AI-Detected CAC Notification for Cardiovascular Disease

(HEARTWISE Trial)

Not yet recruiting at 5 trial locations
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Stanford University
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

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.12345

Why 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?

FR

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

My last LDL-C level was 70 mg/dL or higher, or I haven't had it checked in 2 years.
My eligibility may vary based on local guidelines and patient group.
I am enrolled in my site's healthcare plan, or had my LDL-C measured, or was prescribed cardiovascular medication recently.
See 2 more

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants receive AI-based CAC screening and notification intervention to improve cholesterol treatment

6 months
Notification at baseline and potentially at 2 months

Follow-up

Participants are monitored for changes in lipid levels and healthcare resource use

6 months

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

Group I: Early NotificationExperimental Treatment1 Intervention
Group II: Delayed NotificationActive Control1 Intervention

Find a Clinic Near You

Who Is Running the Clinical Trial?

Stanford University

Lead Sponsor

Trials
2,527
Recruited
17,430,000+

Kaiser Permanente

Collaborator

Trials
563
Recruited
27,400,000+

University of California, Los Angeles

Collaborator

Trials
1,594
Recruited
10,430,000+

Amgen

Industry Sponsor

Trials
1,508
Recruited
1,433,000+
Founded
1980
Headquarters
Thousand Oaks, USA
Known For
Human Therapeutics
Top Products
Enbrel, Prolia, Neulasta, Otezla
Robert A. Bradway profile image

Robert A. Bradway

Amgen

Chief Executive Officer since 2012

MBA from Harvard Business School

Paul Burton profile image

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

Trials
18
Recruited
61,200+

Vanderbilt University Medical Center

Collaborator

Trials
922
Recruited
939,000+

Duke University

Collaborator

Trials
2,495
Recruited
5,912,000+

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 ...

AI 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 ...