AI Enables Single-Click Cardiac MRI

Cardiac MRI is one of the most powerful imaging tools for assessing heart function, but it’s difficult and time-consuming to perform. Could automated AI planning offer a solution? A new research paper shows how AI-based software can speed up cardiac MRI workflow

Cardiac MRI has a variety of useful clinical applications, generating high-resolution images for tissue characterization and functional assessment without the ionizing radiation of angiography or CT.

  • But cardiac MR also requires highly trained MR technologists to perform complex tasks like finding reference cardiac planes, adjusting parameters for every sequence, and interacting with patients – all challenges in today’s era of workforce shortages. 

Cardiac MRI’s complexity also increases the number of clicks required by technologists to plan exams. 

  • This can introduce scan errors and produces inter-operator variability between exams. 

Fortunately, vendors are developing AI-based software that automates cardiac MR planning – in this case, Siemens Healthineers’ myExam Cardiac Assist and AI Cardiac Scan Companion. 

  • The solution enables single-click cardiac MR planning with a pre-defined protocol that includes auto-positioning to identify the center of the heart and shift the scanner table to isocenter, as well as positioning localizers to perform auto-align without manual intervention. 

How well does it work in the real world? Researchers tested the AI software against conventional manual cardiac MR exam planning in 82 patients from August 2023 to February 2024, finding that automated protocols had … 

  • A lower mean rate of procedure errors (0.45 vs. 1.13).
  • A higher rate of error-free exams (71% vs. 45%).
  • Shorter duration of free-breathing studies (30 vs. 37 minutes).
  • But similar duration of breath-hold exams (42 vs. 44 minutes, p=0.42).
  • While reducing the error gap between more and less experienced technologists. 

In their discussion of the study’s significance, the researchers note that most of the recent literature on AI in medical imaging has focused on its use for image reconstruction, analysis, and reporting.

  • Meanwhile, there’s been relatively little attention paid to one of radiology’s biggest pain points – exam preparation and planning. 

The Takeaway

The new study’s results are exciting in that they offer not only a method for performing cardiac MR more easily (potentially expanding patient access), but also address the persistent shortage of technologists. What’s not to like?

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.

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