Background: Whole slide imaging (WSI) using high-resolution scanners is gaining acceptance as a platform for consultation as well as for frozen section (FS) evaluation in surgical pathology. We report results of an intra-observer concordance study comparing evaluation of WSI of scanned FS microscope slides with the original interpretation of the same microscope slides after an average lag time of approximately 1-year. Methods: A total of 70 FS cases (148 microscope slides) originally interpreted by 2 pathologists were scanned at ×20 using Aperio CS2 scanner (Leica Biosystems, San Diego, CA, USA). Reports were redacted such that the study pathologists reviewed images using eSlide Manager Healthcare Network application (Leica Biosystems) accompanied by the same clinical information available at the time of original FS evaluation. Discrepancies between the original FS diagnosis and WSI diagnosis were categorized as major (impacted patient care) or minor (no impact on patient care). Results: Lymph nodes, margins for head and neck cancer resections, and arthroplasty specimens to exclude infection, were the most common FS specimens. The average wash-out interval was 380 days (range: 303–466 days). There was one major discrepancy (1.4% of 70 cases) where the original FS was interpreted as severe squamous dysplasia, and the WSI FS diagnosis was mild dysplasia. There were two minor discrepancies; one where the original FS was called focal moderate squamous dysplasia and WSI FS diagnosis was negative for dysplasia. The second case was an endometrial adenocarcinoma that was originally interpreted as Federation of Gynecology and Obstetrics (FIGO) Grade I, while the WSI FS diagnosis was FIGO Grade II. Conclusions: These findings validate and support the use of WSI to provide interpretation of FS in our network of affiliated hospitals and ambulatory surgery centers.

Background: Current histologic methods for diagnosis are limited by intra- and inter-observer variability. Immunohistochemistry (IHC) methods are frequently used to assess biomarkers to aid diagnoses, however, IHC staining is variable and nonlinear and the manual interpretation is subjective. Furthermore, the biomarkers assessed clinically are typically biomarkers of epithelial cell processes. Tumors and premalignant tissues are not composed only of epithelial cells but are interacting systems of multiple cell types, including various stromal cell types that are involved in cancer development. The complex network of the tissue system highlights the need for a systems biology approach to anatomic pathology, in which quantification of system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making. Aims: Here, we describe a quantitative, multiplexed biomarker imaging approach termed TissueCypher™ that applies systems biology to anatomic pathology. Applications of TissueCypher™ in understanding the tissue system of Barrett's esophagus (BE) and the potential use as an adjunctive tool in the diagnosis of BE are described. Patients and Methods: The TissueCypher™ Image Analysis Platform was used to assess 14 epithelial and stromal biomarkers with known diagnostic significance in BE in a set of BE biopsies with nondysplastic BE with reactive atypia (RA, n = 22) and Barrett's with high-grade dysplasia (HGD, n = 17). Biomarker and morphology features were extracted and evaluated in the confirmed BE HGD cases versus the nondysplastic BE cases with RA. Results: Multiple image analysis features derived from epithelial and stromal biomarkers, including immune biomarkers and morphology, showed significant differences between HGD and RA. Conclusions: The assessment of epithelial cell abnormalities combined with an assessment of cellular changes in the lamina propria may serve as an adjunct to conventional pathology in the assessment of BE.

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.

Genomic, proteomic, epigenomic, and other "omic" data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requiring innovative approaches to translate such data into patient care. Here, we outline a conceptual model for the application of omic data in the clinical context, called "the omic funnel." This model parallels the classic "Data, Information, Knowledge, Wisdom pyramid" and adds context for how to move between each successive layer. Its goal is to allow informaticians, researchers, and clinicians to approach the problem of translating omic data from bench to bedside, by using discrete steps with clearly defined needs. Such an approach can facilitate the development of modular and interoperable software that can bring precision medicine into widespread practice.