fostering international collaborations such as Eurotransplant, which optimize organ distribution.

In other regions of the world, the number of transplants varies greatly, depending on several factors. While countries like Canada, Brazil, Argentina, China, and India have advanced transplant programs, liver transplant access across Africa remains extremely limited.

The liver transplant waiting list in Germany

The liver transplant waiting list in Germany has seen a slight decrease from 2019 to 2023. The most recent data from 2023 shows 1.382 individuals active on the Eurotransplant waiting list for a liver transplant, indicating a continued downward trend.

Despite the decrease in waiting list numbers, Germany's organ transplantation rates remain relatively low compared to other European countries. In 2022, the liver transplant rate was 8,9 per million population, down from 10,1 in 2019.

Indications and selection criteria

The main indications for transplantation are advanced liver diseases, liver tumors, and decompensated cirrhosis. In recent years, the rise in the incidence of hepatic steatosis and alcohol-related disorders has shifted the landscape of indications. Additionally, due to the new antiviral treatments, hepatitis C is no longer the leading cause of liver transplants.

Selection criteria are not homogeneous across different countries. In the United States, the priority for patients on the waiting list for a deceased donor liver transplant is based on the level of urgency (MELD and PELD scores have been the main tools used to prioritize patients on the waiting list). In the United Kingdom, however, since 2018, livers from deceased donors are allocated based on the expected benefit for the patient rather than urgency. Priority criteria need to be improved and standardized.

Expanding the pool of livers

Organ shortages have spurred innovative strategies:

Donors with infections (HIV, HCV): using organs from infected donors has improved access for some patients.
Machine perfusion of donor liver: techniques such as normothermic perfusion allow better preservation and evaluation of organs.
Living donors: this modality is particularly popular in Asia and provides outcomes comparable to those of deceased donors.
Liver split for pediatric liver transplantation: one strategy that appears to be helpful is to split a liver from a deceased donor into two allografts, typically with one piece transplanted into a small child and the other into an adult.

Major challenges and the role of AI

The one-year survival rate after transplantation is 94%, with an average life expectancy of around 20 years. However, major challenges remain: biliary and vascular complications (a significant cause of morbidity), immunosuppression and rejection, HCC recurrence (20% of HCC patients develop recurrences, often with a poor prognosis).

Artificial intelligence is emerging as a key tool to improve the management of liver transplantation. Here are its main applications:

Pre-transplantation: machine learning algorithms optimize donor-recipient matching and predict waiting list mortality more accurately than the MELD score
Organ quality assessment: technologies such as image analysis using neural networks enable faster and more accurate identification of liver steatosis
Post-transplant management: deep learning models help predict complications such as rejection, HCC recurrence and post-transplant diabetes, supporting personalized clinical decisions.

Liver transplantation is likely to remain the treatment of last resort for life-threatening liver disease for some years to come. The development of new treatments for severe liver disease and prevention campaigns to avoid “lifestyle disease” will probably decrease the demand for organs for transplantation. However, the discrepancy between supply and demand for donor livers is likely to persist for the foreseeable future. Important innovations could come from the use of xenotransplantation or tissue engineering.

References:

Bhat M, Rabindranath M, Chara BS, Simonetto DA. Artificial intelligence, machine learning, and deep learning in liver transplantation. J Hepatol. 2023 Jun;78(6):1216-1233. doi: 10.1016/j.jhep.2023.01.006. PMID: 37208107.
Lucey MR, Furuya KN, Foley DP. Liver Transplantation. N Engl J Med. 2023 Nov 16;389(20):1888-1900. doi: 10.1056/NEJMra2200923. PMID: 37966287.
WHO, ONT. Global Observatory on Donation and Transplantation. International report on organ donation and transplantation activities 2022. October 2023.
EDQM Council of Europe. Newsletter Transplant International figures on donation and transplantation 2022