Meeting Banner
Abstract #3442

Automated MRI fat quantification in obese patients – impact of reader experience and degree of obesity on time exposure

Nicolas Linder1,2, Alexander Schaudinn1,2, Nikita Garnov1,2, Roland Stange1,2, Kilian Solty1,2, Thomas Rakete1,2, Nora Dipper1,2, Sophia Michel1,2, Thomas Karlas2,3, Matthias Blüher2,4, Stefanie Lehmann2, Andreas Oberbach2, Rima Chakaroun4, Thomas Kahn1, and Harald Busse1

1Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany, 2Integrated Research and Treatment Center (IFB) AdiposityDiseases, Leipzig University Medical Center, Leipzig, Germany, 3Department of Internal Medicine, Neurology and Dermatology, Division of Gastroenterology and Rheumatology, Leipzig University Hospital, Leipzig, Germany, 4Department of Internal Medicine, Neurology and Dermatology, Division of Endocrinology and Nephrology, Leipzig University Hospital, Leipzig, Germany

The last decades have seen an increasing socioeconomic impact of obesity and obesity-related diseases. Noninvasive measures like subcutaneous and visceral adipose tissue (SAT, VAT) amounts and are also increasingly correlated with other, often clinical or metabolic findings as well as independent patient characteristics, even interventional complication rates. MRI fat quantification is common but manual processing is often laborious and time consuming while fully automatic segmentation is prone to errors. This work takes a custom-made semiautomatic MRI tool and prospectively analyzes the processing and interaction times for readers with different experience as well as patients from different BMI groups.

This abstract and the presentation materials are available to members only; a login is required.

Join Here