Cardiovascular magnetic resonance of myocardial edema using a short inversion time inversion recovery (STIR) black-blood technique: Diagnostic accuracy of visual and semi-quantitative assessment

<p>Abstract</p> <p>Background</p> <p>The short inversion time inversion recovery (STIR) black-blood technique has been used to visualize myocardial edema, and thus to differentiate acute from chronic myocardial lesions. However, some cardiovascular magnetic resonance (CMR) groups have reported variable image quality, and hence the diagnostic value of STIR in routine clinical practice has been put into question. The aim of our study was to analyze image quality and diagnostic performance of STIR using a set of pulse sequence parameters dedicated to edema detection, and to discuss possible factors that influence image quality. We hypothesized that STIR imaging is an accurate and robust way of detecting myocardial edema in non-selected patients with acute myocardial infarction.</p> <p>Methods</p> <p>Forty-six consecutive patients with acute myocardial infarction underwent CMR (day 4.5, +/- 1.6) including STIR for the assessment of myocardial edema and late gadolinium enhancement (LGE) for quantification of myocardial necrosis. Thirty of these patients underwent a follow-up CMR at approximately six months (195 +/- 39 days). Both STIR and LGE images were evaluated separately on a segmental basis for image quality as well as for presence and extent of myocardial hyper-intensity, with both visual and semi-quantitative (threshold-based) analysis. LGE was used as a reference standard for localization and extent of myocardial necrosis (acute) or scar (chronic).</p> <p>Results</p> <p>Image quality of STIR images was rated as diagnostic in 99.5% of cases. At the acute stage, the sensitivity and specificity of STIR to detect infarcted segments on visual assessment was 95% and 78% respectively, and on semi-quantitative assessment was 99% and 83%, respectively. STIR differentiated acutely from chronically infarcted segments with a sensitivity of 95% by both methods and with a specificity of 99% by visual assessment and 97% by semi-quantitative assessment. The extent of hyper-intense areas on acute STIR images was 85% larger than those on LGE images, with a larger myocardial salvage index in reperfused than in non-reperfused infarcts (p = 0.035).</p> <p>Conclusions</p> <p>STIR with appropriate pulse sequence settings is accurate in detecting acute myocardial infarction (MI) and distinguishing acute from chronic MI with both visual and semi-quantitative analysis. Due to its unique technical characteristics, STIR should be regarded as an edema-weighted rather than a purely T2-weighted technique.</p

Smart Contracts in Insurance: A Law and Futurology Perspective

Smart contracts are innovative contracts that differ from traditional ones in that they are self-executing, as they entail the possibility of representing contract terms in programming code that gets automatically executed on a blockchain or other distributed ledgers. Following the latest developments in blockchain technology, smart contracts have been the focus of growing attention and are currently among the major innovations that are taking place in financial services. This paper investigates the scope for their application in insurance both in the near and longer term, exploring the legal challenges that they pose. The analysis shows that in the near term smart contracts will be mainly exploited to automate underwriting, claims handling and payouts. It considers how the automation of these processes will operate at law and emphasises the impact that smart contracts can have especially on the reduction of transaction costs and on the very essence of the insurance contract—the insurer's promise to pay. Building on current technological developments, the paper then turns to role that smart contracts can play in insurance in the longer term, advancing the prospect of the automation of the entire insurance contract. In particular, it argues that the interaction between smart contracts and artificial intelligence and machine learning can challenge traditional frameworks of thought such as incomplete contracting and, in the farther-distant future, will culminate in contracts that will both self-interpret and self-enforce their terms—what can be called the true smart contracts. The analysis identifies and addresses the main legal issues that can arise in this context, exploring how to strike a balance between the goal of fostering innovation and the need to ensure policyholder and investor protection

Studying user income through language, behaviour and affect in social media

Automatically inferring user demographics from social media posts is useful for both social science research and a range of downstream applications in marketing and politics. We present the first extensive study where user behaviour on Twitter is used to build a predictive model of income. We apply non-linear methods for regression, i.e. Gaussian Processes, achieving strong correlation between predicted and actual user income. This allows us to shed light on the factors that characterise income on Twitter and analyse their interplay with user emotions and sentiment, perceived psycho-demographics and language use expressed through the topics of their posts. Our analysis uncovers correlations between different feature categories and income, some of which reflect common belief e.g. higher perceived education and intelligence indicates higher earnings, known differences e.g. gender and age differences, however, others show novel findings e.g. higher income users express more fear and anger, whereas lower income users express more of the time emotion and opinions

Cardiovascular magnetic resonance in pericardial diseases

The pericardium and pericardial diseases in particular have received, in contrast to other topics in the field of cardiology, relatively limited interest. Today, despite improved knowledge of pathophysiology of pericardial diseases and the availability of a wide spectrum of diagnostic tools, the diagnostic challenge remains. Not only the clinical presentation may be atypical, mimicking other cardiac, pulmonary or pleural diseases; in developed countries a shift for instance in the epidemiology of constrictive pericarditis has been noted. Accurate decision making is crucial taking into account the significant morbidity and mortality caused by complicated pericardial diseases, and the potential benefit of therapeutic interventions. Imaging herein has an important role, and cardiovascular magnetic resonance (CMR) is definitely one of the most versatile modalities to study the pericardium. It fuses excellent anatomic detail and tissue characterization with accurate evaluation of cardiac function and assessment of the haemodynamic consequences of pericardial constraint on cardiac filling. This review focuses on the current state of knowledge how CMR can be used to study the most common pericardial diseases

Assessment of acute myocardial infarction: current status and recommendations from the North American society for cardiovascular imaging and the European society of cardiac radiology

There are a number of imaging tests that are used in the setting of acute myocardial infarction and acute coronary syndrome. Each has their strengths and limitations. Experts from the European Society of Cardiac Radiology and the North American Society for Cardiovascular Imaging together with other prominent imagers reviewed the literature. It is clear that there is a definite role for imaging in these patients. While comparative accuracy, convenience and cost have largely guided test decisions in the past, the introduction of newer tests is being held to a higher standard which compares patient outcomes. Multicenter randomized comparative effectiveness trials with outcome measures are required