What is driving digital pathology?

(And why you should care)

Pathology is in transition. There simply aren’t enough pathologists to go around. With an aging population the number of pathology cases and the number of samples to process keeps growing. Since new graduate pathologists can’t be trained and educated fast enough to satisfy demand, the only option* is to make the existing and incoming pathologists process more samples. Since just working more hours is not feasible for medical professionals in charge of diagnosing to save lives, we must find a way to make the pathologists work more efficiently.

Today, most hospital workflows still include extracting a tissue sample, shaving a thin slice of it onto a glass slide, and having a pathologist examine it under a microscope for anomalies. To get the pathologist to view the sample, either the sample slides or the pathologist themselves may travel long distances for a diagnosis. This is at once unnecessarily time-consuming, expensive and stressful.

The digitalization of pathology is simply applying digital imaging technology, i.e. a digital camera, to take a high-resolution photograph of the sample slide, which can be zoomed in and out for best scale view and emailed instantly across the world. Doing away with shipping slides or making the professional travel on-site frees an enormous amount of time in the process. This change can let the pathologist use their time more wisely, process more slides per day and thus be much more efficient.

There’s about a 20-minute window for diagnosing a tissue sample in surgery, before the patient has to be sewn up again. Without a pathologist immediately available additional surgery may be necessary or worse yet malignant tissue may go undetected. Every one of us could need this at one or several points in our lives. Fast scanning of the sample slide and diagnosis (and a potential second opinion) online democratize professional diagnosis and make it available for all.

*Yes, machine vision and artificial intelligence hold great promise in getting diagnosis done, but computational pathology is not ready yet to replace the pathologist in their work. To get where AI can be relied on to diagnose or even sort cases, slides must be scanned, and the workflow has to be digital.