SynthesisFrontiers in oncology2022
Technical and Diagnostic Issues in Whole Slide Imaging Published Validation Studies.
Synthesis in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- 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
- A comparative analysis of deep learning models for disease classification in multi-organ histopathological images.Scientific reports · 2026Article
- Mobile device smartphones for intraoperative diagnosis at the University Hospital Trust of Modena/UNIMORE: from validation process to costs analysis.Diagnostic pathology · 2026Article
- Artificial intelligence‑based quantitative analysis of hepatic fibrosis in carbon tetrachloride-induced mouse model of metabolic dysfunction-associated steatohepatitis.Toxicological research · 2026Article
- Digital Pathology Displays Under Pressure: Benchmarking Performance Across Market Grades.Journal of imaging informatics in medicine · 2025Article
- A dual-stream deep learning framework for skin cancer classification using histopathological-inherited and vision-based feature extraction.Scientific reports · 2025Article
- Automating Colon Polyp Classification in Digital Pathology by Evaluation of a "Machine Learning as a Service" AI Model: Algorithm Development and Validation Study.JMIR formative research · 2025Article
- Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers.BMC gastroenterology · 2025Article
- Computational pathology for breast cancer: Where do we stand for prognostic applications?Breast (Edinburgh, Scotland) · 2025Review
- An update on applications of digital pathology: primary diagnosis; telepathology, education and research.Diagnostic pathology · 2025Review
- Artificial Intelligence in Breast Cancer Diagnosis and Treatment: Advances in Imaging, Pathology, and Personalized Care.Life (Basel, Switzerland) · 2024Review
- Digital pathology structure and deployment in Veneto: a proof-of-concept study.Virchows Archiv : an international journal of pathology · 2024Article
- Digital pathology, deep learning, and cancer: a narrative review.Translational cancer research · 2024Review
- Artificial intelligence-based triage of large bowel biopsies can improve workflow.Journal of pathology informatics · 2023Article
- Standard operating procedures for biobank in oncology.Frontiers in molecular biosciences · 2022Article
- Artificial intelligence in head and neck cancer diagnosis.Journal of pathology informatics · 2022Review
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Digital pathology with whole-slide imaging (WSI) has many potential clinical and non-clinical applications. In the past two decades, despite significant advances in WSI technology adoption remains slow for primary diagnosis. The aim of this study was to identify common pitfalls of WSI reported in validation studies and offer measures to overcome these challenges. Methods: A systematic search was conducted in the electronic databases Pubmed-MEDLINE and Embase. Inclusion criteria were all validation studies designed to evaluate the feasibility of WSI for diagnostic clinical use in pathology. Technical and diagnostic problems encountered with WSI in these studies were recorded. Results: A total of 45 studies were identified in which technical issues were reported in 15 (33%), diagnostic issues in 8 (18%), and 22 (49%) reported both. Key technical problems encompassed slide scan failure, prolonged time for pathologists to review cases, and a need for higher image resolution. Diagnostic challenges encountered were concerned with grading dysplasia, reliable assessment of mitoses, identification of microorganisms, and clearly defining the invasive front of tumors. Conclusion: Despite technical advances with WSI technology, some critical concerns remain that need to be addressed to ensure trustworthy clinical diagnostic use. More focus on the quality of the pre-scanning phase and training of pathologists could help reduce the negative impact of WSI technical difficulties. WSI also seems to exacerbate specific diagnostic tasks that are already challenging among pathologists even when examining glass slides with conventional light microscopy.
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