Method and system for comprehensive patient-specific modeling of the heart

Abstract

The present invention relates to methods and systems for comprehensive patient-specific modeling of the heart. A method and system for patient-specific modeling of overall cardiac anatomy, dynamics, hemodynamics, and fluid-structure interactions from 4D medical image data is disclosed. The anatomy and dynamics of the heart are determined by estimating patient-specific parameters of a physiological model of the heart from 4D medical image data for the patient. The patient-specific anatomy and dynamics are used as input to a 3D Navier-Stokes solver that derives the actual hemodynamics subject to topographic constraints along the entire cardiac cycle. Fluid-structure interactions are determined iteratively during the heart cycle by simulating blood flow at a given time step and calculating deformations of cardiac structures based on the simulated blood flow such that in the blood flow simulation at the next time step The deformation of the heart structure is used.

Description

[0001] This application claims U.S. Provisional Application No. 61 / 366,294, filed July 21, 2010, U.S. Provisional Application No. 61 / 383,942, filed September 17, 2010, and U.S. Provisional Application No. 61 / 409,633, the disclosure of which is incorporated herein by reference. technical field [0002] The present invention relates to modeling the heart using medical images, and more particularly to patient-specific comprehensive modeling of the heart based on 4D medical image data. Background technique [0003] Heart disease is the leading cause of death for both men and women in the United States and accounts for no less than 30 percent of all deaths worldwide. Although medical advances in recent years have provided important improvements in the diagnosis and treatment of complex heart disease such as valvular disease, thoracic aortic aneurysm, and tetralogy of Fallot, premature onset still occurs in large numbers and death (morality). Large amounts of morphological and ...

AI Technical Summary

Problems solved by technology

But due to lags in data understanding, physicians are forced to make critically important decisions based on a limited range of measurements and methods

These limitations are due at least in part to the lack of efficient and accurate estimation of patient-specific parameters describing cardiac-aortic anatomy, physiology, and hemodynamics, and the absence of disease progression models

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