Year: 2024
Type: article
Abstract: Objective: Stain normalization is a technique used to standardize the color appearance of digital whole slide images (WSIs). This study aimed to assess the impact of digital stain normalization on prostate cancer diagnosis by pathologists. Methods: A multi-institutional board of four pathologists evaluated 407 hematoxylin and eosin (H&E) prostate WSIs before and after stain normalization. The presence/absence of prostate adenocarcinoma, the Grade Groups as well as color quality perception and time required for diagnosis were recorded. Results: After normalization, color quality improved significantly for all pathologists (median scores increased from 4-6 to 7-8/10). Average diagnosis time decreased from 50s to 35s (p < 0.001). Inter-pathologist reproducibility for Gleason risk group showed a fair to good level of agreement, with an improvement after normalization. Conclusions: Stain normalization enhanced pathologists' diagnosis of prostate cancer by improving color standardization, reducing diagnosis time, and increasing inter-observer reproducibility. These findings highlight the potential of stain normalization to improve accuracy and efficiency in digital pathology.
Source: Pathologica
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406038627