Validation of whole slide imaging for primary diagnosis in surgical pathology
Open accessAbstract
CONTEXT: High-resolution scanning technology provides an opportunity for pathologists to make diagnoses directly from whole slide images (WSIs), but few studies have attempted to validate the diagnoses so obtained. OBJECTIVE: To compare WSI versus microscope slide diagnoses of previously interpreted cases after a 1-year delayed re-review ("wash-out") period. DESIGN: An a priori power study estimated that 450 cases might be needed to demonstrate noninferiority, based on a null hypothesis: "The true difference in major discrepancies between WSI and microscope slide review is greater than 4%." Slides of consecutive cases interpreted by 2 pathologists 1 year prior were retrieved from files, and alternate cases were scanned at original magnification of ×20. Each pathologist reviewed his or her cases using either a microscope or imaging application. Independent pathologists identified and classified discrepancies; an independent statistician calculated major and minor discrepancy rates for both WSI and microscope slide review of the previously interpreted cases. RESULTS: The 607 cases reviewed reflected the subspecialty interests of the 2 pathologists. Study limitations include the lack of cytopathology, hematopathology, or lymphoid cases; the case mix was not enriched with difficult cases; and both pathologists had interpreted several hundred WSI cases before the study to minimize the learning curve. The major and minor discrepancy rates for WSI were 1.65% and 2.31%, whereas rates for microscope slide reviews were 0.99% and 4.93%. CONCLUSIONS: Based on our assumptions and study design, diagnostic review by WSI was not inferior to microscope slide review (P < .001).
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“…in recognizing lesions like basal cell carcinoma (BCC), seborrheic keratosis (SK), and dermal nevi (DN), further development is needed to improve their ability to differentiate between some challenging melanocytic lesions, such as Spitz nevi, and to diagnose inflammatory conditions [2,5].”
- Authors
- Bauer, T. W., Schoenfield, L., Slaw, R. J., Yerian, L., Sun, Z., & Henricks, W. H.
- Affiliations
- Cleveland Clinic (US)
- Venue
- Archives of Pathology & Laboratory Medicine
- Published
- 2013-04
- Volume
- 137
- Issue
- 4
- Pages
- 518-524
- ISSN
- 0003-9985 (ISSN-L)
- 1543-2165
- OpenAlex
- W2078437730
- Cited by
- 155
- References
- 17
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 7 · 2023: 5 · 2022: 8 · 2021: 23 · 2020: 17 · 2019: 11 · 2018: 14 · 2017: 13 · 2016: 10 · 2015: 21 · 2014: 16 · 2013: 2
- FWCI
- 18.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Archives of Pathology & Laboratory Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
- Keywords
- whole slide imaging, digital pathology, diagnostic accuracy, non-inferiority, diagnostic discordance, surgical pathology diagnosis
- MeSH terms
- Female, Humans, Image Interpretation, Computer-Assisted, Male, Microscopy, Pathology, Surgical, Quality Assurance, Health Care, Reproducibility of Results, Observer Variation
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