Top Radiology Trends for 2025

There’s no question that 2025 will be a watershed year for radiology. AI is on the cusp of going mainstream, the radiologist shortage won’t go away, and a number of new U.S. regulatory initiatives promise to reshape the field. 

As we did in 2024, The Imaging Wire asked key opinion leaders in medical imaging to provide their predictions on the technologies, clinical applications, and regulatory developments that will shape the specialty for the next 12 months.

AI Blurs Lines with Generative Models: “Providers will interchangeably use both general-purpose and custom-built GenAI models for regulated (e.g., draft reporting) and unregulated (e.g., EHR summaries) tasks. This will blur current lines for medical device determination, shift performance testing from regulators to providers, and encourage regulators to define comprehensive clearance pathways for GenAI.” – Keith Dreyer, DO, PhD, and Bernardo Bizzo, MD, PhD, Mass General Brigham/Harvard Medical School

AI Focus on Reporting and Synthetic Data: “There will be continued interest in using generative AI for reporting and synthetic data alongside ongoing discussions about bias, fairness, and regulations. We can expect an increasing focus on automated draft report generation. I look forward to seeing the community explore radiology use cases for test-time compute and agentic AI.” Woojin Kim, MD, CMIO, Rad AI

Breast Density Reporting Now in Effect: “The FDA ‘dense breast’ reporting standard is now in effect; needed next is standardization of insurance coverage. Individual state insurance laws are inconsistent, and while a federal Find It Early Act did not pass in 2024, supporters will likely reintroduce the legislation in 2025 to ensure health plans cover screening/diagnostic breast imaging with no out-of-pocket costs for women with dense breasts or at higher risk for breast cancer.” – JoAnn Pushkin, executive director, DenseBreast-info

Breast Screening Based on Risk: “The future direction of breast screening will likely include AI to analyze mammograms and other screening imaging studies as well as patient health data rather than family history and lifestyle choices, allowing more accurate risk assessment. Patients will receive tailored screening recommendations, and imaging may include breast MRI, DBT with AI assistance, and other technologies to identify small high-grade aggressive tumors. Genetic testing results will help identify patients at high elevated risk, providing patients with accurate, clear information about their individual risk and engaging them with shared decision-making regarding benefits and harms of screening opportunities.” – Stamatia Destounis, MD, managing partner, Elizabeth Wende Breast Care 

MRI Safety Comes of Age: “2025 will be the year of MRI safety’s ‘coming of age.’ New CPT codes to reimburse providers for the additional effort required to ensure safe scanning of patients with implants are the first time a formal structure has been established to ensure at least some MRI safety. This CPT change isn’t a stand-alone revolution, but a bellwether of the ‘young adulthood’ of MRI safety and changes yet to come.” Tobias Gilk, founder, Gilk Radiology Consultants

New Era for CT Colonography: “A new era for CT colonography started on January 1, 2025, when CMS started coverage for colorectal cancer screening. Adding CTC as an option for CRC screening will ultimately save lives since it identifies precursor polyps as well as cancer. Expanding screening CTC to some of our most vulnerable patients – including African Americans, who have higher rates of colorectal cancer – will help to improve health disparities. Radiologists need to be prepared to handle increased CTC volumes to assure efficient and effective patient care.” – Judy Yee, MD, Montefiore Medical Center/Albert Einstein College of Medicine

Patients Discover AI for Medical Images:Patients will use consumer-grade, multi-modal generative AI chatbots like ChatGPT to interpret their medical images and verify radiology reports for missed findings. Because they are not marketed for medical use, regulators will struggle to enforce oversight and could announce enforcement discretion for consumer use of these general-purpose AI models.” – Keith Dreyer, DO, PhD, and Bernardo Bizzo, MD, PhD, Mass General Brigham/Harvard Medical School

Radiologist Shortage Deepens:  “Maintaining proper staffing to support increasing volume will be the number one priority for private practices with hospital-based services in 2025. The shortage of radiologists is deepening, and with the demand for staffing growing so is the compensation package necessary to attract candidates. Private practices serving hospitals with weaker payor mix profiles will continue to seek financial support from their hospital partners to remain competitive in the market, not only to recruit new radiologists but also to retain current staff.” – Daniel Corbett, chief of business development, Radiology Business Solutions

Radiology in the Spotlight – for Better or Worse: “2025 will be the first year of Trump 2.0. Elon Musk and Vivek Ramaswamy will be busy beavering through the federal government. All attention will be on healthcare costs again. Radiology will be in the spotlight with calls to curb utilization, adopt AI, abolish fee-for-service, and adopt alternative payment models.” –  Saurabh Jha, MBBS, AKA RogueRad, Hospital of the University of Pennsylvania

Radiology’s Tough Economy Triggers Action: “I expect the global imaging market to look quite different at the end of 2025 versus the start, as tough economic conditions trigger action: M&A of small and mid-size hardware innovators; consolidation in imaging AI with category leaders emerging; the growing influence of non-imaging actors (pharma and life sciences, imaging service providers, big tech); price competition biting for the largest hardware vendors in emerging markets; and speculatively, at least one multi-billion top 20 vendor ‘mega-merger.’ Buckle up!” – Steve Holloway, CEO, Signify Research     

Regulation and Reimbursement: “Reimbursement decreases and recruitment challenges persist in 2025. While it remains critical that radiologists continue to advocate for the specialty and diversify their business plans, it’s becoming increasingly important for hospital-based groups to understand the fair market value of their services and potentially negotiate for additional support.” – Sandy Coffta, VP of client services, Healthcare Administrative Partners

Reimbursement Aids Nuclear Medicine Access: “In 2025, CMS reimbursement policy adjustments are expected to increase nuclear medicine usage and patient access. Ongoing clinical trials will likely drive approval of new radiopharmaceutical therapies and theranostics. With the radiopharmaceutical market projected to reach $12.4B, we expect improved access to nuclear medicine diagnostics and treatments in oncology, neurology, and cardiac imaging.” – Cathy Sue Cutler, PhD, SNMMI president and chair/Brookhaven National Laboratory

The Takeaway 

Making predictions is never easy, and that’s particularly true in a discipline as dynamic as radiology. Whatever happens in 2025, you’ll be sure to read all about it in The Imaging Wire

Is Radiation Dose Too Low?

A new study raises a provocative question: Is radiation dose from medical imaging exams too low? The authors propose in a paper in Nature’s Communications Medicine that lowering radiation dose too much negatively impacts patient care by making exams less diagnostic. But radiation dose experts are pushing back on the claim.

Efforts to minimize medical radiation dose are almost as old as radiology itself. 

  • The arrival of CT in the 1970s saw a sharp rise in radiation dose exposure, but a series of radiation overdose incidents in the 2000s spurred new efforts to  monitor and reduce dose. 

Today, CT radiation doses are remarkably low, with some ultra-low-dose protocols enabling exams at levels below 1 mSv – only slightly higher than a chest X-ray at 0.1 mSv. 

What’s more, CMS this year is launching new dose reporting quality measures designed to reward radiology practices for tracking and reporting radiation dose. 

  • Imaging practices will be able to secure additional reimbursement by complying with an electronic clinical quality measure (eCQM), CMS1074v2, issued by CMS to reduce excessive CT dose exposure. 

That brings us to the new paper. Researchers from Duke University developed a statistical model that they believe balances radiation risk from imaging exams with imaging’s clinical benefit.

  • They created a “detectability index” to quantify the benefit of imaging’s precise characterization of disease – which could lead to misdiagnosis if pathology isn’t adequately visualized – and weigh it against the lifetime cancer risk from an exam. 

They then tested the model in a simulated dataset of 1M liver cancer patients, finding …

  • The clinical risk of lower dose outweighed the radiation risk by 400%.
  • Radiation dose should be increased for over 90% of abdominal CT scans under their formula.

But pushing back against the paper are advocates for radiation dose reduction, including radiologist Rebecca Smith-Bindman, MD, of UCSF. 

  • She points out that the use of imaging continues to grow exponentially, with little evidence to justify its benefit for many uses, and therefore every effort should be taken to minimize harms like radiation risk. 

The Takeaway

The new paper shows that even concepts thought to be self-evident – like the benefit of radiation dose reduction – can still be open to debate. Time will tell whether the new paper gains traction in the discussion over radiation dose management.

Top 10 Radiology Stories of 2024

What were the top 10 radiology stories of 2024 in The Imaging Wire? This year’s top 10 list as measured by reader views demonstrates the fascinating new developments going on every day in medical imaging.

  1. Radiologist Shortage Looms: A July report painted a gloomy picture of the demographic crush facing radiology as the U.S. population ages and imaging volumes rise, but the number of radiologists remains static.
  1. Study Shows AI’s Economic Value: A March study in JACR tackled arguments against AI’s economic value, demonstrating AI’s ability to both improve radiologist efficiency and also drive new revenues for imaging facilities. 
  1. Radiology’s Private-Practice Squeeze: It’s no secret that U.S. radiology’s traditional private-practice model has been slowly fading away, but a study published in AJR in June illustrated the magnitude of the shift. The number of radiologist-affiliated and radiologist-only practices has dropped, even as the total number of U.S. radiologists has gone up.
  1. Radiologist Pay Rebounds: Radiologist pay grew 5.6% and radiology moved up one notch in a May survey of highest-paid U.S. medical specialties for 2023. Physician salaries generally rebounded last year after a decline in 2022.
  1. FDA Keeps Pace on AI Approvals: The FDA in August updated its list of AI- and machine learning-enabled medical devices that have received regulatory authorization, showing the agency keeping a brisk pace of authorizations.
  1. Is Radiology’s AI Edge Fading? FDA figures from May hinted that radiology’s AI edge might be fading, at least when it comes to the specialty’s share of AI-enabled medical devices being granted regulatory authorization.
  1. Is Head CT Overused in the ED? A study in March suggested that head CT could be overused in the emergency department for patients presenting with conditions like headache and dizziness, as researchers found a big increase in CT angiography utilization.
  1. AI Speeds Up MRI Scans: Researchers in March found that AI-based data reconstruction sped up MRI scans and helped their hospital avoid buying a new scanner by improving throughput. 
  1. 6 Solutions to the RT Shortage: A new report published in July from the ASRT and other groups confirmed the shortage of radiologic technologists is severe, but offers some solutions. 
  1. MASAI Gets Even Better at ECR 2024: At ECR 2024, researchers in the MASAI study presented final data indicating that AI could have an even bigger impact on mammography screening than we thought.

The Takeaway
The Imaging Wire’s list of top 10 articles for 2024 shows that bread-and-butter issues like the radiologist shortage and physician reimbursement continue to be top of mind for our readers. The use of AI in radiology is a close second, and our readers can be assured that we will follow all of these issues closely in 2025.

Mobile Mammography’s Value

Despite the proven value of breast screening, compliance rates still aren’t as high as they should be. A new study in Clinical Breast Cancer shows how mobile mammography can improve screening adherence – especially among groups traditionally underserved in the healthcare system.

Estimates of mammography compliance vary – the American Cancer Society estimates that the overall U.S. breast screening rate held steady at 64-66% from 2000 to 2018. 

  • But a variety of factors can influence screening rates, from race to income to location.

Mobile mammography is an obvious solution that brings the imaging test to women rather than requiring them to travel. 

  • But some questions have persisted about mobile screening, such as whether it might cannibalize facility-based mammography programs, which have higher fixed costs. 

In the new study, researchers from the Harvey L. Neiman Health Policy Institute reviewed CMS claims data for 2.6M eligible women from 2004 to 2021. 

Researchers found …  

  • 50% of women had received a screening mammogram.
  • Only 0.4% used mobile mammography, but rates were higher in rural areas (1%) compared to large cities (0.3%) and small towns (0.4%).
  • American Indian or Alaska Native race was the factor most predictive for receiving mobile mammography (OR=5.5).
  • Other predictive factors included residence in a rural geography (OR=3.3), as well as in a community with lower income (OR=1.4).
  • Mobile mammography did not cannibalize facility-based mammography, based on data from heat maps showing utilization of both types of service.

Researchers concluded that mobile mammography can reduce health disparities by bringing imaging technology to underserved communities that might not otherwise have access to it. 

  • The findings echo a study earlier this year in which mobile mammography was also found to benefit the environment by reducing greenhouse gas emissions that occur when patients have to travel to medical facilities for screening.

The Takeaway

It may seem like a no-brainer to bring imaging to the people who need it, but the new study provides valuable evidence that the practice works on a national scale. Increased use of mobile imaging is an important tool for addressing persistent disparities in access to care. 

Unlocking Body Composition Insights with Voronoi Health Analytics

Body composition plays a pivotal role in monitoring organ and tissue health and predicting treatment outcomes. Accurate changes in body composition metrics can indicate reduced muscle quantity and quality – a sign of sarcopenia – as well as altered fat distribution in organs such as the liver in metabolic diseases, epicardial and paracardial fats in cardiovascular health, and more.

However, manual segmentation is time-consuming and labor-intensive. 

  • Voronoi Health Analytics eliminates this bottleneck by combining cutting-edge AI with efficient visualization tools, automating the extraction of body composition metrics from CT and MRI scans. The company’s solutions transform imaging data into actionable insights, improving patient outcomes.

Voronoi Health Analytics provides innovative, intuitive AI tools that enable clinicians and researchers to extract quantitative body composition measurements rapidly and with high accuracy – no programming required. 

  • The company’s platforms are trusted by over 175 research labs across 25 countries, with numerous publications validating their accuracy and impact on clinical care and medical research.

Voronoi has two flagship solutions …

  • DAFS: A comprehensive 3D segmentation platform for analyzing multiple tissues, organs, lesions, and vasculature across CT and PET/CT imaging. DAFS also overlays CT segmentations onto PET scans, enabling rapid, high-accuracy assessments of PET tracer uptake in organs, tissues, and lesions.
  • DAFS Express: Optimized for single-slice body composition analysis from CT and MRI scans, this tool delivers precise measurements of skeletal muscle, visceral fat, intermuscular fat, and subcutaneous fat in seconds, making it ideal for high-throughput clinical settings.

Accurate body composition analysis is critical for staging body habitus, detecting onset of signatures of adverse health such as metabolic or cardiovascular disorders, evaluating disease progression, and monitoring organ and tissue health as a function of disease and intervention. Voronoi’s platforms address key challenges such as …

  • Reducing Workloads: Automate routine segmentation tasks and allow clinicians to focus on complex cases.
  • Improving Precision: Deliver consistent, reproducible results across patients and studies.
  • Advancing Care: Provide predictive insights that help optimize treatment strategies.

DAFS and DAFS Express seamlessly integrate into existing imaging workflows, enhancing efficiency without disrupting operations.

Body composition analysis goes beyond measuring muscle and fat. It quantifies all organs and tissues, creating data that drives predictive models. 

  • Voronoi’s vision is to empower healthcare professionals with tools that simplify complexity, support proactive care, and enhance patient outcomes.

Discover how Voronoi Health Analytics is revolutionizing body composition analysis. Visit the company’s website to request a demo and elevate your workflow today.

AI As Malpractice Safety Net

One of the emerging use cases for AI in radiology is as a safety net that could help hospitals avoid malpractice cases by catching errors made by radiologists before they can cause patient harm. The topic was reviewed in a Sunday presentation at RSNA 2024

Clinical AI adoption has been held back by economic factors such as limited reimbursement and the lack of strong return on investment. 

  • Healthcare providers want to know that their AI investments will pay off, either through direct reimbursement from payors or improved operational efficiency.

At the same time, providers face rising malpractice risk, with a number of recent high-profile legal cases.

  • For example, a New York hospital was hit with a $120M verdict after a resident physician working the night shift missed a pulmonary embolism. 

Could AI limit risk by acting as a backstop to radiologists? 

  • At RSNA 2024, Benjamin Strong, MD, chief medical officer at vRad, described how they have deployed AI as a QA safety net. 

vRad mostly develops its own AI algorithms, with the first algorithm deployed in 2015. 

  • vRad is running AI algorithms as a backstop for 13 critical pathologies, from aortic dissection to superior mesenteric artery occlusion.

vRad’s QA workflow begins after the radiologist issues a final report (without using AI), and an algorithm then reviews the report automatically. 

  • If discrepancies are found the report is sent to a second radiologist, who can kick the study back to the original radiologist if they believe an error has occurred. The entire process takes 20 minutes. 

In a review of the program over one year, vRad found …

  • Corrections were made for about 1.5k diagnoses out of 6.7M exams.
  • The top five AI models accounted for over $8M in medical malpractice savings. 
  • Three pathologies – spinal epidural abscess, aortic dissection, and ischemic bowel due to SMA occlusion – would have amounted to $18M in payouts over four years.
  • Adding intracranial hemorrhage and pulmonary embolism creates what Strong called the “Big Five” of pathologies that are either the most frequently missed or the most expensive when missed.

The Takeaway

The findings offer an intriguing new use case for AI adoption. Avoiding just one malpractice verdict or settlement would more than pay for the cost of AI installation, in most cases many times over. How’s that for return on investment?

RSNA 2024 Video Highlights

Last week’s RSNA 2024 meeting saw a major bounce in attendance, with early numbers indicating an 18% jump in the number of radiology professionals wandering the halls of McCormick Place. The increase brought total attendance at midweek to 40k. 

As in past years, AI dominated the discussion, both in the presentation rooms and on the exhibit floor. Researchers presented the latest findings on AI’s ability to aid radiologists, while vendors showcased new algorithms for use cases from mammography screening to fracture detection. New technologies like foundation models for AI training bubbled under the surface and promise to have a major impact in years to come.

It was our privilege to speak with many of the most interesting vendors exhibiting at RSNA 2024, from multinational vendors to small but promising start-ups.

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

How Are Doctors Using AI?

How are healthcare providers who have adopted AI really using it? A new Medscape/HIMSS survey found that most providers are using AI for administrative tasks, while medical image analysis is also one of the top AI use cases. 

AI has the potential to revolutionize healthcare, but many industry observers have been frustrated with the slow pace of clinical adoption. 

  • Implementation challenges, regulatory issues, and lack of reimbursement are among the reasons keeping more healthcare providers from embracing the technology.

But the Medscape/HIMSS survey shows some early successes for AI … as well as lingering questions. 

  • Researchers surveyed a total of 846 people in the U.S. who were either executive or clinical leaders, practicing physicians or nurses, or IT professionals, and whose practices were already using AI in some way.

The top four tasks for which AI is being used were administrative rather than clinical, with image analysis occupying the fifth spot … 

  1. Transcribing patient notes (36%). 
  2. Transcribing business meetings (32%).
  3. Creating routine patient communications (29%).
  4. Performing patient record-keeping (27%).
  5. Analyzing medical images (26%).

The survey also analyzed attitudes toward AI, finding …

  • 57% said AI helped them be more efficient and productive.
  • But lower marks were given for reducing staff hours (10%) and lowering costs (31%).
  • AI got the highest marks for helping with transcription of business meetings (77%) and patient notes (73%), reviewing medical literature (72%), and medical image analysis (70%).

The findings track well with developments at last week’s RSNA 2024, where AI algorithms dedicated to non-clinical tasks like radiology report generation, scheduling, and operation analysis showed growing prominence. 

  • Indeed, many AI developers have specifically targeted the non-clinical space, both because commercialization is easier (FDA authorization is not typically needed) and because doctors often say they need more help with administrative rather than clinical tasks.

The Takeaway

While it’s easy to be impatient with AI’s slow uptake, the Medscape/HIMSS survey shows that AI adoption is indeed occurring at medical practices. And while image analysis was radiology’s first AI use case, speeding up workflow and administrative tasks may end up being the technology’s most impactful application.

RSNA Goes All-In on AI

CHICAGO – It’s been AI all the time this week at RSNA 2024. From clinical sessions packed with the latest findings on AI’s utility to technical exhibits crowded with AI vendors, artificial intelligence and its impact on radiology was easily the hottest trend at McCormick Place.

Radiology greeted AI with initial skepticism when the first applications like IBM Watson were introduced at RSNA around a decade ago.

  • But the field’s attitude has been evolving to the point where AI is now being viewed as perhaps the only technology that can save the discipline from the vicious cycle of rising exam volume, falling reimbursement, and pervasive levels of burnout.

RSNA telegraphed the shift last year by announcing that Stanford University’s Curtis Langlotz, MD, PhD, would be RSNA 2024 president. 

  • Langlotz is one of the most respected AI researchers and educators in radiology, and even coined the phrase that while AI would not replace radiologists, radiologists with AI would replace those without it. 

In his president’s address, Langlotz echoed this theme, painting a picture of a future radiology in which humans and machines collaborate to deliver better patient care than either could alone.

  • Langlotz’s talk was followed by a presentation by another prominent AI luminary – Nina Kottler, MD, of Radiology Partners.

Kottler took on the concerns that many in radiology (and in the world at large) have about AI as a disruptive force in a field that cherishes its traditions.

  • She advised radiology to take a leading role in AI adoption, repeating a famous quote that the best way to predict the future is to create it yourself. 

What were the other trends besides AI at RSNA 2024? They included…

  • Photon-counting CT, which is likely to see new market entrants in 2025.
  • Total-body PET, with PET scanners that have extra-long detector arrays.
  • Theranostics, a discipline that integrates diagnosis and therapy and promises to breathe new life into SPECT.
  • CT colonography and CCTA, which will see positive reimbursement changes in 2025.
  • Continued growth of CT lung screening, especially as a tool for opportunistic screening of other conditions.
  • Continued expansion of AI for breast screening.

The Takeaway

The RSNA meeting has been called radiology’s Super Bowl and World Cup all rolled into one, and this year didn’t disappoint. RSNA 2024 showed that radiology is prepared to fully embrace AI – and a future in which humans and machines collaborate to deliver better patient care.

Mammo AI Kicks Off RSNA 2024

Welcome to RSNA 2024! This year’s meeting is starting with a bang, with two important sessions highlighting the key role AI can play in breast screening. 

Sunday’s presentations cap a year that’s seen the publication of several large studies demonstrating that AI can improve breast cancer screening while potentially reducing radiologist workload. 

  • That momentum is continuing at RSNA 2024, with morning and afternoon sessions on Sunday dedicated to mammography AI. 

Some findings from yesterday’s morning session include … 

  • Two AI algorithms were better than one when supporting radiologists in breast screening, with cancer detection ratios relative to historic performance rising from 0.97 to 1.08 with one AI to 1.09 to 1.14 with two algorithms.
  • ScreenPoint Medical’s Transpara algorithm was able to prioritize the worklist for 57% of breast screening exams by assigning risk scores to mammograms, helping reduce report turnaround times. 
  • iCAD’s ProFound AI software helped radiologists detect 7.8% more breast cancers on DBT exams, and cancers were detected at an earlier stage. 
  • Applying AI for breast screening to a racially diverse population yielded evenly distributed performance improvements.

Meanwhile, the Sunday afternoon session also included significant mammography AI presentations, such as …

  • A hybrid screening strategy – with suspicious breast cancer cases only recalled if the AI exhibits high certainty – reduced workload 50%. 
  • Lunit’s Insight DBT AI showed potential to reduce interval cancer rates in DBT screening by identifying 27% of false-negative and 36% of interval cancers.
  • In the ScreenTrustCAD trial in Sweden, using Lunit’s Insight MMG algorithm to replace a double-reading radiologist reduced workload 50% with comparable cancer detection rates.
  • A German screening program found that ScreenPoint Medical’s Transpara AI boosted the cancer detection rate by 8.7% (from 0.68% to 0.74%), with 8.8% of cancers solely detected by AI.
  • Researchers took a look back at abnormality scores from three commercially available AI algorithms after cancer diagnosis, finding evidence that cancers could be detected earlier. 

The Takeaway

Breast screening seems to be the clinical use case where radiologists need the most help, and Sunday’s sessions show the progress AI is making toward achieving that reality. 

Be sure to check back on our X, LinkedIn, and YouTube pages for more coverage of this week’s events in Chicago. And if you see us on the floor of McCormick Place, stop and say hello!

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