Category: Imaging IT

SIIM 2026 Video Highlights

Posted on by Brian Casey

The annual meeting of the Society for Imaging Informatics in Medicine is always one of the highlights on the radiology calendar. SIIM 2026 was no exception, once again underscoring the vibrant community driving advances in imaging IT.

From radiology reporting to enterprise image management, SIIM 2026 highlighted the state of the art in imaging IT. We talked to many of radiology IT’s key opinion leaders in Pittsburgh, and we’re pleased to bring the discussions to you in this newsletter.

We hope you enjoy watching our SIIM 2026 video coverage as much as we enjoyed producing it! 

Check out the SIIM 2026 video links below or visit the Shows page on our website, and keep an eye out for our next Imaging Wire newsletter on Thursday.

– Brian Casey, Managing Editor

Top Trends from SIIM 2026

Posted on by Brian Casey

Last week’s SIIM 2026 conference demonstrated once again radiology’s ongoing evolution, from a discipline once known for big iron to one dominated by software. From radiology reporting to the evolving AI platform segment, below are the top seven trends from Pittsburgh. 

  • Reporting Stays Red Hot: Radiology reporting was the top theme from SIIM 2025, and the segment got even hotter with Microsoft’s decision to sunset its PowerScribe 360 radiology reporting software, which has drawn a host of new competitors into the segment. At SIIM 2026, a common theme was enterprise imaging companies adding reporting modules to their solutions.  
  • AI Adoption Moving Slowly But Surely: Adoption of radiology AI has been frustratingly slow, but it’s moving inexorably toward broader clinical use. At SIIM 2026, some 68% of the radiology-oriented papers focused on AI in some way, especially the new generation of foundation and vision language models that are enabling targeted AI algorithms to be developed more quickly than ever.
  • AI Governance Gets Real: Growing adoption of AI algorithms is creating a new issue: How to manage all this new technology. AI governance therefore was a major issue at SIIM 2026 as healthcare providers debated the legal and ethical necessity to better manage AI adoption, deployment, and utilization.
  • Other ‘Ologies Get into the Act: Radiology likes to think of SIIM as its own conference, but it also encompasses other ‘ologies that are moving into digital image management, like pathology and ophthalmology. At SIIM 2026, several imaging IT vendors showed integration with data from these disciplines, giving healthcare institutions a single source for their healthcare data management.
  • The Rise of All-in-One Vendors: A growing number of imaging IT vendors are rolling out solutions that combine image viewer, worklist, and reporting into a single platform, simplifying purchasing, deployment, and maintenance for radiology customers. Many of these firms seem to be getting traction with potential buyers, indicating the all-in-one concept could be one whose time has come.
  • Agentic AI Takes Shape: Agentic AI is a growing trend in radiology as algorithm developers build solutions to take on mundane tasks and free up radiologists to focus on their primary task: interpreting images. But the question is, will agentic AI work in the real world, or simply pile more technology on clinicians?
  • What Next for AI Platforms? Bayer’s withdrawal from the AI platform market by pulling its support for Blackford in 2025 raised many questions about the platform model that persisted at SIIM 2026. AI platforms seem to be evolving to add additional services like AI monitoring and governance.

The Takeaway

SIIM may not be radiology’s largest show, but for those in the imaging IT space it may be the most valuable one outside of RSNA. SIIM 2026 proved that point, with the top trends from Pittsburgh illustrating the discipline’s direction at the midpoint of the radiology year. For our overview of the top trends at SIIM 2026, check out our YouTube channel or the Shows tab on our webpage.

You’ve Gone Full Circle. Now Move Forward with Modern Reporting

Posted on by Dhruv Chopra

Say goodbye to PowerScribe 360. Microsoft is sunsetting the legacy platform by ending maintenance renewals in August 2026 and full support in 2027. Conveniently, they’re urging customers to switch to their cloud-based PowerScribe One solution.

For many practices, transitioning to Microsoft’s newer solution or another similar replacement means incurring a new monthly subscription fee just to maintain the same standalone reporting workflow. 

  • Instead of paying to maintain status quo reporting, forward-thinking radiology teams are realizing this forced migration is a rare opportunity to upgrade their operating model.

Moving to a modern, AI-powered platform like CIVR by CIVIE can turn a mandatory technology shift into a better business advantage, with…

  • Cleaner, higher-quality reports: CIVR is radiology-native ASR built to do more than transcribe – it helps radiologists produce cleaner, higher-quality reports with AI-driven dictation, structured reporting support, and clinical concordance intelligence.
  • More than just dictation: Other similar solutions are fundamentally just reporting silos. CIVIE goes further by bundling advanced speech-to-text directly with your RIS, PACS, VNA, RCM, and patient workflows. The result is a unified ecosystem that eliminates vendor sprawl and integration friction.
  • Enterprise security and AI safety: HiTrust certified. SOC 2 compliant. HIPAA BAA. Clinical guardrails on every generated impression.
  • Real-time operational visibility + efficiency: Upgrading to CIVIE unlocks business insights on a granular level, allowing you to track productivity by seat, shift, or individual radiologist. Practices that switched to CIVR have reported a 40% improvement in radiologist productivity and a 60% reduction in operational expense.

PowerScribe 360 helped radiologists move from transcription toward structured reporting. Simple replacements will be familiar, but they won’t be an improvement. 

  • CIVR takes the next step by unifying speech recognition with the rest of radiology operations while still providing the ease of cloud-native architecture.

What our customers and partners are saying: Krishna Das, MD, practices at Sol Radiology in Victorville, California. He shared… 

  • “CIVIE’s AI-powered radiology dictation solution has been an absolute game changer for me. The product [has] taken my efficiency to the next level. I’m able to keep my eyes on images at all times and dictate my findings in real time.”

The Takeaway

No speech-to-text solution on the market has everything radiology, security, IT, and RCM teams need – built in natively. Stop accepting fragmented tools as the cost of doing business. Demand a platform purpose-built for radiology. Better is possible – and done right, it’s cheaper too. Ready to see what that looks like? Request a demo.

Dhruv Chopra is founder and CEO of CIVIE.

Microsoft Sunsets PowerScribe 360 Reporting Software

Posted on by Brian Casey

In a move sure to shake the fast-growing radiology reporting segment, Microsoft has begun notifying customers that it is retiring its PowerScribe 360 software and will end renewal and maintenance in August in favor of its newer cloud-based PowerScribe One reporting technology.

Microsoft began sending “end-of-life” letters to its customer base last week, confirming rumors circulating for months that it was backing away from PowerScribe 360. 

  • Microsoft is recommending that PowerScribe 360 customers transition to PowerScribe One, a newer cloud-based reporting solution available on a subscription basis rather than as an on-premises installation, as is the case with PowerScribe 360.

The company confirmed the news in an email to The Imaging Wire…

“Microsoft is retiring the on-premises product, PowerScribe 360, as part of a broader effort to ensure our customers continue to benefit from secure, future-ready solutions like PowerScribe One – which has cloud and AI capabilities at its core. This transition reflects our broader focus on providing solutions that empower healthcare organizations to meet the demands of modern care delivery securely and at scale. We are working closely with our customers to ensure a smooth transition.”

The news marks the end of the road for PowerScribe 360, which was originally developed by Nuance Communications and rose to become the dominant reporting solution for radiologists. 

  • Nuance launched PowerScribe 360 at RSNA 2010, and radiologists quickly adopted the technology, drawn to its improved speech recognition accuracy and structured reporting templates. Soon the company held 75% of the U.S. market for radiology reporting solutions.

Nuance introduced PowerScribe One in 2018 as the next generation of the software. Three years later Nuance was acquired by Microsoft and folded into Microsoft’s healthcare business. 

  • Microsoft’s strategy was to transition PowerScribe 360 users to PowerScribe One, which not only included newer tools but was also cloud-based with a regular subscription fee. This reportedly alienated many radiology customers who had already paid to have an on-premises reporting solution.  

Indeed, it only took a few years for rumors to begin circulating that Microsoft was looking to sunset PowerScribe 360 (despite many existing users), as evidenced by a recent Reddit thread on the topic. 

  • Last week’s EOL notifications inform customers that PowerScribe is being retired “as part of a broader effort to ensure our customers continue to benefit from secure, modern, and future ready solutions.” 

The letter goes on to state that PowerScribe users will need to convert to the latest version of PowerScribe One. This will require monthly payments even if they already “owned” PowerScribe 360.

  • What’s more, pricing agreements with Nuance or Microsoft will no longer be valid after the renewal date, and Microsoft will no longer provide support after the end-of-life date.

The news comes as radiology reporting is being transformed by new technology, particularly solutions driven by generative AI with large language models. 

  • Multiple startups are leveraging dissatisfaction with legacy solutions to offer reporting applications that promise more efficient workflow, and some offer better integration with image viewers and worklists to give radiologists a more unified reading experience. 

We’re also seeing a growing number of major PACS players announce new reporting solutions or outline future plans to add reporting capabilities, further complicating the market.

The Takeaway

The news that Microsoft is pulling the plug on PowerScribe 360 isn’t a surprise given the software’s age, persistent rumors of its demise, and Microsoft’s strategic focus on PowerScribe One. But it clears the field for what’s sure to be a scramble for the reporting application’s large market share.

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. 

An All-in-One Radiology Platform Built for the AI Era

Posted on by Partner Content

Early in the COVID pandemic, software engineer Shiva Suri found himself working from home alongside his radiologist mother in his parents’ basement. What he saw would lead him to build New Lantern, an AI-native platform set to disrupt the legacy radiology software market.

Suri witnessed his “world-class radiologist” mom wasting far too much time switching between five different PACS platforms and repeating the same cumbersome reporting processes with each case.

“I thought a radiologist’s job was supposed to be playing Sherlock Holmes in images,” Suri recalls, “not constantly mouse-clicking all over their PACS and tab-dictating endlessly in their reporting software.”

That imperfect workflow is an unfortunate reality for today’s radiologists, who’ve seen their processes become more tedious, while their caseloads grow in both volume and complexity.

Rads Don’t Need Another Widget

Suri’s time spent working from home became the foundation for New Lantern’s bold mission:  keep radiologists’ eyes on their images and let AI do the rest. 

  • That mission evolved over time, as Suri’s first attempt at solving radiology’s efficiency problem was a widget to automate report impressions.
  • Radiologists loved it, but… each wave of praise came with requests for more automation, leading Suri to realize that radiology’s problems weren’t going to be solved with another widget. The solution had to be fundamentally different.

The Time Is Right for an All-in-One Solution

Developing radiology’s go-to reading and reporting platform had to start with radiologists’ dream state, with their eyes on the viewer, reading image after image. 

  • It had to be based on the understanding that this dream can’t be achieved while radiologists are navigating a loosely integrated software stack.
  • The good news is, now is the perfect time to solve radiology’s software problem. The radiologist shortage and surging imaging volumes are finally driving radiology practices to look for new tech partners, and the emergence of generative AI is allowing startups to gain traction in segments that have long been dominated by entrenched legacy players. 

Enter New Lantern Curie

This perfectly timed mix of tech and market readiness set the stage for Curie, New Lantern’s all-in-one platform that combines a smart worklist, cloud PACS viewer, and AI reporter to produce AI-automated radiology report drafts.

Radiology report automation is no small task, and there’s a lot that goes into Curie’s ability to automate over 75% of non-diagnostic radiology work…

  • Streamlined Dictation – Radiologists free-dictate positive findings (no punctuation or commands), and the AI weaves them into complete sentences, generates guideline-based impressions (calculating BI-RADS, etc.), and flags errors.
  • No Tech Translations – Curie uses OCR technology to decipher technologist worksheets, applies clinical context via an LLM, and intelligently places data in the right report sections.
  • Remove Repetition – Radiologists no longer need to dictate measurements or enter prior dates. Curie handles these and a long list of other duplicative tasks for them.

The Numbers Tell the Story

All of these automations really add up, giving radiologists over 100 minutes back per shift, so they can get more done and get their lives back.

Here’s one real-world example presented at SIIM 2025 of a radiologist’s process for reading a pulmonary embolism CTA chest exam, before and after Curie…

  • Words dictated — 205 vs. 57
  • Punctuation marks & commands — 19 vs. 0
  • Fields navigated — 32 vs. 1
  • Metadata entries — 8 vs. 0 

In this example, Curie produced the same complete, accurate report with 72% fewer dictated words and 97% less navigation through dictation fields and hanging protocol changes. That’s one type of “AI taking radiologists’ jobs” that just about every radiologist would welcome.

The Takeaway

As imaging volumes surge and antiquated platforms push radiologists to the breaking point, New Lantern Curie offers them a way to work like it’s 2025 instead of 2005 – automating the fragmentation and duplication out of their days so world-class radiologists like Shiva Suri’s mom can focus on what they do best: reading images.

Learn more about New Lantern and its all-in-one approach to radiology workflow in this Imaging Wire Show video interview. 

Radiology Untethered: Sirona’s Approach to Unified Radiology

Posted on by Partner Content

Radiology stands at a breaking point. 

Hospitals and imaging practices are overwhelmed by fragmented IT systems, cumbersome technology integrations, and staff burnout. Medical imaging is the central hub through which more than 80% of healthcare data flows, but it’s become hobbled by technology that was never designed to work together.

Sirona Medical is changing the equation by rebuilding radiology software from the ground up with a cloud-based architecture that’s as simple as launching a web browser. The company hopes to free radiologists from the constraints of legacy infrastructure and redefine how diagnostic medicine operates in the cloud era, and is demonstrating its approach to radiology professionals.

The fragmented roots of radiology IT. For over two decades, diagnostic imaging has relied on three separate technological worlds that each evolved independently: PACS, reporting, and worklists…

  • PACS revolutionized image storage and viewing in the 1990s, replacing film with pixels. 
  • Reporting software brought speed through voice recognition, ending the days of transcription backlogs. 
  • Worklists organized the chaos of multi-site reading, giving radiologists a unified queue.

Yet these systems were never designed to function as one. Every integration became a brittle patchwork of custom connections. Every update risked breaking the workflow. 

The result was a “house of cards” of on-prem servers, co-located databases, and expensive maintenance contracts. Radiologists found themselves acting as system operators rather than clinical specialists, forced to navigate between screens and dictate into isolated software, losing valuable time that could be spent on patient care.

The hidden cost of separation. This disconnected infrastructure carries enormous financial, operational, and human costs. Hospitals often juggle dozens of software solutions that must be maintained, updated, and bridged by manual effort. 

A single broken link can break the entire workflow. Meanwhile, legacy vendors profit from the complexity, locking customers into long-term contracts that drain budgets and stifle innovation.

The radiologist shortage and rising imaging demand only worsen the problem. Real progress requires not another integration, but a complete re-architecture of the radiology technology stack.

Sirona’s break from the past. Enter Sirona Medical with the mission of rebuilding radiology software as a single, cloud-native platform where PACS, reporting, and worklist live together seamlessly. Delivered entirely through a Chrome browser, Sirona’s system eliminates handoffs, brittle integrations, and costly local servers.

At the platform’s foundation is RadOS, a unified data model and operating system that ingests, normalizes, and orchestrates imaging and text data across formats including DICOM, HL7, FHIR, PDFs, and clinical notes. By consolidating all this information into one consistent data model, RadOS replaces thousands of fragile interfaces with a single source of truth.

RadOS does more than unify; it enables intelligence. Built-in large language and ontology-classification models transform raw imaging and text data into structured, machine-readable insights. As a result, radiologists can work as fast as they can think, and organizations can operate profitably while improving care quality.

Powered by AWS: Streaming radiology to the world. Sirona’s platform runs on AWS, the world’s most robust cloud infrastructure. Sirona delivers massive imaging datasets to radiologists, ensuring near-instant access regardless of geography.

This design provides…

  • Low-latency performance through local caching.
  • HIPAA-compliant, military-grade security across devices and networks.
  • Global reliability backed by AWS’s resilient backbone.
  • Automatic updates via simple browser refresh.
  • Scalable storage without hardware investment.

Hospitals and imaging practices can now connect radiologists worldwide without maintaining physical servers or dealing with VPN bottlenecks.

The application layer: Intelligence built in. Sirona’s application layer sits on top of RadOS and is a seamlessly integrated environment that merges the universal worklist, diagnostic viewer, and AI-driven reporting solution. 

Key capabilities include…

  • Auto-Impressions: AI generates customizable draft impressions, fine-tuned for each reader.
  • Focus Mode: Radiologists dictate naturally while AI maps findings to structured report sections.
  • Quality Assist: A radiology-specific large language model detects speech-to-text errors and clinical inconsistencies in real time.
  • AI Orchestration: Third-party AI tools plug directly into reporting, no brittle middleware required.
  • Priors Summary and Auto-Priors: AI retrieves and summarizes prior exams automatically, accelerating interpretation and ensuring continuity of care.

These features turn the radiology report from a static document into a dynamic, intelligent artifact that supports decision-making across the care continuum.

The time is now for cloud-native PACS, and for the unified approach to radiology viewing, reporting, and worklist that Sirona Medical has pioneered. Radiology’s next era has arrived: one PACS, one worklist, one reporter – and it’s a reality right now.

Learn more about Sirona Medical’s approach to radiology software by booking a demo today.

AI in Radiology: Old Problems, New Tech

Posted on by Partner Content

By Mo Abdolell, CEO, Densitas

Radiology has seen this movie before. Big promises (efficiency, accuracy, burnout relief). Big anxieties (ROI, workflow chaos, pressure to “keep up”). The question isn’t whether AI is powerful. It’s whether we’ve learned how to deploy new technology without repeating the pain of PACS migrations and the EHR era.

The Myth of the Perfect Rollout. Health technology assessment (HTA) sounds great in theory – rigorous, comprehensive, evidence-first. In practice, few organizations have the time, talent, or budget to execute it at scale. 

  • Remember EHRs: adoption happened because policy and money forced it, not because the playbook was tidy. Healthcare’s default pattern is to adopt, then evolve – messy, market-driven, and iterative. Waiting for perfect plans is how you get left behind.

Are AI’s Problems really new?

  • Black box déjà vu. Radiology has long trusted complex, opaque systems (reconstruction algorithms, vendor-specific pipelines). What mattered – and still matters – is validated performance and dependable outputs, not full internal transparency.
  • Model drift ≈ old friends. We’ve always recalibrated clinical tools as populations and scanners change. Monitoring and revalidation are known problems, not alien ones.

What’s Different This Time? Unlike the top-down EHR mandate, AI is largely market-driven. That gives providers agency. 

  • AI solutions must save time, improve outcomes, or avoid costs – not just publish a ROC curve. They must show operational value inside the native radiology workflow.

Fortunately, there are ways to adopt AI and then evolve your processes to make it work…

  • Workflow or bust. Demand in-viewer evidence objects, one-click report insertion, and EHR write-back. If AI adds steps, it subtracts value.
  • Start narrow, scale deliberately. Pick high-volume, high-friction tasks. Prove value in weeks, not years. Expand only when the operational signal is undeniable.
  • Measure what matters. Track operational metrics like seconds saved and coverage (e.g. eligible cases processed before dictation), reliability (e.g. results present before finalization, fail-open behavior), and user friction like context-switching rate and time-to-evidence.
  • Monitor. Stand up organization and site-level performance checks. Treat AI like equipment – scheduled, observed, and maintained.
  • Invest in long-term value. Favor standards, vendor-agnostic interoperability, clear telemetry, and transparent pricing.

The Takeaway

AI’s success in radiology won’t be defined by elegance of algorithms but by pragmatism of deployment. This will be an evolution – hands-on, incremental, sometimes messy. The difference now is that radiology can drive. Make the technology serve the service line – not the other way around.

Target the toughest workflows. Adapt and evolve with Densitas Breast Imaging AI Suite.

AI First Drafts: A New Dawn for Radiology Reporting

Posted on by Partner Content

For radiologists – the medical detectives who find clues in our medical images – the daily grind can feel like a “death by a thousand cuts.” Much of their time is spent not on diagnosis, but on tedious reporting. 

Now, a new generation of artificial intelligence is stepping in to serve as a high-tech scribe, automating the drudgery.

  • This AI tackles reporting, the most time-consuming part of radiologists’ workflow.

AI-enabled radiology reporting makes transcribing data from technologist worksheets a thing of the past, using Optical Character Recognition (OCR) to decipher everything, even what looks like “chicken scratch handwriting.” Then…

  • A large language model (LLM) applies clinical context to ensure it understands the meaning.
  • It intelligently injects that data into the correct sections of the radiologist’s personal report template.
  • Finally, it performs its own “inference,” like calculating a TI-RADS score and dropping it right into the impression.

Modern AI also learns from a radiologist’s actions, providing a hands-free way to build a report, with features such as…

Smart Measurements: When a lesion is measured, the AI recognizes the location and automatically adds the data and comparisons to prior scans into the report.

Automated Prior Population: Instead of struggling with speech-to-text, the AI notices when a prior study is opened for comparison and automatically populates that exam’s date.

Streamlined Expert Findings: A radiologist can simply state positive findings, and the AI acts as both writer and editor. 

AI-enabled radiology reporting weaves dictated phrases into complete sentences, generates an impression based on clinical guidelines like BI-RADS, and serves as a vigilant proofreader, flagging errors like laterality mistakes or semantic impossibilities. 

As AI technology matures, the software itself is becoming easier to build. The true differentiator is the team behind it. 

  • For radiologists evaluating these new reporting tools, it’s critical to look for teams that are “AI native” – built from the ground up with AI at their core. 

Companies founded on these principles, such as New Lantern, are pioneering these all-in-one radiology reporting solutions, treating the challenge not as a problem to be fixed with another widget, but as an opportunity to build one complete, intelligent platform. 

The Takeaway 

The evolution in AI-enabled radiology reporting isn’t about replacing radiologists; it’s a tool to augment their skills. Radiologists who harness AI to create reports faster will significantly outpace those who do not, allowing them to return their full focus to the art of diagnosis.

RadGPT Simplifies Radiology Reports for Patients

Posted on by Brian Casey

When it comes to informing patients of their imaging results, radiologists are caught between a rock and hard place. A new study in JACR shows how generative AI can help by drafting patient-friendly reports that are simple but accurate.

Patients must be informed immediately of their medical results according to a 2021 final rule under the 21st Century Cures Act that prevents medical information blocking. 

  • And while the technology exists to do that through tools like email and electronic patient portals, rapid notification can create confusion because the language physicians use to communicate with each other isn’t easily understood by anyone outside medicine.

Sure, radiology reports could be rewritten manually for patients, who typically read at about the eighth-grade level.

  • But given today’s workforce shortages, who’s going to do that?

Generative AI and large language models offer a solution. In the new JACR paper, researchers from Stanford University led by senior author Curtis Langlotz, MD, PhD, described their development of RadGPT, an LLM designed to improve patient communication.

  • To develop RadGPT, researchers started with OpenAI’s GPT-4 model and the RadGraph concept extraction tool to create an LLM that analyzes patient radiology reports and generates concept explanations and question-and-answer pairs.

How well did RadGPT work? The researchers tested it on 30 radiology reports generated at Stanford from 2012 to 2020, including different modalities and clinical applications. 

  • The LLM was asked to generate reports at a fifth-grade reading level (the level recommended by the Joint Commission for patient-facing healthcare materials).

Five radiology-trained physicians then rated the quality of RadGPT’s responses, finding …

  • The average rating of RadGPT-generated concept explanations was 4.8 out of 5.
  • 95% of concept explanations had an average rating of 4 or higher.
  • 50% of concept explanations were rated 5, the highest possible rating.
  • Questions and answers generated by RadGPT were also rated highly, with an average rating of 3.0 on a three-point scale..

The Stanford researchers told The Imaging Wire that their goal is to make RadGPT more widely available as part of a prospective evaluation with real patients.

  • They are also developing a user-friendly interface in which patients can receive hyperlinked radiology reports.

The Takeaway

RadGPT and solutions like it fill a desperate need for tools that can save time for radiologists while helping patients better understand their reports and get more engaged in their care. The next step is to get technology like this into the hands of practicing radiologists.

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