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
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.
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?
The major cardiac imaging societies weighed-in on the AHA/ACC’s new Chest Pain Guidelines, highlighting the notable shifts coming to cardiac imaging, and the adjustments they could require.
The cardiac CT and MRI societies took a victory lap, highlighting CCTA and CMR’s now-greater role in chest pain diagnosis, while forecasting that the new guideline will bring:
Increased demand for cardiac CT & MR exams and scanners
A need for more cardiac CT & MR staff, training, and infrastructure
Requests for more cardiac CT & MR funding and reimbursements
More collaborations across radiology, cardiology, and emergency medicine
The angiography and nuclear cardiology societies were less celebratory. Rather than warning providers to start buying more scanners and training more techs (like CT & MR), they focused on defending their roles in chest pain diagnosis, reiterating their advantages, and pointing out how the new guidelines might incorrectly steer patients to unnecessary or insufficient tests.
FFR-CT’s new role as a key post-CT diagnostic step made headlines when the guidelines came out, but the cardiac imaging societies don’t seem to be ready to welcome the AI approach. The nuclear cardiology and radiology societies called out FFR-CT’s low adoption and limited supporting evidence, while the SCCT didn’t even mention FFR-CT in its statement (and they’re the cardiac CT society!).
Echocardiography maintained its core role in chest pain diagnosis, but the echo society clearly wanted more specific guidelines around who can perform echo and how well they’re trained to perform those exams. That reaction is understandable given the sonographer workforce challenges and the expansion of cardiac POCUS to new clinical roles (w/ less echo training), although some might argue that echo AI tools might help address these problems.
Imaging and shared decision-making play a prominent role in the new chest pain guidelines, which seems like good news for patient-specific care (and imaging department/vendor revenues), but it also leaves room for debate within the clinic and across clinical societies.
The JACC seems to understand that it needs to clear up many of these gray areas in future versions of the chest pain guidelines. Until then, it will be up to providers to create decision-making and care pathways that work best for them, and evolve their teams and technologies accordingly.
A major new study from the DISCHARGE Trial Group showed that coronary CT is as effective as invasive coronary angiography (ICA) for the management of patients with obstructive coronary artery disease (CAD), potentially challenging current guidelines.
Background – Invasive coronary angiography (ICA) is the reference standard for diagnosing and managing CAD and it’s performed over 3.5 million times each year in the European Union alone (many more millions globally). However, over 60% of these exams prove negative and theoretically could have been diagnosed via non-invasive CT exams.
The Study – The randomized, multi-center trial (26 sites, 16 EU countries) used CT or ICA as the initial diagnostic and treatment guidance exam for 3,523 patients with stable chest pain and intermediate probability of obstructive CAD (1,808 patients w/ CT). By the end of the study’s 3.5-year follow-up period, patients in the CT group had:
A lower rate of major adverse cardiovascular events (2.1% vs. 3% w/ ICA)
A far lower major procedure-related complication rate (0.5% vs. 1.9% w/ ICA)
A slightly higher rate of reported angina (8.8% vs. 7.5% w/ ICA)
These results suggest that following a CT-first strategy for evaluating patients with a medium risk of CAD produces similar longer-term outcomes as the current ICA-first strategy (maybe even better outcomes), while significantly reducing major complications and unnecessary cath lab procedures.
That’s pretty compelling and could actually influence procedural changes, given the size / credibility of the DISCHARGE Trial Group and the fact that CT was already proposed in the Chest Pain Guidelines as a gatekeeper for invasive coronary angiography.
A new Radiology Journal study found that combining Triple-rule-out CT (TRO CT) with Late Contrast Enhancement CT (LCE CT) significantly improves acute chest pain diagnosis.
Background – It’s traditionally been challenging to diagnose patients with acute chest pain and mild troponin rise, as TRO CT is effective for several key diagnoses (coronary artery disease, acute aortic syndrome, pulmonary embolism) but can’t identify nonvascular causes of myocardial injury.
The Study – The researchers examined 84 troponin-positive patients with acute chest pain using TRO CT, and then performed LCE CT exams on the 42 patients who had negative/inconclusive results.
The Results – The added LCE CT exams revealed positive/conclusive findings in 34 of the 42 previously-negative/inconclusive patients (including 22 w/ myocarditis), improving overall diagnostic rates from 50% to 90% (from 42/84 to 76/84).
The Takeaway – This new TRO CT + LCE CT protocol could make cardiac CT a “one-stop shop” for diagnosing acute chest pain, eliminating the need for follow-up MRI exams and allowing faster diagnoses. That’s especially notable considering that CT is already recommended for patients with low-risk acute chest pain (to exclude CAD) and was recently proposed as a gatekeeper for invasive coronary angiography.
UCSF is now using AI to automatically screen all of its routine non-contrast chest CTs for elevated coronary artery calcium scores (CAC scores), representing a major milestone for an AI use case that was previously limited to academic studies and future business strategies.
UCSF’s Deployment –UCSF becomes the first medical center to deploy the end-to-end AI CAC scoring system that it developed with Stanford and Bunkerhill Health earlier this year. The new system automatically identifies elevated CAC scores in non-gated / non-contrast chest CTs, creating an “opportunistic screening pathway” that allows UCSF physicians to identify high-CAC patients and get them into treatment.
Why This is a Big Deal – Over 20m chest CTs are performed in the U.S. annually and each of those scans contains insights into patients’ cardiac health. However, an AI model like this would be required to extract cardiac data from the majority of CT scans (CAC isn’t visible to humans in non-gated CTs) and efficiently interpret them (there’s far too many images). This AI system’s path from academic research to clinical deployment seems like a big deal too.
The Commercial Impact – Most health systems don’t have the AI firepower of Stanford and UCSF, but they certainly produce plenty of chest CTs and should want to identify more high-risk patients while treatable (especially if they’re also risk holders). Meanwhile, there’s growing commercial efforts from companies like Cleerly and Nanox.AI to create opportunistic CAC screening pathways for all these health systems that can’t develop their own CAC AI workflows (or prefer not to).
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