Digital pathology
Digital Pathology is an image-based information environment which is enabled by computer technology that allows for the management of information generated from a digital slide. Digital pathology is enabled in part by virtual microscopy, which is the practice of converting glass slides into digital slides that can be viewed, managed, and analyzed on a computer monitor. With the advent of Whole-Slide Imaging, the field of digital pathology has exploded and is currently regarded as one of the most promising avenues of diagnostic medicine in order to achieve even better, faster and cheaper diagnosis, prognosis and prediction of cancer and other important diseases.
Potential
In pathology, trained pathologists look at tissue slides under a microscope. The tissue on those slides may be subjected to staining to highlight structures. When those slides are digitized, they then have the potential to be numerically analyzed using computer algorithms. Algorithms can be used to automate the manual counting of structures, or for classifying the condition of tissue such as is used in grading tumors.[1] This could reduce human error and improve accuracy of diagnoses. Digital slides are also, by nature, easier to share than physical slides. This increases potential for using data for education and consultations between two or more experts.
Challenges
Digital pathology is not yet approved by the FDA for primary diagnosis.[2] Unlike digital radiology where the elimination of film made return on investment (ROI) clear, the ROI on digital pathology equipment is less obvious. The strongest ROI justification includes improved quality of healthcare, increased efficiency for pathologists, and reduced costs in handling glass slides.[3]
Digital Pathology Environment
Scan
Digital slides are created from glass slides using a scanning device. Digital pathology requires high quality scans free of dust, scratches, and other obstructions.[4]
View
Digital slides are accessible for viewing via a computer monitor and viewing software either locally or remotely via the Internet.
Example: digital pathology tissue slide stained with Her2/neu biomarker used for diagnosis of breast cancer.
Manage
Digital slides are maintained in an information management system that allows for archival and intelligent retrieval.
Network
Digital slides are often stored and delivered over the Internet or private networks, for viewing and consultation.
Analyze
Image analysis tools are used to derive objective quantification measures from digital slides. Pattern recognition and visual search tools are used to classify specimen imagery and identify medically significant regions of digital slides.
Integrate
Digital pathology workflow is integrated into the institution's overall operational environment.
Sharing
Digital pathology also allows internet information sharing for education, diagnostics, publication and research.
See also
References
- ↑ "The Pathology of Tumors, Part III: Grading, Staging & Classification". doi:10.3322/canjclin.29.2.66/pdf (inactive 2016-06-26). Retrieved April 26, 2015.
- ↑ "Digital Pathology Association". Retrieved April 26, 2015.
- ↑ "How to Build a Business Case to Justify the Investment in Digital Pathology". Sectra Medical Systems. Retrieved April 26, 2015.
- ↑ Flagship Biosciences. "How to Improve Whole Slide Scanning in Digital Pathology". Flagship Biosciences LLC. Retrieved 25 September 2013.
Further reading
- Kayser, K; Kayser, G; Radziszowski, D; Oehmann, A (1999). "From telepathology to virtual pathology institution: The new world of digital pathology" (PDF). Romanian journal of morphology and embryology. 45: 3–9. PMID 15847374.
- McCullough, Bruce; Ying, Xiaoyou; Monticello, Thomas; Bonnefoi, Marc (2004). "Digital Microscopy Imaging and New Approaches in Toxicologic Pathology". Toxicologic Pathology. 32 (5): 49–58. doi:10.1080/01926230490451734.
- Schlangen, David; Stede, Manfred; Bontas, Elena Paslaru (2004). "Feeding OWL: Extracting and Representing the Content of Pathology Reports". NLPXML '04 Proceeedings of the Workshop on NLP and XML.
- Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio (2011). "Automatic Annotation of Histopathological Images Using a Latent Topic Model Based On Non-negative Matrix Factorization". Journal of Pathology Informatics. 2 (4): 4. doi:10.4103/2153-3539.92031.
- "E-Health and Telemedicine". International Journal of Computer Assisted Radiology and Surgery. 1 (Supplement 1): 119–35. 2006. doi:10.1007/s11548-006-0012-1.
- Fine, Jeffrey L.; Grzybicki, Dana M.; Silowash, Russell; Ho, Jonhan; Gilbertson, John R.; Anthony, Leslie; Wilson, Robb; Parwani, Anil V.; et al. (2008). "Evaluation of whole slide image immunohistochemistry interpretation in challenging prostate needle biopsies". Human Pathology. 39 (4): 564–72. doi:10.1016/j.humpath.2007.08.007. PMID 18234276.
- Kayser, Klaus; Kayser, Gian; Radziszowski, Dominik; Oehmann, Alexander (2004). "New Developments in Digital Pathology: from Telepathology to Virtual Pathology Laboratory". In Duplaga, Mariusz; Zieliński, Krzysztof; Ingram, David. Transformation of Healthcare with Information Technologies. Studies in Health Technology and Informatics. IOS Press. pp. 61–9. ISBN 978-1-58603-438-2. ISSN 0926-9630. PMID 15718595.
- Tolksdorf, Robert; Bontas, Elena Paslaru (2004). "Object-Oriented and Internet-Based Technologies". Lecture Notes in Computer Science. 3263: 115–56. doi:10.1007/978-3-540-30196-7_4. ISBN 978-3-540-23201-8.
|chapter=ignored (help) - Potts, Steven J. (2009). "Digital pathology in drug discovery and development: Multisite integration". Drug Discovery Today. 14 (19–20): 935–41. doi:10.1016/j.drudis.2009.06.013. PMID 19596461.
- Potts, Steven J.; Young, G. David; Voelker, Frank A. (2010). "The role and impact of quantitative discovery pathology". Drug Discovery Today. 15 (21–22): 943–50. doi:10.1016/j.drudis.2010.09.001. PMID 20946967.
- Zwonitzer, R; Kalinski, T; Hofmann, H; Roessner, A; Bernarding, J (2007). "Digital pathology: DICOM-conform draft, testbed, and first results". Computer Methods and Programs in Biomedicine. 87 (3): 181–8. doi:10.1016/j.cmpb.2007.05.010. PMID 17618703.
External links
- More information about definition, technology and teaching
- Digital Pathology News
- APIII (a national pathology informatics meeting's website with archived presentations and contact information for faculty)
- Pathology Visions (a national digital pathology conference)
- Association for Pathology Informatics
- Digital Pathology Association
- Digital Pathology Blog
- The Digital Pathology Wiki
Academic Digital Pathology Sites
- Welcome to Digital Pathology at Brown Medical School
- Holycross Cancer Center (Poland, Kielce) Pathomorphology Department virtual slides
- Digital Pathology Imaging Group at University of Pittsburgh Medical Center
- Computational Pathology Workshop series; organized for the first time in 2016 to bring together the fields of bioinformatics and digital pathology
Commercial Digital Pathology Sites
- Leica/Aperio Digital Pathology
- Huron Digital Pathology
- Objective Pathology Services - infrastructure: imaging, networking, engineering
- Pathomation
- PathXL
- Pixcelldata
- Proscia's Pathology Cloud
- Interactive Digital Pathology Imaging for your own microscope
- Indica Labs Informed Pathology
Other Relevant sites
- Guidon Blog on whole slide image analysis
- OpenSlide — C library that provides a simple interface to read whole-slide images.
- pushglass: pathology image search
- Digital Pathology Service Network: Providers of Digital Pathology services
- Digital Pathology in Australia: Digital Pathology Solutions Integration for Australian Pathology Labs
- Aperio ePathAccess