Tag: medical imaging

Top 10 Radiology Videos of 2025

Posted on by Brian Casey

If a picture tells a thousand words, then how much more does a video tell you? Here at The Imaging Wire, we believe there’s nothing like having healthcare professionals and industry executives tell you in their own words what’s really going on in radiology.

That’s why video has been an important part of our story since the early days of The Imaging Wire. And over the course of 2025, we published over 80 videos, including on-the-showfloor reports from ECR, HIMSS, SIIM, and RSNA.  

Below are the best of the best – The Imaging Wire’s top 10 radiology videos for 2025 – as measured by views on our YouTube channel. We hope you’ve enjoyed watching our interviews as much as we’ve enjoyed producing them, and we look forward to bringing you more top-notch radiology video content in 2026. 

The Imaging Wire Team

Risk-Based Mammo Screening – Ready for Prime Time?

Posted on by Brian Casey

Is mammography screening based on patient risk ready to take over for age-based screening? Results from the WISDOM study presented at last week’s San Antonio Breast Cancer Symposium and published simultaneously in JAMA suggest that while risk-based screening has its merits, more work may need to be done. 

Cancer screening exams like mammography have reduced disease-specific mortality, but (with the exception of lung cancer screening) all use exclusively age-based criteria to determine who should get screened.

  • Age isn’t a great tool for determining who’s at higher risk of getting cancer, but it’s the best tool we’ve had – up to now.

New cancer risk prediction tools are now becoming available, prompting debate over whether these techniques could make screening more precise by directing it to those most at risk.

  • Higher-risk people could get more frequent screening, while lower-risk individuals might be directed to longer screening intervals.

The WISDOM study presented at SABCS 2025 investigates this question. WISDOM is a randomized clinical trial that compared risk-based breast screening to age-based annual screening in 28.4k women followed for five years. 

  • Risk categorization was performed with genetic testing, polygenic risk scores, and BCSC scores, which incorporate family history and imaging results. 

Women in the risk-based screening group were directed into one of four screening strategies, from alternating mammography and MRI every six months for high-risk women to no screening until age 50 for low-risk women.

  • The study’s primary outcomes were detection rates for breast cancers rated as stage IIB or higher and effectiveness in reducing biopsy rates – a proxy for screening-caused morbidity.

Across the study population, researchers found…

  • The rate of mammograms per 100k person-years was lower in the risk-based cohort compared to age-based screening (43.1k vs. 46.9k). 
  • The rate of stage IIB or higher cancers per 100k person-years was also lower in the risk-based cohort (30 vs. 48).
  • But there was no statistically significant difference in biopsy rates, with a rate difference of 99 per 100k person-years (p = 0.10).

One problem with the WISDOM trial was that the actual screening exams were performed outside the study, and some patients did not comply with screening recommendations, potentially confounding results. 

The Takeaway

The WISDOM authors concluded that a risk-based screening approach is safe, but the lack of a difference in biopsy rates makes one wonder if veering from established age-based criteria is worth it. In any event, the coming arrival of risk stratification based on AI mammogram analysis could make the genetic testing-based approach used in WISDOM obsolete.

FDA AI Approvals Surge Past 1k for Radiology

Posted on by Brian Casey

The number of AI-enabled medical devices granted FDA marketing authorization for radiology surged past the 1k mark in the latest update from the agency. The numbers show that radiology’s share of authorizations remains stable at just over three-quarters of total approvals.

The FDA regularly releases the list in what’s become a closely watched barometer of both total approvals as well as which medical specialties are most active in AI.

  • Radiology has historically garnered the lion’s share of approvals – perhaps no surprise given the discipline’s early adoption of both digital image management and AI – with the first authorization granted in 1998 (for ImageChecker mammography CAD from R2 Technology/Hologic). 

The new list tracks authorizations through the end of September 2025, and indicates the agency has…

  • Authorized 1,356 AI-enabled devices since it started tracking, up 8.5% since its last report.
  • Approved 1,039 AI-enabled radiology devices, with imaging accounting for 77% of total medical authorizations since 1998.
  • Radiology secured 75% of total authorizations from June to September (83/110), compared to 78% from January to May 2025, 73% for all of 2024, and 80% for 2023. 
  • GE HealthCare retains the top spot as the company with the most radiology AI authorizations, at 110 (including recent acquisitions Caption Health, MIM Software, and icometrix).
  • Next is Siemens Healthineers at 86 (including Varian), then Philips at 48 (including DiA Analysis and TomTec), Canon at 41 (including Vital Images and Olea), United Imaging at 38, and Aidoc at 30. 

As always, it’s worth noting that the FDA’s list includes not only standalone software applications, but also imaging equipment that might have AI applications embedded into it, such as a mobile X-ray system with AI algorithms for detecting emergent conditions. 

  • Also, the agency noted that it is exploring ways to identify and tag AI-based devices that use foundation models and large language models. The FDA has yet to approve an LLM-based medical device.

The Takeaway

The new numbers indicate that radiology’s dominance of medical AI continues. But they also show that the FDA has returned to a regular twice-yearly cadence of updating its list of AI-enabled medical devices after a break of nearly a year – news that’s welcome to AI developers.

RSNA 2025 Video Highlights

Posted on by Brian Casey

RSNA 2025 is a wrap, and this year’s meeting offers an intriguing look at the forces that are shaping radiology – especially AI and imaging informatics.

It’s no secret that AI has come to dominate recent RSNA conferences, with its promise of fundamentally reshaping how radiologists do their jobs.

  • The hope is that by making radiologists more efficient, AI will help radiologists manage rising imaging volumes with a workforce that’s been largely stagnant.

But that dream has been a long time in coming, and the AI sector is being forced to make adjustments as it waits for broader clinical adoption. Many of these trends were on display at RSNA 2025, including…

  • Industry consolidation as AI developers make acquisitions to build out integrated suites of AI algorithms.
  • New questions about the commercial viability of the AI platform model given Bayer’s step back from Blackford.
  • The rise of AI network alliances as alternatives to the integrated suite or platform approaches.
  • Building excitement over the performance of foundation and vision language models for clinical tasks.
  • Renewed attention on radiology reporting as perhaps the primary use case where AI can truly help radiologists work more efficiently. 

Our video interviews from RSNA 2025 explore many of these topics and more, giving you an as-it-happened look at news from McCormick Place.

The Takeaway

We hope you enjoy watching our coverage as much as we enjoyed producing it! Check out the links below, on our YouTube page, or visit the Shows page on our website.

Risks of Rising Contrast Use

Posted on by Brian Casey

The use of contrast media in medical imaging procedures has been rising steadily in recent years, a trend that creates environmental risks. So says a new study in JAMA Network Open that documents growth in contrast use over the past 13 years. 

Contrast is an essential part of many imaging exams, helping radiologists better visualize pathology that might be harder to see on unenhanced scans.

  • But contrast use also comes with a wide array of risks, from patient reactions that on rare occasions can be fatal to environmental buildup of contrast that’s excreted from patients after exams and makes its way into local waterways – including drinking water.

This latter phenomenon is what’s explored in the new paper, authored by researchers from the ACR’s Harvey L. Neiman Health Policy Institute. 

  • They analyzed Medicare claims from 2011 to 2024 for 169M contrast-enhanced imaging exams that involved the use of 13.5B milliliters of contrast for both CT and MRI studies. 

HPI’s analysis found…

  • Iodinated CT contrast use grew 5.2% and gadolinium MRI was up 3.5% from 2014 to 2019.
  • Contrast use fell 9.6% for CT and 15.6% for MRI during the COVID-19 pandemic in 2020, but then rebounded afterward.
  • A small number of exams accounted for most of the CT contrast usage, such as CT abdomen and pelvis (4.4B mL) and CT chest (2.7B mL).
  • MRI numbers were far lower, such as for brain MRI scans (221M mL) and abdominal MRI studies (70M).

So what can radiology do? Simply reducing contrast use for environmental reasons isn’t much of a solution, as it has implications not only for patient care but also for medical malpractice risk. 

  • But ongoing efforts to reduce inappropriate imaging would have a follow-on effect of also lowering contrast use, as would protocols to reduce contrast use for patient safety reasons (the introduction of high-relaxivity gadolinium-based agents that cut MRI contrast dose by 50% is a great example).

The authors also cite the development of AI-based techniques that could create contrast-like exams from existing non-contrast data, offering AI developers another possible segment to target. 

The Takeaway

The new study offers an interesting twist in the debate over contrast reduction, pointing out that efforts to reduce unnecessary contrast use promise to benefit not only patients but also the planet.

Snow Doesn’t Slow RSNA 2025

Posted on by Brian Casey

RSNA 2025 is wrapping up this week in what’s been a cold and snowy Chicago. While many attendees experienced travel delays getting into the show on Sunday, the disruptions didn’t slow the blistering pace of radiology innovation on display.

As has been the case all year in radiology, AI has been a hot topic at McCormick Place, both in the presentation rooms and on the technical exhibit floor.

  • Much of the conversation is shifting away from individual point sources of AI – such as for analyzing images – and toward solutions that provide operational efficiencies such as faster radiology reporting.

But big iron has always been RSNA’s bread and butter, and RSNA 2025 didn’t disappoint. 

  • Major new product launches took place in the vendor exhibits, especially in helium-free MRI, photon-counting and spectral CT, and angiography, showing that vendors continue to invest in hardware development. Check out our coverage of the major OEMs in The Wire section below.

What were the other trends at RSNA 2025? They included…

  • Growing buzz around new AI technologies like foundation and vision language models.
  • Real-world clinical applications of AI such as triaging mammography screening.
  • Growing momentum of CT lung cancer screening, both internationally and in the U.S.
  • Use of generative AI to improve radiology reporting.
  • Imaging’s contribution to greenhouse gas emissions – and how to reduce them. 
  • Imaging-based biomarkers that can predict future disease incidence.
  • Opportunistic screening with imaging tests that can detect multiple diseases in one exam.

The Takeaway

Despite weather-related challenges, RSNA 2025 once again showed the importance of radiology’s showcase annual conference for bringing together academics, private-practice providers, vendors, and allied health professionals to meet, exchange ideas, and work together toward providing better patient care. It was great seeing everyone in Chicago – safe travels home!

CT Lung Screening Leads RSNA’s First Day

Posted on by Brian Casey

Day 1 of RSNA 2025 is in the books, and new research into CT lung cancer screening dominated the scientific sessions at Chicago’s McCormick Place.

Lung cancer screening is drawing attention as screening programs go into effect internationally.

  • In the U.S., lung screening is hampered by low completion rates (18-19%), but providers are finding that participation can be improved with aggressive identification and outreach to eligible patients.

Some highlights from Sunday (with handy session numbers to help you follow along) include…

  • The ScreenLungNet AI model predicted three-year lung cancer risk from CT lung screening scans with AUCs from 0.93-0.94 (S4-SSCH02-1).
  • In a study of 2.6k patients with lung cancer, only 36% met 2021 USPSTF lung cancer screening criteria, and just 5% actually got screened. Only 23% had data on their smoking history in the EMR (S4-SSCH02-2).
  • Risk assessment scores were used to perform CT lung screening of lower-risk people every two years rather than annually, reducing screening’s harms without missing many cancers (S4-SSCH02-4).
  • Compared to the landmark NLST study, a real-world CT lung screening program had fewer benign surgeries (12% vs. 18%), lower complication rates (24% vs. 32%), and better recurrence-free survival (HR = 0.60) (S4-SSCH02-5).
  • CT radiation dose was reduced 51% and contrast iodine use 61% through a triple-optimized protocol that included 80-kVp scanning, GE HealthCare’s TrueFidelity deep learning reconstruction, and low-iodine adaptive contrast injection (S2-SSCA01-1).
  • Using AI for automated patient positioning and scan range in CT exams cut positioning time 41% with 10-13% lower radiation dose and no discernible impact on image quality (S4-SSIN01-1).
  • Measures of adiposity acquired opportunistically from coronary artery calcium CT scans using HeartLung Technologies’ AI-CVD algorithm predicted adults at risk of diabetes in a study of 2.9k people (S5-SSCA02-6). 
  • The Promedius AI algorithm for osteoporosis assessment of chest radiographs had an AUC of 0.84 in a study of 1k adults from three countries (M3-SSCH03-1).
  • A real-world study of 2.1k patients found that DeepTek’s chest X-ray AI algorithm had an AUROC of 0.95 for detecting any of 13 clinically significant findings (M3-SSCH03-2).
  • Researchers presented a feasibility study of a compression-free spectral DBT mammography system, finding spatial resolution close to state-of-the-art systems (S4-SSPH02-6).
  • Researchers presented their protocol for MRI scanning of patients with cardiac implanted electronic devices. Over 10 years they scanned 7.3k patients with no major adverse events (S5-SSCA02-1).
  • Adding MRI data to a multimodal transformer AI model improved its ability to predict five-year breast cancer risk in intermediate- and high-risk women (S2-SSBR01-6).

The Takeaway

RSNA 2025 is off to a great start. Be sure to check back with Thursday’s newsletter for more radiology news from Chicago, and follow along on our social media channels for ongoing video updates. 

GE to Buy Intelerad in Massive $2.3B Acquisition

Posted on by Brian Casey

In what could be the biggest radiology IT acquisition in years, GE HealthCare will acquire medical image management software company Intelerad in a purchase valued at $2.3B. The acquisition will bolster GE’s position in the outpatient image management segment, which is rapidly shifting from on-premises PACS models to cloud-based environments.

Intelerad was founded in Montreal in 1999 as a PACS developer and has grown through acquisitions of its own in recent years.

  • U.K. private equity firm Hg took a controlling interest in Intelerad in 2020, and the company soon embarked on a series of acquisitions that rolled up smaller imaging IT companies like Digisonics (2020), Ambra Health (2021), Insignia (2021), Lumedx (2021), Life Image (2022), and PenRad Technologies (2022). 

After taking a few years to digest the new companies, Intelerad began focusing on moving its technology and customers to cloud-based architecture, such as by releasing a cloud-native version of its InteleHeart software and by moving its PACS, VNA, and image-sharing applications to AWS cloud hosting.

GE needs no introduction, of course, but the company clearly sees the attraction of Intelerad’s core market in outpatient imaging, which complements GE’s focus on larger hospitals and health systems. 

In a conversation with The Imaging Wire, Scott Miller, president and CEO, Solutions for Enterprise Imaging at GE HealthCare, explained several of the acquisition’s advantages …

  • Imaging exams are moving from hospitals to outpatient centers due to lower costs.
  • Outpatient facilities are following hospitals in moving their data to the cloud, putting Intelerad at the intersection of two major trends.
  • Intelerad’s geographic focus has been on English-speaking countries, giving GE the opportunity to plug Intelerad products into its international distribution network. 

GE estimates that Intelerad will generate $270M in revenue in its first full year under GE ownership. 

  • Intelerad’s sales have been growing at a rate in the low double digits, and GE expects that pace to accelerate. 

Is the new acquisition a sign of growing consolidation in the radiology AI and image management sectors? 

  • Other recent purchases in 2025 include Radiology Partners’ purchase of Cognita Imaging, Lunit’s acquisition of Prognosia, and GE’s own purchase of icometrix, completed earlier this month. RadNet also acquired iCAD earlier in the year.

The Takeaway

GE’s acquisition of Intelerad offers multiple benefits to the multimodality OEM, from Intelerad’s presence in the outpatient imaging sector to its experience in cloud-based image management and broad product portfolio. The question is whether the purchase spurs other big iron vendors to answer with acquisitions of their own. 

Next-Generation AI Platform Redefines Radiology Workflow Standards

Posted on by Partner Content

AI is no longer being viewed as a diagnostic aid but as essential medical infrastructure. Nowhere is that more apparent than in lung screening, with Germany and other European Union countries increasingly embedding AI into their lung cancer screening guidelines and pilot programs.

This evolution will be on display at RSNA 2025, where Coreline Soft will introduce its groundbreaking chest AI platform AVIEW 2.0.

  • The solution demonstrates how unified AI automation is fundamentally transforming radiology workflows and elevating diagnostic precision across pulmonary, cardiac, and airway pathologies.

AVIEW 2.0 represents a paradigm shift from task-specific tools to an integrated diagnostic ecosystem. 

  • The platform seamlessly combines lung-cancer screening (LCS), coronary-artery calcium (CAC) scoring, and COPD quantification into a single, continuous analytical pipeline. 

Clinical validation shows radiologists using AVIEW 2.0 achieve 89% increase in case throughput and 60% reduction in interpretation time compared to the previous generation. 

  • This effectively consolidates multi-disease CT assessment into one streamlined, automated workflow.

AVIEW’s clinical foundation extends far beyond pilot studies. The platform has processed over 2.5M cases across 19 countries, establishing itself as a proven solution in diverse healthcare ecosystems. 

  • Most notably, AVIEW has been selected as the AI platform for major government-led lung cancer screening pilots and programs in Germany, France, and Italy.

Beyond Europe, AVIEW solutions are already integrated into major U.S. medical centers, where their clinical reliability has been independently validated in real-world settings…

  • UMass Memorial Medical Center has deployed the system as an integrated platform for LCS, CAC, and COPD diagnosis, supporting full-spectrum thoracic screening in daily radiology operations.
  • Temple Lung Center, 3DR Labs, and ImageCare Radiology have incorporated AVIEW products into their research and diagnostic environments – each adapting AI functions to site-specific workflows and physician preferences.

SOL Radiology, a fast-growing radiologist-owned practice serving communities across California and Illinois, has deployed AVIEW LCS Plus across its outpatient centers and hospital network, leveraging the platform for high-confidence nodule detection, rapid turnaround, and integrated COPD/CAC assessment. 

  • The group reports significant gains in diagnostic efficiency and consistency within one week of implementation, supporting its vision for technology-driven, high-quality community radiology.

With national-scale validation in Europe, clinical adoption across top-tier U.S. institutions, and 2.5M cases processed globally, Coreline Soft is positioning AVIEW 2.0 as the new benchmark for AI-driven thoracic imaging – where efficiency, accuracy, and scalability converge.

The Takeaway

Coreline Soft will conduct an end-to-end AI workflow demonstration in the “Radiology Reimagined” demo zone at RSNA 2025, using real-world clinical scenarios. With AVIEW and HUB, the full pathway – from triage and interpretation to reporting and quality management – will be validated against standards such as IHE and FHIR, allowing attendees to experience integrated flow firsthand. Learn more or book an appointment on Coreline Soft’s website.

RP Acquires Vision AI Firm Cognita Imaging

Posted on by Brian Casey

Radiology Partners ramped up its investment in AI by acquiring Cognita Imaging, a startup that’s developed AI vision language models for analyzing CT and X-ray images and drafting initial radiology reports. RP executives see the acquisition as going beyond traditional point-source AI models and toward a future where AI automates much of the traditional image interpretation process.

The $80M acquisition expands on an equity stake RP already had in Cognita, which had been operating in stealth mode since its spin-off from Stanford University’s Center for Artificial Intelligence in Medicine and Imaging lab.

  • Cognita was formed by a team led by CEO Louis Blankemeier, PhD, to commercialize Stanford research on vision language models, a type of generative AI that’s far more versatile than the traditional point-source models being commercialized to analyze medical images.

Instead, Cognita’s technology is able to analyze text as well as CT or X-ray images and produce first drafts of radiology reports that just need a radiologist’s review and signature to be complete.

  • Extremely positive clinical tests with Cognita’s VLM models spurred RP to acquire the rest of the company it didn’t already own, said Rich Whitney, chairman and CEO of Radiology Partners. 

Cognita’s technology powers Mosaic Drafting, RP’s new application for helping radiologists draft reports that operates under the company’s recently launched Mosaic Clinical Technologies branding. Early clinical testing has found that Mosaic Drafting…

  • Increases radiologist detection rates by 52%.
  • Results in a fourfold decline in radiologist errors.
  • Reduces radiologist reading times by up to 76%.

RP plans to deploy Mosaic Drafting through Mosaic Clinical Technologies, which the company launched in July as the technological foundation for a massive rollout of AI across its physician practices. 

  • Mosaic Chief Medical AI Officer Nina Kottler, MD, said Mosaic Drafting is currently being used within Radiology Partners under IRB approval, but the company will pursue an FDA authorization – most likely under a de novo pathway – that probably will come sometime in 2026.

In a broader sense, RP sees Mosaic Drafting and other VLM tools as key to the growing mismatch between rising imaging volume and stagnant radiologist supply – a mismatch that can only be solved through greater automation. 

  • And as the largest private radiology organization in the U.S., Radiology Partners has the organizational heft to make VLMs work on a wide scale.

The Takeaway 

RP’s acquisition of Cognita is a major development in putting vision language models on the fast track to real-world clinical use. Unlike point-source AI, VLMs could hold the key to really solving radiology’s volume overload dilemma.

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