ArticleLaboratory investigation; a journal of technical methods and pathology2023
Quality Management System in Clinical Digital Pathology Operations at a Tertiary Cancer Center.
Article in Laboratory investigation; a journal of technical methods and pathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- GrandQC adaptation as an artificial intelligence tool for quantitative artifact detection in hematoxylin and eosin whole-slide images-Simulation of quality control biopsies day.Journal of pathology informatics · 2026Article
- Deployment of AI-driven automated quality control of whole-slide images in a large tertiary cancer center.Journal of pathology informatics · 2026Article
- Article
- Interobserver Variability Across Whole-Slide Imaging Systems.Archives of pathology & laboratory medicine · 2026Article
- Integration of Digital Cytology in Quality Assurance Programs for Cytopathology.Acta cytologica · 2026Review
- Digital pathology imaging artificial intelligence in cancer research and clinical trials: An NCI workshop report.Journal of pathology informatics · 2026Review
- Deep learning for digital pathology: A critical overview of methodological framework.Journal of pathology informatics · 2025Review
- From Microscopes to Monitors: Unique Opportunities and Challenges in Digital Pathology Implementation in Remote Canadian Regions.Diagnostics (Basel, Switzerland) · 2025Article
- Digital slide scanning at scale: Comparison of whole slide imaging devices in a clinical setting.Journal of pathology informatics · 2025Article
- Artificial Intelligence-Based Quality Assessment of Histopathology Whole-Slide Images within a Clinical Workflow: Assessment of 'PathProfiler' in a Diagnostic Pathology Setting.Diagnostics (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
Digital pathology workflows can improve pathology operations by allowing reliable and fast retrieval of digital images, digitally reviewing pathology slides, enabling remote work and telepathology, use of computer-aided tools, and sharing of digital images for research and educational purposes. The need for quality systems is a prerequisite for successful clinical-grade digital pathology adoption and patient safety. In this article, we describe the development of a structured digital pathology laboratory quality management system (QMS) for clinical digital pathology operations at Memorial Sloan Kettering Cancer Center (MSK). This digital pathology-specific QMS development stemmed from the gaps that were identified when MSK integrated digital pathology into its clinical practice. The digital scan team in conjunction with the Department of Pathology and Laboratory Medicine quality team developed a QMS tailored to the scanning operation to support departmental and institutional needs. As a first step, systemic mapping of the digital pathology operations identified the prescan, scan, and postscan processes; instrumentation; and staffing involved in the digital pathology operation. Next, gaps identified in quality control and quality assurance measures led to the development of standard operating procedures and training material for the different roles and workflows in the process. All digital pathology-related documents were subject to regulatory review and approval by departmental leadership. The quality essentials were developed into an extensive Digital Pathology Quality Essentials framework to specifically address the needs of the growing clinical use of digital pathology technologies. Using the unique digital experience gained at MSK, we present our recommendations for QMS for large-scale digital pathology operations in clinical settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.