“This is really a tectonic shift in healthcare.“
Zebra Medical Vision CEO, Zohar Elhanani, on imaging AI’s healthcare impact and how it could revolutionize public health.
Imaging Wire Sponsors
- Arterys – Reinventing imaging so you can practice better and faster.
- Bayer Radiology – Providing a portfolio of radiology products, solutions, and services that enable radiologists to get the clear answers they need.
- Canon Medical Systems – Delivering innovative imaging solutions and services through industry leading partnerships to improve the quality of life for all people.
- GE Healthcare – Enabling clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications and services.
- Healthcare Administrative Partners – Empowering radiology groups through expert revenue cycle management, clinical analytics, practice support, and specialized coding.
- Hitachi Healthcare Americas – Delivering best in class medical imaging technologies and value-based reporting.
- Novarad – Transformational imaging technologies that empower hospitals and clinicians to deliver clinical, operational and fiscal excellence.
- Nuance – AI and cloud-powered technology solutions to help radiologists stay focused, move quickly, and work smarter.
- Riverain Technologies – Offering artificial intelligence tools dedicated to the early, efficient detection of lung disease.
- Siemens Healthineers – Shaping the digital transformation of imaging to improve patient care.
- United Imaging – Our mission, Equal Healthcare for All, pushes us beyond conventional boundaries to help clinicians expand modern, digital, intelligent care to more people within their communities.
- Zebra Medical Vision – Transforming patient care with the power of AI.
The Imaging Wire
Nuance, a Microsoft Company
The healthcare tech industry got a lot bigger this week with Microsoft’s $16B acquisition of Nuance Communications. Here’s some details and perspectives:
- The Acquisition – Microsoft will pay $56 a share for Nuance, equaling $16B (a 23% stock premium, ~14x revenue), with a total cost of $19.7B including Nuance’s liabilities. Nuance becomes Microsoft’s biggest acquisition since LinkedIn ($26.2B in 2015) but the Seattle tech giant can also afford it, given that it ended 2020 $132B in the bank. Nuance CEO, Mark Benjamin, will continue to lead the organization, which will operate as part of Microsoft’s Intelligent Cloud business.
- Microsoft’s Healthcare Intentions – Nuance’s speech recognition technology is used across a number of industries, but Microsoft made it quite clear that this is a healthcare acquisition. That might not be a major surprise to some, noting that Microsoft’s last 18 months brought big-name healthcare hires (including GE’s imaging CEO Tom McGuiness), a major healthcare cloud launch, and new healthcare partnerships (including one with Nuance).
- Nuance’s Healthcare Contributions – With the addition of Nuance, Microsoft doubles its addressable healthcare market, while giving it a suite of AI-based products that are used by the majority of U.S. hospitals, physicians, and radiologists (77%, 55%, 75%). Microsoft also has a history of scaling acquired technologies to its other industries and regions, and some coverage suggests that Microsoft will do the same with Nuance’s speech solutions (e.g. grow Nuance in Europe).
- The Next Tech Battleground – The business media pointed to this acquisition as a sign that healthcare is the next tech battleground, noting medicine’s need to embrace data and software, and the increased healthcare focus from tech giants like Amazon and Google.
- The Takeaway – Nuance just became the tip of the spear for Microsoft’s healthcare expansion. Short term, that likely means a better-funded and better-connected version of the Nuance we already know, and mid-to-longer term that likely means a much bigger healthcare role for Microsoft (and potentially Nuance).
Imaging Wire Q&A: Zebra-Med Thinks Big
In the latest Imaging Wire Q&A we sat down with Zebra Medical Vision CEO, Zohar Elhanani, to discuss imaging’s AI evolution and how AI’s role in public health could be much bigger than many of us imagine. Here are some of the takeaways:
- AI Evolution – AI is already becoming a driving force in medical imaging, particularly in the areas of triage and diagnostic support, although imaging AI ROI is still unclear for many healthcare providers.
- Going Public – During Zebra’s own AI evolution, Elhanani and his colleagues identified a major opportunity to bring AI into public health. As a result, Zebra is now expanding its suite of public health solutions, with a focus on detecting chronic conditions and managing the pathway to care.
- Public Health Evolution – AI’s ability to detect early stage illnesses fits well with healthcare’s value-based shift and the main goals of public health programs. There’s still plenty of work to be done to bring AI into public health’s diagnostic and care pathways, and Zebra-Med is working with its public health clients to create these pathways.
Read more about Zebra-Med’s vision for public health AI in the new Q&A.
- TG-CXR Benefits: A new study out of Toronto’s St. Michael’s Hospital detailed how its emergency department benefited from adopting the “portable chest radiography through glass” imaging technique (TG-CXR) when scanning suspected COVID-19 patients. TG-CXR allowed the hospital to perform COVID CXRs with just one technologist (vs. 2), while saving it $51k/yr (RT labor, PPE use, machine sanitization), reducing its machine downtime (-4:48 per study), and halving its technologist exposure.
- ABR’s Pivot: “Y’all Heard of Worldcom?” That’s the opening line from a famous scene in HBO’s excellent series, “The Wire,” where Baltimore drug kingpin Stringer Bell explains why his organization should rename an unpopular batch of heroin. Bell of course didn’t invent this tactic (we’ve seen it from Worldcom > MCI, Phillip Morris > Altria, and others), and we’re now seeing it from the ABR, which is renaming its often-criticized Maintenance of Certification program as the “Continuing Certification” program. The ABR is also considering reducing its user fees (coincidentally, Stringer Bell’s other option) and seems to be backtracking on an unpopular family leave proposal. The ABR’s latest efforts might not change the minds of its strongest critics (at least not right away), but it does show that they’re listening and trying to get better.
- COVID Capacity AI: Altis Labs, Bayer, and Canada’s Digital Technology Supercluster are teaming up with Toronto-area hospitals to use imaging AI to support ICU capacity decision making during the COVID emergency. Combining Altis’ AI tools with funding from Bayer and the Supercluster, the project will initially analyze CXRs and CTs to predict COVID patients’ risk of ICU admission and their discharge timelines. If successful, the project will expand across Canada.
- United Imaging in Growth Mode: United Imaging took another step in its growth strategy this week, announcing a trio of channel partnerships and opening a number of new account executive roles to drive its direct growth. United Imaging’s expansion into the partner channel includes alliances with Radon Medical Imaging (mid-Atlantic region, CT/MRI/MI products), Imaging Solutions (mid & northern U.S., CT/DR/MRI/MI products), and Medimax (Puerto Rico, CT/DR/MRI/MI products).
- Duplex Ultrasound for Revascularization: Duplex ultrasound (DUS) could be a good alternative to CTA for endovascular revascularization planning, especially among patients who might be sensitive to contrast. That’s from an Italian study that performed DUS and CTA on 94 patients with peripheral arterial disease prior to endovascular revascularization treatment. DUS and CTA comparably assessed the patients’ femoro-popliteal district, while DUS outperformed CTA when assessing the infra-geniculate area, and CTA more accurately defined the patients’ iliac arterial district compared to DUS.
- Koios’ Breakthrough Designation: Koios Medical’s Koios DS decision support software platform just received FDA Breakthrough Device designation for breast and thyroid ultrasound image interpretation, fast-tracking the solution’s Medicare coverage. Koios Medical earned its new FDA designation by showing that Koios DS improves patient care by increasing cancer detection and reducing unnecessary biopsies.
- DEXA Cardiac Assessments: New research in the Bone journal details a machine learning algorithm that’s able to predict heart disease using dual-energy x-ray absorptiometry (DEXA) vertebral fracture assessment images (VFA), suggesting that DEXA scans could be repurposed for population health screening. Using 1,100 DXA VFA images originally intended for osteoporosis assessments, the researchers developed and tested a pair of CNNs (770 training, 110 validation, 220 testing) that were able to identify patients’ abdominal aortic calcification scores (AAC, a cardiac disease marker) with 88% accuracy and high correlations with human-assigned scores.
- Siemens’ Ultrasound Options: Bloomberg reports that Siemens Healthineers is considering selling its ultrasound unit for roughly $1B to either private equity or “strategic bidders.” Siemens hasn’t confirmed these reports and at first glance divesting from the ultrasound segment doesn’t seem to fit with the company’s imaging leadership goals. That said, Bloomberg is generally accurate when it reports about M&A “considerations” and Siemens’ limited ultrasound portfolio (solid at the high-end, but not as broad or current as some competitors) would make the ultrasound business unit a more likely spin-off candidate than its other modalities.
- The ACR’s National Registry: The ACR just launched the ACR National Clinical Imaging Research Registry (ANCIRR), calling it “the future of radiology research registries” and a platform that will “democratize” radiology research. The ANCIRR will feature eight different registries (6 are already live) that collect and curate images / data from a variety of practice settings to produce large and diverse datasets for research use.
- FDA’s AI Inadequacies: A new Stanford study found that many FDA-approved AI devices were not “adequately” evaluated, calling for more formal FDA review standards. Their review of 130 medical AI devices, found that nearly all only underwent retrospective studies (126/130), none of the 54 high-risk AI products were evaluated using prospective studies, most didn’t use data from multiple sites (93/130), many had small study sizes (median = 300), and very few accounted for performance with different patient groups (17/130).
- Ultrasound Game Changer: A team of Belgian and German scientists developed a new optomechanical silicon photonics-based ultrasound (OMUS) detector that’s 100-times more sensitive than current piezoelectric-based tech and could expand how ultrasound is used. The OMUS detector overcomes piezoelectric detectors’ key limitations (OMUS’ sensitivity isn’t size-dependent, its operational wavelengths aren’t restricted, each sensor doesn’t require a dedicated electric wire), potentially making it a “game changer” for deep tissue imaging (mammography, tumor detection, and even brain imaging) and making disposable sensors a possibility (catheter and endoscope applications).
- Arterys & AMG Medtech’s British Isles Alliance: Arterys and UK-based healthcare AI consultancy, AMG Medtech, announced that AMG Medtech will sell and market Arterys’ AI solutions in the UK and Ireland. AMG Medtech primarily focused on radiotherapy AI solutions before now.
- AI Liability Risks: A Boston-based radiologist and lawyer duo shared a solid overview of MSK radiologists’ legal liability as AI takes on a larger role in their workflows. The editorial details a range of liability scenarios that are worth a review, although the main takeaways are that the lack of AI malpractice precedence means “all parties face an uncertain liability landscape,” while federal law and the tort system will serve as radiologists’ “unlikely allies” because they both “emphasize the primacy of physician decision-making.”
The Resource Wire
– This is sponsored content.
- This AI economics overview from Healthcare Administrative Partners details the various AI ROI scenarios and ways that AI can contribute to radiology practices until reimbursements become more of a reality.
- Check out how Baptist Health South Florida increased its radiology team’s output by more than 25% using Nuance PowerScribe Workflow Orchestration and PowerConnect Communicator.
- See how East Texas Medical Center reduced its abdominal CT contrast volumes by 30% after adopting Bayer Radiology’s contrast dose management software.
- This new ebook looks at how you can empower your CT technologist team and set up your department for success by looking at four key areas.
- GE Healthcare is recognizing technologists who went above and beyond during the COVID-19 pandemic with its 2021 X-Ray Technologist Awards. If any of your technologist colleagues stepped-up last year, nominate them today.
- 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 phrase “Prevention is better than cure” was made famous 520 years ago, and it’s a core part of Zebra Med’s strategy today. Learn how and why Zebra-Med is shifting its emphasis to population health as we head into 2021.
- Learn how Aavicenna.AI’s LVO detection and triage algorithm (available via Arterys) improves large vessel occlusion treatment decisions and clinical outcomes.
- Watch Jared Christensen, MD, MBA explain how Duke University Health uses Riverain Technology’s ClearRead CT Vessel Suppress and ClearRead CT Detect in its daily practice.
- Learn how Novarad’s Nova RIS system helps radiology departments streamline front office workflows, ensuring they get all the reimbursements they’ve earned while also providing a great patient experience.
- In this Hitachi blog, VidiStar users share how they’ve benefitted from the cardiovascular information system’s flexible SaaS-based pricing model and leveraged its productivity advantages to increase reimbursements.
- United Imaging’s approach to brain imaging in molecular imaging puts the patient first, with a focus on reducing scan times and correcting for patient motion to avoid repeat studies, while supporting interpretation with high resolution images and quantitative values.