Tag: RSNA

AI Powers Opportunistic Screening

Posted on by Brian Casey

The growing power of AI is opening up new possibilities for opportunistic screening – the detection of pathology using data acquired for other clinical indications. The potential of CT-based opportunistic screening – and AI’s role in its growth – was explored in a session at RSNA 2023.

What’s so interesting about opportunistic screening with CT? 

  • As one of imaging’s most widely used modalities, CT scans are already being acquired for many clinical indications, collecting body composition data on muscle, fat, and bone that can be biomarkers for hidden pathology. 

What’s more, AI-based tools are replacing many of the onerous manual measurement tasks that previously required radiologist involvement. There are four primary biomarkers for opportunistic screening, which are typically related to several major pathologies, said Perry Pickhardt, MD, of the University of Wisconsin-Madison, who led off the RSNA session:

  • Skeletal muscle density (sarcopenia)
  • Hard calcified plaque, either coronary or aortic (cardiovascular risk)
  • Visceral fat (cardiovascular risk)
  • Bone mineral density (osteoporosis and fractures) 

But what about the economics of opportunistic screening? 

  • A recent study in Abdominal Radiology found that in a hypothetical cohort of 55-year-old men and women, AI-assisted opportunistic screening for cardiovascular disease, osteoporosis, and sarcopenia was more cost-effective compared to both “no-treatment” and “statins for all” strategies – even assuming a $250/scan charge for use of AI.

But there are barriers to opportunistic screening, despite its potential. In a follow-up talk, Arun Krishnaraj, MD, of UVA Health in Virginia said he believes fully automated AI algorithms are needed to avoid putting the burden on radiologists. 

And the regulatory environment for AI tools is complex and must be navigated, said Bernardo Bizzo, MD, PhD, of Mass General Brigham.

Ready to take the plunge? The steps for setting up a screening program using AI were described in another talk by John Garrett, PhD, Pickhardt’s colleague at UW-Madison. This includes: 

  • Normalizing your data for AI tools
  • Identifying the anatomical landmarks you want to focus on
  • Automatically segmenting areas of interest
  • Making the biomarker measurements
  • Plugging your data into AI models to predict outcomes and risk-stratify patients

The Takeaway

Opportunistic screening has the potential to flip the script in the debate over radiology utilization, making imaging exams more cost-effective while detecting additional pathology and paving the way to more personalized medicine. With AI’s help, radiologists have the opportunity to place themselves at the center of modern healthcare. 

AI’s Incremental Revolution

Posted on by Brian Casey

So AI dominated the discussion at last week’s RSNA 2023 meeting. But does that mean it’s finally on the path to widespread clinical use? 

Maybe not so much. For a technology that’s supposed to have a revolutionary impact on medicine, AI is taking a frustratingly long time to arrive. 

Indeed, there was plenty of skepticism about AI in the halls of McCormick Place last week. (For two interesting looks at AI at RSNA 2023, also see Hugh Harvey, MD’s list of takeaways in a post on X/Twitter and Herman Oosterwijk’s post on LinkedIn.) 

But as one executive we talked to pointed out, AI’s advance to routine clinical use in radiology is likely to be more incremental than all at once. 

  • And from that perspective, last week’s RSNA meeting was undoubtedly positive for AI. Scientific sessions were full of talks on practical clinical applications of AI, from breast AI to CT lung screening. 

Researchers also discussed the use of AI apart from image interpretation, with generative AI and large language models taking on tasks from answering patient questions about their reports to helping radiologists with dictation.

It’s fine to be a skeptic (especially when it comes to things you hear at RSNA), but for perspective look at many of the past arguments casting doubt on AI: 

  • AI algorithms don’t have FDA clearance (the FDA authorized 171 algorithms in just the past year)
  • You can’t get paid for using AI clinically (16 algorithms have CPT codes, with more on the way) 
  • There isn’t enough clinical evidence backing the use of AI (tell that to the authors of MASAI, PERFORMS, and a number of other recent studies with positive findings)
  • The AI market is overcrowded with companies and ripe for consolidation (what exciting new growth market isn’t?)

The Takeaway

Sure, it’s taking longer than expected for AI to take hold in radiology. But last week’s conference showed that AI’s incremental revolution is not only advancing but expanding in ways no one expected when IBM Watson was unveiled to an RSNA audience a mere 6-7 years ago. One can only imagine what the field will look like at RSNA 2030.

Looking for more coverage of RSNA 2023? Be sure to check out our videos from the technical exhibit floor, which you can find on our new Shows page.

Welcome to RSNA 2023

Posted on by Brian Casey

It’s off to the races at RSNA 2023 as radiology’s showcase conference kicked off on Sunday. 

“Leading Through Change” is the theme of this year’s meeting, and it’s an appropriate slogan for a specialty that seems on the cusp of disruption with the growing use of AI, deep learning, and other tools. 

  • AI is being featured prominently in scientific presentations and vendor exhibits in McCormick Place, with a particular focus on whether large language models like ChatGPT can find practical application in radiology. Early research is promising but still inconclusive.

Another major focus at RSNA 2023 has been lung cancer screening, with Sunday afternoon sessions investigating how screening can be expanded: 

  • Researchers mined a database of 32k women who got screening mammography to find eligible candidates for lung screening, finding 5% who met screening criteria. 
  • Using the USPTSF’s 2021 guideline revision to find screening candidates led to shorter smoking histories (42 vs. 29 pack-years) and slightly more women being eligible (48% vs. 46%). 
  • ChatGPT gave more correct answers than Google Bard to non-expert questions on lung screening (71% vs. 52%).
  • ChatGPT, GPT-4, and Bard needed multiple iterations to produce reports readable by patients. 

AI is also proving its value for selecting screening candidates and identifying lung pathology: 

  • An AI algorithm analyzed chest X-rays to determine whether an individual would benefit from CT lung cancer screening – even if they don’t smoke. In 17.4k patients, the model classified 28% as high risk, 2.9% of whom were later diagnosed with lung cancer, a higher level than the 1.3% six-year threshold at which guidelines recommend CT lung screening.
  • A deep learning algorithm analyzed chest X-rays in a cohort of 10k patients to predict who would develop type 2 diabetes, turning in better accuracy than a model that only looked at clinical factors like age, BMI and HbA1c levels (AUCs:  0.84 vs. 0.79). 

Looking for more coverage of RSNA 2023? Be sure to check out our videos from the technical exhibit floor, which you can find on our new Shows page. 

The Takeaway
The RSNA has always been known as the Super Bowl of radiology, and this year’s meeting is off to a great start. Be sure to check back on our Twitter/X, LinkedIn, and YouTube pages for more coverage of this week’s events in Chicago.

Vendors Enter RSNA on Q3 Roll

Posted on by Brian Casey

As RSNA 2023 approaches, medical imaging vendors appear to be on a roll when it comes to financial results. In the weeks leading up to the meeting, companies have posted numbers that for the most part are strongly positive and appear to be leaving the bad old days of the COVID-19 pandemic behind.

Agfa – Between Agfa’s two imaging divisions, healthcare IT continues to outperform the radiology solutions business. Healthcare IT saw growth in revenue (3.3% to $67M) and EBITDA (44.3% to $6.4M), but revenue declined at radiology solutions (-5.7% to $127M) as did EBITDA (-21% to $10M). 

Canon – Canon Medical Systems saw firm revenues in Japan and Europe, which propelled the business unit to higher revenues (5% to $913M) while income before taxes edged up (0.3% to $46M). 

Fujifilm – Revenues tapered off slightly in Fujifilm’s healthcare business at constant currency rates (-1.9% to $1.66B) as a 12.4% decline in its contract manufacturing business offset 1.7% growth in medical systems. Operating income in healthcare slipped due to a one-time benefit in the year-ago quarter (-6.5% to $217M).

GE HealthCare – Revenue growth in its molecular imaging and CT businesses helped propel GE HealthCare’s revenue growth (5.4% to $4.82B), assisted by 13% growth in pharmaceutical diagnostics and a 9% increase in patient care solutions. Net income was lower (-23% to $375M). 

Guerbet – Strong revenues for the third quarter in Asia (+15%) and stability in the EMEA region (0.6%) helped counter a decline in the Americas (-5.2%), enabling Guerbet to turn in overall quarterly revenue growth at constant exchange rates (2.3% to $212M). The company expects sales of its Elucirem MRI contrast agent to ramp up in the fourth quarter. 

Hologic – The semiconductor shortage that had impacted Hologic in previous quarters eased, leading to a sharp jump in revenues in the company’s breast health business (27% to $353M). The rebound didn’t extend to Hologic’s overall net income as its net margin narrowed (-24% to $91M). 

Konica Minolta – A decline in sales of X-ray systems to hospitals in its core market of Japan and a slower US hospital market produced lower revenues in Konica Minolta’s healthcare division (-5% to $238M), and the business posted an operating loss (-$5.5M).

Philips – Philips rebounded in the most recent quarter, with revenues in its diagnosis and treatment division rising sharply after currency conversion thanks to double-digit growth in all businesses (14% to $2.39B). Operating income doubled (to $272M). 

RadNet – RadNet saw a double-digit jump in revenues (15% to $402M) while net income leaped ($17.5M vs. $668k). Revenue jumped 221% in the company’s AI segment, which made progress narrowing its EBITDA loss (-$2.5M vs. -$4.5M) on higher consumer adoption of its Enhanced Breast Cancer Detection offering.  

Siemens Healthineers – Siemens Healthineers closed its financial year with “outstanding” 8.3% revenue growth at constant exchange rates, including double-digit growth in its imaging business (11% to $3.62B) while adjusted EBIT edged up (2% to $812M). Its Varian radiation therapy business saw a strong recovery in revenue (30% to $1.1B) and adjusted EBIT (90% to $207M).

Varex – Growth in Varex’s industrial X-ray imaging business propelled the company to higher overall revenues even as revenues in its medical business fell (-9.8% to $164M). The medical division’s gross profit also slipped (-7% to $53M).

The Takeaway

Not every company was a winner in this last round of quarterly earnings, but at least the macroeconomic headwinds of the COVID-19 pandemic are fading. The fourth calendar quarter is typically radiology’s strongest period due to the impact of the RSNA conference on equipment purchasing, so let’s hope the momentum continues.

Canon’s Meaningful RSNA Innovations

Posted on by Jake Fishman

After taking a virtual approach to RSNA last year, Canon Medical Systems made its presence felt at RSNA 2022, unveiling an interactive “digital patient journey” booth that featured an interesting mix of new products and business model innovations. 

SP MRIs – Canon unveiled SP-suffix configurations of its Vantage Orian and Galan MRIs (1.5T & 3T), adding new features intended to enhance MRI team efficiency (tablet UX interface, intelligent Ceiling Camera), while making a number of its image quality and productivity-focused solutions standard (AiCE DLR, Fast 3D acceleration, ForeSee View automation).

Mobile XR – The new Mobirex i9 brings a rare update to Canon’s U.S. mobile X-ray lineup, launching with an emphasis on its small size, mobile/flexible design, and its use of Canon’s next-gen CXDI-Elite wireless detectors.

Mobile MI – In a different type of mobile expansion, Canon launched a mobile version of its Cartesion Prime Digital PET/CT, which seems to be a good fit for mobile coaches given its Air Cooled technology and small footprint (fits in 3.15×7.1 meters).

Future Proof Packages – Canon rolled out its interesting new Non-Obsolescence Program, which allows CT and MRI customers to purchase an up-front package that gives them access to all future hardware, software, and service options as they become available. The program covers five years of upgrades, and is priced well below what users would pay if they ordered each item individually.

Glassbeam Clinsights – Canon’s Inclusive Analytics Suite added Glassbeam Clinsights Utilization Analytics, which analyzes DICOM and HL7 data to help Canon service customers understand imaging utilization and productivity levels across their fleets (multi-modalities and vendors).

The Imaging Wire’s RSNA 2022 Reflections

Posted on by Jake Fishman

RSNA 2022 is officially a wrap. We hope you had a blast if you made it, and had a great week if you stayed home. We also hope you enjoy our recap of radiology’s most important event in at least three years.

Crowds & Conversations – RSNA’s attendance and overall energy continued to trend upward, as most of the 31k people on-site were super engaged and truly excited to be there. Although attendance was still well below RSNA 2019 (~49k on-site), it was a big jump from last year (~23k on-site), and infinitely better than 2020’s virtual RSNA.

Much Rad Love – If you had “I’m not a radiologist but…” on your RSNA bingo card you’d be in a good spot, because the exhibit hall was full of non-rads talking about how to help radiology teams be more effective and more satisfied.

Focus on Productivity – Perhaps due to all that vendor empathy, just about every new product (hardware and software) focused on eliminating steps / clicks / interruptions, improving workflow integration, alleviating burnout and labor challenges, and better matching diagnostic processes.

Getting Cloudy – There’s no debate that imaging’s shift to the cloud was one of RSNA’s top trends, as informatics vendors continued to strengthen their cloud capabilities and expand their list of cloud-based customers (especially if you include hybrid). There were, however, plenty of debates about who’s cloud tech is truly native and who’s aren’t.

AI’s Two Sides – It seems like many folks are still in AI’s “trough of disillusionment,” as conversations often drifted towards problems with AI’s performance, use cases, funding climate, and provider ROI. However, AI adoption has never been wider, AI products have never worked better, and there are plenty of AI trends to be excited about…

  • AI is becoming less narrow
  • AI workflow integration keeps getting better
  • More radiologists are interested in AI
  • There’s solid traction with operational and efficiency AI
  • We’re not talking about AI replacing radiologists (as much)

Modality Progress – Although there were only a handful of completely new scanners at RSNA, the major OEMs showed continued advancements in MR (image quality, low-helium, low-field, reconstruction, coils) and CT (spectral, photon-counting, upgradability), while nearly all scanners took big strides in operator efficiency.

The Takeaway

Radiology faces plenty of challenges, but it’s populated by some of the smartest people in medicine/medtech who are working hard to solve those challenges. Hats off to the RSNA team for getting all the smart people together every year to push those solutions forward.

RSNA 2021 Reflections

Posted on by Jake Fishman

The first in-person RSNA since COVID is officially a wrap. Hope you had a blast if you made it to Chicago and a productive week if you stayed home. We also hope you enjoy The Imaging Wire’s big takeaways from what might have been both the most special and most subdued RSNA ever.

Crowds & Conversations – We were already expecting 50% lower attendance than RSNA 2019, but the exhibit hall and cab lines looked more like 70% below 2019’s crowds (even less on Sunday & Wednesday). That said, most of the stronger companies had steady booth traffic and nearly every exhibitor emphasized that the attendees who did show up were ready to have high-quality conversations.

Focus on Productivity – Just about every product message at RSNA focused on productivity and efficiency, often with greater emphasis than clinical effectiveness. The modality-based efficiency enhancements seemed to be the most impactful, which is good news for technologist bandwidth and patient throughput, but might be bad news for rad burnout unless informatics/AI efficiency can catch up (it doesn’t seem like that happened this year).

Modality Milestones – The major OEMs did a good job making modalities cool again, debuting milestone innovations across both their MR (low-helium, low-field, reconstruction, coils) and CT (photon-counting, spectral, upgradability) lineups. We also saw the latest scanners take big strides in operator efficiency and patient experience. There weren’t many breakthroughs with X-ray or ultrasound, and most point-of-care ultrasound OEMs stayed home (rads aren’t their market anyway), but attendees seemed okay with that.

AI Showcase – The RSNA AI Showcase had solid traffic and high energy (especially on Mon & Tues), helped by continued AI buzz and the fact that RSNA finally let AI vendors out of the basement. The AI Showcase highlighted many of the trends we’ve been seeing all year, including larger vendors transitioning to AI platform strategies, an increased focus on workflow integration and care coordination, and a greater emphasis on radiologist efficiency. There were also far fewer brand-new AI tools than previous years, as many vendors focused on improving their current products and/or expanding their portfolio via partnerships. 

PACS Cloud Focus – PACS vendors continued to place a major emphasis on their respective cloud advantages, and there was a widespread consensus that cloud is on every imaging IT roadmap. The PACS vendors seemed to talk less about multi-ology enterprise imaging than previous years, and expanding EI beyond radiology/cardiology still seemed pretty futuristic for most players. It was also quite clear that most of the PACS players’ AI marketplaces/platforms haven’t been as prioritized as earlier announcements might have suggested.

Best RSNA Since… 2019 – We’ve heard some folks saying this was the “best RSNA ever” because it was easy to get around and it was great to see everyone, but those seem more like pandemic silver linings than “best ever” qualifications. Still, the imaging industry made the most of RSNA 2021, and everyone seemed truly happy to be together again after two long years of working from home. As long as COVID cooperates, we should be set up for an excellent RSNA 2022.

Get every issue of The Imaging Wire, delivered right to your inbox.

You might also like..

Select All

You're signed up!

It's great to have you as a reader. Check your inbox for a welcome email.

-- The Imaging Wire team

You're all set!