Aortic Stenosis Clinical Trial
Official title:
Artificial Intelligence-based Risk Stratification and Outcome in Patients With Severe Aortic Stenosis Undergoing Cardiac Magnetic Resonance Imaging
Verified date | November 2023 |
Source | Medical University of Vienna |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
Background: Artificial Intelligence (AI) in cardiac imaging has previously been shown to provide highly reproducible and accurate results, outperforming clinical experts. Cardiac magnetic resonance (CMR) imaging represents the gold standard for assessment of myocardial structure and function. However, measurements of more sensitive markers of early left (LV) and right ventricular (RV) function, such as global longitudinal shortening (GLS), mitral annular plane systolic excursion (MAPSE), and tricuspid annular plane systolic excursion (TAPSE), are frequently not performed due to the lack of automated analysis. Objectives: The investigators aim to evaluate whether AI-based measurements of ventricular structure and function convey important prognostic information in patients with severe aortic stenosis (AS) beyond LV and RV ejection fraction (EF) and represent early markers of adverse cardiac remodeling. Materials & Methods: This large-scale international, multi-center, observational study will recruit ~1500 patients with severe AS scheduled for aortic valve replacement (AVR). Patients are invited to undergo CMR imaging prior to AVR and at 12-months post-AVR. An AI-based algorithm, developed in the UK, will be used for fully automated assessment of parameters of cardiac structure (end-diastolic volume, end-systolic volume, LV mass, maximum wall thickness) and function (EF, GLS, MAPSE, TAPSE). Application of the AI-model allows to capture these parameters for large patient cohorts within seconds (as opposed to the current practice of time-consuming manual post-processing). Association of AI-based CMR parameters with clinical outcomes post-AVR will be analyzed. The composite of all-cause mortality and heart failure hospitalization will serve as the primary endpoint. Trajectories of AI-based parameters from pre- to post-AVR will be assessed as a secondary endpoint. Future Outlook: In severe AS, a novel AI-based algorithm allows immediate and precise measurements of ventricular structure and function on CMR imaging. Our goal is to identify early markers of cardiac dysfunction indicating adverse prognosis post-AVR. This has guideline-forming potential as the optimal timepoint for AVR in patients with AS is currently a matter of debate.
Status | Not yet recruiting |
Enrollment | 1500 |
Est. completion date | February 28, 2026 |
Est. primary completion date | September 30, 2025 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Written informed consent - Severe AS scheduled for Heart Team decision Exclusion Criteria: - Inability or unwillingness to perform any of the diagnostic tests - Inability or unwillingness to participate in follow-up visits - Metal implants, e.g. cochlear implants and pacemakers - Chronic kidney failure (GFR < 30 ml/min/1.73m2) |
Country | Name | City | State |
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n/a |
Lead Sponsor | Collaborator |
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Medical University of Vienna |
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | Number of patients with AI-measured parameters of impaired left and right ventricular structure and function on cardiac magnetic resonance imaging at baseline and changes at 1-year follow-up after aortic valve replacement (AVR). | Longitudinal trajectories of AI-based parameters (end-diastolic volume [ml], end-systolic volume [ml], left ventricular mass [gram], maximum wall thickness [mm], ejection fraction [%], global longitudinal shortening [%], mitral/tricuspid annular plane systolic excursion [mm]) on cardiac magnetic resonance imaging from pre- to 1-year post-AVR.
Captured clinical endpoints will include all-cause death, cardiovascular mortality, and heart failure hospitalization. Data will be ascertained by follow-up visits, state-wide electronic hospital charts, and phone calls. In addition, mortality data will be obtained via National Death Registries of the participating countries. CMR will be repeated at 1 year. |
1 year | |
Primary | Number of patients with AI-measured parameters of impaired left and right ventricular structure and function on cardiac magnetic resonance imaging and association with the composite of all-cause death and heart failure hospitalization. | Association of AI-based parameters (end-diastolic volume [ml], end-systolic volume [ml], left ventricular mass [gram], maximum wall thickness [mm], ejection fraction [%], global longitudinal shortening [%], mitral/tricuspid annular plane systolic excursion [mm]) on cardiac magnetic resonance imaging with the composite of all-cause death and heart failure hospitalization.
Captured clinical endpoints will include all-cause death, cardiovascular mortality, and heart failure hospitalization. Data will be ascertained by follow-up visits, state-wide electronic hospital charts, and phone calls. In addition, mortality data will be obtained via National Death Registries of the participating countries. |
2 years | |
Secondary | Number of patients with AI-measured parameters of impaired left and right ventricular structure and function on cardiac magnetic resonance imaging and association with components of the primary endpoint analyzed individually. | Association of AI-based parameters (end-diastolic volume [ml], end-systolic volume [ml], left ventricular mass [gram], maximum wall thickness [mm], ejection fraction [%], global longitudinal shortening [%], mitral/tricuspid annular plane systolic excursion [mm]) on cardiac magnetic resonance imaging with components of the primary endpoint (all-cause death and heart failure hospitalization) analyzed individually.
Captured clinical endpoints will include all-cause death, cardiovascular mortality, and heart failure hospitalization. Data will be ascertained by follow-up visits, state-wide electronic hospital charts, and phone calls. In addition, mortality data will be obtained via National Death Registries of the participating countries. |
2 years | |
Secondary | Number of patients with AI-measured parameters of impaired left and right ventricular structure and function on cardiac magnetic resonance imaging and association with cardiovascular mortality. | Association of AI-based parameters (end-diastolic volume [ml], end-systolic volume [ml], left ventricular mass [gram], maximum wall thickness [mm], ejection fraction [%], global longitudinal shortening [%], mitral/tricuspid annular plane systolic excursion [mm]) on cardiac magnetic resonance imaging with cardiovascular mortality.
Captured clinical endpoints will include all-cause death, cardiovascular mortality, and heart failure hospitalization. Data will be ascertained by follow-up visits, state-wide electronic hospital charts, and phone calls. In addition, mortality data will be obtained via National Death Registries of the participating countries. |
2 years |
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