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CT Supports Better Stroke Care, CT Dose, and COVID’s Cancer Impact
February 9, 2026
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Together with
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“The next phase of radiology informatics looks less defined by isolated departmental tools and more by consolidation, interoperability, and workflow systems that function as long term infrastructure. That is what this year’s Best in KLAS winners quietly reflect.”
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Jay Gurney of Projectus, on this year’s winners in the Best in KLAS awards.
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When it comes to stroke, time is brain. And the faster stroke patients can be diagnosed, the sooner brain-saving treatment can start. Researchers in Germany found that sending stroke patients to hospitals equipped with CT scanners and telemedicine connections might be more effective than transferring them directly to specialized stroke centers.
CT is critical for assessing stroke patients and determining whether they should receive intravenous thrombolysis with clot-busting drugs or endovascular thrombectomy with catheter-guided devices.
- It’s particularly important that patients be treated within the “golden hour” of stroke symptom onset, as every 10 minutes of delay results in eight weeks of healthy life lost.
Specialized stroke centers outfitted with dedicated equipment have sprung up to deliver better care, but they’re not that common and patient transfers can take extra time.
- Far more common are hospitals with CT scanners, giving rise to the suggestion of a hub-and-spoke model in which patients are sent first to a hospital equipped with CT and telemedicine for diagnosis and initial thrombolysis (the spoke), and then on to a specialized center (the hub) if necessary.
This approach is tested in a new study in The Lancet Regional Health – Europe, in which German researchers performed a modeling study to see how hub-and-spoke stroke treatment compared to direct transfer to specialized stroke centers.
- They developed a map of CT-equipped hospitals and dedicated stroke centers in Germany, and calculated minimum travel and time benefits in 10-minute thresholds.
The researchers found that of Germany’s population…
- 76% were within 15 minutes of at least one hospital with on-site CT, and 99% were within 30 minutes.
- 51% were within 15 minutes of a stroke-ready hospital (hospitals that treat a set number of stroke patients but aren’t yet certified), and 90% within 30 minutes.
- Only 46% lived within 15 minutes of a stroke-certified hospital, a figure that grew to 85% within 30 minutes.
- 36% would reach a CT-equipped hospital at least 10 minutes faster than a certified stroke unit.
Not surprisingly, there were geographic differences in accessibility, with urban areas having good access to specialized stroke centers but rural and underserved areas less so (90% vs. 55%).
- So the hub-and-spoke model might be better suited for rural areas while the direct transfer approach would still work for urban zones.
The Takeaway
While this study was conducted in Germany, its lessons could be applied to any country that has to juggle healthcare resources with clinical demands. The question is how much the findings might be impacted by new technologies like mobile stroke units and AI-based stroke assessment.
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Pioneering AI for Medical Imaging
With more than 40 clinical publications and real-world deployments, Gleamer combines scientific rigor and medical expertise to redefine AI for radiology. Learn more about the company’s pioneering suite of AI solutions on this page.
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Every Image Tells a Story
Intelerad’s enterprise image management solutions are empowering radiologists and patients while transforming radiology workflows. Learn about the technologies they highlighted at RSNA 2025 for empowering imaging professionals.
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- AI Boosts Stroke Therapy Rates: A U.K. study tested AI for guiding stroke therapy, finding that the Brainomix 360 Stroke algorithm boosted endovascular thrombectomy rates. In a study of 453k patients in The Lancet Digital Health, AI helped evaluate stroke patients from 2019 to 2023. Sites using AI saw their endovascular therapy use rate double (from 2.3% to 4.6%), while sites not using AI saw a slower 63% increase (from 1.6% to 2.6%). AI also reduced transfer times by 64 minutes.
- CT Radiation Dose Reduction: When it comes to CT radiation dose, 2025 was a rough year, with several (controversial) papers published on CT’s cancer-causing dangers. But a review in AJR of CT dose pointed out that radiation levels have been reduced 2X to 10X over the past 25 years through hardware and software advances, while image quality has improved dramatically. Photon-counting CT and deep-learning reconstruction are driving dose even lower, such that the dream of CT scans routinely performed at < 1 mSv is becoming a reality.
- COVID’s Cancer Impact: The COVID-19 pandemic depressed cancer screening rates as people postponed scheduled appointments, and a new study in JAMA Oncology finally shows the long-term impact. Of 1M U.S. patients diagnosed with cancer from 2020 to 2021, there were 17.3k more cancer-related deaths (13%) within one year of diagnosis than would have been expected, most likely due to later diagnosis. There was also a statistically significant decline in one-year cancer survival rates for late-stage diagnosis in both 2020 and 2021 (1.34 and 1.20 percentage points, respectively).
- Spatial Computing Aids Aortic Surgery: In one of the first published clinical case studies we’ve seen with Apple’s Vision Pro headset, researchers used the device in combination with Visage Imaging’s Visage Ease software to guide endovascular repair of a fistula with 3D images viewed in extended reality. In this case, 3D volume-rendered CT angiography images viewed in XR made it easier to visualize and assess an esophageal stent eroding into the thoracic aorta. This had created an emergent situation that required immediate intervention, also performed under XR guidance.
- GE Bolsters Ultrasound with Fetal AI: GE HealthCare is adding new fetal AI capabilities to its Voluson women’s health ultrasound scanners through new algorithms available on its Voluson Solution Store. First, GE added Diagnoly’s Fetoly for fetal heart and brain analysis, as well as verification of exam completeness and quality. GE also added BrightHeart’s B-Right AI Platform for detecting congenital anomalies to the store. GE is showcasing the integrations at this week’s SMFM 2026 Pregnancy Meeting in Las Vegas.
- Patients Prefer Head-Only 3T MRI: Compared to conventional whole-body MRI, patients gave high marks to a prototype compact 3T head-only scanner developed by Mayo Clinic and GE Technology and Innovation Center. The C3T scanner has a 37cm bore for head imaging, which enables much more powerful gradients (80 mT/m gradient amplitude and 700 T/m/s slew rate simultaneously), with 99% lower helium use. In tests with 50 subjects, patients rated it more highly in several categories like noise levels and vibration, indicating C3T could be ready for clinical use.
- FDA Clears Neonatal 3T MRI Scanner: A 3T MRI scanner dedicated to neonatal imaging received FDA clearance. Eyas Medical Imaging’s Ascent3T scanner is a whole-body system optimized for neonatal and infant anatomy and is designed to overcome the disadvantages of adult-sized MRI scanners for imaging small children. The scanner’s small footprint allows it to be sited in the NICU, eliminating the need to transport infants. What’s more, Ascent3T is virtually helium-free and does not require a quench pipe or external venting.
- AI for Alzheimer’s Cleared: A new tool for evaluating brain MRI scans of patients with Alzheimer’s disease is now available following FDA clearance of Neurophet AQUA AD Plus. Anti-amyloid drugs can cause side effects like amyloid-related imaging abnormalities, and Neurophet AQUA AD Plus supports detection and quantification of ARIA including hypointense lesions associated with cerebral microbleeds and hyperintense lesions related to brain edema.
- AI Reduces Breast MRI False Positives: Broader breast MRI adoption has been limited in part due to the modality’s high number of false positives. But researchers in China could solve the problem with BL4AS, an open-source AI algorithm they developed using foundation models. In a paper in Nature Communications, they tested it with 2.7k women with breast lesions, finding that radiologists using BL4AS had higher sensitivity (0.91 vs. 0.87) and specificity (0.76 vs. 0.49), with 25% lower inter-reader variability. BL4AS is available on GitHub.
- AI Triage Gets FDA Clearance: MedCognetics received FDA clearance for CogNet AI-MT+, the company’s AI algorithm for computer-aided triage and notification of suspicious breast cancer lesions on DBT exams. The clearance builds on a 510(k) MedCognetics received in 2022 for QmTriage, a previous generation of its software for 2D mammography, and extends the CogNet AI platform’s capabilities into triage and notification.
- Bad EMR Data Limits Lung Cancer Screening: Incomplete EMR data in patients’ clinical histories may be making it harder to identify whether they are eligible for CT lung cancer screening. Researchers in the Journal of Surgical Research analyzed records for 3.2k patients focusing on best practice advisories, which are EMR alerts advising clinicians that patients meet clinical criteria for certain tests. There wasn’t enough data to calculate smoking histories for 49% of patients, and perhaps as a result the lung screening order rate was just 2.5%.
- Mammo AI for Triple Reading: The discussion in Europe around mammography AI has focused on whether it can eliminate double-reading. But what if you used it for triple reading – AI plus two radiologists? Researchers in Germany tried that with ScreenPoint Medical’s Transpara AI algorithm in 15.4k women in a paper in European Radiology. They found that third-reader AI boosted the cancer detection rate per 1k women 9.5% compared to double-reading or standalone AI (0.75% vs. 0.68% and 0.66%, respectively).
- Italian Screening Guidelines Recommend AI: In what could be an international first, a group of 10 Italian medical societies are recommending the use of AI as part of Italy’s national breast cancer screening program. The guidelines advise using AI as a first step to determine which mammograms should get double-reading and which should get single-reading. That’s a departure from previous guidelines recommending AI in a supporting role for double-reading. Studies like MASAI have shown AI can improve cancer detection while reducing radiologist workload.
- Norway’s Positive Lung Screening Pilot: Add Norway to the list of countries that may soon add CT lung cancer screening programs. Researchers in Acta Oncologica reported positive results from a pilot project that scanned 1k people with smoking histories, revealing a lung cancer incidence rate of 2.3%. There was a high early-stage cancer detection rate (83% stage I and 9% stage II), and the false-positive rate was just 0.6% after pulmonology referral and 1.7% after radiological staging. Complication rates from diagnostic procedures were low.
- France Moves Ahead on Lung Screening: Meanwhile in France, health officials said last week that they expect to have a national CT lung cancer screening program in place by 2030. Lung cancer kills 30k people a year in France, and lung screening could prevent up to 10k deaths over five years. In March, the country will launch the IMPULSION pilot program targeting 20k people aged 50 to 74 who are current or former smokers, with AI from Coreline Soft selected to help radiologists interpret images.
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Will Radiologists Lead or Be Led?
Radiology is facing a defining moment. In this episode of The Radiology Report, host Daniel Arnold of Medality sat down with Frank Lexa, MD, to talk candidly about what comes next for the specialty.
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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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Making AI a Trusted Part of Imaging Workflow
Join Philips experts for this February 10 webinar as they share insights from the 2025 AHRA-Philips Survey, capturing perspectives from imaging leaders as they explore key findings and discuss how organizations can make AI a practical, trusted part of imaging workflow.
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- Discover AI-Powered Radiology Screening Solutions: Visit DeepHealth at ECR 2026 to learn more about how they are transforming population health and cancer screening with innovative AI solutions. Book a meeting today.
- The World’s Happiest Customers – 13 Straight Years: Sectra continues to top the charts when it comes to customer satisfaction. The company recently won seven Best in KLAS awards, including the 13th straight for its Sectra PACS enterprise imaging solution. Find out why on this page.
- The Next Generation of Universal Remote Imaging: Step into the next generation of universal remote imaging with LUMINOS Q.namix R from Siemens Healthineers. Designed for intuitive operation and patient comfort, this award-winning system sets a new standard in fluoroscopy. Explore its precision and efficiency.
- Opportunistic Detection of CAC and Pulmonary Nodules: Achieve a newfound certainty of search for thoracic CT when using ClearRead CT from Riverain Technologies. It’s a natural addition for opportunistic CAC scoring and nodule detection, or as part of a CT lung cancer screening program.
- 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.
- A Global Customer Reach: Mach7 Technologies serves a diverse range of healthcare organizations worldwide, from large integrated delivery networks to smaller community hospitals and imaging centers. Learn what Mach7 can do for you.
- Enlitic’s RSNA 2025 Highlights: What were RSNA 2025 highlights at Enlitic? Chief Strategy Officer Steve Rankin explains the company’s approach to data standardization as well as its recent emphasis on data migration thanks to its acquisition of Laitek.
- A New Era of Imaging Technology: MosaicOS is the cloud-native and AI-native operating system from Mosaic Clinical Technologies designed to expand capacity, cut reporting time, and deliver faster, smarter patient care. Discover how it can improve your radiology operations today.
- Turning Clinical AI Research into Real-World Readiness: Discover how a strategic partnership between Stanford University and Radiology Partners’ Mosaic Clinical Technologies division will pioneer new methods for assessing and monitoring AI tools for medical imaging.
- The Advantages of Cloud-Based PACS: Visage Imaging’s CloudPACS offers significant advantages to healthcare providers for enterprise imaging, including no on-premise requirements and enhanced reliability. Learn more about the advantages of CloudPACS in this video.
- Empowering Radiologists at the Point of Interpretation: Reserve your seat at this February 12 webinar to learn how Rad AI and RSNA Ventures have partnered to deliver trusted, peer-reviewed RSNA insights directly into the radiologist’s workflow — at the exact point of interpretation.
- Leadership in Life Sciences: Quibim is committed to accelerating its development within the life sciences sector and strengthening collaborations with leading pharmaceutical companies. Learn about recent leadership developments that are moving the company forward.
- Experience the Next Evolution: From Day 1, AGFA HealthCare has understood that striking the critical balance between clinical efficiency and quality patient care starts with the physician experience. Learn about their history of firsts on this page.
- Powering Reporting Progress with Efficiency and Interoperability: Radiologists are looking to maximize their efficiency through new reporting tools that integrate easily with their PACS and RIS. Watch this Imaging Wire Show interview with Kailo Medical’s Jason Mercieca and Dieter Smith about new developments in reporting.
- One Imaging Platform for Your Enterprise: Bring radiology and all departments across the enterprise on the same page: one platform, one user experience, with no extra tools or training required. Find out what Merge has to offer on this page.
- Uncovering Hidden Cardiac Amyloidosis with Echo: Us2.ai’s automated echocardiography analysis technology was used in the AI-Screen-CA study to surface previously unrecognized cardiac amyloidosis in an unselected clinical population. Learn about its transformative impact on this page.
- Digital Radiography Designed for Freedom: United Imaging’s new uDR Aurora CX digital radiography system was designed to give you unprecedented freedom in imaging patients thanks to its new advances in computer vision, automation, and AI diagnostics.
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