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Implementing the DICOM Standard for Digital Pathology

BACKGROUND: Digital Imaging and Communications in Medicine (DICOM(®)) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the...

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Autores principales: Herrmann, Markus D., Clunie, David A., Fedorov, Andriy, Doyle, Sean W., Pieper, Steven, Klepeis, Veronica, Le, Long P., Mutter, George L., Milstone, David S., Schultz, Thomas J., Kikinis, Ron, Kotecha, Gopal K., Hwang, David H., Andriole, Katherine P., Iafrate, A. John, Brink, James A., Boland, Giles W., Dreyer, Keith J., Michalski, Mark, Golden, Jeffrey A., Louis, David N., Lennerz, Jochen K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236926/
https://www.ncbi.nlm.nih.gov/pubmed/30533276
http://dx.doi.org/10.4103/jpi.jpi_42_18
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author Herrmann, Markus D.
Clunie, David A.
Fedorov, Andriy
Doyle, Sean W.
Pieper, Steven
Klepeis, Veronica
Le, Long P.
Mutter, George L.
Milstone, David S.
Schultz, Thomas J.
Kikinis, Ron
Kotecha, Gopal K.
Hwang, David H.
Andriole, Katherine P.
Iafrate, A. John
Brink, James A.
Boland, Giles W.
Dreyer, Keith J.
Michalski, Mark
Golden, Jeffrey A.
Louis, David N.
Lennerz, Jochen K.
author_facet Herrmann, Markus D.
Clunie, David A.
Fedorov, Andriy
Doyle, Sean W.
Pieper, Steven
Klepeis, Veronica
Le, Long P.
Mutter, George L.
Milstone, David S.
Schultz, Thomas J.
Kikinis, Ron
Kotecha, Gopal K.
Hwang, David H.
Andriole, Katherine P.
Iafrate, A. John
Brink, James A.
Boland, Giles W.
Dreyer, Keith J.
Michalski, Mark
Golden, Jeffrey A.
Louis, David N.
Lennerz, Jochen K.
author_sort Herrmann, Markus D.
collection PubMed
description BACKGROUND: Digital Imaging and Communications in Medicine (DICOM(®)) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. METHODS: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software. RESULTS: Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed. CONCLUSION: Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.
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spelling pubmed-62369262018-12-07 Implementing the DICOM Standard for Digital Pathology Herrmann, Markus D. Clunie, David A. Fedorov, Andriy Doyle, Sean W. Pieper, Steven Klepeis, Veronica Le, Long P. Mutter, George L. Milstone, David S. Schultz, Thomas J. Kikinis, Ron Kotecha, Gopal K. Hwang, David H. Andriole, Katherine P. Iafrate, A. John Brink, James A. Boland, Giles W. Dreyer, Keith J. Michalski, Mark Golden, Jeffrey A. Louis, David N. Lennerz, Jochen K. J Pathol Inform Original Article BACKGROUND: Digital Imaging and Communications in Medicine (DICOM(®)) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. METHODS: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software. RESULTS: Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed. CONCLUSION: Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology. Medknow Publications & Media Pvt Ltd 2018-11-02 /pmc/articles/PMC6236926/ /pubmed/30533276 http://dx.doi.org/10.4103/jpi.jpi_42_18 Text en Copyright: © 2018 Journal of Pathology Informatics http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Herrmann, Markus D.
Clunie, David A.
Fedorov, Andriy
Doyle, Sean W.
Pieper, Steven
Klepeis, Veronica
Le, Long P.
Mutter, George L.
Milstone, David S.
Schultz, Thomas J.
Kikinis, Ron
Kotecha, Gopal K.
Hwang, David H.
Andriole, Katherine P.
Iafrate, A. John
Brink, James A.
Boland, Giles W.
Dreyer, Keith J.
Michalski, Mark
Golden, Jeffrey A.
Louis, David N.
Lennerz, Jochen K.
Implementing the DICOM Standard for Digital Pathology
title Implementing the DICOM Standard for Digital Pathology
title_full Implementing the DICOM Standard for Digital Pathology
title_fullStr Implementing the DICOM Standard for Digital Pathology
title_full_unstemmed Implementing the DICOM Standard for Digital Pathology
title_short Implementing the DICOM Standard for Digital Pathology
title_sort implementing the dicom standard for digital pathology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236926/
https://www.ncbi.nlm.nih.gov/pubmed/30533276
http://dx.doi.org/10.4103/jpi.jpi_42_18
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