Assessment of bone fragility in projection images using radiomic features

Qian Cao; Nicholas Petrick; Stephanie Coquia; Kenny H. Cha; Rongping Zeng; Keith Wear; Berkman Sahiner; Qin Li

doi:10.1117/12.2581489

15 February 2021 Assessment of bone fragility in projection images using radiomic features

Qian Cao, Nicholas Petrick, Stephanie Coquia, Kenny H. Cha, Rongping Zeng, Keith Wear, Berkman Sahiner, Qin Li

Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis; 1159713 (2021) https://doi.org/10.1117/12.2581489
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

A radiomics-based model was developed to predict bone fragility based on x-ray projection images. The model was trained using ROIs of MicroCT images, in which mean von Mises stress was computed using finite element modeling. The average normalized RMSE of the estimated von Mises stress of all folds was 14.7%. The model identifies GLSZM and GLDM features as important texture features for estimating stress. This work demonstrates radiomic features from projection images can be combined with nonlinear regression techniques to predict bone fragility and may result in a more accurate projection-domain estimate than areal bone mineral density.

Conference Presentation

Citation Download Citation

Qian Cao, Nicholas Petrick, Stephanie Coquia, Kenny H. Cha, Rongping Zeng, Keith Wear, Berkman Sahiner, and Qin Li "Assessment of bone fragility in projection images using radiomic features", Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 1159713 (15 February 2021); https://doi.org/10.1117/12.2581489

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