Cardiovascular computed tomography imaging for coronary artery disease risk: plaque, flow and fat

Cardiac imaging is central to the diagnosis and risk stratification of coronary artery disease, beyond symptoms and clinical risk factors, by providing objective evidence of myocardial ischaemia and characterisation of coronary artery plaque. CT coronary angiography can detect coronary plaque with high resolution, estimate the degree of functional stenosis and characterise plaque features. However, coronary artery disease risk is also driven by biological processes, such as inflammation, that are not fully reflected by severity of stenosis, myocardial ischaemia or by coronary plaque features. New cardiac CT techniques can assess coronary artery inflammation by imaging perivascular fat, and this may represent an important step forward in identifying the ‘residual risk’ that is not detected by plaque or ischaemia imaging. Coronary artery disease risk assessment that incorporates clinical factors, plaque characteristics and perivascular inflammation offers a more comprehensive individualised approach to quantify and stratify coronary artery disease risk, with potential healthcare benefits for prevention, diagnosis and treatment recommendations. Furthermore, identifying new biomarkers of cardiovascular risk has the potential to refine early-life prevention strategies, before atherosclerosis becomes established

Complementary role of cardiac CT in the assessment of aortic valve replacement dysfunction

Aortic valve replacement is the second most common cardiothoracic procedure in the UK. With an ageing population, there are an increasing number of patients with prosthetic valves that require follow-up. Imaging of prosthetic valves is challenging with conventional echocardiographic techniques making early detection of valve dysfunction or complications difficult. CT has recently emerged as a complementary approach offering excellent spatial resolution and the ability to identify a range of aortic valve replacement complications including structural valve dysfunction, thrombus development, pannus formation and prosthetic valve infective endocarditis. This review discusses each and how CT might be incorporated into a multimodal cardiovascular imaging pathway for the assessment of aortic valve replacements and in guiding clinical management

Mortality trends and diff erentials in South Africa from 1997 to 2012: second National Burden of Disease Study

Background The poor health of South Africans is known to be associated with a quadruple disease burden. In the second National Burden of Disease (NBD) study, we aimed to analyse cause of death data for 1997–2012 and develop national, population group, and provincial estimates of the levels and causes of mortality. Method We used underlying cause of death data from death notifi cations for 1997–2012 obtained from Statistics South Africa. These data were adjusted for completeness using indirect demographic techniques for adults and comparison with survey and census estimates for child mortality. A regression approach was used to estimate misclassifi ed HIV/AIDS deaths and so-called garbage codes were proportionally redistributed by age, sex, and population group population group (black African, Indian or Asian descent, white [European descent], and coloured [of mixed ancestry according to the preceding categories]). Injury deaths were estimated from additional data sources. Age-standardised death rates were calculated with mid-year population estimates and the WHO age standard. Institute of Health Metrics and Evaluation Global Burden of Disease (IHME GBD) estimates for South Africa were obtained from the IHME GHDx website for comparison. Findings All-cause age-standardised death rates increased rapidly since 1997, peaked in 2006 and then declined, driven by changes in HIV/AIDS. Mortality from tuberculosis, non-communicable diseases, and injuries decreased slightly. In 2012, HIV/AIDS caused the most deaths (29·1%) followed by cerebrovascular disease (7·5%) and lower respiratory infections (4·9%). All-cause age-standardised death rates were 1·7 times higher in the province with the highest death rate compared to the province with the lowest death rate, 2·2 times higher in black Africans compared to whites, and 1·4 times higher in males compared with females. Comparison with the IHME GBD estimates for South Africa revealed substantial diff erences for estimated deaths from all causes, particularly HIV/AIDS and interpersonal violence. Interpretation This study shows the reversal of HIV/AIDS, non-communicable disease, and injury mortality trends in South Africa during the study period. Mortality diff erentials show the importance of social determinants, raise concerns about the quality of health services, and provide relevant information to policy makers for addressing inequalities. Diff erences between GBD estimates for South Africa and this study emphasise the need for more careful calibration of global models with local data

Deep-Learning for Epicardial Adipose Tissue Assessment with Computed Tomography: Implications for Cardiovascular Risk Prediction

Background: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been documented./ Objectives: This study sought to develop a deep-learning network for automated quantification of EAT volume from CCTA, test it in patients who are technically challenging, and validate its prognostic value in routine clinical care./ Methods: The deep-learning network was trained and validated to autosegment EAT volume in 3,720 CCTA scans from the ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) cohort. The model was tested in patients with challenging anatomy and scan artifacts and applied to a longitudinal cohort of 253 patients post-cardiac surgery and 1,558 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) Trial, to investigate its prognostic value./ Results: External validation of the deep-learning network yielded a concordance correlation coefficient of 0.970 for machine vs human. EAT volume was associated with coronary artery disease (odds ratio [OR] per SD increase in EAT volume: 1.13 [95% CI: 1.04-1.30]; P = 0.01), and atrial fibrillation (OR: 1.25 [95% CI:1.08-1.40]; P = 0.03), after correction for risk factors (including body mass index). EAT volume predicted all-cause mortality (HR per SD: 1.28 [95% CI: 1.10-1.37]; P = 0.02), myocardial infarction (HR: 1.26 [95% CI:1.09-1.38]; P = 0.001), and stroke (HR: 1.20 [95% CI: 1.09-1.38]; P = 0.02) independently of risk factors in SCOT-HEART (5-year follow-up). It also predicted in-hospital (HR: 2.67 [95% CI: 1.26-3.73]; P ≤ 0.01) and long-term post–cardiac surgery atrial fibrillation (7-year follow-up; HR: 2.14 [95% CI: 1.19-2.97]; P ≤ 0.01). Conclusions: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification

Cardiac CT Improves Outcomes in Stable Coronary Heart Disease: Results of Recent Clinical Trials

Purpose of Review The purpose of this study was to review the recent randomised controlled trials of coronary computed tomography angiography (CCTA) for patients with stable coronary artery disease. Recent Findings The initial results and subsequent papers from the SCOT-HEART (Scottish COmputed Tomography of the HEART) and PROMISE (PROspective Multicentre Imaging Study for Evaluation of chest pain) trials have shown that CCTA is a safe and appropriate addition to standard care or alternative to functional testing. The SCOT-HEART study showed that CCTA changes diagnoses, improves diagnostic certainty, changes management, leads to more appropriate use of invasive coronary angiography, and reduces fatal and non-fatal myocardial infarction. A meta-analysis of the four randomised controlled trials showed that CCTA leads to a major reduction in myocardial infarction in patients with stable chest pain. Summary CCTA is now an established technique for the assessment of coronary artery disease. Recent ‘test and treat’ randomised controlled trials have shown that CCTA guided changes in management can improve clinical outcomes

Expert elicitation to inform a cost effectiveness analysis of screening for renal cancer: methodological and practical considerations

Background: Population screening for renal cell carcinoma (RCC) using ultrasound has the potential to improve survival outcomes; however a cost-effectiveness analysis (CEA) has yet to be performed. Due to the lack of existing evidence, we performed structured expert elicitation to derive unknown quantities to inform the CEA. Objectives: To elicit the cancer stage distribution (proportion of individuals with each stage of cancer) for different RCC screening scenarios and the annual transition probabilities for undiagnosed disease becoming diagnosed in the NHS. Methods: The study design and reporting adhered to the Reporting Guidelines for the Use of Expert Judgement in Model-Based Economic Evaluations. The elicitation was conducted face-to-face or via telephone between each individual expert and the facilitator, aided by online material. For multinomial data, Connor Mosimann and modified Connor Mosimann distributions were fitted for each expert and for all experts combined using mathematical linear pooling. Results: A total of 24 clinical experts were invited, and 71% participated (7 urologists, 6 oncologists, 4 radiologists). The modified Connor Mosimann distribution provided the best fit for the majority of elicited quantities. Greater uncertainty was noted for the elicited transition probabilities compared to the elicited stage distributions. Conclusion: We performed the first expert elicitation of RCC screening parameters, crucial information which will inform the CEA of screening. Additionally, the elicited quantities may enable future health economic evaluations assessing the value of diagnostic tools and pathways in RCC

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials