In vivo quantification of regional circumferential Green strain in the thoracic and abdominal aorta by 2D spiral cine DENSE MRI

Correction of phase offset errors and quantification of background noise, signal-to-noise ratio, and encoded-displacement uncertainty on DENSE MRI for kinematics of the descending thoracic and abdominal aorta

Displacement encoding with stimulated echoes (DENSE) MRI is a phase contrast technique that allows the encoding of tissue displacement into the phase of the magnetic resonance signal. Recent developments in this technique allow the imaging of relatively thin structures such as the aortic wall. Quantifying background noise associated to DENSE MRI is required to assess the uncertainty of derived displacement measurements and for the design and implementation of adequate noise-reduction techniques. Although noise and error management of cardiac DENSE MRI has been previously studied, developments for aortic applications are scarce. Herein, we evaluate the noise and uncertainty of DENSE MRI scans at three different locations along the descending aorta: the distal aortic arch (DAA), the descending thoracic aorta (DTA), and infrarenal abdominal aorta (IAA). Additionally, we analyze three datasets from in vitro validation experiments with polyvinyl alcohol phantoms. We implement and evaluate the effectiveness of an offset-error correction algorithm and noise filtering techniques on DENSE MRI for aortic motion applications. Our results show that the phase signal of pixels composing the static background was normally distributed, centered on average at 0.003 ± 0.02 rad and - 0.02 ± 0.024 rad for each phase directions, suggesting that background noise is random, isotropic, and DENSE MRI has little offset errors. However, background signal noise significantly increased with elapsed time of the cardiac cycle; and was spatially heterogeneous consistently increased towards the anterior space. Background noise showed no significant differences between the 3 aortic locations and the in vitro experiments. However, SNR depended on the displacement of the region of interest, in consequence it was found significantly larger at DAA (16.7 ± 8.5, p = 0.003) and DTA (15.4 ± 7.6, p = 0.008) than at the IAA (8.0 ± 4.1), but not significantly different than the SNR of in vitro experiments (8.0 ± 3.7), and had an overall average of 13 ± 7. The applied methods significantly reduced the offset error and effect of noise on the estimation of encoded displacements. Finally, this analysis suggests that the implemented DENSE MRI protocol is adequate to assess the motion of healthy human aortas. However, the relative effect of noise increased considerably on the analysis of an ageing or diseased aortas with impaired mobility, calling for further analyses on pathologically stiffened aortas.

Quantification of the heterogeneous effect of static and dynamic perivascular structures on patient-specific local aortic wall mechanics using inverse finite element modeling and DENSE MRI

Recent studies have highlighted the relevance of perivascular interactions on aortic wall mechanics. Most of the approaches assume static perivascular structures; however, the beating heart dynamically displaces the neighboring aorta. We develop a model to account for the effect of periaortic interactions due to static and dynamic structures by prescribing a moving elastic foundation boundary condition (EFBC) embedded into an inverse finite element algorithm using in vivo displacements from 2D displacement encoding with stimulated echoes (DENSE) MRI as target data. We applied this method at three different locations of interest, the distal aortic arch (DAA), descending thoracic aorta (DTA), and infrarenal abdominal aorta (IAA) for a total of 27 cases in healthy humans. The model reproduces the target diastole-to-systole deformation and bulk displacement of the aortic wall with median displacement errors below 0.5mm. The EFBC showed good agreement with the location of anatomical features and was consistent among individuals of similar characteristics. Results show that an energy source acting on the adventitia is required to reproduce the displacements measured at the vicinity of the heart, but not at the abdomen. The average adventitial load as a percentage of the luminal pulse-pressure was found to increase with age and to decrease along the descending aorta, from 61% at the DAA to 37% at the DTA, and 30% at the IAA. This approach offers a patient-specific method to estimate in vivo adventitial loads and aortic wall stiffness, which can bring a better understanding of normal and pathological in vivo aortic function.

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.

Multiparametric MRI identifies subtle adaptations for demarcation of disease transition in murine aortic valve stenosis

Aortic valve stenosis (AS) is the most frequent valve disease with relevant prognostic impact. Experimental model systems for AS are scarce and comprehensive imaging techniques to simultaneously quantify function and morphology in disease progression are lacking. Therefore, we refined an acute murine AS model to closely mimic human disease characteristics and developed a high-resolution magnetic resonance imaging (MRI) approach for simultaneous in-depth analysis of valvular, myocardial as well as aortic morphology/pathophysiology to identify early changes in tissue texture and critical transition points in the adaptive process to AS. AS was induced by wire injury of the aortic valve. Four weeks after surgery, cine loops, velocity, and relaxometry maps were acquired at 9.4 T to monitor structural/functional alterations in valve, aorta, and left ventricle (LV). In vivo MRI data were subsequently validated by histology and compared to echocardiography. AS mice exhibited impaired valve opening accompanied by significant valve thickening due to fibrotic remodelling. While control mice showed bell-shaped flow profiles, AS resulted not only in higher peak flow velocities, but also in fragmented turbulent flow patterns associated with enhanced circumferential strain and an increase in wall thickness of the aortic root. AS mice presented with a mild hypertrophy but unaffected global LV function. Cardiac MR relaxometry revealed reduced values for both T1 and T2 in AS reflecting subtle myocardial tissue remodelling with early alterations in mitochondrial function in response to the enhanced afterload. Concomitantly, incipient impairments of coronary flow reserve and myocardial tissue integrity get apparent accompanied by early troponin release. With this, we identified a premature transition point with still compensated cardiac function but beginning textural changes. This will allow interventional studies to explore early disease pathophysiology and novel therapeutic targets.

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.

Recent Advances in Biomechanical Characterization of Thoracic Aortic Aneurysms

Thoracic aortic aneurysm (TAA) is a focal enlargement of the thoracic aorta, but the etiology of this disease is not fully understood. Previous work suggests that various genetic syndromes, congenital defects such as bicuspid aortic valve, hypertension, and age are associated with TAA formation. Though occurrence of TAAs is rare, they can be life-threatening when dissection or rupture occurs. Prevention of these adverse events often requires surgical intervention through full aortic root replacement or implantation of endovascular stent grafts. Currently, aneurysm diameters and expansion rates are used to determine if intervention is warranted. Unfortunately, this approach oversimplifies the complex aortopathy. Improving treatment of TAAs will likely require an increased understanding of the biological and biomechanical factors contributing to the disease. Past studies have substantially contributed to our knowledge of TAAs using various ex vivo, in vivo, and computational methods to biomechanically characterize the thoracic aorta. However, any singular approach typically focuses on only material properties of the aortic wall, intra-aneurysmal hemodynamics, or in vivo vessel dynamics, neglecting combinatorial factors that influence aneurysm development and progression. In this review, we briefly summarize the current understanding of TAA causes, treatment, and progression, before discussing recent advances in biomechanical studies of TAAs and possible future directions. We identify the need for comprehensive approaches that combine multiple characterization methods to study the mechanisms contributing to focal weakening and rupture. We hope this summary and analysis will inspire future studies leading to improved prediction of thoracic aneurysm progression and rupture, improving patient diagnoses and outcomes.

Assessment of the regional distribution of normalized circumferential strain in the thoracic and abdominal aorta using DENSE cardiovascular magnetic resonance

BACKGROUND

Displacement Encoding with Stimulated Echoes (DENSE) cardiovascular magnetic resonance (CMR) of the aortic wall offers the potential to improve patient-specific diagnostics and prognostics of diverse aortopathies by quantifying regionally heterogeneous aortic wall strain in vivo. However, before regional mapping of strain can be used to clinically assess aortic pathology, an evaluation of the natural variation of normal regional aortic kinematics is required.

METHOD

Aortic spiral cine DENSE CMR was performed at 3 T in 30 healthy adult subjects (range 18 to 65 years) at one or more axial locations that are at high risk for aortic aneurysm or dissection: the infrarenal abdominal aorta (IAA, n = 11), mid-descending thoracic aorta (DTA, n = 17), and/or distal aortic arch (DAA, n = 11). After implementing custom noise-reduction techniques, regional circumferential Green strain of the aortic wall was calculated across 16 sectors around the aortic circumference at each location and normalized by the mean circumferential strain for comparison between individuals.

RESULTS

The distribution of normalized circumferential strain (NCS) was heterogeneous for all locations evaluated. Despite large differences in mean strain between subjects, comparisons of NCS revealed consistent patterns of strain distribution for similar groupings of patients by axial location, age, and/or mean displacement angle. NCS at local systole was greatest in the lateral/posterolateral walls in the IAAs (1.47 ± 0.27), medial wall in anteriorly displacing DTAs (1.28 ± 0.20), lateral wall in posteriorly displacing DTAs (1.29 ± 0.29), superior curvature in DAAs < 50 years-old (1.93 ± 0.22), and medial wall in DAAs > 50 years (2.29 ± 0.58). The distribution of strain was strongly influenced by the location of the vertebra and other surrounding structures unique to each location.

CONCLUSIONS

Regional in vivo circumferential strain in the adult aorta is unique to each axial location and heterogeneous around its circumference, but can be grouped into consistent patterns defined by basic patient-specific metrics following normalization. The heterogeneous strain distributions unique to each group may be due to local peri-aortic constraints (particularly at the aorto-vertebral interface), heterogeneous material properties, and/or heterogeneous flow patterns. These results must be carefully considered in future studies seeking to clinically interpret or computationally model patient-specific aortic kinematics.