Ultrafast four-dimensional imaging of cardiac mechanical wave propagation with sparse optoacoustic sensing

Propagation of electromechanical waves in excitable heart muscles follows complex spatiotemporal patterns holding the key to understanding life-threatening arrhythmias and other cardiac conditions. Accurate volumetric mapping of cardiac wave propagation is currently hampered by fast heart motion, particularly in small model organisms. Here we demonstrate that ultrafast four-dimensional imaging of cardiac mechanical wave propagation in entire beating murine heart can be accomplished by sparse optoacoustic sensing with high contrast, ∼115-µm spatial and submillisecond temporal resolution. We extract accurate dispersion and phase velocity maps of the cardiac waves and reveal vortex-like patterns associated with mechanical phase singularities that occur during arrhythmic events induced via burst ventricular electric stimulation. The newly introduced cardiac mapping approach is a bold step toward deciphering the complex mechanisms underlying cardiac arrhythmias and enabling precise therapeutic interventions.

A Robot Mimicking Heart Motions: An Ex-Vivo Test Approach for Cardiac Devices

Purpose The pre-clinical testing of cardiovascular implants gains increasing attention due to the complexity of novel implants and new medical device regulations. It often relies on large animal experiments that are afflicted with ethical and methodical challenges. Thus, a method for simulating physiological heart motions is desired but lacking so far. Methods We developed a robotic platform that allows simulating the trajectory of any point of the heart (one at a time) in six degrees of freedom. It uses heart motion trajectories acquired from cardiac magnetic resonance imaging or accelero-meter data. The rotations of the six motors are calculated based on the input trajectory. A closed-loop controller drives the platform and a graphical user interface monitors the functioning and accuracy of the robot using encoder data. Results The robotic platform can mimic physiological heart motions from large animals and humans. It offers a spherical work envelope with a radius of 29 mm, maximum acceleration of 20 m/s2 and maximum deflection of ±19° along all axes. The absolute mean positioning error in x-, y- and z-direction is 0.21 ±0.06, 0.31 ±0.11 and 0.17 ±0.12 mm, respectively. The absolute mean orientation error around x-, y- and z-axis (roll, pitch and yaw) is 0.24 ±0.18°, 0.23 ±0.13° and 0.18 ±0.18°, respectively. Conclusion The novel robotic approach allows reproducing heart motions with high accuracy and repeatability. This may benefit the device development process and allows re-using previously acquired heart motion data repeatedly, thus avoiding animal trials.

A Probabilistic Approach for Contact Stability and Contact Safety Analysis of Robotic Intracardiac Catheter

The disturbances caused by the blood flow and tissue surface motions are major concerns during the motion planning of a intracardiac robotic catheter. Maintaining a stable and safe contact on the desired ablation point is essential for achieving effective lesions during the ablation procedure. In this paper, a probabilistic formulation of the contact stability and the contact safety for intravascular cardiac catheters under the blood flow and surface motion disturbances is presented. Probabilistic contact stability and contact safety metrics, employing a sample based representation of the blood flow velocity distribution and the heart motion trajectory, are introduced. Finally, the contact stability and safety for a MRI-actuated robotic catheter under main pulmonary artery blood flow disturbances and left ventricle surface motion disturbances are analyzed in simulation as example scenarios.

Contact Stability and Contact Safety of a Magnetic Resonance Imaging-Guided Robotic Catheter Under Heart Surface Motion

Contact force quality is one of the most critical factors for safe and effective lesion formation during catheter based atrial fibrillation ablation procedures. In this paper, the contact stability and contact safety of a novel magnetic resonance imaging (MRI)-actuated robotic cardiac ablation catheter subject to surface motion disturbances are studied. First, a quasi-static contact force optimization algorithm, which calculates the actuation needed to achieve a desired contact force at an instantaneous tissue surface configuration is introduced. This algorithm is then generalized using a least-squares formulation to optimize the contact stability and safety over a prediction horizon for a given estimated heart motion trajectory. Four contact force control schemes are proposed based on these algorithms. The first proposed force control scheme employs instantaneous heart position feedback. The second control scheme applies a constant actuation level using a quasi-periodic heart motion prediction. The third and the last contact force control schemes employ a generalized adaptive filter-based heart motion prediction, where the former uses the predicted instantaneous position feedback, and the latter is a receding horizon controller. The performance of the proposed control schemes is compared and evaluated in a simulation environment.

Systolic stretching of the ascending aorta

IntroductionLongitudinal stretching of the aorta due to systolic heart motion contributes to the stress in the wall of the ascending aorta. The objective of this study was to assess longitudinal systolic stretching of the aorta and its correlation with the diameters of the ascending aorta and the aortic root.Material and methodsAortographies of 122 patients were analyzed. The longitudinal systolic stretching of the aorta caused by the contraction of the heart during systole and the maximum dimensions of the aortic root and ascending aorta were measured in all patients.ResultsThe maximum dimension of the aortic root was on average 34.9 ±4.5 mm and the mean diameter of the ascending aorta was 33.9 ±5.4 mm. The systolic aortic stretching negatively correlated with age (r = –0.49, p < 0.001) and the diameter of the tubular ascending aorta (r = –0.44, p < 0.001). There was no significant correlation between the stretching and the dimension of the aortic root (r = –0.11, p = 0.239). There was a statistically significant (p < 0.001) difference in the longitudinal aortic stretching values between patients with a normal aortic valve (10.6 ±3.1 mm) and an aortic valve pathology (8.0 ±3.2 mm in all patients with an aortic valve pathology; 7.5 ±4.3 mm in isolated aortic stenosis, 8.5 ±2.9 mm in the case of isolated insufficiency, 8.2 ±2.8 mm for valves that were both stenotic and insufficient).ConclusionsSystolic aortic stretching negatively correlates with the diameter of the tubular ascending aorta and the age of the patients, and does not correlate with the diameter of the aortic root. It is lower in patients with an aortic valve pathology.

MEMBRANE FINITE ELEMENT FOR MODELING HEART WALL

Modeling of heart wall deformation remains a challenge due to complex structure of tissue, which contains different group of cells and connective tissue. Muscle cells are dominant where, besides stresses coming from tissue deformation, active stresses are generated representing the load which produces heart motion and function. These cells form a helicoidal structure within so- called wall sheets and are considered as tissue fibers. Usual approach in the finite element (FE) discretization is to use 3D isoparametric elements. The dominant stresses lie in the sheet planes, while normal stresses in the wall normal directions are of the order smaller. Taking this stress state into account, we explore a possibility to model heart wall by membrane finite elements, hence considering the wall as a thick membrane (shell without bending effects). The membrane element is composite, containing layers over the thickness and variation of the direction of fibers. The formulated element is applied to a simplified left ventricle geometry to demonstrate a possibility to simulate heart mechanics by models which are much smaller and simpler for use than 3D conventional models.