There is no current digital pathology signature that is generally acknowledged to directly indicate a molecular profile or a precision-medicine class. For example, my colleagues and I recently published data regarding the potential for detecting actionable mutations directly from digital histology, and we validated the ability to detect microsatellite instability directly from digital slides. H&O How is digital pathology currently being used to practice precision medicine?ĪP The use of digital pathology as a biomarker of genomic data is in early stages. For glass slides, in contrast, a technician might need to visit an off-site repository and search through hundreds of thousands of samples, depending on the location and institution. ![]() Access to the digital files becomes extremely quick if they can be pulled up through a network. At my institution and many others, glass slides can be evaluated, captured, and stored in a digital format. H&O What are the other advantages of digital pathology?ĪP Digital pathology is becoming more economical as clinicians increase the throughput. As researchers are building information repositories, it is helpful to use digital forms as opposed to physical glass slides. With the right clinical setup, the process can be performed at the same clinical speed as needed for glass slides.įrom a research and data perspective, I think it is much easier to keep a digital imaging repository compared with a repository of glass slides. A digitized version of a suspicious sample can be assessed in the same way as a glass slide image the pathologist can provide input regarding the diagnosis, characteristics, grading, and other factors. H&O How is digital pathology used in hematology and oncology?ĪP Currently, digital pathology is being used by pathologists to assist the diagnostic workflow in both cancer and noncancer applications. Eventually, this information will serve as potential building blocks for the implementation of algorithmic-based diagnostics. ![]() There has been a tremendous increase in the volume of digital health information that is being collected and stored. This endeavor has been assisted by the growth of the clinical digital pathology domain. My colleagues and I are researching ways to use algorithms, machine learning techniques, and artificial intelligence to extract information from pathologic images. For example, pathologists may be able to review cases from different sites at a single digital pathology workstation, obviating the need to be physically present at an off-site location to view a glass slide under a microscope. AP Digital pathology entails the digitizing of standard diagnostic pathologic information and decentralization of pathologic review.
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