Chest Pain Implications

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.

The Takeaway

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 CT-First Approach to CAD

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)

The Takeaway

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.

One-Stop Cardiac CT

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 Automates CAC Scoring

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).

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

You're signed up!

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

-- The Imaging Wire team