Enhancement Pattern Mapping for Detection of Hepatocellular Carcinoma in Patients with Cirrhosis
Newsha Nikzad, David Thomas Fuentes, Millicent Roach, Tasadduk, Chowdhury, Matthew Cagley, Mohamed Badawy, Ahmed Elkhesen, Manal Hassan,, Khaled Elsayes, Laura Beretta, Eugene Jon Koay, Prasun Kumar Jalal

TL;DR
This study demonstrates that enhancement pattern mapping (EPM) using RMSD can effectively differentiate hepatocellular carcinoma from benign cirrhotic tissue on MRI, potentially enabling earlier detection and improved risk stratification.
Contribution
The paper introduces the application of EPM with RMSD as a quantitative imaging biomarker to distinguish HCC from benign tissue in cirrhotic patients, showing promising diagnostic accuracy.
Findings
EPM RMSD cutoff of 0.37 distinguishes HCC with 89% accuracy.
EPM achieves high specificity (97%) in identifying HCC.
EPM can differentiate HCC from background tissue before diagnostic scans.
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)…
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Taxonomy
TopicsLiver Disease Diagnosis and Treatment · Hepatocellular Carcinoma Treatment and Prognosis · Liver Disease and Transplantation
