Computational hemodynamic modeling based on transesophageal echocardiographic imaging

Patient-specific mitral valve closure prediction using 3D echocardiography

This article presents an approach to modeling the closure of the mitral valve using patient-specific anatomical information derived from 3D transesophageal echocardiography (TEE). Our approach uses physics-based modeling to solve for the stationary configuration of the closed valve structure from the patient-specific open valve structure, which is recovered using a user-in-the-loop, thin-tissue detector segmentation. The method uses a tensile shape-finding approach based on energy minimization. This method is employed to predict the aptitude of the mitral valve leaflets to coapt. We tested the method using 10 intraoperative 3D TEE sequences by comparing the closed valve configuration predicted from the segmented open valve with the segmented closed valve, taken as ground truth. Experiments show promising results, with prediction errors on par with 3D TEE resolution and with good potential for applications in pre-operative planning.

Patient-specific modeling of stress/strain for surgical planning and guidance

We describe a method for performing modeling and simulation to predict the strain and stress experienced by tissues resulting from reconstructive cardiothoracic surgery. Stress computation is an important predictor of the quality and longevity of a repair and can therefore be used as guidance by a surgeon when deciding between various repair options. This paper uses the mitral valve repair as a use case because of its relevance and prevalence among reconstructive cardiac interventions. The modeling method presented here is informed by the patient specific anatomical structure recovered from real time 3D echocardiography. The method exploits hyperelastic models to infer realistic strain-stresses. We show through experiments using actual clinical data that results are in line with physiological expectations.

A personalized mitral valve closure simulator

We describe a method for performing modeling and simulation to predict the closure of the Mitral Valve (MV) using patient specific anatomical information derived from 3D Transesophageal Echocardiography (3D TEE). The ability to predict the MV closure behavior is an important step along the way of developing personalized simulation tools that would allow a surgeon to perform preoperative planning and decide between various MV repair options. While the MV is an important use case because of its relevance and prevalence among reconstructive cardiac interventions, the study described here can provide a blueprint to perform pre-operative planning for other cardiac surgical interventions. The method reported here exploits the Saint Venant-Kirchhoff elasticity model that is tuned to match empirical observations of the MV strainstress behavior. Using intraoperative 3D TEE data, the proposed simulator was evaluated over 10 test cases and resulted in mean prediction absolute error values of 1.81 mm.

Valvular closure prediction using anisotropic and hyperelastic tissue models and individualized anatomy derived from RT3DE

We describe a method for modeling the closure of the Mitral Valve (MV) and to compute realistic strain and stresses in MV tissues. This informs preoperative planning by allowing a surgeon to evaluate various MV repairs options. The modeling method exploits individualized (patient-specific) anatomical structure recovered from real-time 3D echocardiography (RT3DE). This study utilizes hyperelastic models of the MV tissues and employs patient specific leaflets, chordal length assessment and annulus shapes. We report experiments on ten intraoperative test cases, where we compute strain and stresses using several different tissue models from MV empirical studies by May-Newman and Holzapfel.