2023 ARRS ANNUAL MEETING - ABSTRACTS

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1012. Four Quadrant Vector Mapping of Hybrid Multidimensional MRI Data For the Diagnosis of Prostate Cancer
Authors * Denotes Presenting Author
  1. Aritrick Chatterjee *; University of Chicago
  2. Xiaobing Fan; University of Chicago
  3. Aytekin Oto; University of Chicago
  4. Gregory Karczmar; University of Chicago
Objective:
To investigate whether four quadrant vector mapping of hybrid multi-dimensional MRI (HM-MRI) data can be used to diagnose prostate cancer (PCa) and determine cancer aggressiveness.

Materials and Methods:
Twenty-one patients (mean age 65 years, mean PSA 6.9 ng/mL) with confirmed PCa underwent preoperative MRI on 3T Philips Achieva MR system prior to radical prostatectomy. Axial HM-MRI was acquired with all combinations of TE = 47, 75, 100 ms and b-values of 0, 750, 1500 s/mm2, resulting in a 3 × 3 data matrix associated with each voxel. Prostate Quadrant (PQ) mapping analysis represents HM-MRI data for each voxel as a color-coded vector in 2D plot with components T2 and ADC/TE with associated amplitude and angle in the 4-quadrant space of HM-MRI parameters representing the change in T2 and ADC as a function of b-value and TE (slope of ADC with changing TE or ADC/TE in the y-axis and slope of TE with changing b-value or T2 in the x-axis), respectively. Quadrant mapping metrics include amplitude, angle, PQ1 (percentage of voxels in quadrant 1; color coded blue), PQ2 (green), PQ3 (black), and PQ4 (red) which were calculated for ROIs taken for cancerous and benign tissue. Statistical differences (ANOVA), correlation with Gleason score and receiver operating characteristic (ROC) analysis were used to evaluate the performance of measured metrics in differentiating cancer from normal prostatic tissue.

Results:
Cancers have a higher PQ4 (22.50 ± 21.27%) and lower PQ2 (69.86 ± 28.24%) compared to benign tissue: peripheral, transition and central zone (PQ4 = 0.13 ± 0.56, 5.73 ± 15.07, 2.66 ± 4.05% and PQ2 = 98.51 ± 3.05, 86.18 ± 21.75, 93.38 ± 9.88% respectively). Therefore, cancers appear as red (higher PQ4), while benign tissue appears green (higher PQ2) on the four-quadrant map. Cancers have a higher vector angle (206.5 ± 41.8°) and amplitude (0.017 ± 0.013) compared to benign tissue. PQ metrics showed moderate correlation with Gleason score (|p| = 0.388-0.609) with more aggressive cancers being associated with increased PQ4 and angle and reduced PQ2 and amplitude. Vector amplitude followed by PQ4, PQ2, and angle were effective in differentiating between cancer and benign tissue evidenced by an area under the ROC curve of 0.857, 0.786, 0.765, and 0.741 (p < 0.001). A combination of four quadrant analysis metrics provided an area under the curve of 0.904 ( p <0.001) for the differentiation of prostate cancer from benign prostatic tissue.

Conclusion:
Four quadrant vector mapping of HM-MRI data provides effective cancer markers, with cancers associated with high PQ4 and high vector angle and lower PQ2 and vector amplitude. The PQ4, vector angle and amplitude that are specific to cancer may be associated with restricted diffusion combined with long T2 in the enlarged nuclei of rapidly growing cancer cells. Quadrant mapping parameters show promise for determining cancer aggressiveness as they are moderately correlated with cancer Gleason score.