Heart motion adapted cine phase-contrast flow measurements through the aortic valve

Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast

PURPOSE

Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automated valve-tracking 2D method for measuring flow through the dynamic tricuspid valve.

METHODS

Nine healthy subjects and 2 patients were imaged. The approach uses a previously trained deep learning network, TVnet, to automatically track the tricuspid valve plane from long-axis cine images. Subsequently, the tracking information is used to acquire 2D phase contrast (PC) with a dynamic (moving) acquisition plane that tracks the valve. Direct diastolic net flows evaluated from the dynamic PC sequence were compared with flows from 2D-PC scans acquired in a static slice localized at the end-systolic valve position, and also ventricular stroke volumes (SVs) using both planimetry and 2D PC of the great vessels.

RESULTS

The mean tricuspid valve systolic excursion was 17.8 ± 2.5 mm. The 2D valve-tracking PC net diastolic flow showed excellent correlation with SV by right-ventricle planimetry (bias ± 1.96 SD = -0.2 ± 10.4 mL, intraclass correlation coefficient [ICC] = 0.92) and aortic PC (-1.0 ± 13.8 mL, ICC = 0.87). In comparison, static tricuspid valve 2D PC also showed a strong correlation but had greater bias (p = 0.01) versus the right-ventricle SV (10.6 ± 16.1 mL, ICC = 0.61). In most (8 of 9) healthy subjects, trace regurgitation was measured at begin-systole. In one patient, valve-tracking PC displayed a high-velocity jet (380 cm/s) with maximal velocity agreeing with echocardiography.

CONCLUSION

Automated valve-tracking 2D PC is a feasible route toward evaluation of tricuspid regurgitant velocities, potentially solving a major clinical challenge.

Three-Dimensional Characterization of Aortic Root Motion by Vascular Deformation Mapping

The aorta is in constant motion due to the combination of cyclic loading and unloading with its mechanical coupling to the contractile left ventricle (LV) myocardium. This aortic root motion has been proposed as a marker for aortic disease progression. Aortic root motion extraction techniques have been mostly based on 2D image analysis and have thus lacked a rigorous description of the different components of aortic root motion (e.g., axial versus in-plane). In this study, we utilized a novel technique termed vascular deformation mapping (VDM(D)) to extract 3D aortic root motion from dynamic computed tomography angiography images. Aortic root displacement (axial and in-plane), area ratio and distensibility, axial tilt, aortic rotation, and LV/Ao angles were extracted and compared for four different subject groups: non-aneurysmal, TAA, Marfan, and repair. The repair group showed smaller aortic root displacement, aortic rotation, and distensibility than the other groups. The repair group was also the only group that showed a larger relative in-plane displacement than relative axial displacement. The Marfan group showed the largest heterogeneity in aortic root displacement, distensibility, and age. The non-aneurysmal group showed a negative correlation between age and distensibility, consistent with previous studies. Our results revealed a strong positive correlation between LV/Ao angle and relative axial displacement and a strong negative correlation between LV/Ao angle and relative in-plane displacement. VDM(D)-derived 3D aortic root motion can be used in future studies to define improved boundary conditions for aortic wall stress analysis.

Advances in machine learning applications for cardiovascular 4D flow MRI

Four-dimensional flow magnetic resonance imaging (MRI) has evolved as a non-invasive imaging technique to visualize and quantify blood flow in the heart and vessels. Hemodynamic parameters derived from 4D flow MRI, such as net flow and peak velocities, but also kinetic energy, turbulent kinetic energy, viscous energy loss, and wall shear stress have shown to be of diagnostic relevance for cardiovascular diseases. 4D flow MRI, however, has several limitations. Its long acquisition times and its limited spatio-temporal resolutions lead to inaccuracies in velocity measurements in small and low-flow vessels and near the vessel wall. Additionally, 4D flow MRI requires long post-processing times, since inaccuracies due to the measurement process need to be corrected for and parameter quantification requires 2D and 3D contour drawing. Several machine learning (ML) techniques have been proposed to overcome these limitations. Existing scan acceleration methods have been extended using ML for image reconstruction and ML based super-resolution methods have been used to assimilate high-resolution computational fluid dynamic simulations and 4D flow MRI, which leads to more realistic velocity results. ML efforts have also focused on the automation of other post-processing steps, by learning phase corrections and anti-aliasing. To automate contour drawing and 3D segmentation, networks such as the U-Net have been widely applied. This review summarizes the latest ML advances in 4D flow MRI with a focus on technical aspects and applications. It is divided into the current status of fast and accurate 4D flow MRI data generation, ML based post-processing tools for phase correction and vessel delineation and the statistical evaluation of blood flow.

Relationship between Pulmonary Regurgitation and Ventriculo-Arterial Interactions in Patients with Post-Early Repair of Tetralogy of Fallot: Insights from Wave-Intensity Analysis

This study aimed to investigate the effect of pulmonary regurgitation (PR) on left ventricular ventriculo-arterial (VA) coupling in patients with repaired tetralogy of Fallot (ToF). It was hypothesised that increasing PR severity results in a smaller forward compression wave (FCW) peak in the aortic wave intensity, because of right-to-left ventricular interactions. The use of cardiovascular magnetic resonance (CMR)-derived wave-intensity analysis provided a non-invasive comparison between patients with varying PR degrees. A total of n = 201 patients were studied and both hemodynamic and wave-intensity data were compared. Wave-intensity peaks and areas of the forward compression and forward expansion waves were calculated as surrogates of ventricular function. Any extent of PR resulted in a significant reduction in the FCW peak. A correlation was found between aortic distensibility and the FCW peak, suggesting unfavourable (VA) coupling in patients that also present stiffer ascending aortas. Data suggest that VA coupling is affected by increased impedance.

Cardiac MR: From Theory to Practice

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.

In-silico study of accuracy and precision of left-ventricular strain quantification from 3D tagged MRI

Cardiac Magnetic Resonance Imaging (MRI) allows quantifying myocardial tissue deformation and strain based on the tagging principle. In this work, we investigate accuracy and precision of strain quantification from synthetic 3D tagged MRI using equilibrated warping. To this end, synthetic biomechanical left-ventricular tagged MRI data with varying tag distance, spatial resolution and signal-to-noise ratio (SNR) were generated and processed to quantify errors in radial, circumferential and longitudinal strains relative to ground truth. Results reveal that radial strain is more sensitive to image resolution and noise than the other strain components. The study also shows robustness of quantifying circumferential and longitudinal strain in the presence of geometrical inconsistencies of 3D tagged data. In conclusion, our study points to the need for higher-resolution 3D tagged MRI than currently available in practice in order to achieve sufficient accuracy of radial strain quantification.

Patient-Specific Analysis of Ascending Thoracic Aortic Aneurysm with the Living Heart Human Model

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs.

Importance of through-plane heart motion correction for the assessment of aortic regurgitation severity using phase contrast magnetic resonance imaging

PURPOSE

To elucidate the influence of through-plane heart motion on the assessment of aortic regurgitation (AR) severity using phase contrast magnetic resonance imaging (PC-MRI).

APPROACH

A patient cohort with chronic AR (n = 34) was examined with PC-MRI. The regurgitant volume (RVol) and fraction (RFrac) were extracted from the PC-MRI data before and after through-plane heart motion correction and was then used for assessment of AR severity.

RESULTS

The flow volume errors were strongly correlated to aortic diameter (R = 0.80, p < 0.001) with median (IQR 25%;75%): 16 (14; 17) ml for diameter>40mm, compared with 9 (7; 10) ml for normal aortic size (p < 0.001). RVol and RFrac were underestimated (uncorrected:64 ± 37 ml and 39 ± 17%; corrected:76 ± 37 ml and 44 ± 15%; p < 0.001) and ~ 20% of the patients received lower severity grade without correction.

CONCLUSION

Through-plane heart motion introduces relevant flow volume errors, especially in patients with aortic dilatation that may result in underestimation of the severity grade in patients with chronic AR.

Importance of complex blood flow in the assessment of aortic regurgitation severity using phase contrast magnetic resonance imaging

This study aimed to investigate if and how complex flow influences the assessment of aortic regurgitation (AR) using phase contrast MRI in patients with chronic AR. Patients with moderate (n = 15) and severe (n = 28) chronic AR were categorized into non-complex flow (NCF) or complex flow (CF) based on the presence of systolic backward flow volume. Phase contrast MRI was performed repeatedly at the level of the sinotubular junction (Ao1) and 1 cm distal to the sinotubular junction (Ao2). All AR patients were assessed to have non-severe AR or severe AR (cut-off values: regurgitation volume (RVol) ≥ 60 ml and regurgitation fraction (RF) ≥ 50%) in both measurement positions. The repeatability was significantly lower, i.e. variation was larger, for patients with CF than for NCF (≥ 12 ± 12% versus ≥ 6 ± 4%, P ≤ 0.03). For patients with CF, the repeatability was significantly lower at Ao2 compared to Ao1 (≥ 21 ± 20% versus ≥ 12 ± 12%, P ≤ 0.02), as well as the assessment of regurgitation (RVol: 42 ± 34 ml versus 54 ± 42 ml, P < 0.001; RF: 30 ± 18% versus 34 ± 16%, P = 0.01). This was not the case for patients with NCF. The frequency of patients that changed in AR grade from severe to non-severe when the position of the measurement changed from Ao1 to Ao2 was higher for patients with CF compared to NCF (RVol: 5/26 (19%) versus 1/17 (6%), P = 0.2; RF: 4/26 (15%) versus 0/17 (0%), P = 0.09). Our study shows that complex flow influences the quantification of chronic AR, which can lead to underestimation of AR severity when using PC-MRI.

Functional assessment of bioprosthetic mitral valves by cardiovascular magnetic resonance: An in vitro validation and comparison to Doppler echocardiography

BACKGROUND

A comprehensive non-invasive evaluation of bioprosthetic mitral valve (BMV) function can be challenging. We describe a novel method to assess BMV effective orifice area (EOA) based on phase contrast (PC) cardiovascular magnetic resonance (CMR) data. We compare the performance of this new method to Doppler and in vitro reference standards.

METHODS

Four sizes of normal BMVs (27, 29, 31, 33 mm) and 4 stenotic BMVs (27 mm and 29 mm, with mild or severe leaflet obstruction) were evaluated using a CMR- compatible flow loop. BMVs were evaluated with PC-CMR and Doppler methods under flow conditions of; 70 mL, 90 mL and 110 mL/beat (n = 24). PC-EOA was calculated as PC-CMR flow volume divided by the PC- time velocity integral (TVI).

RESULTS

PC-CMR measurements of the diastolic peak velocity and TVI correlated strongly with Doppler values (r = 0.99, P < 0.001 and r = 0.99, P < 0.001, respectively). Across all conditions tested, the Doppler and PC-CMR measurement of EOA (1.4 ± 0.5 vs 1.5 ± 0.7 cm2, respectively) correlated highly (r = 0.99, P < 0.001), with a minimum bias of 0.13 cm2, and narrow limits of agreement (- 0.2 to 0.5 cm2).

CONCLUSION

We describe a novel method to assess BMV function based on PC measures of transvalvular flow volume and velocity integration. PC-CMR methods can be used to accurately measure EOA for both normal and stenotic BMV's and may provide an important new parameter of BMV function when Doppler methods are unobtainable or unreliable.

Valvular imaging in the era of feature-tracking: A slice-following cardiac MR sequence to measure mitral flow

Background

In mitral valve dysfunction, noninvasive measurement of transmitral blood flow is an important clinical examination. Flow imaging of the mitral valve, however, is challenging, since it moves in and out of the image plane during the cardiac cycle.

Purpose

To more accurately measure mitral flow, a slice‐following MRI phase contrast sequence is proposed. This study aimed to implement such a sequence, validate its slice‐following functionality in a phantom and healthy subjects, and test its feasibility in patients with mitral valve dysfunction.

Study Type

Prospective.

Phantom and Subjects

The slice‐following functionality was validated in a cone‐shaped phantom by measuring the depicted slice radius. Sixteen healthy subjects and 10 mitral valve dysfunction patients were enrolled at two sites.

Field Strength/Sequence

1.5T and 3T gradient echo cine phase contrast.

Assessment

A single breath‐hold retrospectively gated sequence using offline feature‐tracking of the mitral valve was developed. Valve displacements were measured and imported to the scanner, allowing the slice position to change dynamically based on the cardiac phase. Mitral valve imaging was performed with slice‐following and static imaging planes. Validation was performed by comparing mitral stroke volume with planimetric and aortic stroke volume.

Statistical Tests

Measurements were compared using linear regression, Pearson's R, parametric paired t‐tests, Bland–Altman analysis, and intraclass correlation coefficient (ICC).

Results

Phantom experiments confirmed accurate slice displacements. Slice‐following was feasible in all subjects, yielding physiologically accurate mitral flow patterns. In healthy subjects, mitral and aortic stroke volumes agreed, with ICC = 0.72 and 0.90 for static and slice‐following planes; with bias ±1 SDs 23.2 ± 13.2 mls and 8.4 ± 10.8 mls, respectively. Agreement with planimetry was stronger, with ICC = 0.84 and 0.96; bias ±1 SDs 13.7 ± 13.7 mls and –2.0 ± 8.8 mls for static and slice‐following planes, respectively.

Data Conclusion

Slice‐following outperformed the conventional sequence and improved the accuracy of transmitral flow, which is important for assessment of diastolic function and mitral regurgitation.

Level of Evidence: 2

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2020;51:1412–1421.

Investigating heartbeat-related in-plane motion and stress levels induced at the aortic root

Background

The axial motion of aortic root (AR) due to ventricular traction was previously suggested to contribute to ascending aorta (AA) dissection by increasing its longitudinal stress, but AR in-plane motion effects on stresses have never been studied. The objective is to investigate the contribution of AR in-plane motion to AA stress levels.

Methods

The AR in-plane motion was assessed on magnetic resonance imagining data from 25 healthy volunteers as the movement of the AA section centroid. The measured movement was prescribed to the proximal AA end of an aortic finite element model to investigate its influences on aortic stresses. The finite element model was developed from a patient-specific geometry using LS-DYNA solver and validated against the aortic distensibility. Fluid–structure interaction (FSI) approach was also used to simulate blood hydrodynamic effects on aortic dilation and stresses.

Results

The AR in-plane motion was 5.5 ± 1.7 mm with the components of 3.1 ± 1.5 mm along the direction of proximal descending aorta (PDA) to AA centroid and 3.0 ± 1.3 mm perpendicularly under the PDA reference system. The AR axial motion elevated the longitudinal stress of proximal AA by 40% while the corresponding increase due to in-plane motion was always below 5%. The stresses at proximal AA resulted approximately 7% less in FSI simulation with blood flow.

Conclusions

The AR in-plane motion was comparable with the magnitude of axial motion. Neither axial nor in-plane motion could directly lead to AA dissection. It is necessary to consider the heterogeneous pressures related to blood hydrodynamics when studying aortic wall stress levels.

Electronic supplementary material

The online version of this article (10.1186/s12938-019-0632-7) contains supplementary material, which is available to authorized users.

Relations Between Aortic Stiffness and Left Ventricular Mechanical Function in the Community

Background

Aortic stiffness impairs optimal ventricular–vascular coupling and left ventricular systolic function, particularly in the long axis. Left ventricular global longitudinal strain (GLS) has recently emerged as a sensitive measure of early cardiac dysfunction. In this study, we investigated the relation between aortic stiffness and GLS in a large community‐based sample.

Methods and Results

In 2495 participants (age 39–90 years, 57% women) of the Framingham Offspring and Omni cohorts, free of cardiovascular disease, we performed tonometry to measure arterial hemodynamics and echocardiography to assess cardiac function. Aortic stiffness was evaluated as carotid–femoral pulse wave velocity and as characteristic impedance, and GLS was calculated using speckle tracking–based measurements. In multivariable analyses adjusting for age, sex, height, systolic blood pressure, augmentation index, left ventricular structure, and additional cardiovascular risk factors, increased carotid–femoral pulse wave velocity (B±SE: 0.122±0.030% strain per SD, P<0.0001) and characteristic impedance (0.090±0.029, P=0.002) were both associated with worse GLS. We observed effect modification by sex on the relation between characteristic impedance and GLS (P=0.004); in sex‐stratified multivariable analyses, the relation between greater characteristic impedance and worse GLS persisted in women (0.145±0.039, P=0.0003) but not in men (P=0.73).

Conclusions

Multiple measures of increased aortic stiffness were cross‐sectionally associated with worse GLS after adjusting for hemodynamic variables. Parallel reductions in left ventricular long axis shortening and proximal aortic longitudinal strain in individuals with a stiffened proximal aorta, from direct mechanical ventricular‐vascular coupling, offers an alternative explanation for the observed relations.

Utility of Cardiovascular Magnetic Resonance-Derived Wave Intensity Analysis As a Marker of Ventricular Function in Children with Heart Failure and Normal Ejection Fraction

OBJECTIVE

This study sought to explore the diagnostic insight of cardiovascular magnetic resonance (CMR)-derived wave intensity analysis to better study systolic dysfunction in young patients with chronic diastolic dysfunction and preserved ejection fraction (EF), comparing it against other echocardiographic and CMR parameters.

BACKGROUND

Evaluating systolic and diastolic dysfunctions in children is challenging, and a gold standard method is currently lacking.

METHODS

Patients with presumed diastolic dysfunction [n = 18; nine aortic stenosis (AS), five hypertrophic, and four restrictive cardiomyopathies] were compared with age-matched control subjects (n = 18). All patients had no mitral or aortic incompetence, significant AS, or reduced systolic EF. E/A ratio, E/E' ratio, deceleration time, and isovolumetric contraction time were assessed on echocardiography, and indexed left atrial volume (LAVi), acceleration time (AT), ejection time (ET), and wave intensity analyses were calculated from CMR. The latter was performed on CMR phase-contrast flow sequences, defining a ratio of the peaks of the early systolic forward compression wave (FCW) and the end-systolic forward expansion wave (FEW).

RESULTS

Significant differences between patients and controls were seen in the E/E' ratio (8.7 ± 4.0 vs. 5.1 ± 1.3, p = 0.001) and FCW/FEW ratio (2.5 ± 1.6 vs. 7.2 ± 4.2 × 10^-5 m/s, p < 0.001), as well as-as expected-LAVi (80.7 ± 22.5 vs. 51.0 ± 10.9 mL/m², p < 0.001). In particular, patients exhibited a lower FCW (2.5 ± 1.6 vs. 7.2 ± 4.2 × 10^-5 m/s, p < 0.001) in the face of preserved EF (67 ± 11 vs. 69 ± 5%, p = 0.392), as well as longer isovolumetric contraction time (49 ± 7 vs. 34 ± 7 ms, p < 0.001) and ET/AT (0.35 ± 0.04 vs. 0.27 ± 0.04, p < 0.001).

CONCLUSION

This study shows that the wave intensity-derived ratio summarizing systolic and diastolic function could provide insight into ventricular function in children, on top of CMR and echocardiography, and it was here able to identify an element of ventricular dysfunction with preserved EF in a small group of young patients.

The Impact of Cardiac Motion on Aortic Valve Flow Used in Computational Simulations of the Thoracic Aorta

Advancements in image-based computational modeling are producing increasingly more realistic representations of vasculature and hemodynamics, but so far have not compensated for cardiac motion when imposing inflow boundary conditions. The effect of cardiac motion on aortic flow is important when assessing sequelae in this region including coarctation of the aorta (CoA) or regurgitant fraction. The objective of this investigation was to develop a method to assess and correct for the influence of cardiac motion on blood flow measurements through the aortic valve (AoV) and to determine its impact on patient-specific local hemodynamics quantified by computational fluid dynamics (CFD). A motion-compensated inflow waveform was imposed into the CFD model of a patient with repaired CoA that accounted for the distance traveled by the basal plane during the cardiac cycle. Time-averaged wall shear stress (TAWSS) and turbulent kinetic energy (TKE) values were compared with CFD results of the same patient using the original waveform. Cardiac motion resulted in underestimation of flow during systole and overestimation during diastole. Influences of inflow waveforms on TAWSS were greatest along the outer wall of the ascending aorta (AscAo) (∼30 dyn/cm2). Differences in TAWSS were more pronounced than those from the model creation or mesh dependence aspects of CFD. TKE was slightly higher for the motion-compensated waveform throughout the aortic arch. These results suggest that accounting for cardiac motion when quantifying blood flow through the AoV can lead to different conclusions for hemodynamic indices, which may be important if these results are ultimately used to predict patient outcomes.

Advanced flow MRI: emerging techniques and applications

Magnetic resonance imaging (MRI) techniques provide non-invasive and non-ionising methods for the highly accurate anatomical depiction of the heart and vessels throughout the cardiac cycle. In addition, the intrinsic sensitivity of MRI to motion offers the unique ability to acquire spatially registered blood flow simultaneously with the morphological data, within a single measurement. In clinical routine, flow MRI is typically accomplished using methods that resolve two spatial dimensions in individual planes and encode the time-resolved velocity in one principal direction, typically oriented perpendicular to the two-dimensional (2D) section. This review describes recently developed advanced MRI flow techniques, which allow for more comprehensive evaluation of blood flow characteristics, such as real-time flow imaging, 2D multiple-venc phase contrast MRI, four-dimensional (4D) flow MRI, quantification of complex haemodynamic properties, and highly accelerated flow imaging. Emerging techniques and novel applications are explored. In addition, applications of these new techniques for the improved evaluation of cardiovascular (aorta, pulmonary arteries, congenital heart disease, atrial fibrillation, coronary arteries) as well as cerebrovascular disease (intra-cranial arteries and veins) are presented.

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.

Regional Mapping of Aortic Wall Stress by Using Deformable, Motion-coherent Modeling based on Electrocardiography-gated Multidetector CT Angiography: Feasibility Study

Purpose To investigate the feasibility of deformable, motion-coherent modeling based on electrocardiography-gated multidetector computed tomographic (CT) angiography of the thoracic aorta and to evaluate whether quantifiable information on aortic wall stress as a function of patient-specific cardiovascular parameters can be gained. Materials and Methods For this institutional review board-approved, HIPAA-compliant study, thoracic electrocardiography-gated dual-source multidetector CT angiographic images were used from 250 prospectively enrolled patients (150 men, 100 women; mean age, 79 years). On reconstructed 50-phase CT angiographic images, aortic strain and deformation were determined at seven cardiac and aortic locations. One-way analysis of variance was used by assessing the magnitude for longitudinal and axial strain and axial deformation, as well as time-resolved peak and maxima count for longitudinal strain and axial deformation. Interdependencies between aortic strain and deformation with extracted hemodynamic parameters were evaluated. Results With increasing heart rates, there was a significant decrease in longitudinal strain (P = .009, R(2) = 0.95) and a decrease in the number of longitudinal strain peaks (P < .001, R(2) = 0.79); however, a significant increase in axial deformation (P < .001, R(2) = 0.31) and axial strain (P = .009, R(2) = 0.61) was observed. Increasing aortic blood velocity led to increased longitudinal strain (P = .018, R(2) = 0.42) and longitudinal strain peak counts (P = .011, R(2) = 0.48). Pronounced motion in the longitudinal direction limited motion in the axial plane (P < .019, R(2) = 0.29-0.31). Conclusion The results of this study render a clinical basis and provide proof of principle for the use of deformable, motion-coherent modeling to provide quantitative information on physiological motion of the aorta under various hemodynamic circumstances. (©) RSNA, 2016 Online supplemental material is available for this article.

When and How to Enlarge the Small Aortic Root

Successful enlargement of the small aortic root in children has remained a management challenge, particularly in the neonates and small infants. Achieving this aim requires thorough understanding of the anatomic features of the left ventricular outflow tract, careful patient selection, and skilful execution of complex surgery. This article reviews the anatomical principles upon which the surgical techniques rely, the decision-making, the timing of surgery, the surgical options, and the outcomes.

Longitudinal and circumferential strain of the proximal aorta

Background

Accurate assessment of mechanical properties of the proximal aorta is a requisite first step for elucidating the pathophysiology of isolated systolic hypertension. During systole, substantial proximal aortic axial displacement produces longitudinal strain, which we hypothesize causes variable underestimation of ascending aortic circumferential strain compared to values in the longitudinally constrained descending aorta.

Methods and Results

To assess effects of longitudinal strain, we performed magnetic resonance imaging in 375 participants (72 to 94 years old, 204 women) in the Age, Gene/Environment Susceptibility‐Reykjavik Study and measured aortic circumferential and longitudinal strain. Circumferential ascending aortic area strain uncorrected for longitudinal strain was comparable in women and men (mean [95% CI], 8.3 [7.8, 8.9] versus 7.9 [7.4, 8.5]%, respectively, P=0.3). However, longitudinal strain was greater in women (8.5±2.5 versus 7.0±2.5%, P<0.001), resulting in greater longitudinally corrected circumferential ascending aortic strain (14.4 [13.6, 15.2] versus 13.0 [12.4, 13.7]%, P=0.010). Observed circumferential descending aortic strain, which did not require correction (women: 14.0 [13.2, 14.8], men: 12.4 [11.6, 13.2]%, P=0.005), was larger than uncorrected (P<0.001), but comparable to longitudinally corrected (P=0.12) circumferential ascending aortic strain. Carotid‐femoral pulse wave velocity did not correlate with uncorrected ascending aortic strain (R=−0.04, P=0.5), but was inversely related to longitudinally corrected ascending and observed descending aortic strain (R=−0.15, P=0.004; R=−0.36, P<0.001, respectively). Longitudinal strain was also inversely related to carotid‐femoral pulse wave velocity and other risk factors for higher aortic stiffness including treated hypertension.

Conclusions

Longitudinal strain creates substantial and variable errors in circumferential ascending aortic area strain measurements, particularly in women, and should be considered to avoid misclassification of ascending aortic stiffness.

Quantification of Respiratory Movement of the Aorta and Side Branches

Purpose: To assess and quantify the magnitude and direction of respiratory movement of the aorta and origins of its side branches. Methods: A quantitative 3-dimensional (3D) subtraction analysis of computed tomography (CT) scans during inspiration and expiration was performed to determine the respiratory geometric movements of the aorta and side branches in 60 patients. During breath-hold expiration and inspiration, 1-mm-thick CT slices of the aorta were acquired in unenhanced and contrast-enhanced scans. The datasets were compared using dedicated multiplanar reformation image subtraction software to determine the change in position of relevant anatomic sections, including the ascending thoracic aorta (AA), the origins of the brachiocephalic artery (BA) and left subclavian artery (LSA), the descending thoracic aorta (DTA) at the level of the tenth thoracic vertebra, as well as the origins of the celiac trunk, superior mesenteric artery, and the renal arteries. Results: Complex movement was visible during inspiration; the regions of interest in the thoracic aorta and side branches moved in the anterior, medial, and caudal directions compared with the expiration state. Mean 3D movement vectors (± standard deviation) were 8.9±3.6 mm (AA), 12.0±4.1 mm (BA), 11.1±3.9 mm (LSA), and 4.9±2.5 mm (DTA). Abdominal side branches moved in the caudal direction 1.3±1.1 mm. There was significantly less movement in the DTA compared to AA (p<0.001). The correlation coefficient between the extent of LSA movement and thoracic excursion was 0.78. Conclusion: The aorta and side branches undergo considerable respiratory movement. The results from this study provide an important contribution to understanding aortic dynamics.

Relations between aortic stiffness and left ventricular structure and function in older participants in the Age, Gene/Environment Susceptibility--Reykjavik Study

BACKGROUND

Left ventricular (LV) contraction displaces the aortic annulus and produces a force that stretches the ascending aorta. We hypothesized that aortic stiffening increases this previously ignored component of LV load and may contribute to hypertrophy. Conversely, aortic stretch-related work represents stored energy that may facilitate early diastolic filling.

METHODS AND RESULTS

We performed MRI of the aorta and LV in 347 participants (72-91 years old, 189 women) in the Age, Gene/Environment Susceptibility-Reykjavik Study to examine relations of aortic stretch with LV structure and function. Aortic stiffness was evaluated as the product of Young's modulus and aortic wall thickness. Force was computed from Young's modulus and longitudinal aortic strain; work was the integrated product of force and annulus displacement during systole. LV mass and dynamic volume were measured using the area-length method. Filling was assessed from time-resolved LV volume curves. In multivariable models that adjusted for age, sex, height, weight, end-diastolic LV volume, augmentation index, end-systolic pressure, and cardiovascular disease risk factors, higher aortic stiffness was associated with increased LV mass (β=3.0±0.8% per SD, P<0.001; sex interaction, P=0.8). Greater stretch-related aortic work was associated with enhanced early filling in men (β=4.0±0.8 mL/SD; P<0.001), but not in women (β=-0.4±0.7 mL/SD; P=0.6).

CONCLUSIONS

Higher aortic stiffness was associated with higher LV mass, independently of pressure. Higher stretch-related work was associated with greater early diastolic filling in men only. Impaired diastolic recovery of energy stored by systolic proximal aortic stretch may contribute to increased susceptibility to diastolic dysfunction in women.

Heart valve disease: investigation by cardiovascular magnetic resonance

Cardiovascular magnetic resonance (CMR) has become a valuable investigative tool in many areas of cardiac medicine. Its value in heart valve disease is less well appreciated however, particularly as echocardiography is a powerful and widely available technique in valve disease. This review highlights the added value that CMR can bring in valve disease, complementing echocardiography in many areas, but it has also become the first-line investigation in some, such as pulmonary valve disease and assessing the right ventricle. CMR has many advantages, including the ability to image in any plane, which allows full visualisation of valves and their inflow/outflow tracts, direct measurement of valve area (particularly for stenotic valves), and characterisation of the associated great vessel anatomy (e.g. the aortic root and arch in aortic valve disease). A particular strength is the ability to quantify flow, which allows accurate measurement of regurgitation, cardiac shunt volumes/ratios and differential flow volumes (e.g. left and right pulmonary arteries). Quantification of ventricular volumes and mass is vital for determining the impact of valve disease on the heart, and CMR is the 'Gold standard' for this. Limitations of the technique include partial volume effects due to image slice thickness, and a low ability to identify small, highly mobile objects (such as vegetations) due to the need to acquire images over several cardiac cycles. The review examines the advantages and disadvantages of each imaging aspect in detail, and considers how CMR can be used optimally for each valve lesion.

Cardiovascular magnetic resonance tagging of the right ventricular free wall for the assessment of long axis myocardial function in congenital heart disease

BACKGROUND

Right ventricular ejection fraction (RV-EF) has traditionally been used to measure and compare RV function serially over time, but may be a relatively insensitive marker of change in RV myocardial contractile function. We developed a cardiovascular magnetic resonance (CMR) tagging-based technique with a view to rapid and reproducible measurement of RV long axis function and applied it in patients with congenital heart disease.

METHODS

We studied 84 patients: 56 with repaired Tetralogy of Fallot (rTOF); 28 with atrial septal defect (ASD): 13 with and 15 without pulmonary hypertension (RV pressure > 40 mmHG by echocardiography). For comparison, 20 healthy controls were studied. CMR acquisitions included an anatomically defined four chamber cine followed by a cine gradient echo-planar sequence in the same plane with a labelling pre-pulse giving a tag line across the basal myocardium. RV tag displacement was measured with automated registration and tracking of the tag line together with standard measurement of RV-EF.

RESULTS

Mean RV displacement was higher in the control (26 ± 3 mm) than in rTOF (16 ± 4 mm) and ASD with pulmonary hypertension (18 ± 3 mm) groups, but lower than in the ASD group without (30 ± 4 mm), P < 0.001. The technique was reproducible with inter-study bias ± 95% limits of agreement of 0.7 ± 2.7 mm. While RV-EF was lower in rTOF than in controls (49 ± 9% versus 57 ± 6%, P < 0.001), it did not differ between either ASD group and controls.

CONCLUSIONS

Measurements of RV long axis displacement by CMR tagging showed more differences between the groups studied than did RV-EF, and was reproducible, quick and easy to apply. Further work is needed to assess its potential use for the detection of longitudinal changes in RV myocardial function.

Automatic evaluation of the Valsalva sinuses from cine-MRI

OBJECT

Although, there is no global consensus on their measurement, magnetic resonance imaging (MRI) appears to be particularly attractive for the study of the sinuses of Valsalva (SV). The purpose of this study was to automatically evaluate the SV from cine-MRI using a standardized method.

MATERIALS AND METHODS

An automatic method based on mathematical morphology was elaborated to segment the aortic root from cross-sectional cine-MRI, and to detect relevant points, such as the commissures, the cusps and the centre of the SV. The distances between these points allow a metric evaluation of the SV. Our method was tested on synthesized data and 41 patient data sets and radii calculations were compared with manual processing.

RESULTS

On the patient data sets, there are excellent correlation and concordance between manual and automatic measurements for images at diastole (r=0.97; y=0.97x+0.57; P<10(-5); mean of differences=0.2 mm; standard deviation of differences=2.0 mm) and at systole (r=0.96; y=0.96x+1.2; P<10(-5); mean of differences<0.1 mm; standard deviation of differences=2.4 mm).

CONCLUSION

Our automatic method provides reliable morphometric evaluation of the SV. Measures of distances between relevant points allow a precise evaluation of each cusp of the SV. This robust evaluation can be helpful in the follow-up of patients with aortic root diseases.

MR image-based geometric and hemodynamic investigation of the right coronary artery with dynamic vessel motion

The aim of this study was to develop a fully subject-specific model of the right coronary artery (RCA), including dynamic vessel motion, for computational analysis to assess the effects of cardiac-induced motion on hemodynamics and resulting wall shear stress (WSS). Vascular geometries were acquired in the right coronary artery (RCA) of a healthy volunteer using a navigator-gated interleaved spiral sequence at 14 time points during the cardiac cycle. A high temporal resolution velocity waveform was also acquired in the proximal region. Cardiac-induced dynamic vessel motion was calculated by interpolating the geometries with an active contour model and a computational fluid dynamic (CFD) simulation with fully subject-specific information was carried out using this model. The results showed the expected variation of vessel radius and curvature throughout the cardiac cycle, and also revealed that dynamic motion of the right coronary artery consequent to cardiac motion had significant effects on instantaneous WSS and oscillatory shear index. Subject-specific MRI-based CFD is feasible and, if scan duration could be shortened, this method may have potential as a non-invasive tool to investigate the physiological and pathological role of hemodynamics in human coronary arteries.

Quantification of hemodynamic wall shear stress in patients with bicuspid aortic valve using phase-contrast MRI

Bicuspid aortic valve (BAV) is often concomitant with aortic dilatation, aneurysm, and dissection. This valve lesion and its complications may affect positional and temporal wall shear stress (WSS), a parameter reported to regulate transcriptional events in vascular remodeling. Thus, this pilot study seeks to determine if the WSS in the ascending aorta (AAo) of BAV patients differs from control patients. Phase-contrast magnetic resonance imaging (PC-MRI) was used to perform flow analysis at the level of the AAo in 15 BAV and 15 control patients. Measurement of the aorta dimensions, flow rates, regurgitant fraction (RF), flow reversal ratio (FRR), temporal and spatial WSS, and shear range indices (SRI) were performed. The BAV and control group showed a significant difference between the circumferentially averaged WSS (p=0.03) and positional WSS at systole (minimum p<0.001). Regressions found that SRI (r=0.77, p<0.001), RF (r=0.68, p<0.001), and WSS at systole (r=0.66, p<0.001) were correlated to AAo size. The spatial distribution and magnitude of systolic WSS in BAV patients (-6.7+/-4.3 dynes/cm2) differed significantly from control patients (-11.5+/-6.6 dynes/cm2, p=0.03). The SRI metric, a measure of shear symmetry along the lumen circumference, was also significantly different (p=0.006) and indicated a heterogenic pattern of dilatation in the BAV patients.

Valvular and hemodynamic assessment with CMR

Cardiovascular magnetic resonance is able to provide a comprehensive assessment of valvular and hemodynamic function, including quantification of valve regurgitation and other flows, and accurate cardiac volumes and mass for assessing the effect on both ventricles. Combined with the ability to image all areas of the heart (including difficult areas, such as the right ventricle and pulmonary veins), it is an ideal technique for investigating patients who have heart failure in whom these areas need to be examined.

Calculations of cardiovascular shunts and regurgitation using magnetic resonance ventricular volume and aortic and pulmonary flow measurements

BACKGROUND

Cardiovascular magnetic resonance measurements of the volumes of the right and left ventricle and of the flows in the ascending aorta and main pulmonary artery contribute to the assessment of patients with valvular regurgitation or intracardiac or extracardiac shunts. Ventricular volumes are measured by planimetry and summation of end-diastolic and end-systolic areas measured in a stack of ventricular short-axis cines. The volumes of blood flowing through planes transecting the great arteries are measured using phase contrast velocity mapping. The two approaches are essentially different and can be used either for mutual validation, or separately or in combination to quantify regurgitation and/or shunting. In the presence of shunts, the relations between the stroke volumes and arterial flows of each side of the heart vary depending on the level of shunting (for example, atrial, ventricular or ductal).

CONCLUSION

This article aims to explain and illustrate the technical and theoretical basis for calculations using volumetric and flow measurements, providing formulae and diagrams to facilitate the interpretation of results.

Finite element modeling of the thoracic aorta: including aortic root motion to evaluate the risk of aortic dissection

OBJECTIVE

We propose that the aortic root motion plays an important role in aortic dissection.

METHODS AND RESULTS

A finite element model of the aortic root, arch and branches of the arch was built to assess the influence of aortic root displacement and pressure on the aortic wall stress. The largest stress increase due to aortic root displacement was found at approximately 2 cm above the top of the aortic valve. There, the longitudinal stress increased by 50% to 0.32 MPa when 8.9 mm axial displacement was applied in addition to 120 mmHg luminal pressure. A similar result was observed when the pressure load was increased to 180 mmHg without axial displacement.

CONCLUSIONS

Both aortic root displacement and hypertension significantly increase the longitudinal stress in the ascending aorta, which could play a decisive role in the development of various aortic pathologies, including aortic dissection.

Motion in cardiovascular MR imaging

Modern rapid magnetic resonance (MR) imaging techniques have led to widespread use of the modality in cardiac imaging. Despite this progress, many MR studies suffer from image degradation due to involuntary motion during the acquisition. This review describes the type and extent of the motion of the heart due to the cardiac and respiratory cycles, which create image artifacts. Methods of eliminating or reducing the problems caused by the cardiac cycle are discussed, including electrocardiogram gating, subject-specific acquisition windows, and section tracking. Similarly, for respiratory motion of the heart, techniques such as breath holding, respiratory gating, section tracking, phase-encoding ordering, subject-specific translational models, and a range of new techniques are considered.

Heartbeat-related displacement of the thoracic aorta in patients with chronic aortic dissection type B: quantification by dynamic CTA

PURPOSE

The purpose of this study was to characterize the heartbeat-related displacement of the thoracic aorta in patients with chronic aortic dissection type B (CADB).

MATERIALS AND METHODS

Electrocardiogram-gated computed tomography angiography was performed during inspiratory breath-hold in 11 patients with CADB: Collimation 16 mm x 1 mm, pitch 0.2, slice thickness 1mm, reconstruction increment 0.8 mm. Multiplanar reformations were taken for 20 equidistant time instances through both ascending (AAo) and descending aorta (true lumen, DAoT; false lumen, DAoF) and the vertex of the aortic arch (VA). In-plane vessel displacement was determined by region of interest analysis.

RESULTS

Mean displacement was 5.2+/-1.7 mm (AAo), 1.6+/-1.0 mm (VA), 0.9+/-0.4 mm (DAoT), and 1.1+/-0.4mm (DAoF). This indicated a significant reduction of displacement from AAo to VA and DAoT (p<0.05). The direction of displacement was anterior for AAo and cranial for VA.

CONCLUSION

In CADB, the thoracic aorta undergoes a heartbeat-related displacement that exhibits an unbalanced distribution of magnitude and direction along the thoracic vessel course. Since consecutive traction forces on the aortic wall have to be assumed, these observations may have implications on pathogenesis of and treatment strategies for CADB.

Aortic Root Measurement by Cardiovascular Magnetic Resonance

Background— Cardiovascular magnetic resonance is widely used for aortic root visualization and measurement, but methods still need to be standardized. Our aim was to identify appropriate planes of acquisition and lines of measurement and record corresponding normal values.

Methods and Results— We studied 120 healthy volunteers, 10 of each gender in each decile between 20 and 80 years, by using a 1.5-T cardiovascular magnetic resonance system. Steady-state free precession cine acquisitions aligned with the left ventricular outflow tract in oblique sagittal and coronal orientations were used to locate 2 sinus planes that transected the root at its widest point in its maximally expanded systolic and at its end diastolic positions. We measured the cusp-cusp and the cusp-commissure dimensions in these cine planes, each as the average of 3. Diastolic cusp-commissure dimensions were smaller than diastolic cusp-cusp dimensions (32.0�3.5 mm versus 34.6�4.0 mm in men, 28.4�2.8 mm versus 30.7�3.3 mm in women, P <0.001 for both). The diastolic cusp-commissure dimensions increased by 0.9 mm per decade in men and 0.7 mm per decade in women ( P <0.001 for both) and gave higher R 2 values with respect to age and body surface area (0.40 for men, 0.27 for women) than diastolic cusp-cusp, systolic cusp-commissure, or sinus measurements made in the left ventricular outflow tract planes.

Conclusions— The results indicate the importance of consistent methods for measurement of the aortic root by cardiovascular magnetic resonance. We recommend diastolic cusp-commissure measurements, which yielded favorable R 2 values with respect to age and body surface area and were found to correspond closely with reference echocardiographic root measurements recorded in the Framingham cohort. We recorded reference values for these and other possible aortic root measurements by cardiovascular magnetic resonance.

Characterization of the highly nonlinear and anisotropic vascular tissues from experimental inflation data: a validation study toward the use of clinical data for in-vivo modeling and analysis

We study whether an inverse modeling approach is applicable for characterizing vascular tissue subjected to various levels of internal pressure and axial stretch that approximate in-vivo conditions. To compensate for the limitation of axial-displacement/pressure/diameter data typical of clinical data, which does not provide information about axial force, we propose to constrain the ratio of axial to circumferential elastic moduli to a typical range. Vessel wall constitutive behavior is modeled with a transversely isotropic hyperelastic equation that accounts for dispersed collagen fibers. A single-layer and a bi-layer approximation to vessel ultrastructure are examined, as is the possibility of obtaining the fiber orientation as part of the optimization. Characterization is validated against independent pipette-aspiration biaxial data on the same samples. It was found that the single-layer model based on homogeneous wall assumption could not reproduce the validation data. In contrast, the constrained bi-layer model was in excellent agreement with both types of experimental data. Due to covariance, estimations of fiber angle were slightly outside of the normal range, which can be resolved by predefining the angles to normal values. Our approach is relatively invariant to a constant or a variable axial response. We believe that it is suitable for in-vivo characterization.