AI Device for Pulmonary Hypertension in Interstitial Lung Disease

(MOMENTOUS Trial)

Recruiting at 17 trial locations

Overseen By Momentous Study

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Tempus AI

Must not be taking: Pulmonary hypertension therapies

Disqualifiers: Pulmonary hypertension, Low ejection fraction, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

1000 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests an AI device that uses heart activity data from an ECG to predict hidden pulmonary hypertension (high blood pressure in the lungs) in individuals with interstitial lung disease (a group of lung disorders). The aim is to identify those at high risk for earlier intervention. Participants will be grouped based on the device's risk assessment, with some receiving additional tests and others following usual care. The study seeks individuals with interstitial lung disease who are unaware of having pulmonary hypertension. As an unphased trial, it offers participants the chance to contribute to innovative research that could lead to earlier diagnosis and improved care for others with similar conditions.

Do I have to stop taking my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the study team or your doctor.

What prior data suggests that this ECG-based AI device is safe for predicting pulmonary hypertension in interstitial lung disease?

Research has shown that AI devices using ECG (a test that records heart activity) are generally easy to use and well-tolerated. Studies have found that these devices can help predict the risk of high blood pressure in the lungs for people with certain lung diseases. No major reports of problems have emerged from using these AI tools, suggesting they are safe for this purpose.

The AI device analyzes heart activity to help doctors identify patients who might need further tests for lung issues. Although this device is new for this specific use, similar AI tools have been used safely in other areas. So far, users of these types of AI devices have not reported any major problems. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the ECG-based AI device because it offers a new way to detect pulmonary hypertension in patients with interstitial lung disease. Unlike traditional methods that rely on more invasive procedures, this AI device uses ECG data to assess the risk level, potentially allowing for quicker and less invasive evaluations. The device's ability to return results directly to healthcare providers offers a personalized approach, enabling more tailored diagnostic decisions. This innovation could lead to earlier detection and improved management of pulmonary hypertension, making it a game-changer in the field.

What evidence suggests that this AI device is effective for predicting pulmonary hypertension in interstitial lung disease?

Research has shown that an AI device using ECGs (electrocardiograms) can help detect high blood pressure in the lungs, known as pulmonary hypertension, in people with lung disease. In this trial, participants will be assigned to different arms to evaluate the AI device's effectiveness. Some participants will be in the "High Risk Device" arm, where the device result will be returned to the treating provider, and they will undergo a study-sponsored diagnostic work-up. Others will be in the "Not High Risk Device" arm, where the device result will also be returned, but participants will continue with standard care evaluations. Studies have found that this AI tool can identify patients with high pressure in their lung arteries and predict their risk for future heart problems. By using ECGs, the AI device can detect issues early, potentially leading to quicker diagnosis and treatment. Initial results suggest that this noninvasive method could improve patient health by identifying the condition sooner. This technology represents an exciting advancement in managing pulmonary hypertension. ^{1 4 5 6 7}

Are You a Good Fit for This Trial?

This trial is for people with a known case of interstitial lung disease who can consent to and undergo all study procedures. It's not suitable for those who cannot follow the required steps or have conditions that would exclude them from safely participating.

Inclusion Criteria

I agree to participate in all required study procedures.

I have been diagnosed with interstitial lung disease.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline Assessment

Participants receive a 12-lead ECG to assess risk of undiagnosed pulmonary hypertension

1 week

1 visit (in-person)

Randomization and Diagnostic Evaluation

Participants are randomly assigned to Device or Control group; high-risk participants in the Device group undergo additional diagnostic tests

6 months

Multiple visits as needed

Follow-up

Participants are monitored for new diagnoses of pulmonary hypertension

6 months

What Are the Treatments Tested in This Trial?

Interventions

• ECG-based AI Device

Trial Overview The MOMENTOUS study tests an ECG-based AI device's ability to predict undiagnosed pulmonary hypertension in ILD patients. Participants are randomly chosen to either know their AI results or not, followed by echocardiograms and heart catheterizations as needed.

How Is the Trial Designed?

Group I: Not High Risk Device Experimental Treatment 1 Intervention

The device result will be returned to the treating provider. Participants will continue to be evaluated for PH according to the current standard of care with any diagnostic procedures ordered at the discretion of the treating provider.

Group II: Not High Risk Control Arm Experimental Treatment 1 Intervention

The device result will not be returned to the treating provider. Participants will continue to be evaluated for PH according to the current standard of care with any diagnostic procedures ordered at the discretion of the treating provider.

Group III: High Risk Device Experimental Treatment 2 Interventions

The device result will be returned to the treating provider and participants will undergo a study sponsored diagnostic work-up consisting of a transthoracic echocardiogram and an RHC.

Group IV: High Risk Control Arm Experimental Treatment 1 Intervention

The device result will not be returned to the treating provider. Participants will continue to be evaluated for PH according to the current standard of care with any diagnostic procedures ordered at the discretion of the treating provider.

Who Is Running the Clinical Trial?

Tempus AI

Lead Sponsor

Trials

18

Recruited

20,700+

United Therapeutics

Industry Sponsor

Trials

112

Recruited

14,500+

Dr. Martine Rothblatt

United Therapeutics

Chief Executive Officer since 1996

PhD in Medical Ethics from the Royal London College of Medicine and Dentistry, JD and MBA from UCLA

Dr. Michael Benkowitz

United Therapeutics

Chief Medical Officer since 2023

MD from Harvard Medical School

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT06911632

Multi-site Study of the Clinical Impact of an AI-assisted ... Interventional Model Description: An ECG-based AI device, will provide a prediction of a participant's risk of having undiagnosed pulmonary hypertension.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC9627911/

Artificial Intelligence-Enabled Electrocardiogram Improves the ... The ECG-based AI model identified patients with ePAP and predicted their future risk for cardiovascular mortality. This model could serve as a ...

3. publications.ersnet.org publications.ersnet.org/content/erj/64/1/2400192

An electrocardiogram-based AI algorithm for early detection of ... The PH-EDA is a noninvasive, ECG-based algorithm that has the potential to accelerate the diagnosis and management of patients with PH.

4. research-studies.allinforhealth.info research-studies.allinforhealth.info/us/en/listing/13538/momentous-study-impact-of/

MOMENTOUS study (iMpact Of an ecg ai ModEl This study investigates the use of an ECG-based artificial intelligence (AI) device to assess the risk of undiagnosed pulmonary hypertension ...

5. sciencedirect.com sciencedirect.com/science/article/pii/S2666668525000588

The role of artificial intelligence and mobile health in ... Deep learning applied to echocardiography achieves expert-level PAH classification and provides automated right-heart quantification while CT/CMR-based models ...

6. trialx.com trialx.com/clinical-trials/listings/300797/multi-site-study-of-the-clinical-impact-of-an-ai-assisted-approach-to-referring-patients-with-interstitial-lung-disease-for-diagnostic-evaluation-of-pulmonary-hypertension/

Multi-site Study of the Clinical Impact of an AI-assisted ... The goal of this study is to evaluate the use of an ECG-based AI device that may help predict if participants with interstitial lung disease ( ...

7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12322453/

AI-powered evaluation of lung function for diagnosis ... AI-guided interpretation of pulmonary function tests significantly increases the identification of interstitial lung disease and thus provides ...