Thomas Ramsay Presents Imago Systems at LSI USA '23

Transcription

Thomas Ramsay  0:05  

First of all, thank you for coming and taking precious time to hear what Imago is about. So I'm Tom Ramsey, one of the co founders and co-inventors of this technology. And so, I'm going to start with a story, because that's the genesis of our company. So my background has been in developing bomb detection for TSA and satellite imaging, tuberculosis detection in South Africa. And I sent my retired when my cousin Joanne lost both of her daughters to metastatic breast cancer. And I had been inventing with my brother over time. And I said, medicine imaging is failing the doctors who then cannot save our daughters, our mothers, our sisters. So we said, if you have tomo and you have mammograms, you have ultrasound, you have breast MRI, and it's failing them. Is there another way to look at an image, that there's information in that image, particularly for women who have dense breast tissue? Who right now get an FDA disclosure, you have dense breast tissue, you may have a higher propensity for breast cancer, and we have no solution for you. So out of that, we said, Could we have a technology that sees into the images that see into the body, in other words, any existing imaging modality could work. So we were funded by the National Cancer Institute, NIH out of the moonshot program to look at various cancers, in this case, mostly image but we also worked on brain cancer, lung cancer, as well as breast cancer. And what you're seeing now is revealing essentially, almost for the first time, a technology that transforms that original image, like you see on the left into geometries known as fractals, and fractals are embedded in every image that we have CT, MRI, it doesn't matter. But in addition to that, we have a process that can extract from any image, no additional imaging is required no additional radiation. And so the image that you see on the right over here looks is breast cancer. And that self emerges in the way that old photographic print, put in in developer emerges from the latent image. Ours emerge from the latent images, pixels within the image data. So right now, we know that there are major issues relative to diagnostics, including over 40 million diagnostic imaging processes annually, where the doctor, trade clinicians top in their industry simply cannot see it. We also know that there's no additional imaging modalities coming of any sort. That's going to save us. So this is an example a woman sent us her mammogram. She had had a mastectomy and the other breast 10 years before and she said, I want a mastectomy. I don't want to think about it anymore. I have aunts that have cancer, and they told her you don't have breast cancer, MR ultrasound, and mammogram all came back negative. They sent us the images before that. And when we sent the images back, we said you have multifocal patterns of ductal carcinoma. And pathology showed it at the earliest stages including atypical hyperplasia and ductal carcinoma in situ the earliest stages ever seen in cancer, much less a mammogram of high density. So, in addition to that, we were asked, Could you apply this to cardiovascular medicine? What if you could take an angiogram? Is there image information inside of that that could assist clinicians, radiologists, cardiologists, and so in this case, the doctor saw obvious stenosis and brake on the left artery. And yet the patient had angina after we processed it with one of our 200 algorithms, and they're all They're all patented, we showed that the right artery had significant stenosis turbulence, as well as a rupture. And that came just from the standard. All of this can be done in real time. And later, I'll show you a picture where we now are revealing hemodynamic flow without any intervention in the artery at all. So our product works, essentially with any image in any clinical workflow and our design It was that we could take a mammogram and provide the new kinds of images that the doctor could see without disrupting a cardiologist or radiologists workflow. So a standard workstation and the radiologist can pull it up. Rapid deployment, we have it built into a VM. We currently host have it hosted on AWS and Google clouds, we take images from anywhere in the world, essentially real time. And it's agnostic to the platform, tissue and disease. So we've run initial clinical studies on PET CT, MRI, and so on. So where we're at relative to our pathway with FDA is we're going to be submitting to the FDA, we've had two meetings now with them on the cardiovascular. And that will be submitted within the next 120 days. They've told us it's a retrospective study, we have all the images, and it's going to be a class two 510 K. On the breast imaging, it's a little longer because we come under the MQSA requirements from FDA. But we expect that that will be available to us after the first of next year. So the markets that we look at are, are, first of all just focused on two aspects. One is cardiovascular medicine. We're starting out with angiography, but the technology has been tested already for peripheral vascular. We've been looking at CCTA in terms of 3d modeling, and how this technology can be applied. So that the doctors can see this kind of geometry in 3d and axial axis and so on. The market opportunity on the cardiovascular already is 2024 is about $67 million, I'm sorry, billion. And we expect that the same thing is going to be true for us on the on the breast imaging, so it doesn't require any new additional studies for the woman. So how do we get to market we see that because we can work with X ray, PET CT ultrasound, MR, we want to be the Intel of the imaging society where we can take any image, and we can transform it. In this case, our first two markets are breast imaging and cardiovascular. But we look at beneficiaries not only for the patient, physician and so on. But we transform the images from unstructured to structured data. And we have found in our research, that we could hit numbers in the 80 to 90 percentiles of sensitivity and specificity after we process the images. So we've partnered now with Mayo Clinic, they've made an investment in us relative to the breast imaging Met Axiom just invested in us and they become our marketing partner. They're a wholly owned subsidiary of the American College of Cardiology. And we're launching at the end of April at a conference in Orlando with Met Axiom. This is the only second company in the American colleges history to invest in a company. And then in just south here in La Jolla. We have a capability now a three year partnership to do all of our internal review to take a look at the possibility of removing the necessity to put wires in arteries to measure pressure and blood flow. So our board of directors, Dr. Susan Alpert was with the FDA for 13 years, and she was the director of the device division. For six years. Mark Lipitor has created a number of technologies and had IPOs. On several of his technologies on our advisory board, Peter McBride is here he's our head of cardiology, Dr. Bassou, is the president and CEO of Cancer Treatment Centers of America. Dr. Khesari is the top 1% and neuro oncologist in the country. Dr. Griffith has perceived as completed over 7000 procedures head call, and Dr. Portrush. I'll leave. And we can talk about them when I follow up. So in conclusion, we're showing you now what's possible from a standard LG Gram in the lower right, which is in grayscale. And what you're seeing is hemodynamic flow for the first time in the body in real time, without any invasive procedure like IVs or ocgt. Thank you very much.