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      Integration and acceleration of virtual microscopy as the key to successful implementation into the routine diagnostic process

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          Abstract

          Background

          The virtual microscopy is widely accepted in Pathology for educational purposes and teleconsultation but is far from the routine use in surgical pathology due to the technical requirements and some limitations. A technical problem is the limited bandwidth of a usual network and the delayed transmission rate and presentation time on the screen.

          Methods

          In this study the process of secondary diagnostic was evaluated using the "T.Konsult Pathologie" service of the Professional Association of German Pathologists within the German breast cancer screening program. The characteristics of the access to the WSI (Whole Slide Images) have been analyzed to explore the possibilities of prefetching and caching to reduce the presentation and transfer time with the goal to increase user acceptance. The log files of the web server were analyzed to reconstruct the movements of the pathologist on the WSI and to create the observation path. Using a specialized tool the observation paths were extracted automatically from the log files. The attributes linearity, 3-point-linearity, changes per request, and number of consecutive requests were calculated to design, develop and evaluate different caching and prefetching strategies.

          Results

          The analysis of the observation paths showed that a complete accordance of two image requests is a very rare event. But more frequently a partial covering of two requested image areas can be found. In total 257 diagnostic paths from 131 WSI have been extracted and analysed. On average a diagnostic path consists of 16 image requests and takes 189 seconds between first and last image request. The mean linearity was 0,41 and the mean 3-point-linearity 0,85. Three different caching algorithms have been compared with respect to hit rate and additional image requests on the WSI server. Tests demonstrated that 95% of the diagnostic paths could be loaded without any deletion of entries in the cache (cache size 12,2 Megapixel). If the image parts are stored after JPEG compression this complies with less than 2 MB.

          Discussion

          WSI telepathology is a technology which offers the possibility to break the limitations of conventional static telepathology. The complete histological slide may be investigated instead of sets of images of lesions sampled by the presenting pathologist. The benefit is demonstrated by the high diagnostic security of 95% accordance between first and second diagnosis.

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          Most cited references17

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          Telepathology overview: from concept to implementation.

          Telepathology is the practice of pathology at a distance by using video imaging and telecommunications. Significant progress has been made in telepathology. To date, 12 classes of telepathology systems have been engineered. Rapid and ultrarapid virtual slide processors may further expand the range of telepathology applications. Next-generation digital imaging light microscopes, such as miniaturized microscope arrays (MMA), may make virtual slide processing a routine laboratory tool. Diagnostic accuracy of telepathology is comparable with that of conventional light microscopy for most diagnoses. Current telepathology applications include intraoperative frozen sections services, routine surgical pathology services, second opinions, and subspecialty consultations. Three telepathology practice models are discussed: the subspecialty practice (SSP) model; the case triage practice (CTP) model; and the virtual group practice (VGP) model. Human factors influence performance with telepathology. Experience with 500 telepathology cases from multiple organs significantly reduces the video viewing time per case (P < .01). Many technology innovations can be represented as S-curves. After long incubation periods, technology use and/or efficiency may accelerate. Telepathology appears to be following an S-curve for a technical innovation. Copyright 2001 by W.B. Saunders Company
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            Trends in histology laboratory teaching in United States medical schools.

            Owing to competition for faculty time among the three major missions of today's academic medical centers, as well as the rapid development of computer-based instructional technologies, laboratory instruction in medical schools in the United States has been undergoing dramatic change. In order to determine recent trends in histology laboratory instruction at U.S. medical schools, a detailed Web survey was administered to histology course directors, with about two-thirds of schools responding. The survey was designed to identify trends in the number of hours of histology laboratory instruction that each medical student receives, the amount of faculty effort devoted to histology laboratory instruction, and the use of various computer-based technologies (including virtual microscopy and virtual slides) in histology laboratory instruction. Consistent with the long-term trend of declining total laboratory teaching hours in U.S. medical schools, there is an ongoing reduction in the number of hours of faculty-directed histology laboratory instruction that each medical student receives, with a concomitant reduction in hours of faculty time devoted to histology laboratory instruction. In terms of the tools used in the histology laboratory, there has been a dramatic increase in the use of various forms of computer-aided instruction (including virtual slides). The large increase in the number of schools using computer-aided instruction has not been accompanied by an equivalent decrease in the number of schools that utilize microscopes and glass slides. Rather, the clear trend has been toward a blending of the new computer-based instructional technologies with the long-standing use of microscopes and glass slides. (c) 2006 Wiley-Liss, Inc.
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              Towards an automated virtual slide screening: theoretical considerations and practical experiences of automated tissue-based virtual diagnosis to be implemented in the Internet

              Aims To develop and implement an automated virtual slide screening system that distinguishes normal histological findings and several tissue – based crude (texture – based) diagnoses. Theoretical considerations Virtual slide technology has to handle and transfer images of GB Bytes in size. The performance of tissue based diagnosis can be separated into a) a sampling procedure to allocate the slide area containing the most significant diagnostic information, and b) the evaluation of the diagnosis obtained from the information present in the selected area. Nyquist's theorem that is broadly applied in acoustics, can also serve for quality assurance in image information analysis, especially to preset the accuracy of sampling. Texture – based diagnosis can be performed with recursive formulas that do not require a detailed segmentation procedure. The obtained results will then be transferred into a "self-learning" discrimination system that adjusts itself to changes of image parameters such as brightness, shading, or contrast. Methods Non-overlapping compartments of the original virtual slide (image) will be chosen at random and according to Nyquist's theorem (predefined error-rate). The compartments will be standardized by local filter operations, and are subject for texture analysis. The texture analysis is performed on the basis of a recursive formula that computes the median gray value and the local noise distribution. The computations will be performed at different magnifications that are adjusted to the most frequently used objectives (*2, *4.5, *10, *20, *40). The obtained data are statistically analyzed in a hierarchical sequence, and in relation to the clinical significance of the diagnosis. Results The system has been tested with a total of 896 lung cancer cases that include the diagnoses groups: cohort (1) normal lung – cancer; cancer subdivided: cohort (2) small cell lung cancer – non small cell lung cancer; non small cell lung cancer subdivided: cohort (3) squamous cell carcinoma – adenocarcinoma – large cell carcinoma. The system can classify all diagnoses of the cohorts (1) and (2) correctly in 100%, those of cohort (3) in more than 95%. The percentage of the selected area can be limited to only 10% of the original image without any increased error rate. Conclusion The developed system is a fast and reliable procedure to fulfill all requirements for an automated "pre-screening" of virtual slides in lung pathology.
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                Author and article information

                Journal
                Diagn Pathol
                Diagnostic Pathology
                BioMed Central
                1746-1596
                2009
                9 January 2009
                : 4
                : 3
                Affiliations
                [1 ]VMscope GmbH, Chariteplatz 1, 10117 Berlin, Germany
                [2 ]Lausitz University of Applied Sciences, Großenhainer Str. 57, 01968 Senftenberg, Germany
                [3 ]Institue of Pathology, Charité – University Hospital Berlin, Chariteplatz 1, 10117 Berlin, Germany
                Article
                1746-1596-4-3
                10.1186/1746-1596-4-3
                2654030
                19134181
                793d2963-16d5-4ddb-aa21-ab909a89c9b2
                Copyright © 2009 Wienert et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 March 2008
                : 9 January 2009
                Categories
                Software

                Pathology
                Pathology

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