The European Society of Cardiology annual meeting concluded on September 2 in London, with around 32k clinicians from 171 countries attending some 4.4k presentations. Organizers reported that attendance finally rebounded to pre-COVID numbers.
While much of ESC 2024 focused on treatments for cardiovascular disease, diagnosis with medical imaging still played a prominent role.
Cardiac CT dominated many ESC sessions, and AI showed it is nearly as hot in cardiology as it is in radiology.
AI of low-dose CT scans had an AUC of 0.95 for predicting pulmonary congestion, a sign of acute heart failure.
Echocardiography AI identified HFpEF with higher AUC than clinical models (0.75 vs. 0.69).
AI of transthoracic echo detected hypertrophic cardiomyopathy with AUC=0.85.
Another ESC hot topic was CT for calculating coronary artery calcium (CAC) scores, a possible predictor of heart disease. Sessions found …
AI-generated volumetry of cardiac chambers based on CAC scans better predicted cardiovascular events than Agatston scores over 15 years of follow-up in an analysis of 5.8k patients from the MESA study.
AI-CAC with CT was comparable to cardiac MRI read by humans for predicting atrial fibrillation (0.802 vs. 0.798) and stroke (0.762 vs. 0.751) over 15 years, which could give an edge to AI-CAC given its automated nature.
An AI algorithm enabled opportunistic screening of CAC quantification from non-gated chest CT scans of 631 patients, finding high CAC scores in 13%. Many got statins, while 22 got additional imaging and 2 intervention.
AI-generated CAC scores were also highlighted in a Polish study, detecting CAC on contrast CT at a rate comparable to humans on non-contrast CT (77% vs. 79%), possibly eliminating the need for additional non-contrast CT.
The Takeaway
This week’s ESC 2024 sessions demonstrate the vital role of imaging in diagnosing and treating cardiovascular disease. While radiologists may not control the patients, they can always apply knowledge of advances in other disciplines to their work.
Echocardiography is a pillar of cardiac imaging, but it is operator-dependent and time-consuming to perform. In this interview, The Imaging Wire spoke with Seth Koeppel, Head of Business Development, and José Rivero, MD, RCS, of echo AI developer Us2.ai about how the company’s new V2 software moves the field toward fully automated echocardiography.
The Imaging Wire: Can you give a little bit of background about Us2.ai and its solutions for automated echocardiography?
Seth Koeppel: Us2.ai is a company that originated in Singapore. The first version of the software (Us2.V1) received its FDA clearance a little over two years ago for an AI algorithm that automates the analysis and reporting on echocardiograms of 23 key measurements for the evaluation of diastolic and systolic function.
In April 2024 we received an expanded regulatory clearance for more measurements – now a total of 45 measurements are cleared. When including derived measurements, based on those core 45 measurements, now up to almost 60 measurements are fully validated and automated, and with that Us2.V2 is bordering on full automation for echocardiography.
The application is vendor-agnostic – we basically can ingest any DICOM image and in two to three minutes produce a full report and analysis.
The software replicates what the expert human does during the traditional 45-60 minutes of image acquisition and annotation in echocardiography. Typically, echocardiography involves acquiring images and video at 40 to 60 frames per second, resulting in some cases up to 100 individual images from a two- or three-second loop.
The human expert then scrolls through these images to identify the best end-diastolic and end-systolic frames, manually annotating and measuring them, which is time-consuming and requires hundreds of mouse clicks. This process is very operator-dependent and manual.
And so the advantage the AI has is that it will do all of that in a fraction of the time, it will annotate every image of every frame, producing more data, and it does it with zero variability.
The Imaging Wire: AI is being developed for a lot of different medical imaging applications, but it seems like it’s particularly important for echocardiography. Why would you say that is?
José Rivero: It’s well known that healthcare institutions and providers are dealing with a larger number of patients and more complex cases. Echo is basically a pillar of cardiac imaging and really touches every patient throughout the path of care. We bring efficiency to the workflow and clinical support for diagnosis and treatment and follow-ups, directly contributing to enhanced patient care.
Additionally, the variability is a huge challenge in echo, as it is operator-dependent. Much of what we see in echo is subjective, certain patient populations require follow-up imaging, and for such longitudinal follow-up exams you want to remove the inter-operator variability as much as possible.
Seth Koeppel: Echo is ripe for disruption. We are faced with a huge shortage of cardiac sonographers. If you simply go on Indeed.com and you type in “cardiac sonographer,” there’s over 4,000 positions open today in the US. Most of those have somewhere between a $10,000, $15,000, up to $20,000 signing bonus. It is an acute problem.
We’re very quickly approaching a situation where we’re running huge backlogs – months in some situations – to get just a baseline echo. The gold standard for diagnosis is an echocardiogram. And if you can’t perform them, you have patients who are going by the wayside.
In our current system today, the average tech will do about eight echoes a day. An echo takes 45 to 60 minutes, because it’s so manual and it relies on expert humans. For the past 35 years echo has looked the same, there has been no innovation, other than image quality has gotten better, but at same time more parameters were added, resulting in more things to analyze in that same 45 or 60 minutes.
This is the first time that we can think about doing echo in less than 45 to 60 minutes, which is a huge enhancement in throughput because it addresses both that shortage of cardiac sonographers and the increasing demand for echo exams.
It also represents a huge benefit to sonographers, who often suffer repetitive stress injuries due to the poor ergonomics of echo, holding the probe tightly pressed against the patient’s chest in one hand, and the other hand on the cart scrolling/clicking/measuring, etc., which results in a high incidence of repetitive stress injuries to neck, shoulder, wrists, etc.
Studies have shown that 20-30% of techs leave the field due to work-related injury. If the AI can take on the role of making the majority of the measurements, in essence turning the sonographer into more of an “editor” than a “doer,” it has the potential to significantly reduce injury.
Interestingly, we saw many facilities move to “off-cart” measurements during COVID to reduce the time the tech was exposed to the patient, and many realized the benefits and maintained this workflow, which we also see in pediatrics, as kids have a hard time lying on the table for 45 minutes.
So with the introduction of AI in the echo workflow, the technicians acquire the images in 15/20 minutes and, in real-time, the images processed via the AI software are all automatically labeled, annotated, and measured. Within 2-3 minutes, a full report is available for the tech to review, adjust (our measures are fully editable) and confirm, and sign off on the report.
You can immediately see the benefits of reducing the time the tech has the probe in their hand and the patient spends on the table, and the tech then gets to sit at an ergonomically correct workstation (proper keyboard, mouse, large monitors, chair, etc.) and do their reporting versus on-cart, which is where the injuries occur.
It’s a worldwide shortage, it’s not just here in the US, we see this in other parts of the world, waitlist times to get an echo could be eight, 10, 12, or more months, which is just not acceptable.
The OPERA study in the UK demonstrated that the introduction of AI echo can tackle this issue. In Glasgow, the wait time for an echo was reduced from 12 months to under six weeks.
The Imaging Wire: You just received clearance for V2, but your V1 has been in the clinical field for some time already. Can you tell us more about the feedback on the use of V1 by your customers.
José Rivero: Clinically, the focus of V1 was heart failure and pulmonary hypertension. This is a critical step, because with AI, we could rapidly identify patients with heart failure or pulmonary hypertension.
One big step that has been taken by having the AI hand-in-hand with the mobile device is that you are taking echocardiography out of the hospital. So you can just go everywhere with this technology.
We demonstrated the feasibility of new clinical pathways using AI echo out of the hospital, in clinics or primary care settings, including novice screening1, 2 (no previous experience in echocardiography but supported by point-of-care ultrasound including AI guidance and Us2.ai analysis and reporting).
Seth Koeppel: We’re addressing the efficiency problem. Most people are pegging the time savings for the tech on the overall echo somewhere around 15 to 20 minutes, which is significant. In a recent study done in Japan using the Us2.ai software by a cardiologist published in the Journal of Echocardiography, they had a 70% reduction in overall time for analysis and reporting.3
The Imaging Wire: Let’s talk about version 2 of the software. When you started working on V2, what were some of the issues that you wanted to address with that?
Seth Koeppel: Version 1, version 2, it’s never changed for us, it’s about full automation of all echo. We aim to automate all the time-consuming and repetitive tasks the human has to do – image labeling and annotation, the clicks, measurements, and the analysis required.
Our medical affairs team works closely with the AI team and the feedback from our users to set the roadmap for the development of our software, prioritizing developments to meet clinical needs and expectations. In V2, we are now covering valve measurements and further enhancing our performance on HFpEF, as demonstrated now in comparison to the gold standard, pulmonary capillary wedge pressure (PCWP)4.
A new version is really about collaborating with leading institutions and researchers, acquiring excellent datasets for training the models until they reach a level of performance producing robust results we can all be confident in. Beyond the software development and training, we also engage in validation studies to further confirm the scientific efficiency of these models.
With V2 we’re also moving now into introducing different protocols, for example, contrast-enhanced imaging, which in the US is significant. We see in some clinics upwards of 50% to 60% use of contrast-enhanced imaging, where we don’t see that in other parts of the world. Our software is now validated for use with ultrasound-enhancing agents, and the measures correlate well.
Stress echo is another big application in echocardiography. So we’ve added that into the package now, and we’re starting to get into disease detection or disease prediction.
As well as for cardiac amyloidosis (CA), V2 is aligned with guidelines-based measurements for identification of CA in patients, reporting such measurements when found, along with the actual guideline recommendations to support the identification of such conditions which could otherwise be missed
José Rivero: We are at a point where we are now able to really go into more depth into the clinical environment, going into the echo lab itself, to where everything is done and where the higher volumes are. Before we had 23 measurements, now we are up to 45.
And again, that can be even a screening tool. If we start thinking about even subdividing things that we do in echocardiography with AI, again, this is expanding to the mobile environment. So there’s a lot of different disease-based assessments that we do. We are now a more complete AI echocardiography assessment tool.
The Imaging Wire: Clinical guidelines are so important in cardiac imaging and in echocardiography. Us2.ai integrates and refers to guideline recommendations in its reporting. Can you talk about the importance of that, and how you incorporate this in the software?
José Rivero: Clinical guidelines play a crucial role in imaging for supporting standardized, evidence-based practice, as well as minimizing risks and improving quality for the diagnosis and treatment of patients. These are issued by experts, and adherence to guidelines is an important topic for quality of care and GDMT (guideline-directed medical therapies).
We are a scientifically driven company, so we recognize that international guidelines and recommendations are of utmost importance; hence, the guidelines indications are systematically visible and discrepant values found in measurements clearly highlighted.
Seth Koeppel: The beautiful thing about AI in echo is that echo is so structured that it just lends itself so perfectly to AI. If we can automate the measurements, and then we can run them through all the complicated matrices of guidelines, it’s just full automation, right? It’s the ability to produce a full echo report without any human intervention required, and to do it in a fraction of the time with zero variability and in full consideration for international recommendations.
José Rivero: This is another level of support we provide, the sonographer only has to focus on the image acquisition, the cardiologist doing the overreading and checking the data will have these references brought up to his/her attention
With echo you need to include every point in the workflow for the sonographer to really focus on image acquisition and the cardiologist to do the overreading and checking the data. But in the end, those two come together when the cardiologist and the sonographers realize that there’s efficiency on both ends.
The Imaging Wire: V2 has only been out for a short time now but has there been research published on use of V2 in the field and what are clinicians finding?
Seth Koeppel: In V1, our software included a section labeled “investigational,” and some AI measurements were accessible for research purposes only as they had not yet received FDA clearance.
Opening access to these as investigational-research-only has enabled the users to test these out and confirm performance of the AI measurements in independently led publications and abstracts. This is why you are already seeing these studies out … and it is wonderful to see the interest of the users to publish on AI echo, a “trust and verify” approach.
With V2 and the FDA clearance, these measurements, our new features and functionalities, are available for clinical use.
The Imaging Wire: What about the economics of echo AI?
Seth Koeppel: Reimbursement is still front and center in echo and people don’t realize how robust it is, partially due to it being so manual and time consuming. Hospital echo still reimburses nearly $500 under HOPPS (Hospital Outpatient Prospective Payment System). Where compared to a CT today you might get $140 global, MRI $300-$350, an echo still pays $500.
When you think about the dynamic, it still relies on an expert human that makes typically $100,000 plus a year with benefits or more. And it takes 45 to 60 minutes. So the economics are such that the reimbursement is held very high.
But imagine if you can do incrementally two or three more echoes per day with the assistance of AI, you can immediately see the ROI for this. If you can simply do two incremental echoes a day, and there’s 254 days in a working year, that’s an incremental 500 echoes.
If there’s 2,080 hours in a year, and we average about an echo every hour, most places are producing about 2,000 echoes, now you’re taking them to 2,500 or more at $500, that’s an additional $100k per tech. Many hospitals have 8-10 techs scanning in any given day, so it’s a really compelling ROI.
This is an AI that really has both a clinical benefit but also a huge ROI. There’s this whole debate out there about who pays for AI and how does it get paid for? This one’s a no brainer.
The Imaging Wire: If you could step back and take a holistic view of V2, what benefits do you think that your software has for patients as well as hospitals and healthcare systems?
Seth Koeppel: It goes back to just the inefficiencies of echo – you’re taking something that is highly manual, relies on expert humans that are in short supply. It’s as if you’re an expert craftsman, and you’ve been cutting by hand with a hand tool, and then somebody walks in and hands you a power tool. We still need the expert human, who knows where to cut, what to cut, how to cut. But now somebody has given him a tool that allows him to just do this job so much more efficiently, with a higher degree of accuracy.
Let’s take another example. Strain is something that has been particularly difficult for operators because every vendor, every cart manufacturer, has their own proprietary strain. You can’t compare strain results done on a GE cart to a Philips cart to a Siemens cart. It takes time, you have to train the operators, you have human variability in there.
In V2, strain is now included, it’s fully automated, and it’s vendor-neutral. You don’t have to buy expensive upgrades to carts to get access to it. So many, many problems are solved just in that one simple set of parameters.
If we put it all together and look at the potential of AI echo, we can address the backlog, allow for more echo to be done in the echo lab but also in primary care settings and clinics where AI echo opens new pathways for screening and detection of heart failure and heart disease at an early stage, early detection for more efficient treatment.
This helps facilities facing the increasing demand for echo support and creates efficient longitudinal follow-up for oncology patients or populations at risk.
In addition, we can open access to echo exams in parts of the world which do not have the expensive carts nor the expert workforce available and deliver on our mission to democratize echocardiography.
José Rivero: I would say that V2 is a very strong release, which includes contrast, stress echo, and strain. I would love to see all three, including all whatever we had on V1, to be mainstream, and see the customer satisfaction with this because I think that it does bring a big solution to the echo world.
The Imaging Wire: As the year progresses, what else can we look forward to seeing from Us2.ai?
José Rivero: In the clinical area, we will continue our work to expand the range of measurements and validate our detection models, but we are also very keen to start looking into pediatric echo.
Seth Koeppel: Our user interface has been greatly improved in V2 and this is something we really want to keep focus on. We are also working on refining our automated reporting to include customization features, perfecting the report output to further support the clinicians reviewing these, and integrating LLM models to make reporting accessible for non-experts HCP and the patients themselves.
REFERENCES
Tromp, J., Sarra, C., Bouchahda Nidhal, Ben Messaoud Mejdi, Fourat Zouari, Hummel, Y., Khadija Mzoughi, Sondes Kraiem, Wafa Fehri, Habib Gamra, Lam, C. S. P., Alexandre Mebazaa, & Faouzi Addad. (2023). Nurse-led home-based detection of cardiac dysfunction by ultrasound: Results of the CUMIN pilot study. European Heart Journal. Digital Health.
Huang, W., Lee, A., Tromp, J., Loon Yee Teo, Chandramouli, C., Choon Ta Ng, Huang, F., Carolyn S.P. Lam, & See Hooi Ewe. (2023). Point-of-care AI-assisted echocardiography for screening of heart failure (HANES-HF). Journal of the American College of Cardiology, 81(8), 2145–2145.
Hirata, Y., Nomura, Y., Yoshihito Saijo, Sata, M., & Kusunose, K. (2024). Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time. Journal of Echocardiography.
Hidenori Yaku, Komtebedde, J., Silvestry, F. E., & Sanjiv Jayendra Shah. (2024). Deep learning-based automated measurements of echocardiographic estimators invasive pulmonary capillary wedge pressure perform equally to core lab measurements: results from REDUCE LAP-HF II. Journal of the American College of Cardiology, 83(13), 316–316.
In a landmark study of 40k patients from the UK published in The Lancet, an AI-derived score that analyzed coronary arterial inflammation on coronary CT angiography scans was effective in predicting future cardiac risk in people regardless of whether they had obstructive coronary artery disease.
CCTA’s power for predicting heart problems has been demonstrated in multiple studies, and it’s now considered a first-line test for individuals with chest pain.
But the situation is trickier in those without obstructive disease – prompting researchers to ask whether CCTA’s ability to visualize subtle changes in cardiac structure and function could be leveraged – such as with AI – to deliver even more prognostic power.
The Oxford Risk Factors And Noninvasive imaging (ORFAN) study in the UK is addressing that question by conducting CCTA scans in 40k patients as part of routine clinical care at eight hospitals.
Researchers analyzed outcomes in the entire ORFAN population of 40k patients, then followed a subset of 3.4k higher-risk patients for 7.7 years to study the value of a perivascular fat attenuation index (FAI) score.
FAI scores measure heart inflammation in coronary arteries and are calculated using Caristo Diagnostics’ CaRi-Heart AI software.
The scores are combined with other traditional risk factors to create an AI-Risk classification that predicts the likelihood of an adverse event.
Researchers found that …
Across the entire 40k cohort, patients without obstructive CAD accounted for 64% of cardiac deaths and 66% of MACE – twice as many as those with obstructive CAD
In the smaller higher-risk cohort, patients with an elevated FAI score in all three coronary arteries had a higher risk of cardiac mortality (HR=29.8) or MACE (HR=12.6)
Elevated FAI scores in any coronary artery also predicted cardiac mortality
AI-Risk scores were associated with cardiac mortality (HR=6.75) and MACE (HR=4.68) when comparing very-high-risk versus low- or medium-risk patients
The first data point is worth noting, as it illustrates the need to improve risk stratification and management in people without obstructive CAD.
The Takeaway The ORFAN results are an exciting development for cardiac CT AI (in addition to being a major coup for Caristo, which raised $16.3M last year to commercialize CaRi-Heart globally). Measurements of coronary inflammation could give clinicians another tool – in addition to plaque measurements and calcium scoring – to predict cardiac events.
A new study in Radiologyoffers more support for the value of CT-based coronary artery calcium scoring, finding that people with higher CAC scores had worse outcomes, and suggesting that those with scores of 0 could potentially avoid invasive coronary angiography.
Evidence has been building that by measuring calcium buildup in the heart, CAC scores can predict clinical outcomes, in particular major adverse cardiac events, particularly in patients with stable chest.
Studies ranging from MESA to SCOT-HEART to PROMISE have found that patients with CAC scores of 0 have MACE risk that’s lower than 2% – meaning they could be discharged without further invasive workup.
The new study is an update to the DISCHARGE trial, which in 2022 published results comparing a CT-first evaluation strategy to one with invasive coronary angiography. The new study investigates the value of CAC scoring by analyzing its prognostic power in patients with stable chest pain who were referred for invasive coronary angiography.
The DISCHARGE study is notable for its diversity – 26 clinical centers in 16 European countries – as well as its use of 13 different models of CT scanners from all four major CT OEMs from 2015 to 2019.
In all, 1.7k patients were studied, and CAC scores were generated based on CT scans and used to stratify patients into one of three groups; they were then followed for 3.5 years and rates of MACE were correlated to CAC levels, finding …
Patients with CAC scores of 0 had the lowest rates of MACE compared to those with scores of 1-399 and ≥400 (0.5% vs. 1.9% & 6.8%)
Rising CAC scores corresponded to higher prevalence of obstructive coronary artery disease (0=4.1% vs. 1-399=29.7% & ≥400=76%)
Revascularization rates rose with CAC scores (0=1.7% vs. ≥400=46.2%)
While the authors steered away from commenting on the study’s impact on clinical management, the findings – if confirmed with additional studies – suggest that stable chest pain patients may not need invasive coronary angiography.
And in another interesting wrinkle to the study, the researchers pointed out that 57% of the DISCHARGE study’s patient population were women, a fact that addresses sex bias in previous research.
The Takeaway
The DISCHARGE study’s findings are yet another feather in the cap for cardiac CT, with higher CAC scores indicating the long-term presence of atherosclerosis. Should they be confirmed, individuals with stable chest pain in the future will benefit from less invasive – and less expensive – management.
CT should be used first to evaluate patients with stable chest pain who are suspected of having a heart attack. That’s the message of a paper being presented this week at the American College of Cardiology Cardiovascular Summit in Washington, DC.
CT is proving itself useful for a variety of applications in cardiac imaging, from predicting heart disease risk through coronary calcium scores to assessing whether people with chest pain need treatment like invasive angiography – or can be sent home and monitored.
But cardiac CT often runs up against decades of clinical practice that relies on tools like stress testing or diagnostic invasive coronary angiography for evaluating patients, with the CT-first strategy reserved for a limited number of people, such as those with unestablished coronary artery disease.
But the new study suggests that the CT-first approach could be used for the vast majority of patients presenting with stable chest pain.
A research team led by senior author Markus Scherer, MD, of Atrium Health-Sanger Heart & Vascular Institute in Charlotte, North Carolina tested the strategy in 786 patients seen from October 2022 to June 2023 who had no prior diagnosis of coronary artery disease and underwent elective invasive angiography to evaluate suspected angina.
The CT-first strategy compared CT angiography with provisional FFRCT testing to traditional evaluation pathways, which included stress echo, stress myocardial perfusion imaging, stress MRI, or no invasive testing before direct referral to angiography. Revascularization rates by strategy were as follows …
62% for CT-first
50% for stress MRI
40% for stress echo
34% for no prior test
31% for stress MPI
The Takeaway
The results presented this week offer real-world evidence that support recent clinical studies backing broader use of CT for patients with chest pain. Given CT’s advantages in terms of cost and noninvasiveness, the findings raise the question of whether more can be done to get clinicians to adhere to established guidelines calling for a CT-first protocol.
CT has established itself as an excellent cardiac imaging modality. But there can still be some fine-tuning in terms of exactly how and when to use it, especially for assessing people presenting with chest pain.
Two studies in JAMA Cardiology tackle this head-on, presenting new evidence that supports a more conservative – and precise – approach to determining which patients get follow-up testing. The studies also address concerns that using coronary CT angiography (CCTA) as an initial test before invasive catheterization could lead to unnecessary testing.
In the PRECISE study, researchers analyzed 2.1k patients from 2018 to 2021 who had stable symptoms of suspected coronary artery disease (CAD). Patients were randomized to a usual testing strategy (such as cardiac SPECT or stress echo), or a precision strategy that employed CCTA with selected fractional flow reserve CT (FFR-CT).
The precision strategy group was further subdivided into a subgroup of those at minimal risk of cardiac events (20%) for whom testing was deferred to see if utilization could be reduced even further. In the precision strategy group….
Rates of invasive catheterization without coronary obstruction were lower (4% vs. 11%)
Testing was lower versus the usual testing group (84% vs. 94%)
Positive tests were more common (18% vs. 13%)
64% of the deferred-testing subgroup got no testing at all
Adverse events were higher, but the difference was not statistically significant
To expand on the analysis, JAMA Cardiologypublished a related study that further investigated the safety of the deferred-testing strategy at one-year follow-up. Researchers compared adverse events in the deferred testing group to those who got the usual testing strategy, finding that the deferred testing group had…
A lower incidence rate of adverse events (0.9 vs. 5.9)
A lower rate of invasive cardiac cath without obstructive CAD per 100 patient years (1.0 vs. 6.5)
The results from both studies show that a strategy of deferring testing for low-risk CAD patients while sending higher-risk patients to CCTA and FFR-CT is clinically effective with no adverse impact on patient safety.
The Takeaway The new findings don’t take any of the luster off cardiac CT; they simply add to the body of knowledge demonstrating when to use – and not to use – this incredibly powerful tool for directing patient care. And in the emerging era of precision medicine, that’s what it’s all about.
CT continues to flex its muscles as a tool for predicting heart disease risk, in large measure due to its prowess for coronary artery calcium scoring. In JAMA, a new paper found CT-derived CAC scores to be more effective in predicting coronary heart disease than genetic scores when added to traditional risk scoring.
Traditional risk scoring – based on factors such as cholesterol levels, blood pressure, and smoking status – has done a good job of directing cholesterol-lowering statin therapy to people at risk of future cardiac events. But these scores still provide an imprecise estimate of coronary heart disease risk.
Two relatively new tools for improving CHD risk prediction are CAC scoring from CT scans and polygenic risk factors, based on genetic variants that could predispose people toward heart disease. But the impact of either of these tools (or both together) when added to traditional risk scoring hasn’t been investigated.
To answer this question, researchers analyzed the impact of both types of scoring on participants in the Multi-Ethnic Study of Atherosclerosis (1,991 people) and the Rotterdam Study (1,217 people). CHD risk was predicted based on both CAC and PRS and then compared to actual CHD events over the long term.
They also tracked how accurate both tools were in reclassifying people into different risk categories (higher than 7.5% risk calls for statins). Findings included:
Both CAC scores and PRS were effective in predicting 10-year risk of CHD in the MESA dataset (HR=2.60 for CAC score, HR=1.43 for PRS). Scores were slightly lower but similar in the Rotterdam Study
The C statistic was higher for CAC scoring than PRS (0.76 vs. 0.69; 0.7 indicates a “good” model and 0.8 a “strong” model)
The improved accuracy in reclassifying patient risk was statistically significant when CAC was added to traditional factors (half of study participants moved into the high-risk group), but not when PRS was added
The Takeaway
This study adds to the growing body of evidence supporting cardiac CT as a prognostic tool for heart disease, and reinforces CT’s prowess in the heart. The findings also support the growing chorus in favor of using CT as a screening tool in cases of intermediate or uncertain risk for future heart disease.
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 Radiologyin which Dr. David Bluemke and Dr. João Lima look into the future and offer a top 10 list of major developments in cardiovascular imaging in 2040.
Cardiovascular disease carries a massive medical burden, with over 800,000 myocardial infarctions occurring annually in the US alone. By 2030 almost one-third of deaths worldwide are expected to be due to cardiovascular disease.
Multiple different imaging modalities are adept at identifying both ischemic and nonischemic heart disease, but CT has risen to the top for ischemic imaging, making “quantum” advances in the last decade thanks to its growing prowess in the coronary arteries.
CT’s advances have been so great that the modality occupies seven of the top 10 spots on Bluemke and Lima’s list. In brief, they see:
Coronary CTA becoming totally automated, a development that will no doubt benefit AI developers like HeartFlow (see below).
CCTA becoming a preventive tool rather than a gatekeeper to interventional cardiology (also hinted at in a recent study from Denmark). For example, CCTA will be used to track the effectiveness of statin therapy
Photon-counting CT flexing its muscles for coronary artery evaluation and routine plaque characterization and quantification
Next-generation cardiac CT becoming more like MRI
Next-generation cardiac MRI becoming more like CT
They also see a major growing role for software-assisted cardiac CT with AI and other tools. Software-based automation has simplified the “postprocessing nightmares” once common with coronary CT, making it “wonderfully ordinary” to perform.
The Takeaway
Bluemke and Lima offer a fascinating glimpse of cardiac imaging’s future. But one area they don’t touch on is whether CT’s rising prominence means radiologists will start taking back turf in heart imaging once ceded to cardiologists. Heart specialists haven’t taken over cardiac CT in the same way that they monopolized echocardiography and nuclear cardiology. Could we be seeing a renaissance of radiology in the heart?
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.
We hear a lot about AI’s potential to expand ultrasound to far more users and clinical settings, and a new study out of Singapore suggests that ultrasound’s AI-driven expansion might go far beyond what many of us had in mind.
The PANES-HF trial set up a home-based echo heart failure screening program that equipped a team of complete novices (no experience with echo, or in healthcare) with EchoNous’s AI-guided handheld ultrasound system and Us2.ai’s AI-automated echo analysis and reporting solution.
After just two weeks of training, the novices performed at-home echocardiography exams on 100 patients with suspected heart failure, completing the studies in an average of 11.5 minutes per patient.
When compared to the same 100 patients’ NT-proBNP blood test results and reference standard echo exams (expert sonographers, cart-based echo systems, and cardiologist interpretations), the novice echo AI pathway…
Yielded interpretable results in 96 patients
Improved risk prediction accuracy versus NT-proBNP by 30%
Detected abnormal LVEF <50% scans with an 0.880 AUC (vs. NT-proBNP’s 0.651-0.690 AUCs)
Achieved good agreement with expert clinicians for LVEF<50% detection (k=0.742)
These findings were strong enough for the authors to suggest that emerging ultrasound and AI technologies will enable healthcare organizations to create completely new heart failure pathways. That might start with task-shifting from cardiologists to primary care, but could extend to novice-performed exams and home-based care.
The Takeaway
Considering the rising prevalence of heart failure, the recent advances in HF treatments, and the continued sonographer shortage, there’s clearly a need for more accessible and efficient echo pathways — and this study is arguably the strongest evidence that AI might be at the center of those new pathways.
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