Abstract

Introduction. Dynamic contrast-enhanced (DCE) MRI provides quantitative information on tissue properties that enhances the specificity of breast cancer diagnosis; however, mammography remains the standard screening protocol due to its lower cost. There is a push to develop more accessible abbreviated breast MRI scans for screening high-risk patients without compromising diagnostic power. Here we analyze the effects of the limited dynamic time course afforded by an abbreviated breast MRI exam on the diagnostic performance of quantitative DCE-MRI. Methods and Results. We evaluate the ability of five quantitative measures to retrospectively differentiate malignant (N=21) and benign (N=24) lesions using DCE-MRI data acquired with 15 second temporal resolution in a cohort of 45 patients from the ACRIN 6883 multi-site breast trial. The first two measures are the volume transfer constant (Ktrans) estimated by, respectively, fitting the standard Kety-Tofts (STK) perfusion model and the Patlak approximation of the STK model (Patlak model) to patient data sets that have been truncated into a series of abbreviated-time courses (ATCs). An ATC is defined as containing the first n time points of a time course and is referred to as “ATC n.” For the first measure, n is the inclusive set of integers from 7 to 14, and, for the second measure, n is the set of 4 and 7 since the Patlak approximation only holds during the initial enhancement. For each patient, the fitting procedure provides Ktrans values for each voxel within the region of interest (ROI). The values are averaged and statistically evaluated for performance in discriminating malignant from benign tumors. For Ktrans, the maximum AUC of 0.61 was achieved using ATC 14 (i.e., 3.50 minutes), while for the Patlak model, the maximum AUC of 0.55 was achieved using ATC 7 (i.e., 1.75 minutes). The third measure is a modified median signal enhancement ratio (SER) computed for a series of four ATCs per patient, where n is now the inclusive set of integers 8 through 11. The SER is defined as (S1-S0)/(S2-S0), where S0 is the pre-contrast signal, S1 is the peak enhancement, and S2 is the signal at the last time point. Abbreviating the time course effectively shifts S2 to an earlier time point. For each ATC for each patient, the SERs are computed for all voxels within the ROI after which the median is computed. We calculate the AUC under the ROC curve to evaluate the diagnostic performance of each ATC-derived median SER. ATC 10 (i.e., 2.5 minutes) yields a maximum AUC of 0.79 among all ATCs. The fourth and fifth measures are, respectively, the area under the enhancement phase and the slope of the washout phase of the patient DCE time courses. The fourth measure is computed by numerically integrating the time course of each voxel within a patient’s ROI between the first and seventh time points and averaging the values. Similarly, for the fifth measure, the slope is calculated between the seventh and last time points within the ROI and averaged. We find that the fourth measure yields an AUC under the ROC curve of 0.76, and the fifth measure yields an AUC of 0.77. Discussion and Conclusion. The highest AUC from the two pharmacokinetic measures is 0.61, which suggests ineffective diagnostic ability in this data set. The median SER computed using ATC10 yields an AUC of 0.79, showing promise as a quantitative diagnostic tool in the abbreviated scan setting. Inter-site variability and the low temporal resolution of this data set may explain the relatively lower performance of measures one, two, four, and five as compared to measure three. It is necessary to repeat this analysis using a state-of-the-art acquisition of DCE-MRI data to determine the specificity of the remaining quantitative measures to imaging specifications. Citation Format: Kalina P Slavkova, Julie C DiCarlo, Anum K Syed, Chengyue Wu, John Virostko, Anna G Sorace, Thomas E Yankeelov. Investigating the feasibility of performing quantitative DCE-MRI in an abbreviated breast examination [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-04.