MRI and CT coronary angiography in survivors of COVID-19

ObjectivesTo determine the contribution of comorbidities on the reported widespread myocardial abnormalities in patients with recent COVID-19.MethodsIn a prospective two-centre observational study, patients hospitalised with confirmed COVID-19 underwent gadolinium and manganese-enhanced MRI and CT coronary angiography (CTCA). They were compared with healthy and comorbidity-matched volunteers after blinded analysis.ResultsIn 52 patients (median age: 54 (IQR 51–57) years, 39 males) who recovered from COVID-19, one-third (n=15, 29%) were admitted to intensive care and a fifth (n=11, 21%) were ventilated. Twenty-three patients underwent CTCA, with one-third having underlying coronary artery disease (n=8, 35%). Compared with younger healthy volunteers (n=10), patients demonstrated reduced left (ejection fraction (EF): 57.4±11.1 (95% CI 54.0 to 60.1) versus 66.3±5 (95 CI 62.4 to 69.8)%; p=0.02) and right (EF: 51.7±9.1 (95% CI 53.9 to 60.1) vs 60.5±4.9 (95% CI 57.1 to 63.2)%; p≤0.0001) ventricular systolic function with elevated native T1 values (1225±46 (95% CI 1205 to 1240) vs 1197±30 (95% CI 1178 to 1216) ms;p=0.04) and extracellular volume fraction (ECV) (31±4 (95% CI 29.6 to 32.1) vs 24±3 (95% CI 22.4 to 26.4)%; p<0.0003) but reduced myocardial manganese uptake (6.9±0.9 (95% CI 6.5 to 7.3) vs 7.9±1.2 (95% CI 7.4 to 8.5) mL/100 g/min; p=0.01). Compared with comorbidity-matched volunteers (n=26), patients had preserved left ventricular function but reduced right ventricular systolic function (EF: 51.7±9.1 (95% CI 53.9 to 60.1) vs 59.3±4.9 (95% CI 51.0 to 66.5)%; p=0.0005) with comparable native T1 values (1225±46 (95% CI 1205 to 1240) vs 1227±51 (95% CI 1208 to 1246) ms; p=0.99), ECV (31±4 (95% CI 29.6 to 32.1) vs 29±5 (95% CI 27.0 to 31.2)%; p=0.35), presence of late gadolinium enhancement and manganese uptake. These findings remained irrespective of COVID-19 disease severity, presence of myocardial injury or ongoing symptoms.ConclusionsPatients demonstrate right but not left ventricular dysfunction. Previous reports of left ventricular myocardial abnormalities following COVID-19 may reflect pre-existing comorbidities.Trial registration numberNCT04625075.

Pericoronary adipose tissue attenuation, low-attenuation plaque burden and 5-year risk of myocardial infarction

Introduction Pericoronary adipose tissue (PCAT) attenuation has emerged as a surrogate marker of pericoronary inflammation. To date, no studies have compared the impact of pericoronary adipose tissue (PCAT) attenuation and quantitative plaque burden on cardiac outcomes. Purpose We aimed to establish the relative merits of these approaches to risk prediction and hypothesised that the combination of PCAT attenuation and quantitative plaque burden measures could provide additive and improved prediction of myocardial infarction in patients with stable chest pain. Methods In a post-hoc analysis of a randomized controlled trial, we investigated the association between the future risk of fatal or non-fatal myocardial infarction and PCAT attenuation measured from CT coronary angiography using multivariable Cox regression models including plaque burden, obstructive coronary disease and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidaemia and family history of cardiovascular disease). Results In 1697 evaluable participants (mean age 58±10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 [interquartile interval, 4.0–5.7] years. Median low-attenuation plaque burden was 4.20 [0–6.86] % and mean PCAT −76±8 Hounsfield units (HU). PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (hazard ratio [HR] 1.55, 95% CI 1.08–2.22; p=0.017, per 1 standard deviation increment) with an optimum threshold of −70.5 HU [Hazards ratio (HR) 2.45, 95% CI 1.2–4.9; p=0.01]. Univariable analysis also identified the burden of non-calcified, low-attenuation and calcified plaque as well as Agatston coronary calcium score, presence of obstructive coronary artery disease and cardiovascular risk score were predictors of myocardial infarction (Figure 1). In multivariable analysis, only the low-attenuation plaque burden (HR 1.80, 95% CI 1.16 to 2.81, p=0.011, per doubling) and PCAT-RCA (HR 1.47 95%1.02 to 2.13, p=0.040, per standard deviation increment) remained predictors of myocardial infarction (Figure 1). In multivariable analysis, adding PCAT-RCA ≥-70.5 HU to low-attenuation plaque burden &gt;4% (optimum threshold for future myocardial infarction; HR = 4.87, 95% CI 2.03–11.78; p&lt;0.0001) led to improved prediction of future myocardial infarction (HR 11.7, 95% CI 3.3–40.9; p&lt;0.0001); Figure 2. In ROC analysis, integration of PCAT-RCA attenuation and LAP burden, increased the prediction for myocardial infarction compared to LAP alone (ΔAUC=0.04; p=0.01). Conclusion CT coronary angiography defined PCAT attenuation and low-attenuation plaque have marked and additive predictive value for the risk of fatal or non-fatal myocardial infarction. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The Chief Scientist Office of the Scottish Government Health and Social Care Directorates, British Heart Foundation, National Institute of Health/National Heart, Lung, and Blood Institute grant

Early computed tomography coronary angiography in patients with suspected acute coronary syndrome: randomised controlled trial

Objectives To establish if the use of early computed tomography (CT) coronary angiography improves one year clinical outcomes in patients presenting to the emergency department with acute chest pain and at intermediate risk of acute coronary syndrome and subsequent clinical events. Design Randomised controlled trial. Setting 37 hospitals in the UK. Participants Adults with suspected or a provisional diagnosis of acute coronary syndrome and one or more of previous coronary heart disease, raised levels of cardiac troponin, or abnormal electrocardiogram. Interventions Early CT coronary angiography and standard of care compared with standard of care only. Main outcome measures Primary endpoint was all cause death or subsequent type 1 or 4b myocardial infarction at one year. Results Between 23 March 2015 and 27 June 2019, 1748 participants (mean age 62 years (standard deviation 13), 64% men, mean global registry of acute coronary events (GRACE) score 115 (standard deviation 35)) were randomised to receive early CT coronary angiography (n=877) or standard of care only (n=871). Median time from randomisation to CT coronary angiography was 4.2 (interquartile range 1.6-21.6) hours. The primary endpoint occurred in 51 (5.8%) participants randomised to CT coronary angiography and 53 (6.1%) participants who received standard of care only (adjusted hazard ratio 0.91 (95% confidence interval 0.62 to 1.35), P=0.65). Invasive coronary angiography was performed in 474 (54.0%) participants randomised to CT coronary angiography and 530 (60.8%) participants who received standard of care only (adjusted hazard ratio 0.81 (0.72 to 0.92), P=0.001). There were no overall differences in coronary revascularisation, use of drug treatment for acute coronary syndrome, or subsequent preventive treatments between the two groups. Early CT coronary angiography was associated with a slightly longer time in hospital (median increase 0.21 (95% confidence interval 0.05 to 0.40) days from a median hospital stay of 2.0 to 2.2 days). Conclusions In intermediate risk patients with acute chest pain and suspected acute coronary syndrome, early CT coronary angiography did not alter overall coronary therapeutic interventions or one year clinical outcomes, but reduced rates of invasive angiography while modestly increasing length of hospital stay. These findings do not support the routine use of early CT coronary angiography in intermediate risk patients with acute chest pain and suspected acute coronary syndrome. Trial registration ISRCTN19102565 , NCT02284191 .

Detection of 3D Arterial Centerline Extraction in Spiral CT Coronary Angiography

This paper presents an in-depth study and analysis of the 3D arterial centerline in spiral CT coronary angiography, and constructs its detection and extraction technique. The first time, the distance transform is used to complete the boundary search of the original figure; the second time, the distance transform is used to calculate the value of the distance transform of all voxels, and according to the value of the distance transform, unnecessary voxels are deleted, to complete the initial contraction of the vascular region and reduce the computational consumption in the next process; then, the nonwitnessed voxels are used to construct the maximum inner joint sphere model and find the skeletal voxels that can reflect the shape of the original figure. Finally, the skeletal lines were optimized on these initially extracted skeletal voxels using a dichotomous-like principle to obtain the final coronary artery centerline. Through the evaluation of the experimental results, the algorithm can extract the coronary centerline more accurately. In this paper, the segmentation method is evaluated on the test set data by two kinds of indexes: one is the index of segmentation result evaluation, including dice coefficient, accuracy, specificity, and sensitivity; the other is the index of clinical diagnosis result evaluation, which is to refine the segmentation result for vessel diameter detection. The results obtained in this paper were compared with the physicians’ labeling results. In terms of network performance, the Dice coefficient obtained in this paper was 0.89, the accuracy was 98.36%, the sensitivity was 93.36%, and the specificity was 98.76%, which reflected certain advantages in comparison with the advanced methods proposed by previous authors. In terms of clinical evaluation indexes, by performing skeleton line extraction and diameter calculation on the results obtained by the segmentation method proposed in this paper, the absolute error obtained after comparing with the diameter of the labeled image was 0.382 and the relative error was 0.112, which indicates that the segmentation method in this paper can recover the vessel contour more accurately. Then, the results of coronary artery centerline extraction with and without fine branch elimination were evaluated, which proved that the coronary artery centerline has higher accuracy after fine branch elimination. The algorithm is also used to extract the centerline of the complete coronary artery tree, and the results prove that the algorithm has better results for the centerline extraction of the complete coronary vascular tree.