Background:Cytology poses different obstacles in whole slide imaging compared to surgical pathology slides. A single focal plane suffices for most of the latter, but cytology slides are thicker, potentially requiring multiple focal planes for adequate diagnostic information. Multiple focal planes adversely impact scanning time per slide, evaluation times, and file sizes. In this pilot study, we evaluated and compared the multilayer stack method to the extended focus algorithm as an alternative which collapses multiple focal planes into a single image, retaining only focused areas from each plane.Materials and Methods:10 SurePath® cervical cytology slides were scanned at three thickness settings: 18, 24, and 30 μm. Three scanners were used: (1) Hamamatsu Nanozoomer 2.0-HT, (2) 3DHISTECH Mirax scan, and (3) Bioimagene iScan Coreo Au. The Nanozoomer and iScan utilized multilayer stacking, while the Mirax files were composited by extended focus. Scan times and file sizes were recorded, and image quality compared.Results:The Nanozoomer stacks averaged 1.58 gb and around 25 min for each slide, while the iScan stacks ranged from 6.23 to 9.3 gb and took 34-50 min to scan. The Mirax images averaged 210 mb and took 13-20 min to scan. Multilayer stack image quality from both Nanozoomer and iScan was fairly comparable. The iScan revealed significant mechanical issues that did not correspond to user settings. The Mirax images showed worrisome loss of crisp focus detail, worsening with increasing focal planes and impacting assessment of nuclear contours and chromatin detail.Conclusions:The optimal number of focal planes remains unknown for cytology. Multilayer stacks require excessive scanning time, network bandwidth, and file storage. Extended focus was evaluated as an alternative, but significant image quality issues were revealed. Further large-scale studies are needed to assess their clinical impact.
Abstract. Background: Whole slide Imaging (WSI) has been touted by many as the future of pathology, with estimates of full adoption occurring sometime in the next 5 to 15 years. While WSI devices have become increasingly capable since their inception, there has been little consideration of how WSI will be implemented and subsequently affect the workflow of high-volume histology laboratories.Methods: Histology workflow process data was collected from a high-volume histology laboratory (Massachusetts General Hospital) and a process model developed using business process management software. Computerized workflow simulations were performed and total histology process time evaluated under a number of different WSI conditions.Results: Total histology process time increased approximately 10-fold to 20-fold over baseline with the presence of one WSI robot in the histology workflow. Depending on the specifications of the WSI robot, anywhere from 9 to 14 WSI robots were required within the histology workflow to minimize the effects of WSI.Conclusions: Placing a WSI robot into the current workflow of a high-volume histology laboratory with the intent of full adoption is not feasible. Implementing WSI without making significant changes to the current workflow of the histology laboratory would prove to be both disruptive and costly to surgical pathology.
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.
Background:In 2007, our healthcare system established a clinical fellowship program in Pathology Informatics. In 2010 a core didactic course was implemented to supplement the fellowship research and operational rotations. In 2011, the course was enhanced by a formal, structured core curriculum and reading list. We present and discuss our rationale and development process for the Core Curriculum and the role it plays in our Pathology Informatics Fellowship Training Program.Materials and Methods:The Core Curriculum for Pathology Informatics was developed, and is maintained, through the combined efforts of our Pathology Informatics Fellows and Faculty. The curriculum was created with a three-tiered structure, consisting of divisions, topics, and subtopics. Primary (required) and suggested readings were selected for each subtopic in the curriculum and incorporated into a curated reading list, which is reviewed and maintained on a regular basis.Results:Our Core Curriculum is composed of four major divisions, 22 topics, and 92 subtopics that cover the wide breadth of Pathology Informatics. The four major divisions include: (1) Information Fundamentals, (2) Information Systems, (3) Workflow and Process, and (4) Governance and Management. A detailed, comprehensive reading list for the curriculum is presented in the Appendix to the manuscript and contains 570 total readings (current as of March 2012).Discussion:The adoption of a formal, core curriculum in a Pathology Informatics fellowship has significant impacts on both fellowship training and the general field of Pathology Informatics itself. For a fellowship, a core curriculum defines a basic, common scope of knowledge that the fellowship expects all of its graduates will know, while at the same time enhancing and broadening the traditional fellowship experience of research and operational rotations. For the field of Pathology Informatics itself, a core curriculum defines to the outside world, including departments, companies, and health systems considering hiring a pathology informatician, the core knowledge set expected of a person trained in the field and, more fundamentally, it helps to define the scope of the field within Pathology and healthcare in general.
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.
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