HeartBeam’s Artificial Intelligence Algorithm Combined with Vectorcardiography (VCG) Outperforms Expert Cardiologists in Detecting Arrhythmias
HeartBeam (NASDAQ: BEAT) announced new study data showing that its AI algorithm combined with vectorcardiography (VCG) outperformed expert cardiologists in detecting atrial flutter, a common arrhythmia. The study, presented at the Heart Rhythm Society annual meeting, involved 173 VCGs, single-lead ECGs, and 12-lead ECGs. Key findings revealed a 40% improvement in detection sensitivity compared to single-lead ECGs reviewed by cardiologists and a 6% improvement over 12-lead ECGs. HeartBeam's core technology captures heart signals in three projections, aiming for a more personalized cardiac care approach. Their AIMIGo™ device, for patient use, is under FDA review.
- HeartBeam AI combined with VCG showed a 40% improvement in detecting atrial flutter over expert cardiologists using single-lead ECGs.
- The AI demonstrated a 6% improvement in detection sensitivity compared to 12-lead ECGs reviewed by experts.
- HeartBeam's technology delivered zero variability in detection, indicating consistent and reliable results.
- The company’s AI program is advancing toward more personalized cardiac care, aiming to improve diagnostic accuracy outside medical facilities.
- HeartBeam AIMIGo™, a portable device under FDA review, promises enhanced cardiac monitoring for patients at home.
- The FDA review status of HeartBeam AIMIGo™ indicates it is not yet approved for patient use, posing a risk of potential delays or rejections.
- The study's results, although promising, are based on a sample size, which may not fully represent broader clinical scenarios.
- Reliance on AI algorithms may face scrutiny regarding data security, patient privacy, and potential biases in algorithmic decisions.
Insights
This development is significant because it demonstrates that AI can potentially outperform human cardiologists in diagnosing atrial flutter, a common and potentially dangerous heart rhythm disorder. By using vectorcardiography (VCG) and applying sophisticated AI algorithms, HeartBeam has achieved a 40% improvement in detection sensitivity compared to a panel of expert electrophysiologists analyzing single-lead ECGs. Atrial flutter is a condition that greatly increases the risk of stroke, so improved detection can lead to earlier interventions, better patient outcomes and possibly reduced healthcare costs.
The technology’s zero variability in detection further enhances its appeal, as consistency is critical in medical diagnostics. The real excitement here is the AI's application to patient care outside of clinical settings through the AIMIGo device, which is currently under FDA review. This could significantly shift how cardiac care is managed, providing continuous monitoring and early detection of potential issues.
For investors, the successful FDA approval and commercialization of AIMIGo could mean a substantial market opportunity, given the prevalence of atrial flutter and the demand for remote patient monitoring solutions.
The use of deep learning in medical technology is a game-changer. This AI algorithm's ability to process and analyze vectorcardiography (VCG) data more effectively than human experts highlights the transformative potential of AI in healthcare. The 40% improvement in sensitivity for single-lead ECGs and even the 6% improvement for 12-lead ECGs are impressive, considering the entrenched use of these standards in cardiology. It suggests that AI can augment traditional diagnostic tools, making them more reliable and accurate.
HeartBeam's approach of leveraging AI to offer a longitudinal view of a patient's cardiac status could move cardiac care from reactive to proactive. By continuously analyzing data, the AI can identify trends that may indicate early signs of arrhythmias or other heart conditions, potentially catching issues before they become critical.
For investors, this innovation not only represents a breakthrough in medical technology but also suggests a scalable solution that could be adopted widely, possibly becoming a standard in cardiac care diagnostics. The technological edge provided by AI might give HeartBeam a competitive advantage in a rapidly evolving market.
New Data Presented at Heart Rhythm Society Conference Demonstrates Continued Progress with Company’s AI Program
Data Show That Applying AI to VCG Data Provides More Consistent and Reliable Detection of Atrial Flutter
In the study, HeartBeam AI was applied to a set of 173 VCGs, single-lead ECGs and 12-lead ECGs to identify atrial flutter. The same set of single-lead ECGs and 12-lead ECGs was reviewed by a panel of three electrophysiologists (EP panel) for atrial flutter, a common arrhythmia that significantly increases a patient’s risk for stroke. Key findings from the analysis show that HeartBeam AI combined with VCG:
-
Outperformed an expert panel reviewing single-lead ECGs, with a statistically significant
40% improvement in the detection of atrial flutter cases (sensitivity:97.3% for HeartBeam AI+VCG vs.69.4% for EP panel). -
Demonstrated a statistically significant
6% improvement in the detection of atrial flutter cases compared to an expert panel reviewing 12-lead ECGs (sensitivity:97.3% for HeartBeam AI+VCG vs.91.1% for EP panel). - Delivered zero variability in the detection of atrial flutter compared to the EP panel.
Additional details about the study can be found here.
Dr. Lampert commented, “The modern vectorcardiogram is nearly 100 years old, and yet we are cautiously breathing new life into it with the advent of novel acquisition technologies and deep learning algorithms. This study demonstrates that a deep learning algorithm applied to a transformed VCG performs comparably as well when applied to the gold-standard 12-lead ECG. The AI algorithm overall outperformed a panel of electrophysiologists in distinguishing atrial flutter from sinus rhythm with perfect agreement between multiple model predictions compared to significant interobserver variability amongst electrophysiologists, a finding particularly notable on single lead ECG analysis.”
HeartBeam’s core vectorelectrocardiography (3D VECG) technology captures the heart’s signals in three projections (X, Y, Z), similar to VCG, and synthesizes a 12-lead ECG. The Company’s first planned application of the 3D VECG platform technology is HeartBeam AIMIGo™, a credit card-sized device for patient use at home or anywhere, which is currently under review with FDA.
By leveraging AI to analyze the data-rich signals, HeartBeam believes it will be able to improve diagnostic accuracy and to unlock a more personalized approach to cardiac care for patients. As a patient uses AIMIGo over time, there will be a series of ECG readings. HeartBeam aims to leverage AI to analyze the data to provide a longitudinal view of the patient’s cardiac status and move beyond today’s 12-lead ECGs, which typically only provide a snapshot in time.
“The data is incredibly encouraging, showcasing the potential of our artificial intelligence program to improve diagnostic accuracy when a patient is outside of a medical facility,” said Branislav Vajdic, PhD, CEO and Founder of HeartBeam. “We’ll continue to build upon this strong foundation as we advance our AI program to revolutionize cardiac care management in the future.”
Dr. Lampert has no relevant conflicts of interest and HeartBeam did not fund his participation in this work or make the decision to submit the analysis for presentation.
About HeartBeam, Inc.
HeartBeam, Inc. (NASDAQ: BEAT) is a medical technology company that is dedicated to transforming cardiac care through the power of personalized insights. The company’s proprietary vectorelectrocardiography (VECG) technology collects 3D signals of the heart’s electrical activity and converts them into a 12-lead ECG. This platform technology is designed to be used on portable, patient-friendly devices such as a credit-card sized monitor, watch or patch. Physicians will be able to identify cardiac health trends and acute conditions and direct patients to the appropriate care – all outside of a medical facility, thus redefining how cardiac health is managed in the future. For additional information, visit HeartBeam.com.
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Source: HeartBeam, Inc.
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