Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model
Maren M. Sjaastad Andreassen, Ana E. Rodríguez‐Soto, Christopher C. Conlin, Igor Vidić, Tyler M. Seibert, Anne M. Wallace, Somaye Zare, Joshua Kuperman, Boya Abudu, Grace S. Ahn, Michael E. Hahn, Neil P. Jerome, Agnes Østlie, Tone F. Bathen, Haydee Ojeda‐Fournier, Pål Erik Goa, Rebecca Rakow‐Penner, Anders M. Dale
Abstract
Abstract Purpose: Diffusion-weighted MRI (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between predefined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxelwise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model. Experimental Design: Patients with pathology-proven breast cancer from two datasets (n = 81 and n = 25) underwent multi-b-value DW-MRI. The three-component signal contributions C1 and C2 and their product, C1C2, and signal fractions F1, F2, and F1F2 were compared with the image defined on maximum b-value (DWImax), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (Kapp). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR80) and ROC AUC. Results: Mean FPR80 for both datasets was 0.016 [95% confidence interval (CI), 0.008–0.024] for C1C2, 0.136 (95% CI, 0.092–0.180) for C1, 0.068 (95% CI, 0.049–0.087) for C2, 0.462 (95% CI, 0.425–0.499) for F1F2, 0.832 (95% CI, 0.797–0.868) for F1, 0.176 (95% CI, 0.150–0.203) for F2, 0.159 (95% CI, 0.114–0.204) for DWImax, 0.731 (95% CI, 0.692–0.770) for ADC, and 0.684 (95% CI, 0.660–0.709) for Kapp. Mean ROC AUC for C1C2 was 0.984 (95% CI, 0.977–0.991). Conclusions: The C1C2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating predefining lesions. This novel DW-MRI method may serve as noncontrast alternative to standard-of-care dynamic contrast-enhanced MRI.