3 years ago

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma using Quantitative Image Analysis

Microvascular invasion (MVI) is a significant risk factor for early recurrence after resection or transplantation for hepatocellular carcinoma (HCC). Knowledge of MVI status would help guide treatment recommendations but is generally identified after surgery. This study aims to predict MVI preoperatively using quantitative image analysis. Study Design From 2 institutions, 120 patients submitted to resection of HCC from 2003 to 2015 were included. The largest tumor from preoperative CT was subjected to quantitative image analysis, which uses an automated computer algorithm to capture regional variation in CT enhancement patterns. Quantitative imaging features by automatic analysis, qualitative radiographic descriptors by 2 radiologists, and preoperative clinical variables were included in multivariate analysis to predict histologic MVI. Results Histologic MVI was identified in 19 (37%) patients with tumors ≤ 5 cm and 34 (49%) patients with tumors > 5 cm. Among patients with ≤ 5 cm tumors, none of clinical findings or radiographic descriptors was associated with MVI; however, quantitative feature based on angle co-occurrence matrix predicted MVI with area under curve (AUC) 0.80, positive predictive value (PPV) 63% and negative predictive value (NPV) 85%. In patients with > 5 cm tumors, higher α-fetoprotein (AFP) level, larger tumor size, and viral hepatitis history were associated with MVI, whereas radiographic descriptors did not. However, a multivariate model combining AFP, tumor size, hepatitis status, and quantitative feature based on local binary pattern predicted MVI with AUC 0.88, PPV 72% and NPV 96%. Conclusions This study reveals the potential importance of quantitative image analysis as a predictor of MVI.

Publisher URL: www.sciencedirect.com/science

DOI: S1072751517319658

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