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Intermountain Centers | AI Database | Zebra’s CAC FDA

“It’s wrecked my life.”

VA technologist Jeff Dettbarn, after he reported the Iowa City VA’s cancelled scans and didn’t receive the whistleblower protections he expected.



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Arterys | Bayer Radiology | Blackford Analysis
Canon Medical Systems | Fujifilm Healthcare Americas
GE Healthcare | Novarad | Nuance
Riverain Technologies | Siemens Healthineers
United Imaging | Zebra Medical Vision



The Imaging Wire


Intermountain’s Imaging Centers

Intermountain Healthcare expanded into outpatient imaging with the launch of its new imaging center subsidiary, Tellica Imaging. Plenty of hospital systems have outpatient imaging centers, but how and why Intermountain created Tellica brings some important takeaways.

About Tellica – Tellica Imaging plans to open a fleet of outpatient MRI and CT centers, starting with three Utah locations by late 2021, five locations in 2022, and more locations in “subsequent years.” The Tellica centers will prioritize patient convenience and value, targeting easy-to-access locations and adopting a novel flat-rate pricing model that’s well below typical in-hospital rates.

The Value-Based Angle – Given Intermountain’s role as one of the country’s flagship value-based care systems and its unique payor-provider structure, launching a series of imaging centers that are lower cost and more convenient makes a lot of sense. It’s also a step away from the hospital-based/owned procedure trend that’s helped hospitals from a reimbursement perspective, but brought a long list of unintended consequences (higher patient/payor costs, provider consolidation, imaging overuse, etc.).

The Payor Angle – Even though many patients use Intermountain’s in-house insurer (SelectHealth), Intermountain also works with a long list of commercial and government payors, nearly all of which have been incentivizing (or forcing) health systems to move more imaging procedures to outpatient centers. SelectHealth likely has the same preferences.

The Offsite Trend – In addition to the above payor pressures, there are some major trends underway that favor offsite imaging, including the rapid adoption of at-home/remote patient care, new COVID-related offsite policies, and the federal government’s efforts to make healthcare procedures more “shoppable.”

The Takeaway – Hospital-owned outpatient imaging centers aren’t all that unique, but Intermountain’s structure definitely is (payor-provider, value-based, non-profit) and so is its decision to launch these centers with such a patient-friendly value proposition. Even if most hospitals aren’t yet ready to offer flat-rate scans, the factors that drove Intermountain to create Tellica are likely forcing plenty of other systems to rethink their own approach to offsite imaging.


Einstein & Bayer’s Injection System Upgrade

See how Einstein Healthcare Network reduced its syringe expenses, enhanced its syringe loading, and improved its contrast documentation when it upgraded to Bayer Radiology’s MEDRAD Stellant FLEX CT Injection System.

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Solving AI’s Adoption Challenges

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.

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The Wire

  • The FDA’s AI Database: The FDA just published a complete list of FDA-cleared AI/ML-enabled medical devices, including 343 products overall and 241 radiology devices (yes, 70% of approved AI devices are for radiology). The FDA plans to continuously update this list, as part of its AI Action Plan.
  • Masks and Dictation Errors: Wearing face masks might increase dictation errors in radiology reports. That’s the unsurprising conclusion from a new UNC study that had six radiologists dictate 40 reports with and without masks, revealing a 25% higher error rate while masked (21.7 vs. 27.1 per 1k words). The good news is most errors were minor (11.9 vs. 15.2 per 1k), although masks also increased major error rates (5.6 vs. 7.3 per 1k).
  • Zebra Medical’s CAC FDA: Zebra Medical Vision announced the FDA clearance of its Coronary Artery Calcium (CAC) solution, representing Zebra-Med’s 8th FDA-approval and its 2nd FDA-approved population health product (following Vertebral Compression Fractures). The new HealthCCSng solution (also CE marked) analyzes existing non-gated CT scans and quantifies CAC scores to allow providers to identify at-risk patients and recommend preventative care. This is a very different type of AI tool than we usually cover, but it’s one that could be valuable for payors, patients, and providers considering how many people have undetected heart disease.
  • GE Definium Tempo Unveiled: GE Healthcare announced its Definium Tempo fixed overhead tube suspension X-ray system, highlighted by a range of new technologist-friendly workflow and productivity features. The Definium Tempo’s RT-friendly features include a tube-mounted console (supports all exam setup and positioning at the system) and a suite of automated workflows intended to reduce exam times, errors, image variability, retakes, and physical strain.
  • End-to-End MRI AI: A Microsoft-led team developed an end-to-end deep learning framework that combines image reconstruction and pathology detection within a single cloud-based workflow (exams, pre-processing, DL reconstruction, DL lesion detection, image output), creating an automated process to evaluate DLIR models. The team trained and tested the framework to detect meniscus tears (typically a challenge with MRI DLIR) using knee MRIs captured at three acceleration rates, confirming that reconstructed MRI images still lack the fine image details needed for automatic DL-based pathology detection. However, this study is still a building block for future MRI DLIR research, and those future researchers can leverage the same fastMRI+ dataset used in this study.
  • Prestige’s PE: Prestige Medical Imaging (PMI) just took on a private equity investment from Atlantic Street Capital (ACS) that the major Eastern U.S. imaging dealer will use to fund its geographic and product portfolio expansions. PMI was already in growth mode, acquiring Southeast U.S. dealer G.E. Walker in February, while ACS has a history of scaling similar healthcare companies and plans to make “several” more medical imaging acquisitions going forward.
  • Bayer & Huma’s NSCLC Project: Bayer’s Oncology division and Huma are working together to develop a machine learning system that can distinguish different types of non-small-cell lung carcinomas (NSCLCs) in CT scans, allowing faster diagnosis and more personalized treatment. This is the latest step in the Bayer-Huma relationship, as Bayer contributed to Huma’s Series B (2019) and Series C (2021) rounds. It’s also the latest addition to the growing list of cancer treatment companies partnering with cancer detection companies to help catch more cancers while they’re treatable (and increase demand for cancer treatments).
  • CTC Evidence: CT colonography (CTC) could be the most effective non-invasive colorectal cancer (CRC) screening test, detecting more CRCs and avoiding more colonoscopies than multitarget stool DNA testing (mt-sDNA) and fecal immunochemical testing (FIT). An AJR study review (studies: 10 mt-sDNA, 27 CTC, and 88 FIT) found that when using a ≥10mm polyp size threshold, CTC had a 6.6% positive test rate (vs. 13.5% & 6.4%), a 6% CRC PPV (vs. 2.4% & 4.9%), a 4% advanced neoplasia detection rate (vs. 3.4% & 2%), and a 61% advanced neoplasia PPV (vs. 26.9% & 31.8%).
  • Leveljump’s Imaging Centers: Canadian teleradiology company Leveljump Healthcare now has a physical presence, acquiring three Ontario imaging centers for $4.3m. The new imaging centers will become part of Canadian Teleradiology Services (a Leveljump subsidiary), and although teleradiology remains Leveljump’s primary business, the company plans to continue to acquire imaging centers going forward.
  • Mutual Information AI: MIT researchers developed a new AI learning approach that analyzes both images and text in radiology reports and then leverages the image/text correlations within each report (aka mutual information) to train more accurate imaging AI models. The MIT mutual information model uses three CNNs (analysis of image portions, sentence-level text analysis, image/text mutual information analysis) to classify downstream images – potentially more accurately than AI models only trained with images.
  • VA Whistleblower Punished: The Iowa City VA radiology department is on the wrong side of the news this week, amid reports that a veteran technologist was unfairly punished after reporting (and eventually testifying to Congress) that diagnostic exams were being cancelled without physician approval. Earlier this year, the technologist was ordered back to the same unit that he reported, but with a lower salary and less patient care responsibilities. He’s currently in mediation with the VA, and he’s making his concerns about VA whistleblower protections public.

Fast. Flexible. Modern.

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The Resource Wire

  • Cardiovascular disease is the number one global cause of death, but it’s also preventable, which is one of the reasons why Zebra-Med views AI-powered cardiovascular screening as the next frontier in population health.
  • Rising CT volumes and related costs are creating new pressures on CT teams, but these trends can be corrected through greater communication, education, and awareness. See how in this new GE Healthcare report.
  • This Riverain Technologies case study details how Einstein Medical Center adopted ClearRead CT enterprise-wide (all 13 CT scanners) and how the solution allowed Einstein radiologists to identify small nodules faster and more reliably.
  • See how Fujifilm Healthcare VidiStar users have benefitted from the cardiovascular information system’s flexible SaaS-based model and leveraged its productivity advantages to increase reimbursements.
  • Here’s the first session in Nuance’s latest Fireside Chat series, featuring Healthcare Diagnostics leader, Karen Holzberger and new CMIO, Dr. Sheela Agarwal, and detailing how Nuance’s latest innovations are impacting the patient journey and outcomes.
  • Did you know 80% to 90% of sonographers experience pain while performing scans at some stage in their career? Check out this Canon Medical Systems video detailing its latest innovations that improve sonographer comfort and help reduce risk of injury.
  • Novarad’s COVID-19 AI Diagnostic Assistant was named the 2021 MedTech Breakthrough Awards’ ‘Best New Radiology Solution,’ for its ability to quickly and accurately diagnose COVID-19 patients.