Can color-coded parametric maps improve dynamic enhancement pattern analysis in MR mammography?

ABSTRACT

PURPOSE: Post-contrast enhancement characteristics (PEC) are a major criterion for differential diagnosis in MR mammography (MRM). Manual placement of regions of interest (ROIs) to obtain time/signal intensity curves (TSIC) is the standard approach to assess dynamic enhancement data. Computers can automatically calculate the TSIC in every lesion voxel and combine this data to form one color-coded parametric map (CCPM). Thus, the TSIC of the whole lesion can be assessed. This investigation was conducted to compare the diagnostic accuracy (DA) of CCPM with TSIC for the assessment of PEC. MATERIALS AND METHODS: 329 consecutive patients with 469 histologically verified lesions were examined. MRM was performed according to a standard protocol (1.5 T, 0.1 mmol/kgbw Gd-DTPA). ROIs were drawn manually within any lesion to calculate the TSIC. CCPMs were created in all patients using dedicated software (CAD Sciences). Both methods were rated by 2 observers in consensus on an ordinal scale. Receiver operating characteristics (ROC) analysis was used to compare both methods. RESULTS: The area under the curve (AUC) was significantly (p=0.026) higher for CCPM (0.829) than TSIC (0.749). The sensitivity was 88.5% (CCPM) vs. 82.8% (TSIC), whereas equal specificity levels were found (CCPM 63.7%, TSIC 63.0%). CONCLUSION: The color-coded parametric maps (CCPMs) showed a significantly higher DA compared to TSIC, in particular the sensitivity could be increased. Therefore, the CCPM method is a feasible approach to assessing dynamic data in MRM and condenses several imaging series into one parametric map.