The incidence and prevalence of valvular heart disease (VHD) is increasing and has been described as the next cardiac epidemic. Advances in imaging and therapeutics have revolutionized how we assess ...and treat patients with VHD. Although echocardiography continues to be the first-line imaging modality to assess the severity and the effects of VHD, advances in cardiac computed tomography (CT) now provide novel insights into VHD. Transcatheter valvular interventions rely heavily on CT guidance for procedural planning, predicting and detecting complications, and monitoring prosthesis. This review focuses on the current role and future prospects of CT in the assessment of aortic and mitral valves for transcatheter interventions, prosthetic valve complications such as thrombosis and endocarditis, and assessment of the myocardium.
ObjectivesThis study evaluates predictors of conduction abnormalities (CA) following transcatheter aortic valve implantation (TAVI) in patients with bicuspid aortic valves (BAV).BackgroundTAVI is ...associated with CA that commonly necessitate a permanent pacemaker. Predictors of CA are well established among patients with tricuspid aortic valves but not in those with BAV.MethodsThis is a single-centre, retrospective, observational study of patients with BAV treated with TAVI. Pre-TAVI ECG and CT scans and procedural characteristics were evaluated in 58 patients with BAV. CA were defined as a composite of high-degree atrioventricular block, new left bundle branch block with a QRS >150 ms or PR >240 ms and right bundle branch block with new PR prolongation or change in axis. Predictors of CA were identified using regression analysis and optimum cut-off values determined using area under the receiver operating characteristic curve analysis.ResultsCA occurred in 35% of patients. Bioprosthesis implantation depth, the difference between membranous septum (MS) length and implantation depth (δMSID) and device landing zone (DLZ) calcification adjacent to the MS were identified as univariate predictors of CA. The optimum cut-off for δMSID was 1.25 mm. Using this cut-off, low δMSID and DLZ calcification adjacent to MS predicted CA, adjusted OR 8.79, 95% CI 1.88 to 41.00; p=0.01. Eccentricity of the aortic valve annulus, type of BAV and valve calcium quantity and distribution did not predict CA.ConclusionsIn BAV patients undergoing TAVI, short δMSID and DLZ calcification adjacent to MS are associated with an increased risk of CA.
Abstract Background To identify patients with early signs of myocardial perfusion reduction, a reference base for perfusion measures is needed. Objective To analyze perfusion parameters derived from ...dynamic computed tomography perfusion imaging (CTPI) in patients with suspected coronary artery disease (CAD), and relationship with risk factors. Methods In this multicenter study, coronary CT angiography (cCTA) and dynamic CTPI were performed by second-generation dual-source CT in patients suspected of CAD. Risk factors were collected from hospital records. Patients with visual perfusion defects on CTPI, previous coronary intervention, or missing risk factor details were excluded. This analysis included 98 patients (mean age ± standard deviation SD, 59.0 ± 8.6yrs; 73 male). Global measures of left ventricular myocardial blood flow (MBF), myocardial blood volume (MBV) and volume transfer constant (Ktrans ) were calculated. Results Mean MBF was 139.3 ± 31.4 mL/100 mL/min, MBV 19.1 ± 2.7 mL/100 mL, and Ktrans 85.0 ± 17.5 mL/100 mL/min. No significant differences in perfusion parameters were found by gender or age category. Hypertension and diabetes mellitus resulted in lower perfusion parameters (hypertension vs normotension: MBV 18.5 ± 3.0 vs 19.7 ± 2.3 mL/100 mL and Ktrans 82.0 ± 18.0 vs 89.0 ± 16.0, p < 0.05; diabetes vs no diabetes: MBF 128.5 ± 31.5 vs 144.0 ± 30.5 mL/100 mL/min and MBV 17.9 ± 2.4 vs 19.4 ± 2.8 mL/100 mL, p < 0.05). In patients with hyperlipidemia, MBF was higher (146.8 ± 34.4 vs 130.7 ± 24.3 mL/100 mL/min, p < 0.05). Smoking and family history did not show perfusion parameter differences. Conclusions Dynamic CTPI identifies early perfusion disturbances in conditions like diabetes and hypertension. With further standardization, absolute perfusion measures may improve CAD risk stratification in patients without visual perfusion defects.
The coronavirus disease-2019 (COVID-19) pandemic has had an unprecedented impact leading to novel adaptations in post-graduate medical education for cardiovascular and general internal medicine. ...Whilst the results of initial community COVID-19 vaccination are awaited, continuation of multimodality teaching and training that incorporates telelearning will have enduring benefit to post-graduate education and will place educational establishments in good stead to nimbly respond in future pandemic-related public health emergencies. With the rise in innovative virtual learning solutions, medical educators will have to leverage technology to develop electronic educational materials and virtual courses that facilitate adult learning. Technology-enabled virtual learning is thus a timely progression of hybrid classroom initiatives that are already adopted to varying degrees, with a need for faculty to serve as subject matter experts, to host and moderate online discussions, and to provide feedback and overall mentorship. As an extension from existing efforts, simulation-based teaching (SBT) and learning and the use of mixed reality technology should also form a greater core in the cardiovascular medicine curriculum. We highlight five foundational themes for building a successful e-learning model in cardiovascular and general post-graduate medical training: (1) digital solutions and associated infrastructure; (2) equity in access; (3) participant engagement; (4) diversity and inclusion; and (5) patient confidentiality and governance framework. With digitalisation impacting our everyday lives and now how we teach and train in medicine, these five guiding principles provide a cognitive scaffold for careful consideration of the required ecosystem in which cardiovascular and general post-graduate medical education can effectively operate. With due consideration of various e-learning options and associated infrastructure needs; and adoption of strategies for participant engagement under sound and just governance, virtual training in medicine can be effective, inclusive and equitable through the COVID-19 era and beyond.
Abstract Background There is no published data on the prognostic value of global myocardial perfusion values at stress dynamic CT myocardial perfusion imaging (CTMPI). Methods Data of 144 patients ...from 6 centers who had undergone coronary CT angiography (coronary CTA) and CTMPI were assessed. Coronary CTA studies were acquired at rest; CTMPI was performed under vasodilator stress. Coronary CTA data were evaluated for coronary artery stenosis (≥50% luminal narrowing) on a per-vessel basis. Volumes-of-interest were placed over the entire left ventricular myocardium to obtain global myocardial blood flow (MBF), myocardial blood volume (MBV), and volume transfer constant (Ktrans ). Follow-up was obtained at 6/12/18 months. Major adverse cardiac events (MACE, defined as cardiac death, non-fatal myocardial infarction, unstable angina requiring hospitalization, and revascularization) served as the endpoint. Results MACE occurred in 40 patients (nonfatal myocardial infarction, n = 1, unstable angina, n = 13, PCI, n = 23, and CABG, n = 3). Patients with global MBF of <121 mL/100 mL/min were at increased risk for MACE (HR 2.07, 95% confidence interval CI: 1.12–3.84, p = 0.02). This association remained significant after adjusting for age, gender, and clinical risk factors (HR 2.17, 95%CI: 1.16–4.06, p = 0.02), after further adjusting for presence of ≥50% stenosis at coronary CTA (HR 2.18, 95%CI: 1.16–4.10, p = 0.02) and when excluding early (<6 months) revascularizations (HR 2.34, 95%CI: 1.01–5.43, p = 0.0486). Global MBV and Ktrans were not independent predictors of MACE. . Conclusion Global quantification of left ventricular MBF at stress dynamic CTMPI may have incremental predictive value for future MACE over clinical risk factors and assessment of stenosis at coronary CTA.
To retrospectively compare sensitivity and specificity of four generations of multidetector computed tomographic (CT) scanners for diagnosing significant (>or=50%) coronary artery stenosis, with ...quantitative conventional coronary angiography as reference standard.
The institutional review board approved this study. All patients consented to undergo CT studies prior to conventional coronary angiography, after they were informed of the additional radiation dose, and to the use of their data for future retrospective research. Two hundred four patients (157 men, 47 women; mean age, 58 years +/- 11 standard deviation), classified in four groups of 51 patients each, underwent coronary CT angiography with four-section, first- and second-generation 16-section, and 64-section CT scanners. Patients in sinus rhythm scheduled for conventional coronary angiography (stable angina, atypical chest pain) were included. Patients with bypass grafts and stents were excluded. Two readers unaware of results of conventional coronary angiography evaluated CT scans. Coronary artery segments of 2 mm or larger in diameter were included for comparative evaluation with quantitative coronary angiography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for detection of significant stenoses (>or=50% luminal diameter reduction) were calculated.
Image quality was rated poor for the following percentages of coronary artery segments: 33.1% at four-section CT, 14.4% at first-generation 16-section CT, 6.3% at second-generation 16-section CT, and 2.6% at 64-section CT. Sensitivity, specificity, PPV, and NPV, respectively, were as follows: 57%, 91%, 60%, and 90% at four-section CT; 90%, 93%, 65%, and 99% at first-generation 16-section CT; 97%, 98%, 87%, and 100% at second-generation 16-section CT; and 99%, 96%, 80%, and 100% at 64-section CT. Diagnostic performance of four-section CT was significantly poorer than that of second-generation 16-section CT (odds ratio = 4.57) and 64-section CT (odds ratio = 2.89).
Diagnostic performance of coronary CT angiography varies among scanners of different generations. Earlier-generation scanners (four sections) had significantly poorer performance; performance of 16- compared with 64-section CT scanners showed progressive, although not significant, improvement.
Abstract Background In patients with chronic angina-like chest pain, the probability of coronary artery disease (CAD) is estimated by symptoms, age, and sex according to the Genders clinical model. ...We investigated the incremental value of circulating biomarkers over the Genders model to predict functionally significant CAD in patients with chronic chest pain. Methods In 527 patients (60.4 years, standard deviation, 8.9 years; 61.3% male participants) enrolled in the European Ev aluation of In tegrated Cardiac I maging (EVINCI) study, clinical and biohumoral data were collected. Results Functionally significant CAD—ie, obstructive coronary disease seen at invasive angiography causing myocardial ischemia at stress imaging or associated with reduced fractional flow reserve (FFR < 0.8), or both—was present in 15.2% of patients. High-density lipoprotein (HDL) cholesterol, aspartate aminotransferase (AST) levels, and high-sensitivity C-reactive protein (hs-CRP) were the only independent predictors of disease among 31 biomarkers analyzed. The model integrating these biohumoral markers with clinical variables outperformed the Genders model by receiver operating characteristic curve (ROC) (area under the curve AUC, 0.70 standard error (SE), 0.03 vs 0.58 SE, 0.03, respectively, P < 0.001) and reclassification analysis (net reclassification improvement, 0.15 SE, 0.07; P = 0.04). Cross-validation of the ROC analysis confirmed the discrimination ability of the new model (AUC, 0.66). As many as 56% of patients who were assigned to a higher pretest probability by the Genders model were correctly reassigned to a low probability class (< 15%) by the new integrated model. Conclusions The Genders model has a low accuracy for predicting functionally significant CAD. A new model integrating HDL cholesterol, AST, and hs-CRP levels with common clinical variables has a higher predictive accuracy for functionally significant CAD and allows the reclassification of patients from an intermediate/high to a low pretest likelihood of CAD.
We compared the diagnostic accuracy of 64-slice computed tomographic (CT) coronary angiography to detect significant coronary artery disease (CAD) in women and men. The 64-slice CT coronary ...angiography was performed in 402 symptomatic patients, 123 women and 279 men, with CAD prevalence of 51% and 68%, respectively. Significant CAD, defined as ≥50% coronary stenosis on quantitative coronary angiography, was evaluated on a patient, vessel, and segment level. The sensitivity and negative predictive value to detect significant CAD was very good, both for women and men (100% vs 99%, p = NS; 100% vs 98%, p = NS), whereas diagnostic accuracy (88% vs 96%; p <0.01), specificity (75% vs 90%, p <0.05), and positive predictive value (81% vs 95%, p <0.001) were lower in women. The per-segment analysis demonstrated lower sensitivity in women compared with men (82% vs 93%, p <0.001). The sensitivity in women did not show a difference in proximal and midsegments, but was significantly lower in distal segments (56% vs 85%, p <0.05) and side branches (54% vs 89%, p <0.001). In conclusion, CT coronary angiography reliably rules out the presence of obstructive CAD in both men and women. Specificity and positive predictive value of CT coronary angiography were lower in women. The sensitivity to detect stenosis in small coronary branches was lower in women compared with men.
Whereas the clinical diagnosis of in-stent thrombosis is straightforward, that of in-stent restenosis remains a problem, because although many patients experience chest pain after coronary stent ...placement, that symptom is secondary to ischemia in only a few. The use of a noninvasive technique to identify such patients for early invasive intervention versus more conservative management is thus highly desirable. Multidetector computed tomography (CT) performed with 16-section scanners recently emerged as such a technique and has overtaken modalities such as electron-beam CT and magnetic resonance imaging as an alternative to conventional angiography for the assessment of in-stent restenosis. The improved hardware design of the current 64-section CT scanners allows even better delineation of stent struts and lumen. The more reliable criterion of direct lumen visualization thus may be substituted for the presence of distal runoff, which lacks specificity for a determination of in-stent patency because of the possibility of collateral pathways. However, the capability to accurately visualize the in-stent lumen depends partly on knowledge of the causes of artifacts and how they can be compensated for with postprocessing and proper image display settings. In addition, an understanding of the major stent placement techniques used in the treatment of lesions at arterial bifurcations is helpful.
Objectives:
To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess ...the incremental value of the CT coronary calcium score (CTCS).
Methods:
We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance.
Results:
Re-analysing the variables used by Diamond & Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model.
Conclusions:
Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up.
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