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An international 3‐center training and reading study to assess basal cell carcinoma surgical margins with ex vivo fluorescence confocal microscopy
Author(s) -
Kose Kivanc,
Fox Christi Alessi,
Rossi Anthony,
Jain Manu,
Cordova Miguel,
Dusza Stephen W.,
Ragazzi Moira,
Gardini Stefano,
Moscarella Elvira,
Diaz Alba,
Pigem Ramon,
Gonzalez Salvador,
Bennassar Antoni,
Carrera Cristina,
Longo Caterina,
Rajadhyaksha Milind,
Nehal Kishwer S.
Publication year - 2021
Publication title -
journal of cutaneous pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 75
eISSN - 1600-0560
pISSN - 0303-6987
DOI - 10.1111/cup.13980
Subject(s) - dermatopathology , dermatologic surgery , basal cell carcinoma , medicine , ex vivo , mohs surgery , margin (machine learning) , confocal , confocal microscopy , pathology , medical physics , surgical margin , radiology , in vivo , dermatology , surgery , basal cell , resection , computer science , biology , geometry , microbiology and biotechnology , mathematics , machine learning
Background Novel solutions are needed for expediting margin assessment to guide basal cell carcinoma (BCC) surgeries. Ex vivo fluorescence confocal microscopy (FCM) is starting to be used in freshly excised surgical specimens to examine BCC margins in real time. Training and educational process are needed for this novel technology to be implemented into clinic. Objective To test a training and reading process, and measure diagnostic accuracy of clinicians with varying expertise level in reading ex vivo FCM images. Methods An international three‐center study was designed for training and reading to assess BCC surgical margins and residual subtypes. Each center included a lead dermatologic/Mohs surgeon (clinical developer of FCM) and three additional readers (dermatologist, dermatopathologist, dermatologic/Mohs surgeon), who use confocal in clinical practice. Testing was conducted on 30 samples. Results Overall, the readers achieved 90% average sensitivity, 78% average specificity in detecting residual BCC margins, showing high and consistent diagnostic reading accuracy. Those with expertise in dermatologic surgery and dermatopathology showed the strongest potential for learning to assess FCM images. Limitations Small dataset, variability in mosaic quality between centers. Conclusion Suggested process is feasible and effective. This process is proposed for wider implementation to facilitate wider adoption of FCM to potentially expedite BCC margin assessment to guide surgery in real time.