Whole Slide Image Quality in Digital Pathology: Review and Perspectives

With the advent of whole slide image (WSI) scanners, pathology is undergoing a digital revolution. Simultaneously, with the development of image analysis algorithms based on artificial intelligence tools, the application of computerized WSI analysis can now be expected. However, transferring such tools into clinical practice is very challenging as they must deal with many artifacts that can occur during sample preparation and digitization. Therefore, the quality of WSIs is of prime importance, and we propose a review of the state-of-the-art of computational approaches for quality control. In particular, we focus on WSI quality issues related to the presence of sample preparation artifacts, compression artifacts, color variations, and out-of-focus areas. An analysis of the monthly WSI clinical routine in a cytological laboratory confirms the importance of implementing quality control measures. Given this observation, we draw perspectives on how a computational quality process can be included in a computational pathology diagnosis pipeline.

Automated summary

With the development of WSI scanners and artificial intelligence algorithms, computational WSI analysis is becoming possible, but it faces challenges in dealing with artifacts. This review focuses on computational approaches for quality control in WSI, addressing issues such as sample preparation artifacts, compression artifacts, color variations, and out-of-focus areas. The importance of implementing quality control measures is confirmed through analysis of WSI clinical routine, and perspectives on including a computational quality process in pathology diagnosis pipeline are drawn.