When a regulated industry looks to public cloud computing, the number of deal breakers can run high. For the ChRIS Project (Research Integration Service), the challenges are many to create an open-source platform that maintains patient scans for medical practitioners to access, compare and analyze images quickly and remotely. This type of project requires a compliant cloud platform, as well as hefty computing power at the edge of the network, to allow for continuous updates and highly secure data storage.

“For the price of a cellphone and a cell signal, you can use this kind of technology anywhere,” said Dr. Rudolph Pienaar (pictured, left), technical director of the Fetal-Neonatal Neuroimaging and Developmental Science Center at Boston Children’s Hospital and instructor at Harvard Medical School. “You can compare images that are collected, wherever it might be, just for the price of connecting to the internet.”

Pienaar and Dr. Ellen Grant (pictured, right), director of the FNNDSC and professor at Harvard Medical School, spoke with John Walls (@JohnWalls21) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the Red Hat Summit in Boston. They discussed the ChRIS Project and how both patients and clinicians can benefit from technology innovation (see the full interview with transcript here). (* Disclosure below.)

[Editor’s note: The following answers have been condensed for clarity.]

Walls: We’re talking about what’s called the ChRIS Project, which was a technically based project at Boston Children’s Hospital. Dr. Grant, if you would, talk about the genesis of this project, what its goal was, and how it’s been carried out.

Grant: The goal of the ChRIS Project was to bring innovative imaging analysis to the bedside, to the front end where clinicians like me are working all the time but aren’t sophisticated enough or don’t have enough memory to remember how to do line code in Linux.

When I was reading clinical studies and I wanted to run a complex analysis, but there was no way to do it easily, I’d have to call up someone to log into a different computer, bring the images over, and it took lots of complex steps to run that analysis. Even to do any of these analyses, you have to download the program and set up your environment. I would rather deal with the interpretation and understanding the meaning of those images than all the infrastructure steps to bring it together.

That was the genesis of ChRIS, trying to have a simple Windows point-and-click way for a physician, such as myself, to be able to rapidly do something interesting and then be able to show it to a clinician in a conference or at the bedside.

Walls: Who was supplying what kind of manpower to the project?

Pienaar: In the beginning I would say that we wanted to bring this research software, which lives mostly on Linux, onto a Windows world, right? So, the people developing that software were researchers or computational researchers who do a lot of amazing stuff with image processing. But those tools just never really make it from the research lab outside of that.

One of the reasons is because someone like Ellen might not ever want to fire up a terminal and type in these commands. So people working on it are this huge population of researchers making these tools. What I try to help with is how we get those tools really easily usable and accessible, and to make a difference. That was the need that we had in the beginning. It started out as a bunch of shell scripts. Gradually with time, we tried to move to the web. Then it began to grow. Then from the web, stretching to the cloud. That’s kind of the trajectory in a nutshell. As each step moved along, more and more people came into play.

Miniman: Let’s talk about the patient side of things. We talk about order of magnitude that cloud can make things faster and easier, but what does this mean to patient care and quality of service?

Grant: I think the goal for patient care is really getting to specialized medicine or individualized medicine, and to be able to not just rely on my memory as to what a normal or abnormal image is or the patients I may have seen just in my institution. Can we pull together all the knowledge across multiple institutions throughout the country and use more rigorous data analysis to support my memory? I want to have these big, parietal and frontal lobes that are the cloud that help me remember things and not have to just rely on my visual distal memory, which is obviously going to have some flaws.

If I’ve never seen a specific disorder, for example, at my institution, but they’ve seen it at other institutions and we can run these comparisons, all of a sudden I may be aware of a new treatment that otherwise I may not have known about.

Miniman: Rudolph, my understanding is, this is tied into the Mass Open Cloud. Talk a little bit about how this is enabled. There are massive amounts of data, and you need to make sure you get the right data and the valuable information to the right people, and it gets updated all the time. Give us a little bit of the inner workings.

Pienaar: If we can get data in one place — and not just from one institution, but from many places — then we can start to do things that are not really possible otherwise. That’s the grand vision, so we’re moving along those steps.

The Mass Open Cloud makes perfect sense because there’s an academic link to Boston University, and then there’s the Red Hat being one of the academic sponsors. This kind of a synergy that came together, almost perfectly at the right time as the cloud was developing, as Red Hat was moving in, as we were trying to move to the cloud, it just began to link together. That’s very much how we got there at the moment.

There’s all these amazing devices, but computationally, medicine lags so far behind the rest of the industry. There’s so little integration. There’s so little advance processing going on. With so little effort you can do so much. So that’s part of the vision as well.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of Red Hat Summit 2019. (* Disclosure: TheCUBE is a paid media partner for Red Hat Summit. Neither Red Hat Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE