Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model

• Published in: Clinical cancer research Vol. 27; no. 4; pp. 1094 - 1104
• Main Authors: Andreassen, Maren M Sjaastad, Rodríguez-Soto, Ana E, Conlin, Christopher C, Vidić, Igor, Seibert, Tyler M, Wallace, Anne M, Zare, Somaye, Kuperman, Joshua, Abudu, Boya, Ahn, Grace S, Hahn, Michael, Jerome, Neil P, Østlie, Agnes, Bathen, Tone F, Ojeda-Fournier, Haydee, Goa, Pål Erik, Rakow-Penner, Rebecca, Dale, Anders M
• Format: Journal Article
• Language: English
• Published: United States 15-02-2021
• Subjects: Adult; Aged; Aged, 80 and over; Breast - diagnostic imaging; Breast - pathology; Breast Neoplasms - diagnosis; Breast Neoplasms - pathology; Datasets as Topic; Diagnosis, Differential; Diffusion Magnetic Resonance Imaging - methods; Feasibility Studies; Female; Humans; Image Processing, Computer-Assisted; Middle Aged; ROC Curve; Young Adult
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1078-0432.CCR-20-2017

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.
Patients with pathology-proven breast cancer from two datasets (
= 81 and
= 25) underwent multi-b-value DW-MRI. The three-component signal contributions
and
and their product,
, and signal fractions
,
, and
were compared with the image defined on maximum b-value (
), conventional apparent diffusion coefficient (
), and apparent diffusion kurtosis (
). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR
) and ROC AUC.
Mean FPR
for both datasets was 0.016 [95% confidence interval (CI), 0.008-0.024] for
, 0.136 (95% CI, 0.092-0.180) for
, 0.068 (95% CI, 0.049-0.087) for
, 0.462 (95% CI, 0.425-0.499) for
, 0.832 (95% CI, 0.797-0.868) for
, 0.176 (95% CI, 0.150-0.203) for
, 0.159 (95% CI, 0.114-0.204) for
, 0.731 (95% CI, 0.692-0.770) for
, and 0.684 (95% CI, 0.660-0.709) for
. Mean ROC AUC for
was 0.984 (95% CI, 0.977-0.991).
The
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.