Microvascular dysfunction, particularly endothelial dysfunction, is increasingly recognized as a key mechanism underlying various cardiovascular diseases (CVD), including heart failure, ischemic heart disease, atherosclerosis, stroke, dementia, and kidney failure. Chronic low-grade inflammation linked to metabolic syndrome may further drive systemic microvascular impairment. Early detection of these subclinical processes using non-invasive assessments could facilitate timely interventions to prevent disease progression. SCAPIS 2 Spectrum is a prospective observational sub-study of the Swedish Cardiopulmonary Bioimage Study (SCAPIS-2), recruiting approximately 900 subjects aged 60-75 years. The study is organized into five arms-obstructive coronary artery disease (O-CAD), angina with nonobstructive coronary arteries (ANOCA), metabolic syndrome with diabetes, left ventricular systolic dysfunction, and left ventricular diastolic dysfunction-each defined by specific inclusion and exclusion criteria. Participants will undergo a comprehensive microvascular assessment using investigational devices (including Perimed Periflux EPOS, PeriCam MultiFlow, and TCI P4) alongside stress cardiac magnetic resonance imaging (stress-CMR) for cardiac-specific evaluation.
Non-invasive microvascular Assessment A comprehensive microvascular evaluation is performed using three investigational devices designed to capture detailed information on dermal perfusion. The Perimed Periflux 6000 EPOS employs diffuse reflectance spectroscopy (DRS) and laser Doppler flowmetry (LDF) for a single-point multi-modal assessment. The PeriCam MultiFlow performs imaging of dermal perfusion using multi-exposure laser contrast imaging (MELSCI) and measures blood oxygen saturation via multispectral imaging (MSI). Additionally, the TCI P4 utilizes spatial frequency domain imaging technology for quantification of perfusion and chromophore concentrations in the skin. Functional methods, including Post-Occlusive Reactive Hyperemia (PORH), Flow-Motion Analysis, and Thermal Provocation, are applied to assess dynamic microvascular responses. Cardiac Magnetic Resonance Imaging (CMR) Stress#CMR is conducted using adenosine infusion and contrast enhancement to evaluate cardiac-specific microvascular function. This approach includes first-pass perfusion imaging and quantitative myocardial blood flow analyses, which allow for calculation of myocardial perfusion reserve.
Study Type
OBSERVATIONAL
Enrollment
900
Danderyd Hospital
Stockholm, Danderyd, Sweden
RECRUITINGCorrelation between device-derived skin microcirculation variables and CCTA severity metrics including CAD-RADS (0-5) and plaque burden
Assess the correlation between skin microcirculation parameters measured by investigational devices (icluding PORH; 42°C local heat plateau; flow-motion endothelial-band power; iontophoresis acetylcholine response), coronary CT angiography (CCTA) severity metrics: CAD-RADS score, 0-5, zero is equivalent to no plaque and 5 indicates complete occlusionan (fully blocked) and Plaque burden indices (e.g., Segment Involvement Score \[SIS\]) The device-derived microcirculation parameters are: Baseline perfusion, Perfusion after provocation, Peak perfusion, Time to peak, Recovery time, Capillary recruitment and Oxygen saturation (StO₂) The goal is to determine if these microcirculation measurements reflect coronary disease severity.
Time frame: Baseline
Discriminative performance of device-derived microcirculatory variables for significant coronary stenosis
Evaluate the ability of microcirculatory variables measured by investigational devices to discriminate between patients with and without significant coronary stenosis, defined as CAD-RADS ≥ 3 (≥50% luminal narrowing on coronary CT angiography).
Time frame: Baseline
Proportion of ANOCA participants (CAD-RADS <3 with angina per Rose questionnaire) who meet CMD criteria on stress-cardiac MRI using perfusion assessment
Calculate the proportion of participants classified as ANOCA (defined as CAD-RADS \< 3 and angina symptoms per Rose Angina Questionnaire) who fulfill criteria for coronary microvascular dysfunction (CMD) based on stress cardiac MRI perfusion assessment according to site-standard protocols
Time frame: Baseline
Proportion of INOCA participants (CAD-RADS <3 with ishemia per Rose questionnaire) who meet CMD criteria on stress-cardiac MRI using perfusion assessment.
Calculate the proportion of participants classified as INOCA (CAD-RADS \< 3 and objective ischemia evidence) who fulfill CMD criteria based on stress cardiac MRI perfusion assessment..
Time frame: Baseline and at stress cardiac MRI- visit within 3 months
Proportion of ANOCA participants who have INOCA
Among participants identified with ANOCA (non-obstructive coronary artery disease on CT angiography), the proportion who demonstrate myocardial ischemia (INOCA) will be calculated. Ischemia will be assessed using cardiac MRI stress perfusion imaging, which is considered the gold standard for myocardial microcirculatory dysfunction
Time frame: Baseline and at stress cardiac MRI- visit within 3 months
Assess whether peripheral microvascular function reflects myocardial perfusion abnormalities in CMD and mild CAD
This outcome examines whether skin microcirculation parameters measured by investigational devices correlate with quantitative/ semiquantitative myocardial perfusion metrics obtained from stress cardiac-MRI in participants with: Coronary Microvascular Dysfunction (CMD) Non-obstructive coronary disease (CAD-RADS \<3)
Time frame: Baseline and at stress cardiac MRI- visit within 3 months
Correlation between investigational device variables and presence of Coronary Microvascular Dysfunction (CMD).
Evaluate whether distinct cut-off values in device-derived microvascular parameters correlate with significant CMD. CMD will be defined by cardiac MRI stress perfusion imaging. The following variables will be assessed using investigational devices
Time frame: Baseline and at stress cardiac MRI- visit within 3 months
Correlation of skin microcirculation variables with echocardiographic marker for diastolic function
Assess the general correlation between investigational device variables and E/é ratio (echocardiographic marker) to assess diastolic function. A high E/é ratio suggests elevated left atrial pressure and impaired relaxation (diastolic dysfunction). A low E/é ratio indicates normal filling pressures.
Time frame: Baseline
Association of skin microcirculation variables with elevated echocardiographic marker for diastolic dysfunction.
Determine whether investigationnal device-derived variables correlate with E/é \> 15, indicative of increased left ventricular filling pressures.
Time frame: Baseline
Correlation of skin microcirculation variables with biomarker for cardiac stress
Assess general correlation between investigationnal device-derived variables and ProBNP as a biomarker of cardiac stress.
Time frame: Baseline
Association of skin microcirculation variables with elevated biomarker for measuring cardiac stress
Assess general correlation between investigationnal device-derived variables s and ProBNP as a biomarker of cardiac stress.
Time frame: Baseline
Identification of device variable thresholds predicting diastolic dysfunction/heart failure
Evaluate whether specific cut-off values of investigational device-derived microcirculation variables are associated with confirmed dysfunction/heart failure
Time frame: Baseline and at stress cardiac MRI- visit within 3 months
Correlation of skin microcirculation variables with high levels of a biomarker for average blood glucose
Calculate the correlation between the respective variables of the investigational devices and the incidence of HbA1c being \> 65 mmol/mol.
Time frame: Baseline
Correlation of device-derived microcirculation variables with nephropathy
Calculate the correlation between the respective variables of the investigational devices and the incidence of nephropathy
Time frame: Baseline
Correlation betweed device-derived microcirculatory variables with endothelial/glycocalyx/inflammation biomarkers
Correlation between microcirculatory variables from investigational devices and biomarker panels (thrombomodulin, circulating endothelial cells, VE-cadherin, syndecan-1, hyaluronan, hsCRP, IL-6, GlycA).
Time frame: Baseline
Correlation of Myogenic Response with Cardiovascular Disease
Asses the association between myogenic response from device-derived variables and cardiovascular disease incidence; includes incidence of myogenic vs endothelial dysfunction.
Time frame: Baseline
Association of Vascular Inflammation with Microcirculatory Variables
Correlation between systemic inflammation biomarkers (e.g., hsCRP, IL-6, GlycA) and device-derived microcirculatory measures; exploratory detection of early inflammatory alterations.
Time frame: Baseline
Mechanisms of endothelial damage and Cardiovascular Disease devlopment
Analysis of biomarker panels (endothelial/glycocalyx damage: thrombomodulin, VE-cadherin, syndecan-1, hyaluronan) to identify progression patterns and explore the correlation with device-derived microcirculatory variables.
Time frame: Baseline
Development of multi-modal Cardiovascular Disease risk score
Creation and validation of a composite risk score integrating microcirculatory variables derived from investigationa devices and biomarker data; evaluation of predictive performance for Cardiovascular Disease endpoints.
Time frame: Baseline
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