| 11. |
- Ström, Peter, et al.
(författare)
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Pathologist-Level Grading of Prostate Biospies with Artificial intelligence
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Background: An increasing volume of prostate biopsies and a world-wide shortage of uro-pathologists puts a strain on pathology departments. Additionally, the high intra- and inter-observer variability in grading can result in over- and undertreatment of prostate cancer. Artificial intelligence (AI) methods may alleviate these problems by assisting pathologists to reduce workload and harmonize grading. Methods: We digitized 6,682 needle biopsies from 976 participants in the population based STHLM3 diagnostic study to train deep neural networks for assessing prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test set comprising 1,631 biopsies from 245 men. We additionally evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics (ROC) and tumor extent predictions by correlating predicted millimeter cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI and the expert urological pathologists using Cohen's kappa. Results: The performance of the AI to detect and grade cancer in prostate needle biopsy samples was comparable to that of international experts in prostate pathology. The AI achieved an area under the ROC curve of 0.997 for distinguishing between benign and malignant biopsy cores, and 0.999 for distinguishing between men with or without prostate cancer. The correlation between millimeter cancer predicted by the AI and assigned by the reporting pathologist was 0.96. For assigning Gleason grades, the AI achieved an average pairwise kappa of 0.62. This was within the range of the corresponding values for the expert pathologists (0.60 to 0.73).
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| 12. |
- van der Kwast, Theo, et al.
(författare)
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International Society of Urological Pathology Expert Opinion on Grading of Urothelial Carcinoma
- 2022
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Ingår i: European Urology Focus. - : Elsevier BV. - 2405-4569. ; 8:2, s. 438-446
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Forskningsöversikt (refereegranskat)abstract
- Context: Grading is the mainstay for treatment decisions for patients with non–muscle-invasive bladder cancer (NMIBC). Objective: To determine the requirements for an optimal grading system for NMIBC via expert opinion. Evidence acquisition: A multidisciplinary working group established by the International Society of Urological Pathology reviewed available clinical, histopathological, and molecular evidence for an optimal grading system for bladder cancer. Evidence synthesis: Bladder cancer grading is a continuum and five different grading systems based on historical grounds could be envisaged. Splitting of the World Health Organization (WHO) 2004 low-grade class for NMIBC lacks diagnostic reproducibility and molecular-genetic support, while showing little difference in progression rate. Subdividing the clinically heterogeneous WHO 2004 high-grade class for NMIBC into intermediate and high risk categories using the WHO 1973 grading is supported by both clinical and molecular-genetic findings. Grading criteria for the WHO 1973 scheme were detailed on the basis of literature findings and expert opinion. Conclusions: Splitting of the WHO 2004 high-grade category into WHO 1973 grade 2 and 3 subsets is recommended. Provision of more detailed histological criteria for the WHO 1973 grading might facilitate the general acceptance of a hybrid four-tiered grading system or—as a preferred option—a more reproducible three-tiered system distinguishing low-, intermediate (high)-, and high-grade NMIBC. Patient summary: Improvement of the current systems for grading bladder cancer may result in better informed treatment decisions for patients with bladder cancer. A three-tiered grading system for non–muscle invasive bladder cancer derived by splitting the heterogeneous World Health Organization (WHO) 2004 high-grade category into WHO 1973 grade 2 and 3 subsets is recommended, as this may result in more informed treatment decisions.
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