Enhancement Pattern Mapping for Detection of Hepatocellular Carcinoma in Patients with Cirrhosis

Abstract

Background and Aims: Limited methods exist to accurately characterize risk of malignant progression of liver lesions in patients undergoing surveillance for hepatocellular carcinoma (HCC). Enhancement pattern mapping (EPM) measures voxel-based root mean square deviation (RMSD) and improves the contrast-to-noise ratio (CNR) of liver lesions on standard of care imaging. This study investigates the utilization of EPM to differentiate between HCC versus benign cirrhotic tissue. Methods: Patients with liver cirrhosis undergoing MRI surveillance at a single, tertiary-care hospital were studied prospectively. Controls (n=99) were patients without lesions during surveillance or progression to HCC. Cases (n=48) were defined as patients with LI-RADS 3 and 4 lesions who developed HCC within the study period. RMSD measured with EPM was compared to the signal from MRI arterial and portovenous (PV) phases. EPM signals of liver parenchyma between cases and controls were quantitatively validated on an independent patient set using cross validation. Results: With EPM, RMSD of 0.37 was identified as a quantitative cutoff for distinguishing lesions that progress to HCC from background parenchyma on pre-diagnostic scans with an area under the curve (AUC) of 0.83 (CI: 0.73-0.94) and a sensitivity, specificity, and accuracy of 0.65, 0.97, and 0.89, respectively. At the time of diagnostic scans, a sensitivity, specificity, and accuracy of 0.79, 0.93, and 0.88 was achieved with an AUC of 0.89 (CI: 0.82-0.96). EPM RMSD signals of background parenchyma in cases and controls were similar (case EPM: 0.22 +/- 0.08, control EPM: 0.22 +/- 0.09, p=0.8). Conclusions: EPM differentiates between HCC and non-cancerous parenchyma in a surveillance population and may aid in early detection of HCC. Future directions involve applying EPM for risk stratification of indeterminate lesions.