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A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional
Chien-Chang Liao1, Yu-Fan Cheng1, Chun-Yen Yu1
1Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan.
Journal of Clinical Medicine
|July 9, 2022
Summary
A new scoring system integrating diffusion-weighted imaging and tumor features accurately predicts microvascular invasion (MVI) in hepatocellular carcinoma (HCC). This tool aids in assessing recurrence risk before treatment.
Area of Science:
- Hepatobiliary Imaging
- Oncologic Imaging
- Radiomics and Quantitative Imaging
Background:
- Microvascular invasion (MVI) is a critical histopathological indicator of recurrence risk in hepatocellular carcinoma (HCC).
- Accurate prediction of MVI is essential for guiding treatment decisions and improving patient outcomes in HCC management.
Purpose of the Study:
- To develop and validate a novel scoring system for predicting MVI in HCC using integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) findings.
- To assess the diagnostic performance of the developed scoring system in a cohort of HCC patients.
Main Methods:
- Retrospective analysis of 228 HCC patients with pathologically confirmed MVI who underwent resection or transplant.
- Integration of DWI and MR tumor characteristics, including tumor segment involvement, minimum apparent diffusion coefficient (ADCmin), and largest tumor diameter, into a multivariate logistic regression model.
- Model development using a right liver lobe dataset and validation using an independent left liver lobe dataset.
Main Results:
- The scoring model identified tumor segment involvement, ADCmin ≤ 0.95 × 10⁻³ mm²/s, and largest tumor diameter ≥ 3 cm as significant predictors of MVI.
- The overall cohort demonstrated high sensitivity (89.66%) and negative predictive value (84.41%) for MVI prediction.
- The validation dataset showed good performance with sensitivity of 80.64% and specificity of 70.83%.
Conclusions:
- The developed scoring system, incorporating ADCmin, tumor diameter, and segment involvement, offers a non-invasive method for predicting MVI in HCC.
- This scoring model demonstrates high sensitivity and negative predictive value, making it a valuable tool for routine functional MR in MVI assessment.
- The findings support the utility of quantitative MR imaging features in improving the preoperative risk stratification of HCC patients.
Keywords:
diffusion-weighted imagehepatocellular carcinomamicrovascular invasionpredictive scoring model
