Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study.

Kurt Li,Brendan Moloney,Alina Tudorica,Karen Y Oh,Wei Huang,Neda Jafarian,Archana Machireddy,Savannah C Partridge,Xin Li

doi:10.18383/j.tom.2019.00028

Abstract

We aimed to compare diagnostic performance in discriminating malignant and benign breast lesions between two intravoxel incoherent motion (IVIM) analysis methods for diffusion-weighted magnetic resonance imaging (DW-MRI) data and between DW- and dynamic contrast-enhanced (DCE)-MRI, and to determine if combining DW- and DCE-MRI further improves diagnostic accuracy. DW-MRI with 12 b-values and DCE-MRI were performed on 26 patients with 28 suspicious breast lesions before biopsies. The traditional biexponential fitting and a 3-b-value method were used for independent IVIM analysis of the DW-MRI data. Simulations were performed to evaluate errors in IVIM parameter estimations by the two methods across a range of signal-to-noise ratio (SNR). Pharmacokinetic modeling of DCE-MRI data was performed. Conventional radiological MRI reading yielded 86% sensitivity and 21% specificity in breast cancer diagnosis. At the same sensitivity, specificity of individual DCE- and DW-MRI markers improved to 36%–57% and that of combined DCE- or combined DW-MRI markers to 57%–71%, with DCE-MRI markers showing better diagnostic performance. The combination of DCE- and DW-MRI markers further improved specificity to 86%–93% and the improvements in diagnostic accuracy were statistically significant (P < .05) when compared with standard clinical MRI reading and most individual markers. At low breast DW-MRI SNR values (<50), like those typically seen in clinical studies, the 3-b-value approach for IVIM analysis generates markers with smaller errors and with comparable or better diagnostic performances compared with biexponential fitting. This suggests that the 3-b-value method could be an optimal IVIM-MRI method to be combined with DCE-MRI for improved diagnostic accuracy.

Highlights

High false-positive rate in breast cancer diagnosis using standard-of-care imaging methods, including mammography, ultrasonography, and magnetic resonance imaging (MRI), remains a significant healthcare problem, resulting in unnecessary biopsies of many benign lesions
diffusion-weighted magnetic resonance imaging (DW-MRI) signal-to-noise ratio (SNR) was estimated for each voxel within the lesions regions of interest (ROIs) using the multiframe method [47], in which the voxel SNR was calculated as the mean of signal intensities from images obtained with three orthogonal diffusion weightings at b = 10 s/mm2 over the standard deviation of signal intensities from the same images
The selection of the images with the lowest diffusion weighting used in this study was intended to estimate the highest possible SNR in the DW-MRI images

Summary

Introduction

High false-positive rate in breast cancer diagnosis using standard-of-care imaging methods, including mammography, ultrasonography, and magnetic resonance imaging (MRI), remains a significant healthcare problem, resulting in unnecessary biopsies of many benign lesions. The American College of Radiology (ACR) MRI Breast Imaging Reporting and Data System (BI-RADS) lexicon [1] is routinely used in standard of care for diagnosis of MRI-detected lesions. This approach mainly relies on interpretations of lesion morphology and qualitative assessment of contrast uptake and washout in the lesion [1]. It is important to improve diagnostic specificity and overall accuracy for MRI to be a valuable and widely used imaging tool for breast cancer diagnosis

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