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CardiomyopathiesAID-MRINCT05793840

International Study of Artificial Intelligence-based Diagnosis of Cardiomyopathy Using Cardiac MRI (AID-MRI)

An observational study of Cardiomyopathies, run by University of Calgary at 2 sites in Canada.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
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Trial summary

The goal of this observational study is to test the accuracy of computer (machine learning-based) algorithms to diagnosis heart diseases and predict if and when heart complications will occur. Read more about this study

Who is it for?
Ages 18 years and older
Conditions the study is for
Cardiomyopathies
How many people
1,100 participants
Where
2 sitesCanada
Study dates
30 Jun 2023to 30 Jul 2025
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: Patients referred to CMR clinical services at recruiting medical centers for the evaluation of known or suspected ischemic or non-ischemic cardiomyopathy.

Who may be able to join

  • Must have provided informed consent in a manner approved by the Investigator's Institutional Review Board (IRB) prior to any study-related procedure being performed. If a participant is unable to provide informed consent due to his/her medical condition, the participant's legally authorized representative may consent on behalf of the study participant, as permitted by local law and institutional Standard Operating Procedures
  • Age ≥18 years at the time of informed consent;
  • In-patient or out-patient referral for CMR imaging;
  • Referral for suspected acute or chronic cardiomyopathy state(s) of ischemic and/or non-ischemic etiology;
  • Recently drawn (≤180 days) and available serum laboratory markers of hemoglobin, hematocrit, and creatinine;
  • Willing and able to abide by all study requirements

Who cannot join

  • Standard contraindication(s) to magnetic resonance imaging performance based upon local site policies;
  • Able to breath hold (i.e. real-time cine imaging not supported);
  • Current or recent (≤ 60 days) pregnancy;
  • Current or recent (≤ 60 days) sepsis requiring intubation;
  • Cardiac implantable electronic implanted device (CIED) of any type (excluded due to likelihood of reduced image quality and anticipated influence on algorithm performance), inclusive of permanent pacemaker, implantable cardioverter defibrillator or implantable loop recorder;
  • Severe aortic valve stenosis (i.e., mean AVG >40 mmHg);
  • Prosthetic valve (mechanical or bioprosthetic) in mitral or aortic position
  • Congenital heart disease, inclusive of any surgically-corrected disease, dextrocardia, Tetralogy of Fallot, uncorrected partial anomalous pulmonary venous return, or large atrial septal defect (Qp:Qs ≥1.5) [Note: bicuspid aortic valve disease is not an exclusion criterion in isolation];

Trial locations and contacts

2 sites in 1 country.

Canada2 sites

  • Foothills Medical Centre

    Calgary, Alberta, T2N2T9

  • South Health Campus

    Calgary, Alberta, T3M1M4

Other trials in Canada

About this study

The goal of this observational study is to test the accuracy of computer (machine learning-based) algorithms to diagnosis heart diseases and predict if and when heart complications will occur. The AID-MRI research team has developed algorithms aimed at modelling 3D heart structure and movement (deformation), showing these may be of value to achieve these tasks. The International AID-MRI study aims to test the performance of these algorithms across 11 international sites, using data obtained from a broad variety of patients using different MRI scanners. In addition to an established cohort of 10,000 patients, AID-MRI will recruit an additional 1100 patients from its international sites, these serving as an external validation cohort.

Read the detailed description

There are many types of heart muscle diseases that can reduce heart function or lead to heart rhythm problems, these collectively called cardiomyopathies. Cardiac MRI is a non-invasive test without radiation that can be used to diagnose these diseases as well as help to predict future complications. Currently, the interpretation of these tests relies on the experience of physicians looking at these images and their ability to recognize specific features. However, computers can be trained to pick up more subtle features of disease from images that a human may not see, and can be more rapidly trained from thousands of cases where the final diagnosis has already been confirmed. The AID-MRI research team has collected cardiac MRI images and heart diagnoses from over 10,000 patients in Alberta, Canada and is using this data to train computer algorithms to diagnose heart disease and predict if heart complications will occur in the future. The International AID-MRI study is a publicly funded, investigator initiated study testing the accuracy of these algorithms to accomplish these tasks in an international setting.

The primary approach being tested is conversion of raw 2D cine MRI images into a standardized 4D model of cardiac shape and deformation. This approach has been shown to allow computer algorithms to recognize different cardiomyopathies. We will test the ability of this data to inform computer algorithms to i) decide what disease a patient has, and ii) predict if a patient will experience a major cardiac complication in the near future. The value and influence of other non-imaging data (i.e., patient features), to improve performance will also be assessed.

Keywords
deep learning, cardiac mri, strain analysis
Medical subject headings
Cardiomyopathies

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Prediction accuracy

    The primary endpoint is performance gains using 3D myocardial deformation analysis (3D-MDA) classification versus raw image-based classification. The primary outcome will be assessed in 1,000 externally recruited subjects.

    For diagnostic models, performance will be described by AUC, Precision, Recall and F1 for each disease class. Predicted disease class will be defined as the highest probability observed across all possible classes. Ground truth will be assigned by pre-defined diagnostic criteria by enrolling site PIs following CMR interpretation with access to medical records.

    For prognostic models, algorithm-predicted major adverse cardiovascular events (MACE) will be tested from CMR to first observed MACE. Both regression (time to event) and classification modelling (at 1-year and 2-year time points) will be assessed. Classification performance will be assessed similar to diagnostic models. Regression performance will be assessed by time-dependent AUC (tAUC).

    Measured: 2 years

Secondary outcomes (1)

  1. Secondary Efficacy

    The secondary outcomes of AID-MRI are aimed at identifying the influence of bias in AI-model performance and to assess the capacity of image pre-processing using 3D-MDA to mitigate such influence and improve generalizability. This will be achieved through stratified analyses of the primary endpoint across pre-defined sub-groups of the prospectively recruited patient population.

    These analyses will include the following:

    • Comparative model performance in female versus male birth sex
    • Comparative model performance in major ethnicity subgroups
    • Comparative model performance in binary versus non-binary gender
    • Comparative model performance based on vendor hardware and field strength

    Measured: 2 years

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted31 Mar 2023
  2. Study start30 Jun 2023
  3. Primary completion31 Dec 2024 (estimated)
  4. Study completion30 Jul 2025 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Prospective
Enrolment
1,100 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT05793840
Sponsor's protocol ID
AID-MRI-001
Acronym
AID-MRI
Status last verified
Mar 2024
First submitted
22 Jun 2022
Last updated
13 Mar 2024
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Yes: A user consortium will be established to access collective data resources contributing to the AID-MRI study. Each participating site will be permitted to submit voluntary withdrawal from the consortium at any time with complete removal of data resources. Proposed studies leveraging AID-MRI consortium data resources will be reviewed and must be approved the steering committee. Data resources will be accessed on a secure server "under glass", meaning that data resources cannot be removed from the host's environment. Requesting teams will be responsible for establishing and maintaining their own environment for data analyses on a provisioned virtual machine.

Questions about this trial

What is this clinical trial studying?

An observational study of Cardiomyopathies, run by University of Calgary at 2 sites in Canada.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 6 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 13 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 2 sites in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Prediction accuracy (time frame: 2 years). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT05793840.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Mar 2024.

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