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.

Eosine Yellowish-(YS) Hematoxylin Humans Male Neoplasm Recurrence, Local / pathology Prognosis Prostate / pathology Prostatectomy / methods Prostatic Neoplasms / pathology
Biochemical recurrence Cribriform Digital pathology Gleason grading Machine learning Prostate cancer

Journal

European urology focus
ISSN: 2405-4569
Titre abrégé: Eur Urol Focus
Pays: Netherlands
ID NLM: 101665661

Informations de publication

Date de publication:
Jul 2021
Historique:
received: 11 12 2020
revised: 11 03 2021
accepted: 16 04 2021
pubmed: 5 5 2021
medline: 14 4 2022
entrez: 4 5 2021
Statut: ppublish

Résumé

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. To investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups. 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. The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR). 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). 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. 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.

Sections du résumé

BACKGROUND 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 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 METHODS
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 METHODS
The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR).
RESULTS AND LIMITATIONS CONCLUSIONS
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 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 RESULTS
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.

Identifiants

DOI: 10.1016/j.euf.2021.04.016 PMID: 33941504 PMC: PMC8419103
pubmed: 33941504
pii: S2405-4569(21)00122-X
doi: 10.1016/j.euf.2021.04.016
pmc: PMC8419103
mid: NIHMS1696840
pii:
doi:

Substances chimiques

Eosine Yellowish-(YS) TDQ283MPCW
Hematoxylin YKM8PY2Z55

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

722-732

Subventions

Organisme : NCATS NIH HHS
ID : UL1 TR002548
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216579
Pays : United States
Organisme : NCRR NIH HHS
ID : C06 RR012463
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA199374
Pays : United States
Organisme : NIBIB NIH HHS
ID : R43 EB028736
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA239055
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA249992
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL151277
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA220581
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA202752
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA208236
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA248226
Pays : United States
Organisme : BLRD VA
ID : I01 BX004121
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA257612
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA254566
Pays : United States

Informations de copyright

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

Références

J Clin Oncol. 2019 Jan 20;37(3):213-221
pubmed: 30526194
Lancet Oncol. 2020 Feb;21(2):222-232
pubmed: 31926806
Mod Pathol. 2015 Mar;28(3):457-64
pubmed: 25189638
Eur Urol. 2017 Sep;72(3):442-447
pubmed: 27574819
Am J Surg Pathol. 2020 Aug;44(8):e87-e99
pubmed: 32459716
Lancet. 2012 Dec 8;380(9858):2018-27
pubmed: 23084481
Cancer. 2011 Nov 15;117(22):5039-46
pubmed: 21647869
Med Image Comput Comput Assist Interv. 2013;16(Pt 2):403-10
pubmed: 24579166
Adv Anat Pathol. 2018 Jan;25(1):31-37
pubmed: 28820750
Mod Pathol. 2019 Jan;32(1):139-146
pubmed: 30349027
Urology. 2010 Feb;75(2):407-13
pubmed: 19758683
J Med Imaging (Bellingham). 2016 Oct;3(4):047502
pubmed: 27803941
Lancet Oncol. 2020 Feb;21(2):233-241
pubmed: 31926805
J Urol. 2011 Aug;186(2):465-9
pubmed: 21679996
Eur Urol. 2014 Sep;66(3):550-60
pubmed: 24836057
BMC Genomics. 2013 Oct 08;14:690
pubmed: 24103217
NPJ Precis Oncol. 2021 May 3;5(1):35
pubmed: 33941830
Am J Clin Pathol. 2011 Jul;136(1):98-107
pubmed: 21685037
Nat Rev Clin Oncol. 2019 Nov;16(11):703-715
pubmed: 31399699
Lancet Digit Health. 2020 Aug;2(8):e407-e416
pubmed: 33328045
Scand J Urol. 2016 Dec;50(6):420-424
pubmed: 27416104
IEEE Trans Biomed Eng. 2013 Aug;60(8):2089-99
pubmed: 23392336
J Clin Oncol. 2005 Oct 1;23(28):7005-12
pubmed: 16192588
Histopathology. 2019 Jan;74(1):146-160
pubmed: 30565302
PLoS Curr. 2015 Nov 17;7:
pubmed: 26664778
Urol Oncol. 2015 Feb;33(2):71.e1-9
pubmed: 25131660
PLoS One. 2014 May 29;9(5):e97954
pubmed: 24875018
Am J Surg Pathol. 2016 Oct;40(10):1400-6
pubmed: 27379821
Am J Surg Pathol. 2014 Jan;38(1):128-37
pubmed: 24145650
Sci Rep. 2018 Oct 8;8(1):14918
pubmed: 30297720
J Urol. 1974 Jan;111(1):58-64
pubmed: 4813554
Arch Pathol Lab Med. 2021 Apr 1;145(4):461-493
pubmed: 32589068
Histopathology. 2016 Sep;69(3):441-9
pubmed: 27028587
Prostate. 2015 Sep;75(12):1277-84
pubmed: 25963383
Virchows Arch. 2015 Oct;467(4):437-42
pubmed: 26229020
NPJ Digit Med. 2019 Jun 7;2:48
pubmed: 31304394
Am J Surg Pathol. 2005 Sep;29(9):1228-42
pubmed: 16096414
Mod Pathol. 2016 Jun;29(6):630-6
pubmed: 26939875
Eur J Cancer. 2014 Jun;50(9):1610-6
pubmed: 24703897
Arch Pathol Lab Med. 2018 Aug;142(8):938-946
pubmed: 30040459
Eur Urol. 2016 Jul;70(1):106-119
pubmed: 26996659
Am J Surg Pathol. 2016 Nov;40(11):1439-1456
pubmed: 27635949
Am J Surg Pathol. 2013 Dec;37(12):1855-61
pubmed: 24145642
Pathol Res Pract. 2014 Oct;210(10):640-4
pubmed: 25042388

Auteurs

Patrick Leo (P)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Sacheth Chandramouli (S)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Xavier Farré (X)

Public Health Agency of Catalonia, Lleida, Catalonia, Spain.

Robin Elliott (R)

Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.

Andrew Janowczyk (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Oncology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

Kaustav Bera (K)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Pingfu Fu (P)

Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.

Nafiseh Janaki (N)

Department of Pathology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.

Ayah El-Fahmawi (A)

Department of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.

Mohammed Shahait (M)

Department of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.

Jessica Kim (J)

Department of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.

David Lee (D)

Department of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.

Kosj Yamoah (K)

Department of Radiation Oncology, Moffitt Cancer Center, University of South Florida, Tampa, FL, USA.

Timothy R Rebbeck (TR)

T.H. Chan School of Public Health and Dana Farber Cancer Institute, Harvard University, Boston, MA, USA.

Francesca Khani (F)

Departments of Pathology and Laboratory Medicine and Urology, Weill Cornell Medicine, New York, NY, USA.

Brian D Robinson (BD)

Departments of Pathology and Laboratory Medicine and Urology, Weill Cornell Medicine, New York, NY, USA.

Natalie N C Shih (NNC)

Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA.

Michael Feldman (M)

Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA.

Sanjay Gupta (S)

Department of Urology, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA.

Jesse McKenney (J)

Department of Anatomic Pathology, Cleveland Clinic, Cleveland, OH, USA.

Priti Lal (P)

Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA.

Anant Madabhushi (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA. Electronic address: anant.madabhushi@case.edu.

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Classifications MeSH

questionsmedicales.fr › Composés polycycliques › Spiranes › Fluorescéines › Éosine jaunâtre › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Composés hétérocycliques › Composés hétérocycliques à cycles fusionnés › Composés hétérobicycliques › Benzopyranes › Hématoxyline › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › États, signes et symptômes pathologiques › Processus pathologiques › Processus néoplasiques › Récidive tumorale locale › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Diagnostic › Pronostic › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Tissus › Glandes exocrines › Prostate › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Procédures de chirurgie opératoire › Procédures de chirurgie urogénitale › Procédures de chirurgie urologique › Procédures de chirurgie urologique masculine › Prostatectomie › Computationally Derived Cribriform Area Index...
questionsmedicales.fr › Maladies urogénitales › Tumeurs de l'appareil urogénital › Tumeurs de l'appareil génital mâle › Tumeurs de la prostate › Computationally Derived Cribriform Area Index...