Abstract #0188

Predicting TP53 mutational status of breast cancers on clinical DCE MRI using directional-gradient based radiogenomic descriptors

Nathaniel Braman¹, Prateek Prasanna¹, Donna Plecha², Hannah Gilmore², Lyndsay Harris², Kristy Miskimen¹, Tao Wan³, Vinay Varadan¹, and Anant Madabhushi¹

¹Case Western Reserve University, Cleveland, OH, United States, ²University Hospitals, Cleveland, OH, United States, ³Beihang University, Beijing, China, People's Republic of

In this work, we report preliminary success in the prediction of TP53 mutational status in breast cancer from DCE-MRI using a computer-extracted radiogenomic descriptor of multi-scale disorder, Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe). A set of 8 distinguishing CoLlAGe features yielded accuracy of 78% in predicting TP53 mutational status and outperformed standard DCE-MRI pharmacokinetic parameters in an unsupervised hierarchical clustering. A non-invasive means of discerning TP53 mutational status may allow clinicians to more easily determine prognosis, assess treatment response, and inform treatment strategy.

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