4.7 Article

T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology

Journal

EUROPEAN RADIOLOGY
Volume 31, Issue 3, Pages 1336-1346

Publisher

SPRINGER
DOI: 10.1007/s00330-020-07214-9

Keywords

Prostatic neoplasms; Prostatitis; Magnetic resonance imaging; Prostatectomy; Deep learning

Funding

  1. National Cancer Institute of the National Institutes of Health [1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01]
  2. National Center for Research Resources [1 C06 RR12463-01]
  3. VA Merit Review Award from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service [IBX004121A]
  4. DOD Prostate Cancer Idea Development Award [W81XWH-15-1-0558]
  5. DOD Lung Cancer Investigator-Initiated Translational Research Award [W81XWH-18-1-0440]
  6. DOD Peer Reviewed Cancer Research Program [W81XWH-16-1-0329]
  7. Ohio Third Frontier Technology Validation Fund
  8. Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering
  9. Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University
  10. DoD Prostate Cancer Research Program Idea Development Award [W81XWH-18-1-0524]

Ask authors/readers for more resources

Significant differences were observed in TCRs and T1 and T2 MRF between PCa, prostatitis, and normal PZ. T1 and T2 MRF showed correlations with epithelium and stroma of PCa, with T1 MRF in opposite directions between PCa and prostatitis. T2 MRF was positively correlated with lumen of PCa and prostatitis.
Objectives To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis. Materials and methods A retrospective, IRB-approved, HIPAA-compliant cohort consisting of 14 PCa patients who underwent 3 T multiparametric MRI along with T1 and T2 MRF maps prior to radical prostatectomy was used. Correspondences between whole mount specimens and MRI and MRF were manually established. Prostatitis, PCa, and normal peripheral zone (PZ) regions of interest (ROIs) on pathology were segmented for TCRs of epithelium, lumen, and stroma using two U-net deep learning models. Corresponding ROIs were mapped to T2-weighted MRI (T2w), apparent diffusion coefficient (ADC), and T1 and T2 MRF maps. Their correlations with TCRs were computed using Pearson's correlation coefficient (R). Statistically significant differences in means were assessed using one-way ANOVA. Results Statistically significant differences (p < 0.01) in means of TCRs and T1 and T2 MRF were observed between PCa, prostatitis, and normal PZ. A negative correlation was observed between T1 and T2 MRF and epithelium (R = - 0.38, - 0.44,p < 0.05) of PCa. T1 MRF was correlated in opposite directions with stroma of PCa and prostatitis (R = 0.35, - 0.44,p < 0.05). T2 MRF was positively correlated with lumen of PCa and prostatitis (R = 0.57, 0.46,p < 0.01). Mean T2 MRF showed significant differences (p < 0.01) between PCa and prostatitis across both transition zone (TZ) and PZ, while mean T1 MRF was significant (p = 0.02) in TZ. Conclusion Significant associations between MRF (T1 in the TZ and T2 in the PZ) and tissue compartments on corresponding histopathology were observed.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available