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Abstract #2327

Textural kinetics of suspicious breast lesions on ultrafast DCE-MRI as a lesion classifier

Federico Pineda1, Ty Easley1, Deepa Sheth1, Hiroyuki Abe1, Milica Medved1, and Gregory Karczmar1
1University of Chicago, Chicago, IL, United States

MRI will likely take on a greater role in breast cancer screening. However, one of the main concerns with MRI's expanded role is that it will lead to many false positives. This work aims to alleviate this problem by leveraging the advantages of ultrafast imaging of initial enhancement. Here we calculated parameters descriptive of the texture of enhancement and its changes throughout the ultrafast series. The results show that 4-D texture parameters may be useful in classifying suspicious lesions (AUC=0.75), the resulting model could have ruled out malignancy in 18% of the benign lesions analyzed, while maintaining 100% sensitivity.

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