S Mussurakis1, P Gibbs, A Horsman. 1. Centre for MR Investigations, University of Hull, Hull Royal Infirmary, England.
Abstract
PURPOSE: The purpose of our study was to determine if quantitative analysis of peripheral enhancement and spatial contrast uptake heterogeneity is useful in the characterisation of abnormalities seen at breast MRI. METHOD: Ninety-one women underwent dynamic gadolinium-enhanced breast MRI. Regions of interest were processed by a parallel thinning algorithm to define central and peripheral subregions of lesions. Peripheral enhancement was quantified at every time point of the dynamic sequence as a signal difference-to-noise ratio. Moreover, a radiologist assessed the images for the presence of peripheral enhancement and classified the regional and subregional time-intensity profiles of each lesion. RESULTS: Sixty-four invasive carcinomas and 30 benign lesions were analysed. Significant differences were found between benign and malignant lesions in peripheral enhancement as determined from the dynamic images (p = 0.0002; sensitivity, 0.34; specificity, 1.00) in time-intensity profiles (p < 0.000005; sensitivity, 0.67; specificity, 0.93) and in peripheral percentage signal changes at 1 min postcontrast (p = 0.001). There was a much higher relative signal increase centrally than peripherally (p < 0.0005), but peripheral signal changes had greater diagnostic value than central ones (Az = 0.72 vs. 0.63; p = 0.02). Carcinomas showed higher peripheral enhancement than benign lesions (p = 0.001). Peripheral enhancement reached maximum diagnostic value at 4 min postcontrast (Az = 0.80) and performed best as a highly sensitive but moderately specific diagnostic index. CONCLUSION: Quantification of peripheral enhancement is diagnostically useful and offers insight into the enhancement mechanisms encountered in breast MRI. Primary breast tumours show substantial spatial contrast uptake heterogeneity. Lesion differentiation based on percentage signal changes is improved by restricting sampling to the periphery of tumours.
PURPOSE: The purpose of our study was to determine if quantitative analysis of peripheral enhancement and spatial contrast uptake heterogeneity is useful in the characterisation of abnormalities seen at breast MRI. METHOD: Ninety-one women underwent dynamic gadolinium-enhanced breast MRI. Regions of interest were processed by a parallel thinning algorithm to define central and peripheral subregions of lesions. Peripheral enhancement was quantified at every time point of the dynamic sequence as a signal difference-to-noise ratio. Moreover, a radiologist assessed the images for the presence of peripheral enhancement and classified the regional and subregional time-intensity profiles of each lesion. RESULTS: Sixty-four invasive carcinomas and 30 benign lesions were analysed. Significant differences were found between benign and malignant lesions in peripheral enhancement as determined from the dynamic images (p = 0.0002; sensitivity, 0.34; specificity, 1.00) in time-intensity profiles (p < 0.000005; sensitivity, 0.67; specificity, 0.93) and in peripheral percentage signal changes at 1 min postcontrast (p = 0.001). There was a much higher relative signal increase centrally than peripherally (p < 0.0005), but peripheral signal changes had greater diagnostic value than central ones (Az = 0.72 vs. 0.63; p = 0.02). Carcinomas showed higher peripheral enhancement than benign lesions (p = 0.001). Peripheral enhancement reached maximum diagnostic value at 4 min postcontrast (Az = 0.80) and performed best as a highly sensitive but moderately specific diagnostic index. CONCLUSION: Quantification of peripheral enhancement is diagnostically useful and offers insight into the enhancement mechanisms encountered in breast MRI. Primary breast tumours show substantial spatial contrast uptake heterogeneity. Lesion differentiation based on percentage signal changes is improved by restricting sampling to the periphery of tumours.