Periodontal Disease Is Associated with Increased Vulnerability of Coronary Atheromatous Plaques in Patients Undergoing Coronary Computed Tomography Angiography—Results from the Atherodent Study
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SUBMITTER: Rodean I
PROVIDER: S-EPMC8004050 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Among HIV-infected patients, high rates of myocardial infarction (MI) and sudden cardiac death have been observed. Exploring potential underlying mechanisms, we used multidetector spiral coronary computed tomography angiography (coronary CTA) to compare atherosclerotic plaque morphology in HIV-infected patients and non-HIV-infected controls.Coronary atherosclerotic plaques visualized by CTA in HIV-infected (101) and non-HIV-infected (41) men without clinically apparent heart disease matched on cardiovascular risk factors were analyzed for three vulnerability features: low attenuation, positive remodeling, and spotty calcification.Ninety-five percent of HIV-infected patients were receiving ART (median duration 7.9 years) and had well controlled disease (median CD4 cell count, 473?cells/?l; median HIV RNA <50?copies/ml). Age and traditional cardiovascular risk factors were similar in HIV-infected patients and controls. Among the HIV-infected (versus control) group, there was a higher prevalence of patients with at least one: low attenuation plaque (22.8 versus 7.3%, P?=?0.02), positively remodeled plaque (49.5 versus 31.7%, P?=?0.05) and high-risk 3-feature plaque (7.9 versus 0%, P?=?0.02). Moreover, patients in the HIV-infected (versus control) group demonstrated a higher number of low attenuation plaques (P?=?0.01) and positively remodeled plaques (P?=?0.03) per patient.Our data demonstrate an increased prevalence of vulnerable plaque features among relatively young HIV-infected patients. Differences in coronary atherosclerotic plaque morphology - namely, increased vulnerable plaque among HIV-infected patients - are here for the first time reported and may contribute to increased rates of MI and sudden cardiac death in this population.
| S-EPMC3740057 | biostudies-literature
Project description:ObjectivesThe aim of this study was to precisely phenotype culprit and nonculprit lesions in myocardial infarction (MI) and lesions in stable coronary artery disease (CAD) using coronary computed tomography angiography (CTA)-based radiomic analysis.BackgroundIt remains debated whether any single coronary atherosclerotic plaque within the vulnerable patient exhibits unique morphology conferring an increased risk of clinical events.MethodsA total of 60 patients with acute MI prospectively underwent coronary CTA before invasive angiography and were matched to 60 patients with stable CAD. For all coronary lesions, high-risk plaque (HRP) characteristics were qualitatively assessed, followed by semiautomated plaque quantification and extraction of 1,103 radiomic features. Machine learning models were built to examine the additive value of radiomic features for discriminating culprit lesions over and above HRP and plaque volumes.ResultsCulprit lesions had higher mean volumes of noncalcified plaque (NCP) and low-density noncalcified plaque (LDNCP) compared with the highest-grade stenosis nonculprits and highest-grade stenosis stable CAD lesions (NCP: 138.1 mm3 vs 110.7 mm3 vs 102.7 mm3; LDNCP: 14.2 mm3 vs 9.8 mm3 vs 8.4 mm3; both Ptrend < 0.01). In multivariable linear regression adjusted for NCP and LDNCP volumes, 14.9% (164 of 1,103) of radiomic features were associated with culprits and 9.7% (107 of 1,103) were associated with the highest-grade stenosis nonculprits (critical P < 0.0007) when compared with highest-grade stenosis stable CAD lesions as reference. Hierarchical clustering of significant radiomic features identified 9 unique data clusters (latent phenotypes): 5 contained radiomic features specific to culprits, 1 contained features specific to highest-grade stenosis nonculprits, and 3 contained features associated with either lesion type. Radiomic features provided incremental value for discriminating culprit lesions when added to a machine learning model containing HRP and plaque volumes (area under the receiver-operating characteristic curve 0.86 vs 0.76; P = 0.004).ConclusionsCulprit lesions and highest-grade stenosis nonculprit lesions in MI have distinct radiomic signatures compared with lesions in stable CAD. Within the vulnerable patient may exist individual vulnerable plaques identifiable by coronary CTA-based precision phenotyping.
| S-EPMC9072980 | biostudies-literature
Project description:Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been shown to reflect local inflammation and increased cardiovascular risk. Our goal was to determine whether PCAT radiomics extracted from coronary CT angiography (CCTA) images are associated with intravascular optical coherence tomography (IVOCT)-identified vulnerable-plaque characteristics (e.g., microchannels (MC) and thin-cap fibroatheroma (TCFA)). The CCTA and IVOCT images of 30 lesions from 25 patients were registered. The vessels with vulnerable plaques were identified from the registered IVOCT images. The PCAT-radiomics features were extracted from the CCTA images for the lesion region of interest (PCAT-LOI) and the entire vessel (PCAT-Vessel). We extracted 1356 radiomic features, including intensity (first-order), shape, and texture features. The features were reduced using standard approaches (e.g., high feature correlation). Using stratified three-fold cross-validation with 1000 repeats, we determined the ability of PCAT-radiomics features from CCTA to predict IVOCT vulnerable-plaque characteristics. In the identification of TCFA lesions, the PCAT-LOI and PCAT-Vessel radiomics models performed comparably (Area Under the Curve (AUC) ± standard deviation 0.78 ± 0.13, 0.77 ± 0.14). For the identification of MC lesions, the PCAT-Vessel radiomics model (0.89 ± 0.09) was moderately better associated than the PCAT-LOI model (0.83 ± 0.12). In addition, both the PCAT-LOI and the PCAT-Vessel radiomics model identified coronary vessels thought to be highly vulnerable to a similar standard (i.e., both TCFA and MC; 0.88 ± 0.10, 0.91 ± 0.09). The most favorable radiomic features tended to be those describing the texture and size of the PCAT. The application of PCAT radiomics can identify coronary vessels with TCFA or MC, consistent with IVOCT. Furthermore, the use of CCTA radiomics may improve risk stratification by noninvasively detecting vulnerable-plaque characteristics that are only visible with IVOCT.
| S-EPMC10045206 | biostudies-literature
Project description:In this single-center cross-sectional study on patients undergoing coronary computed tomography angiography (CCTA), we assessed the prognostic significance of metabolic dysfunction associated steatotic liver disease (MASLD), metabolic syndrome (MetS), and CCTA-derived parameters for predicting major adverse cardiovascular events (MACE). Over a mean follow-up of 26.9 months, 2038 patients were analyzed, with 361 (17.7%) experiencing MACE. MASLD was associated with a higher MACE incidence (25.90% vs. 14.71% without MASLD, p < 0.001). Cox regression revealed significant associations between MASLD, coronary calcium score (CCS), number of plaques (NoP), epicardial fat volume (EFV), and MACE, with hazard ratios of 1.843, 1.001, 1.097, and 1.035, respectively (p < 0.001 for all). A composite risk score integrating CCS, NoP, EFV, and MASLD demonstrated superior predictive value for MACE (AUC = 0.948) compared to individual variables (p < 0.0001 for all). In conclusion, MASLD is linked to an elevated risk of MACE, and a comprehensive risk-scoring system incorporating imaging and clinical factors enhances MACE prediction accuracy.
| S-EPMC10971240 | biostudies-literature
Project description:This study evaluates the association between high sensitivity troponin I (hsTnI) and T (hsTnT) and the morphology of coronary artery plaques detected by coronary computed tomography angiography (CCTA) in patients with suspected coronary artery disease (CAD).Patients undergoing CCTA were prospectively enrolled. CCTA was indicated by a low to intermediate pretest probability for CAD during routine clinical care. Within 24 hours of CCTA examination, peripheral blood samples were taken to measure hsTnI, hsTnT, and N-terminal probrain natriuretic peptide (NT-proBNP).A total of 99 patients were enrolled with 43% without CAD, 9% with noncalcified plaques, 28% with calcified plaques, and 19% with mixed type plaque lesions. Both hsTnI and hsTnT levels were able to discriminate significantly between the groups, especially in the presence of mixed coronary plaques (AUC range: 0.741-0.752; p = 0.0001). In multivariate logistic regression models, hsTnT, but not hsTnI, was still significantly associated with mixed coronary plaque morphology (odds ratio?=?8.968; 95% CI 1.999-40.241; p = 0.004).Both hsTnI and hsTnT are able to discriminate between different coronary artery plaques morphologies, whereas hsTnT was significantly associated with mixed coronary plaques in patients with suspected CAD. This trial is registered with NCT03074253.
| S-EPMC5540457 | biostudies-literature
Project description:AimsIdentification of invasive and radionuclide imaging markers of coronary plaque vulnerability by a single, widely available non-invasive technique may provide the opportunity to identify vulnerable plaques and vulnerable patients in broad populations. Our aim was to assess whether radiomic analysis outperforms conventional assessment of coronary computed tomography angiography (CTA) images to identify invasive and radionuclide imaging markers of plaque vulnerability.Methods and resultsWe prospectively included patients who underwent coronary CTA, sodium-fluoride positron emission tomography (NaF18-PET), intravascular ultrasound (IVUS), and optical coherence tomography (OCT). We assessed seven conventional plaque features and calculated 935 radiomic parameters from CTA images. In total, 44 plaques of 25 patients were analysed. The best radiomic parameters significantly outperformed the best conventional CT parameters to identify attenuated plaque by IVUS [fractal box counting dimension of high attenuation voxels vs. non-calcified plaque volume, area under the curve (AUC): 0.72, confidence interval (CI): 0.65-0.78 vs. 0.59, CI: 0.57-0.62; P < 0.001], thin-cap fibroatheroma by OCT (fractal box counting dimension of high attenuation voxels vs. presence of low attenuation voxels, AUC: 0.80, CI: 0.72-0.88 vs. 0.66, CI: 0.58-0.73; P < 0.001), and NaF18-positivity (surface of high attenuation voxels vs. presence of two high-risk features, AUC: 0.87, CI: 0.82-0.91 vs. 0.65, CI: 0.64-0.66; P < 0.001).ConclusionCoronary CTA radiomics identified invasive and radionuclide imaging markers of plaque vulnerability with good to excellent diagnostic accuracy, significantly outperforming conventional quantitative and qualitative high-risk plaque features. Coronary CTA radiomics may provide a more accurate tool to identify vulnerable plaques compared with conventional methods. Further larger population studies are warranted.
| S-EPMC6806259 | biostudies-literature
Project description:BackgroundExtracranial atherosclerosis is one of the major causes of stroke. Carotid computed tomography angiography (CTA) is a widely used imaging modality that allows detailed assessments of plaque characteristics. This study aimed to develop and test radiomics models of carotid plaques and perivascular adipose tissue (PVAT) to distinguish symptomatic from asymptomatic plaques and compare the diagnostic value between radiomics models and traditional CTA model.MethodsA total of 144 patients with carotid plaques were divided into symptomatic and asymptomatic groups. The traditional CTA model was built by the traditional radiological features of carotid plaques measured on CTA images which were screened by univariate analysis and multivariable logistic regression. We extracted and screened radiomics features from carotid plaques and PVAT. Then, a support vector machine was used for building plaque and PVAT radiomics models, as well as a combined model using traditional CTA features and radiomics features. The diagnostic value between radiomics models and traditional CTA model was compared in identifying symptomatic carotid plaques by Delong method.ResultsThe area under curve (AUC) values of traditional CTA model were 0.624 and 0.624 for the training and validation groups, respectively. The plaque radiomics model and PVAT radiomics model achieved AUC values of 0.766, 0.740 and 0.759, 0.618 in the two groups, respectively. Meanwhile, the combined model of plaque and PVAT radiomics features and traditional CTA features had AUC values of 0.883 and 0.840 for the training and validation groups, respectively, and the receiver operating characteristic curves of combined model were significantly better than those of traditional CTA model in the training group (P<0.001) and validation group (P=0.029).ConclusionsThe combined model of the radiomics features of carotid plaques and PVAT and the traditional CTA features significantly contributes to identifying high-risk carotid plaques compared with traditional CTA model.
| S-EPMC10498225 | biostudies-literature
Project description:ObjectivesTo compare the detection of relevant extracardiac findings (ECFs) on coronary computed tomography angiography (CTA) and invasive coronary angiography (ICA) and evaluate the potential clinical benefit of their detection.MethodsThis is the prespecified subanalysis of ECFs in patients presenting with a clinical indication for ICA based on atypical angina and suspected coronary artery disease (CAD) included in the prospective single-center randomized controlled Coronary Artery Disease Management (CAD-Man) study. ECFs requiring immediate therapy and/or further workup including additional imaging were defined as clinically relevant. We evaluated the scope of ECFs in 329 patients and analyzed the potential clinical benefit of their detection.ResultsECFs were detected in 107 of 329 patients (32.5%; CTA: 101/167, 60.5%; ICA: 6/162, 3.7%; p < .001). Fifty-nine patients had clinically relevant ECFs (17.9%; CTA: 55/167, 32.9%; ICA: 4/162, 2.5%; p < .001). In the CTA group, ECFs potentially explained atypical chest pain in 13 of 101 patients with ECFs (12.9%). After initiation of therapy, chest pain improved in 4 (4.0%) and resolved in 7 patients (6.9%). Follow-up imaging was recommended in 33 (10.0%; CTA: 30/167, 18.0%; ICA: 3/162, 1.9%) and additional clinic consultation in 26 patients (7.9%; CTA: 25/167, 15.0%; ICA: 1/162, 0.6%). Malignancy was newly diagnosed in one patient (0.3%; CTA: 1/167, 0.6%; ICA: 0).ConclusionsIn this randomized study, CTA but not ICA detected clinically relevant ECFs that may point to possible other causes of chest pain in patients without CAD. Thus, CTA might preclude the need for ICA in those patients.Trial registrationNCT Unique ID: 00844220 KEY POINTS: • CTA detects ten times more clinically relevant ECFs than ICA. • Actionable clinically relevant ECFs affect patient management and therapy and may thus improve chest pain. • Detection of ECFs explaining chest pain on CTA might preclude the need for performing ICA.
| S-EPMC8660731 | biostudies-literature
Project description:BackgroundComputed tomography angiography (CTA) is used to plan TAVI procedures. We investigated the performance of pre-TAVI CTA for excluding coronary artery disease (CAD).MethodsIn total 127 patients were included. CTA images were analyzed for the presence of ≥ 50% (significant CAD) and ≥ 70% (severe CAD) diameter stenoses in proximal coronary arteries. Results were compared with invasive coronary angiography (ICA) at vessel and patient levels. Primary endpoint was the negative predictive value (NPV) of CTA for the presence of CAD.ResultsA total of 342 vessels were analyzable. NPV of CTA was 97.5% for significant CAD and 96.3% for severe CAD. Positive predictive value and accuracy were 44.8% and 87.1% for significant CAD and 56.3% and 94.4% for severe CAD. At patient level, NPV for significant CAD was 88.6%.ConclusionPre-TAVI CTA shows good performance for ruling out CAD and could be used as a gatekeeper for ICA in selected patients.
| S-EPMC8575747 | biostudies-literature
Project description:BackgroundCoronary computed tomography angiography stenosis score (CCTA-SS) is a proposed diagnosis score that considers the plaque characteristics, myocardial function, and the diameter reduction rate of the lesions. This study aimed to evaluate the diagnostic performance of the CCTA-SS in seeking coronary artery disease (CAD).MethodsThe 228 patients with suspected CAD who underwent CCTA and invasive coronary angiography (ICA) procedures were under examination. The diagnostic performance was evaluated with the receiver operating curve (ROC) for CCTA-SS in detecting CAD (defined as a diameter reduction of ≥ 50%) and severe CAD (defined as a diameter reduction of ≥ 70%).ResultsThe area under ROC (AUC) of CCTA-SS was 0.909 (95% CI: 0.864-0.943), which was significantly higher than that of CCTA (AUC: 0.826; 95% CI: 0.771-0.873; P = 0.0352) in diagnosing of CAD with a threshold of 50%. The optimal cutoff point of CCTA-SS was 51% with a sensitivity of 90.66%, specificity of 95.65%, positive predictive value of 98.80%, negative predictive value of 72.13%, and accuracy of 91.67%, whereas the optimal cutoff point of CCTA was 55%, and the corresponding values were 87.36%, 93.48%, 98.15%, 65.15%, and 88.60%, respectively. With a threshold of 70%, the performance of CCTA-SS with an AUC of 0.927 (95% CI: 0.885-0.957) was significantly higher than that of CCTA with an AUC of 0.521 (95% CI: 0.454-0.587) (P < 0.0001).ConclusionsCCTA-SS significantly improved the diagnostic accuracy of coronary stenosis, including CAD and severe CAD, compared with CCTA.
| S-EPMC10854174 | biostudies-literature