Inter-reader variability in follicular lymphoma grading: Conventional and digital reading

• Main Authors: Gerard Lozanski, Michael Pennell, Arwa Shana′ah, Weiqiang Zhao, Amy Gewirtz, Frederick Racke, Eric Hsi, Sabrina Simpson, Claudio Mosse, Shadia Alam, Sharon Swierczynski, Robert P Hasserjian, Metin N Gurcan
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2013-01-01
• Series: Journal of Pathology Informatics
• Subjects: Centroblast; follicular lymphoma; inter-reader variability; whole-slide images
• Online Access: http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=30;epage=30;aulast=Lozanski

Context: Pathologists grade follicular lymphoma (FL) cases by selecting 10, random high power fields (HPFs), counting the number of centroblasts (CBs) in these HPFs under the microscope and then calculating the average CB count for the whole slide. Previous studies have demonstrated that there is high inter-reader variability among pathologists using this methodology in grading. Aims: The objective of this study was to explore if newly available digital reading technologies can reduce inter-reader variability. Settings and Design: In this study, we considered three different reading conditions (RCs) in grading FL: (1) Conventional (glass-slide based) to establish the baseline, (2) digital whole slide viewing, (3) digital whole slide viewing with selected HPFs. Six board-certified pathologists from five different institutions read 17 FL slides in these three different RCs. Results: Although there was relative poor consensus in conventional reading, with lack of consensus in 41.2% of cases, which was similar to previously reported studies; we found that digital reading with pre-selected fields improved the inter-reader agreement, with only 5.9% lacking consensus among pathologists. Conclusions: Digital whole slide RC resulted in the worst concordance among pathologists while digital whole slide reading selected HPFs improved the concordance. Further studies are underway to determine if this performance can be sustained with a larger dataset and our automated HPF and CB detection algorithms can be employed to further improve the concordance.