Abnormal wave reflections and left ventricular hypertrophy late after coarctation of the aorta repair

Patients with repaired coarctation of the aorta are thought to have increased afterload due to abnormalities in vessel structure and function. We have developed a novel cardiovascular magnetic resonance protocol that allows assessment of central hemodynamics, including central aortic systolic blood pressure, resistance, total arterial compliance, pulse wave velocity, and wave reflections. The main study aims were to (1) characterize group differences in central aortic systolic blood pressure and peripheral systolic blood pressure, (2) comprehensively evaluate afterload (including wave reflections) in the 2 groups, and (3) identify possible biomarkers among covariates associated with elevated left ventricular mass (LVM). Fifty adult patients with repaired coarctation and 25 age- and sex-matched controls were recruited. Ascending aorta area and flow waveforms were obtained using a high temporal-resolution spiral phase-contrast cardiovascular magnetic resonance flow sequence. These data were used to derive central hemodynamics and to perform wave intensity analysis noninvasively. Covariates associated with LVM were assessed using multivariable linear regression analysis. There were no significant group differences (P≥0.1) in brachial systolic, mean, or diastolic BP. However central aortic systolic blood pressure was significantly higher in patients compared with controls (113 versus 107 mm Hg, P=0.002). Patients had reduced total arterial compliance, increased pulse wave velocity, and larger backward compression waves compared with controls. LVM index was significantly higher in patients than controls (72 versus 59 g/m(2), P<0.0005). The magnitude of the backward compression waves was independently associated with variation in LVM (P=0.01). Using a novel, noninvasive hemodynamic assessment, we have shown abnormal conduit vessel function after coarctation of the aorta repair, including abnormal wave reflections that are associated with elevated LVM

The assessment of pulmonary haemodynamics with magnetic resonance imaging in pulmonary hypertension

Pulmonary hypertension is a rare disease characterised by high pulmonary vascular resistance. Prognosis depends upon mean pulmonary artery pressure at cardiac catheterisation. Historically, measurements of pulmonary haemodynamics and exercise capacity have been used to detect and monitor disease progression and treatment response, however these approaches have a number of limitations and deficiencies. We wondered whether an alternative strategy would be feasible; monitoring the adaptation response of the heart and pulmonary vasculature to pulmonary hypertension. Magnetic resonance imaging (MRI) is a new and exciting form of imaging with the potential to make accurate anatomical and physiological measurements in the cardiopulmonary circulation. In this thesis we set out to investigate whether anatomical and blood flow measurements made with MRI can detect and quantify raised pulmonary artery pressure at cardiac catheterisation. We then looked to see whether MRI has any advantages over doppler echocardiography, the current gold standard noninvasive investigation. We enrolled twenty-eight subjects who were undergoing cardiac catheterisation and doppler echocardiography for investigation of suspected pulmonary hypertension at the Scottish Pulmonary Vascular Unit between September 1999 and March 2001. We used MRI to measure right and left ventricular mass, volume, and wall thickness, and aortic and pulmonary artery diameter. We calculated a novel ventricular mass index by dividing right ventricular mass by left ventricular mass. We then performed a flow quantification in the right pulmonary artery to measure mean and peak velocity of blood flow, acceleration time and ejection time, and calculated the ratio of acceleration time over ejection time. Finally we attempted to study the changes in these variables following straight leg raising exercise.We found that our ventricular mass index (r = 0.81), right ventricular wall thickness (r = 0.83) and the ratio of main pulmonary artery over aortic diameter (r = 0.82) showed better agreement with mean pulmonary artery pressure than doppler echocardiography (r = 0.77) with sensitivity and specificity at least as good. We found significant correlations between right ventricular mass and end-diastolic volume with left ventricular mass (r = 0.53 and r = 0.83 respectively). This suggests either an association between pulmonary hypertension and left ventricular hypertrophy or a survival advantage in those with more massive left ventricles, perhaps due to decreased ventricular compliance protecting left ventricular filling. Mean and peak velocity of blood flow in the right pulmonary artery were sensitive and specific markers of the presence of pulmonary hypertension, but not of severity. Contrary to the published literature, acceleration time and the ratio of acceleration time over ejection time did not correlate with pulmonary artery pressure. We were able to detect changes in all right pulmonary artery blood flow variables in a small number of subjects after exercise, but we encountered some practical difficulties and the significance of these observations is uncertain.In summary, we have shown that anatomical measurements made in the cardiopulmonary circulation with MRI can be used to estimate pulmonary artery pressure with greater accuracy than doppler echocardiography. These estimates are likely to be more reliable than those provided by echocardiography, and may also give a measure of the recent burden of pulmonary vascular disease. An analogy may be made with the use of glycosylated haemoglobin instead of glucose in diabetes; pulmonary artery pressure fluctuates on a minute by minute basis whereas anatomical measurements reflect sustained changes in pulmonary haemodynamics. It should be said that this approach to the detection and monitoring of pulmonary hypertension has not yet been fully validated. Further work needs to be done to test whether it is sensitive to change in longitudinal follow-up and address the issue of inter and intraobserver reproducibility. Finally, we have also shown that MRI measurements of blood flow are sensitive and specific indicators of pulmonary hypertension, and that it may be possible to use MRI to study exercise-related changes in blood flow

Novel Applications of Cardiovascular Magnetic Resonance Imaging-Based Computational Fluid Dynamics Modeling in Pediatric Cardiovascular and Congenital Heart Disease

Cardiovascular diseases (CVDs) afflict many people across the world; thus, understanding the pathophysiology of CVD and the biomechanical forces which influence CVD progression is important in the development of optimal strategies to care for these patients. Over the last two decades, cardiac magnetic resonance (CMR) imaging has offered increasingly important insights into CVD. Computational fluid dynamics (CFD) modeling, a method of simulating the characteristics of flowing fluids, can be applied to the study of CVD through the collaboration of engineers and clinicians. This chapter aims to explore the current state of the CMR-derived CFD, as this technique pertains to both acquired CVD (i.e., atherosclerosis) and congenital heart disease (CHD)

Track 5: Cardiology and the imaging revolution - Part I

Cardiology and the imaging revolution

Automated deep phenotyping of the cardiovascular system using magnetic resonance imaging

Across a lifetime, the cardiovascular system must adapt to a great range of demands from the body. The individual changes in the cardiovascular system that occur in response to loading conditions are influenced by genetic susceptibility, and the pattern and extent of these changes have prognostic value. Brachial blood pressure (BP) and left ventricular ejection fraction (LVEF) are important biomarkers that capture this response, and their measurements are made at high resolution. Relatively, clinical analysis is crude, and may result in lost information and the introduction of noise. Digital information storage enables efficient extraction of information from a dataset, and this strategy may provide more precise and deeper measures to breakdown current phenotypes into their component parts. The aim of this thesis was to develop automated analysis of cardiovascular magnetic resonance (CMR) imaging for more detailed phenotyping, and apply these techniques for new biological insights into the cardiovascular response to different loading conditions. I therefore tested the feasibility and clinical utility of computational approaches for image and waveform analysis, recruiting and acquiring additional patient cohorts where necessary, and then applied these approaches prospectively to participants before and after six-months of exercise training for a first-time marathon. First, a multi-centre, multi-vendor, multi-field strength, multi-disease CMR resource of 110 patients undergoing repeat imaging in a short time-frame was assembled. The resource was used to assess whether automated analysis of LV structure and function is feasible on real-world data, and if it can improve upon human precision. This showed that clinicians can be confident in detecting a 9% change in EF or a 20g change in LV mass. This will be difficult to improve by clinicians because the greatest source of human error was attributable to the observer rather than modifiable factors. Having understood these errors, a convolutional neural network was trained on separate multi-centre data for automated analysis and was successfully generalizable to the real-world CMR data. Precision was similar to human analysis, and performance was 186 times faster. This real-world benchmarking resource has been made freely available (thevolumesresource.com). Precise automated segmentations were then used as a platform to delve further into the LV phenotype. Global LVEFs measured from CMR imaging in 116 patients with severe aortic stenosis were broken down into ~10 million regional measurements of structure and function, represented by computational three-dimensional LV models for each individual. A cardiac atlas approach was used to compile, label, segment and represent these data. Models were compared with healthy matched controls, and co-registered with follow-up one year after aortic valve replacement (AVR). This showed that there is a tendency to asymmetric septal hypertrophy in all patients with severe aortic stenosis (AS), rather than a characteristic specific to predisposed patients. This response to AS was more unfavourable in males than females (associated with higher NT-proBNP, and lower blood pressure), but was more modifiable with AVR. This was not detected using conventional analysis. Because cardiac function is coupled with the vasculature, a novel integrated assessment of the cardiovascular system was developed. Wave intensity theory was used to combine central blood pressure and CMR aortic blood flow-velocity waveforms to represent the interaction of the heart with the vessels in terms of traveling energy waves. This was performed and then validated in 206 individuals (the largest cohort to date), demonstrating inefficient ventriculo-arterial coupling in female sex and healthy ageing. CMR imaging was performed in 236 individuals before training for a first-time marathon and 138 individuals were followed-up after marathon completion. After training, systolic/diastolic blood pressure reduced by 4/3mmHg, descending aortic stiffness decreased by 16%, and ventriculo-arterial coupling improved by 14%. LV mass increased slightly, with a tendency to more symmetrical hypertrophy. The reduction in aortic stiffness was equivalent to a 4-year reduction in estimated biological aortic age, and the benefit was greater in older, male, and slower individuals. In conclusion, this thesis demonstrates that automating analysis of clinical cardiovascular phenotypes is precise with significant time-saving. Complex data that is usually discarded can be used efficiently to identify new biology. Deeper phenotypes developed in this work inform risk reduction behaviour in healthy individuals, and demonstrably deliver a more sensitive marker of LV remodelling, potentially enhancing risk prediction in severe aortic stenosis