Parwani on Ohio State's AI-Driven Pathology and Digital Transformation

Anil Parwani, MD, PhD, professor of pathology at The Ohio State University Wexner Medical Center, discusses an artificial intelligence (AI) technology that is currently being used at his institution.

Transcription:

0:09 | Currently, what we are doing is we are 1 of the few hospitals in the country that have converted from last slide workflow to a digital workflow. In order for us to use AI, we need to have images and a digital format. So traditionally, when you think of pathologists, they look at a glass slide and they make a diagnosis under a microscope. At Ohio State, we were able to take millions of these glass slides, and convert them into digital images. These are images that you can interact with. Each image is made up of millions of pixels. If I am looking at a patient's prostate biopsy, the biopsy was done in a clinic, the tissue was sent to the lab, and the glass slides are still made, but our process really starts after the glass slides. They become digitized, I review them on the monitor, and that was something we started in 2018.

1:15 | We have been able to digitize millions of slides, mostly started with cancer oncology. Now, the next step, like 2 years ago, we started to design and think about ways where we can apply artificial intelligence on top of these images. Basically, for a patient who has prostate cancer, are we able to detect that cancer on a monitor where just like on your iPhone, you have apps, there could be an app for prostate cancer detection, there could be an app for creating prostate cancer, or there could be an app for just finding similar cancers. There could be an app to predict which patients will have a better outcome without actually doing a lot of extensive and aggressive assays.

2:15 | We have worked in this area for 5, 6 years now, and we have been able to test algorithms from different companies. We have also had researchers at Ohio State who have built algorithms here in the computer science department or the bioinformatics department. We have now completed a few clinical trials on prostate cancer, where we have demonstrated that prostate cancer can be detected by the AI tool, it can be diagnosed, can be recreated, it can be cultivated, and we are in the process of now, integrating it into the electronic medical record [EMR], and the lab information system. We can do it standalone, I can go into a website, pull up a patient, run the algorithm, get diagnostic criteria, and the pathologist will review the heatmap of where the cancer is, and then decide is this diagnostic? Then they will sign off on the case and send it to the patient's chart.

3:20 | We have done a lot of careful validation of these algorithms. And we feel they are safe and ready for clinical use. In 2024, our goal is to launch several of these algorithms for clinical use. Right now they are mainly for quality assurance and looking at research, but we have tested it on actual clinical specimens and the results are very promising. The next thing is now to bring it to integration with the EMR.