Digital Pathology: Path to the Future

Digital pathology is now rapidly translating to the clinic facilitating multiple advantages compared to traditional histopathology. Regulatory approval and the advance in associated technology have expedited this translation. Whole slide scanners are now capable of standardized batched image capture coupled to a fully digital workflow including patient records. In the near future patients with no local access to specialist pathology resource will benefit from remote diagnoses across expert networks spanning the globe. This is even true for low-resource countries with the development of mobile and cost-effective digital pathology solutions. Automated image analysis will not be far behind in clinical translation. Algorithms can standardize the quantification of histopathological features and biomarkers while taking into account their spatial interaction within complex tissue. Machine learning will feature in the future of clinical histopathology as the computer learns to exclude tissue- and imaging-based artefacts while including pertinent regions of interest to answer clinical questions. As these algorithms’ complexity advances, they will not only free up pathologists’ time but unravel clinically relevant but as yet undetected complex morphological features and cellular interactions. Big-data currently features in many aspects of medicine and digital pathology will be no different. The wealth of data which image analysis can now produce, coupled with clinical and molecular data will forge the path towards a personalized prognostic and predictive pathology.