Blackford Analysis CEO Ben Panter on their decision to become part of Bayer.

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Artificial Intelligence

Bayer Establishes AI Platform Leadership with Blackford Acquisition

Six months after becoming radiology’s newest AI platform vendor, Bayer accelerated its path towards AI leadership with its acquisition of Blackford Analysis.

The acquisition might prove to be among the most significant in imaging AI’s short history, combining Blackford’s many AI advantages (tech, expertise, relationships) with Bayer’s massive radiology presence and AI ambitions. 

After closing later this year, Blackford will operate independently through Bayer’s well-established “arm’s length” model, allowing Blackford to preserve its entrepreneurial culture, while leveraging Bayer’s “experience, infrastructure and reach” to drive further expansion.

Bayer’s Calantic platform and team will operate separately from Blackford, providing Bayer customers with two distinct AI platforms to choose from, while giving Bayer two ways to drive its AI business forward. 

Although few would have predicted this acquisition, it makes sense given Bayer and Blackford’s relatively long history together and their complementary situations. 

• Blackford was part of Bayer’s 2019 G4A digital health accelerator class
• The companies have been working together to develop Calantic since 2020
• Bayer has big AI goals, but its AI customer base and reputation were unestablished
• Blackford’s AI customer base and reputation are solid, but it needed a new way to scale and a positive exit for its shareholders

Even fewer would have predicted that imaging contrast vendors would be the driving force behind AI’s next consolidation wave, noting that Guerbet invested in Intrasense just last week. However, imaging contrast and imaging AI could serve increasingly interrelated (or alternative) roles in the diagnostic process, and there’s surely advantages to being a leader in both areas for Bayer and Guerbet.

Speaking of AI consolidation, it appears that all those 2023 AI consolidation forecasts are proving to be correct, while bringing some of radiology’s largest companies into an AI segment that’s historically been dominated by startups. It wouldn’t be surprising if that trend continued.

The Takeaway

Bayer and Blackford have been working on their AI strategies for years, and this acquisition appears to give both companies a much better chance of achieving long-term AI leadership. Considering that AI is still in its infancy and could eventually play a dominant role in radiology (and across healthcare), AI leadership might be a far more significant market position in the future than many can imagine today.

Ramapo Radiology’s Case for Novarad CryptoChart

See how New Jersey’s Ramapo Radiology Associates overcame their CD burning problems and improved their physician and patient experiences with Novarad CryptoChart.

Precision Imaging’s Accelerated Enhancement

When one of Precision Imaging Centers’ 3T MRIs wasn’t meeting their requirements, they implemented Subtle Medical’s SubtleMR solution, rather than purchasing a new scanner or an expensive upgrade. See how SubtleMR enhanced Precision’s patient throughput and comfort, without compromising image quality in this case study.

The Wire

• CCTA’s Chest Pain Impact: The UK’s 2016 decision to recommend coronary CTA for chest pain significantly increased the country’s CCTA rates and likely improved outcomes. Analysis of 2012-2018 data (1.9M CAD investigations) showed that CCTA volumes grew by 15.7% per year after 2016 (to 85 exams per 100k patients), which was associated with reductions in myocardial infarction hospitalizations, and lower cardiovascular and ischemic heart disease mortality (Kendall Tau: −0.21; −0.22). The guidelines also modestly reduced invasive coronary angiography (Kendall Tau: −0.19).

• Qure.ai and NHS’ Same-Day Lung Cancer Screening: NHS England will launch a pilot lung cancer screening program leveraging Qure.ai’s qXR solution to notify doctors of suspicious findings in chest X-rays, and potentially allow same-day diagnoses. If the six-month Manchester area pilot is successful, the program could be expanded across the NHS. This is Qure.ai and AstraZeneca’s latest lung cancer screening collaboration, following a pilot to add lung cancer detection to TB screening pathways and other efforts to increase LC screening in developing countries.

• Cancer Rates Declining, Disparities Persist: The American Cancer Society forecast that the U.S. will see 1.95M new cancer cases and 609k cancer deaths in 2023, while highlighting how advances in cancer treatments have significantly reduced mortality rates (-2% 2016 to 2020, -33% since 1991). However, the report warned of increases in certain cancers (breast, uterine corpus, prostate) and disparities adversely affecting women and minorities.

• LDCT AI Cancer Risk Prediction: A team of Boston and Taiwan-based researchers developed an AI model, dubbed Sybil, that can predict patients’ future risk of lung cancer from a single low-dose CT scan (without clinical data or radiologist annotations). The Sybil model was validated on three data sets from the US and Taiwan (total: 27.3k scans), and performed well predicting lung cancer within one year (AUROCs: 0.92, 0.86, 0.94). 

• MRI Demand on The Rise: A new IMV Medical survey suggests that widespread MRI exam volume growth in 2022 (~70% of departments increased) will lead to future MR scanner demand, with 53% of sites considering adding a new scanner before 2025 (up from 51% in 2021). The pandemic’s impact on MR departments was at its lowest since 2020, with 24% of sites experiencing a medium/high impact from COVID in 2022, down from 65% of sites in 2021.

• CryptoChart Lite Expands to Developing Countries: Novarad expanded its CryptoChart Lite solution to developing countries, allowing providers in low-resource regions to share and access patient images at no-cost. Originally launched in the US and Canada last year, CryptoChart Lite is a complimentary version of Novarad’s established CryptoChart solution, similarly leveraging a printed encrypted QR code or web access code to support image storage and transfer (no CDs, logins, portals, or software installs). 

• Post-Surgery DCIS Surveillance: A new Radiology study revealed that half of patients don’t follow recommended imaging surveillance after breast-conserving surgery for primary ductal carcinoma in situ (DCIS). Analysis of 12.5k women found that surveillance adherence decreased from 75% in the first year after surgery to 52% through the first 5 years, while Black and Hispanic women were less likely to follow surveillance recommendations than White women (OR: 0.80 & 0.82).

• Pie Launches CAAS Qardia 2.0: Pie Medical Imaging announced its CAAS Qardia 2.0 echocardiography software, which adds the ability to synchronize stress echo images and right ventricular strain analysis. The web-based CAAS Qardia solution leverages AI workflows to perform key echo measurements, and provides quality control feedback to reduce echo image foreshortening.

• Gleamer’s Resident Impact: New research out of Germany found that Gleamer’s BoneView AI software can improve radiology residents’ fracture detection when integrated into clinical workflows. The study included 1,163 X-ray exams from 735 patients (w/ 367 fractures), finding that AI-assisted residents achieved far higher sensitivity than either AI-only or residents without AI (91.3%, 86.9%, 84.7%) while maintaining similar specificity (97.4%, 84.7%, 97.1%). AI-assistance led to 35 changes, correcting 33 diagnoses and identifying 25 additional fractures.

• Primary Aldosteronism PET/CT: Primary aldosteronism (PA) is a common cause of hypertension and it can be cured or improved with adrenal surgery, but less than 1% of PA patients receive treatment because they have to undergo invasive adrenal vein sampling (AVS) to be diagnosed. A new Nature study of 143 PA patients suggests that 11C-MTO-PET/CT imaging might change that, finding that the non-invasive exam predicted biochemical and clinical treatment success with greater accuracy than AVS (72.7% vs. 63.6%; 65.4% vs. 61.5%).

• Ferrum Adds $6M: Ferrum Health secured $6M in funding (total raised now $15M) to further the development of its Enterprise AI platform. Ferrum isn’t a household name, but its platform is already in use within well-known healthcare organizations (e.g. Sutter Health and Carle Clinic) and features AI apps from a number of established brands (e.g. iCAD, Coreline, Gleamer).

Us2.ai Matches Experts

What if AI could produce echo measurements that are comparable to expert physicians, but with less variability? That’s exactly what this Nature study revealed about Us2.ai’s solution, finding that its measurements had fewer and smaller differences compared to three human experts than when the experts were compared with each other.

Made in Texas. Built for the Modern World.

See how United Imaging’s fresh approach, vertically integrated structure, and unique “all-in” strategy is raising the bar in medical imaging.

CSE Paris’ Case of Arterys MSK AI

Check out this patient case study showing how the Arterys Chest I MSK AI solution allowed radiologists at CSE in Paris to identify a fracture that was missed in three previous interpretations.

The Resource Wire

• Despite significant interest, there’s still confusion about the value of imaging AI. This Blackford Analysis white paper explores the key cost considerations and ROI factors that radiology groups can use to figure out how to make AI valuable for them.

• Pandemic delays, conflicting screening guidelines, and a diverse mix of risk factors may put millions of women at risk of late breast cancer diagnoses. That’s why this editorial by Dr. Amy Patel of Liberty Hospital and Morris Panner of Intelerad emphasize the need to adopt the right technology and best practices to ensure providers can address this challenge.

• Check out this Change Healthcare video explaining the difference between single-tenant and multitenant cloud architecture, and how multitenant solutions can improve your efficiency and flexibility.

• When SyntheticMR validated its SyMRI MSK solution, they leveraged the CARPL platform to compare conventional knee and spine MRI image quality with SyntheticMR images. Check out their validation process and results here.

• We may be entering a third wave of imaging AI’s rapid evolution, that brings a shift from narrow point solutions to comprehensive multi-finding AI systems. Join this discussion with annalise.ai Chief Medical Officer, Rick Abramson, MD, exploring how this transition could take place, how radiologist and VC perspectives on AI are changing, and how AI might continue to evolve in the future.

• Ready to overcome the worklist paradox of choice? See how GE HealthCare’s Intelligent Workload Manager eliminates case selection decision-making burdens and helps reduce radiologist stress.

• “It has changed the face of neuroimaging.” That’s one of the takeaways from Christ Hospital’s experience becoming the first healthcare system in New Jersey to implement point-of-care MR imaging into neurocritical care. Learn about their implementation process and the impact of providing quick bedside MRIs in this Hyperfine webinar.

• This Riverain Technologies case study details how Duke University Medical Center integrated ClearRead CT into its chest CT workflows, reducing read times by 26% and improving nodule detection by 29%.

• Are you seeing the complete picture with your outdated cardiac PET imaging? Check out this Siemens Healthineers patient story, showing how cardiac PET/CT revealed microvascular diseases in a patient who had normal uptake on his PET exam.

• This Bayer case study details how radiation benchmarking programs can help push CT dose exposure reduction initiatives from achieving compliance to driving quality.

• Check out this talk from Eliot Siegel, MD on the “Hype, Myth, Reality and Next Steps” of imaging AI, including a profile on Canon’s AiCE Deep Learning Reconstruction solution at around the 4-minute mark.

• The technology exists to unlock insights hidden within patient data, IF we look at how we use healthcare intelligence differently. See how Enlitic is using AI to solve the decades old data challenges that are keeping healthcare providers from transforming how we deliver healthcare.