Carotid artery lumen segmentation in 3D free-hand ultrasound images using surface graph cuts

We present a new approach for automated segmentation of the carotid lumen bifurcation from 3D free-hand ultrasound using a 3D surface graph cut method. The method requires only the manual selection of single seed points in the internal, external, and common carotid arteries. Subsequently, the centerline between these points is automatically traced, and the optimal lumen surface is found around the centerline using graph cuts. To refine the result, the latter process was iterated. The method was tested on twelve carotid arteries from six subjects including three patients with a moderate carotid artery stenosis. Our method successfully segmented the lumen in all cases. We obtained an average dice overlap with respect to a manual segmentation of 84% for healthy volunteers. For the patient data, we obtained a dice overlap of 66.7%

New 3-Dimensional Volumetric Ultrasound Method for Accurate Quantification of Atherosclerotic Plaque Volume.

Carotid and femoral plaque burden is a recognized biomarker of cardiovascular disease risk. A new electronic-sweep 3-dimensional (3D)-matrix transducer method can improve the functionality and image quality of vascular ultrasound atherosclerosis imaging. This study aimed to validate this method for plaque volume measurement in early and intermediate-advanced plaques in the carotid and femoral territories. Plaque volumes were measured ex vivo in pig carotid and femoral artery specimens by 3-dimensional vascular ultrasound (3DVUS) using a 3D-matrix (electronic-sweep) transducer and its associated 3D plaque quantification software, and were compared with gold-standard histology. To test the clinical feasibility and accuracy of the 3D-matrix transducer, an experiment was conducted in intermediate-high risk individuals with carotid and femoral atherosclerosis. The results were compared with those obtained using the previously validated mechanical-sweep 3D transducer and established 2-dimensional (2D)-based plaque quantification software. In the ex vivo study, the authors assessed 19 atherosclerotic plaques (plaque volume, 0.76 µL-56.30 μL), finding strong agreement between measurements with the 3D-matrix transducer and the histological gold-standard (intraclass correlation coefficient [ICC]: 0.992; [95% CI: 0.978-0.997]). In the clinical analysis of 20 patients (mean age 74.6 ± 4.45 years; 40% men), the authors found 64 (36 carotid and 28 femoral) of 80 scanned territories with atherosclerosis (measured atherosclerotic volume, 10 μL-859 μL). There was strong agreement between measurements made from electronic-sweep and mechanical-sweep 3DVUS transducers (ICC: 0.997 [95% CI: 0.995-0.998]). Agreement was also high between plaque volumes estimated by the 2D and 3D plaque quantification software applications (ICC: 0.999 [95% CI: 0.998-0.999]). Analysis time was significantly shorter with the 3D plaque quantification software than with the 2D multislice approach with a mean time reduction of 46%. 3DVUS using new matrix transducer technology, together with improved 3D plaque quantification software, simplifies the accurate volume measurement of early (small) and intermediate-advanced plaques located in carotid and femoral arteries.This study was partially funded by grants from the Ministerio de Economia, Industria y Competividad (MEIC) with cofunding from the European Regional Development Fund (ERDF) (SAF2016-75580-R to Dr Bentzon) and (BES-2016-076633 to Dr Nogales). Research funding was also received from the Instituto de Salud Carlos III Spain (PIE16/ 00021 to Drs Bueno and Fuster). The CNIC is supported by the Min- isterio de Ciencia, Innovacion y Universidades (MICINN) and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (CEX2020-001041-S). This study forms part of a Master Research Agreement between the CNIC and Philips Healthcare. Drs Sánchez- González, Entrekin, and Collet-Billon are employees of Philips Healthcare. All other authors have reported that they have no re- lationships to disclose related to the contents of this paper.S

Bimodal automated carotid ultrasound segmentation using geometrically constrained deep neural networks

For asymptomatic patients suffering from carotid stenosis, the assessment of plaque morphology is an important clinical task which allows monitoring of the risk of plaque rupture and future incidents of stroke. Ultrasound Imaging provides a safe and non-invasive modality for this, and the segmentation of media-adventitia boundaries and lumen-intima boundaries of the Carotid artery form an essential part in this monitoring process. In this paper, we propose a novel Deep Neural Network as a fully automated segmentation tool, and its application in delineating both the media-adventitia boundary and the lumen-intima boundary. We develop a new geometrically constrained objective function as part of the Network's Stochastic Gradient Descent optimisation, thus tuning it to the problem at hand. Furthermore, we also apply a bimodal fusion of amplitude and phase congruency data proposed by us in previous work, as an input to the network, as the latter provides an intensity-invariant data source to the network. We finally report the segmentation performance of the network on transverse sections of the carotid. Tests are carried out on an augmented dataset of 81,000 images, and the results are compared to other studies by reporting the DICE coefficient of similarity, modified Hausdorff Distance, sensitivity and specificity. Our proposed modification is shown to yield improved results on the standard network over this larger dataset, with the advantage of it being fully automated. We conclude that Deep Neural Networks provide a reliable trained manner in which carotid ultrasound images may be automatically segmented, using amplitude data and intensity invariant phase congruency maps as a data source

Simulated hemodynamics in human carotid bifurcation based on Doppler ultrasound data

Background: Atherosclerotic lesions commonly develop at arterial branch sites. Noninvasive carotid artery ultrasound is a well-established and effective method which allows real-time images and measurements of flow velocities. We aimed to develop a methodology for patient-specific computational 3D reconstruction and blood flow simulation based on ultrasound image data.Material and Methods: Subject-specific studies based on the acquisition of a set of longitudinal and sequential cross-sectional ultrasound images and Doppler velocity measurements at common carotid artery (CCA) bifurcation were performed at a university hospital. A developed simulation code of blood flow by the finite element method (FEM) that includes an adequate structured meshing of the common carotid artery bifurcation was used to investigate local flow biomechanics.Results: Hemodynamic simulations of CCA bifurcations for six individuals were analysed. Comparing pairs (Doppler, FEM) of velocity values, Lin's concordance correlation coefficient analysis demonstrated an almost perfect strength of agreement (c = 0.9911), in patients with different degrees of internal carotid artery (ICA) stenosis. Numerical simulations were able to capture areas of low wall shear stress correlated with stagnation zones.Conclusions: Simulated hemodynamic parameters can reproduce the disturbed flow conditions at the bifurcation of CCA and proximal ICA, which play an important role in the development of local atherosclerotic plaques. This novel technology might help to understand the relationship between hemodynamic environment and carotid wall lesions, and have a future impact in carotid stenosis diagnosis and management

Nonrigid Registration of 3-Dimensional Images of the Carotid Arteries

Atherosclerosis at the carotid bifurcation can result in cerebral emboli, which in turn can block the blood supply to the brain causing ischemic strokes. Non-invasive imaging tools that characterize arterial wall, and atherosclerotic plaque structure and composition may help to determine the factors, which lead to the development of unstable lesions, and identify patients at risk of plaque disruption. Registration of 3D ultrasound (US) images of carotid plaque obtained at different time points, and with Magnetic Resonance (MR) images are required for monitoring of plaque changes in volume and surface morphology, and combining the complementary information of the two modalities for better understanding of factors that define plaque vulnerability. These registration techniques should be nonrigid, to remove deformations caused by bending and torsion in the neck during image acquisition sessions. The high degrees of freedom and large number of parameters associated with nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, high computational complexity, and low reliability. Thus, we used a “twisting and bending” model with only six parameters to model the natural movement of the neck for nonrigid registration. We calculated the Mean Registration Error (MRE) between the segmented vessel surfaces in the target and the registered images using the distance between “matched points” to evaluate registration results. We registered 3D US carotid images acquired at different head positions to simulate images acquired at different times, and obtained an average MRE of 0.8±0.3mm for nonrigid registration. We registered 3D US and MR carotid images at field strengths, 1.5T and 3.0T, of the same subject acquired on the same day, and obtained an average MRE of 1.4±0.3mm for 1.5T and 1.5±0.4mm for 3.0T, using nonrigid registration. Furthermore, we showed that the error metric used here was not significantly different from the widely accepted Target Registration Error (TRE)

Advances in the development of an imaging device for plaque measurement in the area of the carotid artery

This paper describes the advances in the development and subsequent testing of an imaging device for three-dimensional ultrasound measurement of atherosclerotic plaque in the carotid artery. The embolization from the atherosclerotic carotid plaque is one of the most common causes of ischemic stroke and, therefore, we consider the measurement of the plaque as extremely important. The paper describes the proposed hardware for enhancing the standard ultrasonic probe to provide a possibility of accurate probe positioning and synchronization with the cardiac activity, allowing the precise plaque measurements that were impossible with the standard equipment. The synchronization signal is derived from the output signal of the patient monitor (electrocardiogram (ECG)), processed by a microcontroller-based system, generating the control commands for the linear motion moving the probe. The controlling algorithm synchronizes the movement with the ECG waveform to obtain clear images not disturbed by the heart activity.Web of Science28235935

Quantification of carotid vessel wall and plaque thickness change using 3D ultrasound images

Quantitative measurements of carotid plaque burden progression or regression are important in monitoring patients and in evaluation of new treatment options. 3D ultrasound (US) has been used to monitor the progression or regression of carotid artery plaques. This paper reports on the development and application of a method used to analyze changes in carotid plaque morphology from 3D US. The technique used is evaluated using manual segmentations of the arterial wall and lumen from 3D US images acquired in two imaging sessions. To reduce the effect of segmentation variability, segmentation was performed five times each for the wall and lumen. The mean wall and lumen surfaces, computed from this set of five segmentations, were matched on a point-by-point basis, and the distance between each pair of corresponding points served as an estimate of the combined thickness of the plaque, intima, and media (vessel-wall-plus-plaque thickness or VWT). The VWT maps associated with the first and the second US images were compared and the differences of VWT were obtained at each vertex. The 3D VWT and VWT-Change maps may provide important information for evaluating the location of plaque progression in relation to the localized disturbances of flow pattern, such as oscillatory shear, and regression in response to medical treatments

Lumen segmentation in magnetic resonance images of the carotid artery

Investigation of the carotid artery plays an important role in the diagnosis of cerebrovascular events. Segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images is the first step towards evaluating any possible cardiovascular diseases like atherosclerosis. However, the automatic segmentation of the lumen is still a challenge due to the low quality of the images and the presence of other elements such as stenosis and malformations that compromise the accuracy of the results. In this article, a method to identify the location of the lumen without user interaction is presented. The proposed method uses the modified mean roundness to calculate the circularity index of the regions identified by the K-means algorithm and return the one with the maximum value, i.e. the potential lumen region. Then, an active contour is employed to refine the boundary of this region. The method achieved an average Dice coefficient of 0.78 +/- 0.14 and 0.61 +/- 0.21 in 181 3D-T1-weighted and 181 proton density-weighted MR images, respectively. The results show that this method is promising for the correct identification and location of the lumen even in images corrupted by noise