AI ISVs Partner to Deliver Value Beyond Radiology

Publication Date: 16/02/2023


Over 200 vendors compete for a share of the medical imaging AI market. However, despite this number, the overwhelming majority focus on many of the same use cases. Radiologists have also become increasingly more familiar with the benefits that AI can deliver and are more discerning about what they look for in AI solutions.

Vendors, in turn, have had to respond and deliver solutions beyond point algorithms to tools that provide value to the end user, whether the radiologist or the healthcare provider. AI solutions have had to demonstrate a greater depth or breadth by delivering multiple capabilities (for example, detection, triage, measurement, and diagnosis) or looking beyond image analysis and addressing the broader workflow. Focus has also shifted to demonstrating value upstream or downstream of the radiology workflow, or even beyond across multiple departments.

However, as AI independent software vendors (ISVs) have looked to expand their offerings, the challenge of scaling whilst continuing to deliver the value of their core offering has remained. One way in which some have approached this is by entering into partnerships with peers that expand their capabilities, enhance their product offerings, and deliver value to their customer base, especially to address the clinical pathway beyond radiology image analysis.

The objectives of partnerships vary, and more recently, there has been increasing evidence of vendors looking to partner with non-imaging AI vendors to deliver value to the healthcare provider. Some examples include vendors partnering to develop a comprehensive approach to treating a given condition, vendors partnering to create end-to-end solutions to improve disease identification, and even vendors creating ‚Äòvirtual clinic’ solutions. This insight explores some recent examples that leverage image analysis AI to deliver a solution of value.

Illuminating the Silent Killer

One of the more successful AI vendors,, has partnered with Illuminate, a leading company focused on discovery (at-risk patient identification from the EHR), follow-up, and patient management. Although the company has been successful in stroke imaging AI with its ‚Äòend-to-end’ solution, expansion to other critical conditions, such as aortic aneurysms, has prompted it to partner to drive improvements in quality of care rather than doing it alone. Illuminate uses natural language processing (NLP) and AI software to identify at-risk patients from electronic medical records, assess disease severity, and facilitate follow-up surveillance for other diseases.

Aortic aneurysms are seen as a ‚Äòsilent killer’, with few symptoms before it is too late. Although supports the detection of patients at risk for aortic aneurysms via imaging, earlier identification of patients and improved follow-up surveillance via Illuminate is critical to improving patient outcomes or even preventing the disease in the first place. The partnership enhances the value proposition of both vendors’ solutions whilst enabling them to remain focused on their technical ability and not compromise on quality.

Enhancing the Value of Screening

Similarly, Riverain Technologies has partnered with Thynk Health, a lung cancer screening and incidental finding management solution. The partnership aims to improve the detection and diagnosis of patients with lung nodules and improve incidental findings of the condition. Thynk Health integrates with EHRs and health systems to mine structured and unstructured data to support healthcare providers to be more efficient and effective at diagnosing lung cancers.

The partnership enhances these capabilities by leveraging Riverain’s AI technologies to improve the detection and diagnosis of lung nodules. It enables radiologists using Thynk Health’s Clear Visual Intelligence solution to provide an unobstructed view of the thoracic region (Riverain’s solutions remove bones from x-ray images and blood vessels from CT images) to improve interpretation of the findings.

Thynk Health focuses on identifying incidentals upstream of image analysis, and together with Riverain’s AI solutions, the companies can work towards more targeted screening and diagnosis of patients at risk of lung cancer.

Not Missing a Beat

Cleerly, on the back of its recent significant Series C funding round, has also partnered with Heartbeat Health. Cardiovascular disease is complex, but this partnership aims to simplify the route and speed at which a patient meets with a cardiologist.

Cleerly’s solution analyses CCTA to improve the earlier detection and identification of heart disease. The partnership enables at-risk patients to be immediately connected with a cardiologist (via Heartbeat Health) to discuss a treatment plan. The first steps of the follow-up are typically virtual, but patients may then be referred into the healthcare system as necessary. This improves patient management, especially for lower- to mid-risk patients that may be missed to follow-up, resulting in improved longer-term patient outcomes for patients.

Caption Health has previously also partnered with Heartbeat Health, but having been recently acquired by GE HealthCare, the agreement may be terminated.

Facilitating Short-Term Growth

These partnerships show how medical imaging AI vendors can leverage their products into broader solutions that have an impact on patient care. However, partnerships themselves present several weaknesses, including vendors being less able to control the narrative of how their solutions are utilized. In other cases, partnerships may not even be the best approach for a vendor and native developments would be favoured. There is also the risk that some partnerships may not be workable due to other partnerships or conflicts of interest.

However, for the above vendors and many other young AI vendors, partnerships are, for now at least, one of the more sensible routes to growth. It enables AI companies to deliver value beyond its use for image analysis for primary diagnosis. The approaches outlined above enable AI vendors to impact the broader patient pathway beyond radiology and ultimately improve patient care without both vendors straying from their core focus. In a market that is rapidly consolidating, the importance of scale and comprehensiveness is vital to future survival.