Summarizing the 4D image stack of ultrafast dynamic contrast enhancement MRI of breast cancer in 3D using color intensity projections

Background: Each ultrafast dynamic contrast-enhanced (DCE) MRI sequence for breast cancer generates thousands of images in a 4D stack that need to be reviewed by a radiologist. Purpose: To assess whether color intensity projections (CIP) effectively summarizes—using only the time of arrival (ToA) and amount of signal enhancement (AoE) of the contrast agent—the thousands of ultrafast images. Study Type: Retrospective cohort clinical trial. Subjects: The study included 89 patients who had been scanned with an MRI beast protocol, of which 26 had breast cancer and 63 did not. Field Strength/Sequence: The 115-second ultrafast DCE sequence at 3T acquired 19 consecutive frames every 4.26 seconds with 152 slices per frame, yielding a 4D stack with 2888 2D images for each of water and fat. Assessment: For each slice of the water 4D stack a single CIP image was generated that encoded the ToA in the hue (red, orange, yellow, green, cyan, blue) and AoE in the brightness. Each of three experienced radiologists assigned a Breast Imaging and Reporting Data System (BI-RADS) score for each patient, first using only the CIP images, and subsequently using both CIP and the full 4D stack. Statistical Tests: The one-sided Fisher's exact test was used to determine statistical significance of both the sensitivity and specificity between the CIP alone and the CIP plus 4D stack. Results: All malignancies were detected using only CIP by at least one of the radiologists. The CIP and CIP+4D sensitivities for reader 1 were 96% and 96% (P = 0.57), specificities were 59% and 65% (P = 0.29). For reader 2, the values were 96% and 100% (P = 0.51) with 62% and 71% (P = 0.17). For reader 3 the values were 92% and 96% (P = 0.50) with 51% and 62% (P = 0.07). Data Conclusion: With a 95% sensitivity, CIP provides an effective summary of ultrafast DCE images of breast cancer. Level of Evidence: 3. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2019;49:1391–1399.