Tag: RSNA 2025

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.

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. 

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