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

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 2.3 cm³) were enrolled in the study (age 18–85 y, mean 54.2 y). T1-TSE (TR/TE = 400/10 ms) and T2-STIR imaging (TR/TE = 5000/60 ms), dynamic-contrast-enhanced MRI (DCE-MRI), apparent diffusion coefficient (ADC) (b = 0–800 s/mm²), and single-voxel MRS (10 × 10 × 10 mm³, PRESS, TR/TE = 3000 ms/135 ms) were performed by means of a 3T scanner. MRS results were accepted if the FWHM of the water peak was ⩽45 Hz. Total choline (tCho) was considered detected if the signal-to-noise ratio (SNR) of the 3.2 ppm peak 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.