Filed by RadNet, Inc.
Filing pursuant to Rule 425 under the
Securities Act of 1933, as amended
Deemed filed under Rule 14a-12 under the
Securities Exchange Act of 1934, as amended
Subject Company: iCAD Inc.
Commission File Number: 001-09341
Explanatory Note: The following is a transcript from the Media Roundtable held on April 16, 2025, in connection with RadNet, Inc.’s proposed acquisition of iCAD, Inc.
| Marshall Manson | 00:04 | Good afternoon, good evening everyone, and thank you for joining us today. My name is Marshall Manson, and I'm a Senior Partner at communications advisory firm, FleishmanHillard. I have the pleasure of modeta- moderating today's event. We're together today to discuss an important moment. RadNet has announced their intention to acquire iCAD and integrate it into DeepHealth, RadNet's digital health business. |
| 00:27 | This move represents a major step forward in breast cancer screening, and aligns with DeepHealth's mission of addressing clinical and operational challenges to enable better care delivery. By combining iCAD's and DeepHealth's complementary solutions and capabilities, the companies are paving the way for a new era in breast cancer screening, a disease which is sadly diagnosed every 14 seconds. | |
| 00:52 | Today's session is your opportunity to hear directly from the leaders behind this combination. You'll get insight into the strategic rationale, the shared mission, and what this integration would mean for the future of healthcare. Before we begin, please note that during this event, next slide, please, we will discuss forward-looking topics. Therefore, we encourage you to review our safe harbor and forward-looking statements, disclaimers, both on this slide and the next. Next slide, please. | |
| 01:23 | Now let me introduce our speakers. We're joined today by Gregory Sorenson, Chief Science Officer of RadNet and clinical AI leader at DeepHealth. He'll share RadNet's vision in advancing breast health and the challenges the industry and patients are experiencing. Next, Kees Wesdorp, CEO of DeepHealth, who will speak on the company's mission and how this intended acquisition is poised to revolutionize the industry. | |
| 01:51 | Next, Dana Brown, CEO of iCAD, will provide an overview of iCAD's impact in breast health and highlight the opportunities this integration is expected to unlock. And finally, Sham Sokka, Chief Operating and Technology Officer of DeepHealth. Sham will walk us through the portfolio synergies and envisioned value creation. Next slide, please. | |
| 02:15 | So here's the snapshot of the agenda we'll be following in this session. We'll begin with remarks from our speakers, followed by a live Q&A. Please do feel free to submit questions at any time using the Q&A function, uh, which you'll see on your screen. I'll be moderating and directing those questions to our panel at the end of the presentation. So I'm looking forward to hearing from our speakers. And without further ado, let's get, get started. Uh, and we'll start with Greg. |
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| Greg Sorenson: | 02:41 | Hi, everybody. Uh, let's move on to the next slide. Thanks very much for the introduction. One more slide, please. Uh, I'm going to, uh, start off by giving you a little bit of, uh, kind of level setting about who RadNet is and why, uh- and what we do at both RadNet and DeepHealth, that I think that will help understand why the- help you understand better why this acquisition makes so much sense, and why we see this as such a win for, uh- for the patients that we see, the patients that iCAD touches and for, uh, women around the world. |
| 03:11 | So, first, let's, uh, begin, uh, with a little bit about RadNet. I think many of you are familiar with us, but this is the kind of data that we share, uh, frequently. We're about, uh, 398 as of the end of Q4, close to 400 imaging centers. Uh, RadNet grows every year, so this number is gonna continue to go up. We have joint ventures with more than 25, um, academic and, and, uh, health system, uh, partners, where they depend on us to help them manage their outpatient, uh, imaging services. | |
| 03:42 | Um, you can see these other numbers, I won't read them all. But essentially RadNet is, uh, uh, one of the largest, if not the largest outpatient imaging provider in, in the country, if not the world. Um, we do a lot of mammograms. Uh, this year, I think we'll do close to two million, maybe a little bit more, uh, mammograms. So that's roughly about as many as the whole country of England. So we really have a lot of scale when it comes to mammography. | |
| 04:05 | And in fact, uh, when you kind of put all the breast health, uh, related care we do together at RadNet, it's close to a third of our revenue. So this is a really important part of what we do from, um, the screening to the, uh, diagnostic imaging, biopsies, et cetera. We're very focused at RadNet about improving access. A lot of our locations are in traditionally underserved or lesser served areas, and so this is a big focus for us. And, uh... And I'll talk a little bit more about that in a minute. | |
| 04:34 | Um, as of five years ago, uh, RadNet made an investment into, uh, AI when they acquired my company, DeepHealth. And since then, has really doubled down and put a lot more effort, um, into, uh, artificial intelligence in radiology, uh, because we think it's got the, um, potential. And now we've- we'll show you the evidence that it can markedly improve the standard of care for patients at a broad range of geographies in the real world in a very meaningful, impactful way. | |
| 05:05 | And I think there's no better example for- than- uh, for this than breast cancer. So let's go to the next slide. Most of you are very familiar with the stats around breast cancer. These are global numbers. The US numbers are proportional, lot- a big impact. Hundreds of thousands of women in the US, millions of cases worldwide. Lots of deaths still, unfortunately. Um, and unfortunately, as the bottom right stat shows, a lot of these are in underserved or, uh, minority communities. | |
| 05:32 | Black women in particular, uh, for reasons we don't completely understand in the scientific community, die at a higher rate of breast cancer. This is a really serious illness. So if there were something that we could try to attack, uh, uh, uh, with AI or with imaging, breast cancer certainly ranks very highly. It's a... It's a big challenge and, um- and a big opportunity, uh, candidly. | |
| 05:54 | And it's that combination of, uh, the- both our interest in taking on big population health challenges and the scale of this problem that has led RadNet, next slide, please, um, to really invest over time in, um, gr- in, in this area. And so, as I mentioned, uh, the 2024 numbers were about 1.9. I think 2025 numbers will be above two million mammograms. We have really worked hard to try and not only build AI, but change the way we practice based on incorporating that AI. |
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| 06:25 | And that has led us to develop a program we call Enhanced Breast Cancer Detection. And I would just like to emphasize, this is not a single point solution AI, where a doctor like you see in this picture here gets a little colored box. Instead, in addition to that, when a woman enrolls in the EBC program, um, the AI is used in a couple of different sophisticated ways, including, uh, on the most dangerous cases, bringing in a second physician, another interpreter. | |
| 06:51 | And that, we call it, uh, Safeguard Review. It's kind of intelligent use of our manpower to bring the most sophisticated interpretation skills on the most difficult cases. Really has shown a lot of benefit. We have tremendous enthusiasm across our, uh, practices, uh, for using this. And we've demonstrated now in hundreds of thousands of women that we can find cancer at a much higher rate and a substantially meaningful rate, as well as we found ways to lower recall rates. | |
| 07:17 | And as I mentioned earlier, RadNet's very interested in improving access, hence our outreach into new settings such as grocery stores, uh, doctors' offices, et cetera. So that's kind of the baseline. I wanna just kind of set the stage that RadNet's very interested in this question of breast cancer or breast health. We think that screening, we know from many studies, can improve the, the health of women, AI can make a big difference. | |
| 07:41 | And so that's kind of the baseline of where we started. So now let me, uh, turn it over to Kees who will walk you through a little bit more about, um, the, uh- the, the DeepHealth team and what it's doing specifically to help build out the infrastructure and the tools needed to deliver that improvement in care. Over to you Kees. Next slide, please. | |
| Kees Wesdorp: | 07:59 | Thank you. Thank you, Dr. Sorenson. That's a great way to set the context for, uh- for DeepHealth and also, uh, yesterday's news about, uh, the acquisition. Um, so let me re- maybe remind, uh, this audience, and thanks also for tuning in, uh, about our mission, our mission at DeepHealth, which is really about empowering breakthroughs in care through imaging. |
| 08:20 | Now, how do we do that? On the next page, you see some of the dimension in terms of how we rate ourselves in- as a global leader in AI-powered health informatics. As mentioned before, we are a 100% subsidiary, uh, of RadNet. Um, we have 400 plus customers worldwide. So whilst RadNet is an important, let's call it, internal customer to us, we have very significant exposure to external cus- customers as well. | |
| 08:47 | We have a global footprint, we have access to diverse patient data. And over the course of five years, with the start obviously with Dr. Sorenson’s company, DeepHealth, we've been integrating capabilities both in the clinical AI domain, so think of Aidence for lung, for prostate and brain, DeepHealth for breast, current for breast, but also, uh, in the healthcare informatics domain, uh, with the eRAD platform that was already pre-existent with, uh- with RadNet, which is really encompassing our RIS and PACS offering. |
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| 09:18 | That's now branded under the DeepHealth umbrella. And we're being- bringing that in an integrated capability, Sham will talk about it later, in a cloud-native integrated capability form. Next slide, please. So we have, um... We're positioned uniquely in the sense that we're vertically integrated. And the benefits of that, for instance, is our ability to do, uh- drive rapid iteration, validation and prototyping with our clinical AI solutions. | |
| 09:46 | We are clinically proven to have over 800 plus clinical sites and over 3000 radiologists that we work with, and we've demonstrated clinical impact. And for instance, in our breast program, the, um... Uh, we have, um, our SmartMammo solution that drives a 21%, uh, increase in breast cancer detection rate, which is obviously very, very significant. And we're delivering this at scale. | |
| 10:09 | Um, so we're processing 20 million, uh, plus managed, uh, imaging studies per year. Um, and we're powering 300 plus AI-powered cancering, uh- cancer screening sites in the US and in Europe. And that actually prompts me, Dr. Sorenson, would you mind on the next slide talking a little bit more about the impact that we're having, um, with these screening programs? | |
| Greg Sorenson: | 10:32 | Yes. Uh, thanks, Kees. And, uh, let's go on to the next slide. And... And you're right, we have kind of a, a little bit of a complicated story because on the one hand, we've got RadNet that is delivering a lot of services in the US, but as you just heard, DeepHealth as a provider of software, is enabling a lot more care in other countries and in the US. |
| 10:52 | So in addition to the breast cancer screening that we're doing in the US, as I've already mentioned, um, as Kees pointed out with some of the acquisitions we've made, like such, for example, in this case, Aidence, we are powering AI-enabled diagnosis in other diseases. | |
| 11:06 | So perhaps most impressively, as the, um, NHS in England has rolled out its lung cancer screening program where the dominant, probably more than 90% of the sites are using our software and are showing marked stage shift in lung cancer detection, where not only are they finding more stage one cancers, but importantly in their population, they're documenting a substantial reduction in stage four cancers, which is what we all want out of screening. | |
| 11:31 | And that's because the AI enables a single reader, unlike all the other screening programs in Europe and the UK that have two readers, just a single reader plus AI to very efficiently and cost-effectively, uh, deliver a screening program. And now the, uh, NHS has decided that the pilot is ongoing, well, they're gonna scale up to the entire population, to other countries as well. | |
| 11:52 | And now we're hearing that other countries across Europe are starting to roll out lung cancer screening programs. The DeepHealth, uh, AI software and the, the workflow software is a key part of that. And now you're- I think you're starting to get a sense. We started with RadNet. Uh, big, um, internal, uh, uh, use case for our AI software. But there's a much, uh... |
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| 12:13 | Of c... Of course, uh, the vast majority of the market is not RadNet. And... And those customers also want AI solutions, but they want proven establishments. And we're doing that not just in mammography, but beyond. That being said, today's, uh, talk is really about a mammography. So, uh, back over to you, Kees, to sort of talk through this specific acquisition. | |
| 12:37 | Oh, you're on mute, Kees, oh, or at least I can't hear you. | |
| Kees Wesdorp: | 12:40 | Thank you, Dr. Sorenson. And so I'm super excited today to talk about, uh, what we have disclosed yesterday, which is the iCAD acquisition and how that is accelerating our mission. If you go to the next slide. So this acquisition will strengthen our, uh- DeepHealth's leadership in AI-driven breast cancer in, in three specific ways. Um, and I'll... You know, I'll just pause with them for a secs to make sure that, uh, it comes clear that this is also how in the rest presentation we talk about the value creation opportunity. |
| 13:12 | So it accelerates scaling our capabilities. It's ex- expands our commercial reach, and it delivers industry's most comprehensive portfolio. So accelerating scale, uh, of capability across commercial products and engineering functions. And what that does basically is it, it, it, it fast forwards the mission that we have as DeepHealth, uh, with a world-class team that is coming on board from iCAD. | |
| 13:41 | In terms of expanding our reach, together, uh, we will cover 10 million annual mammograms, and we have access to over 1700 provider sites, um, and, uh, with, uh, iCAD's reach to, uh, to over 50 plus countries. Later on, Sham will talk about, uh, the compre- comprehensive portfolio that the combination has. Uh, what will show us that it's highly complementary and also will allow us to accelerate some of the future, uh, products and solutions that we have. | |
| 14:09 | And last but not least, uh, this will enhance iCAD's financial performance with a positive adjusted EBITDA run rate expected by the end of 2026, and this will be done through synergies. Through synergies next to obviously the exciting growth journey that iCAD and DeepHealth are, are on. Next page, please. So I'll hand over to, uh, Dana, the CEO of iCAD to talk a little bit more about, um, iCAD's leadership, but also obviously the excitement around the acquisition. Dana, over to you. | |
| Dana Brown: | 14:43 | Great. Thank you Kees, and thanks to the rest of the DeepHealth leadership team for the opportunity to take a few minutes and just talk to you directly about iCAD. Um, so iCAD's mission is to create a world where cancer can't hide. And on, uh, the right-hand side of this slide, you could see those areas of the world, um, that we've been able to help deliver on that mission. |
| 15:07 | Um, iCAD has a suite of solutions. Uh, we refer to this suite as our ProFound AI Breast Health Suite. And this suite of solutions cover a variety of information needs for the radiologists and serving their patients, specifically in breast cancer. So our foundational solution is a product we call Detection. Uh, Detection actually received its first FDA clearance, believe it or not, over 20 years ago and it was the first FDA cleared product in 2016 to address 3D mammography. |
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| 15:40 | We recently just came out with version 4.0. Um, and so it's continued to deliver on our innovations in AI with impressive results like, compared to our prior version, finding over 22% more cancers, a 38% improvement in identifying cancers smaller than one centimeter, and over a 50% improvement in identifying cancers with dense- within breast tissue. | |
| 16:07 | Um, our other solutions, uh, we have a density assessment solution. We have a short-term risk solution, and we have a breast arterial calcification solution. Each of these solutions, um, may have different regulatory clearances, so to know within which country, uh, we have clearance around the world. Just encourage you to take a look at our website so you can get the full list. | |
| 16:30 | Um, but as Kees mentioned, we are also bringing 1500 healthcare providers, um, into the DeepHealth portfolio, um, and look forward to being able to deliver integrated solutions together to them. We're very excited, um, about the integration and about the merger because we believe as we join forces with RadNet to create this broader offering of AI-driven solutions, we have the opportunity to deliver on that mission of creating a world where cancer can't hide. | |
| 17:01 | We have the opportunity to redefine how breast cancer and other diseases are detected and treated. And we're looking forward, as we put our teams together, to work to expand access to these cutting-edge tools and technologies, to accelerate innovation, advance our product roadmaps, empower radiologists, all with the ultimate goal of improving patient outcomes. With RadNet's ac... | |
| 17:24 | With our access to RadNet scale, access to data, their clinical leadership, we're very excited and think that this helps to ensure our current and future products get brought to market, improving the radiologists' and the patients' clinical outcomes. So with that, um, would love to turn it back over to Kees | |
| Kees Wesdorp: | 17:45 | Thank you, Dana. That's a great overview. If you go to the next page, operator, I just to also baseline those in terms of the financial overview of the two companies. Um, so on the left-hand side, you see DeepHealth, and we've previously, uh, issued guidance for 2025 as 80 to 90 million in revenues for the full year of 2025, and 15 to 70 million in adjusted EBITDA for 2025. |
| 18:09 | We add to this iCAD's, and if you look at the reported numbers for 2024, that is, uh, close to 20 million additional turnover. And following the acquisition, we expect positive adjusted EBITDA run rate by the end of 2026. Uh, how do we do that? We do that through attractive synergies. And on the next page, um, three, uh, domains of synergies are highlighted; the cost synergies, commercial synergies, and product synergies. | |
| 18:39 | More short term, we will capture cost synergies, uh, to the tune of 7 million plus on a run rat- rate basis, uh, relate to roughly half of it, direct savings. So these are duplicative, uh, uh- duplicative costs between iCAD's and RadNet/DeepHealth in terms of board of directors cost, public company cost audits, et cetera. The other half this fulfilled by fulfilling pre-existing hiring plans of DeepHealth. |
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| 19:08 | So really read here that we're super excited to bring on board the capabilities of iCAD, the great team, uh, and that actually accelerates our journey because we're on the hunt for this type of talent anyhow, to deliver on the DeepHealth mission. The second category of, uh, synergies is commercial synergies. Um, and so we're excited to have access to, uh- as part of DeepHealth, uh, the DeepHealth offerings, to have access to the iCAD installed base. | |
| 19:33 | We already mentioned 1500, uh, provider lo uh- locations, um, with access to our 50 plus countries. And we really believe that, for instance, our European growth will be accelerated. Um, now, moreover, on top of that, we will obviously combine the commercial funnel and capture, uh, all the benefits, um, out of that. Third domain of, uh, synergies are the product synergies. Um, and so I'll say it again, there's a highly complementary offering as of day one. | |
| 20:02 | Sham will talk us through that. Uh, but we also see, um, uh, the great future products that iCAD has in the pipeline, or actually, already, uh, is delivering, uh, in terms of, for instance, breast arterial calcification and image-based risk assessments. And last, not least, this will expand our product, R&D and regulatory capacity and capability to accelerate new solutions over and on top of that. | |
| 20:27 | Before talking more about the portfolio, I wanna present one more slide, and that is about the world class team of iCAD that's on this page indeed, uh, and how that will accelerate DeepHealth growth, uh, plan. A 66 FTE strong team will join us with roughly 26, uh, people in products and R&D. And by the way, there, we include Q&R and clinical affairs, given the tight, uh, teamwork that needs to happen across those domains. | |
| 20:54 | 26 people in the commercial domain, that includes marketing and service. And 14 FTE or people in the support functions. They have a strong s- uh, track record with global reach to develop, market, deploy and service AI solutions at scale. And as I mentioned, uh, we're very, very glad to bring this talent on board also because it'll accelerate, uh, our, um, uh, pre-existing hiring plans that we had as part of DeepHealth journey. | |
| 21:21 | Um, on the next page, I'm gonna hand it over to Sham. Sham, it will be great to hear about the strength, uh, of, um, the combined portfolio as you bring it to market. | |
| Sham Sokka: | 21:32 | Great. Thanks, Kees. Um, you know, as emphasized by Dr. Sorenson, Kees and Dana actually, key pillars of both of our missions is expanding the reach of high-quality mammography screening, uh, to more and more people, right? And, uh, Dr. Sorenson talked about how we're doing that directly at the RadNet level. And a big part of the mission of DeepHealth is to provide those screening services, uh, beyond, uh, RadNet, uh, in- globally. |
| 22:01 | And with this acquisition now, we have a complementary progressive set of offerings for customers along various stages of their AI-powered detection strategies. And I think that that's really, um, the core of how we see this portfolio coming together, right? So you have customers that are, you know, um, early in their AI-powered adoption that are looking really, um... I have, you know, all these other tools already. I just want the AI, I want to be able to integrate it. |
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| 22:32 | And you know, now with iCAD, you have a very strong offering to come into that, uh, environment, deliver a product really fast, and start people on the journey. Uh, what I also wanna emphasize that, you know, what's nice about that as, as well, is you have now global availability. So we can now address multiple markets. Uh, they support both 2D and 3D mammography, as we know in the US we're, uh, heavily in the 3D space. Um, although there's still quite some 2D mammography done. | |
| 23:00 | But outside of the US, there's actually, uh, mostly 2D, right? So you wanna expand the access. Um, the other, uh, really interesting piece is that they have, um- they support multiple OEM manufacturers on AI side. So GE systems, Hologic systems, Siemens systems, Fuji systems. So you can really, you know, uh, uh, come into a broad variety, uh, of install base and have an impact, right? So that's, let's say, stage one of AI-powered detection, right? First need to have AI there. | |
| 23:31 | Um, what we've now seen at RadNet, and now we've created an offering, is we've taken, um, DeepHealth AI, integrated that into viewing and reporting solutions. And what you see there is when you can actually bring AI right into the viewer, snap directly to the image plane where there's detection, you know, ra- radiologists are able to detect faster, read faster, and then taking all those results, putting them automatically into the report allows them to really drive workflow efficiency. | |
| 24:01 | And that speed also allows a better cancer detection, because they're not- they have more time to actually focus. And we've seen that data, uh, at, at RadNet, and we've created a turnkey offering there. Um, that's kind of the next step, okay? So not, not only AI only, but now I have a cockpit, right? That's really from mammography, that's really dr- driving around efficiency. | |
| 24:23 | And then the third stage, which you see here is, um, what, uh, Greg alluded to earlier that RadNet, um, pioneered, which is this concept of using AI in multiple stages. First stage, we use AI to support the primary radiologist to detect the cancer, very similar to what iCAD is doing. But then there's a second stage in which the AI makes a deterministic conclusion in terms of, uh, radiologist says there's cancer, the AI makes its own determination. | |
| 24:52 | And if there's disagreement, it's routed to a, uh, second radiologist, uh, which we call it a process called Safeguard Review, um, which then allows for a better cancer detection rate as well as a reduced recall rate, um, uh, in the same time. So now you've compounded these solutions, AI, uh, improved, uh, cancer detection, improved workflow efficiency through the cockpit- this integrated cockpit kind of approach. | |
| 25:21 | And then with a- with a, um- a second reader safeguard review process, you've now even further improved, um, uh, the cancer detection and recall reduction. I just wanna remind folks that that is the standard of care actually in many parts of Europe, where every mammogram is read twice. What we're doing here is we're using AI assist to dramatically, uh, uh, reduce the cost of that kind of operation, because you don't need to do it in every case, and you get kind of the benefits of a second reader workflow, right? | |
| 25:50 | So the, the fundamental vision is to now, um, uh, um, provide, uh, um, uh, customers with different layers of solutions and then start to help them, uh, on their broader journey. Um, as we also look, uh, beyond the detection products, uh, in, uh... Kees and Dana both alluded to both the image-based risk product as well as- as well as breast arterial calcification. | |
| 26:15 | Uh, both of those products have various approvals outside the United States. They're, um, going through the FDA pipeline now for the US. And one, you know, real opportunity we see is taking those products, bringing them into the RadNet environment, uh, boosting that with RadNet data, looking at the outcomes, uh, and driving continuous improvement on that so we can really accelerate both the image-based risk product as well as the breast arterial calc- uh, uh, calcification. |
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| 26:41 | Just to explain what the both of those products do. Image-based risk, uh, product, um, even though there may not be cancer in the current mammogram, it projects out a risk profile in the 12 to 20 more time- 24-month time horizon so you can kind of manage patients not just today, but maybe put them on accelerated schedules or different type of screening approaches. | |
| 27:02 | And the breast arterial, uh, uh, calcification is trying to correlate, let's say, calcification on a mammogram with potentially increased coronary artery risk, uh, uh, uh- artery disease risk. And so potentially, you could get them on, uh, um, screening profiles for cardiac disease as well. So in sort of an integrated approach to women's health, right? | |
| 27:25 | So improve the detection journey and then bring along these sort of risk products that can kind of help, um, um, uh, attach other type of screening, uh, uh, uh, processes to the core women's health journey, right? So, um, if you can advance to the next slide, so how does this fit into the broader, um, DeepHealth portfolio? I just wanna remind folks, DeepHealth is in, uh, a broader, uh, business, um, really two verticals, uh, in the broader, uh, health informatics space. | |
| 27:54 | One is enterprise imaging, which is the core platform for image delivery, right? So both, uh, interpreting images, which is a PACS plus solution, but also operating imaging centers, which is a essentially RISC radiology information solution. Um, and that's all integrated together on the cloud in, uh, what we call DeepHealth OS with various types of, uh, uh, products that you see on the left. | |
| 28:17 | And then we will integrate, um, the mammography portfolio into the, the reporting side of the, the, the business, uh, enhance the view- enhance the viewing, enhance the radiology experience, but also a reminder that we have prostate screening products, um, lung screening products. We have products on the brain space. Um, and so what you see here is an offering that it's not just that we want to go after and eradicate, uh, uh, breast cancer, which we are very passionate about. | |
| 28:47 | But we see the opportunity to really transform radiology into a well-care, preventive care, uh, uh, opportunity, um, by bringing other, uh, screening tool sets into a well-orchestrated operation, operating in clinical platform, uh, that can allow radiology departments to expand, uh, as well as, let's say, uh, non-primary radiology sites, um, um, uh, non-traditional sites to start delivering these kinds of, uh, imaging services, right? | |
| 29:17 | So with that, um, let me- let me conclude sort of the more organized portion of the presentation. I'm gonna hand it back to Marshall, who's gonna help facilitate some questions. | |
| Marshall Manson: | 29:27 | Brilliant. Thanks so much, Sham, uh, and thanks to all the speakers. Uh, as Sham said, we're gonna go to Q&A now. Uh, if you haven't had a chance to post your question in the Q&A function, be grateful if you do it now. We've had a few in already, which is fantastic. Thanks very much for submitting so far. Um, I... I'm just going to summarize for a second while we wait for your questions to come in. |
| 29:49 | Uh, you know, clearly this is a, a coming together of two influential companies in the breast cancer field, uh, working together to come up with solutions which could drive meaningful impact for patients globally. Just to pull out a few things that struck me. First, the increased impact for patients and radiologists that this combination can enable in the fight against breast cancer around the world. |
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| 30:11 | Second, how the joint capabilities will enhance scale across engineering product and commercial areas and lead to accelerated AI adoption in radiology, which is incredibly important with today's fast-paced industry. And lastly, the comprehensive portfolio of AI powered solutions, uh, for breast cancer screening, uh, that the combination, uh, brings together. | |
| 30:34 | Um, so look, we're gonna open the floor for questions now. We've had... As I say, we've had a few through. Uh, please do submit yours. We're eager to answer as many as we can, and we will get through as many as we possibly can in the time we have. Uh, if we don't get to your questions, please do email 'em to us. I think you will all know where to find either Fabian or Andra, uh, and we'll make sure to get the, the questions back to you. | |
| 30:55 | Um, but if I can, I'm gonna start with, uh- with the first one we received, uh, which really is for Kees to start, at least, um, which is, why was iCAD specifically the right move for RadNet and DeepHealth in this transaction? | |
| Kees Wesdorp: | 31:12 | Hey, thanks, Marshall. Look, I think first and foremost, I want to iterate what Dr. Sorenson's, uh, uh, presented is, um, mammography or, uh, fighting breast cancer or cancer, uh, screening and cancer detection is, is super, super important and voluminous for, for RadNet. Uh, it's a core competence, and it's, uh- RadNet has demonstrated leadership there. |
| 31:34 | So therefore, as DeepHealth, to be focused on that clinical domain is incredibly obvious, um, because of also the tight, um, integration that we have, vertical integration that we have with RadNet. Then if you look in the industry, we obviously carefully looked at leadership. Uh, iCAD, as Dana has very clear, uh- clearly mentioned in this, uh- in this presentation, uh, is a clear leader and with, uh, proven capabilities and a track record of impact. | |
| 32:04 | And then thirdly, I would say, um, you know, for us, scaling our capabilities, making sure that we have the most comprehensive suite to offer, and having the global reach, uh, were key determinants to get very, very excited about the opportunity that we have jointly with, uh- with iCAD. | |
| Greg Sorenson: | 32:26 | And I would just jump in and add, you know, um, this is... We're starting to see an evolution in how AI can help patients with breast cancer. Um, and as, as Sham pointed out when he walked you through with the Safeguard Review stuff, um, it's really clear that by adding this, uh, second physician, uh, in the- just the right cases, we can, in a very cost-effective way, um, really improve, uh, and deliver all the benefits that double readers have been shown to, you know- to bene- to, to deliver in multiple studies. |
| 32:56 | The question is, how can you do that in a cost-effective way in the US system? As RadNet has demonstrated this, now payers have started to, um, embrace this. We've got a couple of payers who already- employers who've already said, "We want EBCD for all of the, um, employees." We have all the covered lives in, in our pool, essentially. These are typically ERISA plans. | |
| 33:17 | And we're talking with some commercial insurers who expect that over the coming, uh, months and years, dozens or more companies will, will embrace this. Well, how can... RadNet can't meet that demand. So we were looking, we'll go, how... If we've got this lifesaving technology that really makes a difference, how do we get it out there? And iCAD's reach and, um, its trust with, uh, so many customers and so many, uh, practitioners just seemed like a really good fit. | |
| 33:44 | So just to reemphasize what Kees said, this was just a natural evolution of where DeepHealth, um, is going. And, uh... And a perfect example of how, uh, tools that have been shown to work so well at RadNet, not just AI, but other workflow tools can now be spread to a much greater group of, uh- a, a group of healthcare providers. |
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Marshall Manson: | 34:05 | Great. Thank you very much, uh, both. Um, the next question, uh, Sham probably comes to you to start. Uh, how many AI products, uh, with FDA authorization does RadNet currently own? Uh, and how many would it own after completing the iPad- iCAD acquisition? |
| Sham Sokka: | 34:24 | Um, if you're talking about just FDA, I think, uh, we have about, uh, uh, seven FDA approved products, uh, in the AI domain, uh, just in the AI domain. And then with, uh- with, uh, iCAD, we would add another, uh, uh- another, uh, uh, one, but two that are pending in various stages of, of, of, uh, pending. Now, the other opportunity here is, um, in some ways you get to combine models, uh, and, and bring, you know, multiple approved models together to drive, uh, uh- to improve the accuracy. |
| 35:01 | So that's another area that we're looking at as we get into the integration with iCAD. And there's also opportunities as we now take those- all those AI products and now start to put them together with our viewing and reporting products. Um, we're also creating other medical devices as well, uh, uh, going forward. | |
| Kees Wesdorp: | 35:21 | Yeah. And... And Sham, we're- |
| Dana Brown: | 35:23 | I think that is- |
| Kees Wesdorp: | 35:23 | Yeah, go ahead, Dana. |
| Dana Brown: | 35:24 | Clarify just a little bit. So for FDA clearance for iCAD, Sham mentioned on the one is our core product detection, although detection comes in multiple versions, each of which have its own FDA clearance. So there's 2D, there's 3D, there's our version 3, our version 4. So there's multiple in the detection family. We just keep it simple, right, and talk about detection. The other, um, algorithm, the other solution that has FDA clearance is our density solution. So there are actually two families, um, that have FDA clearance. |
| Marshall Manson: | 35:58 | Great. Uh, thanks very much. Dr. Sorensen, did you wanna get in on that one as well? |
| Greg Sorenson: | 36:03 | No, I think they- they've covered it nicely. I think that it's, um... When... Once you start about individual product, just as Dana said, it's easier to think about the families. |
| Dana Brown: | 36:11 | Yeah. |
| Greg Sorenson: | 36:12 | Uh, and so there's a detection family, uh, and then there's, uh... I would say she's nicely said, there's- both companies have had density and detection, uh, then there are these, uh, added workflow things, and I think the bigger portfolio that, uh, that Sham laid out, um, is, is really the right vision to have. Thank you. |
| Dana Brown: | 36:28 | Mm-hmm. |
| Marshall Manson: | 36:30 | Great. All right. Thanks very much. So, uh, Sham, and next one for you as well, uh, until the integration occurs, will DeepHealth continue to provide iCAD's current products as standalone? |
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Sham Sokka: | 36:41 | Yeah, let me clarify. Um, until integration, we're not- we're operating as two separate companies. So iCAD will continue to, um, provide their product, you know, as they see fit. Um, it's important to maybe just remind that- uh, folks here, right? So we're in a... We've signed and announced the acquisition. |
| 36:59 | Um, the... The formal close requires board approval and various other steps, uh, which we'll go through the summer. And in that period, iCAD is, uh, managing its business. And, uh, I'll let Da- Dana comment on that, but I think absolutely they're continuing to, um, um, | |
| Dana Brown: | 37:15 | Yeah. |
| Sham Sokka: | 37:16 | ... offer and sell their products. And the intention is a- absolutely to do the same, uh, post-close as well. |
| Dana Brown: | 37:25 | Yep. |
| Marshall Manson: | 37:25 | Brilliant. Dana, did you wanna get in on that one? |
| Dana Brown: | 37:27 | That was perfectly said. Um, continue to operate standalone till we get through shareholder approval. Um, and then at that point in time, we get all the smart folks in the room from the engineering and research teams and, and collectively figure out our roadmap and future together, so... |
| Marshall Manson: | 37:46 | Super. All right. Um, thanks very much. We've got another question, and I think this is probably to Dr. Sorensen. Um, who currently pays for ProFound in the US? Is it the patients as an add-on fee like EBCD, or will they be absorbed by a provider? |
| Greg Sorenson: | 38:04 | Right, great question. So, um, it takes a little bit of history just to follow this. So, um, uh, back when iCAD got its approval, you know, 16 plus years ago-ish, as, uh- as Dana mentioned- |
| Dana Brown: | 38:15 | Mm-hmm.. |
| Greg Sorenson: | 38:16 | ... um, Medicare actually had a separate payment, um, for computer aided detection. And then in 20, I think it was 17 or 2018, uh, Medicare bundled that payment into the payment for a screening mammogram. So today, Medicare says they're paying for a mammogram with or without, um, uh, uh, computer-aided detection. So in a sense, Medicare's already paying for the ProFound tool. |
| 38:42 | And so that- the, the, um, provider receives that money from a payer, Medicare or whoever, and then uses that budget to buy their equipment, to pay their radiologist to, um, pay per- for profound, et cetera. What's different about EBCD is in addition to the computer-aided detection, which is part of what that Medicare bundle is, there is computer-aided diagnosis, which is not part of what Medicare does. That's CAT-X as opposed to CAT-E technically. |
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| 39:09 | But then there's also these two other, uh, uh, steps. There's the adjudication process, which is a separate FDA product, and then as I mentioned earlier, the physician who comes in, and that's really extra work. And those, there are no CPT codes for today. Uh, and in fact, Medicare specifically says they won't pay for dual readers. So, uh, that's why EBCD had to have some other payment mechanism. | |
| 39:31 | And that's why, you know, when, when RadNet decided to offer, uh, and couldn't, uh- that, um, offering it, it came up with a way for patients to self-pay and now some employers, and we, um... Blue Cross Blue Shield of, um, uh... No, who is it? I think it's, um... One of the payers in New Jersey, I can't remember the specific name, actually does facilitate coverage for that employer group, et cetera. So I think we'll see- we see the EBCD self-pay as a transition. | |
| 39:56 | Here now speaking as RadNet, as a transition until payers pay, just like with 3D. Uh, those of you who are- have been around the block know that when 3D first came out, um, many payers did not pay for it. And now almost all payers do cover it because patients were self-paying, some cases $75 extra to get 3D, uh, mammography. Uh, and eventually, uh, payers said, "Okay, we can see the benefits. We'll cover it." | |
| 40:20 | We think unless there is a, uh- a period where somebody pays, the payers will essentially never come around. And so we're on that transition path, but the... Certainly the end game is not to have patients have to pay out of pocket, but to essentially, um, convince the payers with data that patients do value it, they're willing to pay, and that there's clinical value, so they should pay it. | |
| 40:39 | That's kind of how things work, it seems in America. Um... Uh, and so this is quite different than what ProFound, ProFound has already essentially included in the bundle, as well as, um, the other, uh, um, traditional CAT-V tools. | |
| Sham Sokka: | 40:54 | And maybe just a s- a very simple clarification of this, right? I think there's a lot of, um, misunderstanding that, that people are pay- some people are charging for AI and some people are not charging for AI. It... It's really not the case, right, um, as, as Greg is sort of highlighting. What... What different providers have done is create enhanced screening packages that have various tools embedded in them that are beyond the core CAD, uh, assisted, um, mammography service, right? |
| 41:23 | And I think that this, this sort of debate is sort of- is sort of- is sort of a false debate because there are really different packages and different offerings in these enhanced screening packages, right? There's even differences in what RadNet is doing as an enhanced screening package versus some of the other providers. | |
41:39 | Um, they include different things in their bundle, right? And... And that's really... When you get into the details, you could- you'll- you'll kind of... It's easy to extract. See. |
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| Marshall Manson: | 41:50 | Fantastic. Thanks Jim, very much. And the next one, I'm afraid, comes straight back to you. Um- |
| Sham Sokka: | 41:54 | Yeah. |
| Marshall Manson: | 41:55 | On a technical level, uh, how do SmartMammo and ProFound, uh, kind of individually... Their techs, how do they complement one another? |
| Sham Sokka: | 42:05 | Yeah. Um, it... It's a great question. So I think there- as I stated earlier, um, what's- what's really great about ProFound is the broad, uh, coverage of different systems and different, uh, mammography modalities, right? So we talked about 2D, 3D mammography. Um, uh, ProFound also covers many different multimodality- modality types than the, um- the DeepHealth, uh, uh, uh, AI asset, uh. |
| 42:29 | DeepHealth AI asset, right, primarily is Hologic, um, uh, uh, and GE 3D, right? And what we see, uh, an opportunity... And... And the nice thing about, uh, DeepHealth there is we have lots of validation data and very, uh, significantly improving cancer detection rates in very large populations. For example, it's been studied in over 600,000 women, um, uh, in, uh- at RadNet. | |
| 42:55 | And we've- we have shown when we've- when we deliver that in kind of this enhanced screening package, we can get up to 21% improvement in cancer detection. So meaning for every five cancers we find, we find a sixth one, right? So that strong sort of outcome, right, combined with sort of this, uh, um, um, offering which kind of can bring a large base. | |
| 43:20 | And as we put the two models together, I think there's an enormous potential, um, to really create a model that is, um, profound (laugh), um, that, that actually has a dramatic effect in, uh- in, uh, outcomes. And we, you know, uh, see as a potential basis, uh, toward the semi-autonomous, autonomous mammography space over time, right, in the mid to long term horizon. And that's really quite exciting for us, um, as we look at the deep tech, uh, and the ML part, uh, you know, of the business. | |
| 43:56 | One final thing I'd like to add there is, um, ProFound also brings, uh, a strong collaboration with Google, uh, where they've built, uh, uh, you know, uh, a 2D model, uh, uh, together. And again, that potentially also adds to our arsenal, uh, as we start to, uh, put these tools into the market. | |
| Marshall Manson: | 44:16 | Fantastic. Thanks, Sham very much. Kees, last question is for you, uh, for, for... Perhaps I suspect a brief answer, but just to confirm, is the intention to retain AI detection software from iCAD and utilize in your- utilize it in your portfolio along with SmartMammo Dx? Or is there any plans to integrate those at this stage? |
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| Kees Wesdorp: | 44:38 | Yeah. Yes and yes, but I would say, uh, and Sham should also weigh in, um, for sure these will exist, uh, in- certainly initially next to each other. Um, and we intend to continue that roadmap, whether it's ProFound and whether it's the- that's called SmartMammo Dx element. But as Sham has said, certain parts of the ProFound, uh, algorithm, um, are just wider encompassing in terms of system coverage, in terms of 2D versus 3D. And as this move forward, that capabilities will be integrated. |
| 45:10 | Um, now when and how, that's something for, uh, the distance. Uh, not the distance. That's something for the near f- near future. But it's not something that we will rush, uh, because it requires customer validation, install base validation. Uh, and... And in fact, like we said, we are very, very excited about the core offering of ProFound. Sham, any, uh, further, uh [inaudible 00:45:33] | |
| Sham Sokka: | 45:33 | No, I think I'll just emphasize... I think, uh... Uh, I think what I'll- I'll just emphasize, a little bit of what, um, is happening in, in sort of the cutting edge of AI is this really this notion of model ensembling where you take multiple models and put them together. It's kind of like, you know, a, uh- the safeguard review for rats, right? You have a primary reader and a secondary reader. |
| 45:52 | Think about AI doing the same. You have a primary, secondary. They work together. One might pick up things that the other one doesn't pick up. And so you can really bring that together in an- in an ensemble approach. And then as we, you know, uh, approach the market, uh, it's another option, uh, we can bring, um, to sort of really drive, uh, outcomes. It's really what's [inaudible 00:46:14]- what we're really excited about. | |
| Marshall Manson: | 46:17 | Great. Uh, thanks so much, uh, and indeed, thanks to all of you. Uh, really good discussion. Thanks also to everybody who joined us. Uh, that brings us to the close of today's session. Uh, we hope co- today's conversation has provided a clear view of the exciting future ahead in breast cancer screening. Uh, I, for one, I'm certainly interested to see how this combination will flourish. |
| 46:38 | Uh, if you'd like to arrange follow-up interviews or have any additional questions, please don't hesitate to reach out to Fabian or Andra. Thanks again for being here, and we look forward to sharing more as the partnership moves forward. Thanks again. Have a great day. |
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No Offer or Solicitation
This communication does not constitute an offer to sell or the solicitation of an offer to buy any securities or a solicitation of any vote or approval, nor shall there be any sale, issuance or transfer of securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of such jurisdiction. It does not constitute a prospectus or prospectus equivalent document. No offering or sale of securities shall be made except by means of a prospectus meeting the requirements of Section 10 of the Securities Act of 1933, as amended (the “Securities Act”), and otherwise in accordance with applicable law.
Important Information about the Proposed Transaction and Where to Find It
In connection with the proposed transaction between RadNet, Inc. (“RadNet”) and iCAD, Inc. (“iCAD”), RadNet plans to file with the Securities and Exchange Commission (“SEC”) a registration statement on Form S-4 that constitutes a prospectus of RadNet and will also include a proxy statement of iCAD. After the registration statement has been declared effective, iCAD will mail the proxy statement/prospectus to its stockholders. The proxy statement/prospectus to be filed with the SEC related to the proposed merger will contain important information about RadNet, iCAD, the proposed transaction and related matters. RadNet and iCAD may also file other documents with the SEC regarding the proposed transaction. This communication is not a substitute for the proxy statement/prospectus or any other document which RadNet or iCAD may file with the SEC. Investors are urged to carefully read the proxy statement/prospectus and other documents to be filed with the SEC (or incorporated by reference into the proxy statement/prospectus), as well as any amendments or supplements to these documents, in connection with the proposed transaction, when available, because they will contain important information about the proposed transaction and related matters. Investors will be able to obtain free copies of the registration statement on Form S-4 and the proxy statement/prospectus (when available), and other documents filed by RadNet or iCAD with the SEC through the website maintained by the SEC at www.sec.gov. Copies of the documents filed with the SEC by RadNet can be obtained by contacting RadNet’s Investor Relations by telephone at (310) 445-2800 or by mail at 1510 Cotner Avenue, Los Angeles, California 90025. In addition, investors are able to obtain free copies of the documents filed with the SEC on RadNet’s website at www.radnet.com (which website is not incorporated herein by reference). Copies of the documents filed with the SEC by iCAD can be obtained by contacting iCAD’s Investor Relations by telephone at (608) 882-5200 or by mail at 2 Townsend West, Suite 6, Nashua, New Hampshire 03063. In addition, investors are able to obtain free copies of the documents filed with the SEC on iCAD’s website at www.icadmed.com (which website is not incorporated herein by reference).
Participants in the Solicitation
RadNet, iCAD and their respective directors and executive officers may be considered participants in the solicitation of proxies from iCAD’s stockholders in connection with the proposed transaction. Information about the directors and executive officers of RadNet is set forth in its proxy statement for its 2024 annual meeting of stockholders, which was filed with the SEC on April 26, 2024. Information about the directors and executive officers of iCAD is set forth in its proxy statement for its 2024 annual meeting of stockholders, which was filed with the SEC on April 29, 2024. To the extent holdings of RadNet’s or iCAD’s securities by its directors or executive officers have changed since the amounts set forth in such filings, such changes have been or will be reflected on Initial Statements of Beneficial Ownership on Form 3 or Statements of Beneficial Ownership on Form 4 filed with the SEC. Other information regarding the participants in the proxy solicitations and a description of their direct and indirect interests, by security holdings or otherwise, and other information regarding the potential participants in the proxy solicitations, which may be different than those of RadNet’s stockholders and iCAD’s stockholders generally, will be contained in the proxy statement/prospectus and other relevant materials to be filed with the SEC regarding the proposed transaction. You may obtain these documents (when they become available) free of charge through the website maintained by the SEC at http://www.sec.gov and from the investor relations departments at RadNet or iCAD or from RadNet’s website or iCAD’s website, in each case, as described above.
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Forward-Looking Statements
This communication contains certain “forward-looking statements” within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act and Section 21E of the Securities Exchange Act of 1934, as amended. Forward-looking statements can be identified by words such as: “anticipate,” “believe,” “could,” “estimate,” “expect,” “forecast,” “intend,” “may,” “outlook,” “plan,” “potential,” “possible,” “predict,” “project,” “seek, “should,” “target,” “will” or “would,” the negative of these words, and similar references to future periods. Examples of forward-looking statements include statements regarding the anticipated benefits of the proposed transaction, the impact of the proposed transaction on RadNet’s and iCAD’s business and future financial and operating results and prospects, the amount and timing of synergies from the proposed transaction and the closing date for the proposed transaction are based on the current estimates, assumptions and projections of RadNet and iCAD, and are qualified by the inherent risks and uncertainties surrounding future expectations generally, all of which are subject to change. Actual results could differ materially from those currently anticipated due to a number of risks and uncertainties, many of which are beyond RadNet’s and iCAD’s control.
Forward-looking statements are neither historical facts nor assurances of future performance. Instead, they are based only on management’s current beliefs, expectations and assumptions regarding the future of RadNet’s and iCAD’s business, future plans and strategies, projections, anticipated events and trends, the economy and other future conditions. Because forward-looking statements relate to the future, they are subject to inherent uncertainties, risks and changes in circumstances that are difficult to predict and many of which are outside of RadNet’s and iCAD’s control. RadNet’s, iCAD’s and RadNet’s actual results and financial condition following the proposed transaction may differ materially from those indicated in the forward-looking statements as a result of various factors. None of RadNet, iCAD or any of their respective directors, executive officers, or advisors, provide any representation, assurance or guarantee that the occurrence of the events expressed or implied in any forward-looking statements will actually occur, or if any of them do occur, what impact they will have on the business, results of operations or financial condition of RadNet or iCAD. Should any risks and uncertainties develop into actual events, these developments could have a material adverse effect on RadNet’s and iCAD’s businesses, the proposed transaction and the ability to successfully complete the proposed transaction and realize its expected benefits. Risks and uncertainties that could cause results to differ from expectations include, but are not limited to: (1) the termination of or occurrence of any event, change or other circumstances that could give rise to the termination of the merger agreement or the inability to complete the proposed transaction on the anticipated terms and timetable, (2) the inability to complete the proposed transaction due to the failure to obtain approval of the stockholders of iCAD or to satisfy any other condition to closing in a timely manner or at all, or the risk that a regulatory approval that may be required for the proposed transaction is delayed, is not obtained or is obtained subject to conditions that are not anticipated, (3) the ability to recognize the anticipated benefits of the proposed transaction, which may be affected by, among other things, the ability of RadNet or iCAD to maintain relationships with its customers, patients, payers, physicians, and providers and retain its management and key employees, (4) the ability of RadNet following the proposed transaction to achieve the synergies contemplated by the proposed transaction or such synergies taking longer to realize than expected, (5) costs related to the proposed transaction, (6) the ability of RadNet following the proposed transaction to execute successfully its strategic plans, (7) the ability of RadNet following the proposed transaction to promptly and effectively integrate iCAD into its business, (8) the risk of litigation related to the proposed transaction, (9) the diversion of management’s time and attention from ordinary course business operations to completion of the proposed transaction and integration matters, (10) the risk of legislative, regulatory, economic, competitive, and technological changes, (11) risks relating to the value of RadNet’s securities to be issued in the proposed merger, and (12) the effect of the announcement, pendency or completion of the proposed transactions on the market price of the common stock of each of RadNet and iCAD. The foregoing review of important factors should not be construed as exhaustive and should be read in conjunction with the other cautionary statements that are included elsewhere. Additional information concerning risks, uncertainties and assumptions can be found in RadNet’s and iCAD’s respective filings with the SEC, including the risk factors discussed in RadNet’s and iCAD’s most recent Annual Reports on Form 10-K, as updated by their respective Quarterly Reports on Form 10-Q and future filings with the SEC, as well as the proxy statement/prospectus to be filed with the SEC in connection with the proposed transaction.
Forward-looking statements included herein are made only as of the date hereof and, except as required by applicable law, neither RadNet nor iCAD undertakes any obligation to update any forward-looking statements, or any other information in this communication, as a result of new information, future developments or otherwise, or to correct any inaccuracies or omissions in them which become apparent. All forward-looking statements in this communication are qualified in their entirety by this cautionary statement.
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