Attorney Scott Bailey in defense of his radiologist client, who detected the torn artery that he was asked to identify, but was found partially liable for a delayed stroke diagnosis.

Imaging Wire Sponsors

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I’m very happy to share the latest Imaging Wire Show featuring Us2.ai’s co-founders, James Hare and Carolyn Lam MBBS, PhD.

Join us for a great discussion about Us2.ai’s continued clinical and commercial expansion, and their efforts to improve echo echocardiography accuracy, efficiency, and accessibility.

Cardiac Imaging

CCTA AI Predicts Ischemia and MBF

A Cedars-Sinai and Amsterdam UMC-led team developed a machine learning system that analyzes quantitative plaque in coronary CTA exams to identify patients with ischemia and impaired myocardial blood flow (MBF), potentially creating an alternative to current methods.

The researchers trained the ML model using invasive FFR data from 254 patients (484 FFR vessels) to predict ischemia and impaired MBF by analyzing plaque data in CCTA exams. 

They then tested it with CCTAs from 208 patients (581 vessels) who also underwent invasive FFR and H2O PET exams, finding that the CCTA ML scores:

• Predicted FFR-defined ischemia far more accurately than standard CCTA stenosis evaluations, while rivaling FFRCT assessments (AUCs: 0.92 vs. 0.84 & 0.93)
• Predicted PET-based impaired MBF more accurately than standard CCTA stenosis evaluations and FFRCT assessments (AUCs: 0.80 vs. 0.74 & 0.77)

Because the ML scoring system operates locally, the authors highlighted its potential to quickly assess high-risk patients before invasive coronary angiography (avoiding off-site processing delays) or to assess low-risk patients at earlier stages, helping to improve ICA efficiency and accuracy.

The researchers plan to continue to develop their CCTA plaque AI solution, including adding more plaque features and CCTA metrics, and potentially seeking regulatory approval depending on the results of future validation studies.

The Takeaway

CCTA plaque AI is already one of the hottest segments on the commercial side of imaging AI, and this study highlights similar advances in academic centers, while showing that CCTA plaque AI can quickly and accurately predict both ischemia and lower MBF.

United Imaging Innovation

Check out this Imaging Wire Show with United Imaging’s Jeffrey Bundy and Mike Coulter, who detail their unique approach to medical imaging innovations. If you’re trying to figure out a simpler and more scalable way to run your imaging organization, this interview is a great way to start.

Us2.ai’s Echo Evidence

Have more echo studies than sonographers? See how Us2.ai was able to classify, segment, and annotate echocardiographic videos with similar accuracy as expert sonographers.

The Wire

• GE & Accuray’s Precision RT Alliance: GE Healthcare and Accuray launched a global commercial partnership, combining GE’s advanced imaging tools with Accuray’s radiation therapy products. The companies will initially focus on precision lung and brain cancer treatments, while also looking to support digitalization and interoperability within their shared clients. GE appears to be actively expanding its radiation therapy alliances, as it also launched partnerships with RaySearch and Elekta earlier this year.

• Misreporting LLNs: A Netherlands-based study revealed widespread underreporting of lateral lymph nodes (LLNs) in rectal cancer patients’ primary MRI reports, calling for increased LLN awareness and training. The researchers had abdominal radiologists re-review 1k MRIs after undergoing a 2-hour LNN training session, revealing that the primary MRI reports didn’t mention 49.4% of LNNs and 41% of enlarged LLNs, while finding considerable discrepancies for LLN locations and sizes (73% & 42%). 

• Vara Adds €4.5M: Mammography AI company Vara added €4.5M to its Series A round (total funding now €15.2M) to help fund a 400k-woman clinical trial. Vara’s mammography AI solution filters out normal screening exams, allowing radiologists to focus on more complex / urgent cases, eliminate double reading, or support global regions without sufficient screening.

• Automating AAA Screening: A new JACR study detailed an automated EMR-based ordering program that increased ultrasound screenings for abdominal aortic aneurysms (AAA). The researchers compared a health system’s AAA screenings before and after adopting the automated ordering system (4,176 total patients, 148 w/ aneurysms), finding that the system dramatically increased its monthly screening volume (105 vs. 16.3) and reduced AAA incidence (3.2% vs. 5.3%).

• Physician Recruitment Challenges: A report from the Association for Advancing Physician and Provider Recruitment highlighted how physicians are becoming harder to replace, as burnout pushes many to exit the industry. The AAPPR analyzed 23k physician hiring searches from last year, finding that 48% of searches were intended to replace departing doctors (up from 32% in 2018), with 33% of physicians citing burnout as their reason for leaving. To compensate for this physician shortage, healthcare organizations are increasingly relying on physician assistants and nurse practitioners, who are more widely available and easier to credential.

• Radtech Grads in Demand: In other provider staffing news, an AMN Healthcare survey put a spotlight on the radiologic technologist shortage, which is exacerbated by rising imaging volumes. Among 1k respondents, 82% said they hired newly graduated “allied health professionals” over the past year, and of those new grads, radiologic techs were the most frequently hired (38%), followed by physical therapists (36%), lab technicians (31%), occupational therapists (30%), and speech pathologists (26%).

• Qure.ai qCT Matches Lung-RADS: A recent Chest Journal study showed that Qure.ai’s qCT algorithm predicts lung cancer with similar accuracy as radiologist-produced Lung-RADS assessments. The researchers analyzed 210 patients’ low-dose chest CTs (w/ 94 malignant nodules), finding that qCT assigned nearly three-times higher malignancy scores to the malignant nodules than the benign nodules (15.1 vs. 5.2). qCT detected malignant lung nodules with similar performance as Lung-RADS (AUCs: 0.73 vs. 0.74), while achieving higher sensitivity (77% vs. 64%) and similar specificity (64% vs. 65%).

• Mammography Tech Disparities: Black women traditionally have less access to modern mammography technology than White women, even when they are scanned at the same institutions. Researchers analyzed 4M Medicare claims from 2005-2020, finding that Black women were less likely to receive digital mammography exams when that technology first emerged (OR: 0.80) and were later less likely to be screened with digital breast tomosynthesis tech (OR: 0.84). 

• Cerebriu’s MRI AI Stroke Detection Support: Danish AI company Cerebriu secured $1.7M in funding to support its development of an MRI-based stroke diagnostics solution. Cerebriu and its Danish academic and health system collaborators will co-develop a solution that analyzes MRI images while acute stroke patients are still in the scanner, supporting real-time decisions, while improving workflow and access to care. 

• Hospital Occupancy Drives ED Waits: New research in JAMA Network Open showed that higher hospital occupancy was associated with longer ED wait times during the pandemic. Analysis of 2020-2021 EHR data showed that ED wait times lasted more than four hours in 90% of cases when hospital occupancy was greater than 85%, and median wait times were longer than nine hours at the 5% of hospitals with the highest occupancy.

• Delayed Diagnosis Verdict: An ER doctor and radiologist will split a $75M malpractice verdict (60% / 40%), after a delayed stroke diagnosis led to a 32-year-old patient’s paralysis. Following a botched chiropractic adjustment, the patient was brought to North Fulton Regional Hospital and quickly imaged. The radiologist allegedly missed signs of a brain stem stroke (he was tasked with identifying a torn artery) and the ER doctor allegedly omitted key info to the neurologist (didn’t mention chiropractic involvement, miscommunicated imaging results), thus delaying the patient’s diagnosis and treatment until the next day.

AI’s Healthcare System Value

AI delivers value to a wide range of healthcare stakeholders, but its primary value to health systems originate from its ability to automate tasks, democratize care, and deliver hard and soft ROI. See how these factors impact health systems’ bottom line in this latest Arterys report.

Democratizing Enterprise Imaging

Enterprise imaging is mainly adopted in the largest hospitals, but that doesn’t have to be the case. Check out this Imaging Wire Show featuring Novarad product leader Dave GrandPre, where we discuss what’s caused this divide and why smaller hospitals should adopt enterprise imaging.

The Resource Wire

• Did you know one quarter of healthcare organizations have experienced a cyber-attack in the last year? This Change Healthcare animation explains how 3rd-party certified cloud-native enterprise imaging can help secure IT infrastructure that might be exposed with re-platformed imaging systems.

• Think your patients are ready for you to ditch the disk? Join ACR past president, Dr. Geraldine McGinty, and Intelerad president, Morris Panner, for this Imaging Wire Show discussion exploring the state of image sharing, its impact on patient care, and how radiology can finally ditch the disk.

• There’s a lot to learn from St. Michael’s Hospital’s experience implementing the Hyperfine Swoop portable MRI at the point-of-care. See what their hospital leaders had to say about how the ultra-low-field MRI technology impacted their patients and clinicians in this on-demand webinar.

• Take the AiCE challenge and see why half the radiologists in a recent study “had difficulty differentiating” images from Canon Medical Systems’ Vantage Orian 1.5T MR using its AiCE reconstruction technology compared to standard 3T MRI images.

• Contrary to popular belief, imaging’s interoperability problem might actually be a data governance problem. The good news is, Enlitic is a solution to this problem, allowing you to get the most out of our modalities, PACS, and AI without needing your other vendors to intervene.

• Curious how certain your AI is about its own finding? annalise.ai’s confidence bar displays the likelihood of each finding and the AI model’s level of certainty, helping clinicians perform their interpretations with greater confidence.

• 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%.

• Bayer’s cloud-based Calantic Digital Solutions AI platform features a suite of disease-specific AI apps that integrate into radiologist workflows, helping radiology teams scale AI deployment and improve efficiency and quality of care.

• 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.

• Siemens Healthineers’ AI-powered MR image reconstruction technology, Deep Resolve, allows faster scans without compromising imaging resolution. Check out how Deep Resolve improves workflow efficiency and the patient experience, and view their portfolio of reconstructed scans here.

• When Sao Paolo’s Diagnosticos da America SA (DASA, the world’s 4th largest diagnostics company) set out to evaluate Qure.ai’s QXR solution for their pediatric chest X-ray workflows, they leveraged CARPL.ai’s platform to streamline their evaluation. 

• Digitization and AI are an era-defining reality for radiology, and GE Healthcare is rising to the challenge by creating tools to build a world that works better for healthcare. Check out this report detailing GE’s digitization and AI innovations and its vision for precision healthcare.