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Abstract #3886

Optimization of Quantitative MRI Background Parenchymal Enhancement Metrics to Predict Breast Cancer Risk

Cheng-Liang Liu 1 , Savannah C Partridge 1 , Diana L Lam 1 , Constance D Lehman 1 , and Habib Rahbar 1

1 Department of Radiology, University of Washington, Seattle, Washington, United States

Background parenchymal enhancement (BPE) on MRI has been proposed to be a biomarker of breast cancer risk. We sought to develop an optimal method to measure BPE quantitatively for breast cancer risk assessment. By measuring various BPE metrics at enhancement thresholds ranging from 5-100% in a case-control (n=36), we found that quantitative BPE measures are higher in women who developed breast cancer than in controls, with a 70% enhancement threshold for BPE area providing the highest accuracy for predicting risk. Our findings suggest quantitative BPE measures can assess breast cancer risk, potentially allowing individualized screening and prevention strategies.

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