History and structures of telecommunication in pathology, focusing on open access platforms

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Abstract

Background

Telecommunication has matured to a broadly applied tool in diagnostic pathology.

Technology and Systems

Contemporary with the development of fast electronic communication lines (Integrated digital network services (ISDN), broad band connections, and fibre optics, as well as the digital imaging technology (digital camera), telecommunication in tissue - based diagnosis (telepathology) has matured. Open access (internet) and server - based communication have induced the development of specific medical information platforms, such as iPATH, UICC-TPCC (telepathology consultation centre of the Union International against Cancer), or the Armed Forces Institute of Pathology (AFIP) teleconsultation system. They have been closed, and are subject to be replaced by specific open access forums (Medical Electronic Expert Communication System (MECES) with embedded virtual slide (VS) technology). MECES uses php language, data base driven mySqL architecture, X/L-AMPP infrastructure, and browser friendly W3C conform standards.

Experiences

The server - based medical communication systems (AFIP, iPATH, UICC-TPCC) have been reported to be a useful and easy to handle tool for expert consultation. Correct sampling and evaluation of transmitted still images by experts reported revealed no or only minor differences to the original images and good practice of the involved experts. β tests with the new generation medical expert consultation systems (MECES) revealed superior results in terms of performance, still image viewing, and system handling, especially as this is closely related to the use of so - called social forums (facebook, youtube, etc.).

Benefits and Expectations

In addition to the acknowledged advantages of the former established systems (assistance of pathologists working in developing countries, diagnosis confirmation, international information exchange, etc.), the new generation offers additional benefits such as acoustic information transfer, assistance in image screening, VS technology, and teaching in diagnostic sampling, judgement, and verification.

Related collections

Most cited references 32

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Telepathology overview: from concept to implementation.

Ethan K. Scott, Elizabeth Krupinski, Michael R. Descour … (2001)

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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Theory of sampling and its application in tissue based diagnosis

Klaus Kayser, Holger Schultz, Torsten Goldmann … (2009)

Background A general theory of sampling and its application in tissue based diagnosis is presented. Sampling is defined as extraction of information from certain limited spaces and its transformation into a statement or measure that is valid for the entire (reference) space. The procedure should be reproducible in time and space, i.e. give the same results when applied under similar circumstances. Sampling includes two different aspects, the procedure of sample selection and the efficiency of its performance. The practical performance of sample selection focuses on search for localization of specific compartments within the basic space, and search for presence of specific compartments. Methods When a sampling procedure is applied in diagnostic processes two different procedures can be distinguished: I) the evaluation of a diagnostic significance of a certain object, which is the probability that the object can be grouped into a certain diagnosis, and II) the probability to detect these basic units. Sampling can be performed without or with external knowledge, such as size of searched objects, neighbourhood conditions, spatial distribution of objects, etc. If the sample size is much larger than the object size, the application of a translation invariant transformation results in Kriege's formula, which is widely used in search for ores. Usually, sampling is performed in a series of area (space) selections of identical size. The size can be defined in relation to the reference space or according to interspatial relationship. The first method is called random sampling, the second stratified sampling. Results Random sampling does not require knowledge about the reference space, and is used to estimate the number and size of objects. Estimated features include area (volume) fraction, numerical, boundary and surface densities. Stratified sampling requires the knowledge of objects (and their features) and evaluates spatial features in relation to the detected objects (for example grey value distribution around an object). It serves also for the definition of parameters of the probability function in so – called active segmentation. Conclusion The method is useful in standardization of images derived from immunohistochemically stained slides, and implemented in the EAMUS™ system . It can also be applied for the search of "objects possessing an amplification function", i.e. a rare event with "steering function". A formula to calculate the efficiency and potential error rate of the described sampling procedures is given.

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AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

Klaus Kayser, Jürgen Görtler, Milica Bogovac … (2008)

The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue--based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients.

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Author and article information

Journal

Journal ID (nlm-ta): Diagn Pathol

Title: Diagnostic Pathology

Publisher: BioMed Central

ISSN (Electronic): 1746-1596

Publication date Collection: 2011

Publication date (Electronic): 7 November 2011

Volume: 6

Page: 110

Affiliations

[1 ]Charite, University of Berlin, Berlin, Germany

[2 ]IAT (International Academy of Pathology), Heidelberg, Germany

[3 ]Amina Djenouni, Batna, Algeria

[4 ]Institute of Pathology, University of Freiburg, Freiburg, Germany

Article

Publisher ID: 1746-1596-6-110

DOI: 10.1186/1746-1596-6-110

PMC ID: 3231812

PubMed ID: 22059444

SO-VID: 679024f2-a7a6-4d6f-9dba-4494be8d021a

License:

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

Date received : 1 November 2011

Date accepted : 7 November 2011

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History and structures of telecommunication in pathology, focusing on open access platforms

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Abstract

Background

Technology and Systems

Experiences

Benefits and Expectations

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Telemedicine

Most cited references 32

Telepathology overview: from concept to implementation.

Theory of sampling and its application in tissue based diagnosis

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

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