Time to Enhancement Measured From Ultrafast Dynamic Contrast-Enhanced MRI for Improved Breast Lesion Diagnosis.

Journal: Journal Of Breast Imaging
Published:
Abstract

Objective: Breast MRI affords high sensitivity with intermediate specificity for cancer detection. Ultrafast dynamic contrast-enhanced (DCE) MRI assesses early contrast inflow with potential to supplement or replace conventional DCE-MRI kinetic features. We sought to determine whether radiologist's evaluation of ultrafast DCE-MRI can increase specificity of a clinical MRI protocol.

Methods: In this IRB-approved, HIPAA-compliant study, breast MRIs from March 2019 to August 2020 with a BI-RADS category 3, 4, or 5 lesion were identified. Ultrafast DCE-MRI was acquired during the first 40 seconds after contrast injection and before conventional DCE-MRI postcontrast acquisitions in the clinical breast MRI protocol. Three radiologists masked to outcomes retrospectively determined lesion time to enhancement (TTE) on ultrafast DCE-MRI. Interreader agreement, differences between benign and malignant lesion TTE, and TTE diagnostic performance were evaluated.

Results: Ninety-five lesions (20 malignant, 75 benign) were included. Interreader agreement in TTE was moderate to substantial for both ultrafast source images and subtraction maximum intensity projections (overall κ = 0.63). Time to enhancement was greater across benign lesions compared with malignancies (P <.05), and all lesions demonstrating no enhancement during the ultrafast series were benign. With a threshold TTE ≥40 seconds, ultrafast DCE-MRI yielded an average 40% specificity (95% CI, 30%-48%) and 92% sensitivity (95% CI, 81%-100%), yielding a potential reduction in 31% (95% CI, 23%-39%) of benign follow-ups based on conventional DCE-MRI.

Conclusions: Ultrafast imaging can be added to conventional DCE-MRI to increase diagnostic accuracy while adding minimal scan time. Future work to standardize evaluation criteria may improve interreader agreement and allow for more robust ultrafast DCE-MRI assessment.

Authors
Yun Chen, Anum Kazerouni, Matthew Phelps, Daniel Hippe, Inyoung Youn, Janie Lee, Savannah Partridge, Habib Rahbar
Relevant Conditions

Breast Cancer