Abstract #3745

Approach to Improving Anatomical Accuracy of Numerical Body Models Repositioned to Match Subject Posture During MRI

Douglas Brantner^1,2, Jasmine Vu^3,4, Laleh Golestani Rad^3,4, and Christopher M. Collins^1,2

¹Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, ³Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States, ⁴Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States

Synopsis

Keywords: Safety, In Silico, Numerical body position

Motivation: Use of commercial tools to reposition/pose numerical body models to match subject posture in MRI can result in significant non-anatomical distortions of the model.

Goal(s): Introduce approach to avoid non-anatomical distortions for a model in the seated position.

Approach: “Seated” versions of a body model were produced by: 1) using commercial software alone, and 2) strategically combining portions of the seated and original models offline followed by post-processing. SAR was calculated for both models in an open-bore double-donut MRI system.

Results: The Combined model avoided non-anatomical distortions seen when using the repositioning tool alone. These differences are also reflected in SAR distributions.

Impact: We introduce a method for avoiding significant non-anatomical distortions occurring in numerical body models when using commercial tools to reconfigure the posture/pose of the model. Use of this approach can also avoid related inaccuracies in calculated SAR and field distributions.

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