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Abstract #3152

Evaluating Spatial Heterogeneity for Liver PDFF and R2* using Radiomics Features

Marjola Thanaj1, Nicolas Basty1, Ramprakash Srinivasan2, Madeleine Cule2, Elena Sorokin2, Jimmy Bell1, Elizabeth Louise Thomas1, and Brandon Witcher1
1Life Sciences, University of Westminster, London, United Kingdom, 2Calico Life Sciences LLC, South San Francisco, CA, United States

Synopsis

Keywords: Liver, Data Analysis, PDFF, R2*MRI measures specific to the liver such as proton density fat fraction (PDFF) and R2* are proven biomarkers for assessing hepatic fat and iron content. There is an interest in using radiomics to extract additional information relating to spatial heterogeneity from images and apply these to clinical data. Here, we extracted radiomics features from liver PDFF and R2* and selected reproducible features and features that provide independent information to that derived from median liver PDFF and R2*. Additionally, we show that most radiomics features are negatively correlated with age and positively correlated with body mass index (BMI).

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Keywords