Symptomatic Plaques Research Articles

Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.

Carotid atherosclerotic ischemic stroke threatens human health and life. The aim of this study is to establish a radiomics model of perivascular adipose tissue (PVAT) around carotid plaque for evaluation of the association between Peri-carotid Adipose Tissue structural changes with stroke and transient ischemic attack. A total of 203 patients underwent head and neck computed tomography angiography examination in our hospital. All patients were divided into a symptomatic group (71 cases) and an asymptomatic group (132 cases) according to whether they had acute/subacute stroke or transient ischemic attack. The radiomic signature (RS) of carotid plaque PVAT was extracted, and the minimum redundancy maximum correlation, recursive feature elimination, and linear discriminant analysis algorithms were used for feature screening and dimensionality reduction. It was found that the RS model achieved the best diagnostic performance in the Bagging Decision Tree algorithm, and the training set (AUC, 0.837; 95%CI: 0.775, 0.899), testing set (AUC, 0.834; 95%CI: 0.685, 0.982). Compared with the traditional feature model, the RS model significantly improved the diagnostic efficacy for identifying symptomatic plaques in the testing set (AUC: 0.834 vs. 0.593; Z = 2.114, p = 0.0345). The RS model of PVAT of carotid plaque can be used as an objective indicator to evaluate the risk of plaque and provide a basis for risk stratification of carotid atherosclerotic disease.

Abstract 102: Microanatomy of Intracranial Human Thrombi by Single Nuclei Transcriptomics

Introduction: Microvascular dysfunction and inflammation are thought to underlie reperfusion failure following endovascular thrombectomy. Here we present the first study to produce a transcriptome-based cellular landscape of human intracranial thrombi highlighting the importance of cellular plasticity and intercellular communication at the site of occlusion. Methods: We performed single nuclei RNA-sequencing (snRNA-seq) on intracranial human thrombi harvested during revascularization. Unsupervised clustering, data visualization, differential expression and functional gene ontology/pathway analysis were utilized to deconvolve expression data into cell type-specific expression profiles. Thrombi snRNA-seq data were integrated with single cell RNA-seq data from symptomatic and asymptomatic human carotid plaques and healthy brain vasculature to contextualize thrombi in atherosclerotic disease, perform diffusion coefficient analysis, and identify ligand-receptor interactions. Results: Unbiased clustering identified six cellular populations in distinct effector states within the thrombus microenvironment. Functional gene ontology and pathway analysis revealed a monocyte subpopulation in a distinct endothelial-activation and neuroplasticity state, supporting the notion of cellular trans-differentiation and interconversion. Integration with carotid plaque data and diffusion coefficient analysis revealed shared transcriptional programs existing in a continuum, progressing from asymptomatic plaque to embolized thrombus. Ligand-receptor analysis identified macrophage mediated T-cell activation, pro-inflammatory response, immunological synapse stabilization, neuroplasticity, and monocyte trans-endothelial migration. Conclusion: Our novel application of snRNA-seq to thrombectomy specimens provides the highest resolution exploration of cellular differences and a best understanding of individual contextualized cell function to date. This detailed cellular landscape will facilitate mapping novel interventional targets with direct functional relevance and allow for greater personalization of post-reperfusion therapy.

CT-Diagnosed Non-Alcoholic Fatty Liver Disease as a Risk Predictor of Symptomatic Carotid Plaque and Cerebrovascular Symptoms.

We aimed to test whether computed tomography (CT)-diagnosed Non-Alcoholic Fatty Liver Disease (NAFLD) is a risk factor for cerebrovascular symptoms in patients with suspected atherosclerotic disease. A total of 550 patients (mean age 65.2 ± 8.8years, 370 males) with carotid plaques who underwent carotid computed tomographic angiography (CTA) and unenhanced abdominal CT were retrospectively analyzed. NAFLD was diagnosed by abdominal CT. Carotid CTA assessed the presence of carotid artery stenosis or plaque. The relationship between NAFLD and cerebrovascular symptoms was analyzed using generalized estimating equations and receiver operating characteristic (ROC) analysis. The prevalence of NAFLD was significantly higher in symptomatic patients (76.5 vs 9.8%; P < .001). After adjusting for several confounding factors (e.g., hypertension and hyperlipidemia), univariate and multivariate logic regression analysis revealed that NAFLD was still strongly associated with cerebrovascular symptoms (odds ratio, 22.81; 95% CI 13.03-39.93; P < .001). ROC analysis showed that the area under the curve for discriminating symptomatic and asymptomatic plaques using NAFLD measurements was 0.833, with a sensitivity of 76.5% and a specificity of 90.2%. NAFLD is strongly associated with an increased risk of cerebrovascular symptoms. It may be an important predictor of symptomatic carotid plaque and cerebrovascular symptoms.

Characteristics of the gut microbiota of patients with symptomatic carotid atherosclerotic plaques positive for bacterial genetic material.

The gut microbiota (GM) is believed to be closely associated with symptomatic carotid atherosclerosis (SCAS), yet more evidence is needed to substantiate the significant role of GM in SCAS. This study, based on the detection of bacterial DNA in carotid plaques, explores the characteristics of GM in SCAS patients with plaque bacterial genetic material positivity, aiming to provide a reference for subsequent research. We enrolled 27 healthy individuals (NHF group) and 23 SCAS patients (PFBS group). We utilized 16S rDNA V3-V4 region gene sequencing to analyze the microbiota in fecal samples from both groups, as well as in plaque samples from the carotid bifurcation extending to the origin of the internal carotid artery in all patients. Our results indicate significant differences in the gut microbiota (GM) between SCAS patients and healthy individuals. The detection rate of bacterial DNA in plaque samples was approximately 26%. Compared to patients with negative plaques (PRSOPWNP group), those with positive plaques (PRSOPWPP group) exhibited significant alterations in their GM, particularly an upregulation of 11 bacterial genera (such as Klebsiella and Streptococcus) in the gut, which were also present in the plaques. In terms of microbial gene function prediction, pathways such as Fluorobenzoate degradation were significantly upregulated in the GM of patients with positive plaques. In summary, our study is the first to identify significant alterations in the gut microbiota of patients with positive plaques, providing crucial microbial evidence for further exploration of the pathogenesis of SCAS.

Identification of symptomatic carotid artery plaque: a predictive model combining angiography with optical coherence tomography.

Symptomatic carotid artery disease is indicative of an elevated likelihood of experiencing a subsequent stroke, with the morphology of plaque and its specific features being closely linked to the risk of stroke occurrence. Our study based on the characteristics of carotid plaque assessed by optical coherence tomography (OCT), the plaque morphology evaluated by digital subtraction angiography (DSA) and clinical laboratory indicators were combined, develop a combined predictive model to identify symptomatic carotid plaque. Patients diagnosed with carotid atherosclerotic stenosis who underwent whole-brain DSA and OCT examination at the Affiliated Hospital of Jining Medical University from January 2021 to November 2023 were evaluated. Clinical features, as well as DSA and OCT plaque characteristics, were analyzed for differences between symptomatic and asymptomatic cohorts. An analysis of logistic regression was carried out to identify factors associated with the presence of symptomatic carotid plaque. A multivariate binary logistic regression equation was established with the odds ratio (OR) serving as the risk assessment parameter. The receiver operating characteristic curve was utilized to assess the combined predictive model and independent influencing factors. A total of 52 patients were included in the study (symptomatic: 44.2%, asymptomatic: 55.8%). Symptomatic carotid stenosis was significantly linked to four main factors: low-density lipoprotein-cholesterol >3.36 mmol/L [OR, 6.400; 95% confidence interval (CI), 1.067-38.402; p = 0.042], irregular plaque (OR, 6.054; 95% CI, 1.016-36.083; p = 0.048), ruptured plaque (OR, 6.077; 95% CI, 1.046-35.298; p = 0.048), and thrombus (OR, 6.773; 95% CI, 1.194-38.433; p = 0.044). The combined predictive model generated using four indicators showed good discrimination (Area Under Curve, 0.924; 95% CI, 0.815-0. 979). The p value was <0.05 with 78.26% sensitivity and 93.10% specificity. OCT is valuable in evaluating the plaque characteristics of carotid atherosclerotic stenosis. The combined predictive model comprising low-density lipoprotein-cholesterol >3.36 mmol/L, irregular plaque, ruptured plaque, and thrombus could help in the detection of symptomatic carotid plaque. Further research conducted on additional independent cohorts is necessary to confirm the clinical significance of the predictive model for symptomatic carotid plaque.

Signal intensity and volume of carotid intraplaque hemorrhage on magnetic resonance imaging and the risk of ipsilateral cerebrovascular events: The Plaque At RISK (PARISK) study

BackgroundThe Plaque at RISK (PARISK) study demonstrated that patients with a carotid plaque with intraplaque hemorrhage (IPH) have an increased risk of recurrent ipsilateral ischemic cerebrovascular events. It was previously reported that symptomatic carotid plaques with IPH showed higher IPH signal intensity ratios (SIR) and larger IPH volumes than asymptomatic plaques. We explored whether IPH SIR and IPH volume are associated with future ipsilateral ischemic cerebrovascular events beyond the presence of IPH. MethodsTIA and ischemic stroke patients with mild-to-moderate carotid stenosis and an ipsilateral IPH-positive carotid plaque (n=89) from the PARISK study were included. The clinical endpoint was a new ipsilateral ischemic cerebrovascular event during 5 years of follow-up, while the imaging-based endpoint was a new ipsilateral brain infarct on brain MRI after 2 years (n=69). Trained observers delineated IPH, a hyperintense region compared to surrounding muscle tissue on hyper T1-weighted MR images. The IPH SIR was the maximal signal intensity in the IPH region divided by the mean signal intensity of adjacent muscle tissue. The associations between IPH SIR or volume and the clinical and imaging-based endpoint were investigated using Cox-proportional hazard models and logistic regression, respectively. ResultsDuring 5.1 (interquartile range (IQR): 3.1-5.6) years of follow-up, 21 ipsilateral cerebrovascular ischemic events were identified. Twelve new ipsilateral brain infarcts were identified on the 2-year neuro MRI. There was no association for IPH SIR or IPH volume with the clinical endpoint (HR: 0.89 [95% CI: 0.67-1.10] and HR: 0.91 [0.69-1.19] per 100µl increase, respectively) nor with the imaging-based endpoint (OR: 1.04 [0.75-1.45] and OR: 1.21 [0.87-1.68] per 100µl increase, respectively). ConclusionsIPH SIR and IPH volume were not associated with future ipsilateral ischemic cerebrovascular events. Therefore, quantitative assessment of IPH does not seem to provide additional value beyond the presence of IPH for stroke risk assessment.Trial registrationThe PARISK study was registered on ClinicalTrials.gov with ID NCT01208025 on 21 September 2010 (https://clinicaltrials.gov/study/NCT01208025).

HDL subfractions determined by microfluidic chip electrophoresis predict the vulnerability of intracranial plaque: A HRMRI study

AimHigh-density lipoprotein (HDL) can be divided into several subfractions based on density, size and composition. Accumulative evidence strongly suggests that the subfractions of HDL have very different roles in the pathogenesis of atherosclerosis. The purpose of this study was to further delineate the relationship between HDL subfractions extracted by microfluidic chip electrophoresis and the vulnerability of plaques in patients with intracranial atherosclerosis with a high-resolution magnetic resonance imaging (HRMRI) study. MethodsWe prospectively enrolled patients with single atherosclerotic plaque in the middle cerebral artery (MCA) or basilar artery (BA) between July 2020 and Dec 2022 and performed 3-tesla HRMRI on the relevant artery. The HDL cholesterol concentration and HDL subfractions (HDL-2a, HDL-2b and HDL-3) percentage were analyzed in serum samples from the same patients by electrophoresis on a microfluidics system. ResultsA total of 81 MCA or BA plaques [38 (46.9%) symptomatic and 43 (53.1%) asymptomatic] in 81 patients were identified on HRMRI. Patients with symptomatic plaques had a significantly lower HDL-2b level than asymptomatic plaques [symptomatic vs. asymptomatic: 0.16 (0.10–0.18) vs. 0.27(0.21–0.34), p = 0.001]. After adjusting for demographics and vascular risk factors, logistic regression showed that HDL-2b was inversely associated with asymptomatic plaques (B = −0.04, P = 0.017). According to receiver operating characteristic (ROC) curve model analysis, the cutoff point of HDL-2b in predicting asymptomatic plaques was 0.21 mmol/L (Area under curve: 0.719, specificity: 73.7%, sensitivity: 72.1%). Furthermore, plaque enhancement on HRMRI (P < 0.001), positive remodeling (P < 0.001), plaque load (P < 0.001) and luminal stenosis (P < 0.001) were superior among patients with HDL-2b < 0.21 mmol/L. ConclusionsOur data showed that serum HDL-2b levels may serve as a biomarker for predicting vulnerability in intracranial atherosclerotic plaques.

Abstract 045: A Radiomics Based Pipeline for Paired Risk‐Stratification of Intracranial Atherosclerotic Plaques

Introduction High resolution vessel wall imaging (HR‐VWI) enables accurate visualization of intracranial atherosclerotic plaques. Radiomics can be utilized as an objective quantification method of plaque appearance and shape. We aimed to analyze the radiomics features (RFs) obtained from 7T‐HR‐VWI to differentiate between culprit and non‐culprit plaques in patients with intracranial atherosclerotic disease (ICAD). Methods Patients with ICAD as stroke etiology undergoing HR‐VWI were included in the study. Culprit plaques in the vascular territory of the stroke were identified. The degree of stenosis, area degree of stenosis and plaque burden were calculated. Three‐dimensional segmentation of the plaque was performed, and RFs were extracted. We then evaluated multiple machine learning models to predict and identify culprit plaques using significantly different RFs. The dataset was then randomly divided into training and testing datasets, and the trained model was evaluated on the independent testing dataset. Results The study included 33 patients with ICAD as the cause of stroke. Univariate analysis revealed 38 significantly different RFs between culprit and non‐culprit plaques in pre‐contrast MRI, 39 in post‐contrast MRI and 25 RFs that were different between pre and post contrast MRIs. Additionally, seven shape‐based RFs exhibited significant distinctions between the two plaque types. The random forest model achieved an accuracy rate of 81% (88% sensitivity and 75% specificity) in identifying culprit plaques in the independent testing dataset. This model successfully identified the culprit plaque in 7 out of 8 cases during the testing phase. Conclusion In this study symptomatic culprit plaques had a different signature RFs compared to other plaque within the same subject. A machine learning model built with RFs successfully identified the symptomatic atherosclerotic plaques in most cases. Radiomics is a promising tool for stratification of plaques in patients with ICAD.

Computed tomography angiography-based radiomics model to identify high-risk carotid plaques.

Extracranial 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. A 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. The 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). The 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.

Identification of vulnerable carotid plaque with CT-based radiomics nomogram

To develop and validate a radiomics nomogram for identifying high-risk carotid plaques on computed tomography (CT) angiography (CTA). A total of 280 patients with symptomatic (n=131) and asymptomatic (n=139) carotid plaques were divided into a training set (n=135), validation set (n=58), and external test set (n=87). Radiomic features were extracted from CTA images. A radiomics model was constructed based on selected features and a radiomics score (rad-score) was calculated. A clinical factor model was constructed by demographics and CT findings. A radiomics nomogram combining independent clinical factors and the rad-score was constructed. The diagnostic performance of three models was evaluated and validated by region of characteristic curves. Calcification and maximum plaque thickness were the independent clinical factors. Twenty-four features were used to build the radiomics signature. In the validation set, the nomogram (area under the curve [AUC], 0.977; 95% CI, 0.899-0.999) performed better (p=0.017 and p=0.031) than the clinical factor model (AUC, 0.862; 95% CI, 0.746-0.938) and radiomics signature (AUC, 0.944; 95% CI, 0.850-0.987). In external test set, the nomogram (AUC, 0.952; 95% CI, 0.884-0.987) and radiomics signature (AUC, 0.932; 95% CI, 0.857-0.975) showed better discrimination capability (p=0.002 and p=0.037) than clinical factor model (AUC, 0.818; 95% CI, 0.721-0.892). The CT-based nomogram showed satisfactory performance in identification of high-risk plaques in carotid arteries, and it may serve as a potential non-invasive tool to identify carotid plaque vulnerability and risk stratification.

Neovascularization From the Carotid Artery Lumen Into the Carotid Plaque Confirmed by Contrast-Enhanced Ultrasound and Histology.

This study was aimed at assessing intraplaque neovessels, focusing on neovascularization from the vascular luminal side using contrast-enhanced ultrasound (CEUS) and determining that this contrast effect indicates that the neovessel is connected to the vessel lumen histopathologically. Whether plaque vulnerability can be assessed more accurately was also investigated. We enrolled consecutive patients with internal carotid artery stenosis who underwent carotid endarterectomy (CEA) and pre-operative CEUS with perflubutane of the carotid arteries. We graded the contrast effect semi-quantitatively from the vascular luminal and adventitial sides. We compared the contrast effect with the pathological findings, especially the neovascularization of the CEA specimens. In total, 68 carotid arterial atheromatous plaques (47 symptomatic) were analyzed. Symptomatic plaques were significantly correlated with stronger contrast effects from the luminal side than from the adventitial side (p=0.0095). Microbubbles from the luminal side appeared to flow mainly into the plaque shoulder. The contrast effect value for the plaque shoulder and neovessel density were significantly correlated (ρ=0.35, p=0.031). Neovessel density was significantly higher in symptomatic than in asymptomatic plaques (56.2 ± 43.7/mm2 and 18.1 ± 15.2/mm2, respectively, p < 0.0001). Serial histological sections of CEA specimens in a symptomatic plaque with a strong contrast effect from the luminal side revealed multiple neovessels fenestrated to the vessel lumen with endothelial cells, consistent with the CEUS findings. Contrast-enhanced ultrasound can be used to evaluate neovessels originating from the luminal side, histopathologically confirmed in serial sections. Symptomatic vulnerable plaque is correlated more significantly with intraplaque neovascularization from the luminal side than with neovascularization from the adventitia.

Increased Piezo1 expression in myofibroblasts in patients with symptomatic carotid atherosclerotic plaques undergoing carotid endarterectomy: A pilot study.

We aimed to investigate Piezo1 expression in myofibroblasts in symptomatic and asymptomatic patients undergoing carotid endarterectomy and its relationship with atherosclerotic plaque formation. This cross-sectional study analyzed carotid plaques of 17 randomly selected patients who underwent carotid endarterectomy from May 2015 to August 2017. In total, 51 sections (the most stenotic lesion, and the sections 5-mm proximal and distal) stained with hematoxylin-eosin and elastica-Masson were examined. Immunohistochemistry was performed using antibodies to Piezo1. The Piezo1 score of a section was calculated semiquantitatively, averaged across 30 randomly selected myofibroblasts in the fibrous cap of the plaque. Of 17 patients (mean age: 74.2 ± 7.1 years), 15 were men, 9 had diabetes mellitus, and 13 had hypertension. Symptomatic patients had higher mean Piezo1 score than asymptomatic patients (1.78 ± 0.23 vs 1.34 ± 0.17, p < .001). Univariate linear regression analyses suggested an association between plaque rupture, thin-cap fibroatheroma and microcalcifications and the Piezo1 score (p = .001, .008, and 0.003, respectively). Increased Piezo1 expression of myofibroblasts may be associated with atherosclerotic carotid plaque instability. Further study is warranted to support this finding.

Imaging features of vertebrobasilar dolichoectasia combined with posterior circulation ischemic stroke: A vessel wall magnetic resonance imaging study

PurposeTo elucidate the vessel wall changes of vertebrobasilar dolichoectasia (VBD) with ischemic stroke, using vessel wall magnetic resonance imaging (VW-MRI). MethodThirty-four patients with VBD (22 with stroke and 12 without stroke) who underwent VW-MRI were recruited. Forty-one patients without VBD who underwent VW-MRI were also recruited if they had a recent stroke due to atherosclerosis in the basilar artery or the intracranial vertebral artery. The vessel wall features of VBD were compared between stroke and non-stroke groups. The plaque characteristics were compared between VBD and non-VBD stroke patients. ResultsThe frequency of plaques was higher (54.5% vs. 8.3%, P = 0.011) in VBD patients with stroke than that in non-stroke patients, while the frequencies of aneurysm, dissection, intraluminal thrombus, and diffuse/concentric wall enhancement did not differ. When the plaque features were compared between plaque-positive stroke patients with and without VBD, the degree of stenosis (31.0% ± 26.8% vs. 71.5% ± 19.0%, P < 0.001), normalized wall index (NWI) (0.7 ± 0.1 vs. 0.9 ± 0.1, P < 0.001), and remodeling index (RI) (1.0 ± 0.4 vs. 1.3 ± 0.4, P = 0.023) were lower in the VBD group, while intraplaque hemorrhage, and enhancement ratio showed no difference. ConclusionsThis preliminary study suggests that atherosclerosis may be an important cause of stroke in VBD patients. Symptomatic plaques in VBD patients have a lower degree of stenosis, NWI, and RI than that in non-VBD patients. VW-MRI may help to assess stroke mechanisms and identify VBD patients at high risk.

Radiomics and artificial neural networks modelling for identification of high-risk carotid plaques.

In this study, we aimed to investigate the classification of symptomatic plaques by evaluating the models generated via two different approaches, a radiomics-based machine learning (ML) approach, and an end-to-end learning approach which utilized deep learning (DL) techniques with several representative model frameworks. We collected high-resolution magnetic resonance imaging (HRMRI) data from 104 patients with carotid artery stenosis, who were diagnosed with either symptomatic plaques (SPs) or asymptomatic plaques (ASPs), in two medical centers. 74 patients were diagnosed with SPs and 30 patients were ASPs. Sampling Perfection with Application-optimized Contrasts (SPACE) by using different flip angle Evolutions was used for MRI imaging. Repeated stratified five-fold cross-validation was used to evaluate the accuracy and receiver operating characteristic (ROC) of the trained classifier. The two proposed approaches were investigated to train the models separately. The difference in the model performance of the two proposed methods was quantitatively evaluated to find a better model to differentiate between SPs and ASPs. 3D-SE-Densenet-121 model showed the best performance among all prediction models (AUC, accuracy, precision, sensitivity, and F1-score of 0.9300, 0.9308, 0.9008, 0.8588, and 0.8614, respectively), which were 0.0689, 0.1119, 0.1043, 0.0805, and 0.1089 higher than the best radiomics-based ML model (MLP). Decision curve analysis showed that the 3D-SE-Densenet-121 model delivered more net benefit than the best radiomics-based ML model (MLP) with a wider threshold probability. The DL models were able to accurately differentiate between symptomatic and asymptomatic carotid plaques with limited data, which outperformed radiomics-based ML models in identifying symptomatic plaques.

PITFALLS IN THE CLINICAL DIAGNOSIS OF ORAL SQUAMOUS CELL CARCINOMA

Oral squamous cell carcinoma (OSCC) may have several clinical manifestations, which can be confused with other more common lesions found in the oral cavity, delaying diagnoses and treatment, consequently worsening prognoses. We present two clinical cases of patients diagnosed with OSCC and no previous history of smoking or alcoholism. A 74-year-old man presented a small, symptomatic white plaque on the right lateral border of the tongue for 3 months. The initial diagnosis was frictional keratosis due to close contact to the lower second molar. The other patient was a 51-year-old man with symptomatic red area on the gingiva with 3 years of evolution. Initial clinical diagnosis was a possible lichen planus. Both patients underwent incisional biopsy, confirming the diagnosis of OSCC. In summary, it is important to recognize the different aspects of OSCC and establish the diagnosis as soon as possible, since clinical stages are directly related to prognoses. Oral squamous cell carcinoma (OSCC) may have several clinical manifestations, which can be confused with other more common lesions found in the oral cavity, delaying diagnoses and treatment, consequently worsening prognoses. We present two clinical cases of patients diagnosed with OSCC and no previous history of smoking or alcoholism. A 74-year-old man presented a small, symptomatic white plaque on the right lateral border of the tongue for 3 months. The initial diagnosis was frictional keratosis due to close contact to the lower second molar. The other patient was a 51-year-old man with symptomatic red area on the gingiva with 3 years of evolution. Initial clinical diagnosis was a possible lichen planus. Both patients underwent incisional biopsy, confirming the diagnosis of OSCC. In summary, it is important to recognize the different aspects of OSCC and establish the diagnosis as soon as possible, since clinical stages are directly related to prognoses.

Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography

ObjectiveThis study aimed to develop and validate a machine learning model incorporating both dual-energy computed tomography (DECT) angiography quantitative parameters and clinically relevant risk factors for the identification of symptomatic carotid plaques to prevent acute cerebrovascular events. MethodsThe data of 180 patients with carotid atherosclerosis plaques were analysed from January 2017 to December 2021; 110 patients (64.03±9.58 years old, 20 women, 90 men) were allocated to the symptomatic group, and 70 patients (64.70±9.89 years old, 50 women, 20 men) were allocated to the asymptomatic group. Overall, five machine learning models using the XGBoost algorithm, based on different CT and clinical features, were developed in the training cohort. The performances of all five models were assessed in the testing cohort using receiver operating characteristic curves, accuracy, recall rate, and F1 score. ResultsThe shapley additive explanation (SHAP) value ranking showed fat fraction (FF) as the highest among all CT and clinical features and normalised iodine density (NID) as the 10th. The model based on the top 10 features from the SHAP measurement showed optimal performance (area under the curve [AUC] .885, accuracy .833, recall rate .933, F1 score .861), compared with the other four models based on conventional CT features (AUC .588, accuracy .593, recall rate .767, F1 score .676), DECT features (AUC .685, accuracy .648, recall rate .667, F1 score .678), conventional CT and DECT features (AUC .819, accuracy .740, recall rate .867, F1 score .788), and all CT and clinical features (AUC .878, accuracy .833, recall rate .867, F1 score .852). ConclusionFF and NID can serve as useful imaging markers of symptomatic carotid plaques. This tree-based machine learning model incorporating both DECT and clinical features could potentially comprise a non-invasive method for identification of symptomatic carotid plaques to guide clinical treatment strategies.

Comparative Analysis of Symptomatic and Asymptomatic Carotid Plaque With Bilateral Mild Carotid Stenosis (30%-50%).

HomeStrokeAhead of PrintComparative Analysis of Symptomatic and Asymptomatic Carotid Plaque With Bilateral Mild Carotid Stenosis (30%–50%) No AccessResearch ArticleRequest AccessAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissionsDownload Articles + Supplements ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toSupplemental MaterialNo AccessResearch ArticleRequest AccessComparative Analysis of Symptomatic and Asymptomatic Carotid Plaque With Bilateral Mild Carotid Stenosis (30%–50%) Atulabh Vajpeyee, Pushan Sharma, Piyush Kumar Anshu, Shivam Tiwari, Lokendra Bahadur Yadav, Kapil Vyas and Manisha Vajpeyee Atulabh VajpeyeeAtulabh Vajpeyee Correspondence to: Atulabh Vajpeyee, MD, DM (Neurology), FINS, Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, India313001. Email E-mail Address: [email protected] https://orcid.org/0000-0002-7942-4302 Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India (A.V., P.S., P.K.A., S.T., L.B.Y.). *A. Vajpeyee, S. Tiwari, and L.B. Yadav contributed equally. Search for more papers by this author , Pushan SharmaPushan Sharma https://orcid.org/0000-0002-4965-6655 Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India (A.V., P.S., P.K.A., S.T., L.B.Y.). Search for more papers by this author , Piyush Kumar AnshuPiyush Kumar Anshu https://orcid.org/0000-0003-1606-9208 Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India (A.V., P.S., P.K.A., S.T., L.B.Y.). Search for more papers by this author , Shivam TiwariShivam Tiwari https://orcid.org/0000-0001-9465-1215 Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India (A.V., P.S., P.K.A., S.T., L.B.Y.). *A. Vajpeyee, S. Tiwari, and L.B. Yadav contributed equally. Search for more papers by this author , Lokendra Bahadur YadavLokendra Bahadur Yadav https://orcid.org/0000-0002-5035-0573 Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India (A.V., P.S., P.K.A., S.T., L.B.Y.). *A. Vajpeyee, S. Tiwari, and L.B. Yadav contributed equally. Search for more papers by this author , Kapil VyasKapil Vyas Department of Radiology, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India.(K.V.) Search for more papers by this author and Manisha VajpeyeeManisha Vajpeyee https://orcid.org/0000-0001-5010-2863 Department of Reproductive Medicine and Research, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, Rajasthan, India. (M.V.) Search for more papers by this author Originally published2 Jun 2023https://doi.org/10.1161/STROKEAHA.123.042874Stroke. 2023;0"Comparative Analysis of Symptomatic and Asymptomatic Carotid Plaque With Bilateral Mild Carotid Stenosis (30%–50%)." Stroke, , pp. FootnotesFor Sources of Funding and Disclosures, see page XXX.Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/STROKEAHA.123.042874.*A. Vajpeyee, S. Tiwari, and L.B. Yadav contributed equally.Correspondence to: Atulabh Vajpeyee, MD, DM (Neurology), FINS, Department of Neurosciences, Pacific Medical College and Hospital, Pacific Medical University, Udaipur, India313001. Email [email protected]com Previous Back to top Next FiguresReferencesRelatedDetails Advertisement Article InformationMetrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.123.042874PMID: 37264912 Originally publishedJune 2, 2023 Keywordscarotid arterieshemorrhagefibrous capmorphologyconsentPDF download Advertisement SubjectsPhysiologyVascular Biology

Transforming growth factor-β2 is associated with atherosclerotic plaque stability and lower risk for cardiovascular events.

Transforming growth factor-beta (TGF-β) exists in three isoforms TGF-β1, -β2 and -β3. TGF-β1 has been suggested to be important for maintaining plaque stability, yet the role of TGF-β2 and -β3 in atherosclerosis remains to be investigated. This study explores the association of these three isoforms of TGF-β with plaque stability in the human atherosclerotic disease. TGF-β1, -β2 and -β3 proteins were quantified in 223 human carotid plaques by immunoassays. Indications for the endarterectomy were: symptomatic carotid plaque with stenosis >70% or without symptoms and >80% stenosis. Plaque mRNA levels were assessed by RNA sequencing. Plaque components and extracellular matrix were measured histologically and biochemically. Matrix metalloproteinases were measured with ELISA. Monocyte chemoattractant protein-1 (MCP-1) was measured with immunoassays. The effect of TGF-β2 on inflammation and protease activity was investigated in vitro using THP-1 and RAW264.7 macrophages. Patients were followed longitudinally for cardiovascular events.TGF-β2 was the most abundant isoform and was increased at both protein and mRNA levels in asymptomatic plaques. TGF-β2 was the main determinant separating asymptomatic plaques in an Orthogonal Projections to Latent Structures Discriminant Analysis. TGF-β2 correlated positively to features of plaque stability and inversely to markers of plaque vulnerability. TGF-β2 was the only isoform inversely correlated to the matrix-degrading matrix metalloproteinase-9 and inflammation in the plaque tissue. In vitro, TGF-β2 pre-treatment reduced MCP-1 gene and protein levels as well as matrix metalloproteinase-9 gene levels and activity. Patients with plaques with high TGF-β2 levels had a lower risk to suffer from future cardiovascular events. TGF-β2 is the most abundant TGF-β isoform in human plaques and may maintain plaque stability by decreasing inflammation and matrix degradation.

Identification of vulnerable carotid plaque with histologically validated CT-derived plaque maps.

Ruptured carotid plaque causes stroke, but differentiating rupture-prone necrotic core from fibrous tissue with CT is limited by overlap of X-ray attenuation. We investigated the ability of CT-derived plaque maps created from ratios of plaque/contrast attenuation to identify histologically proven vulnerable plaques. Seventy patients underwent carotid CT angiography and carotid endarterectomy. A derivation cohort of 20 patients had CT images matched with histology and carotid plaque components attenuation defined. In a validation cohort of 50 patients, CT-derived plaque maps were compared in 43 symptomatic vs 40 asymptomatic carotid plaques and accuracy detecting vulnerable plaques calculated. In 250 plaque areas co-registered with histology, the median attenuation (HU) of necrotic core 43(26-63), fibrous plaque 127(110-162) and calcified plaque 964 (816-1207) created significantly different ratios of plaque/contrast attenuation. CT-derived plaque maps revealed symptomatic plaques had larger necrotic core than asymptomatic (13.5%(5.9-33.3) vs 7.4%(2.3-14.3), p = 0.004) with large necrotic core predicting symptoms (area under ROC curve 0.68, p = 0.004). Twenty-four of 47 carotid plaques were histologically classified as most vulnerable (Starry-Type VI). Plaque maps revealed Type VI plaques had a greater necrotic core volume than Type IV/V plaques and a necrotic core/fibrous plaque ratio >0.5 distinguished Type VI plaques with sensitivity 75.0% (55.1-88.0) and specificity of 39.1% (22.2-59.2). Carotid plaque components can be differentiated by CT using a ratio of plaque/contrast attenuation. CT-derived plaque map volumes of necrotic core help distinguished the most vulnerable plaques. CT-derived plaque maps based on plaque/contrast attenuation may provide new markers of carotid plaque vulnerability.

Systematic Review on Magnetic Resonance Angiography with Vessel Wall Imaging for the Characterization of Symptomatic Carotid Artery Plaque

To perform a systematic literature review to assess the usefulness of performing magnetic resonance angiography (MRA) with vessel wall imaging (VWI) sequences for the assessment of symptomatic carotid artery plaques and the identification of risky plaque features predisposing for stroke. We performed a systematic review of the literature pertaining to MRA with VWI techniques in patients with carotid artery disease, focusing on symptomatic patients' plaque features and morphology. Independent reviewers screened and analyzed data extracted from eligible studies, and a modified Newcastle-Ottawa Scale was used to appraise the quality of the design and content of the selected manuscripts to achieve an accurate interpretation. This review included nineteen peer-reviewed manuscripts, all of them including MRA and VWI assessments of the symptomatic carotid artery plaque. We focused on patients' comorbidities and reviewed plaque features, including intraplaque hemorrhage, a lipid-rich necrotic core, a ruptured fibrous cap, and plaque ulceration. MRA with VWI is a useful tool in the evaluation of carotid artery plaques. This imaging technique allows clinicians to identify plaques at risk of causing a neurovascular event. The presence of intraplaque hemorrhage, plaque ulceration, a ruptured fibrous cap, and a lipid-rich necrotic core are associated with neurovascular symptoms. The timely identification of these features could have a positive impact on neurovascular event prevention.