Quantification Of Carotid Artery Stenosis Research Articles

CASMatching strategy for automated detection and quantification of carotid artery stenosis based on digital subtraction angiography

Background and objectiveAutomated detection and quantification of carotid artery stenosis is a crucial task in establishing a computer-aided diagnostic system for brain diseases. Digital subtraction angiography (DSA) is known as the "gold standard" for carotid stenosis diagnosis. It is commonly used to identify carotid artery stenosis and measure morphological indices of the stenosis. However, using deep learning to detect stenosis based on DSA images and further quantitatively predicting the morphological indices remain a challenge due the absence of prior work. In this paper, we propose a quantitative method for predicting morphological indices of carotid stenosis. MethodsOur method adopts a two-stage pipeline, first locating regions suitable for predicting morphological indices by object detection model, and then using a regression model to predict indices. A novel Carotid Artery Stenosis Matching (CASMatching) strategy is introduced into the object detection to model the matching relationship between a stenosis and multiple normal vessel segments. The proposed Match-ness branch predicts a Match-ness score for each normal vessel segment to indicate the degree of matching to the stenosis. A novel Direction Distance-IoU (2DIoU) loss based on the Distance-IoU loss is proposed to make the model focused more on the bounding box regression in the direction of vessel extension. After detection, the normal vessel segment with the highest Match-ness score and the stenosis are intercepted from the original image, then fed into a regression model to predict morphological indices and calculate the degree of stenosis. ResultsOur method is trained and evaluated on a dataset collected from three different manufacturers' monoplane X-ray systems. The results show that the proposed components in the object detector substantially improve the detection performance of normal vascular segments. For the prediction of morphological indices, our model achieves Mean Absolute Error of 0.378, 0.221, 4.9 on reference vessel diameter (RVD), minimum lumen diameter (MLD) and stenosis degree. ConclusionsOur method can precisely localize the carotid stenosis and the normal vessel segment suitable for predicting RVD of the stenosis, and further achieve accurate quantification, providing a novel solution for the quantification of carotid artery stenosis.

Accuracy of Carotid Artery Stenosis Quantification with 4-D-Supported 3-D Power-Doppler versus Color-Doppler and 2-D Blood Velocity-Based Duplex Ultrasonography

Assessment of the severity of internal carotid artery stenosis is relevant to therapeutic decisions. Direct measurement of stenosis in static three-dimensionally rendered ultrasonographic color-Doppler images after an orientation with 4-D gray-scale views (4D/3D-C-US) was recently observed to be metrically non-inferior to angiography. In the study described here, power-Doppler (Christian Doppler was a physicist) ultrasonography (4D/3D-P-US) was prospectively compared with angiography, 4D/3D-C-US and 2-D duplex ultrasonography (DUS) in a similar fashion using blinded observers. Percentage stenosis was measured in 36 patients. Continuous percentage stenosis measures (standard deviation of difference and concordance correlation coefficient) between angiography and 4D/3D-P-US did not differ from the results between angiography observers (p > 0.05). Dichotomous diagnosis with 4D/3D-P-US resulted in κ values similar to the inter-rater agreement of angiography and the inter-method agreement of 4D/3D-C-US and DUS compared with angiography. Binary accuracy did not differ between 4D/3D-P-US, 4D/3D-C-US and DUS (p > 0.5). In conclusion, stenosis grading using 4D/3D-P-US exhibited non-inferior inter-method agreement with angiography at good accuracies, similar to 4D/3D-C-US and DUS.

Agreement between multi-detector-row CT angiography and US-ECD in quantification of carotid artery stenosis and plaque characterization

PurposeThe purpose of this work was to evaluate the agreement between ultra-sound echo-color Doppler (US-ECD) and multi-detector-row CT angiography (MDCTA) in the quantification of carotid artery stenosis as well as plaque characterization. Materials and methodsFrom January 2012 to January 2013 forty-five patients who underwent both MDCTA and US-ECD for the study of carotid arteries, were evaluated (33 males, 12 females; age range 43–70years; mean age of 59.6years). For all subjects the following parameters were analyzed: stenosis degree by using the NASCET method, plaque morphology (regular versus irregular), type of the plaque (fatty, mixed and calcified) and presence of ulcerations. Statistical analysis was performed to calculate concordance between the two techniques employed. ResultsThe agreement observed in the quantification of carotid artery stenosis was 94.4% with a kappa value of 0.9306 (95% confidence interval of 0.8612–1.0). In the definition of the type of plaque, the observed agreements were 91.1% and the kappa value was 0.8815 (95% confidence interval: 0.7920–0.9709). In the definition of plaque ulceration, the observed agreements were 88.4% but the kappa value was only 0.325 (95% confidence interval: 0.201–0.449). Agreement observed in the evaluation of plaque morphology was 78.3% with a kappa value of 0.513 (95% confidence interval: 0.452–0.574). ConclusionWe observed a good agreement between US-ECD and MDCTA in the quantification of carotid artery stenosis and the assessment of plaque type. There was, however, a poor agreement in the evaluation of plaque ulceration. The use of US-ECD and MDCTA provides different results in the evaluation of plaque. Our results suggest that information derived from US-ECD should be always critically compared with other diagnostic techniques.

Lumen segmentation and stenosis quantification of atherosclerotic carotid arteries in CTA utilizing a centerline intensity prior

The degree of stenosis is an important biomarker in assessing the severity of cardiovascular disease. The purpose of our work is to develop and evaluate a semiautomatic method for carotid lumen segmentation and subsequent carotid artery stenosis quantification in CTA images. The authors present a semiautomatic stenosis detection and quantification method following lumen segmentation. The lumen of the carotid arteries is segmented in three steps. First, centerlines of the internal and external carotid arteries are extracted with an iterative minimum cost path approach in which the costs are based on a measure of medialness and intensity similarity to lumen. Second, the lumen boundary is delineated using a level set procedure which is steered by gradient information, regional intensity information, and spatial information. Special effort is made in adding terms based on local centerline intensity prior so as to exclude all possible plaque tissues from the segmentation. Third, side branches in the segmented lumen are removed by applying a shape constraint to the envelope of the maximum inscribed spheres of the segmentation. From the segmented lumen, the authors detect and quantify the cross-sectional area-based and cross-sectional diameter-based stenosis degrees according to the North American Symptomatic Carotid En-darterectomy Trial criterion. The method is trained and tested on a publicly available database from the cls2009 challenge. For the segmentation, the authors obtain a Dice similarity coefficient of 90.2% and a mean absolute surface distance of 0.34 mm. For the stenosis quantification, the authors obtain an average error of 15.7% for cross-sectional diameter-based stenosis and 19.2% for cross-sectional area-based stenosis quantification. With these results, the method ranks second in terms of carotid lumen segmentation accuracy, and first in terms of carotid artery stenosis quantification.

Role of MDCTA in Quantification of Carotid Artery Stenosis and Assessment of Atheromatous Plaques

Role of MDCTA in Quantification of Carotid Artery Stenosis and Assessment of Atheromatous Plaques

Automated quantification of carotid artery stenosis on contrast-enhanced MRA data using a deformable vascular tube model

The purpose of this study was to develop and validate a method for automated segmentation of the carotid artery lumen from volumetric MR Angiographic (MRA) images using a deformable tubular 3D Non-Uniform Rational B-Splines (NURBS) model. A flexible 3D tubular NURBS model was designed to delineate the carotid arterial lumen. User interaction was allowed to guide the model by placement of forbidden areas. Contrast-enhanced MRA (CE-MRA) from 21 patients with carotid atherosclerotic disease were included in this study. The validation was performed against expert drawn contours on multi-planar reformatted image slices perpendicular to the artery. Excellent linear correlations were found on cross-sectional area measurement (r = 0.98, P < 0.05) and on luminal diameter (r = 0.98, P < 0.05). Strong match in terms of the Dice similarity indices were achieved: 0.95 ± 0.02 (common carotid artery), 0.90 ± 0.07 (internal carotid artery), 0.87 ± 0.07 (external carotid artery), 0.88 ± 0.09 (carotid bifurcation) and 0.75 ± 0.20 (stenosed segments). Slight overestimation of stenosis grading by the automated method was observed. The mean differences was 7.20% (SD = 21.00%) and 5.2% (SD = 21.96%) when validated against two observers. Reproducibility in stenosis grade calculation by the automated method was high; the mean difference between two repeated analyses was 1.9 ± 7.3%. In conclusion, the automated method shows high potential for clinical application in the analysis of CE-MRA of carotid arteries.

Evaluation of Computer-Assisted Quantification of Carotid Artery Stenosis

The purpose of this study was to evaluate the influence of advanced software assistance on the assessment of carotid artery stenosis; particularly, the inter-observer variability of readers with different level of experience is to be investigated. Forty patients with suspected carotid artery stenosis received head and neck dual-energy CT angiography as part of their pre-interventional workup. Four blinded readers with different levels of experience performed standard imaging interpretation. At least 1 day later, they performed quantification using an advanced vessel analysis software including automatic dual-energy bone and hard plaque removal, automatic and semiautomatic vessel segmentation, as well as creation of curved planar reformation. Results were evaluated for the reproducibility of stenosis quantification of different readers by calculating the kappa and correlation values. Consensus reading of the two most experienced readers was used as the standard of reference. For standard imaging interpretation, experienced readers reached very good (k = 0.85) and good (k = 0.78) inter-observer variability. Inexperienced readers achieved moderate (k = 0.6) and fair (k = 0.24) results. Sensitivity values 80%, 91%, 83%, 77% and specificity values 100%, 84%, 82%, 53% were achieved for significant area stenosis >70%. For grading using advanced vessel analysis software, all readers achieved good inter-observer variability (k = 0.77, 0.72, 0.71, and 0.77). Specificity values of 97%, 95%, 95%, 93% and sensitivity values of 84%, 78%, 86%, 92% were achieved. In conclusion, when supported by advanced vessel analysis software, experienced readers are able to achieve good reproducibility. Even inexperienced readers are able to achieve good results in the assessment of carotid artery stenosis when using advanced vessel analysis software.

Carotid artery stenosis quantification: Concordance analysis between radiologist and semi-automatic computer software by using Multi-Detector-Row CT angiography

Purpose Carotid artery stenosis quantification is still considered a leading parameter in the choice of the therapeutic option. Our purpose was to asses the concordance between radiologist and a semi-automatic computer software in the stenosis quantification of carotid artery studied by using a Multi-Detector-Row CT angiography (MDCTA). Methods and material 45 patients studied by using a 40-detector row CT scanner were retrospectively analyzed. Carotid artery stenosis was quantified by one high experienced radiologist in vessel analysis and by using a dedicated software. Carotid artery stenosis was calculated according to the ECST method. Bland–Altman statistics was used to measure the inter- and intra-concordance between radiologist and software and correlation coefficient between measures were performed by using nonparametric Spearmann correlation statistic. A p value < 0.05 was considered to mean statistical significance. Results A strength correlation according to linear regression (correlation Spearman’ ρ coefficient = 0.975; p < 0.0001) between radiologist and software of vessel analysis was observed. Between first and second stenosis of carotid artery quantification performed by radiologist and software of vessel analysis we observed a Spearman’ ρ coefficient = 0.943 ( p < 0.0001) and a Spearman’ ρ coefficient = 0.9879; ( p < 0.0001) respectively. Conclusions Our results indicated that there is a strength correlation according to linear regression between stenosis of carotid artery quantification performed by radiologist and semi-automatic software. Reproducibility between measurements performed by semi-automatic software are higher compared to radiologist.

Correlation between US-PSV and MDCTA in the quantification of carotid artery stenosis

Purpose Stroke is a major cause of death and serious long-lasting neurological disability and the severity of carotid artery stenosis is one of the most important determinants of cerebrovascular events. The purpose of this paper is to evaluate the correlation between multi-detector-row CT angiography (MDCTA) and ultra-sound peak-systolic-velocity (US-PSV) in the quantification of carotid artery stenosis. Methods and material 52 patients were retrospectively studied by using four-detector row CT and ultra-sound. Each patient was assessed for stenosis degree by using NASCET method when studied by using MDCT and by using PSV when studied by using US. Statistic analysis was performed to determine the entity of correlation (method of Pearson) between MDCTA and US-PSV. The Bland-Altman analysis was applied to assess the level of inter-technique agreement. Results Sonographic PSV measurements ranged from 70 to 589 cm/s. Distal ICA velocities ranged from 29 to 238 cm/s. Linear regression analysis showed a good correlation ( r 2 = 0.613) between MDCTA-NASCET linear percentage stenosis and PSV and measured. PSV value that corresponded to a NASCET linear percentage stenosis of 70% was 283 cm/s and with this values sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 75%, 88.6%, 90.7% and 70.5%, respectively. Conclusions Results of our study suggest that NASCET stenosis measured in MDCTA and PSV values have a good correlation. The use of a threshold of 283 cm/s allows obtaining good value of sensitivity and specificity.

Color-coded duplex ultrasound compared to CT angiography for detection and quantification of carotid artery stenosis

Objective: The purpose of this study was to compare findings on color-coded duplex ultrasound and CT angiography for grading internal carotid artery stenosis, and to investigate whether both these imaging modalities are necessary for an accurate diagnosis of carotid stenosis in the pre-surgical assessment of the internal carotid artery. Patients and methods: We examined 92 internal carotid arteries from 46 randomly chosen patients with suspected carotid stenosis by color-coded duplex ultrasound and by three-dimensional CT angiography (CTA). This retrospective study adhered to international guidelines with gradings of mild, moderate, severe, and occlusive carotid disease. Results: The study demonstrated agreement between the degree of stenosis found on color-coded duplex ultrasound and that found on CTA in 78% of cases overall and in 79% of patients requiring surgical intervention. When compared to CTA, color-coded duplex ultrasound yielded a sensitivity of 78.9% and a specificity of 96.3%. Although findings on color-coded duplex ultrasound and CTA were comparable, disagreement affecting treatment decision occurred in 10:92 arteries. Conclusion: CTA was not found to be beneficial for patients exhibiting mild stenosis on color-coded duplex ultrasound, as none of the mild groupings found by sonography were interpreted as severe or occluded by CTA. However, CTA may be an important adjunct to color-coded duplex ultrasound regarding the categories of moderate, severe and occluded when carotid endarterectomy is considered.

Cerebrovascular ultrasound.

Rapid progress in noninvasive ultrasound techniques has resulted in a wide variety of clinical applications for assessment of both extracranial and intracranial arterial diseases. Recent highlights in cerebrovascular ultrasound research include imaging methods for characterization of intracranial aneurysms, use of echocontrast agents for improved evaluation of acute stroke patients and transient response harmonic imaging for depiction of brain perfusion. The important role of transcranial Doppler microembolism detection in carotid endarterectomy has been defined, new approaches to noninvasive Doppler measurement of intracranial pressure are progressing, and the clinical indications for transcranial Doppler monitoring of intracranial vasospasm to prevent secondary stroke have expanded. New functional transcranial Doppler applications, which are complementary to positron emission tomography and functional magnetic resonance imaging studies, are evolving for evaluation of functional recovery after stroke; investigation of perfusion asymmetries during complex spatial tasks; assessment of hemispheric dominance in surgical candidates for epilepsy surgery; and elucidation of temporal patterns of regional neuronal activity. With increasing sophistication of cerebrovascular ultrasound methodology, it is essential that standards for data acquisition and interpretation be established. Three recent consensus meetings have provided detailed recommendations on quantification of carotid artery stenosis, on characterization of carotid artery plaques and on microembolism detection by transcranial Doppler.