Implementing the DICOM Standard for Digital Pathology.

Autor: Herrmann MD; MGH and BWH Center for Clinical Data Science, Boston, MA, USA., Clunie DA; PixelMed Publishing, LLC, Bangor, PA, USA., Fedorov A; Department of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA., Doyle SW; MGH and BWH Center for Clinical Data Science, Boston, MA, USA., Pieper S; Isomics, Inc., Cambridge, MA, USA., Klepeis V; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA., Le LP; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA., Mutter GL; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA., Milstone DS; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA., Schultz TJ; Enterprise Medical Imaging, Massachusetts General Hospital, Boston, MA, USA., Kikinis R; Department of Radiology, Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA., Kotecha GK; MGH and BWH Center for Clinical Data Science, Boston, MA, USA., Hwang DH; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA., Andriole KP; MGH and BWH Center for Clinical Data Science, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA.; Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA., Iafrate AJ; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA., Brink JA; Harvard Medical School, Boston, MA, USA.; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA., Boland GW; Harvard Medical School, Boston, MA, USA.; Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA., Dreyer KJ; MGH and BWH Center for Clinical Data Science, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA.; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA., Michalski M; MGH and BWH Center for Clinical Data Science, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA.; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA., Golden JA; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA., Louis DN; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA., Lennerz JK; Harvard Medical School, Boston, MA, USA.; Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
Jazyk: angličtina
Zdroj: Journal of pathology informatics [J Pathol Inform] 2018 Nov 02; Vol. 9, pp. 37. Date of Electronic Publication: 2018 Nov 02 (Print Publication: 2018).
DOI: 10.4103/jpi.jpi_42_18
Abstrakt: 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.
Competing Interests: There are no conflicts of interest.
Databáze: MEDLINE
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