Sim JZT, Hui TCH, Chuah TK, Low HM, Tan CH, Shelat VG. Efficacy of texture analysis of pre-operative magnetic resonance imaging in predicting microvascular invasion in hepatocellular carcinoma. World J Clin Oncol 2022; 13(11): 918-928 [PMID: 36483976 DOI: 10.5306/wjco.v13.i11.918]
Corresponding Author of This Article
Jordan Zheng Ting Sim, MBBS, Doctor, Department of Diagnostic Radiology, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Tan Tock Seng Hospital, Singapore 308433, Singapore. jordansim92@gmail.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Retrospective Cohort Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Oncol. Nov 24, 2022; 13(11): 918-928 Published online Nov 24, 2022. doi: 10.5306/wjco.v13.i11.918
Efficacy of texture analysis of pre-operative magnetic resonance imaging in predicting microvascular invasion in hepatocellular carcinoma
Jordan Zheng Ting Sim, Terrence Chi Hong Hui, Tong Kuan Chuah, Hsien Min Low, Cher Heng Tan, Vishal G Shelat
Jordan Zheng Ting Sim, Terrence Chi Hong Hui, Hsien Min Low, Cher Heng Tan, Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
Tong Kuan Chuah, School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore
Cher Heng Tan, Vishal G Shelat, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
Vishal G Shelat, Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
Author contributions: Sim JZT contributed to drafting of manuscript, critical revision; Hui TCH contributed to acquisition of data, analysis and interpretation of data; Chuah TK contributed to acquisition of data, analysis and interpretation of data; Low HM, Shelat VG, and Tan CH contributed to study conception and design, critical revision.
Institutional review board statement: IRB was obtained, the requirement to obtain written consent was waived.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: All the Authors have no conflict of interest related to the manuscript.
Data sharing statement: Not applicable.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jordan Zheng Ting Sim, MBBS, Doctor, Department of Diagnostic Radiology, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Tan Tock Seng Hospital, Singapore 308433, Singapore. jordansim92@gmail.com
Received: September 19, 2022 Peer-review started: September 19, 2022 First decision: October 13, 2022 Revised: October 13, 2022 Accepted: November 4, 2022 Article in press: November 4, 2022 Published online: November 24, 2022 Processing time: 62 Days and 21.5 Hours
ARTICLE HIGHLIGHTS
Research background
Presence of microvascular invasion (MVI) indicates poorer prognosis post-curative resection of hepatocellular carcinoma (HCC), with an increased chance of tumour recurrence. By present standards, MVI can only be diagnosed post-operatively on histopathology.
Research motivation
Texture analysis potentially allows identification of patients who are considered ‘high risk’ through analysis of pre-operative magnetic resonance imaging (MRI) studies. These findings may or may not be readily apparent to the human eye, thus the need for an analytic software. This will in turn allow for better patient selection, improved individualised therapy (such as extended surgical margins or adjuvant therapy) and pre-operative prognostication.
Research objectives
To evaluate the accuracy of texture analysis on pre-operative MRI in predicting MVI in HCC.
Research methods
We recruited patients who underwent hepatectomy. Both qualitative (performed by radiologists) and quantitative data (performed by software) were obtained. Radiomics texture parameters were extracted based on the largest cross-sectional area of each tumor and analysed using MaZda software. Final histology of the tumour was used as ground truth.
Research results
Texture analysis of tumours on pre-operative MRI can predict presence of MVI in HCC with accuracies of up to 87.8%.
Research conclusions
Texture analysis of HCC performed on pre-operative MR images can accurately predict the presence of MVI with an accuracy of up to 87.8%. It has potential to be incorporated into clinical routine as a reliable tool for making pre-operative treatment decisions. Larger studies should be performed to validate the texture parameters and its value over qualitative visual analysis.
Research perspectives
This study demonstrates the utility of texture analysis on pre-operative MRI to potentially impact clinical management in patients with surgically resectable hepatocellular carcinoma.
