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Uneven Access to Brain MRI, Lung Cancer in WTC Responders, and Shutdown’s Impact
October 13, 2025
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Together with
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“[C]ompared to conversational AI in documentation, radiology AI adoption may look slower. But it will come, not through individual radiologists ‘hacking’ it into their workflow, but as the discipline collectively recognizes its value and makes it standard.”
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Amine Korchi, MD, comparing adoption of radiology AI to clinical generative AI.
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Radiology faces a crisis caused by personnel shortages and radiologist burnout, and the field’s legacy IT solutions aren’t helping. What if you built a cloud-based platform that unifies image viewing, reporting, and worklist? In this edition of the Imaging Wire Show, we talked to Kate Kovalenko of Sirona Medical about their clinical-grade solutions.
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Patients from disadvantaged neighborhoods or those traveling farther for brain MRI scans presented in worse clinical condition than patients with better access. That’s according to a new JACR study that reopens the debate over disparities in healthcare access.
The past several years have seen numerous studies published that document disparities in healthcare access and their impact on clinical outcomes.
Many previous studies have also concentrated on access to care in rural areas, in which long distances make it harder for patients to travel to medical centers.
- In the current study, researchers led by authors from Emory University flipped the script to examine care access in the Atlanta metropolitan area in an effort to quantify how distance and socioeconomic status might impact patient care.
They examined the demographic backgrounds of 4.8k patients who got brain MRI scans over a one-year period starting in March 2019, calculating factors like distance from home to imaging facility and socioeconomic status based on the area deprivation index.
- They then correlated these data to patient illness severity – also known as acuity – when they presented for their scans, using a three-point scale ranging from normal (level 1) to findings requiring a change in patient management (level 3).
Based on the data, researchers found…
- Patients in neighborhoods with lower socioeconomic status had 34% higher odds of level 2 acuity versus level 1 for inpatient scans and 27% higher for emergency scans.
- Patients living twice the distance from an imaging facility had 6.5% higher odds of level 2 acuity compared to level 1, and 15% higher for level 3.
- Other factors affecting acuity level included age, race, and insurance status.
- Medicaid recipients in particular were sicker, with 68% higher odds of acuity level 2 and 81% higher odds of acuity level 3 compared to those with commercial insurance.
The findings track with other studies that have linked chronic health conditions with brain pathologies, such as the connection between diabetes and stroke.
The Takeaway
The new findings offer additional details on how patient demographics affect both their health status and their access to care, in particular for advanced imaging scans like brain MRI. Follow-up studies could examine whether a similar phenomenon occurs with CT, which is the workhorse modality for emergency imaging.
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The Transformative Role of AI in Radiology
In this episode of The Radiology Report Podcast, Medality’s Daniel Arnold sits down with Dr. John Simon, who shares his insights into the transformative role of AI in radiology and its ability to enhance efficiency, improve patient care, and unlock new diagnostic possibilities.
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Radiology Case Report
A man in his 40s presented with a known metastasis within his abdomen. Learn how contrast-enhanced MRI helped to diagnose the extent of his disease.
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- Lung Cancer in World Trade Center Responders: First responders to the September 11 terrorist attacks on the World Trade Center have had higher long-term lung cancer rates. In a study in JAMA Network Open, researchers tracked 12.3k first responders for over 20 years, finding that lung cancer incidence was higher in people with severe exposure to toxic substances at the WTC site (21 cases per 10k person-years) compared to those with moderate (12.7) or mild exposure (4.2). Fortunately, WTC responders are eligible for CT lung screening.
- Shutdown’s Impact on Radiology: What impact is the U.S. government shutdown having on radiology? The folks from Healthcare Administrative Partners published a “need to know” guide last week, showing the biggest impact being a 10-day hold on Medicare payments as CMS limps along with staffing at 53% of normal. Another change is the expiration of geographic adjustment factors that could lead to drops in Medicare reimbursement by 1% to 2.7% starting October 1, with higher reductions in rural states.
- AI Reconstruction of CTPA: Image reconstruction using AI and deep learning is a good way to reduce CT radiation dose, and researchers in Academic Radiology achieved 74% dose reduction for CT pulmonary angiography with Canon Medical’s AiCE deep learning-based technique. In testing with 144 patients, AiCE-reconstructed CTPA scans had sharply lower mean effective dose compared to routine dose (0.71 vs. 2.78 mSv), and radiologists rated AiCE’s image quality for detecting pulmonary embolism as higher than reconstruction with either routine dose or hybrid iterative reconstruction techniques.
- ASTRO Disputes NBC Story on Breast Cancer: ASTRO issued a statement about an NBC News story on intraoperative radiation therapy for breast cancer claiming that women have been “shut out” of IORT because ASTRO does not recommend it. The story went on to claim that radiation oncologists prefer traditional radiation therapy because it generates more revenue than IORT. ASTRO said the NBC story “presented inaccurate and misleading information” and published an overview of clinical research backing its position.
- Gleamer Expands BoneView Installation: Gleamer expanded its BoneView AI solution at St. Luke’s University Health Network in Pennsylvania. St. Luke’s began using BoneView to analyze X-rays for fractures at some of its hospital emergency departments in late 2024, and has now expanded it to all EDs as well as urgent care centers. Clinical studies have shown BoneView can reduce missed fractures by up to 30%, and the solution is being applied to more than 1k images per day in St. Luke’s network.
- More Efficient Cardiac MRI: Cardiac MRI is a powerful tool for diagnosing heart disease, but it’s complex and time-consuming. Researchers from Texas in JACC: Case Reports customized CMR scanning protocols to patient pathology and implemented remote scanning with Philips’ Radiology Operations Command Center, finding that for 343 patients the program cut scan duration 35% (61 vs. 95 minutes). This led to a 32% increase in scan volume at the main campus, a 200% increase at a satellite campus, and establishment of a CMR service at a third campus.
- Harrison.ai Touts Breakthrough Designations: Harrison.ai has notched three FDA Breakthrough Designations for its radiology AI software for CT applications. One of the designations, Harrison.ai Comprehensive Care – Obstructive Hydrocephalus, has received FDA clearance and is eligible for Medicare NTAP reimbursement, while two more are under development. One algorithm is for auto-creation of radiology report drafts and is being researched at sites in the U.S. and Australia, while the third is a foundation model for building reporting and other AI applications.
- MRI Guides Breast Cancer Treatment: MRI can help guide surgical treatment of women diagnosed with breast cancer, but patient access is uneven. In a study in JACR, researchers tracked 1.8k women, finding that preoperative breast MRI detected additional lesions in 52% of cases. Those getting breast MRI had higher mastectomy rates (49% vs. 31%) but lower re-excision rates (8% vs. 14%). Breast MRI rates were lower for patients who were older, Black, on Medicare or Medicaid, or who didn’t have full-time employment.
- Texas Hospital to Install 7T MRI: Siemens Healthineers will install a 7T Magnetom Terra.X scanner at UT Health San Antonio’s Center for Brain Health in December. UT clinicians will use the scanner for both research and clinical applications, in particular for neuroimaging, where the system’s sharply higher resolution compared to 1.5T and 3T scanners will help visualize brain structures and distinguish between a benign blood vessel and an aneurysm, for example.
- Fonar Mulls Going Private: MRI pioneer Fonar could go private under a management-led buyout of the company’s publicly traded stock. Fonar was founded by Raymond Damadian, MD – generally credited as one of MRI’s inventors – and while it still manufactures its own scanners most of the company’s $104M in annual revenue now comes from its Health Management Corporation of America diagnostic imaging center business. Fonar management announced in July it may go private through the management buyout.
- Lung Ultrasound vs. Chest X-Ray for Pneumonia: Lung ultrasound proved superior to chest X-ray for diagnosing pneumonia in critically ill ICU patients. In a new paper in The Lancet’s eClinical Medicine, researchers from Italy performed a literature review covering nine studies with 746 patients. Lung ultrasound had higher sensitivity (93% vs. 65%) with comparable specificity (83% vs. 81%) and higher accuracy (AUC = 0.88 vs. 0.76). Lung ultrasound bedside availability is another advantage, although operator variability should be monitored.
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Innovation in Remote Radiology Scanning
Reserve your seat at this October 13 webinar hosted by Philips to learn how remote radiology scanning is transforming care delivery at Outpatient Imaging Associates, improving efficiency and supporting better patient outcomes.
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Cost Savings from AI for Fracture Detection
Using AI to analyze X-rays for wrist, ankle, and hip fractures in the emergency setting can save costs while improving patient care. Read how the NHS did it with Gleamer’s BoneView solution.
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- Unifying All Your Diagnostic Images: The Mach7 eUnity enterprise diagnostic viewer can unify all your images and solve your integration needs under one universal viewing platform. Find out how you can upgrade your enterprise visualization strategy today.
- What’s Next for AI for Cancer Detection? AI is transforming the fight against cancer by enabling faster and more accurate cancer detection. Read this article from DeepHealth to learn how the company is pioneering new ways to advance cancer screening and broader imaging-based care.
- Bring Your Radiology AI into Your Clinical Workflows: CARPL enables healthcare providers and researchers to develop, test, and deploy their own AI models within existing clinical infrastructure. From seamless data ingestion and de-identification to model training, packaging, and live deployment, CARPL provides an end-to-end environment tailored for radiology.
- Echo AI for Cardiac Amyloidosis Diagnosis: AI is reshaping how cardiac amyloidosis is detected. Us2.ai’s pattern recognition model can identify the disease from a single apical four‑chamber echo view – learn how it works on this page.
- How to Standardize CT Images: The quality and appearance of CT scans can vary considerably. In this white paper from Riverain Technologies, find out how image normalization can standardize CT images, making them easier to analyze and interpret.
- Radiology Case Report: A female in her 40s presented with right upper quadrant pain. Learn how contrast-enhanced MRI helped to provide a diagnosis.
- The Future of Fluoroscopy Is Here: The future of fluoroscopy has arrived. The LUMINOS Q.namix fluoroscopy systems from Siemens Healthineers are available on the U.S. market. Discover why they have already earned the prestigious Red Dot Design Award for intuitive design and user-centric innovation.
- How AI Is Redefining Data Migration: Enlitic’s Migratek data migration services – combined with AI-enabled ENDEX data standardization – is changing the game for data migration projects. Discover how it can benefit you in this article.
- What Healthcare Really Needs from AI: The AI hype cycle has flooded healthcare with promises, yet many tools fail to deliver real-world impact. Reserve your seat at this October 29 webinar hosted by Rad AI to hear healthcare leaders share their real-world experiences in making AI work.
- Trailblazing Radiology’s Path to the Cloud: Visage Imaging is trailblazing radiology’s path to the cloud, based on industry standards and multi-cloud support. Visit them at RSNA 2025 booth #4329 or book a priority demo today.
- Solving Burnout through Teleradiology: Is your radiology staff facing burnout? Check out this case study to find out how Northern Light Medical Management addressed burnout with teleradiology solutions from Merge.
- Optimize Radiology Workflows: Harness cloud and AI technology to help your radiology teams unlock insights, increase efficiencies, and improve patient care. Learn more about an integrated approach to AI in radiology in this e-book from Microsoft.
- Denoising AI’s True Potential for Medical Imaging: What is AI’s true potential in medical imaging? Find out in this American Hospital Association podcast with United Imaging CEO Jeffrey Bundy, PhD, and United Imaging Intelligence CEO Terrence Chen, PhD.
- Purchasing a Cloud-Hosted Enterprise Imaging Solution: The decision to move your enterprise imaging to the cloud is significant. But how do you choose the right solution? Discover the 10 critical questions to ask in this guide from AGFA HealthCare.
- Streamlining Sonographer Workflows: Alaska Radiology Associates needed to streamline sonographer workflows, so they turned to SonoReview by Kailo Medical. Learn how the solution enhanced accuracy and saved valuable time for both radiologists and sonographers.
- Transform Imaging Data into Actionable Predictions: When you choose Quibim, you get more than a partner for detecting and diagnosing prostate cancer on MRI scans. Learn how they can help you transform imaging data into actionable predictions by booking a demo today.
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