Whole slide image with image analysis of atypical bile duct brushing: Quantitative features predictive of malignancy

Abstract

Background:Whole slide images (WSIs) involve digitally capturing glass slides for microscopic computer-based viewing and these are amenable to quantitative image analysis. Bile duct (BD) brushing can show morphologic features that are categorized as indeterminate for malignancy. The study aims to evaluate quantitative morphologic features of atypical categories of BD brushing by WSI analysis for the identification of criteria predictive of malignancy.Materials and Methods:Over a 3-year period, BD brush specimens with indeterminate diagnostic categorization (atypical to suspicious) were subjected to WSI analysis. Ten well-visualized groups with morphologic atypical features were selected per case and had the quantitative analysis performed for group area, individual nuclear area, the number of nuclei per group, N: C ratio and nuclear size differential.Results:There were 28 cases identified with 17 atypical and 11 suspicious. The average nuclear area was 63.7 µm2 for atypical and 80.1 µm2 for suspicious (+difference 16.4 µm2; P = 0.002). The nuclear size differential was 69.7 µm2 for atypical and 88.4 µm2 for suspicious (+difference 18.8 µm2; P = 0.009). An average nuclear area >70 µm2 had a 3.2 risk ratio for suspicious categorization.Conclusion:The quantitative criteria findings as measured by image analysis on WSI showed that cases categorized as suspicious had more nuclear size pleomorphism (+18.8 µm2) and larger nuclei (+16.4 µm2) than those categorized as atypical. WSI with morphologic image analysis can demonstrate quantitative statistically significant differences between atypical and suspicious BD brushings and provide objective criteria that support the diagnosis of carcinoma.

Automated analysis of computerized morphological features of cell clusters associated with malignancy on bile duct brushing whole slide images

“…Collins et al manually selected 10 well-visualized clusters and evaluated computational features such as individual nuclear area, nuclear count per cluster, N:C ratio, and nuclear size differential. 17 In this study, we presented a computerized cytomorphological and textural analysis of cell clusters extracted from WSIs of digitized BDBs to quantify the morphological differences between benign and malignant presentations. We were able to identify five nuclear shape and five aggregate texture morphological features that best distinguish benign clusters from malignant clusters in 58 patients and successfully validate those features in 66 patients.…”

“…A selected few have performed analysis on WSIs of atypical and suspicious BDBs. Collins et al manually selected 10 well‐visualized clusters and evaluated computational features such as individual nuclear area, nuclear count per cluster, N:C ratio, and nuclear size differential 17 …”

“…In particular reference to whole slide image (WSI) analysis, Collins et al . evaluated a number of computational features on WSIs such as individual nuclear area, the number of nuclei per group, N:C ratio, and nuclear size differential 17 …”

“…evaluated a number of computational features on WSIs such as individual nuclear area, the number of nuclei per group, N:C ratio, and nuclear size differential. 17 …”

The role of informatics in patient‐centered care and personalized medicine

“…They can be used to identify rare events (eg, count mitoses or detect micrometastases in lymph nodes), quantify stains (eg, most commonly breast biomarkers), measure various features (eg, extent of tissue fibrosis), and analyze spatial patterns. To our knowledge to date, only limited studies have applied image analysis to help resolve challenging cytology problems, such as better diagnosed atypical cases . Unfortunately, there currently are limited applications approved by the US Food and Drug Administration available for routine clinical practice.…”