Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: A pilot study
Purpose: High spectral and spatial resolution magnetic resonance imaging (HiSS MRI) yields information on the local environment of suspicious lesions. Previous work has demonstrated the advantages of HiSS (complete fat-suppression, improved image contrast, no required contrast agent, etc.), leading to initial investigations of water resonance lineshape for the purpose of breast lesion classification. The purpose of this study is to investigate a quantitative imaging biomarker, which characterizes non-Lorentzian components of the water resonance in HiSS MRI datasets, for computer-aided diagnosis (CADx). Methods: The inhomogeneous broadening and non-Lorentzian or “off-peak” components seen in the water resonance of proton spectra of breast HiSS images are analyzed by subtracting a Lorentzian fit from the water peak spectra and evaluating the difference spectrum or “residual.” The maxima of these residuals (referred to hereafter as “off-peak components”) tend to be larger in magnitude in malignant lesions, indicating increased broadening in malignant lesions. The authors considered only those voxels with the highest magnitude off-peak components in each lesion, with the number of selected voxels dependent on lesion size. Our voxel-based method compared the magnitudes and frequencies of off-peak components of all voxels from all lesions in a database that included 15 malignant and 8 benign lesions (yielding ∼3900 voxels) based on the lesions’ biopsy-confirmed diagnosis. Lesion classification was accomplished by comparing the average off-peak component magnitudes and frequencies in malignant and benign lesions. The area under the ROC curve (AUC) was used as a figure of merit for both the voxel-based and lesion-based methods. Results: In the voxel-based task of distinguishing voxels from malignant and benign lesions, off-peak magnitude yielded an AUC of 0.88 (95% confidence interval [0.84, 0.91]). In the lesion-based task of distinguishing malignant and benign lesions, average off-peak magnitude yielded an AUC 0.83 (95% confidence interval [0.61, 0.98]). Conclusions: These promising AUC values suggest that analysis of the water-resonance in each HiSS image voxel using “residual analysis” could have high diagnostic utility and could be used to enhance current CADx methods and allow detection of breast cancer without the need to inject contrast agents.