Association of thoracic aorta calcium and non cardiac vascular events in cardiac disease-free individuals

Validity of Atherosclerotic Calcified Lesions Observed on Low-Dose Computed Tomography and Cardio-Ankle Vascular Index as Surrogate Markers of Atherosclerosis Progression

The significance of atherosclerotic calcified lesions observed on low-dose computed tomography (LDCT) performed during general checkups was investigated. The coronary arteries (CA), ascending aorta and aortic arch (AAAA), descending thoracic aorta (DTA), and abdominal aorta (AA) were examined. Semiquantitative calcified index analysis of the DTA and AA in terms of atherosclerosis risk factors and cardio-ankle vascular index (CAVI) measurements was also performed. We included 1594 participants (mean age: 59.2 years; range: 31-91 years). The prevalence of calcified lesions was 71.0%, 66.6%, 57.2%, and 37.9% in the AA, CA, AAAA, and DTA, respectively. Age-related advances in calcification among participants with no major risk factors, revealed that calcification appeared earliest in the AA, followed by the CA, AAAA, and DTA. Participants with calcified lesions in all arteries had a significantly greater CAVI than those without calcification. The CAVI was negatively correlated with low-density lipoprotein cholesterol levels, particularly in participants without calcified lesions in the DTA. Calcified lesions on LDCT could indicate the end stage of atherosclerotic lesions. The CAVI can be used to assess atherosclerotic changes at all stages of disease progression. A combination of LDCT and CAVI could be used as a routine non-invasive assessment of atherosclerosis.

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this study was to develop a fully automatic system to detect TAC and to evaluate its performance for classifying the patients into four TAC risk categories. The method started by segmenting the thoracic aorta, combining three UNets trained with axial, sagittal and coronal CT images. Afterwards, the surrounding lesion candidates were classified using three combined convolutional neural networks (CNNs) trained with orthogonal patches. Image datasets included 1190 non-enhanced ECG-gated cardiac CT studies from a cohort of cardiovascular patients (age 57 ± 9 years, 80% men, 65% TAC > 0). In the test set (N = 119), the combination of UNets was able to successfully segment the thoracic aorta with a mean volume difference of 0.3 ± 11.7 ml (<6%) and a median Dice coefficient of 0.947. The combined CNNs accurately classified the lesion candidates and 87% of the patients (N = 104) were accurately placed in their corresponding risk categories (Kappa = 0.826, ICC = 0.9915). TAC measurement can be estimated automatically from cardiac CT images using UNets to isolate the thoracic aorta and CNNs to classify calcified lesions.

Thoracic Aorta Calcium Detection and Quantification Using Convolutional Neural Networks in a Large Cohort of Intermediate-Risk Patients

Arterial calcification is an independent predictor of cardiovascular disease (CVD) events whereas thoracic aorta calcium (TAC) detection might anticipate extracoronary outcomes. In this work, we trained six convolutional neural networks (CNNs) to detect aortic calcifications and to automate the TAC score assessment in intermediate CVD risk patients. Cardiac computed tomography images from 1415 patients were analyzed together with their aortic geometry previously assessed. Orthogonal patches centered in each aortic candidate lesion were reconstructed and a dataset with 19,790 images (61% positives) was built. Three single-input 2D CNNs were trained using axial, coronal and sagittal patches together with two multi-input 2.5D CNNs combining the orthogonal patches and identifying their best regional combination (BRC) in terms of lesion location. Aortic calcifications were concentrated in the descending (66%) and aortic arch (26%) portions. The BRC of axial patches to detect ascending or aortic arch lesions and sagittal images for the descending portion had the best performance: 0.954 F1-Score, 98.4% sensitivity, 87% of the subjects correctly classified in their TAC category and an average false positive TAC score per patient of 30. A CNN that combined axial and sagittal patches depending on the candidate aortic location ensured an accurate TAC score prediction.

Risk factors for symptomatic vascular events in giant cell arteritis: a study of 254 patients with large-vessel imaging at diagnosis

Aims

To identify factors associated with vascular events in patients with giant cell arteritis (GCA).

Methods

We performed a retrospective study of GCA patients diagnosed over a 20-year-period, who all underwent vascular imaging evaluation at diagnosis. Symptomatic vascular events were defined as the occurrence of any aortic event (aortic dissection or symptomatic aortic aneurysm), stroke, myocardial infarction, limb or mesenteric ischemia and de novo lower limbs arteritis stage 3 or 4. Patients with symptomatic vascular event (VE+) and without were compared, and risk factors were identified in a multivariable analysis.

Results

Thirty-nine (15.4%) of the 254 included patients experienced at least one symptomatic vascular event during follow-up, with a median time of 21.5 months. Arterial hypertension, diabetes, lower limbs arteritis or vascular complication at diagnosis were more frequent in VE+ patients (p < 0.05), as an abnormal computed tomography (CT)-scan at diagnosis (p = 0.04), aortitis (p = 0.01), particularly of the descending thoracic aorta (p = 0.03) and atheroma (p = 0.03). Deaths were more frequent in the VE+ group (37.1 versus 10.3%, p = 0.0003). In multivariable analysis, aortic surgery [hazard ratio (HR): 10.46 (1.41-77.80), p = 0.02], stroke [HR: 22.32 (3.69-135.05), p < 0.001], upper limb ischemia [HR: 20.27 (2.05-200.12), p = 0.01], lower limb ischemia [HR: 76.57 (2.89-2027.69), p = 0.009], aortic atheroma [HR: 3.06 (1.06-8.82), p = 0.04] and aortitis of the descending thoracic aorta on CT-scan at diagnosis [HR: 4.64 (1.56-13.75), p = 0.006] were independent predictive factors of a vascular event.

Conclusion

In this study on GCA cases with large vessels imaging at diagnosis, aortic surgery, stroke, upper or lower limb ischemia, aortic atheroma and aortitis of the descending thoracic aorta on CT-scan, at GCA diagnosis, were independent predictive factors of a vascular event.

Plain language summary

Risk factors for symptomatic vascular events in giant cell arteritisThis study was performed to identify the risk factors for developing symptomatic vascular event during giant cell arteritis (GCA) because these are poorly known.We performed a retrospective study of GCA patients diagnosed over a 20-year-period, who all underwent vascular imaging evaluation at diagnosis.Patients with symptomatic vascular event (VE+) and without (VE-) were compared, and risk factors were identified in a multivariable analysis.Thirty-nine patients experienced at least one symptomatic vascular event during follow-up, with a median time of 21.5 months.Arterial hypertension, diabetes, lower limbs arteritis or vascular complication at diagnosis were significantly more frequent in VE+ patients, as an abnormal CT-scan at diagnosis, aortitis, particularly of the descending thoracic aorta and atheroma. Deaths were more frequent in the VE+ group.Among 254 GCA patients, 39 experienced at least one vascular event during follow-up.Aortic surgery, stroke, upper and lower limb ischemia were vascular event risk factors.Aortic atheroma and descending thoracic aorta aortitis on CT-scan were vascular event risk factors.This study on GCA cases with large vessels imaging at diagnosis, showed that aortic surgery, stroke, upper or lower limb ischemia, aortic atheroma and aortitis of the descending thoracic aorta on CT-scan, at GCA diagnosis, were independent predictive factors of a vascular event.

Association of calcium density in the thoracic aorta with risk factors and clinical events

OBJECTIVES

In the ascending aorta, calcification density was independently and inversely associated with cardiovascular disease (CVD) risk prediction. Until now, the density of thoracic aorta calcium (TAC) was estimated as the Agatston score divided by the calcium area (D_AG). We thought to analyze TAC density in a full Hounsfield unit (HU) range and to study its association with TAC volume, traditional risk factors, and CVD events.

METHODS

Non-enhanced CT images of 1426 patients at intermediate risk were retrospectively reviewed. A calcium density score was estimated as the average of the maximum HU attenuation in all calcified plaques of the entire thoracic aorta (D_AV).

RESULTS

During a mean 4.0 years follow-up, there were 26 events for a total of 674 patients with TAC > 0. TAC volume and D_AV were positively correlated (R = 0.72). The median D_AV value was 457 HU (IQ 323-603 HU) and was exponentially related to D_AG (R = 0.86). D_AV was inversely associated with systolic pressure (p < 0.05), pulse pressure (p < 0.01), hypertension (p < 0.05), and 10-year FRS (p < 0.001) after adjusting for TAC volume. When TAC volume and D_AV were included in a logistic model, a significant improvement was shown in CVD risk estimation beyond coronary artery calcium (CAC) (AUC = 0.768 vs 0.814, p < 0.05). In multivariable Cox models, TAC volume and D_AV showed an independent association with CVD.

CONCLUSIONS

In intermediate risk patients, TAC density was inversely associated with several risk factors after adjustment for TAC volume. A significant improvement was observed over CAC when TAC volume and density were added into the risk prediction model.

KEY POINTS

• Calcifications in the aorta can be non-invasively assessed using CT images • A higher calcium score is associated with a higher cardiovascular risk • Measuring the calcifications size and the density separately can improve the risk prediction.

Thoracic Aortic Calcification: Diagnostic, Prognostic, and Management Considerations

Thoracic aortic calcification (TAC) is associated with adverse cardiovascular outcomes, and for the cardiovascular imager, is predominantly encountered in 4 settings: 1) incidentally, for example, during a coronary artery calcium scan; 2) as part of dedicated screening; 3) in the evaluation of an embolic event; or 4) in procedural planning. This review focuses on TAC in these contexts. Within atherosclerosis, TAC is common, variable in extent, and begins in the intima with a patchy distribution. In metabolic disorders, aortitis, and radiation-associated cardiovascular disease, calcification preferentially involves the media and is often more concentric. As an incidental finding, atherosclerotic TAC provides limited incremental discriminative value, and current data do not support screening. After an embolic event, the demonstration of thoracic atheroma provides diagnostic clarity, but has limited treatment implications. Before any procedure, the plan often changes if the most severe form of TAC, a porcelain aorta, is discovered.

Extra-coronary calcification (aortic valve calcification, mitral annular calcification, aortic valve ring calcification and thoracic aortic calcification) in HIV seropositive and seronegative men: Multicenter AIDS Cohort Study

INTRODUCTION

Previous studies have demonstrated an association between HIV infection and coronary artery disease (CAD); little is known about potential associations between HIV infection and extra-coronary calcification (ECC).

METHODS

We analyzed 621 HIV infected (HIV+) and 384 HIV uninfected (HIV-) men from the Multicenter AIDS Cohort Study who underwent non-contrast computed tomography (CT) from 2010-2013. Agatston scores were calculated for mitral annular calcification (MAC), aortic valve calcification (AVC), aortic valve ring calcification (AVRC), and thoracic aortic calcification (TAC). The associations between HIV infection and the presence of each type of ECC (score > 0) were evaluated by multivariable logistic regression. We also evaluated the association of ECC with inflammatory biomarker levels and coronary plaque morphology.

RESULTS

Among HIV+ and HIV- men, the age-standardized prevalences were 15% for TAC (HIV+ 14%/HIV- 16%), 10% for AVC (HIV+ 11%/HIV- 8%), 24% for AVRC (HIV+ 23% HIV- 24%), and 5% for MAC (HIV+ 7%/HIV- 3%). After adjustment, HIV+ men had 3-fold greater odds of MAC compared to HIV- men (OR = 3.2, 95% CI: 1.5-6.7), and almost twice the odds of AVC (1.8, 1.1-2.9). HIV serostatus was not associated with TAC or AVRC. AVRC was associated with higher Il-6 and sCD163 levels. TAC was associated with higher ICAM-1, TNF-α RII, and Il-6 levels. AVC and AVRC calcification were associated with presence of non-calcified plaque in HIV+ but not HIV- men.

CONCLUSION

HIV infection is an independent predictor of MAC and AVC. Whether these calcifications predict mortality in HIV+ patients deserves further investigation.