Quantitative Stress Echocardiography to Diagnose Myocardial Ischaemia

• Conditions: Ischemia, Myocardial
• Interventions: Diagnostic Test: Deformation imaging

• Registration Number: NCT03659526
• Lead Sponsor: University Hospital of Wales

Brief Summary

Patients with chest pain on exertion need a reliable non-invasive test to identify if they have inducible myocardial ischaemia. This would reduce the use of diagnostic coronary arteriography, avoid its risks and costs, and guide clinical decisions. Conventional stress echocardiography has poor reproducibility because it relies on qualitative and subjective interpretation. Quantitative approaches based on precise and reliable measurements of myocardial velocity, strain, strain rate and global longitudinal strain have been shown to be able to accurately diagnose myocardial ischaemia. A more accurate test using myocardial velocity imaging was not implemented by ultrasound vendors although it provided an objective measurement of myocardial functional reserve on a continuous scale from normality to severe ischaemia.

The investigators propose an original approach to create a diagnostic software tool that can be used in routine clinical practice. The investigators will extract and compare quantitative data obtained through myocardial velocity imaging and speckle tracking in subjects who undergo dobutamine stress echocardiography.

The data will be analysed using advanced computational mathematics including multiple kernel learning and joint statistics applied to multivariate data across multiple dimensions (including velocity, strain and strain rate traces). This approach will be validated against quantitative coronary arteriography and fractional flow reserve. The results will be displayed as parametric images and placed into a reporting tool. The output will determine the presence and severity of myocardial ischaemia. These new tools will have the capacity for iterative learning so that the precision of the diagnostic conclusions can be continuously refined.

Detailed Description

Not available

Study Timeline

• Study Start: 2016-01-21
• Study First Submitted: 2018-08-17
• Status Verified: 2018-09
• Study First Submitted QC: 2018-09-02
• Last Update Submitted: 2018-09-02
• Study First Posted: 2018-09-06
• Last Update Posted: 2018-09-06
• Primary Completion: 2020-10-31
• Study Completion: 2021-10-31

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 390

Inclusion Criteria

• Chest pain, chest pain equivalent

Exclusion Criteria

• acute coronary syndrome with elevated troponin, severe heart valve disease, uncontrolled hypertension (resting SBP >200mmHg), cardiomyopathy, contraindication to dobutamine, pregnancy

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Deformation imaging	Deformation imaging	Significant coronary disease (diameter stenosis \>50%) has been diagnosed on arteriography or on CT angiography. Fractional flow reserve will be measured as the reference criterion.
High p(CAD)	Deformation imaging	Intermediate-to-high probability of significant epicardial coronary disease (\>50%).
Control	Deformation imaging	Healthy volunteers or if they have had normal invasive or CT coronary arteriography or other functional imaging test
All comers	Deformation imaging	Probability of severe disease ranging from 15 to 85%.

Primary Outcome Measures

Name	Time	Method
Diagnostic accuracy of quantitative measures of dobutamine stress echocardiography	18 months	Echocardiographic measurements of segmental myocardial velocity, strain, strain rate and wall motion scoring referenced against measurements derived from coronary angiography.

Secondary Outcome Measures

Name	Time	Method
Lowest dose of dobutamine to provoke measurable marker of inducible myocardial ischaemia	18 months	Using modelling techniques applied predict lowest dose of dobutamine to maintain diagnostic accuracy
Diagnostic accuracy of using machine learning to interpret multiparametric and multidimensional datasets to diagnose myocardial ischaemia	18 months	Use modelling to combine pre-test probabilities (based on risk factors such as age), physiological factors (e.g., heart rate) that are associated with longitudinal function and data derived throughout the cardiac cycle (i.e., based on analysis of velocity or strain curves and not just a single value like peak velocity or strain).

Trial Locations

Locations (4)

Danderyd Hospital; 🇸🇪 Stockholm, Sweden

UZ Leuven; 🇧🇪 Leuven, Belgium

University Hospital Wales; 🇬🇧 Cardiff, United Kingdom

Castle Hill Hospital; 🇬🇧 Cottingham, United Kingdom