Quantitative myocardial perfusion during stress using CMR is impaired in healthy Middle Eastern immigrants without CV risk factors

Study population and study design

The study was approved by the Regional Ethics Committee of Lund University in Sweden (Dnr 2015/507) and compliant with the Declaration of Helsinki. Written informed consent was given by all participants. A subset of male participants from the previous MEDIM cohort without any signs or established risk factors for CVD were invited to participate in the study. The cohort has been described in detail previously14. Briefly, the MEDIM cohort is a cross-sectional study conducted from 2010 to 2012 among 2155 Iraqi or Swedish residents of Malmö aged 30 to 75. A total of 259 healthy, never-smokers, non-obese men with no risk factors for CVD were identified from the baseline study and invited by mail to participate in the present study. A total of 18 Iraqi-born men and twelve Swedish-born men, of Caucasian origin and none of whom had parents from outside Europe, fulfilled the inclusion criteria and agreed to participate in this CMR sub-study, see Fig. 1A. Exclusion criteria included known cardiovascular disease, diabetes, obesity, kidney disease, history of asthma, smoking, or any active medication. In addition, subjects with clear regional perfusion deficits on CMR were excluded. Subjects were recruited between 2017 and 2019 and examined at Lund University Hospital, Lund, Sweden. All patients underwent rest and adenosine stress CMR and complied with a 24-h caffeine restriction prior to the examination.

Figure 1

(A) Schematic flowchart for eligible participants, all male, performing a cardiovascular magnetic resonance study. (B) CMR analysis protocol timeline with schedules for gadolinium contrast injections.

Basic characteristics and blood samples

Prior to the CMR examination, height, weight, waist circumference and blood pressure (in the supine position) were assessed. Fasting blood glucose, hemoglobin A1c, creatinine, cholesterol, triglycerides, high density lipoproteins, low density lipoproteins and apolipoprotein B/A1 in serum and urine albumin/creatinine were analyzed at young as previously described.5.14. Homeostasis model assessment (HOMA) was used to estimate both insulin resistance (HOMA-IR) and beta cell function (HOMA-β)5. An electrocardiogram was acquired before the CMR examination.

To objectively calculate the ten-year risk of fatal CVD for study participants, the risk scoring systems “Framingham Risk Score for Hard Coronary Heart Disease”15 and “Systematic Coronary Risk Assessment (SCORE)”16 were used including the variables sex, age, systolic blood pressure, total cholesterol and smoking status.

CMR image acquisition

All images were acquired on a CMR Magnetom Aera 1.5 T system (Siemens Healthcare, Erlangen, Germany), see Fig. 1B for an overview of the CMR protocol.

Left ventricular volumes and function

Left ventricular volumes and function were assessed by cine imaging using apnea steady-state free precession (SSFP) sequence in both short-axis and long-axis projections ( 2, 3 and 4 cavity views). Typical imaging parameters included repetition time (TR) = 2.7 ms, echo time (TE) = 1.2 ms, flip angle 60°, spatial resolution 1.5 × 1 .5 × 8 mm without cutting space and field of view (FOV) 270 × 320 mm2.

Quantitative first-pass infusion

A basal image, a mid-ventricular image, and an apical short axis image were acquired at rest and during adenosine stress (Adenosin, Life Medical AB, Stockholm, Sweden, 140 µg/kg/min infusion) using the qFPP imaging during the administration of an intravenous bolus of contrast agent (0.05 mmol/kg, infusion rate 4 ml/s, Gadobutrol, Gadovist, Bayer AB, Solna, Sweden). Stress images were first acquired for 60 heartbeats, starting three minutes after the start of the intravenous adenosine infusion, and rest images were acquired approximately 15 minutes later. Measurements in low-resolution proton density images optimized for high gadolinium concentration in the LV blood pool were used to calculate the arterial input functionten. After motion correction and conversion of signal intensities to gadolinium concentration, myocardial perfusion in ml/min/g was derived on a per-pixel basis10.13. Typical imaging parameters were: SSFP single-shot read, TE 1.0 ms, TR 2.5 ms, flip angle 50°, FOV 360 × 270 mm2slice thickness 8.0 mm, parallel acquisition technique factor 3, acquisition time per single slice 142 ms and saturation delay 105 ms.

Coronary sinus flow

Coronary sinus images were acquired at rest and during adenosine stress for quantification of global perfusion. Resting images were acquired first and stress images were acquired immediately after qFPP images were acquired, approximately 5 minutes later. An apnea phase-contrast CMR with retrospective ECG triggering was used. Typical imaging parameters were: TR 5 ms, TE 2.8 ms, flip angle 20°, parallel imaging factor 2, reconstructed spatial resolution of 1.6 × 1.6 × 8 mm, and encoded velocity factor (VENC) 80 cm/s for rest and 120 cm/s for stress.

Fibrosis and extracellular volume

A modified T1 Look-Locker (MOLLI) sequence was used to generate T1 maps before and after administration of a gadolinium contrast agent. An online extracellular volume map (ECV map) was created after manually entering the hematocrit. Three short axial slices were acquired at the basal, mid-ventricular and apical level. Macroscopic fibrosis was studied using a free-breathing, motion-corrected, late gadolinium enhancement (LGE) sequence acquired in both short-axis and long-axis projections. The reversal time was chosen to nullify the myocardium remotely. The specific parameters for the LGE sequence were: TR 2.8 ms, TE 1.2 ms, flip angle 50°, FOV 360 × 270 mm, resolution 1.4 × 1.4 × 8 mm, no deviation from chopped off.

CMR image analysis

All images were analyzed using Segment software (v2.0 R5378), Medviso AB, Lund, Sweden)17, with the observer blind to the identity of the subject. For all images, the endo- and epicardial borders were delineated manually. Left ventricular (LV) volumes, ejection fraction, and left ventricular mass (LVM) were quantified from the short-axis cine stack. Interobserver variability for LVM was analyzed in six Iraqi controls and six Swedish controls. The rate-pressure product (RPP) was calculated as heart rate × systolic blood pressure for rest and stress.

Quantitative first-pass infusion and ECV

For qFPP and ECV images, the region of interest (ROI) was moved 10% away from the endo- and epicardial borders to avoid inclusion of blood pool or extra-cardiac structures. Myocardial Perfusion (ml/min/g)10.13 and CVS11.12 (%) were assessed manually by drawing an ROI in each short-axis slice. Absolute perfusion could then be extracted directly from the ROI because each pixel contained information about absolute perfusion. Myocardial perfusion and VCE were assessed globally by averaging all acquired short-axis slices. Each short-axis slice in the qFPP images at rest and during exercise was also divided into endocardial (inner 50%) and epicardial (outer 50%) regions. Resting perfusion was corrected for the flow-pressure product (RPP) as resting perfusion × 10,000/((resting heart rate) × (resting systolic blood pressure). Myocardial Perfusion Reserve (MPR) was calculated as the ratio of stress to perfusion at rest and MPR using resting perfusion corrected by RPP was also calculated Transmural gradients of endocardial to epicardial MPR were also calculated Recently, a global stress threshold qFPP 19. We also calculated myocardial perfusion per myocyte mass as qFPP/(1-ECV).

Sinus coronary flow

Overall myocardial perfusion (ml/min/g) was also quantified as CSF (ml/min)/LVM (g)20. LVM for CSF quantification was calculated including papillary muscles and trabeculae by visual thresholding. Interobserver variability for CSF at rest and during exercise was analyzed in six Iraqi and six Swedish controls and for the addition of papillary muscle and trabeculae to the LVM in all subjects.

Late enhancement with gadolinium

Focal fibrosis was assessed on short-axis LGE images by the expectation maximization weighted intensity a priori information (EWA) algorithm. [21].

statistical analyzes

Continuous data are expressed as mean ± standard deviation (SD). Mean values ​​between groups were assessed using Fischer’s exact test, paired or unpaired t-test, as appropriate, in normally distributed data. The relationship between continuous variables was assessed with Pearson’s correlation coefficient. Bland-Altman bias was used to compare coronary qFPP and sinus flow and for interobserver analysis. The univariate association with myocardial perfusion for covariates that differed between groups was analyzed by linear regression. All statistical analyzes were performed using IBM SPSS Statistics (IBM SPSS Statistics 23, IBM, New York, USA) and Graph Pad Prism 7.0 software (Graph Pad Software, Inc., La Jolla, CA , United States). Differences with a P value

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