B-mode Images Research Articles

ISUOG Practice Guidelines (updated): fetal cardiac screening.

ISUOG Practice Guidelines (updated): fetal cardiac screening.

Feasibility and proof of concept of a proprietary non-contact ablation system with low intensity collimated ultrasound

Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): Heailum Medical Inc. Background Utilization of collimated acoustic energy transition as an ablation energy source has the advantage of propagation through blood with negligible absorption. This allows delivery of non-contact, directional and precise ablation lesions to cardiac tissue. In addition, with dual mode ultrasound technology real-time monitoring of the tissue is possible during ablation. Aim To evaluate a proprietary ultrasound-based ablation system in swine and define the characteristics of the isolated ablation lesions and lines performed in-vivo. Methods In female large white swines, bilateral thigh muscle prep ablations were performed using different time and energy ablation parameters while tip to tissue distance measured with the imaging B-mode and set to 10mm. Lesions were analysed for maximal depth and width. Additional assessment for contiguous linear ablation was performed in the thigh muscle, SVC and within the coronary sinus with the transducer rotated to the endocardial direction. Tissue was fixed in formalin and gross pathological examination with lesion measurement was performed. Results 36 distinct ablation lesions were performed in the thigh prep model. No steam pops were observed for any of the lesions. Mean necrotic lesion depth was 5.35 ± 1.5mm, with increased time with greater influence on dimensions compared to small changes in energy delivered (Figure 1). Reversible damage influenced additional 29% of tissue depth, while 55% additional tissue width was reversible. Linear ablation performed at 2.5mm inter-lesion distance showed contiguous lines, with transmural effect in both SVC and coronary sinus. Conclusions A novel ultrasound based catheter ablation has the ability for non-contact effective ablation in cardiac tissue with directional and tailored energy selection to achieve transmural atrial ablation. Additional in-vivo experimentation will allow refinement of this tool for both isolated lesions and linear ablation while enabling tissue visualization.

Skeletal Muscle Assessment Using Quantitative Ultrasound: A Narrative Review.

Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operator and/or US system, and a portion of the potentially useful information carried by raw sonographic data is discarded in image formation for routine qualitative US. Quantitative ultrasound (QUS) methods provide analysis of the raw or post-processed data, revealing additional information about normal tissue structure and disease status. There are four QUS categories that can be used on muscle and are important to review. First, quantitative data derived from B-mode images can help determine the macrostructural anatomy and microstructural morphology of muscle tissues. Second, US elastography can provide information about muscle elasticity or stiffness through strain elastography or shear wave elastography (SWE). Strain elastography measures the induced tissue strain caused either by internal or external compression by tracking tissue displacement with detectable speckle in B-mode images of the examined tissue. SWE measures the speed of induced shear waves traveling through the tissue to estimate the tissue elasticity. These shear waves may be produced using external mechanical vibrations or internal "push pulse" ultrasound stimuli. Third, raw radiofrequency signal analyses provide estimates of fundamental tissue parameters, such as the speed of sound, attenuation coefficient, and backscatter coefficient, which correspond to information about muscle tissue microstructure and composition. Lastly, envelope statistical analyses apply various probability distributions to estimate the number density of scatterers and quantify coherent to incoherent signals, thus providing information about microstructural properties of muscle tissue. This review will examine these QUS techniques, published results on QUS evaluation of skeletal muscles, and the strengths and limitations of QUS in skeletal muscle analysis.

Deep Learning for Ultrasound Speed-of-Sound Reconstruction: Impacts of Training Data Diversity on Stability and Robustness

Ultrasound b-mode imaging is a qualitative approach and diagnostic quality strongly depends on operators’ training and experience. Quantitative approaches can provide information about tissue properties; therefore, can be used for identifying various tissue types, e.g., speed-of-sound in the tissue can be used as a biomarker for tissue malignancy, especially in breast imaging. Recent studies showed the possibility of speed-of-sound reconstruction using deep neural networks that are fully trained on simulated data. However, because of the ever-present domain shift between simulated and measured data, the stability and performance of these models in real setups are still under debate. In prior works, for training data generation, tissue structures were modeled as simplified geometrical structures which does not reflect the complexity of the real tissues. In this study, we proposed a new simulation setup for training data generation based on Tomosynthesis images. We combined our approach with the simplified geometrical model and investigated the impacts of training data diversity on the stability and robustness of an existing network architecture. We studied the sensitivity of the trained network to different simulation parameters, e.g., echogenicity, number of scatterers, noise, and geometry. We showed that the network trained with the joint set of data is more stable on out-of-domain simulated data as well as measured phantom data.

Robust tip localization under continuous spatial and temporal constraints during 2D ultrasound-guided needle puncture.

During ultrasound-guided (US-guided) needle puncture for minimally invasive procedures, automated needle tip localization can help clinicians capture small tips in US images easily and precisely, providing them with obvious tip indicators on the screen and bringing them more confidence during the procedures. However, automated needle tip localization in US images is challenging due to serious interferences arising from all kinds of echoes. We propose a method that localizes needle tips under continuous spatial and temporal constraints in the real-time US frame stream. A temporal constraint is firstly acquired by detecting translational tip motion in motion-enhanced US images with a deep learning-based (DL-based) detector. A spatial constraint and candidate tip locations are obtained by detecting needle shafts and tips in the raw grayscale B-mode images with another DL-based detector. To provide continuous constraints, estimated tip velocity from acquired temporal constraint is used to predict tip locations in frames where no temporal or spatial constraint is detected. Finally, tip coordinates are precisely localized among candidate tips under the spatial and temporal constraints. Experimental results evaluated on 1121 US images from porcine organ punctures, and 895 images from human thyroid punctures demonstrate that the proposed method is effective and efficient, surpassing existing methods. On porcine organ data, a 97.2% recall rate and a 91.9% precision rate on tip detection and 0.88 ± 0.70mm root-mean-square error (RMSE) on tip localization were achieved. On the human thyroid data, which was not involved in the training, 86.5% recall, 84.3% precision and 0.92 ± 0.78mm RMSE were achieved separately. The running speed of 14.5 frames per second was achieved only using a CPU. The proposed method provides a more reliable solution for automated needle tip localization during US-guided needle puncture, being more robust to interferences. Fast running speed leads to its practicability in the real-time US stream.

Randomized channel subsampling method for efficient ultrafast ultrasound imaging

Emerging as a novel modality with high spatiotemporal sensitivity, ultrafast ultrasound imaging has been well established and incorporated into clinical apparatus. However, such a mode typically requires large data acquisitions, with more than thousands of frames per second within a relatively long period, which poses high demands on real-time storage and processing hardware. Herein, an image reconstruction approach based on randomized channel subsampling is presented, which significantly reduces the amount of data acquisition while maintaining imaging performance. In vivo datasets from rats were used to evaluate the performance of the proposed method in B-mode imaging, ultrafast Doppler imaging, and super-resolution ultrasound localization microscopy (ULM) under different subsampling conditions. Following a thorough comparison of the contrast-to-noise ratio, signal-to-noise ratio, and visibility of the ultrafast Doppler based small-vessel imaging, the resolution and saturation of ULM imaging were also investigated under different subsampling conditions. The feasibility of the proposed method was demonstrated in task-based functional ultrasound (fUS) imaging with whisker stimulation. A comparison between the results of fUS based on introduced randomized channel subsampling and conventional fUS was also conducted to evaluate the subsampling effects on reconstruction accuracy and cerebral change detection sensitivity.

High-quality Ultrafast Power Doppler Imaging Based on Spatial Angular Coherence Factor.

The morphological and hemodynamic changes of microvessels are demonstrated to be related to the diseased conditions in tissues. Ultrafast power Doppler imaging (uPDI) is a novel modality with a significantly increased Doppler sensitivity, benefiting from the ultrahigh frame rate plane wave imaging and advanced clutter filtering. However, unfocused plane wave transmission often leads to a low imaging quality, which degrades the subsequent microvascular visualization in power Doppler imaging. Coherence factor (CF) based adaptive beamformers have been widely studied in conventional B-mode imaging. In this study, we propose a spatial and angular coherence factor (SACF) beamformer for improved uPDI (SACF-uPDI) by calculating the spatial coherence factor across apertures and the angular coherence factor across transmit angles, respectively. To identify the superiority of SACF-uPDI, simulations, in vivo contrast-enhanced rat kidney, and in vivo contrast-free human neonatal brain studies were conducted. Results demonstrate that SACF-uPDI can effectively enhance contrast and resolution, and suppress background noise simultaneously, compared with conventional uPDI methods based on DAS (DAS-uPDI) and CF (CF-uPDI). In the simulations, SACF-uPDI can improve the lateral and axial resolutions compared with those of DAS-uPDI, from 176 μm to 108 μm of lateral resolution, and 111 μm to 74 μm of axial resolution. In the in vivo contrast-enhanced experiments, SACF achieves 15.14- and 5.6-dB higher contrast-to-noise ratio (CNR), 15.25- and 3.68-dB lower noise power, and 240- and 15-μm narrower full-width at half-maximum (FWHM) than DAS-uPDI and CF-uPDI, respectively. In the in vivo contrast-free experiments, SACF achieves 6.11- and 1.09-dB higher CNR, 11.93- and 4.01-dB lower noise power, and 528- and 160-μm narrower FWHM than DAS-uPDI and CF-uPDI, respectively. In conclusion, the proposed SACF-uPDI method can efficiently improve the microvascular imaging quality and has the potential to facilitate clinical applications.

A Novel Spectral Index for Tracking Preload Change from a Wireless, Wearable Doppler Ultrasound.

A wireless, wearable Doppler ultrasound offers a new paradigm for linking physiology to resuscitation medicine. To this end, the image analysis of simultaneously-acquired venous and arterial Doppler spectrograms attained by wearable ultrasound represents a new source of hemodynamic data. Previous investigators have reported a direct relationship between the central venous pressure (CVP) and the ratio of the internal jugular-to-common carotid artery diameters. Because Doppler power is directly related to the number of red cell scatterers within a vessel, we hypothesized that (1) the ratio of internal jugular-to-carotid artery Doppler power (V/APOWER) would be a surrogate for the ratio of the vascular areas of these two vessels and (2) the V/APOWER would track the anticipated CVP change during simulated hemorrhage and resuscitation. To illustrate this proof-of-principle, we compared the change in V/APOWER obtained via a wireless, wearable Doppler ultrasound to B-mode ultrasound images during a head-down tilt. Additionally, we elucidated the change in the V/APOWER during simulated hemorrhage and transfusion via lower body negative pressure (LBNP) and release. With these Interesting Images, we show that the Doppler V/APOWER ratio qualitatively tracks anticipated changes in CVP (e.g., cardiac preload) which is promising for both diagnosis and management of hemodynamic unrest.

Binary classification of non-specific low back pain condition based on the combination of B-mode ultrasound and shear wave elastography at multiple sites.

Introduction: Low back pain (LBP) is a prevalent and complex condition that poses significant medical, social, and economic burdens worldwide. The accurate and timely assessment and diagnosis of LBP, particularly non-specific LBP (NSLBP), are crucial to developing effective interventions and treatments for LBP patients. In this study, we aimed to investigate the potential of combining B-mode ultrasound image features with shear wave elastography (SWE) features to improve the classification of NSLBP patients. Methods: We recruited 52 subjects with NSLBP from the University of Hong Kong-Shenzhen Hospital and collected B-mode ultrasound images and SWE data from multiple sites. The Visual Analogue Scale (VAS) was used as the ground truth to classify NSLBP patients. We extracted and selected features from the data and employed a support vector machine (SVM) model to classify NSLBP patients. The performance of the SVM model was evaluated using five-fold cross-validation and the accuracy, precision, and sensitivity were calculated. Results: We obtained an optimal feature set of 48 features, among which the SWE elasticity feature had the most significant contribution to the classification task. The SVM model achieved an accuracy, precision, and sensitivity of 0.85, 0.89, and 0.86, respectively, which were higher than the previously reported values of MRI. Discussion: In this study, we aimed to investigate the potential of combining B-mode ultrasound image features with shear wave elastography (SWE) features to improve the classification of non-specific low back pain (NSLBP) patients. Our results showed that combining B-mode ultrasound image features with SWE features and employing an SVM model can improve the automatic classification of NSLBP patients. Our findings also suggest that the SWE elasticity feature is a crucial factor in classifying NSLBP patients, and the proposed method can identify the important site and position of the muscle in the NSLBP classification task.

The influence of daily exercise on muscle echo intensity and stiffness in young women.

This study aimed to investigate the effect of daily exercise on skeletal muscle function, size, and quality in young women. Twenty-six young women participated in this study, categorized into daily exercise and non-exercise groups. The exercise group had performed exercise or training three times a week for more than six months. Knee extension and flexion, plantar flexion, and dorsiflexion peak torques were measured for muscle function. B-mode ultrasound images were taken from the thigh and calf, and muscle thickness and echo intensity were measured in the vastus lateralis and medial gastrocnemius. Shear modulus at different joint angles of the knee (0° [full extended], 40°, and 90°) and ankle (40 °plantarflexion, 0° [neutral], and 10 °dorsiflexion) was measured from the vastus lateralis and medial gastrocnemius to determine muscle stiffness. Peak torque and echo intensity did not significantly differ between the exercise and non-exercise groups. Shear modulus in the medial gastrocnemius at 10° dorsiflexion was significantly lower in the exercise group compared with the non-exercise group (34.2 ± 7.7 vs. 46.5 ± 13.1 kPa, P < 0.05). These results suggest that daily exercise and training could affect muscle stiffness, but do not lead to an increase in muscle function.

A Method for High-Frequency Mechanical Scanning Ultrasonic Flow Imaging with Motion Compensation.

Mechanical scanning with a single transducer is an alternative method for high-frequency ultrasound imaging, which is simple in structure, convenient to implement, and low in cost. However, traditional mechanical scanning ultrasonic imaging introduces additional Doppler shift due to the movement of the transducer, which brings a challenge for blood velocity measurement. An improved mechanical scanning system for high-frequency ultrasonic color Doppler flow imaging is developed in this paper. The mechanical scanning system has a scanning stroke range of 15 mm, a maximum scanning speed of 168 mm/s, and an imaging depth of 20 mm. Since the mechanical scanning of the system is not in uniform motion, motion compensation was applied to achieve high-precision imaging both in B-mode and Doppler mode. The experiment results show that the system imaging resolution can reach about 140 μm in B-mode imaging, the relative velocity error is less than 5% in color Doppler flow imaging at different flow rates, and the CNR of power Doppler flow imaging of this system is greater than 15 dB. The proposed mechanical scanning imaging system can achieve high-resolution structure imaging and color flow imaging, which can provide more diagnostic information for the practical diagnosis and broaden the application range of mechanical scanning ultrasound imaging.

Improved right ventricular strain estimation in rats using anisotropic diffusion filtering.

Calculating cardiac strains through speckle tracking echocardiography (STE) has shown promise as prognostic markers linked to functional indices and disease outcomes. However, the presence of acoustic shadowing often challenges the accuracy of STE in small animals such as rodents. The shadowing arises due to the complex anatomy of rodents, with operator dexterity playing a significant role in image quality. The effects of the semi-transparent shadows are further exacerbated in right ventricular (RV) imaging due to the thinness and rapid motion of the RV free wall (RVFW). The movement of the RVFW across the shadows distorts speckle tracking and produces unnatural and non-physical strains. The objective of this study was to minimize the effects of shadowing on STE by distinguishing "out-of-shadow" motion and identifying speckles in and out of shadow. Parasternal 2D echocardiography was performed, and short-axis B-mode (SA) images of the RVFW were acquired for a rodent model of pulmonary hypertension (n = 1). Following image acquisition, a denoising algorithm using edge-enhancing anisotropic diffusion (EED) was implemented, and the ensuing effects on strain analysis were visualized using a custom STE pipeline. Speckles in the shadowed regions were identified through a correlation between the filtered image and the original acquisition. Thus, pixel movement across the boundary was identified by enhancing the distinction between the shadows and the cardiac wall, and non-physical strains were suppressed. The strains obtained through STE showed expected patterns with enhanced circumferential contractions in the central region of the RVFW in contrast to smaller and nearly uniform strains derived from the unprocessed images.

Extravascular Ultrasound (EVUS) to Assess the Results of Peripheral Endovascular Procedures

Contrast arteriography (CA) is considered the gold standard to evaluate any phase in peripheral arterial disease (PAD) interventions, from diagnostics to final results. Nevertheless, duplex ultrasonography (DUS) mostly used for the pre/postoperative phase and follow-up control, could be a potential intraoperative adjunctive imaging tool to assess the effects of endovascular revascularization in patients with iliac and femoropopliteal lesions. The PAD "duplex-assisted" protocol includes a preoperative DUS control followed by an intraoperative and a postoperative control. The most important parameters are pulsed doppler spectral analysis and waveform changes, which are impossible to detect with intravascular ultrasound (IVUS). By using a similar acronym, the intraoperative DUS has been previously described as extravascular ultrasound (EVUS). B-mode imaging, color flow, and peak systolic velocity (PSV) are considered. EVUS could be very useful to evaluate the effects of endovascular treatment, mainly in cases of unclear CAs, severe calcifications and/or dissections. In the context of the "leaving nothing behind" strategy, EVUS can drive the physician to evaluate the absence of flow-limiting dissections and decide which target lesion should be treated with antirestenotic therapy, further vessel preparation, or stenting. The EVUS protocol could be a safe and feasible option to improve the completion assessment of endovascular PAD treatment. A better ultrasound waveform is a sign of improved luminal gain and compliance, which is extremely important to finalize the results of new peripheral device technology, such as intravascular lithotripsy.

Advanced Fourier migration for Plane-Wave vector flow imaging

Ultrafast ultrasound imaging modalities have been studied extensively in the ultrasound community. It breaks the compromise between the frame rate and the region of interest by imaging the whole medium with wide unfocused waves. Continuously available data allow monitoring fast transient dynamics at hundreds to thousands of frames per second. This feature enables a more accurate and robust velocity estimation in vector flow imaging (VFI). On the other hand, the huge amount of data and real-time processing demands are still challenging in VFI. A solution is to provide a more efficient beamforming approach with smaller computation complexity than the conventional time-domain beamformer like delay-and-sum (DAS). Fourier-domain beamformers are shown to be more computationally efficient and can provide equally good image quality as DAS. However, previous studies generally focus on B-mode imaging. In this study, we propose a new framework for VFI which is based on two advanced Fourier migration methods, namely, slant stack migration (SSM) and ultrasound Fourier slice beamform (UFSB). By carefully modifying the beamforming parameters, we successfully apply the cross-beam technique within the Fourier beamformers. The proposed Fourier-based VFI is validated in simulation studies, in vitro, and in vivo experiments. The velocity estimation is evaluated via bias and standard deviation and the results are compared with conventional time-domain VFI using the DAS beamformer. In the simulation, the bias is 6.4%, −6.2%, and 5.7%, and the standard deviation is 4.3%, 2.4%, and 3.9% for DAS, UFSB, and SSM, respectively. In vitro studies reveal a bias of 4.5%, −5.3%, and 4.3% and a standard deviation of 3.5%, 1.3%, and 1.6% from DAS, UFSB, and SSM, respectively. The in vivo imaging of the basilic vein and femoral bifurcation also generate similar results using all three methods. With the proposed Fourier beamformers, the computation time can be shortened by up to 9 times and 14 times using UFSB and SSM.

Advantages and drawbacks associated with the use of endosonography in sarcoidosis

Introduction Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a real-time, minimally invasive procedure for sampling intrathoracic lymph nodes. Herein, we discuss EBUS-guided procedures, their benefits, and drawbacks in diagnosing sarcoidosis. Areas covered We first describe the utility of various endosonographic imaging techniques like B-mode, elastography, and doppler imaging. We then review the diagnostic yield and safety of EBUS-TBNA and compare it with the other available diagnostic modalities. Subsequently, we discuss the technical aspects of EBUS-TBNA influencing the diagnostic yield. Recent advances in EBUS-guided diagnostics like EBUS-guided intranodal forceps biopsy (EBUS-IFB) and EBUS-guided transbronchial mediastinal cryobiopsy (EBMC) are reviewed. Finally, we summarize the advantages and disadvantages associated with EBUS-TBNA in sarcoidosis and provide an expert opinion on the optimal use of this procedure in patients with suspected sarcoidosis. Expert opinion EBUS-TBNA is a minimally invasive, safe procedure with a good diagnostic yield, and should be the preferred diagnostic modality for sampling intrathoracic lymph nodes in patients with suspected sarcoidosis. For optimal diagnostic yield, EBUS-TBNA should be combined with endobronchial biopsy (EBB) and transbronchial lung biopsy (TBLB). Newer endosonographic techniques like EBUS-IFB and EBMC might obviate the need for EBB and TBLB due to their superior diagnostic yield.

Variability of Common Carotid Intima-media Thickness Measured using B-mode and M-mode Ultrasound Imaging

Background: Common carotid artery intima-media thickness (cIMT) has been associated with cardiovascular diseases, including stroke and coronary heart disease. There is a limited number of studies that specifically address the variability of ultrasound imaging modes in measuring cIMT. Therefore, this study aimed to assess the agreement-level and inter-observer reproducibility of cIMT measurements using B-mode and M-mode.&#x0D; Materials and Methods: B-mode and M-mode ultrasound imaging were used in measuring cIMT of healthy subjects using linear-array transducer. Inter-imaging mode agreement and inter-observer reproducibility of B-mode and M-mode were assessed using Intraclass correlation coefficient (ICC). Differences in cIMT measurements between imaging modes and observers were determined using paired t-test&#x0D; Results: There was significant difference between B-mode and M-mode in measuring cIMT (mean difference (MD), 0.03 mm, 95% CI 0.02 - 0.05, p&lt;0.001). Intra-imaging mode agreement was poor with ICC of 0.39. Inter-observer reproducibility of cIMT measured using B-mode and M-mode were good and moderate, respectively, (B-mode ICC of 0.76, 95% CI 0.64 - 0.84, p&lt;0.01; M-mode ICC of 0.68, 95% CI 0.52 - 0.78, p&lt;0.01). No significant difference between the two observers in measuring cIMT measured using B-mode or M-mode (B-mode p=0.3; M-mode p=0.4). &#x0D; Conclusion: There was a significant difference and poor intra-imaging mode agreement between B-mode and M-mode in measuring cIMT. B-mode showed higher inter-observer reproducibility of cIMT measurement than M-mode. Further studies investigating the variability and agreement between ultrasound imaging modes of patients with thickened cIMT are required.

B-mode ultrasound based CAD for liver cancers via multi-view privileged information learning

B-mode ultrasound-based computer-aided diagnosis model can help sonologists improve the diagnostic performance for liver cancers, but it generally suffers from the bottleneck due to the limited structure and internal echogenicity information in B-mode ultrasound images. Contrast-enhanced ultrasound images provide additional diagnostic information on dynamic blood perfusion of liver lesions for B-mode ultrasound images with improved diagnostic accuracy. Since transfer learning has indicated its effectiveness in promoting the performance of target computer-aided diagnosis model by transferring knowledge from related imaging modalities, a multi-view privileged information learning framework is proposed to improve the diagnostic accuracy of the single-modal B-mode ultrasound-based diagnosis for liver cancers. This framework can make full use of the shared label information between the paired B-mode ultrasound images and contrast-enhanced ultrasound images to guide knowledge transfer It consists of a novel supervised dual-view deep Boltzmann machine and a new deep multi-view SVM algorithm. The former is developed to implement knowledge transfer from the multi-phase contrast-enhanced ultrasound images to the B-mode ultrasound-based diagnosis model via a feature-level learning using privileged information paradigm, which is totally different from the existing learning using privileged information paradigm that performs knowledge transfer in the classifier. The latter further fuses and enhances feature representation learned from three pre-trained supervised dual-view deep Boltzmann machine networks for the classification task. An experiment is conducted on a bimodal ultrasound liver cancer dataset. The experimental results show that the proposed framework outperforms all the compared algorithms with the best classification accuracy of 88.91 ± 1.52%, sensitivity of 88.31 ± 2.02%, and specificity of 89.50 ± 3.12%. It suggests the effectiveness of our proposed MPIL framework for the BUS-based CAD of liver cancers.

Ultrasonic measurement of thickness of carotid arterial wall using its natural longitudinal displacement

The thickness of the carotid arterial wall obtained from B-mode imaging using ultrasonic diagnostic devices is widely used for the diagnosis of atherosclerosis. However, the measurement interval in the lateral direction of the B-mode image depended on the beam interval (>100 μm). Therefore, the B-mode image is discrete in the lateral direction and cannot reflect changes in local and minute thicknesses. A method for measuring the roughness of the luminal surface of the wall was proposed using the displacement of the carotid arterial wall in the lateral direction during one heartbeat. In this method, the lateral measurement interval is much shorter than the beam interval, enabling a smooth measurement of the luminal surface. By simultaneously applying the method to the lumen-intima and medial-adventitia boundaries of the wall, we propose a novel method to measure the local and minute thicknesses of the carotid arterial wall.

Supervised segmentation for guiding peripheral revascularization with forward-viewing, robotically steered ultrasound guidewire.

Approximately 500000 patients present with critical limb ischemia (CLI) each year in the U.S., requiring revascularization to avoid amputation. While peripheral arteries can be revascularized via minimally invasive procedures, 25% of cases with chronic total occlusions are unsuccessful due to inability to route the guidewire beyond the proximal occlusion. Improvements to guidewire navigation would lead to limb salvage in a greater number of patients. Integrating ultrasound imaging into the guidewire could enable direct visualization of routes for guidewire advancement. In order to navigate a robotically-steerable guidewire with integrated imaging beyond a chronic occlusion proximal to the symptomatic lesion for revascularization, acquired ultrasound images must be segmented to visualize the path for guidewire advancement. The first approach for automated segmentation of viable paths through occlusions in peripheral arteries is demonstrated in simulations and experimentally-acquired data with a forward-viewing, robotically-steered guidewire imaging system. B-mode ultrasound images formed via synthetic aperture focusing (SAF) were segmented using a supervised approach (U-net architecture). A total of 2500 simulated images were used to train the classifier to distinguish the vessel wall and occlusion from viable paths for guidewire advancement. First, the size of the synthetic aperture resulting in the highest classification performance was determined in simulations (90 test images) and compared with traditional classifiers (global thresholding, local adaptive thresholding, and hierarchical classification). Next, classification performance as a function of the diameter of the remaining lumen (0.5 to 1.5mm) in the partially-occluded artery was tested using both simulated (60 test images at each of 7 diameters) and experimental data sets. Experimental test data sets were acquired in four 3D-printed phantoms from human anatomy and six ex vivo porcine arteries. Accuracy of classifying the path through the artery was evaluated using microcomputed tomography of phantoms and ex vivo arteries as a ground truth for comparison. An aperture size of 3.8mm resulted in the best-performing classification based on sensitivity and Jaccard index, with a significant increase in Jaccard index (p<0.05) as aperture diameter increased. In comparing the performance of the supervised classifier and traditional classification strategies with simulated test data, sensitivity and F1 score for U-net were 0.95±0.02 and 0.96±0.01, respectively, compared to 0.83±0.03 and 0.41±0.13 for the best-performing conventional approach, hierarchical classification. In simulated test images, sensitivity (p<0.05) and Jaccard index both increased with increasing artery diameter (p<0.05). Classification of images acquired in artery phantoms with remaining lumen diameters ≥ 0.75mm resulted in accuracies>90%, while mean accuracy decreased to 82% when artery diameter decreased to 0.5mm. For testing in ex vivo arteries, average binary accuracy, F1 score, Jaccard index, and sensitivity each exceeded 0.9. Segmentation of ultrasound images of partially-occluded peripheral arteries acquired with a forward-viewing, robotically-steered guidewire system was demonstrated for the first-time using representation learning. This could represent a fast, accurate approach for guiding peripheral revascularization.

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.