Dual-Time Resolution Characterization of Masses on Breast DCEMR

PURPOSE To assess the diagnostic accuracy of high resolution and transient fast DCEMR individually and both combined in discriminating benign and malignant masses using automatic computer assisted analysis. METHOD AND MATERIALS A set of 97 detected masses (fibroademas and invasive ductal carcinomas) was selected from a consecutive cohort of breast MR in 2008 and 2009. The MR scanning protocol included high temporal resolution combined with high spatial resolution imaging. The high temporal resolution images were acquired every 4.1s using a 3D TurboFLASH sequence during initial enhancement (Fast). The high spatial resolution images were acquired at a temporal resolution of 86s using a 3D FLASH sequence (HighRes). All the masses were annotated with a 3D spheroid volume covering the lesion extent. Subsequent analysis was fully automatic. The contrast enhanced region in of the annotation was segmented using Otsu thresholding followed by binary morphological operators. Each lesion was characterized by a set of features (2 HighRes + 3 Fast) comprising quartiles of relative enhancement, wash-out, and pharmacokinetic image voxel features within the enhancing lesion area. Image feature maps are automatically computed from the Fast and HighRes sequences using curve fitting and pharmacokinetic modeling. An ensemble Support Vector Machine classifier was trained to discriminate between benign and malignant lesions on each of the three feature sets: HighRes, Fast and HighRes+Fast. Using cross-validation and bootstrapping the area under the curve (AUC) for each set was estimated and compared using paired t-tests. RESULTS The diagnostic accuracy of the combined HighRes and Fast features was significantly (p<0.01) better than the HighRes features alone. The individual AUCs were: HighRes 0.78 (074-0.81); Fast 0.69 (0.66-0.72); HighRes+Fast 0.84 (0.82-0.87). CONCLUSION The increased diagnostic performance found when combining HighRes and Fast DCEMR demonstrates the additional value of our method in further improving the diagnostic performance of computerized analysis of breast MRI. This study shows that transient dynamic features from fast sequences provide additional information over conventional curve shape features in slower breast MR sequences. CLINICAL RELEVANCE/APPLICATION Dual time resolution breast MR can improve diagnostic accuracy over conventional single resolution analysis which may help increase specificity.