China
Africa
Explore chapters and articles related to this topic
Myocardial Perfusion Imaging
Published in Michael Ljungberg, Handbook of Nuclear Medicine and Molecular Imaging for Physicists, 2022
Elin Trägårdh, David Minarik, Mark Lubberink
Testing for ischemia by non-invasive imaging is not expected to decrease, but rather the opposite since an exercise test is no longer generally recommended for diagnosing ischemia [3]. In European guidelines, CCTA is recommended in patients with lower pre-test probability of IHD. The pre-test probability is estimated from symptoms, sex and age, and has been revised based on new populatoin studies and found to be lower than previously. CCTA could thus be expected to increase. However, the guidelines stress the importance of taking local expertise and availability into account when selecting the test for diagnosing IHD, why any transition towards one test or another will take time. No clear recommendations regarding when to use MPS, PET, stress echocardiography or CMR are given. Since the prevalence of chronic coronary syndrome is increasing, non-invasive imaging to evaluate new symptoms is expected to rise. As the availability of PET/CT scanners and suitable PET radiopharmaceuticals increase, the use of PET in this population is also expected to rise, especially when it is important to quantify the perfusion. For MPS, the use of cardiac-specific systems, as opposed to general gamma cameras, are expected to increase, at least in departments with a high number of examinations performed annually.
Uses of Biochemical Markers in Environmental Epidemiology
Published in Roberto Bertollini, Michael D. Lebowitz, Rodolfo Saracci, David A. Savitz, Environmental Epidemiology, 2019
A biomarker does not necessarily perform better than a traditional tool such as a questionnaire. For example, on most occasions a smoking questionnaire is quite sufficient to achieve credible information on smoking habits. The additional contribution of biomarkers can be measured following the logic of clinical epidemiology when evaluating the contribution of a diagnostic test. For example, we know that cotinine and nicotine in the urine tend to be more accurate than the use of a questionnaire; but how much and how cost-effectively? Let us suppose that the positive predictive value of a questionnaire is 0.94: what is the additional gain allowed by cotinine-nicotine measurement? According to clinical epidemiology, the rough evaluation based on the questionnaire is the pre-test probability that the individual smokes, and the cotinine-nicotine measurement represents the post-test probability. The contribution of the biomarker can be therefore estimated as the difference between the two probabilities. One property of this clinical reasoning is that the performance of a test is best in intermediate situations between very low a_priori chances (say, pre-test probabilities of 0.1–0.2 or less), and situations of almost certainty (probabilities of 0.9 or more). In other words, it would be justifiable to use a biomarker when it can add significantly to previous knowledge, i.e., in conditions of real uncertainty.
Cardiovascular Imaging for Early Detection of Coronary Artery Disease
Published in Ayman El-Baz, Jasjit S. Suri, Cardiovascular Imaging and Image Analysis, 2018
Giorgos Papanastasiou, George Markousis-Mavrogenis, Sophie I. Mavrogeni
CMRA can reliably assess the initial part of the coronary arteries in almost 100% of patients, with excellent results acquired for the left anterior descending (LAD) and the right coronary artery (RCA); the left circumflex (LCX), due to its peculiar way, is at a increased distance from the cardiac coil, and therefore its visualization is usually of inferior quality, compared to the rest of the coronary arteries. According to previous studies, the imaged length for LAD is 50 mm, for RCA is 80 mm, and for LCX is 40 mm [118–125] (15–22). An excellent agreement between the proximal parts of coronary arteries measured by CMRA and X-ray invasive angiography was assessed by previous studies [126] (23). Unfortunately, the resolution of CMRA remains lower compared with invasive coronary angiography and does not allow the evaluation of stenosis in the mid and peripheral part of coronary arteries; however, CMRA was shown to have a high sensitivity (92%) for the detection of CAD and its diagnostic performance was further improved. In a subanalysis of left main or three vessel disease, a sensitivity of 100% and a negative predictive value of 100% was documented. These findings were also supported by smaller single-center studies [118, 125–133] (15, 24–32). A meta-analysis compared coronary MRA and multislice computed tomography (CT) for assessment of significant CAD (112) (9). CT was more accurate than MRA, and therefore CT was suggested as the preferred non-invasive alternative to X-ray coronary angiography. However, the superiority of CMRA is that it can offer more data about the patient, including cardiac anatomy, function, inflammation, stress perfusion, and fibrosis evaluation. Recently, a multicenter study showed that whole heart CMRA at 1.5 T can detect significant CAD with high sensitivity (88%) and moderate specificity (72%). Additionally, a negative predictive value (NPV) of 88% indicates that this technique can effectively be used to exclude the presence of significant CAD [134] (33). We should mention that this NPV reported by this trial is identical to the NPV of the CORE-64 CTA multicenter study (135) (34). Proving the value of CMRA to rule out CAD in patients with low pre-test probability (<20%) [136] (35). Finally, in a direct comparison between CMRA and CTA no significant difference was proved for the detection of CAD between 3 T MR and 64-slice CTA [137] (36).
The role of cardiac computed tomography in pre-participation screening of mature athletes
Published in European Journal of Sport Science, 2022
Georgios A. Christou, Asterios P. Deligiannis, Evangelia J. Kouidi
Coronary atherosclerosis, defined as CACS > 0, is detected in approximately 50% of male athletes over the age of 40 years (Aengevaeren et al., 2017; Braber et al., 2016; Dores et al., 2020; Merghani et al., 2017; Tsiflikas et al., 2015). These male athletes display CACS>100 at 10–16% and greater than 50% coronary artery stenosis at 5–8%, resulting in up to 19% prevalence of CACS>100 or coronary stenosis >50% (Braber et al., 2016; Dores et al., 2020; Merghani et al., 2017; Schurink et al., 2017; Tsiflikas et al., 2015). The assessment of diagnostic performance of cardiac CT in the context of pre-participation screening should be ideally based on the results of studies with asymptomatic athletes, since athletes presenting with cardiac symptoms have greater pre-test probability for CAD resulting in higher positive predictive value of cardiac CT for CAD (Knuuti et al., 2020).
A cloud-based platform for the non-invasive management of coronary artery disease
Published in Enterprise Information Systems, 2020
Antonis Sakellarios, Joao Correia, Savvas Kyriakidis, Elena Georga, Nikolaos Tachos, Panagiotis Siogkas, Francisco Sans, Paolo Stofella, Valiani Massimiliano, Alberto Clemente, Silvia Rocchiccioli, Gualtiero Pelosi, Nenad Filipovic, Dimitrios I. Fotiadis
Coronary artery disease (CAD) is considered one of the leading causes of death in developing countries ((WHO)). The development and evolution of the disease are multifactorial and several risk factors including age, gender, hypertension, hyperlipidaemia, etc., trigger the atherosclerotic process. Nowadays, effort is devoted to the implementation of diagnostic, prognostic and treatment models. The first step, however, is the accurate risk stratification of patients with established CAD, since they should be treated properly by revascularization, avoiding unnecessary catheterisations. The existing pre-test probability (PTP) models of obstructive CAD adopted by the European Society of Cardiology (ESC) or the American Heart Association (AHA) postulate a logistic regression model of relatively few traditional predictors of the disease. In spite of the reported good discrimination ability of such parametric regression models, a recent systematic review demonstrated poor external validation and head-to-head comparisons, the poor reporting of their technical characteristics as well as the variability in outcome variables, predictors and prediction horizons, which limits their applicability in evidence-based decision-making in healthcare (Damen et al. 2016). Machine learning could be used for this purpose by enabling the identification of the most informative features from big data, which now are becoming available, incorporating several features, ranging from clinical examinations and lab tests to advanced analytics such as lipidomics, proteomics and genomics (Elashoff et al. 2011).
Supervised classification approach of biometric measures for automatic fetal defect screening in head ultrasound images
Published in Journal of Medical Engineering & Technology, 2019
Hanene Sahli, Aymen Mouelhi, Amine Ben Slama, Mounir Sayadi, Radhouane Rachdi
In this part, to make obvious the performance of mentioned methods, statistical analysis is revealed: sensitivity (SE), specificity (SP) and accuracy (AC) are three concepts widely used in medical probability [22]. For factual foetal diagnosis, we are more interested in other statistical measures: the positive predictive value (PPV), the negative predictive value (NPV), the positive likelihood ratio (LR+), the negative likelihood ratio (LR-), the prevalence (P), the pre-test-odds (pre-test-od), the post-test-odds-negative (post-test-od-N), the post-test-odds-positive (post-test-od-P), the pre-test probability (pre-test-prob), the post-test probability (post-test-prob) and the absolute difference (AD). SE, SP, AC, PPV, NPV and P are defined in terms of true positive (TP), true negative (TN), false negative (FN) and false positive (FP).