Cancer Moonshot

The Biden administration “reignited” the US’ Cancer Moonshot initiative, setting a goal to halve the country’s age-adjusted cancer death rate within the next 25 years. Here’s how they plan to achieve this “Moonshot” of a goal, and what that means for imaging.

Cancer Moonshot History – Biden spearheaded the Obama administration’s Cancer Moonshot initiative, inspired by losing his son to brain cancer. The 7-year initiative used $1.8B in federal funding to improve cancer therapeutics, prevention, and detection through scientific discovery, collaboration, and data sharing.

The Reignited Moonshot – The revamped initiative inherits these same goals and approaches, while adding new focus areas and operational structures:

  • Overcoming the COVID pandemic’s cancer screening backlog
  • Addressing inequity in cancer incidence, detection, and care
  • Developing new treatments for rare and childhood cancers
  • Fast-tracking the development of multi-cancer tests
  • Improving the experience of cancer survivors and caregivers
  • Leveraging data to “turn our cancer care system into a learning system”
  • Creating a cancer research funding program modeled after DARPA
  • Appointing federal Cancer Moonshot leaders to coordinate this work

Imaging Alignment – Any government attempt to overcome cancer screening backlogs and to make early detection mainstream would surely result in more imaging, while the Moonshot initiative’s focus on “learning from data” could hold imaging AI upsides. That said, the announcement placed a much brighter spotlight on non-imaging areas (blood tests, vaccines, treatments), and few people on the clinical side of radiology believe more imaging is necessarily better for patients.

Moonshot Critics – The Cancer Moonshot initiative has its fair share of critics, who argued that cutting cancer deaths by 50% would require “curing” cancer (not just catching and treating it), expanding screening has downsides (radiation, unnecessary treatments), and that initiatives like this are largely done for appearances.

The Takeaway
The White House just made the fight against cancer a top administrative priority, meaning that a lot more government attention and resources are on the way, and notable changes in cancer imaging policies and volumes might follow.

Creating a Cancer Screening Giant

A few days after shocking the AI and imaging center industries with its acquisitions of Aidence and Quantib, RadNet’s Friday investor briefing revealed a far more ambitious AI-enabled cancer screening strategy than many might have imagined.

Expanding to Colon Cancer – RadNet will complete its AI screening platform by developing a homegrown colon cancer detection system, estimating that its four AI-based cancer detection solutions (breast, prostate, lung, colon) could screen for 70% of cancers that are imaging-detectable at early stages.

Population Detection – Once its AI platform is complete, RadNet plans to launch a strategy to expand cancer screening’s role in population health, while making prostate, lung, and colon cancer screening as mainstream as breast cancer screening.

Becoming an AI Vendor – RadNet revealed plans to launch an externally-focused AI business that will lead with its multi-cancer AI screening platform, but will also create opportunities for RadNet’s eRAD PACS/RIS software. There are plenty of players in the AI-based cancer detection arena, but RadNet’s unique multi-cancer platform, significant funding, and training data advantage would make it a formidable competitor.

Geographic Expansion – RadNet will leverage Aidence and Quantib’s European presence to expand its software business internationally, as well as into parts of the US where RadNet doesn’t own imaging centers (RadNet has centers in just 7 states).

Imaging Center Upsides – RadNet’s cancer screening AI strategy will of course benefit its core imaging center business. In addition to improving operational efficiency and driving more cancer screening volumes, RadNet believes that the unique benefits of its AI platform will drive more hospital system joint ventures.

AI Financials – The briefing also provided rare insights into AI vendor finances, revealing that DeepHealth has been running at a $4M-$5M annual loss and adding Aidence / Quantib might expand that loss to $10M- $12M (seems OK given RadNet’s $215M EBITDA). RadNet hopes its AI division will become cash flow neutral within the next few years as revenue from outside companies ramp up.

The Takeaway

RadNet has very big ambitions to become a global cancer screening leader and significantly expand cancer screening’s role in society. Changing society doesn’t come fast or easy, but a goal like that reveals how much emphasis RadNet is going to place on developing and distributing its AI cancer screening platform going forward.

RadNet’s Big AI Play

Imaging center giant RadNet shocked the AI world this week, acquiring Dutch startups Aidence and Quantib to support its AI-enabled cancer screening strategy.

Acquisition Details – RadNet acquired Aidence for $40M-$50M and Quantib for $45M, positioning them alongside DeepHealth within its new AI division. Aidence’s Veye Lung Nodules solution (CT lung nodule detection) is used across seven European countries and has been submitted for FDA 510(k) clearance, while Quantib’s prostate and brain MRI solutions have CE and FDA clearance and are used in 20 countries worldwide.

RadNet’s Cancer Screening Strategy – RadNet sees a huge future for cancer screening and believes Aidence (lung cancer) and Quantib (prostate cancer) will combine with DeepHealth (breast cancer) to make it a population health screening leader. 

RadNet’s AI Screening History – Even if these acquisitions weren’t expected, they aren’t out of character for RadNet, which created its mammography AI portfolio through a series of 2019-2020 acquisitions (DeepHealth, Nulogix) and equity investments (WhiteRabbit.ai). Plus, acquisitions have been a core part of RadNet’s imaging center strategy since before we were even talking about AI.

Unanswered Questions – It’s still unclear whether RadNet will take advantage of Aidence / Quantib’s European presence to expand internationally or if RadNet will start selling its AI portfolio to other hospitals and imaging center chains.

Another Consolidation Milestone – All those forecasts of imaging AI market consolidation seem to be quickly coming true in 2022, following MaxQ’s pivot out of imaging and RadNet’s Aidence / Quantib acquisitions. It’s also becoming clearer what type of returns AI startups and VCs are willing to accept, as Aidance and Quantib sold for about 3.5-times and 5.5-times their respective venture funding ($14M & $8M) and Nanox acquired Zebra-Med for 1.7 to 3.5-times its VC funding ($57.4M).

The Takeaway

It seems that RadNet will leverage its newly-expanded AI portfolio to become the US’ premier cancer screening company. That would be a huge accomplishment if cancer screening volumes grow as RadNet is forecasting. However, RadNet’s combination of imaging AI expertise, technology, funding, and training data could allow it to have an even bigger impact beyond the walls of its imaging centers.

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-- The Imaging Wire team