Liver Transplant in Patients with Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence

• Published in: Diagnostics (Basel) Vol. 13; no. 9; p. 1663
• Main Authors: Pomohaci, Mihai Dan, Grasu, Mugur Cristian, Dumitru, Radu Lucian, Toma, Mihai, Lupescu, Ioana Gabriela
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.05.2023; MDPI
• Subjects: Algorithms; Artificial intelligence; Cancer therapies; Care and treatment; cirrhosis; Contraindications; Electronic health records; Hepatitis; hepatocarcinoma; Liver; Liver cancer; Liver cirrhosis; Liver diseases; liver transplant; liver transplantation; Liver transplants; Localization; machine learning; Medical prognosis; Patients; Practice guidelines (Medicine); Public health; Radiomics; Review; Technology application; Transplantation; Europe; deep learning; radiomics; neural networks; machine learning; liver transplant; artificial intelligence; cirrhosis; liver transplantation; hepatocarcinoma
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics13091663

Hepatocellular carcinoma is the most common primary malignant hepatic tumor and occurs most often in the setting of chronic liver disease. Liver transplantation is a curative treatment option and is an ideal solution because it solves the chronic underlying liver disorder while removing the malignant lesion. However, due to organ shortages, this treatment can only be applied to carefully selected patients according to clinical guidelines. Artificial intelligence is an emerging technology with multiple applications in medicine with a predilection for domains that work with medical imaging, like radiology. With the help of these technologies, laborious tasks can be automated, and new lesion imaging criteria can be developed based on pixel-level analysis. Our objectives are to review the developing AI applications that could be implemented to better stratify liver transplant candidates. The papers analysed applied AI for liver segmentation, evaluation of steatosis, sarcopenia assessment, lesion detection, segmentation, and characterization. A liver transplant is an optimal treatment for patients with hepatocellular carcinoma in the setting of chronic liver disease. Furthermore, AI could provide solutions for improving the management of liver transplant candidates to improve survival.