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September 17, 2025Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition0 citations

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

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NMNeeraja MahalingamDBDheevena BachuCCChristopher Crabtree

Key Points

  • Hepatic fat fraction measurement from automated liver segmentation shows strong correlation with manual methods.
  • Results indicate excellent agreement in hepatic fat fraction across automated, semi-automated, and manual approaches.
  • Automatic measurement of hepatic fat fraction enhances efficiency compared to traditional manual methods for liver assessment.
  • This method supports non-invasive evaluation of hepatic steatosis in non-alcoholic fatty liver disease patients.

Abstract

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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Cite This Study

Mahalingam et al. (2025) studied this question.

synapsesocial.com/papers/68d4597031b076d99fa5c7efhttps://doi.org/10.58530/2025/1719
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