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Time-resolved three-dimensional ultrasound (3D + t US) is a promising imaging modality for monitoring abdominal aortic aneurysms (AAAs), providing their 3D geometry and motion. The lateral contrast of US is poor, a well-documented drawback which multi-perspective (MP) imaging could resolve. This study aims to show the feasibility of in vivo multi-perspective 3D + t ultrasound imaging of AAAs for improving the image contrast and displacement accuracy. To achieve this, single-perspective (SP) aortic ultrasound images from three different angles were spatiotemporally registered and fused, and the displacements were compounded. The fused MP had a significantly higher wall-lumen contrast than the SP images, for both patients and volunteers ( P  < .001). MP radial displacements patterns are smoother than SP patterns in 67% of volunteers and 92% of patients. The MP images from three angles have a decreased tracking error ( P  < .001 for all participants), and an improved SNR e compared to two out of three SP images ( P  < .05). This study has shown the added value of MP 3D + t US, improving both image contrast and displacement accuracy in AAA imaging. This is a step toward using multiple or large transducers in the clinic to capture the 3D geometry and strain more accurately, for patient-specific characterization of AAAs., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Aims: Urbanization is related to non-communicable diseases such as congestive heart failure (CHF). Understanding the influence of diverse living environments on physiological variables such as heart rate variability (HRV) in patients with chronic cardiac disease may contribute to more effective lifestyle advice and telerehabilitation strategies. This study explores how machine learning (ML) models can predict HRV metrics, which measure autonomic nervous system responses to environmental attributes in uncontrolled real-world settings. The goal is to validate whether this approach can ascertain and quantify the connection between environmental attributes and cardiac autonomic response in patients with CHF., Methods and Results: A total of 20 participants (10 healthy individuals and 10 patients with CHF) wore smartwatches for 3 weeks, recording activities, locations, and heart rate (HR). Environmental attributes were extracted from Google Street View images. Machine learning models were trained and tested on the data to predict HRV metrics. The models were evaluated using Spearman's correlation, root mean square error, prediction intervals, and Bland-Altman analysis. Machine learning models predicted HRV metrics related to vagal activity well ( R > 0.8 for HR; 0.8 > R > 0.5 for the root mean square of successive interbeat interval differences and the Poincaré plot standard deviation perpendicular to the line of identity; 0.5 > R > 0.4 for the high frequency power and the ratio of the absolute low- and high frequency power induced by environmental attributes. However, they struggled with metrics related to overall autonomic activity, due to the complex balance between sympathetic and parasympathetic modulation., Conclusion: This study highlights the potential of ML-based models to discern vagal dynamics influenced by living environments in healthy individuals and patients diagnosed with CHF. Ultimately, this strategy could offer rehabilitation and tailored lifestyle advice, leading to improved prognosis and enhanced overall patient well-being in CHF., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Abdominal aortic aneurysms (AAAs) are rupture-prone dilatations of the aorta. In current clinical practice, the maximal diameter of AAAs is monitored with 2D ultrasound to estimate their rupture risk. Recent studies have shown that 3-dimensional and mechanical AAA parameters might be better predictors for aneurysm growth and rupture than the diameter. These parameters can be obtained with time-resolved 3D ultrasound (3D+t US), which requires robust and automatic segmentation of AAAs from 3D+t US. This study proposes and validates a deep learning (DL) approach for automatic segmentation of AAAs. 500 AAA patients were included for follow-up 3D+t US imaging, resulting in 2495 3D+t US images. Segmentation masks for model training were obtained using a conventional automatic segmentation algorithm ('nonDL'). Four different DL models were trained and validated by (1) comparison to CT and (2) reader scoring. Performance of the nonDL and different DL segmentation strategies were evaluated by comparing Hausdorff distance, Dice scores, accuracy, sensitivity, and specificity with a sign test. All DL models had higher median Dice scores, accuracy, and sensitivity (all p < 0.003) compared to nonDL segmentation. The full image-resolution model without data augmentation showed the highest median Dice score and sensitivity (p < 0.001). Applying the DL model on an independent test group produced fewer poor segmentation scores of 1 to 2 on a five-point scale (8% for DL, 18% for nonDL). This demonstrates that a robust and automatic segmentation algorithm for segmenting abdominal aortic aneurysms from 3D+t US images was developed, showing improved performance compared to conventional segmentation.

High frame rate ultrasound (US) imaging techniques in 3D are promising tools for capturing abdominal aortic aneurysms (AAAs) over time, however, with the limited number of channel-to-element connections current footprints are small, which limits the field of view. Moreover, the maximal steering angle of the ultrasound beams in transmit and the maximal receptance angle in receive are insufficient for capturing the curvy shape of the AAA. Therefore, an approach is needed towards large arrays. In this study, high frame rate bistatic 3D US data (17 Hz) were acquired with two synchronized matrix arrays positioned at different locations (multi-aperture imaging) using a translation stage to simulate what a larger array with limited channel-to-element connections can potentially achieve. Acquisitions were performed along an AAA shaped phantom with different probe tilting angles (0 up to ± 30°). The performance of different multi-aperture configurations was quantified using the generalized contrast-to-noise ratio of the wall and lumen (gCNR). Furthermore, a parametric model of the multi-aperture system was used to estimate in which AAA wall regions the contrast is expected to be high. This was evaluated for AAAs with increasing diameters and curvature. With an eight-aperture 0° probe angle configuration a 69 % increase in field of view was measured in the longitudinal direction compared to the field of view of a single aperture configuration. When increasing the number of apertures from two to eight, the gCNR improved for the upper wall and lower wall by 35 % and 13 % (monostatic) and by 36 % and 13 % (bistatic). Contrast improvements up to 22 % (upper wall) and 12 % (lower wall) are achieved with tilted probe configurations compared to non-tilted configurations. Moreover, with bistatic imaging with tilted probe configurations gCNR improvements up to 4 % (upper wall) and 7 % (lower wall) are achieved compared to monostatic imaging. Furthermore, imaging with a larger inter-probe distance improved the gCNR for a ± 15° probe angle configuration. The gCNR has an expected pattern over time, where the contrast is lower when there is more wall motion (systole) and higher when motion is reduced (diastole). Furthermore, a higher frame rate (45 Hz) yields a lower gCNR, because fewer compound angles are used. The results of the parametric model suggest that a flat array is suitable for imaging AAA shapes with limited curvature, but that it is not suitable for imaging larger AAA shapes with more curvature. According to the model, tilted multi-aperture configurations combined with bistatic imaging can achieve a larger region with high contrast compared to non-tilted configurations. The findings of the model are in agreement with experimental findings. To conclude, this study demonstrates the vast improvements in field of view and AAA wall visibility that a large, sparsely populated 3D array can potentially achieve when imaging AAAs compared to single or dual aperture imaging. In the future, larger arrays, less thermal noise, more steering, and more channel-to-element connections combined with carefully chosen orientations of (sub-) apertures will likely advance 3D imaging of AAAs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Introduction: In this paper we introduce in vivo multi-aperture ultrasound imaging and elastography of the abdominal aorta. Monitoring of the geometry and growth of abdominal aortic aneurysms (AAA) is paramount for risk stratification and intervention planning. However, such an assessment is limited by the lateral lumen-wall contrast and resolution of conventional ultrasound. Here, an in vivo dual-aperture bistatic imaging approach is shown to improve abdominal ultrasound and strain imaging quality significantly. By scanning the aorta from different directions, a larger part of the vessel circumference can be visualized. Methods: In this first-in-man volunteer study, the performance of multi-aperture ultrasound imaging and elastography of the abdominal aortic wall was assessed in 20 healthy volunteers. Dual-probe acquisition was performed in which two curved array transducers were aligned in the same imaging plane. The transducers alternately transmit and both probes receive simultaneously on each transmit event, which allows for the reconstruction of four ultrasound signals. Automatic probe localization was achieved by optimizing the coherence of the trans-probe data, using a gradient descent algorithm. Speckle-tracking was performed on the four individual bistatic signals, after which the respective axial displacements were compounded and strains were calculated. Results: Using bistatic multi-aperture ultrasound imaging, the image quality of the ultrasound images, i.e. , the angular coverage of the wall, was improved which enables accurate estimation of local motion dynamics and strain in the abdominal aortic wall. The motion tracking error was reduced from 1.3 mm ± 0.63 mm to 0.16 mm ± 0.076 mm, which increased the circumferential elastographic signal-to-noise ratio (SNRe) by 12.3 dB ± 8.3 dB on average, revealing more accurate and homogeneous strain estimates compared to single-perspective ultrasound. Conclusion: Multi-aperture ultrasound imaging and elastography is feasible in vivo and can provide the clinician with vital information about the anatomical and mechanical state of AAAs in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 van Hal, de Hoop, van Sambeek, Schwab and Lopata.)

Cardiovascular strain imaging is continually improving due to ongoing advances in ultrasound acquisition and data processing techniques. The phantoms used for validation of new methods are often burdensome to make and lack flexibility to vary mechanical and acoustic properties. Simulations of US imaging provide an alternative with the required flexibility and ground truth strain data. However, the current Lagrangian US strain imaging models cannot simulate heterogeneous speed of sound distributions and higher-order scattering, which limits the realism of the simulations. More realistic Eulerian modelling techniques exist but have so far not been used for strain imaging. In this research, a novel sampling scheme was developed based on a band-limited interpolation of the medium, which enables accurate strain simulation in Eulerian methods. The scheme was validated in k-Wave using various numerical phantoms and by a comparison with Field II. The method allows for simulations with a large range in strain values and was accurate with errors smaller than -60 dB. Furthermore, an excellent agreement with the Fourier theory of US scattering was found. The ability to perform simulations with heterogeneous speed of sound distributions was demonstrated using a pulsating artery model. The developed sampling scheme contributes to more realistic strain imaging simulations, in which the effect of heterogenous acoustic properties can be taken into account., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

In multiaperture ultrasound, several ultrasound probes with different insonification angles are combined to increase the field of view and angular coverage of image structures. A full reconstruction incorporating all possible combinations of transmitting and receiving probes has been shown to improve resolution, contrast, and angular coverage beyond what can be achieved by the registration of single images from different probes. A major challenge in multiaperture imaging is the correct determination of relative probe locations. A registration based on the content of images from different probes is challenging due to the decorrelation of image structures and speckle with increasing angle between the probes. We propose a probe localization method for plane-wave ultrasound that uses solely the receive dataset of a nontransmitting probe. The localization is performed by signal tracking in the Radon domain. To demonstrate that the method does not rely on common structures in the individual images, we show that a satisfying localization can be performed in pure speckle for angles, where the speckle patterns have completely decorrelated. The method shows potential for real-time probe localization in free-hand multiprobe ultrasound imaging or for flexible and wearable multiarray combination of multiple capacitive micromachined (CMUT)-based systems in the future.

Abdominal ultrasound image quality is hampered by phase aberration, that is mainly caused by the large speed-of-sound (SoS) differences between fat and muscle tissue in the abdominal wall. The mismatch between the assumed and actual SoS distribution introduces general blurring of the ultrasound images, and acoustic refraction can lead to geometric distortion of the imaged features. Large aperture imaging or dual-transducer imaging can improve abdominal imaging at deep locations by providing increased contrast and resolution. However, aberration effects for large aperture imaging can be even more severe, which limits its full potential. In this study, a model-based aberration correction method for arbitrary acquisition schemes is introduced for delay-and-sum (DAS) beamforming and its performance was analyzed for both single- and dual-transducer ultrasound imaging. The method employs aberration corrected wavefront arrival times, using manually assigned local SoS values. Two wavefront models were compared. The first model is based on a straight ray approximation, and the second model on the Eikonal equation, which is solved by a multi-stencils fast marching method. Their accuracy for abdominal imaging was evaluated in acoustic simulations and phantom experiments involving tissue-mimicking and porcine material with large SoS contrast (∼100 m/s). The lateral resolution was improved by up to 90% in simulations and up to 65% in experiments compared to standard DAS, in which the use of Eikonal beamforming generally outperformed straight ray beamforming. Moreover, geometric distortions were mitigated in multi-aperture imaging, leading to a reduction in position error of around 80%. A study on the sensitivity of the aberration correction to shape and SoS of aberrating layers was performed, showing that even with imperfect segmentations or SoS values, aberration correction still outperforms standard DAS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

In the last decade, many advances have been made in high frame rate 3-D ultrasound imaging, including more flexible acquisition systems, transmit (TX) sequences, and transducer arrays. Compounding multiangle transmits of diverging waves has shown to be fast and effective for 2-D matrix arrays, where heterogeneity between transmits is key in optimizing the image quality. However, the anisotropy in contrast and resolution remains a drawback that cannot be overcome with a single transducer. In this study, a bistatic imaging aperture is demonstrated that consists of two synchronized matrix ( 32×32 ) arrays, allowing for fast interleaved transmits with a simultaneous receive (RX). First, for a single array, the aperture efficiency for high volume rate imaging was evaluated between sparse random arrays and fully multiplexed arrays. Second, the performance of the bistatic acquisition scheme was analyzed for various positions on a wire phantom and was showcased in a dynamic setup mimicking the human abdomen and aorta. Sparse array volume images were equal in resolution and lower in contrast compared to fully multiplexed arrays but can efficiently minimize decorrelation during motion for multiaperture imaging. The dual-array imaging aperture improved the spatial resolution in the direction of the second transducer, reducing the average volumetric speckle size with 72% and the axial-lateral eccentricity with 8%. In the aorta phantom, the angular coverage increased by a factor of 3 in the axial-lateral plane, raising the wall-lumen contrast with 16% compared to single-array images, despite accumulation of thermal noise in the lumen.

Despite the notable recent developments in the field of remote photoplethysmography (rPPG), extracting a reliable pulse rate variability (PRV) signal still remains a challenge. In this study, eight image-based photoplethysmography (iPPG) extraction methods (GRD, AGRD, PCA, ICA, LE, SPE, CHROM, and POS) were compared in terms of pulse rate (PR) and PRV features. The algorithms were made robust for motion and illumination artifacts by using ad hoc pre- and postprocessing steps. Then, they were systematically tested on the public dataset UBFC-RPPG, containing data from 42 subjects sitting in front of a webcam (30 fps) while playing a time-sensitive mathematical game. The performances of the algorithms were evaluated by statistically comparing iPPG-based and finger-PPG-based PR and PRV features in terms of Spearman's correlation coefficient, normalized root mean square error (NRMSE), and Bland-Altman analysis. The study revealed POS and CHROM techniques to be the most robust for PR estimation and the assessment of overall autonomic nervous system (ANS) dynamics by using PRV features in time and frequency domains. Furthermore, we demonstrated that a reliable characterization of the vagal tone is made possible by computing the Poincaré map of PRV series derived from the POS and CHROM methods. This study supports the use of iPPG systems as promising tools to obtain clinically useful and specific information about ANS dynamics.

Rupture risk estimation of abdominal aortic aneurysm (AAA) patients is currently based on the maximum diameter of the AAA. Mechanical properties that characterize the mechanical state of the vessel may serve as a better rupture risk predictor. Non-electrocardiogram-gated (non-ECG-gated) freehand 2D ultrasound imaging is a fast approach from which a reconstructed volumetric image of the aorta can be obtained. From this 3D image, the geometry, volume, and maximum diameter can be obtained. The distortion caused by the pulsatility of the vessel during the acquisition is usually neglected, while it could provide additional quantitative parameters of the vessel wall. In this study, a framework was established to semi-automatically segment probe tracked images of healthy aortas ( N  = 10) and AAAs ( N  = 16), after which patient-specific geometries of the vessel at end diastole (ED), end systole (ES), and at the mean arterial pressure (MAP) state were automatically assessed using heart frequency detection and envelope detection. After registration AAA geometries were compared to the gold standard computed tomography (CT). Local mechanical properties, i.e., compliance, distensibility and circumferential strain, were computed from the assessed ED and ES geometries for healthy aortas and AAAs, and by using measured brachial pulse pressure values. Globally, volume, compliance, and distensibility were computed. Geometries were in good agreement with CT geometries, with a median similarity index and interquartile range of 0.91 [0.90-0.92] and mean Hausdorff distance and interquartile range of 4.7 [3.9-5.6] mm. As expected, distensibility (Healthy aortas: 80 ± 15·10 -3  kPa -1 ; AAAs: 29 ± 9.6·10 -3  kPa -1 ) and circumferential strain (Healthy aortas: 0.25 ± 0.03; AAAs: 0.15 ± 0.03) were larger in healthy vessels compared to AAAs. Circumferential strain values were in accordance with literature. Global healthy aorta distensibility was significantly different from AAAs, as was demonstrated with a Wilcoxon test ( p -value = 2·10 -5 ). Improved image contrast and lateral resolution could help to further improve segmentation to improve mechanical characterization. The presented work has demonstrated how besides accurate geometrical assessment freehand 2D ultrasound imaging is a promising tool for additional mechanical property characterization of AAAs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Jansen, Schwab, van de Vosse, van Sambeek and Lopata.)

Methods for patient-specific abdominal aortic aneurysm (AAA) progression monitoring and rupture risk assessment are widely investigated. Three-dimensional ultrasound can visualize the AAA's complex geometry and displacement fields. However, ultrasound has a limited field of view and low frame rate (i.e., 3-8 Hz). This article describes an approach to enhance the temporal resolution and the field of view. First, the frame rate was increased for each data set by sequencing multiple blood pulse cycles into one cycle. The sequencing method uses the original frame rate and the estimated pulse wave rate obtained from AAA distension curves. Second, the temporal registration was applied to multi-perspective acquisitions of the same AAA. Third, the field of view was increased through spatial registration and fusion using an image feature-based phase-only correlation method and a wavelet transform, respectively. Temporal sequencing was fully correct in aortic phantoms and was successful in 51 of 62 AAA patients, yielding a factor 5 frame rate increase. Spatial registration of proximal and distal ultrasound acquisitions was successful in 32 of 37 different AAA patients, based on the comparison between the fused ultrasound and computed tomography segmentation (95th percentile Haussdorf distances and similarity indices of 4.2 ± 1.7 mm and 0.92 ± 0.02 mm, respectively). Furthermore, the field of view was enlarged by 9%-49%., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Ultrasound (US) imaging is a medical imaging modality that uses the reflection of sound in the range of 2-18 MHz to image internal body structures. In US, the frequency bandwidth (BW) is directly associated with image resolution. BW is a property of the transducer and more bandwidth comes at a higher cost. Thus, methods that can transform strongly bandlimited ultrasound data into broadband data are essential. In this work, we propose a deep learning (DL) technique to improve the image quality for a given bandwidth by learning features provided by broadband data of the same field of view. Therefore, the performance of several DL architectures and conventional state-of-the-art techniques for image quality improvement and artifact removal have been compared on in vitro US datasets. Two training losses have been utilized on three different architectures: a super resolution convolutional neural network (SRCNN), U-Net, and a residual encoder decoder network (REDNet) architecture. The models have been trained to transform low-bandwidth image reconstructions to high-bandwidth image reconstructions, to reduce the artifacts, and make the reconstructions visually more attractive. Experiments were performed for 20%, 40%, and 60% fractional bandwidth on the original images and showed that the improvements obtained are as high as 45.5% in RMSE, and 3.85 dB in PSNR, in datasets with a 20% bandwidth limitation.

Significance: Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking., Aim: A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation., Approach: Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood. Ex vivo human plaque samples were simulated to validate the methods in more complex tissues., Results: The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately., Conclusions: A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.

Left ventricular (LV) strains are typically represented with respect to the imaging axes. Contraction within the myocardium occurs along myofibres, which vary in orientation. Therefore, a mismatch exists between the direction in which strain is calculated and that in which contraction occurs. In this study, ultrasound-based fibre orientation and 3-D strain estimation were combined to calculate the fibre-directional strain. Three-dimensional ultrasound volumes were created by simulating simple geometrical phantoms and a phantom based on a finite-element (FE) model of LV mechanics. Fibre-like structures were embedded within tissue-mimicking scatterers. Strains were applied to the numerical phantom, whereas the FE phantom was deformed based on the LV model. Fibre orientation was accurately estimated for both phantoms. There was poor agreement in axial and elevational strains (root mean square error = 29.9% and 12.3%), but good agreement in lateral and fibre-directional strains (root mean square error = 6.4% and 5.9% respectively), which aligned in the midwall. Simplifications to reduce computational complexity caused poor axial and elevational strain estimation. However, calculation of fibre-directional strain from single-modality ultrasound volumes was successful. Further studies, in ex vivo setups because of the fundamental limitations of currently available transducers, are needed to verify real-world performance of the method., Competing Interests: Conflict of interest disclosure The authors declare no conflict of interest that might have influenced the (presentation of the) work described in this article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Ultrasound (US) imaging is used to assess cardiac disease by assessing the geometry and function of the heart utilizing its high spatial and temporal resolution. However, because of physical constraints, drawbacks of US include limited field-of-view, refraction, resolution and contrast anisotropy. These issues cannot be resolved when using a single probe. Here, an interleaved multi-perspective 2-D US imaging system was introduced, aiming at improved imaging of the left ventricle (LV) of the heart by acquiring US data from two separate phased array probes simultaneously at a high frame rate. In an ex-vivo experiment of a beating porcine heart, parasternal long-axis and apical views of the left ventricle were acquired using two phased array probes. Interleaved multi-probe US data were acquired at a frame rate of 170 frames per second (FPS) using diverging wave imaging under 11 angles. Image registration and fusion algorithms were developed to align and fuse the US images from two different probes. First- and second-order speckle statistics were computed to characterize the resulting probability distribution function and point spread function of the multi-probe image data. First-order speckle analysis showed less overlap of the histograms (reduction of 34.4%) and higher contrast-to-noise ratio (CNR, increase of 27.3%) between endocardium and myocardium in the fused images. Autocorrelation results showed an improved and more isotropic resolution for the multi-perspective images (single-perspective: 0.59 mm × 0.21 mm, multi-perspective: 0.35 mm × 0.18 mm). Moreover, mean gradient (MG) (increase of 74.4%) and entropy (increase of 23.1%) results indicated that image details of the myocardial tissue can be better observed after fusion. To conclude, interleaved multi-perspective high frame rate US imaging was developed and demonstrated in an ex-vivo experimental setup, revealing enlarged field-of-view, and improved image contrast and resolution of cardiac images., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Lightweight segmentation models are becoming more popular for fast diagnosis on small and low cost medical imaging devices. This study focuses on the segmentation of the left ventricle (LV) in cardiac ultrasound (US) images. A new lightweight model [LV network (LVNet)] is proposed for segmentation, which gives the benefits of requiring fewer parameters but with improved segmentation performance in terms of Dice score (DS). The proposed model is compared with state-of-the-art methods, such as UNet, MiniNetV2, and fully convolutional dense dilated network (FCdDN). The model proposed comes with a post-processing pipeline that further enhances the segmentation results. In general, the training is done directly using the segmentation mask as the output and the US image as the input of the model. A new strategy for segmentation is also introduced in addition to the direct training method used. Compared with the UNet model, an improvement in DS performance as high as 5% for segmentation with papillary (WP) muscles was found, while showcasing an improvement of 18.5% when the papillary muscles are excluded. The model proposed requires only 5% of the memory required by a UNet model. LVNet achieves a better trade-off between the number of parameters and its segmentation performance as compared with other conventional models. The developed codes are available at https://github.com/navchetanawasthi/Left&#95;Ventricle&#95;Segmentation.

Purpose: Various parameters of mechanical dyssynchrony have been proposed to improve patient selection criteria for cardiac resynchronization therapy, but sensitivity and specificity are lacking. However, echocardiographic parameters are consistently investigated at rest, whereas heart failure (HF) symptoms predominately manifest during submaximal exertion. Although strain-based predictors of response are promising, feasibility and reproducibility during exercise has yet to be demonstrated., Methods: Speckle-tracking echocardiography was performed in patients with HF at two separate visits. Echocardiography was performed at rest, during various exercise intensity levels, and during recovery from exercise. Systolic rebound stretch of the septum (SRSsept), systolic shortening, and septal discoordination index (SDI) were calculated., Results: Echocardiography was feasible in about 70-80% of all examinations performed during exercise. Of these acquired views, 84% of the cine-loops were suitable for analysis of strain-based mechanical dyssynchrony. Test-retest variability and intra- and inter-operator reproducibility at 30% and 60% of the ventilatory threshold (VT) were about 2.5%. SDI improved in the majority of patients at 30% and 60% of the VT, with moderate to good agreement between both intensity levels., Conclusion: Although various challenges remain, exercise echocardiography with strain analysis appears to be feasible in the majority of patients with dyssynchronous heart failure. Inter- and intra-observer agreement of SRSsept and SDI up to 60% of the VT were comparable to resting values. During exercise, the extent of SDI was variable, suggesting a heterogeneous response to exercise. Further research is warranted to establish its clinical significance., (© 2022. The Author(s).)

Knowledge of aneurysm geometry and local mechanical wall parameters using ultrasound (US) can contribute to a better prediction of rupture risk in abdominal aortic aneurysms (AAAs). However, aortic strain imaging using conventional US is limited by the lateral lumen-wall contrast and resolution. In this study, ultrafast multiperspective bistatic (MP BS) imaging is used to improve aortic US, in which two curved array transducers receive simultaneously on each transmit event. The advantage of such bistatic US imaging on both image quality and strain estimations was investigated by comparing it to single-perspective monostatic (SP MS) and MP monostatic (MP MS) imaging, i.e., alternately transmitting and receiving with either transducer. Experimental strain imaging was performed in US simulations and in an experimental study on porcine aortas. Different compounding strategies were tested to retrieve the most useful information from each received US signal. Finally, apart from the conventional sector grid in curved array US imaging, a polar grid with respect to the vessel's local coordinate system is introduced. This new reconstruction method demonstrated improved displacement estimations in aortic US. The US simulations showed increased strain estimation accuracy using MP BS imaging bistatic imaging compared to MP MS imaging, with a decrease in the average relative error between 41% and 84% in vessel wall regions between transducers. In the experimental results, the mean image contrast-to-noise ratio was improved by up to 8 dB in the vessel wall regions between transducers. This resulted in an increased mean elastographic signal-to-noise ratio by about 15 dB in radial strain and 6 dB in circumferential strain.

In the above article [1], one error, (1), was found which has an impact on the results and interpretation of the image quality that was described in four sentences, (2)-(5). This correction does not mitigate the overall conclusion of this work, but does positively support improvements of the proposed method (multi-perspective ultrafast imaging) in comparison with the standard method (focused line-by-line imaging).

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide. An effective management and treatment of CVDs highly relies on accurate diagnosis of the disease. As the most common imaging technique for clinical diagnosis of the CVDs, US imaging has been intensively explored. Especially with the introduction of deep learning (DL) techniques, US imaging has advanced tremendously in recent years. Photoacoustic imaging (PAI) is one of the most promising new imaging methods in addition to the existing clinical imaging methods. It can characterize different tissue compositions based on optical absorption contrast and thus can assess the functionality of the tissue. This paper reviews some major technological developments in both US (combined with deep learning techniques) and PA imaging in the application of diagnosis of CVDs.

Accurate 3-D geometries of arteries and veins are important clinical data for diagnosis of arterial disease and intervention planning. Automatic segmentation of vessels in the transverse view suffers from the low lateral resolution and contrast. Convolutional neural networks are a promising tool for automatic segmentation of medical images, outperforming the traditional segmentation methods with high robustness. In this study, we aim to create a general, robust, and accurate method to segment the lumen-wall boundary of healthy central and peripheral vessels in large field-of-view freehand ultrasound (US) datasets. Data were acquired using the freehand US, in combination with a probe tracker. A total of ±36 000 cross-sectional images, acquired in the common, internal, and external carotid artery ( N = 37 ), in the radial, ulnar artery, and cephalic vein ( N = 12 ), and in the femoral artery ( N = 5 ) were included. To create masks (of the lumen) for training data, a conventional automatic segmentation method was used. The neural networks were trained on: 1) data of all vessels and 2) the carotid artery only. The performance was compared and tested using an open-access dataset. The recall, precision, DICE, and intersection over union (IoU) were calculated. Overall, segmentation was successful in the carotid and peripheral arteries. The Multires U-net architecture performs best overall with DICE = 0.93 when trained on the total dataset. Future studies will focus on the inclusion of vascular pathologies.

Currently, the prediction of rupture risk in abdominal aortic aneurysms (AAAs) solely relies on maximum diameter. However, wall mechanics and hemodynamics have shown to provide better risk indicators. Patient-specific fluid-structure interaction (FSI) simulations based on a non-invasive image modality are required to establish a patient-specific risk indicator. In this study, a robust framework to execute FSI simulations based on time-resolved three-dimensional ultrasound (3D+t US) data was obtained and employed on a data set of 30 AAA patients. Furthermore, the effect of including a pre-stress estimation (PSE) to obtain the stresses present in the measured geometry was evaluated. The established workflow uses the patient-specific 3D+t US-based segmentation and brachial blood pressure as input to generate meshes and boundary conditions for the FSI simulations. The 3D+t US-based FSI framework was successfully employed on an extensive set of AAA patient data. Omitting the pre-stress results in increased displacements, decreased wall stresses, and deviating time-averaged wall shear stress and oscillatory shear index patterns. These results underline the importance of incorporating pre-stress in FSI simulations. After validation, the presented framework provides an important tool for personalized modeling and longitudinal studies on AAA growth and rupture risk., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Fonken, Maas, Nievergeld, van Sambeek, van de Vosse and Lopata.)

Near-field (NF) clutter in echocardiography is depicted as a diffuse haze hindering the visualization of the myocardium and the blood-pool, thereby degrading its diagnostic value. Several clutter filters have been developed, which are limited in patients with contraction motion and rhythm anomalies, and in 3-D ultrasound (US). This study introduces a new NF clutter reduction method, which preserves US speckles required for strain imaging. The filter developed detects the NF clutter region in the spatial frequency domain. The filter employs an oriented, multiscale approach, and assumes the NF clutter to be predominantly present in the highest and lowest bandpass images. These bandpass images were filtered, whilst sparing features in the myocardium and NF clutter-free regions. The performance of the filter was assessed in a volunteer study, in ten 3-D apical and parasternal view acquisitions, and in a retrospective clinical study composed of 20 cardiac patients with different indications for echocardiography. The filter reduced NF clutter in all data sets, whilst preserving all or most of the myocardium. Additionally, it demonstrated a consistent enhancement of image quality, with an increase in contrast of 4.3 dB on average, and generated a clearer myocardial boundary distinction. Furthermore, the speckles were preserved according to the quality index based on local variance, the structural similarity index method, and normalized cross correlation values, being 0.82, 0.92, and 0.95 on average, respectively. Global longitudinal strain measurements on NF clutter reduced images were improved or equivalent compared to the original acquisitions, with an average increase in strain signal-to-noise ratio of 34%.

Vascular ultrasound imaging is inherently hampered by low lateral resolution and contrast. Steering of the ultrasound beams can be used to overcome these limitations in superficial artery imaging because the aperture-to-depth ratio is relatively high. However, in arteries located at larger depths, the steered beams do not overlap for larger steering angles. In this study, the ultrasound probe is physically translated over the abdomen to create large angles between acquisitions, while maintaining overlap on the abdominal aorta. In one phantom setup and 11 volunteers, 2-D cross-sectional multi-perspective ultrasound images of the abdominal aorta were acquired using seven angles between -45° and +45°. Automatic registration of the recorded images was performed by automatic feature detection of the aorta and spine. This automatic detection was successful in 62 out of 77 image sets. Compounded multi-perspective images showed an increase of contrast-to-noise ratios from 0.6 ± 0.1 to 1.2 ± 0.2 over the entire heart cycle in volunteers., Competing Interests: Conflict of Interest The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Current decision-making for clinical intervention of abdominal aortic aneurysms (AAAs) is based on the maximum diameter of the aortic wall, but this does not provide patient-specific information on rupture risk. Ultrasound (US) imaging can assess both geometry and deformation of the aortic wall. However, low lateral contrast and resolution are currently limiting the precision of both geometry and local strain estimates. To tackle these drawbacks, a multiperspective scanning mode was developed on a dual transducer US system to perform strain imaging at high frame rates. Experimental imaging was performed on porcine aortas embedded in a phantom of the abdomen, pressurized in a mock circulation loop. US images were acquired with three acquisition schemes: Multiperspective ultrafast imaging, single perspective ultrafast imaging, and conventional line-by-line scanning. Image registration was performed by automatic detection of the transducer surfaces. Multiperspective images and axial displacements were compounded for improved segmentation and tracking of the aortic wall, respectively. Performance was compared in terms of image quality, motion tracking, and strain estimation. Multiperspective compound displacement estimation reduced the mean motion tracking error over one cardiac cycle by a factor 10 compared to conventional scanning. Resolution increased in radial and circumferential strain images, and circumferential signal-to-noise ratio (SNRe) increased by 10 dB. Radial SNRe is high in wall regions moving towards the transducer. In other regions, radial strain estimates remain cumbersome for the frequency used. In conclusion, multiperspective US imaging was demonstrated to improve motion tracking and circumferential strain estimation of porcine aortas in an experimental set-up.

Accurate estimation of mechanical properties of the different atherosclerotic plaque constituents is important in assessing plaque rupture risk. The aim of this study was to develop an experimental set-up to assess material properties of vascular tissue, while applying physiological loading and being able to capture heterogeneity. To do so, a ring-inflation experimental set-up was developed in which a transverse slice of an artery was loaded in the radial direction, while the displacement was estimated from images recorded by a high-speed video camera. The performance of the set-up was evaluated using seven rubber samples and validated with uniaxial tensile tests. For four healthy porcine carotid arteries, material properties were estimated using ultrasound strain imaging in whole-vessel-inflation experiments and compared to the properties estimated with the ring-inflation experiment. A 1D axisymmetric finite element model was used to estimate the material parameters from the measured pressures and diameters, using a neo-Hookean and Holzapfel-Gasser-Ogden material model for the rubber and porcine samples, respectively. Reproducible results were obtained with the ring-inflation experiment for both rubber and porcine samples. Similar mean stiffness values were found in the ring-inflation and tensile tests for the rubber samples as 202 kPa and 206 kPa, respectively. Comparable results were obtained in vessel-inflation experiments using ultrasound and the proposed ring-inflation experiment. This inflation set-up is suitable for the assessment of material properties of healthy vascular tissue in vitro. It could also be used as part of a method for the assessment of heterogeneous material properties, such as in atherosclerotic plaques.

Left ventricular assist devices (LVAD) provide cardiac support to patients with advanced heart failure. Methods that can directly measure remaining LV function following device implantation do not currently exist. Previous studies have shown that a combination of loading (LV pressure) and deformation (strain) measurements enables quantitation of myocardial work. We investigated the use of ultrasound (US) strain imaging and pressure-strain loop analysis in LVAD-supported hearts under different hemodynamic and pump unloading conditions, with the aim of determining LV function with and without LVAD support. Ex vivo porcine hearts (n = 4) were implanted with LVADs and attached to a mock circulatory loop. Measurements were performed at hemodynamically defined "heart conditions" as the hearts deteriorated from baseline. Hemodynamic (including LV pressure) and radio-frequency US data were acquired during a pump-ramp protocol at speeds from 0 (with no pump outflow) to 10 000 revolutions per minute (rpm). Regional circumferential (ε circ ) and radial (ε rad ) strains were estimated over each heart cycle. Regional ventricular dyssynchrony was quantitated through time-to-peak strain. Mean change in LV pulse pressure and ε circ between 0 and 10 krpm were -21.8 mm Hg and -7.24% in the first condition; in the final condition -46.8 mm Hg and -19.2%, respectively. ε rad was not indicative of changes in pump speed or heart condition. Pressure-strain loops showed a degradation in the LV function and an increased influence of LV unloading: loop area reduced by 90% between 0 krpm in the first heart condition and 10 krpm in the last condition. High pump speeds and degraded condition led to increased dyssynchrony between the septal and lateral LV walls. Functional measurement of the LV while undergoing LVAD support is possible by using US strain imaging and pressure-strain loops. This can provide important information about remaining pump function. Use of novel LV pressure estimation or measurement techniques would be required for any future use in LVAD patients., (© 2020 The Authors. Artificial Organs published by International Center for Artificial Organ and Transplantation (ICAOT) andWiley Periodicals LLC.)

Current guidelines for abdominal aortic aneurysm (AAA) repair are primarily based on the maximum diameter. Since these methods lack robustness in decision making, new image-based methods for mechanical characterization have been proposed. Recently, time-resolved 3D ultrasound (4D US) in combination with finite element analysis was shown to provide additional risk estimators such as patient-specific peak wall stresses and wall stiffness in a non-invasive way. The aim of this study is to: 1) assess the reproducibility of this US-based stiffness measurement in vitro and in vivo, and 2) verify this 4D US stiffness using the gold standard: bi-axial tensile testing of the excised aortic tissue. For the in vitro study, 4D US data were acquired in an idealized inflation experiment using porcine aortas. The full aortic geometry was segmented and tracked over the cardiac cycle, and afterwards finite element analysis was performed by calibrating the finite element model to the measured US displacements to find the global aortic wall stiffness. For verification purposes, the porcine tissue was subjected to bi-axial tensile testing. Secondly, four AAA patients were included and 4D US data were acquired before open aortic surgery was performed. Similar to the experimental approach, the 4D US data were analyzed using the iterative finite element approach. During surgery, aortic tissue was harvested and the resulting tissue specimens were analyzed using bi-axial tensile testing. Finally, reproducibility was quantified for both methods. A high reproducibility was observed for the wall stiffness measurements using 4D US, i.e., an ICC of 0.91 (95% CI: 0.78-0.98) for the porcine aortas and an ICC of 0.98 (95% CI: 0.84-1.00) for the AAA samples. Verification with bi-axial tensile testing revealed a good agreement for the inflation experiment and a moderate agreement for the AAA patients, partially caused by the diseased state and inhomogeneities of the tissue. The performance of aortic stiffness characterization using 4D US revealed overall a high reproducibility and a moderate agreement with ex vivo mechanical testing. Future research should include more patient samples, to statistically assess the accuracy of the current in vivo method, which is not trivial due to the low number of open surgical interventions., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Current clinical guidelines for surgical repair of abdominal aortic aneurysms (AAAs) are primarily based on maximum diameter assessment. From a biomechanical point of view, not only the diameter but also peak wall stresses will play an important role in rupture risk assessment. These methods require patient specific geometry which typically uses computed tomography (CT) or magnetic resonance imaging. Recently, wall stress analysis based on 3D ultrasound (US) has been proposed, and shows promising results. However, the major limitations in these studies were the use of manual segmentation and the limiting field of view of US. Therefore in this study, the AAA is imaged with multiperspective 3D ultrasound, merged to obtain a large field of view, and afterwards automatically segmented. Geometry and wall stress results were validated using CT imaging., Methods: Three dimensional US and CT data were available for 40 AAA patients (maximum diameter 34-61 mm). The full US based AAA geometry was determined using automatic segmentation, and when the aneurysm exceeded a single 3D volume, automatic fusion of multiple 3D US volumes was used. Wall stress analysis was performed for all AAA patients and percentile wall stresses were derived. The accuracy of the US based geometry and wall stress prediction was measured by comparison with CT data., Results: Estimated geometries derived from 3D US and CT data showed good similarity, with an overall median similarity index (SI) of 0.89 and interquartile range of 0.87-0.92, whereas the median Hausdorff distances (HD), a measure for the maximum local mismatch, was 4.6 (4.0-5.9) mm for all AAA geometries. Thereby, the wall stress results based on merged multiperspective 3D US data revealed a greater similarity to CT than single 3D US data., Conclusion: This study showed that large volume geometry assessment of AAAs using multiperspective 3D ultrasound, segmentation and fusion, and wall stress analysis is feasible in a robust and labour efficient manner., (Copyright © 2019 European Society for Vascular Surgery. Published by Elsevier B.V. All rights reserved.)

Purpose: In dynamic musculoskeletal sonography, probe fixation can contribute to field of view (FOV) consistency, which is necessary for valid analysis of architectural parameters. In this volunteer study, the achieved FOV consistency in fixated ultrasonography was quantified and compared with freehand acquisition., Methods: During five resting periods during cycling exercise, longitudinal B-mode images of the vastus lateralis (VL) muscle were acquired on one thigh with a fixated probe, and by two trained observers on the other thigh. In each acquisition, the structural similarity compared to the first resting period was determined using the complex wavelet structural similarity index (CW-SSIM). Also, the pennation angle of the VL was measured. Both CW-SSIM and pennation angle were compared between fixated and freehand acquisition. Furthermore, the compression of tissue by the probe fixation was measured., Results: In fixated acquisition, a significantly higher structural similarity (p < 0.05) and an improved repeatability of pennation angle measurement were obtained compared to freehand acquisition. Probe fixation compressed muscle tissue by 12% on average., Conclusions: Quantification of the structural similarity showed an increase in FOV consistency with sonography compared to freehand acquisition. The demonstrated feasibility of long-term fixated acquisition might be attractive in many medical fields and sports, and for reduction of work-related ergonomic problems among sonographers.

Ultrasound-based 2D speckle-tracking echocardiography (US-2D-STE) is increasingly used to assess the functionality of the heart. In particular, the analysis of cardiac strain plays an important role in the identification of several cardiovascular diseases. However, this imaging technique presents some limitations associated with its operating principle that result in low accuracy and reproducibility of the measurement. In this study, an experimental framework for multimodal strain imaging in an in vitro porcine heart was developed. Specifically, the aim of this work was to analyse displacement and strain in the heart by means of 3D digital image correlation (3D-DIC) and US-2D-STE. Over a single cardiac cycle, displacement values obtained from the two techniques were in strong correlation, although systematically larger displacements were observed with 3D-DIC. Notwithstanding an absolute comparison of the strain measurements was not possible to achieve between the two methods, maximum principal strain directions computed with 3D-DIC were consistent with the longitudinal and circumferential strain distribution measured with US-2D-STE. 3D-DIC confirmed its high repeatability in quantifying displacement and strain over multiple cardiac cycles, unlike US-2D-STE which is affected by accumulated errors over time (i.e. drift). To conclude, this study demonstrates the potential of 3D-DIC to perform dynamic measurement of displacement and strain during heart deformations and supports future applications of this method in ex vivo beating heart platforms, which replicate more fully the complex contraction of the heart., (Copyright © 2019. Published by Elsevier Ltd.)

Recent studies have shown the efficacy of myocardial strain estimated using speckle tracking echocardiography (STE) in predicting response to cardiac resynchronisation therapy. This study focuses on circumferential strain patterns, comparing STE-acquired strains to tagged-magnetic resonance imaging (MRI-T). Second, the effect of regularisation was examined. Two-dimensional parasternal ultrasound (US) and MRI-T data were acquired in the left ventricular short-axis view of canines before (n = 8) and after (n = 9) left bunch branch block (LBBB) induction. US-based strain analysis was performed on Digital Imaging and Communications in Medicine data at the mid-level using three overall methods ("Commercial software," "Basic block-matching," "regularised block-matching"). Moreover, three regularisation approaches were implemented and compared. MRI-T analysis was performed using SinMod. Normalised regional circumferential strain curves, based on standard six or septal/lateral segments, were analysed and cross-correlated with MRI-T data. Systolic strain (SS) and septal rebound stretch (SRS) were calculated and compared. Overall agreement of normalised circumferential strain was good between all methods on a global and regional level. All STE methods showed a bias (≥4% strain) toward higher SS estimates. Pre-LBBB, septal and lateral segment correlation was excellent between the Basic (mean ρ = 0.96) and regularised (mean ρ = 0.97) methods and MRI-T. The Commercial method showed a significant discrepancy between the two walls (septal ρ = 0.94, lateral ρ = 0.68). Correlation with MRI-T reduced between pre- and post-LBBB (Commercial ρ = 0.79, Basic ρ = 0.82, mean regularised ρ = 0.86). Septal strain patterns and SRS varied with the STE software and type of regularisation, with all STE methods estimating non-zero SRS values pre-LBBB. Absolute values showed moderate agreement, with a bias for higher strain from STE. SRS varied with the type of software and extra regularisation applied. Open efforts are needed to understand the underlying causes of differences between STE methods before standardisation can be achieved. This is particularly important given the apparent clinical value of strain-based parameters such as SRS., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: In this study the influence of surrounding tissues including the presence of the spine on wall stress analysis and mechanical characterization of abdominal aortic aneurysms using ultrasound imaging has been investigated., Methods: Geometries of 7 AAA patients and 11 healthy volunteers were acquired using 3-D ultrasound and converted to finite element based models. Model complexity of externally unsupported (aorta-only) models was complemented with inclusion of both soft tissue around the aorta and a spine support dorsal to the aorta. Computed 3-D motion of the aortic wall was verified by means of ultrasound speckle tracking. Resulting stress, strain, and estimated shear moduli were analyzed to quantify the effect of adding surrounding material supports., Results: An improved agreement was shown between the ultrasound measurements and the finite element tissue and spine models compared to the aorta-only models. Peak and 99-percentile Von Mises stress showed an overall decrease of 23-30%, while estimated shear modulus decreased with 12-20% after addition of the soft tissue. Shear strains in the aortic wall were higher in areas close to the spine compared to the anterior region., Conclusions: Improving model complexity with surrounding tissue and spine showed a homogenization of wall stresses, reduction in homogeneity of shear strain at the posterior side of the AAA, and a decrease in estimated aortic wall shear modulus. Future research will focus on the importance of a patient-specific spine geometry and location., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Aims: Using non-invasive 3D ultrasound, peak wall stress (PWS) and aortic stiffness can be evaluated, which may provide additional criteria in abdominal aortic aneurysm (AAA) risk assessment. In this study, these measures were determined in both young and age-matched individuals, and AAA patients while its relation to age, maximum diameter, and growth was assessed statistically., Methods and Results: Time-resolved 3D-US data were acquired for 30 volunteers and 65 AAA patients. The aortic geometry was segmented, and tracked over the cardiac cycle using 3D speckle tracking to characterize the wall motion. Wall stress analysis was performed using finite element analysis. Model parameters were optimized until the model output matched the measured 3D displacements. A significant increase in aortic stiffness was measured between the age-matched volunteers [median 0.58, interquartile range (IQR) 0.48-0.71 kPa⋅m] and the small AAA patients (median 1.84, IQR 1.38-2.46 kPa⋅m; P < 0.001). In addition, an increase in aortic stiffness was evaluated between the small (30-39 mm) and large (≥50 mm) AAAs (median 2.72, IQR 1.99-3.14 kPa⋅m; P = 0.01). The 99th percentile wall stress showed a positive correlation with diameter (ρ = 0.73, P < 0.001), and significant differences between age-matched volunteers and AAA patients., Conclusion: The AAA pathology causes an early and significant increase in aortic stiffness of the abdominal aorta, even after correcting for the expected effect of ageing and differences in arterial pressure. Moreover, some AAAs revealed relatively high PWS, although the maximum diameter was below the threshold for surgical repair. Using the current method, these measures become available during follow-up, which could improve AAA rupture risk assessment.

Ultrasound noninvasive vascular elastography (NIVE) has shown its potential to measure strains of carotid arteries to predict plaque instability. When two-dimensional (2D) strain estimation is performed, either in longitudinal or cross-sectional view, only in-plane motions are considered. The motions in elevation direction (i.e. perpendicular to the imaging plane), can induce estimation artifacts affecting the accuracy of 2D NIVE. The influence of such out-of-plane motions on the performance of axial strain and axial shear strain estimations has been evaluated in this study. For this purpose, we designed a diseased carotid bifurcation phantom with a 70% stenosis and an in vitro experimental setup to simulate orthogonal out-of-plane motions of 1 mm, 2 mm and 3 mm. The Lagrangian speckle model estimator (LSME) was used to estimate axial strains and shears under pulsatile conditions. As anticipated, in vitro results showed more strain estimation artifacts with increasing magnitudes of motions in elevation. However, even with an out-of-plane motion of 2.0 mm, strain and shear estimations having inter-frame correlation coefficients higher than 0.85 were obtained. To verify findings of in vitro experiments, a clinical LSME dataset obtained from 18 participants with carotid artery stenosis was used. Deduced out-of-plane motions (ranging from 0.25 mm to 1.04 mm) of the clinical dataset were classified into three groups: small, moderate and large elevational motions. Clinical results showed that pulsatile time-varying strains and shears remained reproducible for all motion categories since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations (NCC) between radiofrequency (RF) images were above 0.93. In summary, the performance of LSME axial strain and shear estimations appeared robust in the presence of out-of-plane motions (<2 mm) as encountered during clinical ultrasound imaging.

Photoacoustic imaging (PAI) is a promising imaging modality due to its high optical specificity. However, the low signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of in vivo PA images are major challenges that prevent PAI from finding its place in clinics. This paper investigates the merit of spatial compounding of PA images in arterial phantoms and the achievable improvements of SNR, when in vivo conditions are mimicked. The analysis of the compounding technique was performed on a polyvinyl alcohol vessel phantom with black threads embedded in its wall. The in vivo conditions were mimicked by limiting the rotation range in ±30°, adding turbid surrounding medium, and filling the lumen with porcine blood. Finally, the performance of the technique was evaluated in ex vivo human carotid plaque samples. Results showed that spatial compounding elevates the SNR by 5-10 dB and CNR by 1-5 dB, depending on the location of the absorbers. This paper elucidates prospective in vivo PA characterization of carotid plaques by proposing a method to enhance PA image quality.

In recent years, novel ultrasound functional imaging (UFI) techniques have been introduced to assess cardiac function by measuring, e.g. cardiac output (CO) and/or myocardial strain. Verification and reproducibility assessment in a realistic setting remain major issues. Simulations and phantoms are often unrealistic, whereas in vivo measurements often lack crucial hemodynamic parameters or ground truth data, or suffer from the large physiological and clinical variation between patients when attempting clinical validation. Controlled validation in certain pathologies is cumbersome and often requires the use of lab animals. In this study, an isolated beating pig heart setup was adapted and used for performance assessment of UFI techniques such as volume assessment and ultrasound strain imaging. The potential of performing verification and reproducibility studies was demonstrated. For proof-of-principle, validation of UFI in pathological hearts was examined. Ex vivo porcine hearts (n  =  6, slaughterhouse waste) were resuscitated and attached to a mock circulatory system. Radio frequency ultrasound data of the left ventricle were acquired in five short axis views and one long axis view. Based on these slices, the CO was measured, where verification was performed using flow sensor measurements in the aorta. Strain imaging was performed providing radial, circumferential and longitudinal strain to assess reproducibility and inter-subject variability under steady conditions. Finally, strains in healthy hearts were compared to a heart with an implanted left ventricular assist device, simulating a failing, supported heart. Good agreement between ultrasound and flow sensor based CO measurements was found. Strains were highly reproducible (intraclass correlation coefficients  >0.8). Differences were found due to biological variation and condition of the hearts. Strain magnitude and patterns in the assisted heart were available for different pump action, revealing large changes compared to the normal condition. The setup provides a valuable benchmarking platform for UFI techniques. Future studies will include work on different pathologies and other means of measurement verification.

Objective: Vulnerable and nonvulnerable carotid artery plaques have different tissue morphology and composition that may affect plaque biomechanics. The objective of this study is to evaluate plaque vulnerability with the use of ultrasound noninvasive vascular elastography (NIVE)., Materials and Methods: Thirty-one patients (mean [± SD] age, 69 ± 7 years) with stenosis of the internal carotid artery of 50% or greater were enrolled in this cross-sectional study. Elastography parameters quantifying axial strain, shear strain, and translation motion were used to characterize carotid artery plaques as nonvulnerable, neovascularized, and vulnerable. Maximum axial strain, cumulated axial strain, mean shear strain, cumulated shear strain, cumulated axial translation, and cumulated lateral translations were measured. Cumulated measurements were summed over a cardiac cycle. The ratio of cumulated axial strain to cumulated axial translation was also evaluated. The reference method used to characterize plaques was high-resolution MRI., Results: According to MRI, seven plaques were vulnerable, 12 were nonvulnerable without neovascularity, and 12 were nonvulnerable with neovascularity (a precursor of vulnerability). The two parameters cumulated axial translation and the ratio of cumulated axial strain to cumulated axial translation could discriminate between nonvulnerable plaques and vulnerable plaques or determine the presence of neovascularity in nonvulnerable plaques (which was also possible with the mean shear strain parameter). All parameters differed between the non-vulnerable plaque group and the group that combined vulnerable plaques and plaques with neovascularity. The most discriminating parameter for the detection of vulnerable neovascularized plaques was the ratio of cumulated axial strain to cumulated axial translation (expressed as percentage per millimeter) (mean ratio, 39.30%/mm ± 12.80%/mm for nonvulnerable plaques without neovascularity vs 63.79%/mm ± 17.59%/mm for vulnerable plaques and nonvulnerable plaques with neovascularity, p = 0.002), giving an AUC value of 0.886., Conclusion: The imaging parameters cumulated axial translation and the ratio of cumulated axial strain to cumulated axial translation, as computed using NIVE, were able to discriminate vulnerable carotid artery plaques characterized by MRI from nonvulnerable carotid artery plaques. Consideration of neovascularized plaques improved the performance of NIVE. NIVE may be a valuable alternative to MRI for carotid artery plaque assessment.

Tissue growth and remodeling are essential processes that should ensure long-term functionality of tissue-engineered (TE) constructs. Even though it is widely recognized that these processes strongly depend on mechanical stimuli, the underlying mechanisms of mechanically induced growth and remodeling are only partially understood. It is generally accepted that cells sense mechanical changes and respond by altering their surroundings, by means of extracellular matrix growth and remodeling, in an attempt to return to a certain preferred mechanical homeostatic state. However, the exact mechanical cues that trigger cells to synthesize and remodel their environment remain unclear. To identify the driving mechanical stimuli of these processes, it is critical to be able to temporarily follow the mechanical state of developing tissues under physiological loading conditions. Therefore, a novel "versatile tissue growth and remodeling" (Vertigro) bioreactor was developed that is capable of tissue culture and mechanical stimulation for a prolonged time period, while simultaneously performing mechanical testing. The Vertigro's unique two-chamber design allows easy, sterile handling of circular 3D TE constructs in a dedicated culture chamber, while a separate pressure chamber facilitates a pressure-driven dynamic loading regime during culture. As a proof-of-concept, temporal changes in the mechanical state of cultured tissues were quantified using nondestructive mechanical testing by means of a classical bulge test, in which the tissue displacement was tracked using ultrasound imaging. To demonstrate the successful development of the bioreactor system, compositional, structural, and geometrical changes were qualitatively and quantitatively assessed using a series of standard analysis techniques. With this bioreactor and associated mechanical analysis technique, a powerful toolbox has been developed to quantitatively study and identify the driving mechanical stimuli of engineered tissue growth and remodeling.

Assessment of microvasculature and tissue perfusion can provide diagnostic information on local or systemic diseases. Photoacoustic (PA) imaging has strong clinical potential because of its sensitivity to hemoglobin. We used a hand-held PA probe with integrated diode lasers and examined its feasibility and validity in the detection of increasing blood volume and (sub) dermal vascularization. Blood volume detection was tested in custom-made perfusion phantoms. Results showed that an increase of blood volume in a physiological range of 1.3% to 5.4% could be detected. The results were validated with power Doppler sonography. Using a motorized scanning setup, areas of the skin were imaged at relatively short scanning times ( < 10 ?? s / cm 2 ) with PA. Three-dimensional visualization of these structures was achieved by combining the consecutively acquired cross-sectional images. Images revealed the epidermis and submillimeter vasculature up to depth of 5 mm. The geometries of imaged vasculature were validated with segmentation of the vasculature in high-frequency ultrasound imaging. This study proves the feasibility of PA imaging in its current implementation for the detection of perfusion-related parameters in skin and subdermal tissue and underlines its potential as a diagnostic tool in vascular or dermal pathologies.

Photoacoustic imaging (PAI) may have the ability to reveal the composition and the anatomical structure of carotid plaques, which determines its mechanical properties and vulnerability. We used PAI and plane wave ultrasound (PUS) imaging to obtain three-dimensional (3-D) images of endarterectomy samples ex vivo and compared the results with histology to investigate the potential of PAI-based identification of intraplaque hemorrhage. Seven carotid plaque samples were obtained from patients undergoing carotid endarterectomy and imaged with a fully integrated hand-held photoacoustic (PA) probe, consisting of a pulsed diode laser ( t pulse = 130 ?? ns , E pulse = 1 ?? mJ , ? = 808 ?? nm ) and a linear array transducer ( f c = 7.5 ?? MHz ). The samples were rotated 360 deg with 10 deg steps, and data were spatially compounded to obtain complete 3-D images of the plaques. Areas of high absorption in the 3-D datasets were identified and compared to histological data of the plaques. Data in six out of seven endarterectomy samples revealed the presence of intraplaque hemorrhages that were not visible in the PUS images. Due to the noninvasive nature of PAI, this ex vivo study may elucidate preclinical studies toward the in vivo, noninvasive, vulnerability assessment of the atherosclerotic carotid plaque.

When applying models to patient-specific situations, the impact of model input uncertainty on the model output uncertainty has to be assessed. Proper uncertainty quantification (UQ) and sensitivity analysis (SA) techniques are indispensable for this purpose. An efficient approach for UQ and SA is the generalized polynomial chaos expansion (gPCE) method, where model response is expanded into a finite series of polynomials that depend on the model input (i.e., a meta-model). However, because of the intrinsic high computational cost of three-dimensional (3D) cardiovascular models, performing the number of model evaluations required for the gPCE is often computationally prohibitively expensive. Recently, Blatman and Sudret (2010, "An Adaptive Algorithm to Build Up Sparse Polynomial Chaos Expansions for Stochastic Finite Element Analysis," Probab. Eng. Mech., 25(2), pp. 183-197) introduced the adaptive sparse gPCE (agPCE) in the field of structural engineering. This approach reduces the computational cost with respect to the gPCE, by only including polynomials that significantly increase the meta-model's quality. In this study, we demonstrate the agPCE by applying it to a 3D abdominal aortic aneurysm (AAA) wall mechanics model and a 3D model of flow through an arteriovenous fistula (AVF). The agPCE method was indeed able to perform UQ and SA at a significantly lower computational cost than the gPCE, while still retaining accurate results. Cost reductions ranged between 70-80% and 50-90% for the AAA and AVF model, respectively.

Abdominal aortic aneurysms (AAAs) are local dilations of the aorta which can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs has been widely reported in literature to predict the risk of rupture. Usually, the complete AAA geometry including the aortic bifurcation is obtained by computed tomography (CT). However, performing wall stress analysis based on 3D ultrasound (3D US) has many advantages over CT, although, the field-of-view (FOV) of 3D US is limited and the aortic bifurcation is not easily imaged. In this study, the influence of a limited FOV is examined by performing wall stress analysis on CT-based (total) AAA geometries in 10 patients, and observing the changes in 99th percentile stresses and median stresses while systematically limiting the FOV. Results reveal that changes in the 99th percentile wall stresses are less than 10% when the proximal and distal shoulders of the aneurysm are in the shortened FOV. Wall stress results show that the presence of the aortic bifurcation in the FOV does not influence the wall stresses in high stress regions. Hence, the necessity of assessing the complete FOV, including the aortic bifurcation, is of minor importance. When the proximal and distal shoulders of the AAA are in the FOV, peak wall stresses can be detected adequately., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Non-invasive assessment of the elastic properties of the arterial wall is often performed with ultrasound (US) imaging. The purpose of this study is to estimate mechanical properties of the vascular wall using in vitro inflation testing on biological tissue and two-dimensional (2-D) US elastography, and investigate the performance of the proposed methodology for physiological conditions. An inflation experiment was performed on 12 porcine aortas for (a) a large pressure range (0-140mmHg); and (b) physiological pressures (70-130mmHg) to mimic in vivo hemodynamic conditions. Two-dimensional radiofrequency (RF) data were acquired for one longitudinal and two transverse cross-sections for both experiments, and were analyzed to obtain the geometry and diameter-time behavior. The shear modulus (G) was estimated from these data for each pressure range applied. In addition, an incremental study based on the static data was performed to (1) investigate the changes in G for increasing mean arterial pressure (MAP) for a certain pressure difference (30, 40, 50 and 60mmHg); (2) compare the results with those from the dynamic experiment, for the same pressure range. The resulting stress-strain curves and shear moduli G (94±16kPa) for the static experimentare in agreement with literature and previous work. A linear dependency on MAP was found for G, yet the effect of the pulse pressure difference was negligible. The dynamic data revealed a G of 250±20kPa, whereas the incremental shear modulus (Ginc) was 240±39kPa. For all experiments, no significant differences in the values of G were found between different image planes. This study shows that 2-D US elastography of aortas during inflation testing is feasible and reproducible under controlled and physiological circumstances. In future studies, the in vivo, dynamic experiment should be repeated for a range of MAPs, and pathological vessels should be examined., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Knowledge of the intrinsic material properties of healthy and diseased arterial tissue components is of great importance in diagnostics. This study describes an in vitro comparison of 13 porcine carotid arteries using inflation testing combined with functional ultrasound and bi-axial tensile testing. The measured tissue behavior was described using both a linear, but geometrically non-linear, one-parameter (neo-Hookean) model and a two-parameter non-linear (Demiray) model. The shear modulus estimated using the linear model resulted in good agreement between the ultrasound and tensile testing methods, GUS = 25 ± 5.7 kPa and GTT = 23 ± 5.4 kPa. No significant correspondence was observed for the non-linear model aUS = 1.0 ± 2.7 kPa vs. aTT = 17 ± 8.8 kPa, p ∼ 0); however, the exponential parameters were in correspondence (bUS = 12 ± 4.2 vs. bTT = 10 ± 1.7, p > 0.05). Estimation of more complex models in vivo is cumbersome considering the sensitivity of the model parameters to small changes in measurement data and the absence of intraluminal pressure data, endorsing the use of a simple, linear model in vivo., (Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

Objective: Abdominal aortic aneurysms (AAAs) are local dilations that can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs is a novel tool that has proven high potential to improve risk stratification. Currently, wall stress analysis of AAAs is based on computed tomography (CT) and magnetic resonance imaging; however, three-dimensional (3D) ultrasound (US) has great advantages over CT and magnetic resonance imaging in terms of costs, speed, and lack of radiation. In this study, the feasibility of 3D US as input for wall stress analysis is investigated. Second, 3D US-based wall stress analysis was compared with CT-based results., Methods: The 3D US and CT data were acquired in 12 patients (diameter, 35-90 mm). US data were segmented manually and compared with automatically acquired CT geometries by calculating the similarity index and Hausdorff distance. Wall stresses were simulated at P = 140 mm Hg and compared between both modalities., Results: The similarity index of US vs CT was 0.75 to 0.91 (n = 12), with a median Hausdorff distance ranging from 4.8 to 13.9 mm, with the higher values found at the proximal and distal sides of the AAA. Wall stresses were in accordance with literature, and a good agreement was found between US- and CT-based median stresses and interquartile stresses, which was confirmed by Bland-Altman and regression analysis (n = 8). Wall stresses based on US were typically higher (+23%), caused by geometric irregularities due to the registration of several 3D volumes and manual segmentation. In future work, an automated US registration and segmentation approach is the essential point of improvement before pursuing large-scale patient studies., Conclusions: This study is a first step toward US-based wall stress analysis, which would be the modality of choice to monitor wall stress development over time because no ionizing radiation and contrast material are involved., (Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.)

Vascular elastography techniques are promising tools for mechanical characterization of diseased arteries. These techniques are usually validated with simulations or phantoms or by comparing results with histology or other imaging modalities. In the study described here, vascular elastography was applied to porcine aortas in vitro during inflation testing (n = 10) and results were compared with those of standard bi-axial tensile testing, a technique that directly measures the force applied to the tissue. A neo-Hookean model was fit to the stress-strain data, valid for large deformations. Results indicated good correspondence between the two techniques, with GUS = 110 ± 11 kPa and GTT = 108 ± 10 kPa for ultrasound and tensile testing, respectively. Bland-Altman analysis revealed little bias (GUS-GTT = 2 ± 20 kPa). The next step will be the application of a non-linear material model that is also adaptable for in vivo measurements., (Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

Ultrasound imaging can be used to estimate the morphology as well as the motion and deformation of tissues. If the interrogated tissue is actively deforming, this deformation is directly related to its function and quantification of this deformation is normally referred as 'strain imaging'. Tissue can also be deformed by applying an internal or external force and the resulting, induced deformation is a function of the mechanical tissue characteristics. In combination with the load applied, these strain maps can be used to estimate or reconstruct the mechanical properties of tissue. This technique was named 'elastography' by Ophir et al. in 1991. Elastography can be used for atherosclerotic plaque characterisation, while the contractility of the heart or skeletal muscles can be assessed with strain imaging. Rather than using the conventional video format (DICOM) image information, radio frequency (RF)-based ultrasound methods enable estimation of the deformation at higher resolution and with higher precision than commercial methods using Doppler (tissue Doppler imaging) or video image data (2D speckle tracking methods). However, the improvement in accuracy is mainly achieved when measuring strain along the ultrasound beam direction, so it has to be considered a 1D technique. Recently, this method has been extended to multiple directions and precision further improved by using spatial compounding of data acquired at multiple beam steered angles. Using similar techniques, the blood velocity and flow can be determined. RF-based techniques are also beneficial for automated segmentation of the ventricular cavities. In this paper, new developments in different techniques of quantifying cardiac function by strain imaging, automated segmentation, and methods of performing blood flow imaging are reviewed and their application in paediatric cardiology is discussed.