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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