Liver Computed Tomographic Perfusion in the Assessment of Microvascular Invasion in Patients With Small Hepatocellular Carcinoma. Issue 4 (April 2015) - Wu, Dong; Tan, Ming; Zhou, Meiling; Sun, Huichuan; Ji, Yuan; Chen, Lingli; Chen, Gang; Zeng, Mengsu
Abstract : Objectives: Detecting microvascular invasion (mVI) in patients with hepatocellular carcinoma is a diagnostic challenge. The present study aimed to acquire a series of quantitative perfusion parameters from liver computed tomography (CT) with a 320-slice scanner in patients with small hepatocellular carcinoma (sHCC) and study its efficacy in identifying mVI. Materials and Methods: Fifty-six patients who underwent hepatic resection for sHCC (⩽3 cm) were preoperatively examined with a 320-detector row CT scanner. Histopathological analyses of liver biopsies confirmed that 18 patients had sHCC with mVI and that 38 patients had sHCC without mVI. Hepatic artery flow, portal vein flow (PVF), and perfusion index were measured in both tumor and normal liver tissues. Nonparametric receiver operating characteristic curve analysis was performed to quantify the accuracy of the perfusion CT parameters. Results: The tumor PVF (PVFtumor ), difference in PVF between tumor and liver tissue (ΔPVF), and the ΔPVF/liver PVF ratio ( r PVF) were significantly higher in sHCC with mVI than in sHCC without mVI ( P = 0.0094, P = 0.0018, and P = 0.0007, respectively; Wilcoxon signed rank test). The PVFtumor, ΔPVF, and r PVF correctly predicted mVI in 73.2% (sensitivity, 66.7%; specificity, 76.3%; cutoff, 103.8 mL per 100 mL/min), 76.8% (sensitivity, 66.7%; specificity, 81.6%; cutoff, −53.65 mL per 100 mL/min), and 83.9% (sensitivity, 77.8%; specificity, 86.8%; cutoff, −0.38) of a total of 56 patients with sHCC, respectively. Other parameters were not significantly different between the groups. Conclusions: Liver CT perfusion provides a noninvasive, quantitative method that can predict mVI in patients with sHCC through measurement of 3 perfusion parameters: PVFtumor, ΔPVF, and r PVF.