Platforms that host various AI applications and solutions focusing on a whole range of diseases offer much promise for medical imaging AI, according to Dr. Sanjay M Parekh, Senior Market Analyst at Signify Research, who shared his insights and forecasts for the booming market.
What are the current trends on the medical imaging AI market?
The market is still nascent, but it’s growing fast with many developments. Radiologists better understand the technology and the potential it offers, and as such are becoming more discerning when considering AI. The question has shifted from “do I need AI” to “how is AI going to benefit me?” Vendors are responding, and this is reflected in the product developments and broader strategies. It’s not just about offering an algorithm, but rather delivering an AI solution that offers greater value to the end user. For lung cancer, for example, having an algorithm that detected nodules was enough to garner attention several years ago. Now, vendors need to offer a more complete AI solution, which in addition to detection also measures the nodule size and volume, as well as provides characteristics of the nodule, such as the risk of it being malignant, to improve a patient’s prognosis. Such solutions offer greater value to a clinician than detection alone and are therefore more likely to be considered for purchase.
Another approach that some AI vendors have adopted is to mimic and replicate the way radiologists work. Rather than focussing on a particular aspect or finding, these AI solutions can identify a myriad of findings from a single scan.
Yet another approach is to create a workflow around a particular condition, for example stroke. Some vendors have done so by creating a solution that addresses the broader workflow around the condition, improving the turn-around-time from detection to treatment.
Another important trend in the medical imaging AI market is AI platforms. These solutions address the last-mile challenges faced by radiologists, including the back-end deployment, front-end integration, and orchestration of AI solutions. AI platforms are paramount as radiology AI scales, enabling efficient orchestration to deliver the image to the right application for analysis, before delivering the results back to the radiologist in a timely and seamless manner. Although the traction around AI platforms remains limited, their value proposition will increase as AI begins to scale and is increasingly adopted in radiology.
Which solutions have had more traction so far?
Many types of AI solutions have had differing success to date. AI solutions for stroke imaging, particularly those with a broader workflow component, have realized very good traction to date. AI solutions for fractional flow reserve (FFR), measuring blood flow in the coronary arteries from a CT, have also been very successful, including receiving regulatory approval and even reimbursement in multiple regions. Such is the success of these vendors that many AI vendors from China have also developed such solutions as part of their expansive product portfolios, and several of which have received NMPA (China) clearance.
AI solutions for breast imaging –primarily screening – have also benefitted from commercial traction, although AI solutions for digital breast tomosynthesis (DBT) will become increasingly popular compared to AI solutions for 2D mammography, due to the complexity and time it takes to read DBT images. Further, as DBT is increasingly adopted across Europe for screening, the demand for such solutions will also increase.
Chest imaging is another clinical segment that has benefitted from AI, and comprehensive AI solutions, whether for chest X-ray or CT, have gained the most traction due to the value they confer, includ- ing identifying incidental findings beyond the primary read.
What is the market worth today?
As per our latest report published in July 2022, the medical imaging AI world market is forecast to reach $ 1.4 Bn by 2026, up from an estimated $ 400 M in 2021. However, several barriers need to be addressed for this potential to be realized. The lack of reimbursement, including the limited number of CPT codes, remains one of the most significant barriers to date. Other obstacles include the lack of real-world clinical validation demonstrating the generalizability of AI solutions, and lack of health economic studies demonstrating the return-on-investment (ROI) of AI solutions. Furthermore, other global headwinds and the deadline for the European Union Medical Device Regulation (MDR) may also hold back this market.
However, as outlined above, progress is being made thanks to continued investment into the market. Medical imaging AI companies have raised close to $5Bn in venture capital funding since 2015, which is a very healthy amount.
The challenge remains for vendors to generate commercial traction by delivering a ROI for investors. A significant proportion of this funding is skewed towards companies from China. However, in contrast to the US, for example, the revenues generated by these companies for their AI solutions remains low.
Where do you see the market going next?
In the short term, we will see a greater influence on the market from companies from China. As the country increasingly adopts AI, but remains relatively closed to nonnative vendors, it provides a great opportunity for native vendors to realize commercial traction. Other regions where commercial traction will also grow, despite some regions lacking the necessary infrastructure to adopt AI, include India and Brazil. In the mid to longer term, this market will start to mature as AI becomes more ubiquitous in radiology. However, further growth may be spurred on by significant tailwinds in the market, including new CPT codes, and reimbursement for a greater range of tools, especially beyond the US.
Investment in the market will taper off as investors become more discerning and place a greater emphasis on companies which they perceive to offer greater value to providers or are likely to receive reimbursement for their solutions. When reimbursement in medical imaging AI becomes more commonplace, it will likely prompt a renewed enthusiasm from investors given the defined return-on-investment that such companies will benefit from. However, this is unlikely in the near term.
Has the Covid-19 pandemic had an impact on the market?
Covid-19 did not have lasting impact, but it has modestly slowed the pace of commercialization of some solutions. Some countries such as the US were far less affected compared to other regions, e.g. Asia, where more stringent lockdowns persisted for a longer period. However, one of the positive effects of the pandemic was highlighting the broader need for digitalization, including the need for the healthcare industry to follow and adopt newer technologies such as AI at a faster rate. https://
Bayer has recently acquired Blackford Analysis. Why are pharmaceutical companies taking an interest in AI?
There has been a growing interest from companies outside of algorithm developers in the AI market, including pharmaceutical companies. One of the reasons for this is to mitigate the risk of contrast agents being less used in radiology. Another is that such companies may want to expand their reach within this market, especially as commercial traction ramps up. As I highlighted in the Signify Premium Insight addressing this topic, the move will ultimately enable such vendors to be well positioned as demands in radiology change (e.g., less use of contrast agents, greater adoption of AI), rather than playing catch-up later. Other similar developments include Guerbet investing in Intrasense – with the view of potentially acquiring it –, and Tempus acquiring Arterys.
