Background: Synoptic pathology reports can serve as a rich source of cancer information, particularly when the content is available as discrete electronic data fields. Our institution generates such reports as part of a province wide program in Ontario but the resulting data is not easily extracted and analyzed at the local level. Methods: A low cost system was developed using the open sourced and freely available R scripting/data analysis environment to parse synoptic report results into a dataframe and perform basic summary statistics. Results: As a pilot project text reports from 427 prostate needle biopsies were successfully read into R and the data elements split out and converted into appropriated data classes for analysis. Conclusion: This approach provides a simple solution at minimal cost that can make discrete synoptic report data readily available for quality assurance and research activities.

Introduction: Smartphone applications (apps) have become increasingly prevalent in medicine. Due to most pathologists, pathology trainees, technicians, and medical students use smartphones; apps can be a different way for general pathology education. “General pathologist-helper (GP-HELPER)” is a novel app developed as a reference tool in general pathology and especially for general pathologists, developed for Android and iOS platforms. Materials and Methods: “GP-HELPER,” was created using Mobincube website platform. This tool also integrates “FORUM GP-HELPER,” an external website created using Miarroba website (http://forum-gp-helper.mboards.com) and “COMMUNITY GP-HELPER” a multichannel chat created using Chatango website platform. Results: The application was released in July 2015, and it is been periodically updated since then. The app has permanent information (offline data) about different pathology protocols (TNM latest edition, protocols regarding management of tumors of unknown primary origin, and flowcharts for some of the most difficult tumors to diagnose) and a database with more than 5000 immunohistochemistry results from different tumors. Online data have links to more than 1100 reference pathology video lectures, 250 antibodies information, more than 70 pathology association websites, 46 pathology providers, and 78 outstanding pathology journal websites. Besides this information, the app has two interactive places such as “FORUM GP-HELPER” and “COMMUNITY GP-HELPER” that let users to stay in touch everywhere and every time. Expert consult section is also available. Conclusions: “GP-HELPER” pretends to integrate offline and online data about pathology with two interactive external places in order to represent a reference tool for general pathologists and associate members.

Background: The constant growth in the body of knowledge in medicine requires pathologists and pathology trainees to engage in continuing education. Providing them with equitable access to efficient and effective forms of education in pathology (especially in remote and rural settings) is important, but challenging. Methods: We developed three pilot cytopathology virtual microscopy adaptive tutorials (VMATs) to explore a novel adaptive E-learning platform (AeLP) which can incorporate whole slide images for pathology education. We collected user feedback to further develop this educational material and to subsequently deploy randomized trials in both pathology specialist trainee and also medical student cohorts. Cytopathology whole slide images were first acquired then novel VMATs teaching cytopathology were created using the AeLP, an intelligent tutoring system developed by Smart Sparrow. The pilot was run for Australian pathologists and trainees through the education section of Royal College of Pathologists of Australasia website over a period of 9 months. Feedback on the usability, impact on learning and any technical issues was obtained using 5-point Likert scale items and open-ended feedback in online questionnaires. Results: A total of 181 pathologists and pathology trainees anonymously attempted the three adaptive tutorials, a smaller proportion of whom went on to provide feedback at the end of each tutorial. VMATs were perceived as effective and efficient E-learning tools for pathology education. User feedback was positive. There were no significant technical issues. Conclusion: During this pilot, the user feedback on the educational content and interface and the lack of technical issues were helpful. Large scale trials of similar online cytopathology adaptive tutorials were planned for the future.

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: Pathology data contained within the electronic health record (EHR), and laboratory information system (LIS) of hospitals represents a potentially powerful resource to improve clinical care. However, existing reporting tools within commercial EHR and LIS software may not be able to efficiently and rapidly mine data for quality improvement and research applications. Materials and Methods: We present experience using a data warehouse produced collaboratively between an academic medical center and a private company. The data warehouse contains data from the EHR, LIS, admission/discharge/transfer system, and billing records and can be accessed using a self-service data access tool known as Starmaker. The Starmaker software allows users to use complex Boolean logic, include and exclude rules, unit conversion and reference scaling, and value aggregation using a straightforward visual interface. More complex queries can be achieved by users with experience with Structured Query Language. Queries can use biomedical ontologies such as Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine. Result: We present examples of successful searches using Starmaker, falling mostly in the realm of microbiology and clinical chemistry/toxicology. The searches were ones that were either very difficult or basically infeasible using reporting tools within the EHR and LIS used in the medical center. One of the main strengths of Starmaker searches is rapid results, with typical searches covering 5 years taking only 1-2 min. A "Run Count" feature quickly outputs the number of cases meeting criteria, allowing for refinement of searches before downloading patient-identifiable data. The Starmaker tool is available to pathology residents and fellows, with some using this tool for quality improvement and scholarly projects. Conclusion: A data warehouse has significant potential for improving utilization of clinical pathology testing. Software that can access data warehouse using a straightforward visual interface can be incorporated into pathology training programs.

Introduction: Smartphone applications in medicine are becoming increasingly prevalent. Given that most pathologists and pathology trainees today use smartphones, an obvious modality for pathology education is through smartphone applications. "MyDermPath" is a novel smartphone application that was developed as an interactive reference tool for dermatology and dermatopathology, available for iOS and Android. Materials and Methods: "MyDermPath" was developed using Apple Xcode and Google Android SDK. Dermatology images (static and virtual slides) were annotated and configured into an algorithmic format. Each image comprised educational data (diagnosis, clinical information, histopathology, special stains, differential diagnosis, clinical management, linked PubMed references). Added functionality included personal note taking, pop quiz, and image upload capabilities. A website was created (http://mydermpath.com) to mirror the app. Results: The application was released in August 2011 and updated in November 2013. More than 1,100 reference diagnoses, with over 2,000 images are available via the application and website. The application has been downloaded approximately 14,000 times. The application is available for use on iOS and Android platforms. Conclusions: Smartphone applications have tremendous potential for advancing pathology education. "MyDermPath" represents an interactive reference tool for dermatology and dermatopathologists.

Background: The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented. Materials and Methods: To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest. Results: We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs. Conclusions: The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology.

Background: Telepathology practice across international borders has become increasingly popular. Our telepathology consultation service with a laboratory in China was hampered by latency issues when viewing whole slide images. Objective: The aim was to explore data transfer solutions to improve the viewing experience of digital consult cases. Methods: Whole slide image files residing on a server in China were transferred to our data center in the USA using an open source product (Fast Data Transfer). A faster more automated commercial high speed file transfer software solution (Aspera) was also tested. Results: Transferring files with the open source product provided transfer speeds of 2-3 Mbps, but suffered from intermittent dropped connections. Employing commercial software permitted more reliable transmission of digital files with 75-100 Mbps transfer speeds. Conclusions: Successful global telepathology requires dedicated image management. Transfer of files to local servers by employing high speed data transfer tools helped overcome network latency issues, improved the overall turn-around time of digital consultations, and enhanced the viewing experience for end-user digital consultants.

Requisition storage and retrieval are an integral part of the outpatient laboratory testing process. It is frequently necessary to review an original requisition to confirm the ordering physician, patient demographics, diagnostic information, and requested tests. Manual retrieval of a paper requisition is time-consuming and tedious. Although commercial solutions exist for the scanning and archiving of barcoded paper requisitions, the tools to accomplish this are freely available from the open source software community. We present a simple dedicated piece of software, Reqscan, for scanning patient laboratory requisitions, finding all barcode information, and saving the requisition as a portable document format named according the barcode(s) found. This Python application offers a simple solution to patient requisition digitization. Reqscan has been successfully tested and implemented into routine practice for storage and retrieval of outpatient requisitions at St. Paul's Hospital, Department of Pathology and Laboratory Medicine in Vancouver, British Columbia, Canada.

Introduction: For decades cellular differentials have been generated exclusively on analog tabletop cell counters. With the advent of tablet computers, digital cell counters - in the form of mobile applications ("apps") - now represent an alternative to analog devices. However, app-based counters have not been widely adopted by clinical laboratories, perhaps owing to a presumed decrease in count accuracy related to the lack of tactile feedback inherent in a touchscreen interface. We herein provide the first systematic evidence that digital cell counters function similarly to standard tabletop units. Methods: We developed an app-based cell counter optimized for use in the clinical laboratory setting. Paired counts of 188 peripheral blood smears and 62 bone marrow aspirate smears were performed using our app-based counter and a standard analog device. Differences between paired data sets were analyzed using the correlation coefficient, Student's t-test for paired samples and Bland-Altman plots. Results: All counts showed excellent agreement across all users and touch screen devices. With the exception of peripheral blood basophils (r = 0.684), differentials generated for the measured cell categories within the paired data sets were highly correlated (all r ≥ 0.899). Results of paired t-tests did not reach statistical significance for any cell type (all P > 0.05), and Bland-Altman plots showed a narrow spread of the difference about the mean without evidence of significant outliers. Conclusions: Our analysis suggests that no systematic differences exist between cellular differentials obtained via app-based or tabletop counters and that agreement between these two methods is excellent.