High‐throughput whole‐slide scanning to enable large‐scale data repository building. Issue 4 (8th June 2022)

• Record Type: Journal Article
• Authors: Zarella, Mark D; Rivera Alvarez, Keysabelis
• Is Part Of: Journal of pathology. Volume 257:Issue 4(2022)
• Page Start: 383
• Page End: 390
• Publication Date: 2022-06-08
• Subjects: digital pathology -- virtual slide -- whole‐slide imaging -- whole‐slide scanning -- artificial intelligence -- machine learning -- computational pathology -- data repository; Pathology -- Periodicals; 616.07
• DOI: 10.1002/path.5923
• Languages: English
• ISSNs: 0022-3417

Abstract

Abstract: Digital pathology and artificial intelligence (AI) rely on digitization of patient material as a necessary first step. AI development benefits from large sample sizes and diverse cohorts, and therefore efforts to digitize glass slides must meet these needs in an efficient and cost‐effective manner. Technical innovation in whole‐slide imaging has enabled high‐throughput slide scanning through the coordinated increase in scanner capacity, speed, and automation. Combining these hardware innovations with automated informatics approaches has enabled more efficient workflows and the opportunity to provide higher‐quality imaging data using fewer personnel. Here we review several practical considerations for deploying high‐throughput scanning and we present strategies to increase efficiency with a focus on quality. Finally, we review remaining challenges and issue a call to vendors to innovate in the areas of automation and quality control in order to make high‐throughput scanning realizable to laboratories with limited resources. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.