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Leo P, Chandramouli S, Farré X, et al. Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. Eur Urol Focus. 2021;7(4):722-732doi: 10.1016/j.euf.2021.04.016.
Leo, P., Chandramouli, S., Farré, X., Elliott, R., Janowczyk, A., Bera, K., Fu, P., Janaki, N., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T. R., Khani, F., Robinson, B. D., Shih, N. N. C., Feldman, M., Gupta, S., McKenney, J., Lal, P., & Madabhushi, A. (2021). Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. European urology focus, 7(4), 722-732. https://doi.org/10.1016/j.euf.2021.04.016
Leo, Patrick, et al. "Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2." European urology focus vol. 7,4 (2021): 722-732. doi: https://doi.org/10.1016/j.euf.2021.04.016
Leo P, Chandramouli S, Farré X, Elliott R, Janowczyk A, Bera K, Fu P, Janaki N, El-Fahmawi A, Shahait M, Kim J, Lee D, Yamoah K, Rebbeck TR, Khani F, Robinson BD, Shih NNC, Feldman M, Gupta S, McKenney J, Lal P, Madabhushi A. Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2. Eur Urol Focus. 2021 Jul;7(4):722-732. doi: 10.1016/j.euf.2021.04.016. Epub 2021 Apr 30. PMID: 33941504; PMCID: PMC8419103.
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Eur Urol Focus. 2021 Jul;7(4):722-732. doi: 10.1016/j.euf.2021.04.016. Epub 2021 Apr 30.

Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2.

European urology focus

Patrick Leo, Sacheth Chandramouli, Xavier Farré, Robin Elliott, Andrew Janowczyk, Kaustav Bera, Pingfu Fu, Nafiseh Janaki, Ayah El-Fahmawi, Mohammed Shahait, Jessica Kim, David Lee, Kosj Yamoah, Timothy R Rebbeck, Francesca Khani, Brian D Robinson, Natalie N C Shih, Michael Feldman, Sanjay Gupta, Jesse McKenney, Priti Lal, Anant Madabhushi

Affiliations

  1. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
  2. Public Health Agency of Catalonia, Lleida, Catalonia, Spain.
  3. Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
  4. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Oncology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
  5. Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
  6. Department of Pathology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  7. Department of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.
  8. Department of Radiation Oncology, Moffitt Cancer Center, University of South Florida, Tampa, FL, USA.
  9. T.H. Chan School of Public Health and Dana Farber Cancer Institute, Harvard University, Boston, MA, USA.
  10. Departments of Pathology and Laboratory Medicine and Urology, Weill Cornell Medicine, New York, NY, USA.
  11. Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA.
  12. Department of Urology, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA.
  13. Department of Anatomic Pathology, Cleveland Clinic, Cleveland, OH, USA.
  14. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA. Electronic address: [email protected].

PMID: 33941504 PMCID: PMC8419103 DOI: 10.1016/j.euf.2021.04.016

Abstract

BACKGROUND: The presence of invasive cribriform adenocarcinoma (ICC), an expanse of cells containing punched-out lumina uninterrupted by stroma, in radical prostatectomy (RP) specimens has been associated with biochemical recurrence (BCR). However, ICC identification has only moderate inter-reviewer agreement.

OBJECTIVE: To investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups.

DESIGN, SETTING, AND PARTICIPANTS: A machine learning approach was developed for ICC segmentation using 70 RP patients and validated in a cohort of 749 patients from four sites whose median year of surgery was 2007 and with median follow-up of 28 mo. ICC was segmented on one representative hematoxylin and eosin RP slide per patient and the fraction of tumor area composed of ICC, the cribriform area index (CAI), was measured.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR).

RESULTS AND LIMITATIONS: CAI was correlated with BCR (c index 0.62) in the validation set of 411 patients with ICC morphology, especially those with Gleason grade group 2 cancer (n = 192; c index 0.66), and was less prognostic when patients without ICC were included (c index 0.54). A doubling of CAI in the group with ICC morphology was prognostic after controlling for Gleason grade, surgical margin positivity, preoperative prostate-specific antigen level, pathological T stage, and age (HR 1.19, 95% confidence interval 1.03-1.38; p = 0.018).

CONCLUSIONS: Automated image analysis and machine learning could provide an objective, quantitative, reproducible, and high-throughput method of quantifying ICC area. The performance of CAI for grade group 2 cancer suggests that for patients with little Gleason 4 pattern, the ICC fraction has a strong prognostic role.

PATIENT SUMMARY: Machine-based measurement of a specific cell pattern (cribriform; sieve-like, with lots of spaces) in images of prostate specimens could improve risk stratification for patients with prostate cancer. In the future, this could help in expanding the criteria for active surveillance.

Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Keywords: Biochemical recurrence; Cribriform; Digital pathology; Gleason grading; Machine learning; Prostate cancer

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