High-field MR spectroscopy in the multiparametric MRI evaluation of breast lesions

Abstract

Introduction: The aim of this work was to assess the role of 3T-MR spectroscopy (MRS) in the multi-parametric MRI evaluation of breast lesions, using a pattern-recognition based classification method.

Methods: 291 patients (301 lesions, median 2.3cm³) were enrolled in the study (age 18-85y, mean 54.2y). T1-TSE (TR/TE=400/10ms) and T2-STIR imaging (TR/TE=5000/60ms), dynamic-contrast-enhanced MRI (DCE-MRI), apparent diffusion coefficient (ADC) (b=0-800s/mm²), and single-voxel MRS (10×10×10mm³, PRESS, TR/TE=3000ms/135ms) were performed by means of a 3T scanner. MRS results were accepted if the FWHM of the water peak was ⩽45Hz. Total choline (tCho) was considered detected if the signal-to-noise ratio (SNR) of the 3.2ppmpeak was ⩾2. A classifier-based analysis (support-vector-machines, SVM) was performed with 4-dimensional vectors including type of margin, DCE-MRI kinetic curve type, ADC mean value, and tCho SNR. A comparison with 3-dimensional vectors (without tCho SNR) was used to assess MRS impact on sensitivity, specificity, and positive-negative predictive values (PPV-NPV) for malignancy.

Results: 228 lesions (180 malignant/48 benign) showed acceptable spectral quality. Comparison of classification results with histopathological examination of surgical specimens showed sensitivity=93.7%, specificity=84.9%, PPV=95.2%, NPV=81.5% without the inclusion of MRS in the SVM analysis. When MRS was included, the figures increased to 95.1%, 90.7%, 97.2%, and 85.0%, respectively.

Conclusions: Inclusion of 3T-MRS in the multi-parametric MRI evaluation of breast lesions improved the performance of the SVM-based classifier, showing a possible role of high-field MR spectroscopy in the differential diagnosis between benign and malignant breast lesions. Further research is however needed to confirm this initial evidence.

Keywords: Breast imaging; Diffusion weighted imaging; MR spectroscopy; Multi-parametric MRI.