Rabbit monoclonal E-cadherin antibody: A cost-effective alternative to mouse monoclonal antibody in distinguishing ductal carcinoma in situ from lobular carcinoma in situ.

Rabbit monoclonal antibody (RabMAb) demonstrates higher sensitivity without sacrificing specificity than mouse monoclonal antibody (MMAb). MMAb against E-cadherin stain is heavily utilized in distinguishing ductal carcinoma in situ (DCIS) from lobular carcinoma in situ (LCIS). We aimed to compare the E-cadherin stain using RabMAb vs MMAb in distinguishing DCIS from LCIS. One hundred and seventeen in situ breast carcinomas (55 DCIS, 58 LCIS, and 4 DCIS and LCIS) were studied. Sections from a representative block of each were stained with RabMAb [EP700Y] and MMAb [36B5]. Scanned images of stained slides were compared in tandem. All DCIS cases (59/59) showed comparable staining by RabMAb and MMAb. Comparable staining was also observed in all but one case of LCIS (61/62; 98%). One case of pleomorphic LCIS showed mostly complete, weak to moderately intense membranous staining with RabMAb and fragmented, weak membranous staining with MMAb. Consistently better staining quality was observed in slides stained by RabMAb vs MMAb. RabMAb and MMAb against E-cadherin were diagnostically equivalent with the exception of one case where RabMAb may have led to diagnostic misinterpretation. However, the not insignificant cost savings and easier interpretation using RabMAb may justify the risk of misinterpretation of increased staining in rare cases, largely avertable with proper training.

Performance of Automated Classification of Diagnostic Entities in Dermatopathology Validated on Multisite Data Representing the Real-World Variability of Pathology Workload.

CONTEXT.­: More people receive a diagnosis of skin cancer each year in the United States than all other cancers combined. Many patients around the globe do not have access to highly trained dermatopathologists, whereas some biopsy diagnoses of patients who do have access result in disagreements between such specialists. Mechanomind has developed software based on a deep-learning algorithm to classify 40 different diagnostic dermatopathology entities to improve diagnostic accuracy and to enable improvements in turnaround times and effort allocation. OBJECTIVE.­: To assess the value of machine learning for microscopic tissue evaluation in dermatopathology. DESIGN.­: A retrospective study comparing diagnoses of hematoxylin and eosin-stained glass slides rendered by 2 senior board-certified pathologists not involved in algorithm creation with the machine learning algorithm's classification was conducted. A total of 300 glass slides (1 slide per patient's case) from 4 hospitals in the United States and Africa with common variations in tissue preparation, staining, and scanning methods were included in the study. RESULTS.­: The automated algorithm demonstrated sensitivity of 89 of 91 (97.8%), 107 of 107 (100%), and 101 of 102 (99%), as well as specificity of 204 of 209 (97.6%), 189 of 193 (97.9%), and 198 of 198 (100%) while identifying melanoma, nevi, and basal cell carcinoma in whole slide images, respectively. CONCLUSIONS.­: Appropriately trained deep learning image analysis algorithms demonstrate high specificity and high sensitivity sufficient for use in screening, quality assurance, and workload distribution in anatomic pathology.

Proceedings of the Association for Pathology Informatics Bootcamp 2022.

The Pathology Informatics Bootcamp, held annually at the Pathology Informatics Summit, provides pathology trainees with essential knowledge in the rapidly evolving field of Pathology Informatics. With a focus on data analytics, data science, and data management in 2022, the bootcamp addressed the growing importance of data analysis in pathology and laboratory medicine practice. The expansion of data-related subjects in Pathology Informatics Essentials for Residents (PIER) and the Clinical Informatics fellowship examinations highlights the increasing significance of these skills in pathology practice in particular and medicine in general. The curriculum included lectures on databases, programming, analytics, machine learning basics, and specialized topics like anatomic pathology data analysis and dashboarding.

Organizational preparedness for the use of large language models in pathology informatics.

In this paper, we consider the current and potential role of the latest generation of Large Language Models (LLMs) in medical informatics, particularly within the realms of clinical and anatomic pathology. We aim to provide a thorough understanding of the considerations that arise when employing LLMs in healthcare settings, such as determining appropriate use cases and evaluating the advantages and limitations of these models. Furthermore, this paper will consider the infrastructural and organizational requirements necessary for the successful implementation and utilization of LLMs in healthcare environments. We will discuss the importance of addressing education, security, bias, and privacy concerns associated with LLMs in clinical informatics, as well as the need for a robust framework to overcome regulatory, compliance, and legal challenges.

HL7 CDA implementation guide for structured anatomic pathology reports methodology and tools.

UNLABELLED: Anatomic pathology reports (APR) provide diagnostic and prognostic information crucial to patient care, clinical research and epidemiology. Currently, it is difficult to collect and exchange APR data between different healthcare organizations at an international level. OBJECTIVE: IHE and HL7 anatomic pathology joint efforts aim at providing a methodology and tools to define an international HL7 "Clinical Document Architecture" (CDA) implementation guide for APRs and especially in the domain of cancer. METHODS: A four-step methodology is employed, consisting of comparing existing clinical model of APRs originating from different countries; deriving consensus-based clinical models (Delphi technique); providing the corresponding HL7 CDA implementation guide ("CDA templates") and validating these templates. RESULTS: International experts defined HL7 CDA implementation guides for breast and colon cancer APRs within an IHE content profile. CDA templates include required data elements, as well as optional ones, that can be further specified as required in national extensions. CONCLUSION: This study demonstrates that it is possible to define an international HL7 CDA implementation guide for cancer APRs. Further efforts are needed to provide CDA templates for approximately 60 other cancer APRs dedicated to different organs, diagnoses, and procedures as well as for APRs of non neoplastic pathologies. The methodology is not confined to APRs and could be applied to clinical documents of any type.

Ordo ab Chao: framework for an integrated disease report.

CONTEXT: The volume of information that must be assimilated to appropriately manage patients with complex or chronic disease can make this task difficult because of the number of data points, their variable temporal availability, and the fact that they may reside in different systems or even institutions. OBJECTIVE .- To outline a framework for building an integrated disease report (IDR) that takes advantage of the capabilities of electronic reporting to create a single, succinct, interpretative report comprising all disease pertinent data. DESIGN: Disease pertinent data of an IDR include pathology results, laboratory and radiology data, pathologic correlations, risk profiles, and therapeutic implications. We used cancer herein as a representative process for proposing what is, to our knowledge, the first example of standardized guidelines for such a report. The IDR was defined as a modular, dynamic, electronic summary of the most current state of a patient in regard to a particular illness such as lung cancer or diabetes, which includes all information relevant for patient management. RESULTS: We propose the following 11 core data concepts that an IDR should include: patient identification; patient demographics; disease, diagnosis, and prognosis; tumor board dispositions and decisions; graphic timeline; preresection workup and therapy; resection workup; interpretative comment summarizing pertinent findings; biobanking data; postresection workup; and disease and patient status at follow-up. CONCLUSIONS: A well-executed IDR should improve patient care and efficiency for health care team members. It would demonstrate the added value of pathology interpretation and likely contribute to a reduction in errors and improved patient safety by decreasing the risk that important data will be overlooked.

The ongoing evolution of the core curriculum of a clinical fellowship in pathology informatics.

The Partners HealthCare system's Clinical Fellowship in Pathology Informatics (Boston, MA, USA) faces ongoing challenges to the delivery of its core curriculum in the forms of: (1) New classes of fellows annually with new and varying educational needs and increasingly fractured, enterprise-wide commitments; (2) taxing electronic health record (EHR) and laboratory information system (LIS) implementations; and (3) increasing interest in the subspecialty at the academic medical centers (AMCs) in what is a large health care network. In response to these challenges, the fellowship has modified its existing didactic sessions and piloted both a network-wide pathology informatics lecture series and regular "learning laboratories". Didactic sessions, which had previously included more formal discussions of the four divisions of the core curriculum: Information fundamentals, information systems, workflow and process, and governance and management, now focus on group discussions concerning the fellows' ongoing projects, updates on the enterprise-wide EHR and LIS implementations, and directed questions about weekly readings. Lectures are given by the informatics faculty, guest informatics faculty, current and former fellows, and information systems members in the network, and are open to all professional members of the pathology departments at the AMCs. Learning laboratories consist of small-group exercises geared toward a variety of learning styles, and are driven by both the fellows and a member of the informatics faculty. The learning laboratories have created a forum for discussing real-time and real-world pathology informatics matters, and for incorporating awareness of and timely discussions about the latest pathology informatics literature. These changes have diversified the delivery of the fellowship's core curriculum, increased exposure of faculty, fellows and trainees to one another, and more equitably distributed teaching responsibilities among the entirety of the pathology informatics asset in the network. Though the above approach has been in place less than a year, we are presenting it now as a technical note to allow for further discussion of evolving educational opportunities in pathology informatics and clinical informatics in general, and to highlight the importance of having a flexible fellowship with active participation from its fellows.

Clinical fellowship training in pathology informatics: A program description.

BACKGROUND: In 2007, our healthcare system established a clinical fellowship program in pathology informatics. In 2011, the program benchmarked its structure and operations against a 2009 white paper "Program requirements for fellowship education in the subspecialty of clinical informatics", endorsed by the Board of the American Medical Informatics Association (AMIA) that described a proposal for a general clinical informatics fellowship program. METHODS: A group of program faculty members and fellows compared each of the proposed requirements in the white paper with the fellowship program's written charter and operations. The majority of white paper proposals aligned closely with the rules and activities in our program and comparison was straightforward. In some proposals, however, differences in terminology, approach, and philosophy made comparison less direct, and in those cases, the thinking of the group was recorded. After the initial evaluation, the remainder of the faculty reviewed the results and any disagreements were resolved. RESULTS: The most important finding of the study was how closely the white paper proposals for a general clinical informatics fellowship program aligned with the reality of our existing pathology informatics fellowship. The program charter and operations of the program were judged to be concordant with the great majority of specific white paper proposals. However, there were some areas of discrepancy and the reasons for the discrepancies are discussed in the manuscript. CONCLUSIONS: After the comparison, we conclude that the existing pathology informatics fellowship could easily meet all substantive proposals put forth in the 2009 clinical informatics program requirements white paper. There was also agreement on a number of philosophical issues, such as the advantages of multiple fellows, the need for core knowledge and skill sets, and the need to maintain clinical skills during informatics training. However, there were other issues, such as a requirement for a 2-year fellowship and for informatics fellowships to be done after primary board certification, that pathology should consider carefully as it moves toward a subspecialty status and board certification.

Different tracks for pathology informatics fellowship training: Experiences of and input from trainees in a large multisite fellowship program.

BACKGROUND: Pathology Informatics is a new field; a field that is still defining itself even as it begins the formalization, accreditation, and board certification process. At the same time, Pathology itself is changing in a variety of ways that impact informatics, including subspecialization and an increased use of data analysis. In this paper, we examine how these changes impact both the structure of Pathology Informatics fellowship programs and the fellows' goals within those programs. MATERIALS AND METHODS: As part of our regular program review process, the fellows evaluated the value and effectiveness of our existing fellowship tracks (Research Informatics, Clinical Two-year Focused Informatics, Clinical One-year Focused Informatics, and Clinical 1 + 1 Subspecialty Pathology and Informatics). They compared their education, informatics background, and anticipated career paths and analyzed them for correlations between those parameters and the fellowship track chosen. All current and past fellows of the program were actively involved with the project. RESULTS: Fellows' anticipated career paths correlated very well with the specific tracks in the program. A small set of fellows (Clinical - one or two year - Focused Informatics tracks) anticipated clinical careers primarily focused in informatics (Director of Informatics). The majority of the fellows, however, anticipated a career practicing in a Pathology subspecialty, using their informatics training to enhance that practice (Clinical 1 + 1 Subspecialty Pathology and Informatics Track). Significantly, all fellows on this track reported they would not have considered a Clinical Two-year Focused Informatics track if it was the only track offered. The Research and the Clinical One-year Focused Informatics tracks each displayed unique value for different situations. CONCLUSIONS: It seems a "one size fits all" fellowship structure does not fit the needs of the majority of potential Pathology Informatics candidates. Increasingly, these fellowships must be able to accommodate the needs of candidates anticipating a wide range of Pathology Informatics career paths, be able to accommodate Pathology's increasingly subspecialized structure, and do this in a way that respects the multiple fellowships needed to become a subspecialty pathologist and informatician. This is further complicated as Pathology Informatics begins to look outward and takes its place in the growing, and still ill-defined, field of Clinical Informatics, a field that is not confined to just one medical specialty, to one way of practicing medicine, or to one way of providing patient care.

Pathology informatics fellowship retreats: The use of interactive scenarios and case studies as pathology informatics teaching tools.

BACKGROUND: Last year, our pathology informatics fellowship added informatics-based interactive case studies to its existing educational platform of operational and research rotations, clinical conferences, a common core curriculum with an accompanying didactic course, and national meetings. METHODS: The structure of the informatics case studies was based on the traditional business school case study format. Three different formats were used, varying in length from short, 15-minute scenarios to more formal multiple hour-long case studies. Case studies were presented over the course of three retreats (Fall 2011, Winter 2012, and Spring 2012) and involved both local and visiting faculty and fellows. RESULTS: Both faculty and fellows found the case studies and the retreats educational, valuable, and enjoyable. From this positive feedback, we plan to incorporate the retreats in future academic years as an educational component of our fellowship program. CONCLUSIONS: Interactive case studies appear to be valuable in teaching several aspects of pathology informatics that are difficult to teach in more traditional venues (rotations and didactic class sessions). Case studies have become an important component of our fellowship's educational platform.

Image microarrays (IMA): Digital pathology's missing tool.

INTRODUCTION: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. METHODS: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. RESULTS: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. CONCLUSION: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development.

A novel class of laboratory middleware. Promoting information flow and improving computerized provider order entry.

A central duty of the laboratory is to inform clinicians about the availability and usefulness of laboratory testing. In this report, we describe a new class of laboratory middleware that connects the traditional clinical laboratory information system with the rest of the enterprise, facilitating information flow about testing services. We demonstrate the value of this approach in efficiently supporting an inpatient order entry application. We also show that order entry monitoring and iterative middleware updates can enhance ordering efficiency and promote improved ordering practices. Furthermore, we demonstrate the value of algorithmic approaches to improve the accuracy and completeness of laboratory test searches. We conclude with a discussion of design recommendations for middleware applications and discuss the potential role of middleware as a sharable, centralized repository of laboratory test information.