Digital Pathology: Historical Perspectives, Current Concepts & Future Applications

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If pathologists do not embrace innovative ways to improve their methods such as is offered by digital pathology, in a way that is palatable to all pathology groups, we will likely get left behind and at worst marginalized by our clinical colleagues in the emerging era of AI. AI is a tool, and like most tools works best in certa in situ ations and in the hands of trained users. AI works best for identifying patterns in large, high-dimensional datasets that meet certain criterion standards.

Like any other laboratory test, AI should be clinically validated against current quality standards to ensure clinical effectiveness and safety in practice These expert systems were designed to encode the diagnostic clinical expertise of physicians and quickly produce diagnoses or treatment options based on input data.

Even after the clinical effectiveness of an AI system is proven, AI systems still face the challenge of integration into clinical care. Several other challenges to implementing AI solutions in digital pathology have been described, which must be weighed against their benefits when considering their potential application in clinical practice Table 1 While laboratories have long sought automated methods for anatomic pathology, there was only relatively recently renewed excitement with the FDA approval of the Philips IntelliSite Pathology Solution PIPS for primary review and interpretation of formalin fixed surgical pathology specimens This long-awaited approval encouraged a global uptick in the number of whole slide scanning operations and AI start-up companies to process the massive amount of data being generated by slide digitization.

Pathology AI start-up companies have focused not only on making diagnoses 20 , but also on screening, quality assurance, prognostication, and even discovery.


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For example, patterns of lymphocyte infiltration have been shown to provide prognostic and therapeutic information for patients. Applications that are easy to use, financially sustainable, perform well and make a positive impact are more likely to be successfully adopted by pathologists We agree with Thomas James Flotte that surgical pathologists will need to play a critical role in the development of successful AI applications 3.

In addition to curating data and providing annotations, pathologists need to be responsible for validating that these applications are necessary and that they work, verifying their accuracy and safety, as well as encourage their integration into routine workflow. The vast majority of practicing anatomic pathologists will not need to be experts in computer science or informatics, but when clinically using AI tools should understand their limitations and the implementation process required for them to be used in daily practice.

Implementing an AI program that is later found to have done harm to patients could drastically set back the field of AI 15 , which is why we must proceed cautiously during this dawn of AI in digital pathology.

Digital Pathology: The Past, Present, and Future

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Pathology: Lab & Practice Management

A Daoist Events around 17 million learners to content photo equations. Productos 27; s Baader and Nipkov, ; Hoe and Arvind, Telepathology is currently the most publicized application as it will undoubtedly be indispensible in rural and remote settings where physical travel is arduous and the distances involved are occasionally unreasonable. The reason is obvious and it is easy to understand why telepathology is a popular topic both in the pathology literature and at national meetings.

This concept should not be dismissed as a passing fad, but rather recognition of its potential benefit, particular in remote and underserved areas. Data storage is another well known advantage of digital conversion.

In this paradigm, archival glass microscope slides would be to scanned and the data stored digitally. This is no small advantage, since retaining large numbers of glass slides for many years requires not only vast amounts of physical space, but countless person-hours of filing, tracking, retrieval, etc.

Acknowledgements

Regulatory requirements that most slides be retained for a minimum of 20 years force most laboratories, ours included, to rent large amounts of off-site storage space at considerable expense. Furthermore, lost, broken, or misfiled slide may be irreplaceable.

How You Will Benefit

Digital storage also eliminates the need to file and retrieve glass slides. Currently glass slides must be retrieved from the files for tumor boards, for quality assurance, and for comparing current pathology with previous specimens. A busy pathology laboratory can require more than one full FTE dedicated to slide filing and retrieval. As digital storage becomes cheaper, we will reach the point where digital storage is not only easier and more reliable, but also less expensive than maintaining files of glass slides.

Digital mathematical analysis is the most powerful application of digital pathology, yet is, ironically, the least talked about. Probably the two most powerful diagnostic enhancements of digital microscopy are pattern recognition and transformational analysis. The power behind both of these tools is the synergy of the human brain and the computer complementing each other. Some patterns, e.

Digital Pathology Historical Perspectives, Current Concepts & Future Applications 2016

The computer can easily perform the mathematical transformations that convert data into patterns that our brains immediately recognize. This is not so esoteric as it sounds. Rather, the computer simply uses a mathematical transformation digital transformation to enhance our ability to recognize what was already there. Digital transformation allows us to see what is hidden in plain sight.

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All microscopic analysis is based upon the algebraic relationship between a particular dependent variable and anatomic location in 2-dimensional space. There are innumerable dependent variables which can be analyzed;, the most common are pH, concentration of specific chemical moieties, concentration of specific antigenic epitopes, and number of specific nucleic acid sequences. The independent variable is anatomic location. Each microscopic image is a unique pictoral geometric solution to one of these equations. Digitization uses analytic geometry to convert this geometric solution to an algebraic solution.

Almost all microscopy involves differential staining of microscopic slides. In other words, the staining intensity varies with some physicochemical parameter, such as pH, electrical charge, antigenic expression, chemical moiety, etc. Furthermore, this differential staining occurs in situ.


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  7. In other words, the original anatomic relationships are preserved. This allows, at a microscopic level, mapping of differential physicochemical attributes as a function of anatomic position. Eosin is a red dye that preferentially binds to acidic low pH structures. Note that the original anatomic relationships are retained; hence, this is an in situ stain. Hematoxylin is a blue due that preferentially binds to basic high pH structures. This, too, is an in situ stain.

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