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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

  • Magnetic Resonance
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A Correction to this article was published on 18 September 2020

This article has been updated

Abstract

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.

Key Points

Mean T2 MRF measurements and ADC within cancerous regions of interest dropped with increasing ISUP prognostic groups (IPG).

Mean T1 and T2 MRF measurements were significantly different (p < 0.001) across IPGs, prostatitis, and normal peripheral zone (NPZ).

T2 MRF showed stronger correlations in the peripheral zone, while T1 MRF showed stronger correlations in the transition zone with histopathology for prostate cancer.

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Abbreviations

ADC:

Apparent diffusion coefficient

ANOVA:

Analysis of variance

IPG:

International Society of Urologic Pathology (ISUP) Prognostic Groups

MRF:

Magnetic resonance fingerprinting

NPZ:

Normal peripheral zone

PCa:

Prostate cancer

PZ:

Peripheral zone

T2w:

T2-weighted

TCR:

Tissue compartment ratio

TZ:

Transition zone

WM:

Whole mount histopathology

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Funding

Research reported in this manuscript was supported by the National Cancer Institute of the National Institutes of Health under award numbers 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, and 1U01 CA239055-01; National Center for Research Resources under award number 1 C06 RR12463-01; VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service; the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558); the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440); the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329); the Ohio Third Frontier Technology Validation Fund; the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University; and the DoD Prostate Cancer Research Program Idea Development Award W81XWH-18-1-0524.

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Correspondence to Rakesh Shiradkar.

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Guarantor

The scientific guarantor of this publication is Dr. Anant Madabhushi.

Conflict of interest

Dr. Anant Madabhushi is an equity holder in Elucid Bioimaging and in Inspirata Inc. He is also a scientific advisory consultant for Inspirata Inc. and is with its scientific advisory board. Additionally, his technology has been licensed to Elucid Bioimaging and Inspirata Inc, though not related to the work presented in this submission. Drs. Vikas Gulani, Ananya Panda and Shivani Pahwa were funded in part by Siemens Healthcare during their time at University Hospitals Cleveland.

Statistics and biometry

Dr. Pingfu Fu kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was provided by the patients for IRB protocol involving MRI and MRF acquisition. However, their consent was waived by the IRB for this specific study since it is retrospective and computational and poses very minimal risk to patients.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in Yu et al Radiology 2017.

Methodology

• retrospective

• observational/experimental

• performed at one institution

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The original version of this article was revised: The spelling of Pingfu Fu’s name was incorrect.

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Shiradkar, R., Panda, A., Leo, P. et al. 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. Eur Radiol 31, 1336–1346 (2021). https://doi.org/10.1007/s00330-020-07214-9

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