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RadNet’s Big AI Play | X-Ray NFT
January 27, 2022
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Together with
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“If I test positive I have to isolate – i.e. be a radiologist for 5 days.”
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A tweet from Saurabh Jha, MD.
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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 State of AI
Considering your short and long-term AI plan? Check out Canon Medical’s State of AI Roundtable, sharing insights into how imaging AI is being used, where it’s needed most, and how AI might assume a core role in medical imaging.
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Evolving with VidiStar
Learn how Fujifilm Healthcare’s VidiStar PACS system evolved to meet the needs of pediatric cardiologists in this Imaging Wire Q&A.
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- X-Ray NFT: We finally have a medical imaging NFT story, but it’s not as fun as some might have hoped. A French orthopedic surgeon is being sued by his former patient after trying to sell an NFT of her bullet-lodged forearm X-ray. The surgeon believed this scan was particularly NFT-worthy because the patient was among the survivors of Isis’ November 2015 Paris attack (he was asking nearly $2,800).
- CTA Labor Surge: A new MGH study showed how emergency department CT angiograms have produced “a surge of extra work.” Analysis of 4,368 ED aortic CTAs performed between 2005 and 2015 revealed major increases in images per scan (487 to 2,819) and reformat series per scan (6.4 to 13.7), with similar jumps in the proportion of exams that included recommendations (1.8% to 28.9%) and verbal communication (9.3% to 24.6%). When combined with MGH’s ~60% ED CTA volume growth, these increases certainly added labor, but they didn’t result in a higher proportion of CTAs with aortic findings (down from 28% to 25%).
- Aidoc and Novant’s Platform Partnership: Aidoc announced an AI platform partnership with large North Carolina-based health system Novant Health (15 medical centers, 3 states, >1,800 physicians). Novant will leverage a range of Aidoc triage solutions (ICH, PE, c-spine fracture, abdominal free air) to cut its emergency department treatment and discharge times.
- SWE for Rotator Cuff Repair: A new AJR study suggests that shear-wave elastography (SWE) deserves a role alongside MRI for rotator cuff surgery planning. The South Korea-based researchers performed preoperative SWE and MRI exams on 74 patients, finding that patients with higher SWE-derived elasticity (≥2.51 elasticity ratio) were far more likely to have insufficient repairs (100% specificity, 90% specificity).
- LEGO’s MRI Outreach: If you noticed LEGO MRI trending on Twitter this week, it’s because the toymaker is distributing model MRI scanners to hospitals across the world to help pediatric patients deal with pre-scan anxieties. The LEGO MRIs won’t be commercially available, but have been in the works for quite a while.
- Underreported CT-Guided Findings: A new EJR study revealed that procedural images from CT-guided interventions might be a diagnostic blind spot. The Beirut-based authors had two radiologists review 1,336 procedural CT images and compare findings to the pre-surgical reference images (CT, MRI, PET/CT), discovering additional diagnostic findings in 81 of the exams (6.1% – 32 new, 8 characterization, 41 changes). The majority of these procedural CT findings were likely clinically significant (73%) and most weren’t documented in the procedure report (63%).
- Radiologist AI Buy-In: A recent Aunt Minnie editorial by TeraRecon CTO, Sinan Batman, outlined a radiologist-centric approach to drive system-wide AI adoption. Batman reviewed imaging AI’s current radiologists’ trust/adoption barriers (e.g. training/validation/decision transparency, poor workflow integration/interoperability), suggesting that AI providers who address these issues and tackle the most “annoying” tasks will get radiologists on-board. From there, Batman believes radiologists can become the ideal starting point for an enterprise-wide AI strategy.
- Hologic’s Super Bowl Debut: Hologic will run a 30-second commercial during Super Bowl LVI (estimated >100M viewers), promoting the importance of early detection and encouraging women to return to screening. The women’s health leader will reportedly enlist “A-list talent” to share this message (Hologic has worked with Oprah Winfrey, Mary J. Blige, and Sheryl Crow in the past) and will keep the ad going throughout the 2022 Winter Olympics.
- CXR AI for COVID Risk: A new study in Intelligence-Based Medicine detailed how a modified version of Qure.ai’s qXR chest X-ray AI tool (M-qXR) could be used to guide COVID patient management. The researchers had four radiologists and M-qXR analyze 625 CXRs, finding that 98% of M-qXR’s interpretations matched the radiologists’ ground truth, while predicting positive PCR test results with an 89.7% PPV and 80.4% NPV (based on medium to high M-qXR risk scores).
- SubtleIR’s Fast-Track Grant: Subtle Medical landed a NIH Fast-Track Small Business Innovation Research (SBIR) grant to fund the development of its SubtleIR solution that aims to cut fluoroscopy radiation dosage by 83%. Subtle previously won a SBIR grant for its SubtleGAD solution (would cut MRI GBCA dosage by 90%), and currently has FDA/CE-cleared solutions to speed up PET and MRI exams (SubtlePET & SubtleMR).
- Michigan Streamlines Breast Biopsies: Michigan Medicine detailed how it streamlined its breast biopsy workflows after experiencing significant increases in breast MRI and MRI-guided breast biopsies between 2014 and 2018 (395 to 766/yr; 41 to 102/yr). The health system revised its pathway from three separate visits (MRI > MRI-directed ultrasound > ultrasound or MRI-guided core biopsy) to two by sending patients with non-mass enhancement and foci directly to MRI-guided biopsy (skipping ultrasound) and by supporting same-day MRI-directed ultrasound and core biopsy. As a result, patients requiring two visits (31% to 61%) and MRI findings biopsied by ultrasound (47.5% to 55%) both increased.
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ExplainThisPaper: Medical AI research, explained simply.
Scientific papers are hard reads. So ExplainThisPaper’s team of doctors and data scientists summarize new groundbreaking research into bitesized emails. Subscribe to turbocharge your research knowledge.
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- The flow of new AI applications makes it hard for radiology groups to determine which tools would help them and how IT teams can handle increased AI adoption. In this Blackford Analysis white paper, radiology and IT leaders from NYU and Canopy Partners share how a platform approach alongside a curated marketplace can help solve these challenges.
- When Birmingham Radiological Group-GV adopted Nuance PowerScribe One, the practice eliminated 60-75 minutes in daily reporting time and reduced calls to the radiology reading room by 80%. See how in this Nuance Case Study.
- See why the time is right for imaging AI-enabled population health in this Hardian Health profile featuring Nanox AI’s Zohar Elhanani.
- Learn how Salem Regional Medical Center improved its radiology workflows and cut service and syringe expenses after adopting Bayer’s MEDRAD Stellant FLEX system.
- The USPSTF guidelines for lung cancer screening were updated in May 2021, and driving compliance to such guidelines is a long, slow, repetitive process. Because of that, the Riverain team put together a kit to help hospitals and imaging centers educate either referring physicians or patients on the new guidelines either via branded tools or through the media.
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