Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities

doi:10.4251/wjgo.v14.i4.765

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Apr 15, 2022 (publication date) through Mar 2, 2026

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World Journal of Gastrointestinal Oncology

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World J Gastrointest Oncol. Apr 15, 2022; 14(4): 765-793
Published online Apr 15, 2022. doi: 10.4251/wjgo.v14.i4.765

Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities

Chrysanthos D Christou, Georgios Tsoulfas

Chrysanthos D Christou, Georgios Tsoulfas, Department of Transplantation Surgery, Hippokration General Hospital, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki 54622, Greece

Author contributions: Christou CD performed the screening of articles for eligibility and drafted the manuscript; Tsoulfas G performed the screening of articles for eligibility and edited the manuscript.

Conflict-of-interest statement: The authors declare no conflict of interest for this article. The authors received no specific funding for this work.

Corresponding author: Georgios Tsoulfas, MD, PhD, Associate Professor, Surgeon, Department of Transplantation Surgery, Hippokration General Hospital, School of Medicine, Aristotle University of Thessaloniki, 49 Konstantinoupoleos Street, Thessaloniki 54622, Greece. tsoulfasg@gmail.com

Received: April 15, 2021
Peer-review started: April 15, 2021
First decision: June 4, 2021
Revised: August 24, 2021
Accepted: March 25, 2022
Article in press: March 25, 2022
Published online: April 15, 2022
Processing time: 364 Days and 13.5 Hours

Core Tip

Core Tip: The opportunities that arise from the application of three-dimensional (3D) printing and 3D bioprinting in the management of hepatocellular carcinoma (HCC) include resident education, patient education, preoperative planning, fabrication of custom-made medical tools, liver models for antitumor drug development, and patient-derived HCC models for targeted treatment selection. Similarly, the opportunities that arise from the application of artificial intelligence/machine learning in the management of HCC include targeted screening for patients with chronic hepatitis B and C infections, non-invasive early detection of HCC, increased diagnostic accuracy, frameworks for evidence-based, individualized treatment allocation, and prognostic models for the prediction of patient outcomes including overall survival, disease-free survival, and recurrence that could be used for patient and family counseling.