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Abstract #4314

DWI for Improving Diagnostic Performance of Breast MRI: Impact of Alternate Apparent Diffusion Coefficient Quantitation and Cutoff Approaches

Debosmita Biswas1, Daniel Hippe2, Andrea Winter1, Habib Rahbar3, and Savannah C Partridge1,4
1Radiology, University of Washington, Seattle, WA, United States, 2Clinical research Division, Fred Hutchison Cancer Center, Seattle, WA, United States, 3Department of Radiology, University of Washington, Seattle, WA, United States, 4Bioengineering, University of Washington, Seattle, WA, United States

Synopsis

Keywords: Breast, Screening, ADC, breast cancer, biopsy reduction

Motivation: Apparent Diffusion Coefficient (ADC) measures can help reduce false positives in breast MRI.

Goal(s): Explore different approaches for measuring lesion ADC that emphasize different aspects of tumor microenvironment and biology and their effect on reducing unnecessary biopsies.

Approach: Nine ADC measures were computed for each lesion using different b value combinations and segmentation techniques. Different approaches of selecting ADC threshold were explored to reduce unnecessary biopsies.

Results: Applying ADC cutoffs, the largest reduction of benign biopsies (~20%) was achieved using ADC0-800 mapping and the 2D lesion segmentation technique, with the hotspot ROI measurement providing very similar performance.

Impact: This study demonstrates that a variety of ADC measurement techniques can help reduce unnecessary biopsies of breast MRI, suggesting that the easiest approach of segmenting the darkest pixels in the lesion might facilitate integration of DWI into the clinical workflow.

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