Computerized Characterization of Breast Masses Using Dual-Temporal Resolution Dynamic Contrast-enhanced MR Images

B. Platel, H. Huisman, H. Laue, R. Mann, H. Hahn, N. Karssemeijer and R. Mus

Annual Meeting of the Radiological Society of North America 2011.

PURPOSE: Common computerized differentiation algorithms for breast masses use morphological and kinetic curve features from high spatial resolution DCEMR images. We assess the performance change when these features are combined with pharmacokinetic features derived from a specialized dual-temporal resolution MR protocol. METHOD AND MATERIALS: All patients with enhancing masses from a consecutive set of breast MR studies, acquired between 2008 and 2010 on a Sonata or Symphony 1.5T Siemens scanner, were included. This resulted in a cohort of 93 patients, with 66 benign and 67 malignant lesions (validated by biopsy). Our scanning protocol combined high temporal with high spatial resolution imaging. High temporal resolution (HT) images were acquired every 4.5s using a 3D TurboFLASH sequence (TR 7.8ms, TE 4ms, FA 20A-A?A 1/2 , FOV 320mm) during initial enhancement. Additional 4.5s scans were made every 110s to observe late behavior of the contrast agent. High spatial resolution (HS) images were acquired every 110s using a 3D FLASH sequence (TR 72ms, TE 1.54ms, FA 20A-A?A 1/2 , FOV 320mm). Each lesion was automatically segmented using 'smart opening'; a combination of thresholds, region growing and morphological operations. Every lesion was characterized by a set of 6 morphological and 8 kinetic features derived from HS and 3 pharmacokinetic features derived from HT. An SVM classifier with a radial basis function kernel was used. Ten-fold cross-validation was executed 10 times. Performance was measured by the area under the ROC curve, Az. RESULTS: The accuracy of the combined HS and HT kinetic features was significantly better (Az=0.81, p<0.02) than either the HS or HT kinetic features alone (Az=0.77 and 0.71 respectively). The commonly used combination of morphological and kinetic features from HS showed a diagnostic performance of Az=0.85. The addition of pharmacokinetic features from HT increased this performance significantly (Az=0.88, p=0.03). CONCLUSION: Pharmacokinetic features obtained from a high temporal resolution DCEMR sequence provide additional information over conventional morphological and kinetic features from a high spatial resolution sequence. Combining these features leads to significantly better performance for computerized differentiation of breast masses. CLINICAL RELEVANCE/APPLICATION: Dual temporal resolution breast MR can improve diagnostic accuracy over conventional single resolution analysis, which can increase specificity.