Hackensack Meridian Health partners with Etta.io to enhance bladder cancer detection with AI

"What was great about this partnership is we recognized that this is going to be the future of medicine at some point, and we want to be able to be a part of that cutting edge technology," says Nitin K. Yerram, MD.

Nitin K. Yerram, MD

Nitin K. Yerram, MD

In this interview, Nitin K. Yerram, MD, highlights a collaboration between Hackensack University Medical Center and Etta.io that will work to use artificial intelligence to detect bladder tumors earlier.1 Yerram is the director of urologic oncology at Hackensack University Medical Center, Hackensack, New Jersey.

Could you provide an overview of this partnership?

Hackensack University Medical Center has entered into a strategic agreement with Etta.io, which is a health care startup in artificial intelligence. It's to develop a new and novel algorithm to detect bladder cancer using cystoscopy and artificial intelligence.

Could you discuss more about how the technology works?

Bladder cancer is a very aggressive disease and tends to have rates of overdiagnosis or underdiagnosis. The problem with underdiagnosis in bladder cancer is it can be an extremely deadly disease. There's a specific type of bladder cancer called CIS, which is carcinoma in situ, and these tumors tend to be difficult to diagnose on cystoscopy. They can be flat; they can be hidden. In that sense, there's been a lot of interest to see how we can better detect those types of tumors to help patients in terms of their diagnosis and treatment.

This tool here uses artificial intelligence to be able to detect these types of tumors using machine learning neural pathways to be able to identify suspicious areas in the bladder and help augment the clinical decision making that a clinician has for detection of this type of bladder cancer.

How does this partnership work to address a current unmet need in the space?

The unmet need here is how we can better use technology to find these types of aggressive tumors. In the past, there have been solutions to this using medications you have to instill [and] buying new hardware that can tend to be a little bit cumbersome. Especially when we talk about access to this type of technology, sometimes the rural areas and other areas in this country tend not to be able to afford that type of technology. It's a cumbersome step for these patients to have a medication instilled in their bladder with a Foley catheter. Sometimes, you have to buy large capital systems to be able to detect these types of tumors.

Our goal here is to be able to integrate into existing hardware solutions, a software-based application that can be integrated in the clinical workflow and can help detect these types of tumors. The collaboration itself is to develop that type of algorithm, which means there's going to be a lot of data collection, data validation, and proof-of-concept technology evaluations that are going to be part of this collaboration.

What implications does this have for both patients and urologists?

It's a really important area for bladder cancer is to be able to find these types of tumors. At diagnosis, it's important to be able to detect these types of tumors. It's also important to be able to detect these types of tumors after treatment, so that you have reduced [risk of] recurrence. Detection is extremely important. What I think this technology is able to fill in that need is how we can better find these types of tumors. We've talked about other options in terms of medications and hardware solutions, but to be able to make a seamless workflow, to help augment the clinical decision making that a urologist has, is going to be a game-changer.

We hope to be able to integrate this in everyone's workflow, so urologists all over the country can be able to put in the cystoscope that they're very comfortable [with] and do commonly, and using millions and millions of datasets, we're hopeful the software algorithm or platform can be able to help that urologist be able to find these suspicious areas in a bladder. It can help them say, "I think that's something we need to biopsy" or "maybe that was just an area of irritation or inflammation. How can we differentiate between inflammation and cancer?". We're hopeful that our software algorithm is going to be able to do that.

Is there anything else that you’d like to add?

I think what's interesting about this partnership is it's a health system that is able to see the vision of what health care is going to look like in 15 to 20 years, and to be able to support that type of vision. To be able to say, we know that this is where the field is going, we're going to invest on the ground floor to see how we can improve care across the nation in this type of disease state. What was great about this partnership is we recognized that this is going to be the future of medicine at some point, and we want to be able to be a part of that cutting edge technology. This big health care system coming with the health startup, this type of fusion of the great minds is going to show us how healthcare should be performed in years to come.

Reference

1. Partnership aims to detect bladder tumors earlier with help of AI Hackensack Meridian Health teams up with Etta.io in new collaboration. News release. Hackensack Meridian Health. April 19, 2023. Accessed May 10, 2023. https://www.hackensackmeridianhealth.org/en/news/2023/04/19/partnership-aims-to-detect-bladder-tumors-earlier

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