Strain Measurement of Abdominal Aortic Aneurysm with Real-time 3D Ultrasound Speckle Tracking

ACR Appropriateness Criteria® Screening for Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a significant vascular disease found in 4% to 8% of the screening population. If ruptured, its mortality rate is between 75% and 90%, and it accounts for up to 5% of sudden deaths in the United States. Therefore, screening of AAA while asymptomatic has been a crucial portion of preventive health care worldwide. Ultrasound of the abdominal aorta is the primary imaging modality for screening of AAA recommended for asymptomatic adults regardless of their family history or smoking history. Alternatively, duplex ultrasound and CT abdomen and pelvis without contrast may be appropriate for screening. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

In vivo bistatic dual-aperture ultrasound imaging and elastography of the abdominal aorta

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.

3D-Ultrasound Based Mechanical and Geometrical Analysis of Abdominal Aortic Aneurysms and Relationship to Growth

The heterogeneity of progression of abdominal aortic aneurysms (AAAs) is not well understood. This study investigates which geometrical and mechanical factors, determined using time-resolved 3D ultrasound (3D + t US), correlate with increased growth of the aneurysm. The AAA diameter, volume, wall curvature, distensibility, and compliance in the maximal diameter region were determined automatically from 3D + t echograms of 167 patients. Due to limitations in the field-of-view and visibility of aortic pulsation, measurements of the volume, compliance of a 60 mm long region and the distensibility were possible for 78, 67, and 122 patients, respectively. Validation of the geometrical parameters with CT showed high similarity, with a median similarity index of 0.92 and root-mean-square error (RMSE) of diameters of 3.5 mm. Investigation of Spearman correlation between parameters showed that the elasticity of the aneurysms decreases slightly with diameter (p = 0.034) and decreases significantly with mean arterial pressure (p < 0.0001). The growth of a AAA is significantly related to its diameter, volume, compliance, and surface curvature (p < 0.002). Investigation of a linear growth model showed that compliance is the best predictor for upcoming AAA growth (RMSE 1.70 mm/year). To conclude, mechanical and geometrical parameters of the maximally dilated region of AAAs can automatically and accurately be determined from 3D + t echograms. With this, a prediction can be made about the upcoming AAA growth. This is a step towards more patient-specific characterization of AAAs, leading to better predictability of the progression of the disease and, eventually, improved clinical decision making about the treatment of AAAs.

Using averaged models from 4D ultrasound strain imaging allows to significantly differentiate local wall strains in calcified regions of abdominal aortic aneurysms

Abdominal aortic aneurysms are a degenerative disease of the aorta associated with high mortality. To date, in vivo information to characterize the individual elastic properties of the aneurysm wall in terms of rupture risk is lacking. We have used time-resolved 3D ultrasound strain imaging to calculate spatially resolved in-plane strain distributions characterized by mean and local maximum strains, as well as indices of local variations in strains. Likewise, we here present a method to generate averaged models from multiple segmentations. Strains were then calculated for single segmentations and averaged models. After registration with aneurysm geometries based on CT-A imaging, local strains were divided into two groups with and without calcifications and compared. Geometry comparison from both imaging modalities showed good agreement with a root mean squared error of 1.22 ± 0.15 mm and Hausdorff Distance of 5.45 ± 1.56 mm (mean ± sd, respectively). Using averaged models, circumferential strains in areas with calcifications were 23.2 ± 11.7% (mean ± sd) smaller and significantly distinguishable at the 5% level from areas without calcifications. For single segmentations, this was possible only in 50% of cases. The areas without calcifications showed greater heterogeneity, larger maximum strains, and smaller strain ratios when computed by use of the averaged models. Using these averaged models, reliable conclusions can be made about the local elastic properties of individual aneurysm (and long-term observations of their change), rather than just group comparisons. This is an important prerequisite for clinical application and provides qualitatively new information about the change of an abdominal aortic aneurysm in the course of disease progression compared to the diameter criterion.

Fast strain mapping in abdominal aortic aneurysm wall reveals heterogeneous patterns

Abdominal aortic aneurysm patients are regularly monitored to assess aneurysm development and risk of rupture. A preventive surgical procedure is recommended when the maximum aortic antero-posterior diameter, periodically assessed on two-dimensional abdominal ultrasound scans, reaches 5.5 mm. Although the maximum diameter criterion has limited ability to predict aneurysm rupture, no clinically relevant tool that could complement the current guidelines has emerged so far. In vivo cyclic strains in the aneurysm wall are related to the wall response to blood pressure pulse, and therefore, they can be linked to wall mechanical properties, which in turn contribute to determining the risk of rupture. This work aimed to enable biomechanical estimations in the aneurysm wall by providing a fast and semi-automatic method to post-process dynamic clinical ultrasound sequences and by mapping the cross-sectional strains on the B-mode image. Specifically, the Sparse Demons algorithm was employed to track the wall motion throughout multiple cardiac cycles. Then, the cyclic strains were mapped by means of radial basis function interpolation and differentiation. We applied our method to two-dimensional sequences from eight patients. The automatic part of the analysis took under 1.5 min per cardiac cycle. The tracking method was validated against simulated ultrasound sequences, and a maximum root mean square error of 0.22 mm was found. The strain was calculated both with our method and with the established finite-element method, and a very good agreement was found, with mean differences of one order of magnitude smaller than the image spatial resolution. Most patients exhibited a strain pattern that suggests interaction with the spine. To conclude, our method is a promising tool for investigating abdominal aortic aneurysm wall biomechanics as it can provide a fast and accurate measurement of the cyclic wall strains from clinical ultrasound sequences.

Evaluation of aortic biomechanics in patients with aortic disease via imaging: A review

As a bridge between the heart and the arteries, the aorta plays an important role in the cardiovascular system. The morbidity and mortality of aortic disease are extremely high, which is a serious threat to human life. The biomechanical abnormality of the aorta is an important factor of a series of pathological changes in the aortic wall. At present, there are many imaging methods to evaluate the biomechanics of the aorta, which will benefit to the early diagnosis and treatment of aortic disease. In this review, we describe the application of various imaging methods and parameters in aortic disease.

The Evaluation of Longitudinal Strain of Large and Small Abdominal Aortic Aneurysm by Two-Dimensional Speckle-Tracking Ultrasound

OBJECTIVES

Abdominal aortic aneurysm (AAA) is a dangerous and lethal vascular disease. Non-invasive two-dimensional speckle-tracking imaging (2D STI) plays an important role in assessing aortic biomechanical properties. Our study aimed to evaluate the alterations of biomechanical characteristics using 2D STI in 91 AAA patients with different size.

METHODS

Aneurysm strain, elastic modulus, stiffness index β, and aortic distensibility determined by M-Mode ultrasound (US), and longitudinal strain (LS) derived from 2D STI were compared in 40 large AAA patients (diameter ≥ 55 mm) and 51 small AAA patients (diameter < 55 mm).

RESULTS

Compared with small AAA group, anterior wall longitudinal strain (ALS) and posterior wall longitudinal strain (PLS) were significantly decreased in large AAA group (all P < .05) and not affected by age, symptom, hypertension, and thrombus. Meanwhile, ALS and PLS correlated negatively with maximal aneurysm diameters (r = -0.628 and -0.469, respectively, all P < .001). And only ALS was associated with M-Mode US parameters (all P < .05). Based on receiver operating characteristic (ROC) analysis, ALS and PLS had strong diagnostic values for large AAA with the area under the curve (AUC) of 0.82 and 0.72, and cut-off points of 1.71 and 1.64% with a sensitivity of 78 and 72%, and a specificity of 75 and 70%, respectively.

CONCLUSIONS

LS measured by 2D STI could evaluate the biomechanical properties of aneurysm wall with different size, and add additional diagnostic value in distinguishing between small and large AAA.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

Multiperspective Bistatic Ultrasound Imaging and Elastography of the Ex Vivo Abdominal Aorta

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.

Intra- and Interobserver Variability of 4D Ultrasound Examination of the Infrarenal Aorta

OBJECTIVES

The four-dimensional ultrasound (4D-US) enables imaging of the aortic segment and simultaneous determination of the wall expansion. The method shows a high spatial and temporal resolution, but its in vivo reliability is so far unknown for low-measure values. The present study determines the intraobserver repeatability and interobserver reproducibility of 4D-US in the atherosclerotic and non-atherosclerotic infrarenal aorta.

METHODS

In all, 22 patients with non-aneurysmal aorta were examined by an experienced examiner and a medical student. After registration of 4D images, both the examiners marked the aortic wall manually before the commercially implemented speckle tracking algorithm was applied. The cyclic changes of the aortic diameter and circumferential strain were determined with the help of custom-made software. The reliability of 4D-US was tested by the intraclass correlation coefficient (ICC).

RESULTS

The 4D-US measurements showed very good reliability for the maximum aortic diameter and the circumferential strain for all patients and for the non-atherosclerotic aortae (ICC >0.7), but low reliability for circumferential strain in calcified aortae (ICC = 0.29). The observer- and masking-related variances for both maximum diameter and circumferential strain were close to zero.

CONCLUSIONS

Despite the low-measured values, the high spatial and temporal resolution of the 4D-US enables a reliable evaluation of cyclic diameter changes and circumferential strain in non-aneurysmal aortae independent from the observer experience but with some limitations for calcified aortae. The 4D-US opens up a new perspective with regard to noninvasive, in vivo assessment of kinematic properties of the vessel wall in the abdominal aorta.

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Blood flow rate in dialysis (vascular) access is the key parameter to examine patency and to evaluate the outcomes of various endovascular interve7ntions. While angiography is extensively used for dialysis access–salvage procedures, to date, there is no image-based blood flow measurement application commercially available in the angiography suite. We aim to calculate the blood flow rate in the dialysis access based on cine-angiographic and fluoroscopic image sequences. In this study, we discuss image-based methods to quantify access blood flow in a flow phantom model. Digital subtraction angiography (DSA) and fluoroscopy were used to acquire images at various sampling rates (DSA—3 and 6 frames/s, fluoroscopy—4 and 10 pulses/s). Flow rates were computed based on two bolus tracking algorithms, peak-to-peak and cross-correlation, and modeled with three curve-fitting functions, gamma variate, lagged normal, and polynomial, to correct errors with transit time measurement. Dye propagation distance and the cross-sectional area were calculated by analyzing the contrast enhancement in the vessel. The calculated flow rates were correlated versus an in-line flow sensor measurement. The cross-correlation algorithm with gamma-variate curve fitting had the best accuracy and least variability in both imaging modes. The absolute percent error (mean ± SEM) of flow quantification in the DSA mode at 6 frames/s was 21.4 ± 1.9%, and in the fluoroscopic mode at 10 pulses/s was 37.4 ± 3.6%. The radiation dose varied linearly with the sampling rate in both imaging modes and was substantially low to invoke any tissue reactions or stochastic effects. The cross-correlation algorithm and gamma-variate curve fitting for DSA acquisition at 6 frames/s had the best correlation with the flow sensor measurements. These findings will be helpful to develop a software-based vascular access flow measurement tool for the angiography suite and to optimize the imaging protocol amenable for computational flow applications.

Quantitative Evaluation of Mechanical Stimulation for Tissue-Engineered Blood Vessels

Functional small-diameter tissue-engineered blood vessels (TEBVs) have been developed in silico using biodegradable polymeric scaffolds under pulsatile perfusion. Accurate simulation of physiological mechanical stimulations in vitro is a crucial factor in vascular engineering. However, little is known about the patterns of mechanical stimulation on silicone tubes. This study aimed to determine the optimal mechanical conditions required for inducing circumferential deformations in silicone tubes during in vitro vascular development under pulsatile perfusion. For this purpose, we established a data acquisition (DAQ) system with a laser micrometer and pressure transducers to evaluate changes in the diameter of silicone tubes in response to pulsatile flow and validated the results on cultured TEBVs. The established DAQ system showed satisfactory reproducibility for measuring diameter variation in the in silico model. Furthermore, the hardness and thickness of the silicone tubes affected the mechanical conditioning in the three-dimensional culture system under different working pressures, frequencies, and circumferential deformations. We demonstrated a simple and reliable approach to quantify the circumferential strain and deformations to ensure optimal mechanical stimulation of the cultured TEBVs under pulsatile perfusion. Based on the results, we were able to dynamically culture dense cellularized small-diameter TEBVs. This study highlights the importance of mechanical stimulation in vascular tissue engineering. Impact statement This study demonstrated a direct and noncontact data acquisition system for quantifying the strain on the supporting silicone medium during three-dimensional tissue-engineered blood vessel culture, which can help optimize the mechanical parameters for vascular tissue engineering.

Displacement Imaging During Focused Ultrasound Median Nerve Modulation: A Preliminary Study in Human Pain Sensation Mitigation

Focused ultrasound (FUS)-based viscoelastic imaging techniques using high frame rate (HFR) ultrasound to track tissue displacement can be used for mechanistic monitoring of FUS neuromodulation. However, a majority of techniques avoid imaging during the active push transmit (interleaved or postpush acquisitions) to mitigate ultrasound interference, which leads to missing temporal information of ultrasound effects when FUS is being applied. Furthermore, critical for clinical translation, use of both axial steering and real-time (<1 s) capabilities for optimizing acoustic parameters for tissue engagement are largely missing. In this study, we describe a method of noninterleaved, single Vantage imaging displacement within an active FUS push with simultaneous axial steering and real-time capabilities using a single ultrasound acquisition machine. Results show that the pulse sequence can track micron-sized displacements using frame rates determined by the calculated time-of-flight (TOF), without interleaving the FUS pulses and imaging acquisition. Decimation by 3-7 frames increases signal-to-noise ratio (SNR) by 15.09±7.03 dB. Benchmarking tests of CUDA-optimized code show increase in processing speed of 35- and 300-fold in comparison with MATLAB parallel processing GPU and CPU functions, respectively, and we can estimate displacement from steered push beams ±10 mm from the geometric focus. Preliminary validation of displacement imaging in humans shows that the same driving pressures led to variable nerve engagement, demonstrating important feedback to improve transducer coupling, FUS incident angle, and targeting. Regarding the use of our technique for neuromodulation, we found that FUS altered thermal perception of thermal pain by 0.9643 units of pain ratings in a single trial. Additionally, 5 [Formula: see text] of nerve displacement was shown in on-target versus off-target sonications. The initial feasibility in healthy volunteers warrants further study for potential clinical translation of FUS for pain suppression.

Assessing Patient-Specific Mechanical Properties of Aortic Wall and Peri-Aortic Structures From In Vivo DENSE Magnetic Resonance Imaging Using an Inverse Finite Element Method and Elastic Foundation Boundary Conditions

The establishment of in vivo, noninvasive patient-specific, and regionally resolved techniques to quantify aortic properties is key to improving clinical risk assessment and scientific understanding of vascular growth and remodeling. A promising and novel technique to reach this goal is an inverse finite element method (FEM) approach that utilizes magnetic resonance imaging (MRI)-derived displacement fields from displacement encoding with stimulated echoes (DENSE). Previous studies using DENSE MRI suggested that the infrarenal abdominal aorta (IAA) deforms heterogeneously during the cardiac cycle. We hypothesize that this heterogeneity is driven in healthy aortas by regional adventitial tethering and interaction with perivascular tissues, which can be modeled with elastic foundation boundary conditions (EFBCs) using a collection of radially oriented springs with varying stiffness with circumferential distribution. Nine healthy IAAs were modeled using previously acquired patient-specific imaging and displacement fields from steady-state free procession (SSFP) and DENSE MRI, followed by assessment of aortic wall properties and heterogeneous EFBC parameters using inverse FEM. In contrast to traction-free boundary condition, prescription of EFBC reduced the nodal displacement error by 60% and reproduced the DENSE-derived heterogeneous strain distribution. Estimated aortic wall properties were in reasonable agreement with previously reported experimental biaxial testing data. The distribution of normalized EFBC stiffness was consistent among all patients and spatially correlated to standard peri-aortic anatomical features, suggesting that EFBC could be generalized for human adults with normal anatomy. This approach is computationally inexpensive, making it ideal for clinical research and future incorporation into cardiovascular fluid-structure analyses.

The use of ultrasound to assess aortic biomechanics: Implications for aneurysm and dissection

Arterial stiffening, which occurs when conduit arteries thicken and lose elasticity, has been associated with cardiovascular disease and increased risk for future cardiovascular events. Specifically, aortic stiffening plays a large role in the pathogenesis of vascular diseases, such as aneurysm formation and dissection. Current parameters used to assess risk of aortic rupture include absolute diameter and growth rate. However, these properties lack the reliability required to accurately risk-stratify patients. As with any elastic conduit, it is important to assess the biomechanical properties of the aorta in order to assess cardiovascular risk and prevent disease progression. There are several invasive and noninvasive methods by which stiffness of the large arteries can be assessed. Of particular interest are ultrasound-based methods, such as tissue Doppler imaging and speckle-tracking echocardiography, due to their noninvasive and feasible nature. In this review, we summarize studies demonstrating utility of noninvasive ultrasound imaging methods for measuring aortic biomechanics for the assessment and management of aortic aneurysms.

High-frequency murine ultrasound provides enhanced metrics of BAPN-induced AAA growth

An abdominal aortic aneurysm (AAA), defined as a pathological expansion of the largest artery in the abdomen, is a common vascular disease that frequently leads to death if rupture occurs. Once diagnosed, clinicians typically evaluate the rupture risk based on maximum diameter of the aneurysm, a limited metric that is not accurate for all patients. In this study, we worked to evaluate additional distinguishing factors between growing and stable murine aneurysms toward the aim of eventually improving clinical rupture risk assessment. With the use of a relatively new mouse model that combines surgical application of topical elastase to cause initial aortic expansion and a lysyl oxidase inhibitor, β-aminopropionitrile (BAPN), in the drinking water, we were able to create large AAAs that expanded over 28 days. We further sought to develop and demonstrate applications of advanced imaging approaches, including four-dimensional ultrasound (4DUS), to evaluate alternative geometric and biomechanical parameters between 1) growing AAAs, 2) stable AAAs, and 3) nonaneurysmal control mice. Our study confirmed the reproducibility of this murine model and found reduced circumferential strain values, greater tortuosity, and increased elastin degradation in mice with aneurysms. We also found that expanding murine AAAs had increased peak wall stress and surface area per length compared with stable aneurysms. The results from this work provide clear growth patterns associated with BAPN-elastase murine aneurysms and demonstrate the capabilities of high-frequency ultrasound. These data could help lay the groundwork for improving insight into clinical prediction of AAA expansion.NEW & NOTEWORTHY This work characterizes a relatively new murine model of abdominal aortic aneurysms (AAAs) by quantifying vascular strain, stress, and geometry. Furthermore, Green-Lagrange strain was calculated with a novel mapping approach using four-dimensional ultrasound. We also compared growing and stable AAAs, finding peak wall stress and surface area per length to be most indicative of growth. In all AAAs, strain and elastin health declined, whereas tortuosity increased.

Updates on Ultrasonography Imaging in Abdominal Aortic Aneurysm

Abdominal aortic aneurysms (AAAs) are life-threatening and are associated with >80% mortality when they rupture. Therefore, detecting these aneurysms before they rupture is critical. Ultrasonography is a non-invasive tool that is used for screening AAAs by measuring abdominal aorta diameter. A recent meta-analysis demonstrated the positive effects of ultrasonography. To date, aneurysm diameter is the most reliable predictor for aneurysm rupture and is used as a criterion for surgical intervention. However, some AAAs rupture at small diameters. Therefore, a better predictor for AAA rupture that is independent of aneurysm diameter is needed. Recently, an aortic wall strain examined using ultrasonography has been reported to have a potential in predicting AAA rupture. Since the introduction of endovascular aneurysm repair (EVAR), a paradigm shift has occurred in the management of AAAs. EVAR is broadly spread with the advantage of early favorable results but with concerning endoleak complications. At present, computed tomography angiography (CTA) is considered to be a gold standard for surveillance following EVAR, but it encounters some problems, such as contrast usage or radiation exposure. Ultrasonography offers an examination free from these problems and can this be an alternative to CTA. In this review article, current trends and new technologies regarding AAA assessment using ultrasonography are introduced.

Validation of the Strain Assessment of a Phantom of Abdominal Aortic Aneurysm: Comparison of Results Obtained From Magnetic Resonance Imaging and Stereovision Measurements

Predicting aortic aneurysm ruptures is a complex problem that has been investigated by many research teams over several decades. Work on this issue is notably complex and involves both the mechanical behavior of the artery and the blood flow. Magnetic resonance imaging (MRI) can provide measurements concerning the shape of an organ and the blood that flows through it. Measuring local distortion of the artery wall is the first essential factor to evaluate in a ruptured artery. This paper aims to demonstrate the feasibility of this measure using MRI on a phantom of an abdominal aortic aneurysm (AAA) with realistic shape. The aortic geometry is obtained from a series of cine-MR images and reconstructed using Mimics software. From 4D flow and MRI measurements, the field of velocity is determined and introduced into a computational fluid dynamic (CFD) model to determine the mechanical boundaries applied on the wall artery (pressure and ultimately wall shear stress (WSS)). These factors are then converted into a solid model that enables wall deformations to be calculated. This approach was applied to a silicone phantom model of an AAA reconstructed from a patient's computed tomography-scan examination. The calculated deformations were then compared to those obtained in identical conditions by stereovision. The results of both methods were found to be close. Deformations of the studied AAA phantom with complex shape were obtained within a gap of 12% by modeling from MR data.

A novel vision-based system for quantitative analysis of abdominal aortic aneurysm deformation

BACKGROUND

In clinical diagnostics, combination of different imaging techniques is applied to assess spatial configuration of the abdominal aortic aneurysm (AAA) and deformation of its wall. As deformation of aneurysm wall is crucial parameter in assessing wall rupture, we aimed to develop and validate a Non-Invasive Vision-Based System (NIVBS) for the analysis of 3D elastic artificial abdominal aortic models. 3D-printed elastic AAA models from four patients were applied for the reconstruction of real hemodynamic. During experiments, the inlet boundary conditions included the injection volume and frequency of pulsation averaged from electrocardiography traces. NIVBS system was equipped with nine cameras placed at a constant distance to record wall movement from 360^o angle and a dedicated set of artificial lights providing coherent illumination. Additionally, self-prepared algorithms for image acquisition, processing, segmentation, and contour detection were used to analyze wall deformation. Finally, the shape deformation factor was applied to evaluate aorta's deformation. Experimental results were confronted with medical data from AngioCT and 2D speckle-tracking echocardiography (2DSTE).

RESULTS

Image square analyses indicated that the optimal distance between the camera's lens and the investigated object was in the range of 0.30-0.35 m. There was approximately 1.44% difference observed in aneurysm diameters between NIVBS (86.57 ± 5.86 mm) and AngioCT (87.82 ± 6.04 mm) (p = 0.7764). The accuracy of developed algorithm for the reconstruction of the AAA deformation was equal to 98.56%. Bland-Altman analysis showed that the difference between clinical data (2DSTE) and predicted wall deformation (NIVBS) for all patients was 0.00 mm (confidence interval equal to 0.12 mm) for aneurysm size, 0.01 mm (confidence interval equal to 0.13 mm) and 0.00 mm (confidence interval equal to 0.09 mm) for the anterior and posterior side, as well as 0.01 mm (confidence interval equal to 0.18 mm) and 0.01 mm (confidence interval equal to 0.11 mm) for the left and right side. The optimal range of camera's lens did not affect acquired values.

CONCLUSIONS

The NIVBS with proposed algorithm that reconstructs the pressure from surrounding organs is appropriate to analyze the AAAs in water environment. Moreover, NIVBS allowed detailed quantitative analysis of aneurysm sac wall deformation.

Experimental mechanical strain measurement of tissues

Strain, an important biomechanical factor, occurs at different scales from molecules and cells to tissues and organs in physiological conditions. Under mechanical strain, the strength of tissues and their micro- and nanocomponents, the structure, proliferation, differentiation and apoptosis of cells and even the cytokines expressed by cells probably shift. Thus, the measurement of mechanical strain (i.e., relative displacement or deformation) is critical to understand functional changes in tissues, and to elucidate basic relationships between mechanical loading and tissue response. In the last decades, a great number of methods have been developed and applied to measure the deformations and mechanical strains in tissues comprising bone, tendon, ligament, muscle and brain as well as blood vessels. In this article, we have reviewed the mechanical strain measurement from six aspects: electro-based, light-based, ultrasound-based, magnetic resonance-based and computed tomography-based techniques, and the texture correlation-based image processing method. The review may help solving the problems of experimental and mechanical strain measurement of tissues under different measurement environments.

A Methodology for the Derivation of Unloaded Abdominal Aortic Aneurysm Geometry With Experimental Validation

In this work, we present a novel method for the derivation of the unloaded geometry of an abdominal aortic aneurysm (AAA) from a pressurized geometry in turn obtained by 3D reconstruction of computed tomography (CT) images. The approach was experimentally validated with an aneurysm phantom loaded with gauge pressures of 80, 120, and 140 mm Hg. The unloaded phantom geometries estimated from these pressurized states were compared to the actual unloaded phantom geometry, resulting in mean nodal surface distances of up to 3.9% of the maximum aneurysm diameter. An in-silico verification was also performed using a patient-specific AAA mesh, resulting in maximum nodal surface distances of 8 μm after running the algorithm for eight iterations. The methodology was then applied to 12 patient-specific AAA for which their corresponding unloaded geometries were generated in 5-8 iterations. The wall mechanics resulting from finite element analysis of the pressurized (CT image-based) and unloaded geometries were compared to quantify the relative importance of using an unloaded geometry for AAA biomechanics. The pressurized AAA models underestimate peak wall stress (quantified by the first principal stress component) on average by 15% compared to the unloaded AAA models. The validation and application of the method, readily compatible with any finite element solver, underscores the importance of generating the unloaded AAA volume mesh prior to using wall stress as a biomechanical marker for rupture risk assessment.

Cyclic three-dimensional wall motion of the human ascending and abdominal aorta characterized by time-resolved three-dimensional ultrasound speckle tracking

The aim of this study was to measure, characterize, and compare the time-resolved three-dimensional wall kinematics of the ascending and the abdominal aorta. Comprehensive description of aortic wall kinematics is an important issue for understanding its physiological functioning and early detection of adverse changes. Data on the three-dimensional, dynamic cyclic deformation of the aorta in vivo are scarce. Either most imaging techniques available are too slow to capture aortic wall motion (CT, MRI) or they do not provide three-dimensional geometry data. Three-dimensional volume data sets of ascending and abdominal aortae of male healthy subjects (25.5 [24.5, 27.5] years) were acquired by use of a commercial echocardiography system with a temporal resolution of 11-25 Hz. Longitudinal and circumferential strain, twist, and relative volume change were determined by use of a commercial speckle tracking algorithm and in-house software. The kinematics of the abdominal aorta is characterized by diameter change, almost constant length and unidirectional, either clockwise or counter clockwise twist. In contrast, the ascending aorta undergoes a complex deformation with alternating clockwise and counterclockwise twist. Length and diameter changes were in the same order of magnitude with a phase shift between both. Longitudinal strain and its phase shift to circumferential strain contribute to the proximal aorta's Windkessel function. Complex cyclic deformations are known to be highly fatiguing. This may account for increased degradation of components of the aortic wall and therefore promote aortic dissection or aneurysm formation.

A finite element updating approach for identification of the anisotropic hyperelastic properties of normal and diseased aortic walls from 4D ultrasound strain imaging

Computational analysis of the biomechanics of the vascular system aims at a better understanding of its physiology and pathophysiology and eventually at diagnostic clinical use. Because of great inter-individual variations, such computational models have to be patient-specific with regard to geometry, material properties and applied loads and boundary conditions. Full-field measurements of heterogeneous displacement or strain fields can be used to improve the reliability of parameter identification based on a reduced number of observed load cases as is usually given in an in vivo setting. Time resolved 3D ultrasound combined with speckle tracking (4D US) is an imaging technique that provides full field information of heterogeneous aortic wall strain distributions in vivo. In a numerical verification experiment, we have shown the feasibility of identifying nonlinear and orthotropic constitutive behaviour based on the observation of just two load cases, even though the load free geometry is unknown, if heterogeneous strain fields are available. Only clinically available 4D US measurements of wall motion and diastolic and systolic blood pressure are required as input for the inverse FE updating approach. Application of the developed inverse approach to 4D US data sets of three aortic wall segments from volunteers of different age and pathology resulted in the reproducible identification of three distinct and (patho-) physiologically reasonable constitutive behaviours. The use of patient-individual material properties in biomechanical modelling of AAAs is a step towards more personalized rupture risk assessment.

Ultrasound-guided therapeutic focused ultrasound: current status and future directions

This paper reviews ultrasound imaging methods for the guidance of therapeutic focused ultrasound (USgFUS), with emphasis on real-time preclinical methods. Guidance is interpreted in the broadest sense to include pretreatment planning, siting of the FUS focus, real-time monitoring of FUS-tissue interactions, and real-time control of exposure and damage assessment. The paper begins with an overview and brief historical background of the early methods used for monitoring FUS-tissue interactions. Current imaging methods are described, and discussed in terms of sensitivity and specificity of the localisation of the FUS effects in both therapeutic and sub-therapeutic modes. Thermal and non-thermal effects are considered. These include cavitation-enhanced heating, tissue water boiling and cavitation. Where appropriate, USgFUS methods are compared with similar methods implemented using other guidance modalities, e.g. magnetic resonance imaging. Conclusions are drawn regarding the clinical potential of the various guidance methods, and the feasibility and current status of real-time implementation.

Imaging and finite element analysis: a methodology for non-invasive characterization of aortic tissue

Characterization of the mechanical properties of arterial tissues usually involves an invasive procedure requiring tissue removal. In this work we propose a non-invasive method to perform a biomechanical analysis of cardiovascular aortic tissue. This method is based on combining medical imaging and finite element analysis (FEA). Magnetic resonance imaging (MRI) was chosen since it presents relatively low risks for human health. A finite element model was created from the MRI images and loaded with systolic physiological pressures. By means of an optimization routine, the structural material properties were changed until average strains matched those measured by MRI. The method outlined in this work produced an estimate of the in situ properties of cardiovascular tissue based on non-invasive image datasets and finite element analysis.

Strain analysis of wall motion in abdominal aortic aneurysms

OBJECTIVE

In this exploratory study, we used ultrasound speckle-tracking methods, originally used for analyzing cardiac wall motion, to evaluate aortic wall motion.

MATERIALS AND METHODS

We compared 19 abdominal aortic aneurysm (AAA) patients with 10 healthy volunteers (diameter, 48 mm vs. 15 mm). Motion pictures of the axial view of the aneurysm using ultrasonography were analyzed. Circumferential strain and strain rate at 6 equally divided segments of the aorta were semiautomatically calculated. We termed 'peak' strain and strain rate as the maximum of strain and strain rate in a cardiac cycle for each segment. We also evaluated the coefficient of variation of peak strain rate for the six segments.

RESULTS

In the aneurysm and control groups, the mean values of peak strain along the 6 segments were 1.5% ± 0.6% vs. 4.7% ± 1.6% (p <0.0001), respectively. The coefficient of variation of the peak strain rate was higher in the AAA group (0.74 ± 0.20) than in the control group (0.56 ± 0.12; p <0.05).

CONCLUSIONS

Aortic wall compliance decreased in the more atherosclerotic AAA group. The higher relative dispersion of strain rates in the AAA group is indicative of the inhomogeneous movement of the aortic wall.

In vivo determination of elastic properties of the human aorta based on 4D ultrasound data

Computational analysis of the biomechanics of the vascular system aims at a better understanding of its physiology and pathophysiology. To be of clinical use, however, these models and thus their predictions, have to be patient specific regarding geometry, boundary conditions and material. In this paper we present an approach to determine individual material properties of human aortae based on a new type of in vivo full field displacement data acquired by dimensional time resolved three dimensional ultrasound (4D-US) imaging. We developed a nested iterative Finite Element Updating method to solve two coupled inverse problems: The prestrains that are present in the imaged diastolic configuration of the aortic wall are determined. The solution of this problem is integrated in an iterative method to identify the nonlinear hyperelastic anisotropic material response of the aorta to physiologic deformation states. The method was applied to 4D-US data sets of the abdominal aorta of five healthy volunteers and verified by a numerical experiment. This non-invasive in vivo technique can be regarded as a first step to determine patient individual material properties of the human aorta.