AI-Detected CAC Notification for Cardiovascular Disease
(HEARTWISE Trial)
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial tests whether AI can identify calcium buildup in heart arteries from existing chest scans to improve cholesterol treatment. The goal is to determine if informing patients and their doctors about this calcium leads to better cholesterol control and more effective heart care. It seeks adults with known heart disease or significant calcium buildup whose cholesterol is not well managed. Participants should have had a chest CT scan in the last two years and be actively engaged with their health system. As an unphased trial, this study offers a unique opportunity to contribute to innovative heart care solutions using AI technology.
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications. It focuses on improving cholesterol treatment, so it's possible that your current medications might be adjusted, but this isn't clearly stated.
What prior data suggests that this AI-based CAC screening and notification intervention is safe?
Research shows that using artificial intelligence (AI) to detect calcium in heart arteries on chest CT scans is generally safe. This AI tool identifies calcium buildup, which can help predict heart disease risk.
Studies have found that this method effectively identifies calcium without harming patients. The FDA has approved the AI tool used in the trial, confirming it meets safety standards for healthcare use. No serious problems have been directly linked to the AI detection process.
Overall, the AI system is well-received and aids doctors and patients in making informed heart health decisions. Joining the trial could contribute to understanding how this technology can improve care.12345Why are researchers excited about this trial?
Researchers are excited about this trial because it leverages AI to enhance cardiovascular disease care by identifying coronary artery calcium (CAC) more effectively. Unlike standard practice, where CAC might just be noted in a radiology report, the AI-detected CAC notification actively alerts both patients and clinicians, prompting them to have a critical risk discussion. This proactive approach could lead to earlier interventions and personalized care, potentially improving patient outcomes by addressing risks sooner.
What evidence suggests that AI-Detected CAC Notification could be effective for cardiovascular disease?
Research shows that using AI to detect calcium in heart arteries can significantly enhance heart care. Studies have found that AI can identify this calcium on CT scans, potentially predicting heart issues like heart disease and stroke. In this trial, participants in the "Early Notification" arm will receive AI-detected CAC notifications, which may lead to earlier and easier diagnoses, aiding doctors in making better treatment decisions. Early results suggest that informing both patients and doctors about this calcium can improve cholesterol treatment. This approach might help manage cholesterol levels more effectively, supporting overall heart health. Meanwhile, participants in the "Delayed Notification" arm will follow standard clinical practice without additional notifications during the study period.36789
Who Is on the Research Team?
Fatima Rodriguez, MD, MPH
Principal Investigator
Stanford University
Are You a Good Fit for This Trial?
This trial is for adults with known heart artery disease or significant calcium in their arteries, and who have high cholesterol levels. They must have had a chest CT scan within the last two years and be part of an integrated healthcare plan or have recent cholesterol measurements or cardiovascular medication prescriptions.Inclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Intervention
Participants receive AI-based CAC screening and notification intervention to improve cholesterol treatment
Follow-up
Participants are monitored for changes in lipid levels and healthcare resource use
What Are the Treatments Tested in This Trial?
Interventions
- AI-Detected CAC Notification and Care Facilitation
Trial Overview
The study tests if AI-based screening to detect calcium buildup in heart arteries on existing CT scans can help manage cholesterol better by notifying patients and doctors. It will check if this leads to more use of cholesterol-lowering treatments, better control of bad cholesterol (LDL), and changes in follow-up care.
How Is the Trial Designed?
2
Treatment groups
Experimental Treatment
Active Control
For participants randomized to notification, the affiliated clinician will receive a message notifying them of the presence of CAC. The notification will include a description of the significance of CAC, provide guideline recommendations, and include a personalized CAC image (as possible). The message will recommend having a risk discussion with the participant. Based on site-level stakeholder feedback, this alert can be retriggered at 2 months for participants who do not have LLT initiation or intensification or LDL-C testing. Participants will also receive a notification. Based on stakeholder input, this notification can be delivered centrally or from individual clinicians. The notification will include a description of the significance of CAC, a personalized image (as possible), and recommend a risk discussion with their clinician.
Participants will have their CT scans interpreted and reported according to standard clinical practice. This may mention the presence of CAC in the official radiology imaging report, per usual practice. Participants will not receive any notification beyond this standard of care during the 6-month study period. The study team will send a similar notification as the early notification arm to the participants after completion of the study's primary endpoint assessment.
Find a Clinic Near You
Who Is Running the Clinical Trial?
Stanford University
Lead Sponsor
Kaiser Permanente
Collaborator
University of California, Los Angeles
Collaborator
Amgen
Industry Sponsor
Robert A. Bradway
Amgen
Chief Executive Officer since 2012
MBA from Harvard Business School
Paul Burton
Amgen
Chief Medical Officer since 2023
MD from University of London, PhD in Molecular and Cellular Biology from Imperial College London
Baylor Scott and White Health
Collaborator
Vanderbilt University Medical Center
Collaborator
Duke University
Collaborator
Citations
Effects of Real-Time Notification of AI-Detected Incidental ...
A total of 172 (85.1%) were without baseline ASCVD—the median 10-year predicted ASCVD risk was 7.0% for PREVENT (Predicting Risk of ...
Artificial intelligence applied to coronary artery calcium ...
We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke.
AI in CAD Care: Current Applications and Future Directions
AI provides earlier, simpler, and faster diagnosis and analysis that could be potential game changers in helping physicians guide cardiac care ...
Using AI to Flag Coronary Artery Calcification
Explore how AI is transforming cardiovascular health by flagging patients with coronary artery calcification and enhancing value-based care.
Artificial Intelligence for Preventing Heart Disease (AiPHD) ...
Furthermore, we plan to create a novel imaging marker of CAD with unfavorable outcome, to be integrated in the AI-based model, which will be based on ...
Health Enhanced Artery Risk Tracking With Widespread ...
The study uses artificial intelligence to detect calcium buildup in heart arteries (coronary artery calcium or CAC) on chest CT scans that ...
Effects of Real-Time Notification of AI-Detected Incidental ...
For patients randomized to notification, the patient's cardiologist or primary care clinician was notified with an image of the patient's CAC ...
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massgeneralbrigham.org
massgeneralbrigham.org/en/about/newsroom/press-releases/ai-detects-hidden-heart-diseaseAI Detects Hidden Heart Disease Using Existing Scans ...
A deep learning algorithm that detects coronary artery calcium levels in chest CT scans – an important marker that predicts the risk of cardiac events and ...
a case-based review | npj Cardiovascular Health
We describe a case that highlights augmentative AI for the incidental detection of coronary artery calcium, a mobile application to improve ...
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