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TRV-2026-0992Certified recordPeer-reviewed

A CECT-Based 2PI System as a Novel Noninvasive Prognostic Tool for Hepatocellular Carcinoma: A Dual-Validation Study

This study aimed to develop and validate machine learning (ML) models integrating clinical parameters and the 2PI system (Pathology and Prognosis-Informed Imaging System) for predicting postoperative recurrence risk in hepatocellular carcinoma (HCC). The multicenter retrospective study included 496 patients with solitary HCC (≤ 5 cm). Surgical resection (SR) patients from the primary center constituted the training set; radiofrequency ablation (RFA) patients from the same center formed the internal test set; and…

Health · G Space — documented gain · certified 2026-09-06 · v1 · article view · machine-readable

Current reading — gain

A CECT-based 2PI imaging scoring system combined with clinical parameters enabled a Random Survival Forest model to stratify solitary HCC patients into high- and low-risk recurrence groups and predict postoperative recurrence.

What this doesn’t fix

Retrospective design limited to solitary HCC  5 cm and preliminary generalizability across resection and ablation cohorts, with performance dropping from training to external validation.

Evidence

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Truvace Impact Record TRV-2026-0992, v1: “A CECT-Based 2PI System as a Novel Noninvasive Prognostic Tool for Hepatocellular Carcinoma: A Dual-Validation Study.” Truvace, 2026-09-06. /record/TRV-2026-0992 (accessed at citation time). sha256 292826b1bec1c3fe…

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