Abstract #1719

Validation of fully-automated whole liver segmentation for measurement of hepatic fat fraction

Neeraja Mahalingam^1,2, Dheevena M. Bachu³, Christopher D. Crabtree^4,5, Katherine M. Binzel^2,3, Alyssa Marie M. Castillo^2,3, Jeff S. Volek⁵, Yuchi Han^2,3, and Orlando P. Simonetti^2,3,4

¹Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States, ²Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States, ³College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States, ⁴Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, United States, ⁵Department of Human Sciences, The Ohio State University, Columbus, OH, United States

Synopsis

Keywords: Analysis/Processing, Liver, Fat Fraction; Segmentation

Motivation: Hepatic fat fraction (FF) can be non-invasively measured using magnetic resonance imaging (MRI) to assess non-alcoholic fatty liver disease (NAFLD). Manual region of interest placement (ROI) is time-consuming and potentially inaccurate if liver lobes are not sampled evenly.

Goal(s): The purpose of this work was to compare the FF obtained automatically and semi-automatically to those measured manually.

Approach: Liver segmentations were automatically generated and manually corrected. FF was measured using manually placed ROIs in the liver, automatically from liver segmentation without corrections, and semi-automatically from manually corrected automatic liver segmentations.

Results: FF from the three methods were strongly correlated and had excellent agreement.

Impact: Hepatic fat fraction from MRI can non-invasively stage the degree of hepatic steatosis for NAFLD evaluation. Automatic fat fraction measurement is more efficient than manual approaches, making it more suitable for clinical workflows.

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