Digital Pathology: Data-Intensive Frontier in Medical Imaging

• Type of Material: Article
• Authors: Lee Cooper, Emory University; Alexis Carter, Emory University; Alton Farris III, Emory University; Fusheng Wang, Emory University; Jun Kong, Emory University; David Gutman, Emory University; Patrick Widener, Emory University; Tony C. Pan, Emory University; Sharath R. Cholleti, Emory University; Ashish Sharma, Emory University; Tahsin Kurc, Emory University; Daniel Brat, Emory University; Joel H. Saltz, Emory University
• Language: English
• Date: 2012-04-01
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2012 IEEE.
• Final Published Version (URL): http://dx.doi.org/10.1109/JPROC.2011.2182074
• Title of Journal or Parent Work: Proceedings of the IEEE
• ISSN: 0018-9219
• Volume: 100
• Issue: 4
• Start Page: 991
• End Page: 1003
• Grant/Funding Information: This work was supported in part by SAIC/NCI under Contracts HHSN261200800001E and N01-CO-12400 from the National Cancer Institute, by the National Heart Lung and Blood Institute under Grant R24HL085343, by the National Library of Medicine under Grants 1R01LM011119-01 and R01LM009239, by the National Institutes of Health under Grant RC4MD005964, by the Clinical and Translational Science Awards program under PHS Grant UL1RR025008, and by the Biomedical Information Science and Technology Initiative program under Grant P20 EB000591.
• Keywords: SEGMENTATION; INFORMATICS; NEUROBLASTOMA; image analysis; TELEPATHOLOGY; RESIDENCY PROGRAMS; DIAGNOSIS; SYSTEM; QUANTIFICATION; virtual microscopy; Science & Technology; digital pathology; Biomedical imaging; Engineering; Engineering, Electrical & Electronic; Technology; CANCER; biomedical informatics; CLASSIFICATION
• Research Categories: Health Sciences, Pathology; Engineering, Biomedical

Abstract

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses.