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A Transformer-Based microvascular invasion classifier enhances prognostic stratification in HCC following radiofrequency ablation.
- Source :
-
Liver international : official journal of the International Association for the Study of the Liver [Liver Int] 2024 Apr; Vol. 44 (4), pp. 894-906. Date of Electronic Publication: 2024 Jan 23. - Publication Year :
- 2024
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Abstract
- Background & Aims: We aimed to develop a Transformer-based deep learning (DL) network for prognostic stratification in hepatocellular carcinoma (HCC) patients undergoing RFA.<br />Methods: A Swin Transformer DL network was trained to establish associations between magnetic resonance imaging (MRI) datasets and the ground truth of microvascular invasion (MVI) based on 696 surgical resection (SR) patients with solitary HCC ≤3 cm, and was validated in an external cohort (n = 180). The multiphase MRI-based DL risk outputs using an optimal threshold of .5 was employed as a MVI classifier for prognosis stratification in the RFA cohort (n = 180).<br />Results: Over 90% of all enrolled patients exhibited hepatitis B virus infection. Liver cirrhosis was significantly more prevalent in the RFA cohort compared to the SR cohort (72.2% vs. 44.1%, p < .001). The MVI risk outputs exhibited good performance (area under the curve values = .938 and .883) for predicting MVI in the training and validation cohort, respectively. The RFA patients at high risk of MVI classified by the MVI classifier demonstrated significantly lower recurrence-free survival (RFS) and overall survival rates at 1, 3 and 5 years compared to those classified as low risk (p < .001). Multivariate cox regression modelling of a-fetoprotein > 20 ng/mL [hazard ratio (HR) = 1.53; 95% confidence interval (95% CI): 1.02-2.33, p = .047], high risk of MVI (HR = 3.76; 95% CI: 2.40-5.88, p < .001) and unfavourable tumour location (HR = 2.15; 95% CI: 1.40-3.29, p = .001) yielded a c-index of .731 (bootstrapped 95% CI: .667-.778) for evaluating RFS after RFA. Among the three risk factors, MVI was the most powerful predictor for intrahepatic distance recurrence.<br />Conclusions: The proposed MVI classifier can serve as a valuable imaging biomarker for prognostic stratification in early-stage HCC patients undergoing RFA.<br /> (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)
Details
- Language :
- English
- ISSN :
- 1478-3231
- Volume :
- 44
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Liver international : official journal of the International Association for the Study of the Liver
- Publication Type :
- Academic Journal
- Accession number :
- 38263714
- Full Text :
- https://doi.org/10.1111/liv.15846