Obesity and mental stress are potent risk factors for cardiovascular disease but their relationship with each other is unclear. Resilience to stress may differ according to adiposity. Early studies that addressed this are difficult to interpret due to conflicting findings and limited methods. Recent advances in assessment of cardiovascular stress responses and of fat distribution allow accurate assessment of associations between adiposity and stress responsiveness. We measured responses to the Montreal Imaging Stress Task in healthy men (N = 43) and women (N = 45) with a wide range of BMIs. Heart rate (HR) and blood pressure (BP) measures were used with novel magnetic resonance measures of stroke volume (SV), cardiac output (CO), total peripheral resistance (TPR) and arterial compliance to assess cardiovascular responses. Salivary cortisol and the number and speed of answers to mathematics problems in the task were used to assess neuroendocrine and cognitive responses, respectively. Visceral and subcutaneous fat was measured using T2 *-IDEAL. Greater BMI was associated with generalised blunting of cardiovascular (HR:β = −0.50 bpm.unit−1, P = 0.009; SV:β = −0.33 mL.unit−1, P = 0.01; CO:β = −61 mL.min−1.unit−1, P = 0.002; systolic BP:β = −0.41 mmHg.unit−1, P = 0.01; TPR:β = 0.11 WU.unit−1, P = 0.02), cognitive (correct answers: r = −0.28, P = 0.01; time to answer: r = 0.26, P = 0.02) and endocrine responses (cortisol: r = −0.25, P = 0.04) to stress. These associations were largely determined by visceral adiposity except for those related to cognitive performance, which were determined by both visceral and subcutaneous adiposity. Our findings suggest that adiposity is associated with centrally reduced stress responsiveness. Although this may mitigate some long-term health risks of stress responsiveness, reduced performance under stress may be a more immediate negative consequence.

BackgroundReal-time cardiovascular magnetic resonance (CMR) assessment of ventricular volumes and function enables data acquisition during free-breathing. The requirement for high spatiotemporal resolution in children necessitates the use of highly accelerated imaging techniques.MethodsA novel real-time balanced steady state free precession (bSSFP) spiral sequence reconstructed using Compressed Sensing (CS) was prospectively validated against the breath-hold clinical standard for assessment of ventricular volumes in 60 children with congenital heart disease. Qualitative image scoring, quantitative image quality, as well as evaluation of biventricular volumes was performed. Standard BH and real-time measures were compared using the paired t-test and agreement for volumetric measures were evaluated using Bland Altman analysis.ResultsAcquisition time for the entire short axis stack (~ 13 slices) using the spiral real-time technique was ~ 20 s, compared to ~ 348 s for the standard breath hold technique. Qualitative scores reflected more residual aliasing artefact (p < 0.001) and lower edge definition (p < 0.001) in spiral real-time images than standard breath hold images, with lower quantitative edge sharpness and estimates of image contrast (p < 0.001).There was a small but statistically significant (p < 0.05) overestimation of left ventricular (LV) end-systolic volume (1.0 ± 3.5 mL), and underestimation of LV end-diastolic volume (− 1.7 ± 4.6 mL), LV stroke volume (− 2.6 ± 4.8 mL) and LV ejection fraction (− 1.5 ± 3.0%) using the real-time technique. We also observed a small underestimation of right ventricular stroke volume (− 1.8 ± 4.9 mL) and ejection fraction (− 1.4 ± 3.7%) using the real-time imaging technique. No difference in inter-observer or intra-observer variability were observed between the BH and real-time sequences.ConclusionsReal-time bSSFP imaging using spiral trajectories combined with a compressed sensing reconstruction showed good agreement for quantification of biventricular metrics in children with heart disease, despite slightly lower image quality. This technique holds the potential for free breathing data acquisition, with significantly shorter scan times in children.Electronic supplementary materialThe online version of this article (10.1186/s12968-018-0500-9) contains supplementary material, which is available to authorized users.

Purpose we implemented a golden‐angle spiral phase contrast sequence. A commonly used uniform density spiral and a new ‘perturbed’ spiral that produces more incoherent aliases were assessed. The aim was to ascertain whether greater incoherence enabled more accurate Compressive Sensing reconstruction and superior measurement of flow and velocity. Methods A range of ‘perturbed’ spiral trajectories based on a uniform spiral trajectory were formulated. The trajectory that produced the most noise‐like aliases was selected for further testing. For in‐silico and in‐vivo experiments, data was reconstructed using total Variation L1 regularisation in the spatial and temporal domains. In‐silico, the reconstruction accuracy of the ‘perturbed’ golden spiral was compared to uniform density golden‐angle spiral. For the in‐vivo experiment, stroke volume and peak mean velocity were measured in 20 children using ‘perturbed’ and uniform density golden‐angle spiral sequences. These were compared to a reference standard gated Cartesian sequence. Results In‐silico, the perturbed spiral acquisition produced more accurate reconstructions with less temporal blurring (NRMSE ranging from 0.03 to 0.05) than the uniform density acquisition (NRMSE ranging from 0.06 to 0.12). This translated in more accurate results in‐vivo with no significant bias in the peak mean velocity (bias: −0.1, limits: −4.4 to 4.1 cm/s; P = 0.98) or stroke volume (bias: −1.8, limits: −9.4 to 5.8 ml, P = 0.19). Conclusion We showed that a ‘perturbed’ golden‐angle spiral approach is better suited to Compressive Sensing reconstruction due to more incoherent aliases. This enabled accurate real‐time measurement of flow and peak velocity in children.

The purposes of this study were: (1) to evaluate feasibility and acceptability of MRI augmented cardiopulmonary exercise testing (MR-CPET) in healthy adults and (2) to test whether peak values obtained at conventional and MR-CPET correlate and to demonstrate variation in peak oxygen consumption (VO2) relates to both peak cardiac output (CO) and peak oxygen extraction (ΔcO2). Seventeen healthy adults underwent CPET and MR-CPET using an MR compatible ergometer and CPET system customised for MR use. Continuous aortic flow measurement used a validated UNFOLD-SENSE spiral phase contrast magnetic resonance (PCMR) sequence.Fifteen of 17 volunteers completed exercise; exclusions were due to claustrophobia and inability to effectively master exercise technique. Measures of acceptability were lower but still satisfactory for MR-CPET.There were strong correlations between conventional and MR-CPET for peak VO2 (r = 0.94, p < 0.001); VCO2 (r = 0.87, p < 0.001) and VE (r = 0.88, p < 0.001).Multiple linear regression analysis demonstrated peak CO and ΔcO2 were independent predictors of peak VO2 measured during MR-CPET (β = 0.73 and 0.38 p < 0.0001) and conventional CPET (β = 0.78, 0.28 p < 0.0001).MR-CPET is feasible, acceptable and demonstrates physiology not apparent with conventional CPET. MR-CPET allows differentiation of the contributions of CO and ΔcO2 to variation in peak VO2. We believe that this will be useful in understanding the origin of reduced exercise capacity in cardiac disease.

Purpose: To demonstrate the feasibility of real‐time phase contrast magnetic resonance (PCMR) assessment of continuous cardiac output with a heterogeneous (CPU/GPU) system for online image reconstruction. Materials and Methods: Twenty healthy volunteers underwent aortic flow examination during exercise using a real‐time spiral PCMR sequence. Acquired data were reconstructed in online fashion using an iterative sensitivity encoding (SENSE) algorithm implemented on an external computer equipped with a GPU card. Importantly, data were sent back to the scanner console for viewing. A multithreaded CPU implementation of the real‐time PCMR reconstruction was used as a reference point for the online GPU reconstruction assessment and validation. A semiautomated segmentation and registration algorithm was applied for flow data analysis. Results: There was good agreement between the GPU and CPU reconstruction (−0.4 ± 0.8 mL). There was a significant speed‐up compared to the CPU reconstruction (15×). This translated into the flow data being available on the scanner console ≈9 seconds after acquisition finished. This compares to an estimated time using the CPU implementation of 83 minutes. Conclusion: Our heterogeneous image reconstruction system provides a base for translation of complex MRI algorithms into clinical workflow. We demonstrated its feasibility using real‐time PCMR assessment of continuous cardiac output as an example. J. Magn. Reson. Imaging 2012; 36:1477–1482. © 2012 Wiley Periodicals, Inc.