Cardiac magnetic resonance imaging in the diagnosis and determination of outcome of pulmonary hypertension

Pulmonary hypertension (PH) is a rare but serious condition that causes progressive right ventricular (RV) failure and death. PH may be idiopathic, associated with underlying connective-tissue disease or hypoxic lung disease, and is also increasingly being observed in the setting of heart failure with preserved ejection fraction (HFpEF). The management of PH has been revolutionised by the recent development of new disease-targeted therapies which are beneficial in pulmonary arterial hypertension (PAH), but can be potentially harmful in PH due to left heart disease, so accurate diagnosis and classification of patients is essential. These PAH therapies improve exercise capacity and pulmonary haemodynamics, but their overall effect on the right ventricle remains unclear. Current practice in the UK is to assess treatment response with 6-minute walk test and NYHA functional class, neither of which truly reflects RV function. Cardiac magnetic resonance (CMR) imaging has been established as the gold standard for the evaluation of right ventricular structure and function, but it also allows a non-invasive and accurate study of the left heart. The aims of this thesis were to investigate the use of CMR in the diagnosis of PH, in the assessment of treatment response, and in predicting survival in idiopathic and connective-tissue disease associated PAH. In Chapter 3, a left atrial volume (LAV) threshold of 43 ml/m2 measured with CMR was able to distinguish idiopathic PAH from PH due to HFpEF (sensitivity 97%, specificity 100%). In Chapter 4, disease-targeted PAH therapy resulted in significant improvements in RV and left ventricular ejection fraction (p<0.001 and p=0.0007, respectively), RV stroke volume index (p<0.0001), and left ventricular end-diastolic volume index (p=0.0015). These corresponded to observed improvements in functional class and exercise capacity, although correlation coefficients between Δ 6MWD and Δ RVEF or Δ LVEDV were low. Finally, in Chapter 5, one-year and three-year survival was worse in CTD-PAH (75% and 53%) than in IPAH (83% and 74%), despite similar baseline clinical characteristics, lung function, pulmonary haemodynamics and treatment. Baseline right ventricular stroke volume index was an independent predictor of survival in both conditions. The presence of LV systolic dysfunction was of prognostic significance in CTD-PAH but not IPAH, and a higher LAV was observed in CTD-PAH suggesting a potential contribution from LV diastolic dysfunction in this group.

Utility and safety of invasive (fractional flow reserve) and non-invasive (cardiac magnetic resonance imaging) diagnostic tests in patients with NSTEMI

A prospective randomised controlled clinical trial of treatment decisions informed by invasive functional testing of coronary artery disease severity compared with standard angiography-guided management was implemented in 350 patients with a recent non-ST elevation myocardial infarction (NSTEMI) admitted to 6 hospitals in the National Health Service. The main aims of this study were to examine the utility of both invasive fractional flow reserve (FFR) and non-invasive cardiac magnetic resonance imaging (MRI) amongst patients with a recent diagnosis of NSTEMI. In summary, the findings of this thesis are: (1) the use of FFR combined with intravenous adenosine was feasible and safe amongst patients with NSTEMI and has clinical utility; (2) there was discordance between the visual, angiographic estimation of lesion significance and FFR; (3). The use of FFR led to changes in treatment strategy and an increase in prescription of medical therapy in the short term compared with an angiographically guided strategy; (4) in the incidence of major adverse cardiac events (MACE) at 12 months follow up was similar in the two groups. Cardiac MRI was used in a subset of patients enrolled in two hospitals in the West of Scotland. T1 and T2 mapping methods were used to delineate territories of acute myocardial injury. T1 and T2 mapping were superior when compared with conventional T2-weighted dark blood imaging for estimation of the ischaemic area-at-risk (AAR) with less artifact in NSTEMI. There was poor correlation between the angiographic AAR and MRI methods of AAR estimation in patients with NSTEMI. FFR had a high accuracy at predicting inducible perfusion defects demonstrated on stress perfusion MRI. This thesis describes the largest randomized trial published to date specifically looking at the clinical utility of FFR in the NSTEMI population. We have provided evidence of the diagnostic and clinical utility of FFR in this group of patients and provide evidence to inform larger studies. This thesis also describes the largest ever MRI cohort, including with myocardial stress perfusion assessments, specifically looking at the NSTEMI population. We have demonstrated the diagnostic accuracy of FFR to predict reversible ischaemia as referenced to a non-invasive gold standard with MRI. This thesis has also shown the futility of using dark blood oedema imaging amongst all comer NSTEMI patients when compared to novel T1 and T2 mapping methods.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.