Grading of carotid artery stenosis with computed tomography angiography: whether to use the narrowest diameter or the cross-sectional area

Systematic review and meta-analysis of the diagnostic value of computed tomography angiography for severe internal carotid artery stenosis

BACKGROUND

Due to the increasing incidence of ischaemic cerebrovascular diseases, the accurate assessment of internal carotid artery (ICA) stenosis is crucial for the development of treatment plans. This systematic review and meta-analysis aimed to evaluate the diagnostic value of computed tomography angiography (CTA) for severe ICAstenosis, thereby providing support for clinical decision-making and promoting diagnostic updates.

METHODS

The PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database for Chinese Technical Periodicals (VIP), and Chinese Biomedical Literature (CBM) electronic databases were searched from inception to March 21, 2024, to identify publicly available research literature on the use of CTA to diagnose severe ICA stenosis. Literature screening, data extraction, and quality assessment were conducted based on the inclusion and exclusion criteria as well as the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) standards. Data analysis was performed using Stata 17.0 and Meta-Disc 1.4 software. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of the included studies were calculated using Stata 17.0 software, and forest plots and summary receiver operating characteristic (SROC) curves were generated. The area under the curve (AUC) was calculated, and funnel plots were constructed to assess publication bias.

RESULTS

A total of 16 studies with 2368 vascular segments were included. The meta-analysis revealed that the combined sensitivity and specificity of CTA for severe ICA stenosis were 0.93 (95% CI: 0.88 ~ 0.96) and 0.99 (95% CI: 0.96 ~ 1.00), respectively. The combined positive likelihood ratio and negative likelihood ratio were 92.0 (95% CI: 24.2 ~ 349.6) and 0.07 (95% CI: 0.04 ~ 0.13), respectively. The diagnostic odds ratio was 1302 (95% CI: 257 ~ 6606), and the AUC of the SROC curve was 0.98. The Deeks funnel plot suggested no publication bias among the included studies.

CONCLUSION

CTA demonstrated high sensitivity and specificity for diagnosing severe ICA stenosis. Therefore, this study provided important evidence for the accurate diagnosis and treatment of severe ICA stenosis. However, there was considerable heterogeneity among the included studies, thus indicating the need for additional high-quality prospective studies to confirm the clinical applicability of CTA.

30-Day Risk Score for Mortality and Stroke in Patients with Carotid Artery Stenosis Using Artificial Intelligence Based Carotid Plaque Morphology

OBJECTIVES

The gold standard for determining carotid artery stenosis intervention is based on a combination of percent stenosis and symptomatic status. Few studies have assessed plaque morphology as an additive tool for stroke prediction. Our goal was to create a predictive model and risk score for 30-day stroke and death inclusive of plaque morphology.

METHODS

Patients with a CT angiography head/neck between 2010-2021 at a single institution and a diagnosis of carotid artery stenosis were included in our analysis. Each CT was used to create a 3D image of carotid plaque based off image recognition software. A stepwise backward regression was used to select variables for inclusion in our prediction models. Model discrimination was assessed with receiver operating characteristic curves (AUC). Additionally, calibration was performed and the model with the least Akaike Information Criterion (AIC) was selected. The risk score was modeled from the Framingham Study. Primary outcome was mortality/stroke.

RESULTS

We created three models to predict mortality/stroke from 366 patients: model A using only clinical variables, model B using only plaque morphology and model C using both clinical and plaque morphology variables. Model A used age, sex, PAD, hyperlipidemia, BMI, COPD, and history of TIA/stroke and had an AUC of 0.737 and AIC of 285.4. Model B used perivascular adipose tissue volume, lumen area, calcified volume, and target lesion length and had an AUC of 0.644 and AIC of 304.8. Finally, model C combined both clinical and software variables of age, sex, matrix volume, history of TIA/stroke, BMI, perivascular adipose tissue, lipid rich necrotic core, COPD and hyperlipidemia and had an AUC of 0.759 and an AIC of 277.6. Model C was the most predictive because it had the highest AUC and lowest AIC.

CONCLUSION

Our study demonstrates that combining both clinical factors and plaque morphology creates the best predication of a patient's risk for all-cause mortality or stroke from carotid artery stenosis. Additionally, we found that for patients with even 3 points in our risk score model have a 20% chance of stroke/death. Further prospective studies are needed to validate our findings.

Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario

Carotid artery stenosis is a major cause of morbidity and mortality. The journey to understanding carotid disease has developed over time and radiology has a pivotal role in diagnosis, risk stratification and therapeutic management. This paper reviews the history of diagnostic imaging in carotid disease, its evolution towards its current applications in the clinical and research fields, and the potential of new technologies to aid clinicians in identifying the disease and tailoring medical and surgical treatment.

Peak systolic velocity ratio for evaluation of internal carotid artery stenosis correlated with plaque morphology: substudy results of the ANTIQUE study

Background

Accurate assessment of carotid stenosis severity is important for proper patient management. The present study aimed to compare the evaluation of carotid stenosis severity using four duplex sonography (DUS) measurements, including peak systolic velocity (PSV), PSV ratio in stenosis and distal to stenosis (PSVICA/ICA ratio), end-diastolic velocity (EDV), and B-mode, with computed tomography angiography (CTA), and to evaluate the impact of plaque morphology on correlation between DUS and CTA.

Methods

Consecutive patients with carotid stenosis of ≥40% examined using DUS and CTA were included. Plaque morphology was also determined using magnetic resonance imaging. Spearman's correlation and Kendall's rank correlation were used to evaluate the results.

Results

A total of 143 cases of internal carotid artery stenosis of ≥40% based on DUS were analyzed. The PSVICA/ICA ratio showed the highest correlation [Spearman's correlation r = 0.576) with CTA, followed by PSV (r = 0.526), B-mode measurement (r = 0.482), and EDV (r = 0.441; p < 0.001 in all cases]. The worst correlation was found for PSV when the plaque was calcified (r = 0.238), whereas EDV showed a higher correlation (r = 0.523). Correlations of B-mode measurement were superior for plaques with smooth surface (r = 0.677), while the PSVICA/ICA ratio showed the highest correlation in stenoses with irregular (r = 0.373) or ulcerated (r = 0.382) surfaces, as well as lipid (r = 0.406), fibrous (r = 0.461), and mixed (r = 0.403; p < 0.01 in all cases) plaques. Nevertheless, differences between the mentioned correlations were not statistically significant (p > 0.05 in all cases).

Conclusion

PSV, PSVICA/ICA ratio, EDV, and B-mode measurements showed comparable correlations with CTA in evaluation of carotid artery stenosis based on their correlation with CTA results. Heavy calcifications and plaque surface irregularity or ulceration negatively influenced the measurement accuracy.

Transcranial Doppler versus CT angiography: a comparative analysis for the diagnosis of ischaemic cerebrovascular disease

AIMS

To compare the sensitivity, specificity, accuracy, and clinical usefulness of transcranial Doppler (TCD) ultrasound against computed tomography angiography (CTA) for the diagnosis of ischaemic cerebrovascular disease.

METHODS

A total of 1,183 sites (vascular segments) of 169 patients who had been diagnosed with cerebrovascular disease using digital subtraction angiography (DSA) were evaluated by CTA and TCD for the diagnosis of the arterial lesions.

RESULTS

Lesions were identified in 509 sites and 674 sites did not have lesions according to the DSA examination. Each individual site had higher sensitivity, specificity, and accuracy for TCD than those for CTA, respectively. For all sites, TCD had higher true-positive (p=0.0029) and -negative (p=0.0151) values and fewer false-positive and -negative (p<0.0001 for both) values than those of CTA. The sensitivity, specificity, and accuracy of CTA for all sites to detect lesions were 77%, 88%, and 84%, respectively. The same parameters for TCD were 94%, 97%, and 95%, respectively. The beneficial scores for CTA and TCD to detect lesions were 0-0.795 diagnostic confidence and 0-0.91 diagnostic confidence, respectively. Beneficial scores >0.795 and >0.91 indicated a risk of underdiagnosis of lesions at CTA and TCD, respectively.

CONCLUSIONS

Compared with DSA (reference standard) and CTA, the study underscores the use of TCD in cerebrovascular pathology.

3D Ultrasound Reconstructions of the Carotid Artery and Thyroid Gland Using Artificial-Intelligence-Based Automatic Segmentation-Qualitative and Quantitative Evaluation of the Segmentation Results via Comparison with CT Angiography

The aim of this study was to evaluate the feasibility of a noninvasive and low-operator-dependent imaging method for carotid-artery-stenosis diagnosis. A previously developed prototype for 3D ultrasound scans based on a standard ultrasound machine and a pose reading sensor was used for this study. Working in a 3D space and processing data using automatic segmentation lowers operator dependency. Additionally, ultrasound imaging is a noninvasive diagnosis method. Artificial intelligence (AI)-based automatic segmentation of the acquired data was performed for the reconstruction and visualization of the scanned area: the carotid artery wall, the carotid artery circulated lumen, soft plaque, and calcified plaque. A qualitative evaluation was conducted via comparing the US reconstruction results with the CT angiographies of healthy and carotid-artery-disease patients. The overall scores for the automated segmentation using the MultiResUNet model for all segmented classes in our study were 0.80 for the IoU and 0.94 for the Dice. The present study demonstrated the potential of the MultiResUNet-based model for 2D-ultrasound-image automated segmentation for atherosclerosis diagnosis purposes. Using 3D ultrasound reconstructions may help operators achieve better spatial orientation and evaluation of segmentation results.

Challenges and Pitfalls in CT-Angiography Evaluation of Carotid Bulb Stenosis: Is It Time for a Reappraisal?

We aimed to perform an anatomical evaluation of the carotid bulb using CT-angiography, implement a new reliable index for carotid stenosis quantification and to assess the accuracy of relationship between NASCET and ECST methods in a large adult population. The cross-sectional areas of the healthy carotid at five levels were measured by two experienced radiologists. A regression analysis was performed in order to quantify the relationship between the areas of the carotid bulb at different carotid bulbar level. A new index (Regression indeX, RegX) for carotid stenosis quantification was proposed. Five different stenoses with different grade in three bulbar locations were simulated for all patients for a total of 1365 stenoses and were used for a direct comparison of the RegX, NASCET, and ECST methods. The results of this study demonstrated that the RegX index provided a consistent and accurate measure of carotid stenosis through the application of the ECST method, avoiding the limitations of NASCET method. Furthermore, our results strongly depart from the consolidated relationships between NASCET and ECST values used in clinical practice and reported in extensive medical literature. In particular, we highlighted that a major misdiagnosis in patient selection for CEA could be introduced because of the large underestimation of real stenosis degree provided by the NASCET method. A reappraisal of carotid stenosis patients' work-up is evoked by the effectiveness of state-of-the-art noninvasive contemporary carotid imaging.

Duplex ultrasound for diagnosing symptomatic carotid stenosis in the extracranial segments

BACKGROUND

Carotid artery stenosis is an important cause of stroke and transient ischemic attack. Correctly and rapidly identifying patients with symptomatic carotid artery stenosis is essential for adequate treatment with early cerebral revascularization. Doubts about the diagnostic value regarding the accuracy of duplex ultrasound (DUS) and the possibility of using DUS as the single diagnostic test before carotid revascularization are still debated.

OBJECTIVES

To estimate the accuracy of DUS in individuals with symptomatic carotid stenosis verified by either digital subtraction angiography (DSA), computed tomography angiography (CTA), or magnetic resonance angiography (MRA).

SEARCH METHODS

We searched CRDTAS, CENTRAL, MEDLINE (Ovid), Embase (Ovid), ISI Web of Science, HTA, DARE, and LILACS up to 15 February 2021. We handsearched the reference lists of all included studies and other relevant publications and contacted experts in the field to identify additional studies or unpublished data.

SELECTION CRITERIA

We included studies assessing DUS accuracy against an acceptable reference standard (DSA, MRA, or CTA) in symptomatic patients. We considered the classification of carotid stenosis with DUS defined with validated duplex velocity criteria, and the NASCET criteria for carotid stenosis measures on DSA, MRA, and CTA. We excluded studies that included < 70% of symptomatic patients; the time between the index test and the reference standard was longer than four weeks or not described, or that presented no objective criteria to estimate carotid stenosis.

DATA COLLECTION AND ANALYSIS

The review authors independently screened articles, extracted data, and assessed the risk of bias and applicability concerns using the QUADAS-2 domain list. We extracted data with an effort to complete a 2 × 2 table (true positives, true negatives, false positives, and false negatives) for each of the different categories of carotid stenosis and reference standards. We produced forest plots and summary receiver operating characteristic (ROC) plots to summarize the data. Where meta-analysis was possible, we used a bivariate meta-analysis model.

MAIN RESULTS

We identified 25,087 unique studies, of which 22 were deemed eligible for inclusion (4957 carotid arteries). The risk of bias varied considerably across the studies, and studies were generally of moderate to low quality. We narratively described the results without meta-analysis in seven studies in which the criteria used to determine stenosis were too different from the duplex velocity criteria proposed in our protocol or studies that provided insufficient data to complete a 2 × 2 table for at least in one category of stenosis. Nine studies (2770 carotid arteries) presented DUS versus DSA results for 70% to 99% carotid artery stenosis, and two (685 carotid arteries) presented results from DUS versus CTA in this category. Seven studies presented results for occlusion with DSA as the reference standard and three with CTA as the reference standard. Five studies compared DUS versus DSA for 50% to 99% carotid artery stenosis. Only one study presented results from 50% to 69% carotid artery stenosis. For DUS versus DSA, for < 50% carotid artery stenosis, the summary sensitivity was 0.63 (95% confidence interval [CI] 0.48 to 0.76) and the summary specificity was 0.99 (95% CI 0.96 to 0.99); for the 50% to 69% range, only one study was included and meta-analysis not performed; for the 50% to 99% range, the summary sensitivity was 0.97 (95% CI 0.95 to 0.98) and the summary specificity was 0.70 (95% CI 0.67 to 0.73); for the 70% to 99% range, the summary sensitivity was 0.85 (95% CI 0.77 to 0.91) and the summary specificity was 0.98 (95% CI 0.74 to 0.90); for occlusion, the summary sensitivity was 0.91 (95% CI 0.81 to 0.97) and the summary specificity was 0.95 (95% CI 0.76 to 0.99). For sensitivity analyses, excluding studies in which participants were selected based on the presence of occlusion on DUS had an impact on specificity: 0.98 (95% CI 0.97 to 0.99). For DUS versus CTA, we found two studies in the range of 70% to 99%; the sensitivity varied from 0.57 to 0.94 and the specificity varied from 0.87 to 0.98. For occlusion, the summary sensitivity was 0.95 (95% CI 0.80 to 0.99) and the summary specificity was 0.91 (95% CI 0.09 to 0.99). For DUS versus MRA, there was one study with results for 50% to 99% carotid artery stenosis, with a sensitivity of 0.88 (95% CI 0.70 to 0.98) and specificity of 0.60 (95% CI 0.15 to 0.95); in the 70% to 99% range, two studies were included, with sensitivity that varied from 0.54 to 0.99 and specificity that varied from 0.78 to 0.89. We could perform only a few of the proposed sensitivity analyses because of the small number of studies included.

AUTHORS' CONCLUSIONS

This review provides evidence that the diagnostic accuracy of DUS is high, especially at discriminating between the presence or absence of significant carotid artery stenosis (< 50% or 50% to 99%). This evidence, plus its less invasive nature, supports the early use of DUS for the detection of carotid artery stenosis. The accuracy for 70% to 99% carotid artery stenosis and occlusion is high. Clinicians should exercise caution when using DUS as the single preoperative diagnostic method, and the limitations should be considered. There was little evidence of the accuracy of DUS when compared with CTA or MRA. The results of this review should be interpreted with caution because they are based on studies of low methodological quality, mainly due to the patient selection method. Methodological problems in participant inclusion criteria from the studies discussed above apparently influenced an overestimated estimate of prevalence values. Most of the studies included failed to precisely describe inclusion criteria and previous testing. Future diagnostic accuracy studies should include direct comparisons of the various modalities of diagnostic tests (mainly DUS, CTA, and MRA) for carotid artery stenosis since DSA is no longer considered to be the best method for diagnosing carotid stenosis and less invasive tests are now used as reference standards in clinical practice. Also, for future studies, the participant inclusion criteria require careful attention.

Applicability of Transnasal Echography for Identification of Internal Carotid Artery

OBJECTIVE

To study the applicability of transnasal echography for the internal carotid artery (ICA) imaging during endoscopic procedures, primarily nasopharyngectomy.

STUDY DESIGN

Non-randomized controlled cohort.

METHODS

The tip of a pediatric transducer for transesophageal echography was inserted into each nostril under endoscopic control and placed in the ipsilateral Rosenmuller's fossa. The ICA's internal diameter and distance between the nasopharyngeal wall and the artery's closest point were measured on each side. Two independent examiners measured the same parameters on the axial plane of the skull base computer tomography (CT). Agreement between CT and echography measurements was estimated by the Bland-Altman approach.

RESULTS

Twenty-seven ICAs (sides) were available for the echography-CT agreement analysis. Inter method agreement for both parameters was similar to the inter examiner agreement for the CT measurements.

CONCLUSIONS

Our first study on endoscopic echography demonstrated that this method is applicable, potentially allowing safer transnasal surgery in the ICA vicinity.

LEVEL OF EVIDENCE

3 Laryngoscope, 2022.

Reduced magnetic resonance angiography signal intensity in the middle cerebral artery ipsilateral to severe carotid stenosis may be a practical index of high oxygen extraction fraction

Objectives

Angiographic “slow flow” in the middle cerebral artery (MCA), caused by carotid stenosis, may be associated with high oxygen extraction fraction (OEF). If the MCA slow flow is associated with a reduced relative signal intensity (rSI) of the MCA on MR angiography, the reduced rSI may be associated with a high OEF. We investigated whether the MCA slow flow ipsilateral to carotid stenosis was associated with a high OEF and aimed to create a practical index to estimate the high OEF.

Methods

We included patients who underwent digital subtraction angiography (DSA) and MRA between 2015 and 2019 to evaluate carotid stenosis. MCA slow flow by image count using DSA, MCA rSI, minimal luminal diameter (MLD) of the carotid artery, carotid artery stenosis rate (CASr), and whole-brain OEF (wb-OEF) was evaluated. When MCA slow flow was associated with a high wb-OEF, the determinants of MCA slow flow were identified, and their association with high wb-OEF was evaluated.

Results

One hundred and twenty-seven patients met our inclusion criteria. Angiographic MCA slow flow was associated with high wb-OEF. We identified MCA rSI and MLD as determinants of angiographic MCA slow flow. The upper limits of MCA rSI and MLD for angiographic MCA slow flow were 0.89 and 1.06 mm, respectively. The wb-OEF was higher in patients with an MCA rSI ≤ 0.89 and ipsilateral MLD ≤ 1.06 mm than patients without this combination.

Conclusions

The combination of reduced MCA rSI and ipsilateral narrow MLD is a straightforward index of high wb-OEF.

Key Points

• The whole-brain OEF in patients with angiographic slow flow in the MCA ipsilateral to high-grade carotid stenosis was higher than in patients without it.

• Independent determinants of MCA slow flow were MCA relative signal intensity (rSI) on MRA or minimal luminal diameter (MLD) of the carotid stenosis.

• The wb-OEF was higher in patients with an MCA rSI ≤ 0.89 and ipsilateral MLD ≤ 1.06 mm than patients without this combination.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08272-3.

Aortic Calcification in Takayasu Arteritis: Risk Factors and Relationship With Activity and Vascular Lesion. It Is Not Only an Aging Question

INTRODUCTION

Aortic calcification is a frequent finding in Takayasu arteritis (TA). The aim of this study was to evaluate the risk factors for aortic calcification in TA and its relationship with disease activity and the presence and type of vascular lesion.

METHODS

Nineteen patients with TA underwent nonenhanced computed tomography to measure the calcium score of the aorta and its main branches, which were divided into 13 segments. In each segment, the type of vascular lesion was evaluated by noninvasive angiography. Clinical risk factors and disease activity scores were recorded.

RESULTS

Eighteen of 19 patients (95%) were women, with a median age of 25 years. Median of calcium score was 69 AU (0-12,465 AU). Eleven of 19 patients (57.9%) had calcium score greater than 0. Age, evolution time, and dyslipidemia were higher in patients with calcium, whereas the National Institutes Health and Dabague disease activity scores were lower. There was no association between the presence of calcium and vascular lesion: 60 of 160 segments (37.5%) without calcium had some lesion, compared with 24 of 68 (35.3%) with calcium score greater than 0, p = 0.75. However, occlusion was more frequent in patients with calcium, whereas wall thickening was in those without calcium.

CONCLUSIONS

Aortic calcification in TA is related to age, evolution time, and abnormalities in lipid profile and occlusion and, inversely with some activity scores. Identification of calcification could be useful in identifying patients that even without significant lesions might have accelerated atherosclerosis, and who might be benefited with specific treatment.

A Deep Neural Network Method for Arterial Blood Flow Profile Reconstruction

Arterial stenosis will reduce the blood flow to various organs or tissues, causing cardiovascular diseases. Although there are mature diagnostic techniques in clinical practice, they are not suitable for early cardiovascular disease prediction and monitoring due to their high cost and complex operation. In this paper, we studied the electromagnetic effect of arterial blood flow and proposed a method based on the deep neural network for arterial blood flow profile reconstruction. The potential difference and weight matrix are used as inputs to the method, and its output is an estimate of the internal blood flow velocity distribution for arterial blood flow profile reconstruction. Firstly, the weight matrix is input into the convolutional auto-encode (CAE) network to extract its features. Then, the weight matrix features and potential difference are combined to obtain the features of the blood velocity distribution. Finally, the velocity features are reconstructed into blood flow velocity distribution by a convolution neural network (CNN). All data sets are obtained from a model of the carotid artery with different rates of stenosis in a uniform magnetic field by COMSOL. The results show that the average root mean square error of the reconstruction results obtained by the proposed method is 0.0333, and the average correlation coefficient is 0.9721, which is better than the corresponding indicators of the Tikhonov, back propagation (BP) and CNN methods. The simulation results show that the proposed method can achieve high accuracy in blood flow profile reconstruction and is of great significance for the early diagnosis of arterial stenosis and other vessel diseases.

Computed tomography angiography-derived area stenosis calculations overestimate degree of carotid stenosis compared with North American Symptomatic Carotid Endarterectomy Trial-derived diameter stenosis calculations

OBJECTIVE

The degree of carotid artery stenosis, calculated using catheter-based angiography and the North American Symptomatic Carotid Endarterectomy Trial (NASCET) method, has been shown to predict the stroke risk in several, large, randomized controlled trials. In the present era, patients have been increasingly evaluated using computed tomography (CT) angiography (CTA) before carotid artery revascularization, especially as the use of transcarotid artery revascularization has increased. Interpretation of CTA findings regarding the degree of carotid stenosis has not been standardized, with both NASCET methods and the area stenosis used. We performed a single-institution, blinded, retrospective analysis of CTA studies using both the NASCET method and the CT-derived area stenosis to assess the concordance and discordance between the two methods when evaluating ≥70% and ≥80% stenosis.

METHODS

The UMass Memorial Medical Center vascular laboratory database was queried for all carotid duplex ultrasound scans performed from 2008 to 2017. The included patients were limited to those with duplex-defined ≥70% stenosis (defined as a peak systolic velocity of ≥125 cm/s and an internal carotid artery/common carotid artery ratio of ≥4), and a correlative CTA study performed within 1 year of the duplex ultrasound examination. A blinded review of all correlative CTA studies using centerline measurements on a three-dimensional workstation (Aquarius iNtuition Viewer; Terarecon, Durham, NC) was performed to characterize the degree of carotid stenosis using the NASCET method and the area stenosis method. Patients were excluded if revascularization had been performed between the two imaging studies.

RESULTS

Of the 37,204 carotid duplex ultrasound scans reviewed (performed from 2008 to 2017), 3480 arteries met the criteria for duplex ultrasound-defined ≥70% stenosis. A correlative CTA study within 1 year of the duplex ultrasound examination was identified in 460 arteries, of which 320 were adequate quality for blinded review. The median interval between the duplex ultrasound and CTA examinations was 9.5 days. Concordance between the area stenosis and NASCET methods was poor for both ≥70% (κ = 0.32) and ≥80% (κ = 0.25) stenosis. Of the 247 arteries considered to have ≥70% area stenosis, 127 (51.4%) were considered to have ≥70% stenosis using the NASCET method. Of the 169 arteries considered to have ≥80% area stenosis, 44 (26.0%) were considered to have ≥80% stenosis using the NASCET method.

CONCLUSIONS

The area stenosis CTA calculations of carotid artery stenosis dramatically overestimated the degree of carotid stenosis compared with that calculated using the NASCET method. Given that stroke risk estimates have been determined from trials that used the NASCET method, the area stenosis method likely overestimates the risk of stroke. Therefore, area stenosis calculations could lead to unnecessary carotid revascularization procedures. This model highlights the need for standardized usage of the NASCET method when using CTA as the imaging modality to determine the threshold for carotid revascularization.

Overcoming calcium blooming and improving the quantification accuracy of percent area luminal stenosis by material decomposition of multi-energy computed tomography datasets

Purpose: Conventional stenosis quantification from single-energy computed tomography (SECT) images relies on segmentation of lumen boundaries, which suffers from partial volume averaging and calcium blooming effects. We present and evaluate a method for quantifying percent area stenosis using multienergy CT (MECT) images. Approach: We utilize material decomposition of MECT images to measure stenosis based on the ratio of iodine mass between vessel locations with and without a stenosis, thereby eliminating the requirement for segmentation of iodinated lumen. The method was first assessed using simulated MECT images created with different spatial resolutions. To experimentally assess this method, four phantoms with different stenosis severity (30% to 51%), vessel diameters (5.5 to 14 mm), and calcification densities (700 to 1100    mgHA / cc ) were fabricated. Conventional SECT images were acquired using a commercial CT system and were analyzed with commercial software. MECT images were acquired using a commercial dual-energy CT (DECT) system and also from a research photon-counting detector CT (PCD-CT) system. Three-material-decomposition was performed on MECT data, and iodine density maps were used to quantify stenosis. Clinical radiation doses were used for all data acquisitions. Results: Computer simulation verified that this method reduced partial volume and blooming effects, resulting in consistent stenosis measurements. Phantom experiments showed accurate and reproducible stenosis measurements from MECT images. For DECT and two-threshold PCD-CT images, the estimation errors were 4.0% to 7.0%, 2.0% to 9.0%, 10.0% to 18.0%, and - 1.0 % to - 5.0 % (ground truth: 51%, 51%, 51%, and 30%). For four-threshold PCD-CT images, the errors were 1.0% to 3.0%, 4.0% to 6.0%, - 1.0 % to 9.0%, and 0.0% to 6.0%. Errors using SECT were much larger, ranging from 4.4% to 46%, and were especially worse in the presence of dense calcifications. Conclusions: The proposed approach was shown to be insensitive to acquisition parameters, demonstrating the potential to improve the accuracy and precision of stenosis measurements in clinical practice.

Correlation of Cerebral White Matter Lesions with Carotid Intraplaque Neovascularization assessed by Contrast-enhanced Ultrasound

PURPOSE

Carotid atherosclerotic plaque is closely associated with cerebral white matter lesions (WMLs), while intraplaque neovascularization (IPN) contributes significantly to arterial remodeling and plaque vulnerability. In this study, we aim to evaluate the correlation of carotid IPN with cerebral WMLs.

METHODS

The presence of IPN and WMLs were assessed by contrast-enhanced ultrasound (CEUS) and MRI respectively. IPN was evaluated utilizing semi-quantification visual grading scale and WMLs was divided according to Fazekas grading scale. We investigated the baseline data, Fazekas grades, and IPN grades among 269 participants. We explored the influences of each variable on Fazekas grades using ordinal logistic regression and evaluated the relationship between IPN grades and WMLs Fazekas grades.

RESULTS

Increased age (OR: 1.06, P<0.001), hypertension (OR: 2.17, P=0.002), cerebral infarction (OR: 1.74, P=0.046), and elevated carotid IPN grading were significantly associated with aggravated Fazekas grades (grade 2 or 3). To be specific, people having grade 3, 2, and 1 carotid IPN were 25.84 (P<0.001), 10.64 (P<0.001), and 5.96 (P=0.010) times as likely to have elevated Fazekas grades compared with those who having grade 0 carotid IPN.

CONCLUSION

Increased carotid IPN is independently correlated with aggravated cerebral WMLs.

Antithrombotic Therapy in Carotid Artery Disease

The management of asymptomatic atherosclerotic carotid artery disease and the role of antithrombotic therapy is of increasing importance for stroke prevention. Non-invasive imaging of carotid plaques can identify high-risk plaque features that are associated with the risk of plaque rupture. Carotid plaque necrosis, hemorrhage, fibrous cap thinning, and the presence of foam cells have all been correlated with the risk of rupture and onset of neurological symptoms in patients with carotid stenosis. Antiplatelets are currently recommended for patients with a history of ischemic stroke and/or significant carotid artery stenosis, with aspirin and clopidogrel being the most widely used and studied agents. The role of dual antiplatelet therapy remains controversial. Moreover, there is scarce evidence on the role of newer anticoagulant agents in stable patients with carotid artery stenosis. In this review article, we discuss the pathophysiology of carotid atherosclerosis, the use of non-invasive imaging for detecting the vulnerable carotid plaque and summarize the existing clinical evidence on the use of antiplatelet and antithrombotic agents in carotid artery disease.