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Empowering the Future of Remote Pathology with Image Search

By Patrick Myles

According to MIT, 90% of information transmitted to the human brain is visual, with humans being able to identify images seen for as little as 13 milliseconds. No other profession understands this more intuitively or puts it into practice more than pathologists. Yet, even as progressive hospitals adopt digital workflows in the emerging age of remote pathology, we are hobbling along with text-based search to find the data we are looking for. What if we could search visually, based on the content of the image? How much would we improve the quality and speed of diagnosis. How much could we accelerate discovery?

Imagine, for example, a pathologist in a remote location reviewing a difficult case. What if they could instantly search and retrieve multiple results of similar looking tissue along with the associated pathology reports from trusted colleagues – at their hospital or hospital network – or potentially across the world? How much could that help inform their diagnosis. Or, what if a researcher could use image search to discover previously unknown connections to cancer subtypes – or, if we think big, connections to the genome.

In a paper published in March in Nature Digital Medicine, we reported on a recent validation of image search, in which we indexed 33,000 whole slides from 11,000 patients, 25 organs and 32 cancer subtypes from the NIH/NCI public dataset. From the project we learned that building diagnostic consensus with high confidence is possible. In frozen sections and diagnostic slides, accuracy for certain cancer types approached 100%. We identified a positive correlation of 80% between number of patients and the accuracy of majority consensus, i.e, the more data the better.

Over the next five years, hospitals and labs will produce hundreds of millions of digital slides, exabytes of unstructured image data, and tens of millions of pathology reports. Image search will become the “must-have” functionality to bring intelligence to the huge quantity of unstructured image data, with the far-reaching potential to connect pathologists to the collective knowledge of their colleagues, irrespective of geographic location.

This is a guest post by Patrick Myles, CEO of Huron Digital Pathology, a Canada-based company and Inspirata approved partner that offers whole slide image scanners for digital pathology.


Tags: Post-COVID-19, pathology, digital pathology, image search