Carotid Computed Tomography Angiography Research Articles

Examining the Prevalence of Left Atrial Appendage Thrombus in a Cohort of Acute Stroke Patients with an Extended Computed Tomography Angiographic Protocol

Introduction: Current guidelines recommend transthoracic echocardiography (TTE) for routine screening of cardiac emboli; however, the visualization of the left atrial appendage (LAA) where the thrombi are commonly found is poor. Transesophageal echocardiography (TEE) would provide better detectability of LAA thrombus, but it is a time-consuming and semi-invasive method. Extending non-gated carotid computed tomography angiography (CTA) examination to the LAA could reliably detect thrombi and could also aid treatment and secondary prevention of stroke. Methods: We extended the CTA scan range of acute stroke patients 4 cm below the carina to include the left atrium and appendage. During the review, we evaluated LAA thrombi based on contrast relations. We then used gradient boosting to identify the most important predictors of LAA thrombi from a variety of different clinical parameters. Results: We examined 240 acute stroke patients' extended CTA scans. We detected LAA thrombi in eleven cases (4.58%), eight of them had atrial fibrillation. 23.75% of all patients (57 cases) had recently discovered or previously known atrial fibrillation. Windsack morphology was the most commonly associated morphology with filling defects on CTA. According to the gradient-boosting analysis, LAA morphology showed the most predictive value for thrombi. Conclusion: Our extended CTA scans reliably detected LAA thrombi even in cases where TTE did not and showed that 2 patients’ LAA thrombus would have been untreated based on electrocardiogram monitoring and TTE. We also showed that the benefits of CTA outweigh the disadvantages arising from the slight amount of excess radiation.

Relationship between in-stent restenosis following carotid artery stenting and platelet reactivity to clopidogrel

ObjectiveTo analyze the relationship between in-stent restenosis (ISR) following carotid artery stenting (CAS) and platelet clopidogrel reactivity confirmed by the P2Y12 reaction unit (PRU) and inhibition rate (IR).MethodsWe retrospectively analyzed...

Benefits of low-dose carotid CT angiography in stroke patients

Introduction: Computed tomography angiography (CTA) represents the gold standard as a method for the diagnosis of carotid artery diseases. The current topic is the use of CTA for the evaluation of carotid arteries with a reduction in the dose of contrast agent and dose of ionizing radiation, which, with adequate preparation, would enable the use of this method in some risk groups. The aim of this study was to evaluate the feasibility and image quality of a new low-dose CTA protocol in comparison with a standard protocol. Methods: Forty patients with recumbent ischemic stroke were included in the study, twenty of whom underwent lowdose CTA, and the remaining twenty underwent a standard CTA protocol of the carotid arteries. Results: No significant difference was found between the mean values of CT number (Hounsfield unit), signal-to-noise ratio, contrast-to-noise ratio, and subjective assessment of image quality in the comparison of the control and experimental groups. CT dose index, volume, and dose length product were significantly lower in patients who underwent lowdose carotid CTA. There was no significant difference in the degree of carotid stenosis between color Doppler and CTA. Conclusion: The use of the low-dose protocol for carotid CTA allows the application of this method in risk groups, in which it was previously not possible to perform, with the same image quality in comparison with the standard protocol.

A new predictor of coronary artery disease in acute ischemic stroke or transient ischemic attack patients: pericarotid fat density.

The study aims to evaluate the incremental predictive value of pericarotid fat density (PFD) on head and neck computed tomography angiography (CTA) for the obstructive coronary artery disease (CAD) (≥ 50% stenosis) relative to a clinical risk model (Framingham risk score (FRS)) and the degree of carotid artery stenosis and plaque type in acute ischemic stroke (AIS) or transient ischemic attack (TIA) patients without a known history of CAD. In a cohort of 134 consecutive stable patients diagnosed with AIS or TIA undergoing head and neck CTA between January 2010 and December 2021, pericarotid adipose tissue density (PFD) was quantified using a dedicated software. We collected demographic and clinical data, assessed the risk of CAD using the FRS, and analyzed coronary and carotid artery CTA images. Univariate and multivariate logistic regression analyses were performed to assess associations between FRS, PFD, CTA variables, and obstructive CAD risk. Four prediction models were established to evaluate the incremental predictive value of PFD relative to FRS, stenosis degree, and plaque types. Receiver operating characteristic (ROC) curves were generated, and the areas under the curves (AUC) were compared. Increasing FRS, stenosis degree, and PFD values were positively correlated with obstructive CAD (all p < 0.05). In the predictive models for obstructive CAD, the model incorporating carotid stenosis exhibited superior predictive performance compared to FRS alone (p < 0.05). Moreover, the predictive model integrating PFD demonstrated enhanced performance and yielded the highest AUC of the receiver operator characteristic curve (AUC = 0.783), with sensitivity and specificity values of 86.89% and 65.75%, respectively. CTA-derived PFD measurements offer supplementary predictive value for obstructive CAD beyond FRS and stenosis, thereby facilitating improved risk stratification of TIA or stroke patients without a history of CAD history. CTA-derived PFD provides incremental predictive value for obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients without CAD history, beyond Framingham risk score and carotid artery stenosis degree, improving risk stratification. • Pericarotid fat density is associated with obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients. • Higher pericarotid fat density corresponds to an increased risk of obstructive coronary artery disease. • Estimation of pericarotid fat density using computed tomography angiography imparts additional predictive value for obstructive CAD in risk stratification of acute ischemic stroke or transient ischemic attack patients.

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.

CA-UNet Segmentation Makes a Good Ischemic Stroke Risk Prediction.

Stroke is still the World's second major factor of death, as well as the third major factor of death and disability. Ischemic stroke is a type of stroke, in which early detection and treatment are the keys to preventing ischemic strokes. However, due to the limitation of privacy protection and labeling difficulties, there are only a few studies on the intelligent automatic diagnosis of stroke or ischemic stroke, and the results are unsatisfactory. Therefore, we collect some data and propose a 3D carotid Computed Tomography Angiography (CTA) image segmentation model called CA-UNet for fully automated extraction of carotid arteries. We explore the number of down-sampling times applicable to carotid segmentation and design a multi-scale loss function to resolve the loss of detailed features during the process of down-sampling. Moreover, based on CA-Unet, we propose an ischemic stroke risk prediction model to predict the risk in patients using their 3D CTA images, electronic medical records, and medical history. We have validated the efficacy of our segmentation model and prediction model through comparison tests. Our method can provide reliable diagnoses and results that benefit patients and medical professionals.

Change in Peak Systolic Velocity Estimation in Internal Carotid Artery Following Contralateral Near Occlusive Carotid Endarterectomy

Carotid artery stenosis (CAS) is one of the main causes of stroke, as the internal carotid artery (ICA) is a major source of cerebral blood supply. A common surgical intervention for CAS is carotid endarterectomy (CEA), which carries a high risk of stroke and mortality. CEA is indicated for 50% to 99% stenosis in symptomatic patients and 60% to 99% stenosis in asymptomatic patients. Carotid duplex ultrasound is frequently used to estimate peak systolic velocity (PSV), end diastolic velocity (EDV), and ICA/common carotid artery (CCA) ratio to determine the extent of stenosis. This does not account for other factors that can artificially change PSV and EDV, such as a contralateral carotid artery near occlusion with >90% stenosis. Although >70% contralateral stenosis has been previously studied, limited research exists on the impact of ICA near occlusions. We hypothesize that the degree of stenosis in an ipsilateral patent vessel can be more accurately estimated by examining the change in PSV pre- vs post-CEA of the contralateral ICA near occlusion. A retrospective study was conducted on 239 patients, at least 18 years of age, who underwent standard, routine carotid duplex ultrasound at a single institution. Patients who qualified for the study had bilateral carotid stenosis with ICA near occlusive disease on at least one side and underwent CEA. Near occlusion was determined by either a carotid duplex ultrasound >70% with one of the following criteria: PSV >400, EDV >140, or ratio of ICA/CCA >6, or a carotid computed tomography angiography showing near occlusion interpreted by a physician. Preoperative duplex velocities contralateral to the CEA were recorded and compared postoperatively. Interestingly, in the presence of contralateral >50% ICA stenosis, the PSV, EDV, and ICA/CCA ratio in the unoperated artery increased significantly following contralateral CEA (P < .001). In greater than 70% contralateral ICA occlusion, PSV, EDV, and ICA/CCA ratio increased to a greater extent compared with >50% contralateral ICA stenosis (P < .001). In detecting ≥70% stenosis of the patent vessel pre-CEA, PSV ≥250 cm/s had 87.2% sensitivity. In predicting ≥70% stenosis of the patent vessel pre-CEA, PSV >300 cm/s had 96.0% sensitivity. The present study deviates from the current theoretical model and shows that ultrasound PSV, EDV, ICA/CCA ratios can be significantly elevated in the patent vessel pre-CEA and post-CEA of the contralateral ICA near occlusion. This study provides novel insight into customized duplex ultrasound criteria for estimation of stenosis and to avoid unnecessary high-risk surgery.

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.

Carotid Plaque Diagnosis With 3-Dimensional Computed Tomography Angiography: A Comparison With Magnetic Resonance Imaging-Based Plaque Diagnosis.

Although a qualitative diagnosis of plaque causing carotid stenosis has been attempted with carotid computed tomography angiography (CaCTA), no clear findings have been reported. We examined the correlation between the plaque CT values and plaque images obtained by magnetic resonance imaging to derive a qualitative diagnosis of the plaque using CaCTA. Preoperative CaCTA images acquired from patients stented for carotid stenosis were retrospectively analyzed with respect to magnetization-prepared rapid acquisition with gradient echo and time-of-flight magnetic resonance angiography data. Carotid plaques in the stenosed region were quantified in terms of CT density and the plaque/muscle ratio (magnetization-prepared rapid acquisition with gradient echo), and correlations between these 2 features were determined. Plaques were classified as stable or unstable based on the plaque/muscle ratio, with the smallest plaque/muscle ratio observed among plaques positive for intraplaque hemorrhage set as the cutoff value (1.76). A total of 165 patients (179 plaques) were included. Perioperative complications included minor stroke (n = 3), major stroke (n = 1, fatal), and hyperperfusion (n = 2). The correlation between CT density and the plaque/muscle ratio was nonlinear ( P = 0.0139) and negative ( P < 0.0001). The cutoff point (1.76) corresponded to a CT density of 83 HU, supporting this value as a standard reference for plaque stability. Computed tomography density exhibits a nonlinear ( P = 0.0139) and highly negative correlation ( P < 0.0001) with the plaque/muscle ratio. Our results demonstrate that plaque characteristics can be meaningfully diagnosed based on CaCTA image data.

Carotid Plaque Vulnerability Diagnosis by CTA versus MRA: A Systematic Review

Stenosis grade of the carotid arteries has been the primary indicator for risk stratification and surgical treatment of carotid artery disease. Certain characteristics of the carotid plaque render it vulnerable and have been associated with increased plaque rupture rates. Computed tomography angiography (CTA) and magnetic resonance angiography (MRA) have been shown to detect these characteristics to a different degree. The aim of the current study was to report on the detection of vulnerable carotid plaque characteristics by CTA and MRA and their possible association. A systematic review of the medical literature was executed, utilizing PubMed, SCOPUS and CENTRAL databases, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines. The study protocol has been registered to PROSPERO (CRD42022381801). Comparative studies reporting on both CTA and MRA carotid artery studies were included in the analysis. The QUADAS tools were used for risk of bias diagnostic imaging studies. Outcomes included carotid plaque vulnerability characteristics described in CTA and MRA and their association. Five studies, incorporating 377 patients and 695 carotid plaques, were included. Four studies reported on symptomatic status (326 patients, 92.9%). MRA characteristics included intraplaque hemorrhage, plaque ulceration, type VI AHA plaque hallmarks and intra-plaque high-intensity signal. Intraplaque hemorrhage detected in MRA was the most described characteristic and was associated with increased plaque density, increased lumen stenosis, plaque ulceration and increased soft-plaque and hard-plaque thickness. Certain characteristics of vulnerable carotid plaques can be detected in carotid artery CTA imaging studies. Nevertheless, MRA continues to provide more detailed and thorough imaging. Both imaging modalities can be applied for comprehensive carotid artery work-up, each one complementing the other.

Predicting transient ischemic attack risk in patients with mild carotid stenosis using machine learning and CT radiomics.

This study aims to establish a radiomics-based machine learning model that predicts the risk of transient ischemic attack in patients with mild carotid stenosis (30-50% North American Symptomatic Carotid Endarterectomy Trial) using extracted computed tomography radiomics features and clinical information. A total of 179 patients underwent carotid computed tomography angiography (CTA), and 219 carotid arteries with a plaque at the carotid bifurcation or proximal to the internal carotid artery were selected. The patients were divided into two groups; patients with symptoms of transient ischemic attack after CTA and patients without symptoms of transient ischemic attack after CTA. Then we performed random sampling methods stratified by the predictive outcome to obtain the training set (N = 165) and testing set (N = 66). 3D Slicer was employed to select the site of plaque on the computed tomography image as the volume of interest. An open-source package PyRadiomics in Python was used to extract radiomics features from the volume of interests. The random forest and logistic regression models were used to screen feature variables, and five classification algorithms were used, including random forest, eXtreme Gradient Boosting, logistic regression, support vector machine, and k-nearest neighbors. Data on radiomic feature information, clinical information, and the combination of these pieces of information were used to generate the model that predicts the risk of transient ischemic attack in patients with mild carotid artery stenosis (30-50% North American Symptomatic Carotid Endarterectomy Trial). The random forest model that was built based on the radiomics and clinical feature information had the highest accuracy (area under curve = 0.879; 95% confidence interval, 0.787-0.979). The combined model outperformed the clinical model, whereas the combined model showed no significant difference from the radiomics model. The random forest model constructed with both radiomics and clinical information can accurately predict and improve discriminative power of computed tomography angiography in identifying ischemic symptoms in patients with carotid atherosclerosis. This model can aid in guiding the follow-up treatment of patients at high risk.

Reduction in Radiation Exposure of CT Perfusion by Optimized Imaging Timing Using Temporal Information of the Preceding CT Angiography of the Carotid Artery in the Stroke Protocol.

(1) Background: CT perfusion (CTP) is a fast, robust and widely available but dose-exposing imaging technique for infarct core and penumbra detection. Carotid CT angiography (CTA) can precede CTP in the stroke protocol. Temporal information of the bolus tracking series of CTA could allow for better timing and a decreased number of scans in CTP, resulting in less radiation exposure, if the shortening of CTP does not alter the calculated infarct core and penumbra or the resulting perfusion maps, which are essential for further treatment decisions. (2) Methods: 66 consecutive patients with ischemic stroke proven by follow-up imaging or endovascular intervention were included in this retrospective study approved by the local ethics committee. In each case, six simulated, stepwise shortened CTP examinations were compared with the original data regarding the perfusion maps, infarct core, penumbra and endovascular treatment decision. (3) Results: In simulated CTPs with 26, 28 and 30 scans, the infarct core, penumbra and PRR values were equivalent, and the resulting clinical decision was identical to the original CTP. (4) Conclusions: The temporal information of the bolus tracking series of the carotid CTA can allow for better timing and a lower radiation exposure by eliminating unnecessary scans in CTP.

Potential role of bolus-tracking data of carotid CT angiography for atrial fibrillation prediction.

Atrial fibrillation (AF), a significant cause of ischemic stroke, often goes undetected because of its asymptomatic nature. This study investigated whether the total bolus-tracking time (TTT) and average slope (AS) of a bolus-tracking graph could be used to predict AF. This single-center, retrospective study included patients who underwent carotid CTA and a 24-h Holter test. TTT and the average degree of enhancement during bolus-tracking, derived from carotid CTA, were defined as variables of interest. All patients underwent transthoracic echocardiography. Left ventricular diastolic dysfunction and elevated left atrial pressure (LAP) were identified according to the guidelines of the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging. The final cohort comprised 716 patients, 80 of whom presented with AF. The TTT of the AF group was significantly longer (23.8 ± 5.2 s) than that of the non-AF group (18.7 ± 2.8 s); p < 0.001. The AS of the bolus-tracking graph of the AF group was 0.80 ± 0.24, which was significantly lower than that of the non-AF group 1.38 ± 0.21 (p < 0.001). TTT was associated with a significantly higher risk of AF (odds ratio [OR]: 1.36; p < 0.001) and elevated LAP (OR: 1.46; p < 0.001). In contrast, the AS of the bolus-tracking graph was not significantly associated with either AF or an elevated LAP. TTT derived from bolus-tracking carotid CTA is an effective adjuvant tool for detecting AF related to left ventricular diastolic dysfunction and elevated LAP, confirmed using echocardiography. • Atrial fibrillation is not only a significant cause of ischemic stroke but is also often masked because of its atypical and asymptomatic features. • The total tracking time, derived from bolus tracking of carotid computed tomography angiography, may be an effective adjuvant tool for detecting undiagnosed atrial fibrillation and elevated left atrial pressure in patients.

Relationship between annular calcification of plaques in the carotid sinus and perioperative hemodynamic disorder in carotid angioplasty and stenting

Objective: To investigate the correlation between annular plaque calcification in the carotid sinus and perioperative hemodynamic disorder (HD) in carotid angioplasty and stenting (CAS). MethodsThe clinical data of 49 patients undergoing CAS due to narrowing of the carotid sinus were retrospectively analyzed. All patients had preoperative carotid computed tomography angiography (CTA) and were divided into HD and non-HD groups based on the occurrence of HD in the perioperative period of CAS. HD was defined as persistent bradycardia (heart rate < 60 beats per min) or persistent hypotension (systolic blood pressure < 90 mmHg) in the perioperative period and lasting for at least 1 h. The baseline data, including the degree of carotid artery stenosis, plaque length, plaque thickness, calcified plaque morphologies (i.e., plaque circumferential angle: < 90° defined as dotted calcification; 90°–180° defined as arcuate calcification; > 180° defined as annular calcification), contralateral carotid artery conditions, balloon diameter, and stent types, were compared between the two groups. Binary logistic regression was used to analyze the risk factors for the occurrence of HD. ResultsAmong the 49 patients undergoing CAS, 14 (28.57%) developed perioperative HD, and 35 did not. Annular calcification was more common in the patients in the HD group than in the non-HD group. No significant differences in the probabilities of dotted and arcuate calcifications were found between the two groups (p > 0.05). The duration of continuous dopamine consumption in the HD group was 9–71 h. The average hospital stay of the HD group (10.14 ± 4.17 days) was significantly longer than that of the non-HD group (6.57 ± 1.9 days; p < 0.001). Patients in the HD group had significantly more pronounced lumen stenosis (p = 0.033) and longer plaque length (p = 0.034) than those in the non-HD group. After adjusting for age and sex, multivariate regression analysis showed that the presence of annular plaque calcification was an independent predictor of HD (odds ratio: 7.68, 95% confidence interval: 1.46–40.37, p = 0.016). ConclusionsThe occurrence of annular plaque calcification in the carotid sinus was an independent risk factor for perioperative HD in CAS. Preoperative carotid CTA assists with the early identification of high-risk patients who may develop HD.

Prediction of Carotid In-Stent Restenosis by Computed Tomography Angiography Carotid Plaque-Based Radiomics

In-stent restenosis (ISR) after carotid artery stenting (CAS) critically influences long-term CAS benefits and safety. The study was aimed at screening preoperative ISR-predictive features and developing predictive models. Thus, we retrospectively analyzed clinical and imaging data of 221 patients who underwent pre-CAS carotid computed tomography angiography (CTA) and whose digital subtraction angiography data for verifying ISR presence were available. Carotid plaque characteristics determined using CTA were used to build a traditional model. Backward elimination (likelihood ratio) was used for the radiomics model. Furthermore, a combined model was built using the traditional and radiomics features. Five-fold cross-validation was used to evaluate the accuracy of the trained classifier and stability of the selected features. Follow-up angiography showed ISR in 30 patients. Carotid plaque length and thickness were independently associated with ISR (multivariate analysis); regarding the conventional model, the area under the curve (AUC) was 0.84 and 0.82 in the training and validation cohorts, respectively. The corresponding AUC values for the radiomics-based model were 0.87 and 0.82, and those for the optimal combined model were 0.88 and 0.83. Plaque length and thickness could independently predict post-CAS ISR, and the combination of radiomics and plaque features afforded the best predictive performance.

Radiomics versus Conventional Assessment to Identify Symptomatic Participants at Carotid Computed Tomography Angiography

Introduction: Carotid computed tomography angiography (CTA) is routinely used for evaluating the atherosclerotic process. Radiomics allows the extraction of imaging markers of lesion heterogeneity and spatial complexity. These quantitative features can be used as the input for machine learning (ML). Therefore, in this study, we aimed to evaluate the diagnostic performance of radiomics-based ML assessment of carotid CTA data to identify symptomatic patients with carotid artery atherosclerosis. Methods: In this retrospective study, participants with carotid artery atherosclerosis who underwent carotid CTA and brain magnetic resonance imaging from May 2010 to December 2017 were studied. The participants were grouped into symptomatic and asymptomatic groups according to their recent symptoms (determination of ipsilateral ischemic stroke). Eight conventional plaque features and 2,107 radiomics parameters were extracted from carotid CTA images. A radiomics-based ML model was fitted on the training set, and the radiomics-based ML model and conventional assessment were compared using the area under the curve (AUC) to identify symptomatic participants. Results: After excluding participants with other stroke sources, 120 patients with 148 carotid arteries were analyzed. Of these 148 carotid arteries, 34 (22.97%) were classified into the symptomatic group. Plaque ulceration (odds ratio [OR] = 0.257; 95% confidence interval [CI], 0.094–0.698) and plaque enhancement (OR = 0.305; 95% CI, 0.094–0.988) were associated with the symptomatic status. Twenty radiomics parameters were chosen to be inputs in the radiomics-based ML model. In the identification of symptomatic participants, the discriminatory value of the radiomics-based ML model was significantly higher than that of the conventional assessment (AUC = 0.858 vs. AUC = 0.706, p = 0.021). Conclusion: Radiomics-based ML analysis improves the discriminatory power of carotid CTA in the identification of recent ischemic symptoms in patients with carotid artery atherosclerosis.

Comparative study of the image quality of twin beam dual energy and single energy carotid CT angiography

PurposeThe aim of this study was to compare the image quality of low virtual monochromatic image (VMI) from the twin-beam dual energy (TBDE) mode to that from the single energy (SE) mode using both standard and low tube voltage acquisition in carotid computed tomography angiography (CTA). MethodsIn this prospective study, 221 patients were imaged using TBDE mode with 120 kV or SE mode with 80/90/120 kV, patient numbers in all groups are equal(n = 55) except in the group using 80 kV SE mode(n = 56). VMIs ranging from 40 to 90 keV with a step of 1 keV were reconstructed from TBDE mode. In objective image quality assessment, regions of interest (ROIs) were placed in both carotid artery lumens and in both sternocleidomastoid muscles to calculate and compare the contrast-to-noise ratio (CNR) and the dose-normalized CNR (CNRD) among groups. In subjective assessment, a total of 13 arterial segments were assessed using a four-point Likert scale by two observers. Cohen's kappa test was used to quantify the level of agreement between the two observers. ResultsFor ROI1 at the level of the carotid bifurcation, VMIs showed a higher CNR than the 120 kV SE group (p = 0.028)/ 90 kV SE group (p = 0.037) when their energy level were lower than 79 keV (56.92 ± 16.01)/56 keV (90.08 ± 22.14) respectively. The 90 kV SE (80.68 ± 24.47) showed the best CNR in all the SE groups. For CNRD, the 120/90/80 kV SE group was equivalent to 83/63/67 keV VMIs respectively. For ROI2 at the level of the origin of the common carotid artery, VMIs also showed a higher CNR than the 120 kV SE group (p = 0.015)/90 kV SE group (p = 0.034) when their energy level were lower than 83 keV (46.31 ± 14.47)/60 keV (72.23 ± 16.96) respectively. The 90 kV SE (64.98 ± 18.51) showed the best CNR in all the SE groups. For CNRD, the 120/90/80 kV SE group was equivalent to 88/72/75 keV VMIs respectively. The highest subjective rating score was 50 keV TBDE(3.70 ± 0.53). Cohen's Kappa values(0.79–0.85) suggest a substantial level of agreement between the two observers. ConclusionsThe novel TBDE technique with low keV VMI reconstruction provides better image quality of carotid CTA than the low tube voltage scan in the SE mode. VMIs with a keV level below 56 keV have a higher CNR than those from SE scans with 80/90/120 kV. Subjectively, the optimal keV energy level in TBDE for carotid CT angiography is 50 keV.

Reconsidering the Relationship Between Hand Preference and Cerebral Vascular Dominance: A Computed Tomography (CT) Angiography Study.

To date, it has been suggested that there may be many genetic, environmental, and vascular factors that affect hand preference. In previous studies evaluating the relationship between cerebral dominance and hand preference, carotid and vertebral artery (VA) Doppler ultrasonography (USG) was generally preferred; and these studies only measured VA diameters. Unlike other studies, we aimed to reevaluate the relationship between hand preference and cerebral vascular dominance by measuring VA and internal carotid artery (ICA) diameters. In addition, we used carotid and VA computed tomography (CT) angiography instead of Doppler USG. A total of 345 participants were included in the study. The results of carotid and VA CT angiography taken during hospitalization were retrospectively evaluated by two radiologists, and the Edinburgh Hand Preference Questionnaire was applied to these patients. In right-handed patients, the diameter of the left VA was significantly larger than the diameter of the right VA (p = 0.005). In left-handed patients, the diameter of the left ICA was larger than the diameter of the right ICA, but the difference was not statistically significant (p = 0.055). There was no significant difference between the diameter of the right and left ICA in right-handed patients (p = 0.771). In our study, we found a correlation between the dominant hemisphere VA diameter and hand preference. Using CT angiography, we were able to eliminate many challenges of ultrasonography that make radiological evaluation difficult, such as differences of opinion between radiologists, and technical and anatomical reasons.

ESTIMATION OF PATIENT RADIATION DOSES FROM MULTI-DETECTOR COMPUTED TOMOGRAPHY ANGIOGRAPHY PROCEDURES IN TANZANIA.

The aim of the present study was to estimate the volume CT dose index (CTDIvol), dose length product (DLP) and effective dose (ED) to patients from five multi-detector computed tomography angiography (MDCTA) procedures: brain, carotid, coronary, entire aorta and lower limb from four medical institutions in Tanzania; to compare these doses to those reported in the literature, and to compare the data obtained with ICRP 103 and Monte Carlo software. The radiation doses for 217 patients were estimated using patient demographics, patient-related exposure parameters, the geometry of examination and CT-Expo V 2.4 Monte Carlo-based software. The median values of the CTDIvol, DLP and ED for MDCTA procedures of the brain and carotids were 36.8mGy, 1481.0mGy∙cm and 5.2mSv, and 15.9mGy, 1224.0mGy∙cm and 7.8mSv, respectively; while for the coronary, entire aortic, and lower limbs were 49.4mGy, 1493.0mGy∙cm and 30.6mSv; 16.2mGy, 2287.0mGy∙cm and 41.1mSv; and 6.4mGy, 1406.0mGy∙cm and 10.5mSv, respectively. The ratio of the maximum to minimum ED values to individual patients across the four medical centers were 41.4, 11.1, 4.6, 9.5 and 37.4, respectively, for the brain, carotid, coronary, entire aortic and lower limb CT angiography procedures. The mean values of CTDIvol, DLP and ED in the present study were typically higher than the values reported from Kenya, Korea and Saudi Arabia. The 75th percentile values of the DLP were above the preliminary diagnostic references levels proposed by Kenya, Switzerland and Korea. The observed wide range of examination scanning protocols and patient doses for similar MDCTA procedures within and across hospitals; and the observed relatively high patient doses compared to those reported in the literature, call for the need to standardize scanning protocols and optimise patient dose from MDCTA procedures.

875 Using Stress Testing to Identify Vulnerabilities in Artificial Intelligence Models for the Identification of Culprit Carotid Lesions in Cerebrovascular Events

Abstract Introduction Carotid atherosclerosis is a major risk factor for ischaemic stroke, a leading cause of death. Carotid CT angiography (CTA) is commonly performed following a stroke or transient ischaemic attack (TIA) to help guide patient management in secondary prevention of stroke. Deep learning algorithms can help extract greater information from scans. Method The dataset comprised CTA scans from 40 culprit and 40 non-culprit carotid arteries of patients with recent stroke/TIA, and 40 carotid arteries of asymptomatic patients without previous stroke/TIA. A 3D convolutional neural network was trained to classify carotid artery type. Each input comprised 14 axial CTA carotid patches (centred around the carotid artery) concatenated together to form a 3D volume (capturing ∼3cm of artery). 75% of the dataset was used for training and 25% for internal validation. Following training, computer vision operations were applied to input images to assess their impact on the model’s classification decisions. Results The model achieved 100% accuracy on the training set and 67% on the internal validation set. However, after subjecting input images to image operations, vulnerabilities in the deep learning model were revealed, even when using input images from the training set. For example, using a Gaussian blur filter with sigma 1.0 was sufficient to change classification decisions, as was horizontally flipping the image. Conclusions Deep learning has exceptional capabilities for learning, however the risk with such high-capacity models is failure to learn relevant features from the data. Stress testing provides a viable method to further evaluate deep learning models before clinical deployment.