About this trial
The goal of this observational study is to evaluate the diagnostic performance of angiography-derived microcirculatory indices (Angio-IMR) in assessing patients with stable angina or suspected coronary artery disease. The main questions it aims to answer are:
How do the numerical values of Angio-IMR from five different software vendors change across three physiological states (resting, sub-hyperemia induced by nitroglycerin, and maximal hyperemia induced by adenosine)? Which physiological state and software algorithm provide the highest diagnostic accuracy (Area Under the Curve, AUC) for diagnosing Coronary Microvascular Disease (CMD) when compared to the gold standard wire-based IMR? Researchers will compare the Angio-IMR results calculated under the three different physiological conditions within the same patient to see how the hyperemic state impacts the performance and consistency of these non-invasive indices.
Participants will:
Undergo standard-of-care coronary angiography and physiological assessment using a pressure wire for index of microvascular resistance (Wire-IMR) as part of their clinical management.
Have their angiographic images captured at three specific time points: at rest, after intracoronary nitroglycerin, and during adenosine-induced maximal hyperemia.
Allow their de-identified imaging and clinical data to be analyzed by an independent core laboratory using five different Angio-IMR software platforms to evaluate microvascular function.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Stable angina or suspected coronary heart disease.
Scheduled for coronary angiography and physiological assessment.
Target vessel with stenosis < 50% or 50%-90% with fractional flow reserve (FFR) > 0.80.
Provided informed consent.
Disqualifiers
Hemodynamic instability (acute myocardial infarction, cardiogenic shock, severe arrhythmia).
Contraindications to angiography (e.g., end-stage renal disease).
Contraindications to adenosine (e.g., severe asthma, high-degree atrial-ventricular block).
Life expectancy < 1 year or pregnancy.
Trial population
The study population consists of adult patients (aged 18 and older) clinically diagnosed with stable angina or suspected coronary artery disease who are scheduled to undergo conventional coronary angiography and invasive physiological assessment. Participants are prospectively and consecutively recruited from multiple clinical centers in China. The population specifically targets individuals with non-obstructive coronary arteries (stenosis \< 50%) or those with moderate stenosis (50%-90%) but preserved epicardial flow (FFR \> 0.80), where assessment of coronary microvascular function is clinically indicated to investigate the cause of ischemia.
Trial design
Cohort
Prospective
Treatments tested in this trial
Angiography-derived IMR
Diagnostic testUnlike the reference standard "Wire-IMR," which requires the advancement of a specialized pressure-sensor guidewire into the distal coronary artery, Angio-IMR is a wire-free technology. It derives microvascular resistance indices purely through computational fluid dynamics (CFD) or specialized mathematical models based on standard coronary angiographic projections. This eliminates the risk of wire-induced vascular injury or spasm.
Treatment groups
Trial outcomes
Primary outcomes
Area Under the ROC Curve (AUC)
Comparison of AUC for 5 types of Angio-IMR against Wire-IMR (Gold standard, CMD defined as Wire-IMR ≥ 25) under three states.
Secondary outcomes
Diagnostic Accuracy
Sensitivity, specificity, positive predictive value, negative predictive value.
Correlation
Pearson/Spearman coefficients between Angio-IMR and Wire-IMR.
Agreement
Bland-Altman analysis (Bias and Limits of Agreement).
Inter-vendor Agreement
Consistency between different software brands.
Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Shanghai Zhongshan Hospital
Lead sponsor
First Affiliated Hospital, Sun Yat-Sen University
Collaborator
Zhongnan Hospital
Collaborator
The 7th People's Hospital of Zhengzhou
Collaborator