4.5 Article

Complete Digital Pathology for Routine Histopathology Diagnosis in a Multicenter Hospital Network

Journal

ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE
Volume 144, Issue 2, Pages 221-228

Publisher

COLL AMER PATHOLOGISTS
DOI: 10.5858/arpa.2018-0541-OA

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Context.-Complete digital pathology and whole slide imaging for routine histopathology diagnosis is currently in use in few laboratories worldwide. Granada University Hospitals, Spain, which comprises 4 hospitals, adopted full digital pathology for primary histopathology diagnosis in 2016. Objective.-To describe the methodology adopted and the resulting experience at Granada University Hospitals in transitioning to full digital diagnosis. Design.-All histopathology glass slides generated for routine diagnosis were digitized at x40 using the Philips IntelliSite Pathology Solution, which includes an ultrafast scanner and an image management system. All hematoxylin-eosin-stained preparations and immunohistochemistry and histochemistry slides were digitized. The existing sample-tracking software and image management system were integrated to allow data interchange through the Health Level 7 protocol. Results.-Circa 160 000 specimens have been signed out using digital pathology for primary diagnosis. This comprises more than 800 000 digitized glass slides. The scanning error rate during the implementation phase was below 1.5%, and subsequent workflow optimization rendered this rate negligible. Since implementation, Granada University Hospitals pathologists have signed out 21% more cases per year on average. Conclusions.-Digital pathology is an adequate medium for primary histopathology diagnosis. Successful digitization relies on existing sample tracking and integration of the information technology infrastructure. Rapid and reliable scanning at x40 equivalent was key to the transition to a fully digital workflow. Digital pathology resulted in efficiency gains in the preanalytical and analytical phases, and created the basis for computational pathology: the use of computer-assisted tools to aid diagnosis.

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