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Proceedings Paper

Automatic cancer sub-grading on digital histopathology images of radical prostatectomy specimens
Author(s): W. Han; M. Downes; T. H. van der Kwast; J. L. Chin; S. E. Pautler; A. D. Ward
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Paper Abstract

Automatic cancer sub-grading of radical prostatectomy (RP) specimens can support clinical studies seeking the prognostic indications of the sub-grades, and potentially benefits patient risk management and treatment planning. We developed and validated an automatic system which classifies each of nine subgrades (i.e. 4 sub-grades of Gleason grade 3, 3 sub-grades of Gleason grade 4, benign intervening, and other cancerous tissue) on digital histopathology whole-slide images (WSIs). The system was cross-validated against expert-drawn contours on a 25-patient data set comprising 92 mid-gland WSIs of RP specimens. The system used a transfer learning technique by fine-tuning AlexNet to classify each cancerous region of interest (ROI) according to sub-grade. We used leave-one-WSI-out cross-validation to measure classifier performance. The system yielded an area under the receiver-operating characteristic curve (AUC) higher than 0.8 for sub-grades of small fused Gleason 4 (G4), intermediate G3, and other cancerous tissue (AUC of 0.976); and AUCs higher than 0.7 for sub-grades of sparse G3, large cribriform G4, and desmoplastic G3.

Paper Details

Date Published: 16 March 2020
PDF: 6 pages
Proc. SPIE 11320, Medical Imaging 2020: Digital Pathology, 113200H (16 March 2020); doi: 10.1117/12.2551529
Show Author Affiliations
W. Han, Western Univ. (Canada)
Lawson Health Research Institute (Canada)
M. Downes, Univ. of Toronto (Canada)
T. H. van der Kwast, Univ. Health Network (Canada)
J. L. Chin, Western Univ. (Canada)
S. E. Pautler, Western Univ. (Canada)
A. D. Ward, Western Univ. (Canada)
Lawson Health Research Institute (Canada)

Published in SPIE Proceedings Vol. 11320:
Medical Imaging 2020: Digital Pathology
John E. Tomaszewski; Aaron D. Ward, Editor(s)

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