P1824Aortic wall shear stress in bicuspid aortic valve disease - 10-year follow-up

Introduction

Bicuspid aortic valve (BAV) disease leads to deviant complex helical flow patterns in the aorta - especially in the mid-ascending (AoA) part. In association with congenital BAV, aortic wall alterations such as aortic dilatation and dissection may occur. Among others, wall shear stress (WSS) could be one parameter to contribute to the prediction of the long-term outcome of patients with BAV. 4D-flow in cardiovascular magnetic resonance has been established as a valid method to estimate WSS.

Purpose

The aim of this study is to reevaluate WSS and comparing it to values generated in the same patient cohort with bicuspid aortic valve disease in 2008. No one of the above had aortic dilation in 2008 but proven helical flow pattern. The long term follow-up study might show changes in WSS over the period of ten years.

Methods

Ten complete 4D flow datasets of patients (age at follow-up: median 34.5 years; range 19–41 years) with bicuspid aortic valve disease without enlargement of the aorta were obtained in 2008 and reevaluated in 2018/2019 in the same patient collective. Mean WSS values were calculated with identical specific software tools. All data were analyzed by two experienced investigators.

Results

Aortic diameters at the level of the mid AoA did not change significantly in the 10-year period. The WSS values were lower in 2018 at all levels of the ascending aorta (Table 1). Indexed aortic diameters at the level of the mid ascending aorta did not change, median difference 0.06 cm/m2 (range −0.1 cm/m2 to 0.2 cm/m2; p=0.28), absolute values of indexed AoA diameters in 2018/2019 ranged from 1.27 cm/m2 to 2.2 cm/m2 (median 1.76 cm/m2).

Table 1 WSS magnitudinal [N/m2] 2008 (n=10) 2018 (n=10) Median difference p-value median range median range Level aortic bulb 0.95 0.80–1.46 0.42 0.34–0.82 −0.53 <0.01 Level mid ascending aorta 0.72 0.40–0.98 0.39 0.34–0.59 −0.33 <0.01 Level brachiocephalic trunc (BCT) 0.71 0.38–1.03 0.40 0.37–0.61 −0.31 <0.01

Conclusions

Indexed AoA diameters in BAV disease did not change significantly over a 10-year period. WSS of AoA was less compared to values generated in 2008. This might be explained by a slight alteration in hemodynamic flow patterns by the aging aorta, but not by changes of the aortic diameters. Possibly a drop of WSS in BAV could serve as a marker for a benign long term course.

Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling

Computational models of cardiac electromechanics (EM) are increasingly being applied to clinical problems, with patient-specific models being generated from high fidelity imaging and used to simulate patient physiology, pathophysiology and response to treatment. Current structured meshes are limited in their ability to fully represent the detailed anatomical data available from clinical images and capture complex and varied anatomy with limited geometric accuracy. In this paper, we review the state of the art in image-based personalization of cardiac anatomy for biophysically detailed, strongly coupled EM modeling, and present our own tools for the automatic building of anatomically and structurally accurate patient-specific models. Our method relies on using high resolution unstructured meshes for discretizing both physics, electrophysiology and mechanics, in combination with efficient, strongly scalable solvers necessary to deal with the computational load imposed by the large number of degrees of freedom of these meshes. These tools permit automated anatomical model generation and strongly coupled EM simulations at an unprecedented level of anatomical and biophysical detail.

Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling

Computational models of cardiac electromechanics (EM) are increasingly being applied to clinical problems, with patient-specific models being generated from high fidelity imaging and used to simulate patient physiology, pathophysiology and response to treatment. Current structured meshes are limited in their ability to fully represent the detailed anatomical data available from clinical images and capture complex and varied anatomy with limited geometric accuracy. In this paper, we review the state of the art in image-based personalization of cardiac anatomy for biophysically detailed, strongly coupled EM modeling, and present our own tools for the automatic building of anatomically and structurally accurate patient-specific models. Our method relies on using high resolution unstructured meshes for discretizing both physics, electrophysiology and mechanics, in combination with efficient, strongly scalable solvers necessary to deal with the computational load imposed by the large number of degrees of freedom of these meshes. These tools permit automated anatomical model generation and strongly coupled EM simulations at an unprecedented level of anatomical and biophysical detail.

3D strain assessment in ultrasound (Straus): a synthetic comparison of five tracking methodologies

This paper evaluates five 3D ultrasound tracking algorithms regarding their ability to quantify abnormal deformation in timing or amplitude. A synthetic database of B-mode image sequences modeling healthy, ischemic and dyssynchrony cases was generated for that purpose. This database is made publicly available to the community. It combines recent advances in electromechanical and ultrasound modeling. For modeling heart mechanics, the Bestel-Clement-Sorine electromechanical model was applied to a realistic geometry. For ultrasound modeling, we applied a fast simulation technique to produce realistic images on a set of scatterers moving according to the electromechanical simulation result. Tracking and strain accuracies were computed and compared for all evaluated algorithms. For tracking, all methods were estimating myocardial displacements with an error below 1 mm on the ischemic sequences. The introduction of a dilated geometry was found to have a significant impact on accuracy. Regarding strain, all methods were able to recover timing differences between segments, as well as low strain values. On all cases, radial strain was found to have a low accuracy in comparison to longitudinal and circumferential components.

Benchmarking framework for myocardial tracking and deformation algorithms: an open access database

In this paper we present a benchmarking framework for the validation of cardiac motion analysis algorithms. The reported methods are the response to an open challenge that was issued to the medical imaging community through a MICCAI workshop. The database included magnetic resonance (MR) and 3D ultrasound (3DUS) datasets from a dynamic phantom and 15 healthy volunteers. Participants processed 3D tagged MR datasets (3DTAG), cine steady state free precession MR datasets (SSFP) and 3DUS datasets, amounting to 1158 image volumes. Ground-truth for motion tracking was based on 12 landmarks (4 walls at 3 ventricular levels). They were manually tracked by two observers in the 3DTAG data over the whole cardiac cycle, using an in-house application with 4D visualization capabilities. The median of the inter-observer variability was computed for the phantom dataset (0.77 mm) and for the volunteer datasets (0.84 mm). The ground-truth was registered to 3DUS coordinates using a point based similarity transform. Four institutions responded to the challenge by providing motion estimates for the data: Fraunhofer MEVIS (MEVIS), Bremen, Germany; Imperial College London - University College London (IUCL), UK; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Inria-Asclepios project (INRIA), France. Details on the implementation and evaluation of the four methodologies are presented in this manuscript. The manually tracked landmarks were used to evaluate tracking accuracy of all methodologies. For 3DTAG, median values were computed over all time frames for the phantom dataset (MEVIS=1.20mm, IUCL=0.73 mm, UPF=1.10mm, INRIA=1.09 mm) and for the volunteer datasets (MEVIS=1.33 mm, IUCL=1.52 mm, UPF=1.09 mm, INRIA=1.32 mm). For 3DUS, median values were computed at end diastole and end systole for the phantom dataset (MEVIS=4.40 mm, UPF=3.48 mm, INRIA=4.78 mm) and for the volunteer datasets (MEVIS=3.51 mm, UPF=3.71 mm, INRIA=4.07 mm). For SSFP, median values were computed at end diastole and end systole for the phantom dataset(UPF=6.18 mm, INRIA=3.93 mm) and for the volunteer datasets (UPF=3.09 mm, INRIA=4.78 mm). Finally, strain curves were generated and qualitatively compared. Good agreement was found between the different modalities and methodologies, except for radial strain that showed a high variability in cases of lower image quality.

A novel anisotropic fast marching method and its application to blood flow computation in phase-contrast MRI

BACKGROUND

Phase-contrast MRI (PC MRI) can be used to assess blood flow dynamics noninvasively inside the human body. The acquired images can be reconstructed into flow vector fields. Traditionally, streamlines can be computed based on the vector fields to visualize flow patterns and particle trajectories.

OBJECTIVES

The traditional methods may give a false impression of precision, as they do not consider the measurement uncertainty in the PC MRI images. In our prior work, we incorporated the uncertainty of the measurement into the computation of particle trajectories.

METHODS

As a major part of the contribution, a novel numerical scheme for solving the anisotropic Fast Marching problem is presented. A computing time comparison to state-of-the-art methods is conducted on artificial tensor fields. A visual comparison of healthy to pathological blood flow patterns is given.

RESULTS

The comparison shows that the novel anisotropic Fast Marching solver outperforms previous schemes in terms of computing time. The visual comparison of flow patterns directly visualizes large deviations of pathological flow from healthy flow.

CONCLUSIONS

The novel anisotropic Fast Marching solver efficiently resolves even strongly anisotropic path costs. The visualization method enables the user to assess the uncertainty of particle trajectories derived from PC MRI images.

[Myocardial MR tagging: analysis of regional and global myocardial function]

Myocardial MR tagging is a powerful method which allows for assessment of myocardial function and may become an important tool for clinical evaluation of cardiac dysfunction, particularly in ischemic heart disease. In addition to visual assessment it allows direct quantification of myocardial deformation and strain to measure contractility. The use of myocardial tagging has provided new insights into the (patho)physiology of regional wall motion, and several parameters have been described as being useful to identify an ischemic response of the myocardium. One challenge encountered with tagging at 1.5 T is the fading of tags at end-diastole, greatly limiting the evaluation of myocardial function during diastole. Due to longer T(1) relaxation times of the myocardium, tagging at 3 T has shown to have a higher CNR(Tag) and better tag persistence when compared to current clinical gradient-echo tagging protocols at 1.5 T. As a consequence, tagging at higher field strengths may be well suited for the characterization of the diastolic portion of the cardiac cycle in future applications.