Tag: medical devices

Top 10 Radiology Stories of 2023

Posted on by Brian Casey

What were the top 10 radiology stories of 2023 in The Imaging Wire? From worklist cherry-picking to a wearable breast ultrasound scanner – and with lots of AI in between – this year’s top 10 list demonstrates the fascinating new developments going on every day in medical imaging.

1. The Perils of Worklist Cherry-Picking

If you’re a radiologist, chances are at some point in your career you’ve cherry-picked the worklist. But picking easy, high-RVU imaging studies to read before your colleagues isn’t just rude – it’s bad for patients and bad for healthcare. That’s according to a study in Journal of Operations Management that analyzed radiology cherry-picking in the context of operational workflow and efficiency. 

2. Tipping Point for Breast AI? 

Have we reached a tipping point when it comes to AI for breast screening? A study in Radiology demonstrated the value of AI for interpreting screening mammograms. 

3. Autonomous AI for Medical Imaging is Here. Should We Embrace It? 

What is autonomous artificial intelligence, and is radiology ready for this new technology? In this paper, we explored one of the most exciting autonomous AI applications, ChestLink from Oxipit. 

4. Undermining the Argument for NPPs

If you think you’ve been seeing more non-physician practitioners (NPPs) reading medical imaging exams, you’re not alone. A study in Current Problems in Diagnostic Radiology found that the rate of NPP interpretations went up almost 27% over four years. 

5. Reimbursement Drives AI Adoption

It’s no secret that insurance reimbursement drives adoption of new medical technology. But an analysis in NEJM AI showed exactly how reimbursement is affecting the diffusion into clinical practice of perhaps the newest medical technology – artificial intelligence. 

6. Radiation and Cancer Risk

New research on the cancer risk of low-dose ionizing radiation could have disturbing implications for those who are exposed to radiation on the job – including medical professionals. In a study in BMJ, researchers found that nuclear workers exposed to occupational levels of radiation had a cancer mortality risk that was higher than previously estimated.

7. Cardiac Imaging in 2040

What will cardiac imaging look like in 2040? It will be more automated and preventive, and CT will continue to play a major – and growing – role. That’s according to an April 11 article in Radiology in which Dr. David Bluemke and Dr. João Lima looked into the future and offered a top 10 list of major developments in cardiovascular imaging in 2040.

8. When AI Goes Wrong

What impact do incorrect AI results have on radiologist performance? That question was the focus of a study in European Radiology in which radiologists who received incorrect AI results were more likely to make wrong decisions on patient follow-up – even though they would have been correct without AI’s help.

9. The 35 Best Radiology Newsletters, Blogs, and Websites to Follow

We dedicated March 6th’s top story to the people and publications that we rely on to find the most interesting medical imaging stories. Assuming that you already subscribe to The Imaging Wire, these are the 35 other newsletters, websites, blogs, and accounts to follow if you want to know what’s happening in radiology.

10. Breast Ultrasound Gets Wearable

Wearable devices are all the rage in personal fitness – could wearable breast ultrasound be next? MIT researchers have developed a patch-sized wearable breast ultrasound device that’s small enough to be incorporated into a bra for early cancer detection. They described their work in a paper in Science Advances.

The Takeaway

The Imaging Wire’s list of top 10 articles for 2023 shows that, while artificial intelligence featured prominently during the year, there was much more to radiology than just AI. We hope you enjoyed reading our content this year as much as we enjoyed bringing it to you.

Lunit’s Deal for Volpara and AI Consolidation

Posted on by Brian Casey

Is the long-awaited consolidation of the healthcare AI sector gaining steam? In a deal valued at close to $200M, South Korean AI developer Lunit announced a bid to acquire Volpara Health, a developer of software for calculating breast density and cancer risk. 

At first glance, the alliance seems to be a match made in heaven. Lunit is a well-regarded AI developer that has seen impressive results in clinical trials of its Insight family of algorithms for indications ranging from mammography to chest imaging. 

  • Most recently, Lunit received FDA clearance for its Insight DBT software, marking its entry into the US breast screening market, and it also raised $150M in a public stock offering. 

Volpara has a long pedigree as a developer of breast imaging software, although it has shied away from image analysis applications to instead focus on breast center operations and risk assessment, in particular by calculating breast density. 

  • Thus, combining Lunit’s concentration in image analysis with Volpara’s focus on operations and risk assessment enables the combined company to offer a wider breadth of products to breast centers.

Lunit will also be able to take advantage of the marketing and sales structure that Volpara has built in the US mammography sector (97% of Volpara’s sales come from the US, where it has an installed base of 2k sites). Volpara expects 2024 sales of $30M and is cash-flow positive.

The question is whether the acquisition is a sign of things to come in the AI market. 

  • As commercial AI sales have been slow to develop, AI firms have largely funded their operations through venture capital firms – which are notoriously impatient in their quest for returns.

In fact, observers at the recent RSNA 2023 meeting noted that there were very few new start-up entrants into the AI space, and many AI vendors had smaller booths. 

  • And previous research has documented a slowdown in VC funding for AI developers that is prompting start-up firms to seek partners to provide more comprehensive offerings while also focusing on developing a road to profitability. 

The Takeaway

It’s not clear yet whether the Lunit/Volpara deal is a one-off combination or the start of a renewed consolidation trend in healthcare AI. Regardless of what happens, this alliance unites two of the stronger players in the field and has exciting potential for the years to come. 

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.

Unpacking the Biden Administration’s New AI Order

Posted on by Brian Casey

It seems like watershed moments in AI are happening on a weekly basis now. This time, the big news is the Biden Administration’s sweeping executive order that directs federal regulation of AI across multiple industries – including healthcare. 

The order comes as AI is becoming a clinical reality for many applications. 

  • The number of AI algorithms cleared by the FDA has been surging, and clinicians – particularly radiologists – are getting access to new tools on an almost daily basis.

But AI’s rapid growth – and in particular the rise of generative AI technologies like ChatGPT – have raised questions about its future impact on patient care and whether the FDA’s existing regulatory structure is suitable for such a new technology. 

The executive order appears to be an effort to get ahead of these trends. When it comes to healthcare, its major elements are summarized in a succinct analysis of the plan by Health Law Advisor. In short, the order: 

  • Calls on HHS to work with the VA and Department of Defense to create an HHS task force on AI within 90 days
  • Requires the task force to develop a strategic plan within a year that could include regulatory action regarding the deployment and use of AI for applications such as healthcare delivery, research, and drug and device safety
  • Orders HHS to develop a strategy within 180 days to determine if AI-enabled technologies in healthcare “maintain appropriate levels of quality” – basically, a review of the FDA’s authorization process
  • Requires HHS to set up an AI safety program within a year, in conjunction with patient safety organizations
  • Tells HHS to develop a strategy for regulating AI in drug development

Most analysts are viewing the executive order as the Biden Administration’s attempt to manage both risk and opportunity. 

  • The risk is that AI developers lose control of the technology, with consequences such as patients potentially harmed by inaccurate AI. The opportunity is for the US to become a leader in AI development by developing a long-term AI strategy. 

The Takeaway

The question is whether an industry that’s as fast-moving as AI – with headlines changing by the week – will lend itself to the sort of centralized long-term planning envisioned in the Biden Administration’s executive order. Time will tell.

Predicting the Future of Radiology AI

Posted on by Brian Casey

Making predictions is a messy business (just ask Geoffrey Hinton). So we’re always appreciative whenever key opinion leaders stick their necks out to offer thoughts on where radiology is headed and the major trends that will shape the specialty’s future. 

Two of radiology’s top thought leaders on AI and imaging informatics – Curtis Langlotz, MD, PhD, and Paul Chang, MD – gaze into the crystal ball in two articles published this week in Radiology as part of the journal’s centennial celebration. 

Langlotz offers 10 predictions on radiology AI’s future, briefly summarized below:

  • Radiology will continue its leadership position when it comes to AI adoption in medicine, as evidenced by its dominance of FDA marketing authorizations
  • Virtual assistants will help radiologists draft reports – and reduce burnout
  • Radiology workstations will become cloud-based cockpits that seamlessly unify image display, reporting, and AI
  • Large language models like ChatGPT will help patients better understand their radiology reports
  • The FDA will reform its regulation of AI to be more flexible and speed AI authorizations (see our article in The Wire below)
  • Large databases like the Medical Imaging and Data Resource Center (MIDRC) will spur data sharing and, in turn, more rapid AI development

Langlotz’s predictions are echoed by Chang’s accompanying article in Radiology in which he predicts the future of imaging informatics in the coming age. Like Langlotz, Chang sees the new array of AI-enabled tools as beneficial agents that will help radiologists manage growing workloads through dashboards, enhanced radiology reports, and workflow automation. 

The Takeaway

This week’s articles are required reading for anyone following the meteoric growth of AI in radiology. Far from Hinton’s dystopian view of a world without radiologists, Langlotz and Chang predict a future in which AI and IT technologies assist radiologists to do their jobs better and with less stress. We know which vision we prefer.

FDA Data Show AI Approval Boom

Posted on by Brian Casey

In the previous issue of The Imaging Wire, we discovered how venture capital investment in AI developers is fueling rapid growth in new AI applications for radiologists (despite a slowdown this year). 

This trend was underscored late last week with new data from the FDA showing strong growth in the number of regulatory authorizations of AI and machine learning-enabled devices in calendar 2023 compared to the year before. The findings show:

  • A resurgence of AI/ML authorizations this year, with over 30% growth compared to 14% in 2022 and 15% in 2021 – The last time authorizations grew this fast was in 2020 (+39%)
  • The FDA authorized 171 AI/ML-enabled devices in the past year. Of the total, 155 had final decision dates between August 1, 2022 to July 30, 2023, while 16 were reclassifications from prior periods 
  • Devices intended for radiology made up 79% of the total (122/155), an impressive number but down slightly compared to 87% in 2022 
  • Other medical specialities include cardiology (9%), neurology (5%), and gastroenterology/urology (4%)

One interesting wrinkle in the report was the fact that despite all the buzz around large language models for generative AI, the FDA has yet to authorize a device that uses generative AI or that is powered by LLMs. 

The Takeaway

The FDA’s new report confirms that radiology AI shows no sign of slowing down, despite a drop in AI investment this year. 

The data also offer perspective on a JACR report last week predicting that by 2035 radiology could be seeing 350 new AI/ML product approvals for the year. Product approvals would only have to grow at about a 10% annual rate to hit that number – a figure that seems perfectly achievable given the new FDA report.

POCUS Cuts DVT Stays

Posted on by Brian Casey

Using POCUS in the emergency department (ED) to scan patients with suspected deep vein thrombosis (DVT) cut their length of stay in the ED in half. 

Reducing hospital length of stay is one of the holy grails of healthcare quality improvement. 

  • It’s not only more expensive to keep patients in the hospital longer, but it can expose them to morbidities like hospital-acquired infections.

Patients admitted with suspected DVT often receive ultrasound scans performed by radiologists or sonographers to determine whether the blood clot is at risk of breaking off – a possibly fatal result. 

  • But this requires a referral to the radiology department. What if emergency physicians performed the scans themselves with POCUS?

To answer this question, researchers at this week’s European Emergency Medicine Conference presented results from a study of 93 patients at two hospitals in Finland.

  • From October 2017 to October 2019, patients presenting at the ED received POCUS scans from emergency doctors trained on the devices. 

Results were compared to 135 control patients who got usual care and were sent directly to radiology departments for ultrasound. 

  • Researchers found that POCUS reduced ED length of stay from 4.5 hours to 2.3 hours, a drop of 52%.

Researchers described the findings as “convincing,” especially as they occurred at two different facilities. The results also answer a recent study that found POCUS only affected length of stay when performed on the night shift. 

The Takeaway
Radiology might not be so happy to see patient referrals diverted from their department, but the results are yet another feather in the cap for POCUS, which continues to show that – when in the right hands – it can have a big impact on healthcare quality.

Breast Ultrasound Gets Wearable

Posted on by Brian Casey

Wearable devices are all the rage in personal fitness – could wearable breast ultrasound be next? MIT researchers have developed a patch-sized wearable breast ultrasound device that’s small enough to be incorporated into a bra for early cancer detection. They described their work in a new paper in Science Advances.

This isn’t the first use of wearable ultrasound. In fact, earlier this year UCSD researchers revealed their work on a wearable cardiac ultrasound device that obtains real-time data on cardiac function. 

The MIT team’s concept expands the idea into cancer detection. They took advantage of previous work on conformable piezoelectric ultrasound transducer materials to develop cUSBr-Patch, a one-dimensional phased-array probe integrated into a honeycomb-shaped patch that can be inserted into a soft fabric bra. 

The array covers the entire breast surface and can acquire images from multiple angles and views using 64 elements at a 7MHz frequency. The honeycomb design means that the array can be rotated and moved into different imaging positions, and the bra can even be reversed to acquire images from the other breast. 

The researchers tested cUSBr-Patch on phantoms and a human subject, and compared it to a conventional ultrasound scanner. They found that cUSBr-Patch:

  • Had a field of view up to 100mm wide and an imaging depth up to 80mm
  • Achieved resolution comparable to conventional ultrasound
  • Detected cysts as small as 30mm in the human volunteer, a 71-year-old woman with a history of breast cysts
  • The same cysts were detected with the array in different positions, an important capability for long-term monitoring

The MIT researchers believe that wearable breast ultrasound could detect early-stage breast cancer, in cases such as high-risk people in between routine screening mammograms. 

The researchers ultimately hope to develop a version of the device that’s about the size of a smartphone (right now the array has to be hooked up to a conventional ultrasound scanner to view images). They also want to investigate the use of AI to analyze images.

The Takeaway

It’s still early days for wearable breast ultrasound, but the new results are an exciting development that hints of future advances to come. Wearable breast ultrasound could even have an advantage over other wearable use cases like cardiac monitoring, as it doesn’t require continuous imaging during the user’s activities. Stay tuned.

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