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Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists

Bulten, Wouter (author)
Radboud Univ Nijmegen, Netherlands
Balkenhol, Maschenka (author)
Radboud Univ Nijmegen, Netherlands
Belinga, Jean-Joel Awoumou (author)
Univ Yaounde I, Cameroon
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Brilhante, Americo (author)
Salomao Zoppi Diagnost DASA, Brazil
Cakir, Asli (author)
Istanbul Medipol Univ, Turkey
Egevad, Lars (author)
Karolinska Institutet
Eklund, Martin (author)
Karolinska Institutet
Farre, Xavier (author)
Publ Hlth Agcy Catalonia, Spain
Geronatsiou, Katerina (author)
Hop Diaconat Mulhouse, France
Molinie, Vincent (author)
Aix en Provence Hosp, France
Pereira, Guilherme (author)
Histo Patol Cirarg & Citol, Brazil
Roy, Paromita (author)
Tata Med Ctr, India
Saile, Gunter (author)
Abt Histopathol & Zytol, Switzerland
Salles, Paulo (author)
Inst Mario Penna, Brazil
Schaafsma, Ewout (author)
Radboud Univ Nijmegen, Netherlands
Tschui, Joelle (author)
Med Pathol, Switzerland
Vos, Anne-Marie (author)
Radboud Univ Nijmegen, Netherlands
van Boven, Hester (author)
Antoni van Leeuwenhoek Hosp, Netherlands
Vink, Robert (author)
Lab Pathol East Netherlands, Netherlands
van der Laak, Jeroen (author)
Linköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Region Östergötland, Klinisk patologi,Radboud Univ Nijmegen, Netherlands
Hulsbergen-van der Kaa, Christina (author)
Lab Pathol East Netherlands, Netherlands
Litjens, Geert (author)
Radboud Univ Nijmegen, Netherlands
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 (creator_code:org_t)
NATURE PUBLISHING GROUP, 2021
2021
English.
In: Modern Pathology. - : NATURE PUBLISHING GROUP. - 0893-3952 .- 1530-0285. ; 34, s. 660-671
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of 14 observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard increased significantly (quadratically weighted Cohens kappa, 0.799 vs. 0.872;p = 0.019). On an external validation set of 87 cases, the panel showed a significant increase in agreement with a panel of international experts in prostate pathology (quadratically weighted Cohens kappa, 0.733 vs. 0.786;p = 0.003). In both experiments, on a group-level, AI-assisted pathologists outperformed the unassisted pathologists and the standalone AI system. Our results show the potential of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

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