RadNet advanced its AI-led cancer screening strategy, acquiring a 75% stake in Heart & Lung Health, a UK-based teleradiology network with a direct connection to the NHS’ lung cancer screening program.
Heart & Lung Health (HLH) has a network of over 70 cardiothoracic radiologists, and provides teleradiology reporting services for the NHS and a variety of UK hospitals and academic institutions.
Acquiring a UK telerad company might seem out of character for RadNet, which has historically focused its M&A on US-based imaging centers (and more recently global AI developers), only mentioned Europe once in its 2021 annual report, and exited the teleradiology business in 2020. However…
- HLH is the leading reporting provider for NHS England Targeted Lung Health Check (TLHC), an AI-enabled lung cancer screening pilot program that might pave the way for a UK-wide program.
- TLHC requires all radiologists to use AI with their LDCT screening interpretations, suggesting that AI might also be required in a future UK-wide program.
- HLH uses RadNet’s Aidence subsidiary’s lung cancer AI tools, and HLH will work with Aidence to further develop its solutions.
RadNet started 2022 by acquiring two major cancer screening AI companies (Aidence and Quantib), which combined with its DeepHealth breast cancer AI business to support its ambitious new strategy to become a population-scale cancer screening leader.
That goal might have seemed like a longshot to some, given AI’s uncertain path forward and RadNet’s geographic concentration in just seven US states. However, last week’s HLH acquisition showed that RadNet remains very committed to AI-driven cancer screening leadership, and its strategy might not be as geographically-challenged as some initially thought.
RevealDx and contextflow announced a new alliance that should advance the companies’ product and distribution strategies, and appears to highlight an interesting trend towards more comprehensive AI solutions.
The companies will integrate RevealDx’s RevealAI-Lung solution (lung nodule characterization) with contextflow’s SEARCH Lung CT software (lung nodule detection and quantification), creating a uniquely comprehensive lung cancer screening offering.
contextflow will also become RevealDx’s exclusive distributor in Europe, adding to RevealDx’s global channel that includes a distribution alliance with Volpara (exclusive in Australia/NZ, non-exclusive in US) and a platform integration deal with Sirona.
The alliance highlights contextflow’s new partner-driven strategy to expand SEARCH Lung CT beyond its image-based retrieval roots, coming just a few weeks after announcing an integration with Oxipit’s ChestEye Quality AI solution to identify missed lung nodules.
In fact, contextflow’s AI expansion efforts appear to be part of an emerging trend, as AI vendors work to support multiple steps within a given clinical activity (e.g. lung cancer assessments) or spot a wider range of pathologies in a given exam (e.g. CXRs):
- Volpara has amassed a range of complementary breast cancer screening solutions, and has started to build out a similar suite of lung cancer screening solutions (including RevealDx & Riverain).
- A growing field of chest X-ray AI vendors (Annalise.ai, Lunit, Qure.ai, Oxipit, Vuno) lead with their ability to detect multiple findings from a single CXR scan and AI workflow.
- Siemens Healthineers’ AI-RAD Companion Chest CT solution combines these two approaches, automating multiple diagnostic tasks (analysis, quantification, visualization, results generation) across a range of different chest CT exams and organs.
contextflow and RevealDx’s European alliance seems to make a lot of sense, allowing contextflow to enhance its lung nodule detection/quantification findings with characterization details, while giving RevealDx the channel and lung nodule detection starting points that it likely needs.
The partnership also appears to represent another step towards more comprehensive and potentially more clinically valuable AI solutions, and away from the narrow applications that have dominated AI portfolios (and AI critiques) before now.