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

NCT05793840 | Enrolling By Invitation

• 1 other identifier: AID-MRI-001
• Study Type: observational
• Target: 1,100
• Locations: 1 country
• Sites: 2

Brief 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. 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.

Conditions

Cardiomyopathies

Keywords

deep learning; cardiac mri; strain analysis

Outcome Measures

Primary Outcomes (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).

  2 years

Secondary Outcomes (1)

• Secondary Efficacy

  2 years

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

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

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• University of Calgary: lead
• University of Alberta: collaborator

Study Sites (2)

Foothills Medical Centre

Calgary, Alberta, T2N2T9, Canada

Location

South Health Campus

Calgary, Alberta, T3M1M4, Canada

Location

MeSH Terms

Conditions

Cardiomyopathies

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Study Officials

• James White, MD, FRCP(C)

  University of Calgary

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: June 22, 2022
• First Posted: March 31, 2023
• Study Start: June 30, 2023
• Primary Completion: December 31, 2024
• Study Completion: July 30, 2025
• Last Updated: March 13, 2024

Record last verified: 2024-03

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF
• Time Frame: 18 months following completion of study
• Access Criteria: Research only purposes. Submission, review and approval by study steering committee.

Locations

CA (2)