Tag: medical imaging

Is There Hope for CT Lung Screening?

Posted on by Brian Casey

New data on CT lung cancer screening rates offer a good news/bad news story. The bad news is that only 21.2% of eligible individuals in four US states got screened, far lower than other exams like breast or colon screening.

The good news is that, as low as the rate was relative to other tests, 21.2% is still much higher than previous estimates. And the study itself found that the rate of CT lung screening has risen over 8 percentage points in 3 years. 

Compliance has lagged with CT lung screening ever since Medicare approved payments for the exam in 2015. A recent JACR study found that screening rates were low for eligible people for both Medicare and commercial insurance (3.4% and 1.8%).

Why is screening compliance so low? Explanations have ranged from fatalism among people who smoke to reimbursement requirements for “shared decision-making,” which unlike other screening exams require patients and providers to discuss CT lung screening before an exam can be ordered.

In this new study in JAMA Network Open, researchers examined screening rates in four states – Maine, Michigan, New Jersey, and Rhode Island – from January 2021 to January 2022. The study drew data from the National Health Interview Survey and weighted it to reflect the population of the US of individuals eligible for CT lung screening, based on the criteria of ages 55-79, 30-pack-year smoking history, and having smoked or quit within the past 15 years. Major findings included: 

  • The rate for CT lung cancer screening was 21.2%, up from 12.8% in 2019
  • People with a primary health professional (PHP) were nearly 6 times more likely to get screened (OR=5.62)
  • The age sweet spot for screening was 65-77, with lower odds for those 55-64 (OR=0.43) and 78-79 (OR=0.17)
  • Rates varied between states, with Rhode Island having the highest rate (30.3%) and New Jersey the lowest (17.5%).
  • Of those who got screened, 27.7% were in poor health and 4.5% had no health insurance

The Takeaway

The findings offer some hope for CT lung screening, as the compliance rate is among the highest we’ve seen among recent research studies. On the other hand, many of those screened were in such poor health they might not benefit from treatment. The high rate of compliance in people with PHPs indicates that promoting screening with these providers could pay off, especially given the requirement for shared decision-making. 

Mayo’s AI Model

Posted on by Brian Casey

SAN DIEGO – What’s behind the slow clinical adoption of artificial intelligence? That question permeated the discussion at this week’s AIMed Global Summit, an up-and-coming conference dedicated to AI in healthcare.

Running June 4-7, this week’s meeting saw hundreds of healthcare professionals gather in San Diego. Radiology figured prominently as the medical specialty with a lion’s share of the over 500 FDA-cleared AI algorithms available for clinical use.

But being available for use and actually being used are two different things. A common refrain at AIMed 2023 was slow clinical uptake of AI, a problem widely attributed to difficulties in deploying and implementing the technology. One speaker noted that less than 5% of practices are using AI today.

One way to spur AI adoption is the platform approach, in which AI apps are vetted by a single entity for inclusion in a marketplace from which clinicians can pick and choose what they want. 

The platform approach is gaining steam in radiology, but Mayo Clinic is rolling the platform concept out across its entire healthcare enterprise. First launched in 2019, Mayo Clinic Platform aims to help clinicians enjoy the benefits of AI without the implementation headache, according to Halim Abbas, senior director of AI at Mayo, who discussed Mayo’s progress on the platform at AIMed. 

The Mayo Clinic Platform has several main features:

  • Each medical specialty maintains its own internal AI R&D team with access to its own AI applications 
  • At the same time, Mayo operates a centralized AI operation that provides tools and services accessible across departments, such as data de-identification and harmonization, augmented data curation, and validation benchmarks
  • Clinical data is made available outside the -ologies, but the data is anonymized and secured, an approach Mayo calls “data behind glass”

Mayo Clinic Platform gives different -ologies some ownership of AI, but centralizes key functions and services to improve AI efficiency and smooth implementation. 

The Takeaway 

Mayo Clinic Platform offers an intriguing model for AI deployment. By removing AI’s implementation pain points, Mayo hopes to ramp up clinical utilization, and Mayo has the organizational heft and technical expertise to make it work (see below for news on Mayo’s new generative AI deal with Google Cloud). 

But can Mayo’s AI model be duplicated at smaller health systems and community providers that don’t have its IT resources? Maybe we’ll find out at AIMed 2024.

When AI Goes Wrong

Posted on by Brian Casey

What impact do incorrect AI results have on radiologist performance? That question was the focus of a new 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.

The accuracy of AI has become a major concern as deep learning models like ChatGPT become more powerful and come closer to routine use. There’s even a term – the “hallucination effect” – for when AI models veer off script to produce text that sounds plausible but in fact is incorrect.

While AI hallucinations may not be an issue in healthcare – yet – there is still concern about the impact that AI algorithms are having on clinicians, both in terms of diagnostic performance and workflow. 

To see what happens when AI goes wrong, researchers from Brown University sent 90 chest radiographs with “sham” AI results to six radiologists, with 50% of the studies positive for lung cancer. They employed different strategies for AI use, ranging from keeping the AI recommendations in the patient’s record to deleting them after the interpretation was made. Findings included:

  • When AI falsely called a true-pathology case “normal,” radiologists’ false-negative rates rose compared to when they didn’t use AI (20.7-33.0% depending on AI use strategy vs. 2.7%)
  • AI calling a negative case “abnormal” boosted radiologists’ false-positive rates compared to without AI (80.5-86.0% vs. 51.4%)
  • Not surprisingly, when AI calls were correct, radiologists were more accurate with AI than without, with increases in both true-positive rates (94.7-97.8% vs. 88.3%) and true-negative rates (89.7-90.7% vs. 77.3%)

Fortunately, the researchers offered suggestions on how to mitigate the impact of incorrect AI. Radiologists had fewer false negatives when AI provided a box around the region of suspicion, a phenomenon the researchers said could be related to AI helping radiologists focus. 

Also, radiologists’ false positives were higher when AI results were retained in the patient record versus when they were deleted. Researchers said this was evidence that radiologists were less likely to disagree with AI if there was a record of the disagreement occurring. 

The Takeaway 
As AI becomes more widespread clinically, studies like this will become increasingly important in shaping how the technology is used in the real world, and add to previous research on AI’s impact. Awareness that AI is imperfect – and strategies that take that awareness into account – will become key to any AI implementation.

When TIA Imaging Is Incomplete

Posted on by Brian Casey

A new study in AJR calculates the cost to patients when imaging evaluation is incomplete, finding that people with transient ischemic attack (TIA) who didn’t get full imaging workups were 30% more likely to have a new stroke diagnosis within the next 90 days.

Some 240,000 people experience TIA annually in the US. While TIAs typically last only a few minutes and don’t cause lasting neurological damage, they can be a warning sign of future neurological events to come.

Medical imaging – typically CT and MRI – are key in the neurological workup of TIA patients, and TIA can be treated with antithrombotic therapy, which reduces the likelihood of a stroke 90 days later. Therefore, guidelines call for prompt neuroimaging of the brain and neck in TIA patients, typically within 48 hours, with MRI the primary and CT the secondary options.

But what happens if TIA patients don’t get complete imaging as part of their workup? To answer this question, researchers from Colorado and California analyzed a database of 111,417 people seen at 4,253 hospitals who presented to the ED with TIA symptoms from 2016 to 2017. 

They tracked which patients received complete neurovascular imaging within 48 hours as part of their workup, then followed how many received a primary diagnosis of stroke within 90 days of the initial TIA encounter. Findings included:

  • 62.7% of patients received brain imaging and complete neurovascular imaging (both head and neck) within 48 hours
  • 37.3% received brain imaging but incomplete neurovascular imaging 
  • There was a higher rate of stroke at 90 days in TIA patients with incomplete imaging workup (7.0% vs. 4.4%)
  • Patients with incomplete neurovascular imaging also had a greater chance of stroke at 90 days (OR=1.3)

The Takeaway 

While the benefits of neuroimaging for stroke have been demonstrated in the literature, imaging’s value for TIA has been less certain – until now. The AJR study shows that neuroimaging is just as vital for TIA workup, and it supports guidelines calling for cross-sectional imaging of the head and neck within 48 hours of TIA.

AI Investment Shift

Posted on by Brian Casey

VC investment in the AI medical imaging sector has shifted notably in the last couple years, says a new report from UK market intelligence firm Signify Research. The report offers a fascinating look at an industry where almost $5B has been raised since 2015. 

VC investment in the AI medical imaging sector has shifted in the last couple years, with money moving to later-stage companies.

Total Funding Value Drops – Both investors and AI independent software vendors (ISVs) have noticed reduced funding activity, and that’s reflected in the Signify numbers. VC funding of imaging AI firms fell 32% in 2022, to $750.4M, down from a peak of $1.1B in 2021.

Deal Volume Declines – The number of deals getting done has also fallen, to 42 deals in 2022, off 30% compared to 60 in 2021. In imaging AI’s peak year, 2020, 95 funding deals were completed. 

VC Appetite Remains Strong – Despite the declines, VCs still have a strong appetite for radiology AI, but funding has shifted from smaller early-stage deals to larger, late-stage investments. 

HeartFlow Deal Tips Scales – The average deal size has spiked this year to date, to $27.6M, compared to $17.9M in 2022, $18M in 2021, and $7.9M in 2020. Much of the higher 2023 number is driven by HeartFlow’s huge $215M funding round in April; Signify analyst Sanjay Parekh, PhD, told The Imaging Wire he expects the average deal value to fall to $18M by year’s end.

The Rich Get Richer – Much of the funding has concentrated in a dozen or so AI companies that have raised over $100M. Big winners include HeartFlow (over $650M), and Cleerly, Shukun Technology, and Viz.ai (over $250M). Signify’s $100M club is rounded out by Aidoc, Cathworks, Keya Medical, Deepwise Shenrui, Imagen Technologies, Perspectum, Lunit, and Annalise.ai.

US and China Dominate – On a regional basis, VC funding is going to companies in the US (almost $2B) and China ($1.1B). Following them are Israel ($513M), the UK ($310M), and South Korea ($255M).  

The Takeaway 

Signify’s report shows the continuation of trends seen in previous years that point to a maturing market for medical imaging AI. As with any such market, winners and losers are emerging, and VCs are clearly being selective about choosing which horses to put their money on.

Salary Data Reveal Medicine’s Golden Cage

Posted on by Brian Casey

Are you a glass-half-full or a glass-half-empty kind of person? Either way, there’s lots to unpack in the latest data on physician salaries, this time from Medscape. 

Medscape’s survey of over 10k US physicians across over 29 medical specialties found that overall physician salaries have grown 18% over the last five years, to $352k, while specialists made an average of $382k. 

As with last year, radiologists landed in the top 10 of highest-compensated specialists, a finding that’s in line with previous salary surveys, such as from Doximity. Medscape found that radiologists had an average annual salary of $483k in 2023, compared to $437k in 2022. Radiologists had an average annual salary of $504k in the Doximity data. 

Other nuggets from the Medscape survey:

  • “Stagnant” reimbursement relative to rising practice costs has cut into physician income. 
  • The gender gap is narrowing. Male primary care doctors in 2023 earn 19% more than females, compared to about 25% previously.
  • Male specialist physicians earn 27% more than females, down from 31% last year and 33% the year before that.
  • Only 19% of radiologists are women – one of the lowest rates of female participation among medical specialties. 
  • 58% of radiologists feel they are fairly paid.
  • Radiologists report working an average of 49.6 hours a week.
  • 90% of radiologists say they would choose their specialty again, ranking #10.

The Takeaway

On the positive side, physician salaries continue to rise, and medicine is making encouraging progress in narrowing the gender gap. Radiologists seem to be well-compensated and relatively happy, but the specialty has more to do to attract women.

Underlying the raw data is a disturbing undercurrent of physician dissatisfaction, with many feeling as though medicine is a golden cage. In the free-response portion of the survey, doctors described themselves as caught between falling reimbursement and rising costs, with overwork also leading to burnout. 

The Medscape survey shows that addressing physician burnout must become a priority for the US healthcare system, and it can’t be solved merely by boosting salaries. Increasing the number of residency slots is a good first step (see below).

Is CCTA Set for Cardiac Screening?

Posted on by Brian Casey

A new study out of Denmark suggests that coronary CTA could be headed for population-based screening for heart disease. Researchers found that CCTA was remarkably effective in identifying individuals without symptoms who were more likely to experience heart attacks in years to come.

CCTA has proven so effective for cardiac imaging that it’s become a first-line test for stable chest pain, usually for those with symptoms. But researchers have debated whether CCTA’s value could be extended to asymptomatic individuals – which could set the stage for broad-based heart disease screening programs.

To investigate CCTA’s potential in the asymptomatic, researchers in Denmark scanned 9,533 individuals 40 years and older as part of the Copenhagen General Population Study, reporting their results in Annals of Internal Medicine. CCTA scans were conducted with Canon Medical’s 320-detector-row Aquilion One Vision scanner. 

Atherosclerosis was characterized as either obstructive (a luminal stenosis ≥ 50%), extensive (stenoses widely prevalent but not obstructive), or both. Researchers then tracked myocardial events over a median follow-up of 3.5 years. 

They found that 46% of study subjects had evidence of subclinical coronary atherosclerosis, with the type of atherosclerosis impacting risk of myocardial infarction: 

  • Extensive atherosclerosis had eight times higher risk 
  • Obstructive atherosclerosis had nine times higher risk
  • Both extensive and obstructive disease had 12 times higher risk

What’s more, researchers found that 10% of their study population had obstructive disease – which is just 10 percentage points under the 60% atherosclerosis threshold at which therapeutic intervention should be considered for asymptomatic people. 

Participants in the CGPS study did not receive treatment as part of the study, but the researchers have a follow-up study underway – DANE-HEART – in which asymptomatic people will get CCTA scans and some will be directed to preventive treatment if they meet clinical guidelines.

The Takeaway

This study demonstrates not only the widespread incidence of subclinical coronary atherosclerosis, but also CCTA’s ability to detect CAD before symptoms appear. Preventive treatment initiated and directed by CT findings could have a major impact on heart disease morbidity and mortality.

Given CCTA’s prognostic ability and the heavy burden of heart disease on society (more women die of heart disease than breast cancer, for example), how long before calls emerge to add CT-based heart screening to the arsenal of population-based screening programs? DANE-HEART may offer a clue.

Imaging in 2022

Posted on by Jake Fishman

Happy New Year, and welcome to the first Imaging Wire of 2022. For those of you working on your annual gameplans, here are some major imaging themes to keep in mind.

COVID Wave Watch – Nothing will have more influence on imaging in 2022 than how / when the COVID pandemic subsides, and how many more waves and variants emerge until we get there.

Efficiency Focus – It’s abundantly clear that imaging must become more efficient, making workflow improvements arguably the top priority for radiology teams and the folks who sell to them.

AI Matures – Imaging AI should mature at an even faster pace this year, bringing greater clinical adoption (and expectations), better workflow integration, improved use cases and business models, and the emergence of clear AI leaders. We’ll also likely see an initial wave of consolidation due to acquisitions and/or VC-prompted shutdowns.

More M&A – Imaging’s extremely active M&A climate should continue into 2022. Based on recent trends, this year’s M&A hotspots are likely to include PE-backed rad practice and imaging center acquisitions, enterprise imaging vendors adding to their tech and “ology” stacks, and more modality and solution expansions from the major OEMs.

Advanced Imaging Advancements – 2022 is shaping up to be a milestone year for MR and CT technology. On the MRI side, recent breakthroughs in magnet strength, helium requirements, portability, and image enhancement (among others) should lead to big changes in how / where MRI can be used. On the CT side, we’ll see OEMs increase their focus on achieving photon-counting CT leadership, even if most of that focus will be from their R&D and future product marketing teams in 2022.

The Patient Engagement Push – Digital patient engagement continues to gain momentum across healthcare, placing pressure on radiology teams to keep up. In 2022, that might mean getting better at radiology’s current patient engagement methods (e.g. image sharing, patient-friendly reporting, follow-up management), although patients’ expectations will likely evolve at an even faster pace.

Imaging Leaves the Hospital – A lot more imaging exams could be performed outside hospital walls in 2022, as payors continue to incentivize outpatient imaging (and image-related procedures) and at-home care continues its massive growth. 

While it’s hard to say which, if any, of these trends will be the top story of the next 12 months, it seems likely that we’re heading into another year with more big news than can fit into a seven-bullet roundup. Wishing you the best in 2022, Imaging Wire readers!

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