A Pre-TACE Radiomics Model to Predict HCC Progression and Recurrence in Liver Transplantation: A Pilot Study on a Novel Biomarker. Issue 11 (November 2021)

• Record Type: Journal Article
• Authors: Ivanics, Tommy; Salinas-Miranda, Emmanuel; Abreu, Phillipe; Khalvati, Farzad; Namdar, Khashayar; Dong, Xin; Deniffel, Dominik; Gorgen, Andre; Erdman, Lauren; Jhaveri, Kartik; Haider, Masoom; Veit-Haibach, Patrick; Sapisochin, Gonzalo
• Is Part Of: Transplantation. Volume 105:Issue 11(2021)
• Publication Date: 2021-11
• Subjects: Transplantation of organs, tissues, etc -- Periodicals; Transplantation immunology -- Periodicals; 617.95
• DOI: 10.1097/TP.0000000000003605
• Languages: English
• ISSNs: 0041-1337

Abstract

Abstract : Background: Despite transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC), a significant number of patients will develop progression on the liver transplant (LT) waiting list or disease recurrence post-LT. We sought to evaluate the feasibility of a pre-TACE radiomics model, an imaging-based tool to predict these adverse outcomes. Methods: We analyzed the pre-TACE computed tomography images of patients waiting for a LT. The primary endpoint was a combined event that included waitlist dropout for tumor progression or tumor recurrence post-LT. The radiomic features were extracted from the largest HCC volume from the arterial and portal venous phase. A third set of features was created, combining the features from these 2 contrast phases. We applied a least absolute shrinkage and selection operator feature selection method and a support vector machine classifier. Three prognostic models were built using each feature set. The models' performance was compared using 5-fold cross-validated area under the receiver operating characteristic curves. Results: . Eighty-eight patients were included, of whom 33 experienced the combined event (37.5%). The median time to dropout was 5.6 mo (interquartile range: 3.6–9.3), and the median time for post-LT recurrence was 19.2 mo (interquartile range: 6.1–34.0). Twenty-four patients (27.3%) dropped out and 64 (72.7%) patients were transplanted. Of these, 14 (21.9%) had recurrence post-LT. Model performance yielded a mean area under the receiver operating characteristic curves of 0.70 (±0.07), 0.87 (±0.06), and 0.81 (±0.06) for the arterial, venous, and the combined models, respectively. Conclusions: A pre-TACE radiomics model for HCC patients undergoing LT may be a useful tool for outcome prediction. Further external model validation with a larger sample size is required. Abstract : Supplemental Digital Content is available in the text.