I Saknite1,2, M Gill3,4,5, C Alessi-Fox6, J P Zwerner1, J S Lehman7,8, M M Shinohara9,10, R A Novoa11,12, H Chen13,14, M Byrne14, S Gonzalez5, M Ardigo15, E R Tkaczyk1,14,16. 1. Department of Dermatology, Vanderbilt University Medical Center, Nashville, TN, USA. 2. Biophotonics Laboratory, Institute of Atomic Physics and Spectroscopy, University of Latvia, Riga, Latvia. 3. SkinMedical Research and Diagnostics, PLLC, Dobbs Ferry, NY, USA. 4. Department of Pathology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA. 5. Faculty of Medicine and Health Sciences, University of Alcalá, Madrid, Spain. 6. Clinical Development, Caliber Imaging and Diagnostics Inc, Rochester, NY, USA. 7. Department of Dermatology, Mayo Clinic, Rochester, MN, USA. 8. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. 9. Division of Dermatology, Department of Medicine, University of Washington, Seattle, WA, USA. 10. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA. 11. Department of Dermatology, Stanford University, Stanford, CA, USA. 12. Department of Pathology, Stanford University, Stanford, CA, USA. 13. Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA. 14. Vanderbilt-Ingram Cancer Center, Nashville, TN, USA. 15. San Gallicano Dermatological Institute - IRCCS, Rome, Italy. 16. Dermatology Service and Research Service, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA.
Abstract
BACKGROUND: The reliability to non-invasively identify features of inflammatory dermatoses by reflectance confocal microscopy (RCM) remains unknown. Lack of formal training among RCM readers can result in inconsistent assessments, limiting clinical utility. Specific consensus terminology with representative images is necessary to ensure consistent feature-level interpretation among RCM readers. OBJECTIVES: (1) Develop a glossary with representative images of RCM features of cutaneous acute graft-versus-host disease (aGVHD) for consistent interpretation among observers, (2) assess the interobserver reproducibility among RCM readers using the glossary, and (3) determine the concordance between RCM and histopathology for aGVHD features. METHODS: Through an iterative process of refinement and discussion among five international RCM experts, we developed a glossary with representative images of RCM features of aGVHD. From April to November 2018, patients suspected of aGVHD were imaged with RCM and subsequently biopsied. 17 lesions from 12 patients had clinically and pathologically confirmed cutaneous aGVHD. For each of these lesions, four dermatopathologists and four RCM readers independently evaluated the presence of aGVHD features in scanned histopathology slides and 1.5 × 1.5 mm RCM submosaics at 4 depths (blockstacks) respectively. RCM cases were adjudicated by a fifth RCM expert. Interobserver reproducibility was calculated by mean pairwise difference (U statistic). Concordance between modalities was determined by fraction of assignments with agreement. RESULTS: We present a glossary with representative images of 18 aGVHD features by RCM. The average interobserver reproducibility among RCM readers (75%, confidence interval, CI: 71-79%) did not differ significantly from dermatopathologists (80%, 76-85%). The concordance between RCM and histopathology was 59%. CONCLUSIONS: By using the glossary, the interobserver reproducibility among RCM readers was similar to the interobserver reproducibility among dermatopathologists. There was reasonable concordance between RCM and histopathology to visualize aGVHD features. The implementation of RCM can now be advanced in a variety of inflammatory conditions with a validated glossary and representative image set.
BACKGROUND: The reliability to non-invasively identify features of inflammatory dermatoses by reflectance confocal microscopy (RCM) remains unknown. Lack of formal training among RCM readers can result in inconsistent assessments, limiting clinical utility. Specific consensus terminology with representative images is necessary to ensure consistent feature-level interpretation among RCM readers. OBJECTIVES: (1) Develop a glossary with representative images of RCM features of cutaneous acute graft-versus-host disease (aGVHD) for consistent interpretation among observers, (2) assess the interobserver reproducibility among RCM readers using the glossary, and (3) determine the concordance between RCM and histopathology for aGVHD features. METHODS: Through an iterative process of refinement and discussion among five international RCM experts, we developed a glossary with representative images of RCM features of aGVHD. From April to November 2018, patients suspected of aGVHD were imaged with RCM and subsequently biopsied. 17 lesions from 12 patients had clinically and pathologically confirmed cutaneous aGVHD. For each of these lesions, four dermatopathologists and four RCM readers independently evaluated the presence of aGVHD features in scanned histopathology slides and 1.5 × 1.5 mm RCM submosaics at 4 depths (blockstacks) respectively. RCM cases were adjudicated by a fifth RCM expert. Interobserver reproducibility was calculated by mean pairwise difference (U statistic). Concordance between modalities was determined by fraction of assignments with agreement. RESULTS: We present a glossary with representative images of 18 aGVHD features by RCM. The average interobserver reproducibility among RCM readers (75%, confidence interval, CI: 71-79%) did not differ significantly from dermatopathologists (80%, 76-85%). The concordance between RCM and histopathology was 59%. CONCLUSIONS: By using the glossary, the interobserver reproducibility among RCM readers was similar to the interobserver reproducibility among dermatopathologists. There was reasonable concordance between RCM and histopathology to visualize aGVHD features. The implementation of RCM can now be advanced in a variety of inflammatory conditions with a validated glossary and representative image set.
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