Tag Archives: Sanjay Parekh

Signify Premium Insight: The Power of Perspective: AI Vendor Sentiment Index Q2

This Insight is part of your subscription to Signify Premium Insights – Medical ImagingThis content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify ResearchTo view other recent Premium Insights that are part of the service please click here.

Co-written by Dr Sanjay Parekh

Each vendor has a unique view of the market. One of the deliverables offered as part of Signify Research’s AI in Medical Imaging Service, the Vendor Sentiment Index (VSI), captures these views and assesses how confident vendors are feeling about the overall imaging AI market outlook, their ability to establish pilot sites and their ability to convert the pilot sites to paying customers or secure new commercial deals over the coming months and years.

With a cocktail of global headwinds, including inflationary pressures and the risk of a global recession, geopolitical tensions, and stretched healthcare systems dealing with a myriad of other priorities, AI vendors could be expected to be nervous about the months ahead. However, with recent success in procuring new (relatively large) funding, and shifts in potential reimbursement (e.g., new CPT codes), there are, for some at least, also reasons to be cheerful.

The Signify View

Data for the latest edition of the survey was collected from vendors during Q2 (April 1st – June 30th) and offers insight into their sentiment towards the following quarter (calendar Q3) and the upcoming 12 months. It includes data from 26 AI vendors, ranging from those with strong global prominence to those which are relatively unknown, alongside engagement from informatics vendors representing more than 58% of radiology global market share, including 6 of the top 10 vendors according to Signify’s vendor market share data.

Some of the findings of the Q2 survey are consistent with the results from the Q1 analysis. AI vendors, for instance remained more confident than their imaging IT counterparts. This makes sense. Imaging IT vendors are, for the most part, longer established, have more historical experience of the market, and frequently interact with a broader array of healthcare providers, companies providing support and tertiary services, and other vendors. Their point of view is likely to be wider than that of a smaller AI vendor, which has a more specialised focus on its market. As such, imaging IT vendors could face a larger number of risks or face greater exposure to them compared to dedicated AI vendors.

In addition, young, hungry AI vendors, developing not only new products but entirely new product categories, using hitherto unutilised technology, and attempting to sell their wares to often sceptical and cash-strapped providers need to be bullish. Why would they take on such a challenging endeavour if they didn’t believe their product promised worthwhile returns?

There are also some more pragmatic reasons AI vendors can be confident in the face of incoming global headwinds. While providers still face barriers such as clinical validation and technical and legal hurdles, which are stymieing the adoption of medical imaging AI tools, progress is being made. In June, for example, Optellum’s solution became eligible for reimbursement, highlighting that AI solutions are making progress towards becoming more cost-effective and a viable value proposition beyond efficiency gains. During the quarter, there were also some significant funding rounds, such as Viz.ai’s $100m haul, highlighting that AI vendors aren’t out on a limb, with investors also confident in the future of the technology. This, in turn, bolsters the confidence of AI vendors’ Q3 and beyond outlook, as reflected in the VSI.

One of the major observations, however, was that the overall results for the second VSI survey (Q3 outlook) were more conservative and less positive compared to the first VSI survey (Q2 outlook). This was especially true for vendors’ outlook on commercial deployments, which is likely to be a significant influence behind the gloomier outlook in the market overall.

Summer Slowdown

Another trend that held over from the Q1 index was that vendors were more confident about the coming 12 months rather than the coming quarter. This is understandable. The Q3 period, July, August and September, is, especially in Europe, often slower for businesses. Staff are taking vacations, and major purchases and installations are often delayed until the autumn. As such for the three metrics assessed (overall market outlook, pilot installs and commercial deployments), it is likely that vendors expect less activity over the summer months, ramping up over Q4 as teams get back from the summer holiday period, and events like RSNA give them a chance to promote their products.

As such, an uplift in confidence should be seen in the next survey, for which data is currently being collected, which assesses vendors’ confidence in Q4 onwards. This will prove to be something of an acid test. If confidence remains low, it could illustrate the severity of the challenges ahead, and weigh on the overall market outlook for the year ahead. Adoption of AI in medical imaging has long been forecast to be a measured process, but a lack of confidence in the ability to find pilot sites and secure new commercial deployments will highlight that the rollout will take longer than expected.

Alternatively, the fall in confidence seen in the Q2 index may instead represent a return to “normality” after the overconfidence observed among some vendors in Q1. At that time some vendors were perhaps overly bullish, with the lingering optimism from the last RSNA show, and the recession of the Omicron wave of Covid-19 offering a cause for confidence. However, it appears vendors may have failed to consider the other global challenges affecting the fortunes of the AI and imaging IT market performance.

Cooling Confidence

How significant the impacts of this tempering of confidence remains to be seen. It could represent nothing but a periodic bump in the road, with the overall trend of the market still overwhelmingly positive. Alternatively, there could be several, relatively swift repercussions. For imaging IT vendors, which are juggling lots of different priorities, a lack of confidence in the near-term commercial potential of AI solutions, including AI platforms, could encourage them to increasingly focus on these other areas. They are, after all, also looking to facilitate transformative changes among providers, with cloud adoption, enterprise imaging strategies, and workflow integrations, among the other burgeoning trends.

This could be particularly true given the reduction in confidence of securing commercial deployments for both AI vendors and in particular imaging IT vendors, whose confidence fell 2.3 points from 7.0 to 4.7 for the quarterly outlook, and 1.9 points for the 12-month outlook from 7.7 to 5.8. AI vendors are focused only on selling their AI solutions, whereas imaging IT vendors must focus on selling a wider portfolio, which often offers greater margins. Customers could expect some AI functionality as part of a broader imaging IT deal, or AI tools could be used as an incentive to make a deal, for example, with these types of negotiations relying on the sacrificing of AI’s potential for broader commercial aims.

Year-End Celebrations

Despite these nuances, confidence among both imaging IT and AI vendors is, overall, expected to improve in the next survey, with vendors likely to feel more optimistic about both the outlook in Q4 and the following 12 months, in terms of both commercial deployments and pilot sites. There are several factors, from funding to reimbursement that have emphasised the potential of the market going forward. Beyond that, RSNA presents vendors with an opportunity to demonstrate and promote products. The corollary of this expected optimism will be a shrinking of the gap in confidence levels between AI and Imaging IT vendors. Imaging IT vendors are likely to have new AI products at RSNA, while the AI capabilities added to their existing solutions will also have matured, rendering AI a more important part of their offering.

Conversely, if the optimism of imaging IT vendors continues to lag severely behind that of AI specialists, it could either signal a change in strategy and a de-emphasising of AI, or market traction is far slower than previously anticipated, despite AI vendors’ bullishness. Longer-term, other trends could start to dampen vendor confidence, which may represent difficulty in the overall market. Increased competition, for example, could make it more difficult for individual vendors to secure pilot sites or commercial deployment, hurting their confidence. However, the fact that the market can sustain such competition is indicative of its overall health (and depth of investors’ pockets). Another, similar factor ties into the ongoing product evolution of AI solutions. As tools are becoming increasingly sophisticated and focusing on entire care pathways and downstream outcomes, or evolving into comprehensive solutions, for example, less complex tools risk being commodified. As this happens, some AI capabilities may become ‘just’ another feature of an imaging IT system, rather than a stand-alone product with a robust value proposition. Some vendors would see this opportunity very differently to others, resulting in varying confidence levels.

Such concerns can be left for the future. At present, different vendors are drawing different conclusions about the opportunity the market offers. The coming quarters offer a chance for AI to make significant progress, allowing vendors to close out the year on a high. However, if this fails to happen, and vendors still fail to see the upside, 2023 could instead become a year of reflection and renewal instead of growth and optimism.

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Signify Premium Insight: AI Making the Move to Maturity

This Insight is part of your subscription to Signify Premium Insights – Medical ImagingThis content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify ResearchTo view other recent Premium Insights that are part of the service please click here.

Dr Sanjay Parekh, Senior Analyst

The medical imaging AI market is among the most dynamic of all the sectors in medical imaging. Its nascency, its rate of technical development and the application of the technology are combining to create a market that is changing incredibly quickly.

Despite the volatility of the market, senior analyst and author of Signify Research’s AI in Medical Imaging report, Dr Sanjay Parekh, has been able to discern several key trends in the market.

Great Growth

“The market for AI-based image analysis tools for medical imaging is set to reach $1.36bn by 2026,” Parekh states, “up from $402m in 2021.” Much of this revenue is for stand-alone AI tools, but AI-based advanced visualisation (AV) bundled AI tools are also included (accounting for 27% of the total market in 2021).

This represents a CAGR of 27% between 2020 and 2026, highlighting that the AI market is gaining momentum, many of the reasons for which are clear.

“There was for instance a large flurry of regulatory approvals in 2020 and 2021. In the US in 2020 for example, there were more approvals than in 2018 and 2019 combined. There was also the first wave of NMPA Class III approvals in China. With these regulatory approvals vendors can commercialise their tools.

“As well as having more products on the market, there has been continued progress with regards to reimbursement. There is the continued reimbursement for HeartFlow’s FFR-CT solution in the US, the UK and Japan, as well as parts of Europe. Additionally, pockets of China are already reimbursing the use of FFR-CT tools, but national reimbursement is still pending. There has also been a flurry of Category III CPT codes [for which there is no compulsory reimbursement] provisioned for quantitative image analysis tools for ultrasound, MRI and CT, which as well as encouraging the uptake of AI, could lead to reimbursement. While NTAP payments have also been renewed and expanded, such as the recent Optellum clearance, which has defied the norm and will now receive reimbursement for its Virtual Nodule Clinic solution for lung cancer despite the CPT code remaining as Category III.

“All of these factors combined will help the markets continue to grow.”

Areas of Interest

Growth will not be equal across all clinical segments, however, with four areas, which currently represent around 87% of the market, set to continue to stand out. These are cardiology, neurology, pulmonology, and breast imaging, with each having facets that mean they are likely to continue powering growth for AI vendors.

Use of AI is the most mature in the breast imaging market; however, opportunities for growth are more limited than elsewhere. “Because of the relatively limited number of use cases; namely breast nodule detections and breast density analysis, the breast imaging market will not to be as large as the other three,” continues Parekh.

“Cardiology is likely to account for the largest proportion. This will be driven by two factors. The first is increasing uptake and continued reimbursement for FFR-CT tools. Even accounting for its failed SPAC merger, HeartFlow, one of the success stories for the medical imaging AI market, has a relatively large install base and strong commercial traction as well as still offering an appealing value proposition. There are also opportunities for FFR-CT, especially in China, as vendors like Keya Medical, Shukun Technologies, and Raysight receiving regulatory approval for their FFR-CT tools.

“In addition, clinical guidelines recommending CT imaging as a first line diagnostic procedure will drive the adoption of AI.”

Stroke care is also set to rally.

Neurology will be a growth area mainly because of stroke imaging AI solutions. The NTAP code for stroke LVO, which was first issued in 2020 to Viz.ai and then renewed in 2021, was renewed again in 2022 and it looks set to be made permanent soon, thanks to the uptake of stroke imaging AI tools and the increased use of the code in such instances.

“Not only has the payment been created, but providers are using it and its use shows that providers value the end-to-end stroke solutions which benefit the entire care pathway as well as the radiologist.”

There are also other opportunities within neurology, with brain quantification tools, for example achieving moderate success. Some vendors offering such tools are generating revenue, but, while these will continue to be valued, other drivers such as the commercialisation of drugs for neurodegenerative disease are needed before they become a major driver of growth.

“Finally, in pulmonology, the relative value of using AI market is smaller compared to FFR-CT or head CT for example. Although there are vendors working on comprehensive solutions for both chest X-ray and chest CT that do restore that value, the most successful among them are setting a benchmark for other tools looking to gain traction. Further, the continued roll-out of screening programmes for lung cancer and TB, for example, will drive further traction in this market.”

Relinquishing a Point

There are commonalities across these clinical areas, however. It is becoming clear that the utility of point solutions across modalities and clinical areas is in general, very limited. Developers who can only offer single point solutions are looking increasingly unlikely to be selected by providers.

Instead, tools that offer the most value to providers will gain success. This value, however, can manifest in various ways. Many solutions focus on efficiency, but there are also solutions that could actually slow diagnoses, but still enhance the quality of a diagnosis by offering additional metrics, for example. This value is, in some cases, also no longer derived from incremental improvements in specificity or sensitivity that new tools might offer.

“If you offer 93% accuracy compared to 92%, is that going to make a difference,” Parekh asks. “Are you going to get a better diagnosis or is the patient going to be on a completely different treatment pathway? No. Instead value is extended beyond the analysis of the pixels in an image, to patient care and improvements to the clinical care pathway. The vendors that have started doing that are the ones that are going to succeed.

“Breast imaging tools, for example, that combine detection, quantification and classification of nodules, which are far more valuable than those which only offer nodule detection. Moreover, adding in breast density analysis will enhance the value proposition of such a solution even further. More significantly, however, are the tools that are looking at radiology more broadly and seen to offer value across the clinical care pathway (beyond the radiologist). These solutions can come from vendors which solely offer AI, or those which also offer capability to deploy and integrate AI.

“These vendors can bring in advanced visualisation capabilities, workflow capabilities and even structured reporting capabilities to address a given use case, while also offering their own native or third-party AI image analysis capabilities to create entire workflow packages. That is AI demonstrating value.”

Money to Money

Value is also forthcoming in a broader sense. Despite the turbulence in some tech markets and in some corners of the medical imaging market, investment for medical imaging AI vendors is still available, although it is becoming more discerning.

“Investors seem to be more than willing to continue to back vendors that have already shown progress,” opines Parekh, “but we are not seeing many Angel or Series A rounds.”

“Where we are seeing a lot of action is for the later-stage funding rounds, which are increasing in both size and number. This indicates that a set of market leaders are being established, such as the $100m funding club [a term coined by Signify Research including vendors that have received more than $100 million in total in venture capital funding]. Even with this greater investment in established companies we are starting to see evidence of a market shakeout.

“Last year we saw Nanox acquire Zebra Medical Vision, at the start of 2022 we have seen MaxQ-AI closing its radiology business, and Sirona acquiring Nines. RadNet, a large outpatient imaging group in the US also acquired two Dutch-based AI start-ups Aidence and Quantib to add to its portfolio after previously acquiring DeepHealth, and expand its push to deploy AI across screening for some of the most prevalent cancers. There is also some speculation about some other vendors also making pivots after not receiving funding that was expected. We have seen consolidation coming for a long time, but between the investment being focused on the largest vendors, and the difficulties for the smaller vendors, we are starting to see the shakeout take place.”

The impact of this market shakeout will be different in different regions. One area that is more difficult to make predictions for is Europe. Presently, the Western European market is starting to catch up with the US, but this growth is expected to stagnate in May 2024 when the new European Union Medical Device Regulation (EU MDR) is coming into force. There is currently a backlog of 12 to 18 months for vendors to upgrade their CE Mark to the incoming regulation, not to mention the more stringent requirements for this regulation. This raises the possibility of many vendors missing the deadline and therefore being unable to offer their products commercially in the EU.

Approval Ratings

This could have significant impacts, say Parekh.

“It is more likely that the larger vendors, the ones with the funds to pursue the MDR, will be the first to receive it. If you are a smaller vendor, then you may not want to, or be able to go for MDR approval. Ultimately, that will leave those that have MDR certification by May 2024 with an ‘early-to-market’ advantage over those that don’t. It could effectively level the playing field, and serve as a reset button, with only those that have been able to secure the new certification, regardless of past CE Mark approvals. This regulatory backlog is also therefore likely to hold back the market as a whole.

“It could also lead a lack of innovation, with smaller start-ups and research groups shifting their focus from radiology, keen to avoid the additional barriers they must pass, so there could also be a short-term innovation gap. This is another reason we could see more consolidation in the market.”

Despite these challenges the future is still bright for medical imaging AI vendors. The market increased by more than $60 million between 2020 and 2021, and growth is only set to continue. This shows a young market taking the first steps to maturity and a nascent technology making the first moves toward more mainstream adoption.

“Overall,” Parekh concludes, “it is growing, at a steady pace for now but with a big ramp up in the medium term, from 2024 onwards.”

“All signs are positive.”

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Terarecon logo on silicon chip

Signify Premium Insight: The Concerted Effort that TeraRecon Must Make

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Last month saw Boston-based vendor ConcertAI secure $150m in series C funding, adding to the $150m series B round in 2020 and boosting the company’s valuation to $1.9bn. The AI start-up, which specialises in offering real-world data to life sciences firms to manage regulatory clearances and develop clinical trials, and supporting healthcare providers to improve patient experience, will use the money to scale its software solutions.

The funding puts ConcertAI in a strong position. But will AV and medical imaging AI firm TeraRecon, which was integrated into ConcertAI in November 2021, also see any benefit?

The Signify View

TeraRecon first became linked to ConcertAI after being acquired by corporate parent SymphonyAI in March 2020. This portfolio of companies seeking to develop new generation AI solutions across a variety of sectors, from retail to financial services, brought TeraRecon on board and placed it alongside stablemate ConcertAI. At the time the deal seemed to offer clear synergistic opportunities for both parties such combining population data from ConcertAI with imaging biomarker technology and expertise to improve patient stratification for oncology clinical trials. Alternatively, providers could utilise imaging data from TeraRecon alongside EHRs and real-world data from ConcertAI to develop more integrated care management solutions.

Since then, however, TeraRecon has been relatively muted. Instead of revealing new, integrated products, public releases and announcements have slowed and several key c-suite personnel have left. This seems something of a regression from several years ago when TeraRecon was among the earliest of AI vendors to promote the AI-marketplace-platform model, securing patents and forging ahead with a novel approach to radiology AI’s last-mile challenges. Moreover, the senior leadership at TeraRecon were at the forefront of every industry debate and event discussing the role of AI in medical imaging.  Concurrently, the vendor was among the strongest independent AV vendors, securing good market share and beginning to make connections between AV and AI.

The firm hasn’t given up much ground from this position in AV, a market that moves slowly after all, but neither has it moved forward whilst other vendors have made headway, somewhat negating its early ascent. One initiative, for example, was to integrate AI tools from its platform with its own AV capabilities, packaging the combinations into specialist “premium” suites that were more attractive than individual tools. While TeraRecon’s progress slowed on this front, imaging IT vendors, AV vendors and modality vendors have incorporated competitive AI offerings, increasingly eroding the specialism that allowed TeraRecon to shine.

Move to the Money

Against this backdrop of increased competition and lengthy implementation cycles for clinical AI, integrating TeraRecon into ConcertAI is a sound move that offers a more direct route to financial success. Making significant returns in clinical AI is a difficult and drawn-out affair. The technology’s profitability is stymied by several barriers including a lack of reimbursement and a lack of financial impact studies, as well as the fundamental question of who will foot the bill. In preclinical and life sciences, on the other hand, the route to returns is much clearer, with pharmaceutical firms willing to invest in specific drug discovery projects, effectively using ConcertAI or alternatives as an external research team with project or milestone-based fee structures. This approach enables ConcertAI to gain commercial traction whilst waiting for the clinical market to mature. In the near term this could leave TeraRecon as a diagnostic imaging specialist whose expertise is applied to the preclinical space, with areas such as companion diagnostics a potential strength. For ConcertAI, having such expertise in imaging analysis in-house, and promising to utilise imaging data alongside other clinical data, could be a major selling point, improving the vendor’s odds of courting big-pharma and top academic provider interest.

Despite that, in the grand scheme of ConcertAI’s opportunities, TeraRecon’s existing AV business does not appear to be a  priority. ConcertAI has recently announced strategic agreements with the likes of Pfizer and Bristol Myers Squibb, so the returns of its funding round will be spent on the development of capability and service that can support such multi-billion-dollar companies. TeraRecon is not a central part of that strategy. It will, for the most part, be able to maintain the share it has carved out for itself within the AV IT market mid-term, and its technology will lend an edge to ConcertAI in preclinical, but it is unlikely to be able to chart its own course, and invest in its own growth in AV, as it would have been able to prior to its acquisition.

A Deal to be Done?

Given this impasse at which TeraRecon sits, it could be seen as an attractive acquisition target by vendors looking to round out their imaging IT portfolio. While ConcertAI will value TeraRecon’s AI capabilities and the vendor’s AV expertise, aside from being a dependable, albeit comparatively small source of revenue, it will be a lower priority to the vendor. As such ConcertAI could look to pare of TeraRecon’s AI abilities to bolster its preclinical and life sciences package, and then sell off the remaining AV business.

There are several vendors that would both benefit from such an acquisition and have deep enough pockets to make it a reality. Two of the most obvious names are Intelerad and IBM Watson Health. Since private equity investor HG Capital acquired a majority stake in Intelerad in early 2020, the imaging IT vendor has been on an acquisition spree, picking up Ambra, Digisonics and LumedX among others.

The vendor has also shown that it is beginning to link together the capabilities of these formerly disparate businesses into one cohesive whole (see In Step with the HIMSS Set, Intelerad Marches Forward). However, this enterprise imaging platform to-be, as yet lacks an AV solution, an omission that could be readily addressed by the acquisition of TeraRecon. What’s more such a deal would also net the vendor TeraRecon’s 10% share of the North American AV IT market in 2021, handily propelling Intelerad’s total imaging IT market share from 3.5% to 5% in North America.  The story is similar for IBM Watson Health. Freed from the wider tech business Watson Health’s new owners, Francisco Partners, could handily add TeraRecon’s AV capability and market share, to advance Watson Health’s along its enterprise imaging journey.

The Here and Now

For ConcertAI, the funding is another sign of confidence in strategic focus on real world evidence for life sciences. With a valuation of $1.9bn, it is clear great things are expected of the start-up. These, in the near term at least, are unlikely to come from TeraRecon and its strengths in image analysis or AV capability.

There is an advantage to using image analysis in its preclinical and drug discovery remit. Longer term there are lucrative possibilities such as the identification and cataloguing of imaging biomarkers, enabling diseases to be increasingly diagnosed from imaging alone, reducing the need for biopsies and other interventional diagnostic procedures. Such tools could be commercially successful, but would first require significant investment in research and development and would still take several years for any sizable returns.

Instead, it seems that TeraRecon, and the capabilities it brings, may not be the best complement to ConcertAI’s trajectory, while the company’s recent quietude and personnel changes also suggest change could be afoot.

Ultimately, regardless of its origins, this change could be welcome, with the clinical markets in which TeraRecon blossomed, increasingly under pressure; AV tools are being incorporated into broader imaging IT platform vendors to enhance diagnostic capability, interest is growing in edge AI and modality vendors are looking to bring such technology to their hardware, and there is growing appetite for the care pathway approach. Competition from leading imaging giants such as Siemens Healthineers, Philips and GE Healthcare is only going to intensify as AV is encompassed into broader diagnostic care packages of modality, edge AI, diagnostic viewer and service line offerings, while emerging AI platforms such as Blackford Analysis, Aidoc and others attempt to carve out their own piece of the imaging analysis market.

ConcertAI’s funding round will not solve these problems for TeraRecon. However, as ConcertAI grows its path will increasingly diverge from TeraRecon’s AV heartland, forcing the latter to act. Whether that is as part of a different parent, or in new partnerships with others, change is essential. For TeraRecon, stasis is unsustainable.


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Signify Premium Insight: Viz.ai and the Perils of Success

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Medical imaging AI has a new unicorn, after Viz.ai secured $100m in funding at a $1.2bn valuation. The series D round brings Viz.ai’s total funding raised to more than $250m. This figure places it higher than almost all other vendors, with only HeartFlow and Shukun Technology having declared greater funding totals.

In the funding announcement, Viz.ai also revealed that more than 1,000 sites are now using its care coordination platform, which aims to expand on the vendors’ current focus on stroke detection and triage in order to aid and improve decision making in other clinical areas.

The Signify View

Viz.ai has, over the last two years, been on something of a roll. In August 2020 the Centers for Medicare & Medicaid Services (CMS) granted the vendor’s diagnosis and triaging solution (as well as others functionally equivalent) the first New Technology Add-on Payment for artificial intelligence software. This ruling meant that unlike almost all other AI solutions, providers could be reimbursed for the use of Viz’s tool. The vendor followed this up with a $71m series C funding round in March 2021 to finance Viz.ai’s expansion of its Intelligent Care Coordination platform into both other areas of clinical care and into other global markets. This round also propelled the vendor into the $100m club, of vendors with more than $100m of funding. Adding another $100m pushes Viz.ai into even more rarefied air, but also begs the question of what a vendor which has raised $170m in little over twelve months will do next.

This rapid progression suggests that Viz.ai could be heading towards listing publicly, with the vendor utilising its series D funding to pay for expensive product development to target other clinical areas, and sales activities to capitalise on other territories beyond the US. With these initiatives underway the time would be for ripe for Viz.ai to target an IPO and raise the capital it needs to attempt a rise to dominance. However, in reality, this path could prove to be problematic. One need only look at the attempts to list publicly by other large medical imaging AI vendors to see the challenges that could lie in Viz’s future. HeartFlow, example, raised more than $540m, with its latest funding round, a post series E, completed in 2019. In 2021 the vendor then decided to list publicly via a SPAC merger.  However, this plan was ultimately unsuccessful with the vendor abandoning the move earlier this year, citing unfavourable marketing conditions and an inability to properly value the company. More generally review of broader healthcare technology sector in 2022 year to date versus 2021 has seen a collapse of IPO and SPAC deal volume.

The Demands of the Market

A similar fate could befall Viz.ai, with the appetite of VC investors not necessarily translating into demand from public investors. However, there are differences between the two vendors. If Viz.ai decided to go public now it would be doing so with a valuation, that, while significant, is still more than half that given by HeartFlow when it announced its IPO. This could make such a move more manageable, with the more modest valuation more attainable than that of HeartFlow. Alternatively, Viz.ai could follow HeartFlow’s lead and continue to secure funding privately for several years, potentially even ultimately transitioning to private equity ownership, similar to Circle Cardiovascular Imaging. While the potential to raise significant amounts of capital is diminished by such a strategy, in the young and still maturing medical imaging market answering only to a handful of private investors, satisfied with nuanced yet strategic progress, rather than being obliged to deliver headline-grabbing figures to countless unsympathetic shareholders may be preferable.

There are also technological differences between the two vendors that could grant Viz.ai a very different experience to HeartFlow. While the latter remains, in essence, a vendor with a single tool, albeit one which is clinically very valuable, with a strategy to add other tools targeted at cardiovascular disease, the former is a vendor which has already progressed from offering a single algorithm into a vendor with a fleshed-out stroke care coordination platform, expanded beyond neurology. Conversely, HeartFlow is reliant on a single FFR-CT tool, this is an area with, at present, less competition. While there are vendors such as Keya Medical offering similar functionality, they remain focused on the Chinese market. Several young heart health AI developers could begin to offer their own alternatives, but at present HeartFlow is at limited risk from other vendors. In the stroke care space, however, there are numerous competent competitors, some such as RapidAI have already made headway in the US, Viz.ai’s key market, while others are operating and growing in other territories; potentially a significant challenge to Viz.ai’s international ambitions.

Options & Opportunities

This availability of other stroke detection algorithms could also prove a challenge for other reasons. Viz.ai’s image analysis capability is solid and dependable, but not unique. Instead, what presently sets Viz.ai’s Care Coordination Platform apart is the solution’s workflow element. Instead of focusing myopically on the tool’s diagnostic capabilities, the vendor sought to improve stroke diagnostic capabilities into a clinical care pathway, ensuring that the results of the diagnostics could actually benefit doctors, providers and patients. Even if Viz.ai’s stroke detection algorithm could be technically bettered,  its integration may allow it to have a greater impact.

Successful integration also breeds new challenges in terms of regulation and changing care workflows. While not specifically targeted at Viz.ai, the US-FDA’s recent public reminder on April 11th 2022 was a clear warning to vendors of AI-based triage tools for stroke care to be clear on intended use when marketing to providers, while also reminding providers that adoption of CADt must not replace radiologist diagnostic reporting on potential stroke cases regardless of triage prioritisation result.

Viz.ai has gained significant traction by touting its workflow capabilities more so than its AI image analysis capabilities. However, by securing sales based on this workflow integration, Viz.ai leaves itself more open to competitors. These, on the one hand could be other stroke solution providers, RapidAI for example has worked to improve the analytics and prehospital elements of its own product. As Viz.ai boasts of ever-increasing user numbers and ever higher valuations, other vendors, even those outside of stroke imaging could also be attracted to the space. Large healthcare IT vendors could use their scale and breadth of capability to target the market, offering solutions that link stroke care to other departments and either utilising in-house stroke detection algorithms or partner with one of Viz.ai’s competitors.

Electronic Health Record (EHR) vendors are another type of company that could be interested, these vendors are deeply integrated into hospital networks, but could use workflow tools as an opportunity to expand their reach.  There is some precedent for this, with several EHR vendors already offering breast imaging modules for mammography reporting as part of their Radiology Information System (RIS) modules.

With this heritage there is opportunity for the likes of Cerner or Epic, for example, to build on their existent platforms and develop workflow modules, leaving providers to simply partner with a stroke detection algorithm vendor of their choosing. The impetus for such moves will only increase should reimbursement become permanent, rather than the temporary NTAP at present. Although with this reimbursement being renewed for 2022, all signs point to reimbursement for stoke imaging AI becoming permanent. Not only would such a move make the space more lucrative, but including stroke detection within broader tools could make billing and claiming reimbursement more straightforward, attracting provider’s interest.

Suffering from Success

Despite the potential of such prospects, they remain in the longer-term future. For the time being Viz.ai will continue to gain traction. The company now has the necessary funds to enact its short and medium-term strategic objectives, adding significantly to the list of 1,000 sites it caters for and expanding beyond stroke care to take advantage of other lucrative clinical segments. What’s more, through its own activities as well as through partnerships, such as that with medical device company, Medtronic, Viz.ai should increasingly gain a footing in new markets, e.g., Europe, going toe-to-toe with local stroke detection algorithm developers.

How long these good times can continue to roll remains to be seen. Viz.ai has successfully built a useful and commercially viable product, which is enjoying great success in the meeting rooms of VC investment firms. This success, however, could bring more attention to the space and ultimately be responsible for a humbling of the vendor. Viz.ai must acknowledge this threat and act to capitalise on its current momentum and look to make itself indispensable. Now, like HeartFlow before it, Viz.ai will find that more money, really can mean more problems.

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Signify Premium Insight: Just Getting Started? Harrison.ai Raises $100m

This Insight is part of your subscription to Signify Premium Insights – Medical ImagingThis content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify ResearchTo view other recent Premium Insights that are part of the service please click here.

In recent weeks Australian AI developer Harrison.ai joined an exclusive club. After securing AUD129m ($94m) in Series B funding, the outfit has become one of the handful of well-funded medical imaging AI vendors that have raised more than $100m.

The funding, which brings Harrison.ai’s total raised in the last two years to over $120m, was led by returning investor Horizons Ventures and also saw participation from Blackbird Ventures and Skip Capital. These investment firms were also joined by Sonic Healthcare and I-MED Radiology network two Australian providers which have deployed Harrison’s AI offering, lending the round an unusual level of consumer, as well as financial, weight.

Beyond merely investing in the firm, these provider partners will also help Harrison.ai target new areas of healthcare, with the vendor announcing plans to target pathology, among others.

The Signify View

As medical imaging AI success stories go, HeartFlow’s is hard to beat. As discussed in a previous Premium Insight when the heart health developer listed, it set a new financial benchmark. When it first launched on the New York Stock Exchange, the vendor had a pro forma enterprise value of $2.4bn, becoming medical imaging AI’s first unicorn.

Another of medical imaging AI’s financial flyers is Infervision. This Chinese vendor was itself the subject of a Premium Insight when it received $139m in Series D funding in July, bringing its total funding to more than $210m (despite an undisclosed Series C funding round).

Look back a few years however and these vendors’ series B funding rounds pale in comparison to Harrison.ai’s with Infervision securing $47m in 2018, while HeartFlow’s series B was only $20.4m in 2011. Of course, changing markets and changing VC strategies mean that these figures aren’t directly comparable to the nigh-on $100m that Harrison.ai has just secured for itself, but it does indicate the kind of rarefied company that the vendor is joining. It also begs the question of how such a sum has been achieved.

Comprehensive Valuation

There are a number of factors that have gone into establishing its valuation, but at the core is Harrison.ai’s central product, its Annalise.ai diagnostic imaging AI. Key to this product is its comprehensive approach to diagnostic radiology. Most solutions automatically identify a number of findings on an X-ray, but still rely on a radiologist to identify those not covered. AI vendors are addressing these gaps using various methods including partnering with other developers to add additional capability or creating platforms and bundling individual algorithms into suites which address particular clinical requirements.

Annalise.ai instead aims to ‘solve’ a particular scan type (its focus so far has been chest x-ray) and automatically identify all possible findings on any given image. So far, its solution identifies over 125 findings. In doing so it aims to make the selection, deployment and use of AI easier for providers. Further value could also be added to the solution in future as additional workflow tools are included, such as structured reporting, for example.

This approach looks to be effective, with the vendor’s own validation studies, which were published in The Lancet Digital Health in July, showing that radiologists assisted by the tool performed better in the vast majority of cases than those that weren’t assisted. What’s more the model’s AUC was also found to be statistically superior to unassisted radiologists for almost all findings.

Beyond published research, however, real world indications also show the value of the tools, with several providers choosing to use the tools in their own hospitals, including Sonic Healthcare, and I-MED, which have gone on to invest in Harrison’s Series B funding round. The fact that customers have quickly become investors is quite the endorsement.

The company’s ambitions, however, do not stop at chest x-ray, and they are looking to develop comprehensive solutions to other high turn-over scan types. In the long run, the company wants to address most of the high turnover scan types via its potential portfolio of comprehensive AI solutions. Early on, this was viewed as a potentially risky approach, such is the breadth of competition that has homed in on higher-volume scan types like chest X-ray. However, the comprehensive findings approach in a singular offering has allowed Harrison to stand-out from the crowd of aspirant vendors, most of which are offering a singular or a limited number of findings.

Ambitions in Pathology

The performance of Harrison’s radiology AI offering is only half the story, however, with the vendor’s stated ambition in pathology also having an impact on its prospects.

AI applications in pathology do, after all, hold significant potential, but the conditions for this potential to be realised are not yet in place. The most significant challenge is the general under adoption of digital pathology. However, this is starting to change with several factors such as regulation changes in the US, and the turbulence created by Covid-19 highlighting the lack of digitisation in pathology and giving impetus for change.

As these and other catalysts continue to grow in significance, the adoption of digital pathology will increase. As evidenced at RSNA, this is also a trend among imaging IT vendors which will increasingly incorporate pathology into enterprise imaging platforms. Against this backdrop, pathology AI will be able to find a footing.

The quantitative nature of many tasks in pathology as well as the shortage of pathologists (which is even more acute than the shortage of radiologists) means it is an opportune discipline for AI to have a significant impact, especially as the breadth and complexity of pathology diagnostic findings is a multitude higher than in radiology. This could be particularly true for a vendor such as Harrison, which has been especially thorough with its approach to its comprehensive chest X-ray solution. Frankly, singular point applications will have limited traction in pathology.

Cohesive Competence

Harrison.ai is looking to take this cohesive approach further, expanding out of radiology and addressing another slice of the diagnostic workflow. Longer term this digital pathology tool, the chest X-ray tool and potential future tools could all be integrated, leaving solutions that are more complete in both individual areas, but also along the entire workflow. This cohesion could be particularly useful in areas like oncology, as the broader remit of such solutions would see the vendor providing a service rather than a technology solution. This would enable it to prompt purchasing decisions to be made at a more executive level (e.g., C-suite), tapping into a larger budget pool. However, multi-disciplinary convergence in diagnosis is only just gaining traction in care settings, so in the near and mid-term, Harrison should remain focused on serving each individual diagnostic sector to ensure continued success.

The fact that Harrison is also looking to develop its pathology tool alongside recent customer Sonic is also an advantage. Data is obviously one of necessities for vendors looking to develop AI solutions, but, for pathology in particular, this data is scarce. By partnering with Sonic, Harrison will have access to an abundance of clinical data for algorithm training and refinement, as well as a large user base on which to conduct pilot deployments and validation studies. These are all essential for the successful development of a digital pathology AI tool, and having a route to achieve these already in place will give Harrison an edge over some of its competitors.

Looking to develop a pathology solution was also shrewd from a commercial, as well as a clinical, perspective. While increasing numbers of medical imaging AI vendors are securing ever higher funding rounds, pathology vendors have recently tended to fare better as investors have noted that a surge to adoption is pending, with for example Paige securing $100m in a series C round in January, and PathAI netting $165m for series C in July. This disparity is in part a result of the applicability of some solutions to drug discovery, a market which harbours the greatest returns near-term, but also relates to the relative upside of tackling a pathology market that is still heavily analogue and therefore ripe for disruption.

Of Value and of Worth

In receiving $94m in series B funding, Harrison AI has joined a very exclusive group of medical imaging AI vendors funded over $100m. What’s more impressive is that it has achieved this at an earlier stage than any of its peers. The road ahead is long, and the money will be quickly allocated to address its often quite expensive priorities. Continued commercialisation of its chest X-ray solution will be the first order of business; securing US-FDA regulatory approval and selling into and supporting providers will also require significant funds. Looking further ahead, investing in product development for comprehensive solutions that address other high volume scan types will undoubtedly follow. In pathology, Sonic will provide a short-term commercialisation base, but in the more analogue pathology sector, the firm will also have to take on a degree of market education and evangelism, a process that can have a substantial cash-burn rate.

If these priorities can be achieved, and Harrison.ai can begin generating sizable revenues, then the trajectory for future funding rounds and potential listings could be unprecedented. Moreover, the vendor could have a profound influence on the direction of AI. Many of Harrison’s peers are trying to add value in different ways, such partnering to create suites and developing end-to-end solutions that address entire clinical workflows. Harrison.ai offers another way, creating truly comprehensive solutions for specific use cases and then expanding into other adjacent areas. If the vendor is able to achieve commercial success on a par with its funding success, the developer will no doubt sit alongside HeartFlow as a posterchild of the segment. This could be particularly true if the vendor decides to list in the future.

There are, of course, challenges ahead. A lack of standardisation in pathology could make things harder than the DICOM-based world of radiology, while looking to split focus, as well as investment, between different areas, particularly when the vendor is still so young, could prove to be detrimental to both. Doubly so as it begins to compete with more established competition on both fronts.

These are proportionately minor worries, however. Harrison.ai has progressed carefully and methodically and to the pain of its competitive peers, very quickly. Now, bolstered by extra cash, and guided clinically by its customer partners, the precocious vendor is ready to demonstrate that its worth extends far beyond its valuation.



About Signify Premium Insights

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify ResearchTo view other recent Premium Insights that are part of the service please click here