Carotid Artery Imaging Research Articles

Development of Landmark-Based Bit-State Model for Shape Analysis and Segmentation of Variations in Intima-Media Thickness of B-Mode Ultrasound Transverse Cross-Section of Carotid Artery Images

Central to the assessment of carotid artery health is the measurement of intima-media thickness (IMT), a valuable diagnostic marker for atherosclerosis. IMT quantifies the thickness of two arterial layers — the intima and media — providing insights into arterial wall health and atherosclerotic changes. Carotid ultrasound, a non-invasive imaging technique, is the primary modality for IMT measurement. However, it is not without its challenges, including operator dependency and segmentation difficulties. To surmount these limitations and advance our understanding of carotid artery health, in this research paper, we develop the Bit-State model by applying landmark-based geometric morphometrics (GM) that built upon the foundation of cardinal point symmetry landmark distributed models (CPS-LDM) which we have developed in our previous papers to comprehensively characterize and segment carotid artery IMT, unveiling essential insights into variations and alterations. The Bit-State (BS) Model, revolutionizes our approach to understanding carotid artery structural variations. In this paper, there are four regions of interest (ROI) in the B-Mode carotid artery image, hence we designated each ROI as a bit. Each bit is capable of existing in either of two states: bit 1 as thick-walled and bit 0 as thin-walled ROI. In adopting this binary characterization, we generated 16 different modalities and variations of the ROI of the carotid artery, we then proceed to use the CPS-LD Model to formulate 16 equations for the segmentation of the ROI the carotid artery images. This new model simplifies the complexity of B-Mode ultrasound carotid artery images. It systematically characterizes shape variations using CPS-LDM equations, offering an interpretable framework for comprehending arterial wall composition. This research represents a significant leap forward in carotid artery health assessment, promising more precise diagnoses and targeted interventions for cardiovascular health. It highlights the pivotal role of landmark-based GM in addressing the challenges posed by carotid artery diseases and atherosclerosis. By pioneering this innovative model, this research paves the way for a deeper understanding of carotid artery health and its implications for stroke prevention — a critical stride towards mitigating the global burden of cardiovascular diseases.

Resistance- and endurance-trained young men display comparable carotid artery strain parameters that are superior to untrained men

PurposeCentral arterial stiffness, a predictor of cardiovascular risk, attenuates with endurance-exercise in ageing populations. However, in young individuals, this effect is inconsistent and emerging evidence suggests resistance-exercise may increase arterial stiffness. Two-dimensional (2D)-Strain imaging of the common carotid artery (CCA) is more sensitive at detecting endurance-training induced alterations in CCA stiffness than conventional methods, but has not been used to examine CCA stiffness in young resistance-trained individuals. Therefore, we compared CCA 2D-Strain parameters at rest, during acute exercise and recovery between resistance-trained, endurance-trained, and untrained young men.MethodsShort-axis CCA ultrasound images were obtained from 12 endurance-trained [27yrs (95%CI; 24–29)], 14 resistance-trained [24yrs (23–26)] and 12 untrained [23yrs (22–24] men at rest, during isometric handgrip (IHG) exercise and recovery. 2D-Strain analysis quantified CCA peak circumferential strain (PCS) and systolic (S-SR) and diastolic (D-SR) strain rates. Conventional stiffness indices included aortic pulse-wave velocity, CCA β-stiffness (β1) and Petersons elastic modulus (Ep).ResultsResting conventional stiffness indices were not different between groups (P > 0.05). Resting PCS and S-SR were comparable between resistance- [11.6% (10.6–12.5) and 1.46 s−1 (1.37–1.55), respectively] and endurance-trained [11.4% (10.7–12.2) and 1.5 s−1 (1.38–1.62)] men and superior to untrained men [9.5% (9.19–9.9); P < 0.004 and 1.24 s−1 (1.17 – 1.31); P < 0.018)]. Both trained groups displayed comparable reductions in PCS and S-SR during IHG, which returned to resting values during recovery (P < 0.001), whereas these parameters remained unchanged in untrained men. D-SR decreased during IHG in all groups (P < 0.001), but to a lesser extent in endurance-trained men (P < 0.023), whereas β1 and Ep increased to a similar magnitude in all groups and returned to resting values during recovery (P < 0.001).ConclusionResistance- and endurance-trained men display comparable CCA 2D-Strain parameters that are superior to untrained men, which contends previous reports that resistance-training increases CCA stiffness.

Investigating the pathophysiology and evolution of internal carotid dissection: a fluid-structure interaction simulation study.

Arterial dissection, a condition marked by the tearing of the carotid artery's inner layers, can result in varied clinical outcomes, including progression, stability, or spontaneous regression. Understanding these outcomes' underlying mechanisms is crucial for enhancing patient care, particularly with the increasing use of computer simulations in medical diagnostics and treatment planning. The aim of this study is to utilize computational analysis of blood flow and vascular wall to: (1) understand the pathophysiology of stroke-like episodes in patients with carotid artery dissection; and (2) assess the effectiveness of this method in predicting the evolution of carotid dissection. Utilizing contrast-enhanced magnetic resonance angiography (MRA), we segmented images of the patient's right internal carotid artery. These images were transformed into 3D solids for simulation in Ansys multifisic software, employing a two-way fluid structure interaction (FSI) analysis. Simulations were conducted across two wall conditions (atherosclerotic and normal) and three pressure states (hypotension, normotension, hypertension). The simulations indicated a significant pressure discrepancy between the true and false lumens of the artery. This suggests that flap motion and functional occlusion under hypertensive conditions could be the cause of the clinical episodes. Thrombotic risk and potential for dissection extension were not found to be critical concerns. However, a non-negligible risk of vessel dilation was assessed, aligning with the patient's clinical follow-up data. This study highlights specific hemodynamic parameters that could elucidate carotid artery dissection's mechanisms, offering a potential predictive tool for assessing dissection progression and informing personalized patient care strategies.

An Efficient Multi-Scale Wavelet Approach for Dehazing and Denoising Ultrasound Images Using Fractional-Order Filtering

Ultrasound imaging is widely used in medical diagnostics due to its non-invasive and real-time capabilities. However, existing methods often overlook the benefits of fractional-order filters for denoising and dehazing. Thus, this work introduces an efficient multi-scale wavelet method for dehazing and denoising ultrasound images using a fractional-order filter, which integrates a guided filter, directional filter, fractional-order filter, and haze removal to the different resolution images generated by a multi-scale wavelet. In the directional filter stage, an eigen-analysis of each pixel is conducted to extract structural features, which are then classified into edges for targeted filtering. The guided filter subsequently reduces speckle noise in homogeneous anatomical regions. The fractional-order filter allows the algorithm to effectively denoise while improving edge definition, irrespective of the edge size. Haze removal can effectively eliminate the haze caused by attenuation. Our method achieved significant improvements, with PSNR reaching 31.25 and SSIM 0.905 on our ultrasound dataset, outperforming other methods. Additionally, on external datasets like McMaster and Kodak24, it achieved the highest PSNR (29.68, 28.62) and SSIM (0.858, 0.803). Clinical evaluations by four radiologists confirmed its superiority in liver and carotid artery images. Overall, our approach outperforms existing speckle reduction and structural preservation techniques, making it highly suitable for clinical ultrasound imaging.

Abstract P439: An Uncommon and Missed Diagnosis of Hypertension: Fibromuscular Dysplasia

Introduction: Fibromuscular dysplasia is a noninflammatory vascular disease most commonly affecting carotid and renal arteries, especially in young to middle aged women. Renal artery stenosis may cause refractory and severe hypertension in these patients without traditional risk factors. Case: A 58-year-old woman with uncontrolled hypertension on calcium channel and angiotensin receptor blocker and history of left carotid artery stenosis, and carotid endarterectomy at the age of 48 years, was referred cardiac evaluation. Patient’s twin sister had a diagnosis of fibromuscular dysplasia (FMD). Her blood pressure was 190/90 mmHg at presentation. Computed Tomography Angiography (CTA) of the abdomen/pelvis showed a typical nodular stenosis of the mid renal artery consistent with FMD. Patient underwent renal angiogram and successful percutaneous transluminal angioplasty. She still required medical therapy but her BP significantly improved. Discussion: Our patient had severe hypertension, carotid artery stenosis and even surgery but had missed FMD diagnosis for &gt; 10 years. Physicians should have a high level of clinical suspicion for young and middle aged women with refractory hypertension and/or artery stenosis, aneurysm, or dissection in any vascular bed. CTA should be performed for renal and carotid artery imaging looking for typical “string of beads” appearance. Cerebral artery aneurysm should also be evaluated. The inheritance pattern for FMD such as PHACTR1 is most consistent with an autosomal dominant trait with variable penetrance. Renal artery angioplasty may lessen the degree of refractory or severe hypertension.

Ultra-low-field magnetic resonance angiography at 0.05 T: A preliminary study.

We aim to explore the feasibility of head and neck time-of-flight (TOF) magnetic resonance angiography (MRA) at ultra-low-field (ULF). TOF MRA was conducted on a highly simplified 0.05 T MRI scanner with no radiofrequency (RF) and magnetic shielding. A flow-compensated three-dimensional (3D)gradient echo (GRE) sequence with a tilt-optimized nonsaturated excitation RF pulse, and a flow-compensated multislice two-dimensional (2D) GRE sequence, were implemented for cerebral artery and vein imaging, respectively. For carotid artery and jugular vein imaging, flow-compensated 2D GRE sequences were utilized with venous and arterial blood presaturation, respectively. MRA was performed on young healthy subjects. Vessel-to-background contrast was experimentally observed with strong blood inflow effect and background tissue suppression. The large primary cerebral arteries and veins, carotid arteries, jugular veins, and artery bifurcations could be identified in both raw GRE images and maximum intensity projections. The primary brain and neck arteries were found to be reproducible among multiple examination sessions. These preliminary experimental results demonstrated the possibility of artery TOF MRA on low-cost 0.05 T scanners for the first time, despite the extremely low MR signal. We expect to improve the quality of ULF TOF MRA in the near future through sequence development and optimization, ongoing advances in ULF hardware and image formation, and the use of vascular T1 contrast agents.

Diagnostic potential of TSH to HDL cholesterol ratio in vulnerable carotid plaque identification.

This study aimed to investigate the predictive value of the thyroid-stimulating hormone to high-density lipoprotein cholesterol ratio (THR) in identifying specific vulnerable carotid artery plaques. In this retrospective analysis, we included 76 patients with carotid plaques who met the criteria for admission to Zhejiang Hospital from July 2019 to June 2021. High-resolution magnetic resonance imaging (HRMRI) and the MRI-PlaqueView vascular plaque imaging diagnostic system were utilized to analyze carotid artery images for the identification of specific plaque components, including the lipid core (LC), fibrous cap (FC), and intraplaque hemorrhage (IPH), and recording of the area percentage of LC and IPH, as well as the thickness of FC. Patients were categorized into stable plaque and vulnerable plaque groups based on diagnostic criteria for vulnerable plaques derived from imaging. Plaques were categorized based on meeting one of the following consensus criteria for vulnerability: lipid core area over 40% of total plaque area, fibrous cap thickness less than 65 um, or the presence of intraplaque hemorrhage. Plaques meeting the above criteria were designated as the LC-associated vulnerable plaque group, the IPH-associated group, and the FC-associated group. Multivariate logistic regression was employed to analyze the factors influencing carotid vulnerable plaques and specific vulnerable plaque components. Receiver operating characteristic (ROC) curves were used to assess the predictive value of serological indices for vulnerable carotid plaques. We found that THR (OR = 1.976; 95% CI = 1.094-3.570; p = 0.024) and TSH (OR = 1.939, 95% CI = 1.122-3.350, p = 0.018) contributed to the formation of vulnerable carotid plaques. THR exhibited an area under the curve (AUC) of 0.704 (95% CI = 0.588-0.803) (p = 0.003), and the AUC for TSH was 0.681 (95% CI = 0.564-0.783) (p = 0.008). THR was identified as an independent predictor of LC-associated vulnerable plaques (OR = 2.117, 95% CI = 1.064-4.212, p = 0.033), yielding an AUC of 0.815. THR also demonstrated diagnostic efficacy for LC-associated vulnerable plaques. This study substantiated that THR and TSH have predictive value for identifying vulnerable carotid plaques, with THR proving to be a more effective diagnostic indicator than TSH. THR also exhibited predictive value and specificity in the context of LC-associated vulnerable plaques. These findings suggest that THR may be a promising clinical indicator, outperforming TSH in detecting specific vulnerable carotid plaques.

Photon-Counting Computed Tomography in Atherosclerotic Plaque Characterization.

Atherosclerotic plaque buildup in the coronary and carotid arteries is pivotal in the onset of acute myocardial infarctions or cerebrovascular events, leading to heightened levels of illness and death. Atherosclerosis is a complex and multistep disease, beginning with the deposition of low-density lipoproteins in the arterial intima and culminating in plaque rupture. Modern technology favors non-invasive imaging techniques to assess atherosclerotic plaque and offer insights beyond mere artery stenosis. Among these, computed tomography stands out for its widespread clinical adoption and is prized for its speed and accessibility. Nonetheless, some limitations persist. The introduction of photon-counting computed tomography (PCCT), with its multi-energy capabilities, enhanced spatial resolution, and superior soft tissue contrast with minimal electronic noise, brings significant advantages to carotid and coronary artery imaging, enabling a more comprehensive examination of atherosclerotic plaque composition. This narrative review aims to provide a comprehensive overview of the main concepts related to PCCT. Additionally, we aim to explore the existing literature on the clinical application of PCCT in assessing atherosclerotic plaque. Finally, we will examine the advantages and limitations of this recently introduced technology.

Value of carotid corrected flow time or changes value of FTc could be more useful in predicting fluid responsiveness in patients undergoing robot-assisted gynecologic surgery: a prospective observational study.

The aim of this study was to evaluate the ability of point-of-care Doppler ultrasound measurements of carotid corrected flow time and its changes induced by volume expansion to predict fluid responsiveness in patients undergoing robot-assisted gynecological surgery. In this prospective study, carotid corrected flow time was measured using Doppler images of the common carotid artery before and after volume expansion. The stroke volume index at each time point was recorded using noninvasive cardiac output monitoring with MostCare. Of the 52 patients enrolled, 26 responded. The areas under the receiver operating characteristic curves of the carotid corrected flow time and changes in carotid corrected flow time induced by volume expansion were 0.82 and 0.67, respectively. Their optimal cut-off values were 357 and 19.5 ms, respectively. Carotid corrected flow time was superior to changes in carotid corrected flow time induced by volume expansion for predicting fluid responsiveness in this population.

Carotid wave analysis in young adults with a history of adolescent anorexia nervosa: a case control study

BackgroundAnorexia nervosa (AN) is associated with abnormalities that may increase the risk of future cardiovascular disease. This study assessed the cardiovascular health of individuals who recovered from AN during adolescence by conducting wave power analysis.MethodsFormer AN patients discharged from the Royal Children’s and Monash Children’s Hospitals (N = 17) in Melbourne, Australia underwent ultrasound imaging of the right carotid artery. Wave power analysis was conducted to assess biomechanical interactions of the cardiovascular system. Patient measures were compared to healthy controls (N = 51).ResultsEighty-eight percent of the former AN patients and controls were female, aged approximately 25 years, with a healthy body mass index. Mean carotid flow and pulsatility index were not different between groups. Carotid arterial strain and distensibility were lower, and the wave speed and beta stiffness index higher in the former AN patients. Characteristic impedance was not different nor were the forward and backward wave amplitudes. However, wave reflection indices (ratios of backward-to-forward compression wave area, and wave-related effect on pressure and hydraulic power) were 12–18% lower in the former AN patients (p < 0.05).ConclusionsIncreased carotid artery stiffness and reduced wave reflection are evident in young adults who recovered from adolescent AN. This may relate to an adaptive process that helps to maintain or restore flow and characteristic impedance despite increased vessel stiffness, with this warranting future investigation.

An 8-Channel Transceiver Coil for Carotid Artery Imaging at 7T Using an Optimized Shield Design.

To design and fabricate a transmit/receive (T/R) radiofrequency (RF) coil array for MRI of the carotid arteries at 7T with optimal shielding to improve transmit performance in parallel transmit (pTx) mode. The carotid coil included 8 total RF elements, with left and right subarrays, each consisting of 4 overlapping loops with RF shields. Electromagnetic (EM) simulations were performed to optimize and improve the transmit performance of the array by determining the optimal distance between the RF shield and each subarray. EM simulations were further used to calculate local specific absorption rate (SAR) matrices. Based on the SAR matrices, virtual observation points (VOPs) were applied to ensure safety during parallel transmission. The efficacy of the coil design was evaluated by measuring coil performance metrics when imaging a phantom and by acquiring in-vivo images. The optimal distance between the RF shield and each subarray was determined to be 45 mm. This resulted in a maximum B1+ efficiency of 1.23 μT/ √W in the carotid arteries and a peak, 10-g-average SAR per Watt of 0.86 kg-1 when transmitting in the nominal CP+ mode. Optimizing the RF shield resulted in up to 37% improvement in B1+ efficiency and 14% improvement in SAR efficiency compared to an unshielded design. Optimizing the distance between the RF shield and coil array provided significant improvement in the transmit characteristics of the bilateral carotid coil. The bilateral coil topology provides a compelling platform for imaging the carotid arteries with high field MRI.

NIMG-72. CONTRALATERAL PREDOMINANT BLOOD SUPPLY OF FALX AND PARASAGITTAL MENINGIOMA BASED ON ANGIOGRAPHIC ANALYSIS

Abstract INTRODUCTION Preoperative prediction of blood supply in meningiomas is important to avoid unexpected intraoperative bleeding. Herein, we investigated the relationship between the location of meningioma and the dominant side of feeding arteries. METHOD: Between January 2018 and December 2020, a total of 101 consecutive patients underwent craniotomy for meningioma at our hospital. Among them, 43 cases in which the lesions were clearly localized on the right or left sides received preoperative angiography including bilateral common or external carotid artery (ECA) imaging. A region of interest (ROI) was set at the most stained area in (X) meningioma and (Y) main trunk of the ECA. In each affected side (AS) and healthy side (HS), the ratio of ROI (X) value to ROI (Y) value; tumor / vessel ratio (TVR = 0 ~ 1) was calculated. Multivariate analysis was performed to compare TVR between AS and HS, and to analyze factors associated with TVR, such as site of origin (convexity, skull base and relating falx), age, gender, WHO grading, and tumor diameter. RESULTS TVR was significantly higher in AS (0.60; 0.41 - 0.91) than HS (0.47; 0.39 - 0.99) (p=0.0003). HS was superior to AS in 10 cases, all of which were falx (6 of 9 cases) or parasagittal (4 of 10 cases) meningioma. 53% of falx and parasagittal meningiomas showed HS predominant TVR. Concerning factors associated with the TVR of HS predominance, falx origin was extracted as an independent factor (p&amp;lt; 0.0001). DISCUSSION The vessels crossing in the falx, which consist with particular anatomical structure, fusing the meningeal layers in each side of dura mater would contribute to this finding. CONCLUSION Falx and parasagittal meningiomas should consider the predominant influx of tumor feeding vessels from HS.

A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance-A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions.

Atherosclerotic plaque classification in carotid ultrasound images using machine learning and explainable deep learning

ObjectiveThe incidence of cardiovascular diseases (CVD) is rising rapidly worldwide. Some forms of CVD, such as stroke and heart attack, are more common among patients with certain conditions. Atherosclerosis development is a major factor underlying cardiovascular events, such as heart attack and stroke, and its early detection may prevent such events. Ultrasound imaging of carotid arteries is a useful method for diagnosis of atherosclerotic plaques; however, an automated method to classify atherosclerotic plaques for evaluation of early-stage CVD is needed. Here, we propose an automated method for classification of high-risk atherosclerotic plaque ultrasound images. MethodsFive deep learning (DL) models (VGG16, ResNet-50, GoogLeNet, XceptionNet, and SqueezeNet) were used for automated classification and the results compared with those of a machine learning (ML)-based technique, involving extraction of 23 texture features from ultrasound images and classification using a Support Vector Machine classifier. To enhance model interpretability, output gradient-weighted convolutional activation maps (GradCAMs) were generated and overlayed on original images. ResultsA series of indices, including accuracy, sensitivity, specificity, F1-score, Cohen-kappa index, and area under the curve values, were calculated to evaluate model performance. GradCAM output images allowed visualization of the most significant ultrasound image regions. The GoogLeNet model yielded the highest accuracy (98.20%). ConclusionML models may be also suitable for applications requiring low computational resource. Further, DL models could be more completely automated than ML models.

Extended aperture image reconstruction for plane-wave imaging

B-mode images undergo degradation in the boundary region because of the limited number of elements in the ultrasound probe. Herein, a deep learning-based extended aperture image reconstruction method is proposed to reconstruct a B-mode image with an enhanced boundary region. The proposed network can reconstruct an image using pre-beamformed raw data received from the half-aperture of the probe. To generate a high-quality training target without degradation in the boundary region, the target data were acquired using the full-aperture. Training data were acquired from an experimental study using a tissue-mimicking phantom, vascular phantom, and simulation of random point scatterers. Compared with plane-wave images from delay and sum beamforming, the proposed extended aperture image reconstruction method achieves improvement at the boundary region in terms of the multi-scale structure of similarity and peak signal-to-noise ratio by 8% and 4.10 dB in resolution evaluation phantom, 7% and 3.15 dB in contrast speckle phantom, and 5% and 3 dB in in vivo study of carotid artery imaging. The findings in this study prove the feasibility of a deep learning-based extended aperture image reconstruction method for boundary region improvement.

Carotid stenting for treatment of Carotid web which caused stroke: a report of 3 cases

ABSTRACT Introduction: Carotid web is a focal variant of fibromuscular dysplasia, creating a septal in the carotid bulb, from which thrombosis can occur and may cause stroke. It is a rare disease and there is not enough evidence to establish optimal treatment. Case report: We report on three patients with carotid web - related strokes: two males (ages 57 and 68) and one female (age 43). Despite optimal medical treatment, both male patients experienced early recurrent strokes, while the female patient presented with a first - time stroke. All three patients underwent carotid stenting, and during a follow - up period of up to 3 years, there were no procedure - related complications or recurrent stroke events. Conclusion: Carotid web is a cause of ischemic stroke with a high risk of recurrence. Carotid stenting is a safe and effective option for long - term prevention of stroke recurrence. There fore, carotid artery imaging should be carefully evaluated, with attention paid to carotid web in patients with cryptogenic stroke.

Preprocessing techniques with medical ultrasound common carotid artery images

Preprocessing techniques with medical ultrasound common carotid artery images

Enhancement of Ultrasound B-Mode Image Quality Using Nonlinear Filtered-Multiply-and-Sum Compounding for Improved Carotid Artery Segmentation.

In ultrasound B-mode imaging, the axial resolution (AR) is commonly determined by the duration or bandwidth of an excitation signal. A shorter-duration pulse will produce better resolution compared to a longer one but with compromised penetration depth. Instead of relying on the pulse duration or bandwidth to improve the AR, an alternative method termed filtered multiply and sum (FMAS) has been introduced in our previous work. For spatial-compounding, FMAS uses the autocorrelation technique as used in filtered-delay multiply and sum (FDMAS), instead of conventional averaging. FMAS enables a higher frame rate and less computational complexity than conventional plane-wave compound imaging beamformed with delay and sum (DAS) and FDMAS. Moreover, it can provide an improved contrast ratio and AR. In previous work, no explanation was given on how FMAS was able to improve the AR. Thus, in this work, we discuss in detail the theory behind the proposed FMAS algorithm and how it is able to improve the spatial resolution mainly in the axial direction. Simulations, experimental phantom measurements and in vivo studies were conducted to benchmark the performance of the proposed method. We also demonstrate how the suggested new algorithm may be used in a practical biomedical imaging application. The balloon snake active contour segmentation technique was applied to the ultrasound B-mode image of a common carotid artery produced with FMAS. The suggested method is capable of reducing the number of iterations for the snake to settle on the region-of-interest contour, accelerating the segmentation process.

Deep Null Space Learning Improves Dataset Recovery for High Frame Rate Synthetic Transmit Aperture Imaging.

Synthetic transmit aperture (STA) imaging benefits from the two-way dynamic focusing to achieve optimal lateral resolution and contrast resolution in the full field of view, at the cost of low frame rate (FR) and low signal-to-noise ratio (SNR). In our previous studies, compressed sensing based synthetic transmit aperture (CS-STA) and minimal l2-norm least squares (LS-STA) methods were proposed to recover the complete STA dataset from fewer Hadamard-encoded plane wave (PW) transmissions. Results demonstrated that, compared with STA imaging, CS/LS-STA can maintain the high resolution of STA in the full field of view and improve the contrast in the deep region with increased FR. However, these methods would introduce errors to the recovered STA datasets and subsequently produce severe artifacts to the beamformed images, especially in the shallow region. Recently, we discovered that the theoretical explanation for the error introduced in the LS-STA-based recovery is that the LS-STA method neglects the null space component of the real STA dataset. To deal with this problem, we propose to train a convolutional neural network under the null space learning framework (CNN-Null) to estimate the missing null space component) for high-accuracy recovery of the STA dataset from fewer Hadamard-encoded PW transmissions. The mapping between the low-quality STA dataset (i.e., the range space component of the real STA dataset recovered using the LS-STA method) and the missing null space component of the real STA dataset was learned by the network with the high-quality STA dataset (obtained using full Hadamard-encoded STA imaging, HE-STA) as training labels. The performance of the proposed CNN-Null method was compared with the baseline LS-STA, conventional STA, and HE-STA methods, in terms of visual quality, normalized root-mean-square error (NRMSE), generalized contrast-to-noise ratio (gCNR), and lateral full width at half maximum (FWHM). The results demonstrate that the proposed method can greatly improve the recovery accuracy of the STA datasets (lower NRMSE) and therefore effectively suppress the artifacts presented in the images (especially in the shallow region) obtained using the LS-STA method (with a gCNR improvement of 0.4 in the cross-sectional carotid artery images). In addition, the proposed method can maintain the high lateral resolution of STA with fewer (as low as 16) PW transmissions, as LS-STA does.

Remnant Cholesterol and Common Carotid Artery Intima-Media Thickness in Community Population with Normal Low-Density Lipoprotein Cholesterol

Introduction: Remnant cholesterol is a risk factor for cardiovascular disease, especially when low-density lipoprotein cholesterol (LDL-C) levels are normal. However, there are few studies on the relationship between remnant cholesterol and subclinical atherosclerosis. Common carotid artery intima-media thickness (cIMT) is an imaging marker of subclinical atherosclerosis. This study aimed to investigate the relationship between remnant cholesterol and cIMT in a community population with normal LDL-C. Methods: This study is a retrospective analysis; 1,101 community population with available carotid artery imaging and fasting lipid data with LDL-C <4.1 mmol/L were included in this analysis. Remnant cholesterol was calculated as total cholesterol minus LDL-C minus high-density lipoprotein cholesterol. Abnormal cIMT was defined as maximum cIMT value ≥1 mm. Logistic regression was used to assess the relationships between remnant cholesterol levels and abnormal cIMT. Results: As the remnant cholesterol level increased from the lowest to the highest quartile, the rate of abnormal cIMT increased from 24.5% to 38.6% (p trend <0.001) in the community population with normal LDL-C level. In the unadjusted model, the odds ratios (ORs, 95% confidence intervals) in the highest quartile group were 1.937 (1.338–2.803) for abnormal cIMT compared with the lowest quartile. The multivariable-adjusted ORs (95% confidence intervals) for the highest versus lowest quartile of remnant cholesterol were 2.132 (1.420–3.202) for abnormal cIMT. Conclusion: Elevated fasting remnant cholesterol levels were positively associated with abnormal cIMT in community population with normal LDL-C levels. Remnant cholesterol may be an important indicator of risk stratification in community population with normal LDL-C level.