Congress Review | Editors Choice | AHA Scientific Sessions 2024
PanEcho: Advancing Echocardiogram Analysis with Comprehensive AI Reporting
Time to read: 02:22
Time to listen: 05:59
Published on MedED: 25 November 2024
Originally Published: 16 November 2024
Sourced: AHA Scientific Sessions 2024
Type of article: Conference Review | In Brief
MedED Catalogue Reference: MCABC007
Category: Cardiovascular Disease
Cross Reference: Artificial Intelligence,Radiology & Imaging
Keywords: echocardiogram, AI, radiology, imaging techniques, precision medicine
The PanEcho AI system achieved an overall accuracy rate of 0.91 across 18 diagnostic tasks, demonstrating potential for simplified, AI-assisted screening in settings with limited access to expert readers, enabling rapid identification of abnormalities and reducing urgent referrals.
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Presented at AHA Scientific Sessions 2024 as a Research Abstract.This summary does not represent the original research, nor is it intended to replace the original research. Content Disclaimer
Echocardiograms are essential for diagnosing and managing cardiovascular conditions, but delays in interpreting these complex imaging tests often result in prolonged wait times for medical care.
Artificial intelligence (AI) programs have shown promise in cardiology, yet most applications to date have been limited to specific heart views or narrowly focused disease criteria.
A novel AI system called PanEcho was presented at the American Heart Association’s Scientific Sessions 2024, highlighting its potential to revolutionise echocardiogram analysis by providing comprehensive reporting for major findings from any set of echocardiography videos.
The findings of that study are recorded here. This study was presented as a Research Abstract, and the findings should be considered preliminary until published in a peer-reviewed journal.
Study Intention
The trial sought to evaluate the safety and effectiveness of reconditioned permanent pacemakers (PPMs) compared to new devices. Specifically, it assessed the risks of infection, device failure, and procedural complications among patients in MICs for whom new pacemakers were financially inaccessible.
Participants
The imaging dataset included 26,067 unique individuals, predominantly adults (average age: 67 years) and men (52%).
Study Design
PanEcho was developed using 1.23 million echocardiogram videos derived from nearly 34,000 transthoracic echocardiography tests conducted at Yale-New Haven Health System hospitals and outpatient clinics between 2016 and 2022.
The AI system, developed by the CarDS Lab at Yale School of Medicine, was trained to analyse multiple views and classify a wide range of cardiac conditions and parameters.
Results
PanEcho’s diagnostic performance was evaluated using a standard measurement of accuracy for diagnostic tests: the area under the receiver operating characteristic curve (AUC).
A 100% accurate test has an AUC of 1, and an uninformative test (e.g., random guessing) has an AUC of 0.5. PanEcho demonstrated strong performance across 18 diagnostic classification tasks, achieving an average accuracy score of 0.91.
Its accuracy in assessing ventricular function and structure included:
Left ventricle size detection: 0.95 AUC
Systolic dysfunction (left ventricle): 0.98 AUC
Left ventricle hypertrophy: 0.91 AUC
Systolic dysfunction (right ventricle): 0.93 AUC
Severe aortic stenosis: 0.99 AUC
Mitral stenosis: 0.96 AUC
Aortic regurgitation (moderate or greater): 0.93 AUC
Mitral regurgitation (moderate or greater): 0.96 AUC
In estimating continuous echocardiographic parameters, PanEcho achieved a median normalised mean absolute error of 0.13 across 21 tasks. Specifically:
Left ventricle ejection fraction: 4.4% mean absolute error
Intraventricular septum thickness: 1.3 mm mean absolute error
Posterior wall thickness: 1.2 mm mean absolute error
Study Implications
PanEcho effectively quantifies critical cardiac parameters and diagnoses structural and functional heart conditions with high accuracy.
Its ability to process multiple echocardiogram views and report comprehensively offers an improvement over current AI tools, which are limited to single-view analyses.
In an interview given to AHA at the congress, Gregory Holste, M.S.E., a researcher with the Cardiovascular Data Science (CarDS) Lab who presented the study, commented that:
“PanEcho has the potential to be used in simplified, AI-assisted screening echocardiograms. In settings where expert readers may not be readily accessible, PanEcho could rapidly rule out abnormalities that would otherwise require urgent referral.”
Conclusion
The PanEcho AI system marks a significant breakthrough in echocardiography, providing accurate and efficient analysis across a range of diagnostic tasks.
Its widespread adoption has the potential to improve patient outcomes by expediting diagnoses and enabling timely clinical decisions in cardiovascular care. By reducing delays in echocardiogram interpretation, the system helps ensure precise and prompt medical attention, enhancing the overall quality of care.
Limitations
None available for this review
AHA Scientific Sessions 2024 News Release
Funding
Information not available for this review
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