Parallel processing coronary circulation simulation method and simulator apparatus using newton-raphson analysis

Patent metadata

Field	Value
Publication number	US-10013533-B2
Application number	US-201313874904-A
Country	US
Kind code	B2
Filing date	May 1, 2013
Priority date	May 11, 2012
Publication date	Jul 3, 2018
Grant date	Jul 3, 2018

Abstract

A geometric model of an organ represents its shape as a collection of elements formed from nodes and connections among them. A first vessel network model represents a network of first vessels whose diameters are larger than or equal to a threshold. A plurality of second vessel networks each represent a network of second vessels whose diameters are smaller than the threshold. In a simulator apparatus, a first analysis unit analyzes hemodynamics in the first vessels, based on the geometric model and first vessel network model of the organ and reflecting the motion of the organ. A second analysis unit analyzes hemodynamics in the second vessel network models connected to the nodes, by using output data of the first analysis unit which indicates the hemodynamics in the first vessels at each of the nodes.

First claim

What is claimed is:

1. A coronary circulation simulation method executed by a first processor and a plurality of second processors, each of the first and the second processors being coupled to a storage device, the coronary circulation simulation method comprising:
storing a geometric model representing a shape of a heart as a collection of elements formed from a plurality of nodes and a plurality of connections among the nodes in the storage device;
receiving a first vessel network model representing a network of first vessels whose diameters are larger than or equal to a specified threshold, wherein the first vessel network model is a macro model;
storing the first vessel network model in the storage device;
receiving a plurality of second vessel network models each representing a network of second vessels whose diameters are smaller than the specified threshold, the plurality of second vessel network models being independent of each other, wherein one or more of the second vessel network models are connected to each of the nodes, wherein the second vessel network models are micro models;
storing the plurality of second vessel network models in the storage device;
first analyzing, by the first processor, first hemodynamics in the first vessels belonging to the first vessel network model, based on the geometric model of the heart;
second analyzing, by the plurality of second processors in parallel without interactions, second hemodynamics in the second vessels belonging to the second vessel network models connected to the plurality of nodes, by using blood pressure data in the first vessels at the nodes, the blood pressure data being included in result data of the first analyzing which indicates the first hemodynamics in the first vessels at each of the nodes; and
outputting the first hemodynamics in the first vessels and the second hemodynamics in the second vessels,
wherein:
the first analyzing and the second analyzing include analyzing the first and the second hemodynamics in the first and second vessels reflecting motion of the heart by using a Newton-Raphson method for nonlinear analysis, and are performed alternately;
the second analyzing includes calculating tentative blood pressure increments in the second vessel network models by using an equation from which first blood pressure increments in the first vessel network model have been eliminated;
the first analyzing includes calculating the first blood pressure increments in the first vessel network model by using the tentative blood pressure increments in the second vessel network models; and
the second analyzing includes calculating second blood pressure increments in the second vessel network models by using the first blood pressure increments in the first vessel network model.

2. The coronary circulation simulation method according to claim 1 , wherein:
the second vessel network model includes capillaries and intermediate-layer vessels placed at opposite ends of the capillaries to connect the capillaries with the first vessels defined in the first vessel network model; and
the intermediate-layer vessels are divided into arterial vessels and venous vessels which are symmetrically arranged with respect to the capillaries.

3. The coronary circulation simulation method according to claim 1 , wherein a larger number of second vessel network models are connected to a node with a higher vessel density, so as to reflect an anatomical feature of the heart.

4. The coronary circulation simulation method according to claim 1 , wherein a larger number of second vessel network models are placed at the nodes on an endocardial side of a wall of the heart than at the nodes on an epicardial side of the wall of the heart.

5. A coronary circulation simulator apparatus comprising:
a storage device;
a first processor and a plurality of second processors configured to perform a procedure, each of the first and the second processors being coupled to the storage device, the procedure including:
storing a geometric model representing a shape of a heart as a collection of elements formed from a plurality of nodes and a plurality of connections among the nodes in the storage device;
receiving a first vessel network model representing a network of first vessels whose diameters are larger than or equal to a specified threshold, wherein the first vessel network model is a macro model;
storing the first vessel network model in the storage device;
receiving a plurality of second vessel network models each representing a network of second vessels whose diameters are smaller than the specified threshold, the plurality of second vessel network models being independent of each other, wherein one or more of the second vessel network models are connected to each of the nodes, wherein the second vessel network models are micro models;
storing the plurality of second vessel network models in the storage device;
first analyzing, by the first processor, first hemodynamics in the first vessels belonging to the first vessel network model, based on the geometric model of the heart; and
second analyzing, by the plurality of second processors in parallel without interactions, second hemodynamics in the second vessels belonging to the second vessel network models connected to the plurality of nodes, by using blood pressure data in the first vessels at the nodes, the blood pressure data being included in result data of the first analyzing which indicates the first hemodynamics in the first vessels at each of the nodes; and
outputting the first hemodynamics in the first vessels and the second hemodynamics in the second vessels,

wherein:
the first analyzing and the second analyzing include analyzing the first and the second hemodynamics in the first and second vessels reflecting motion of the heart by using a Newton-Raphson method for nonlinear analysis, and are performed alternately;
the second analyzing includes calculating tentative blood pressure increments in the second vessel network models by using an equation from which first blood pressure increments in the first vessel network model have been eliminated;
the first analyzing includes calculating the first blood pressure increments in the first vessel network model by using the tentative blood pressure increments in the second vessel network models; and
the second analyzing includes calculating second blood pressure increments in the second vessel network models by using the first blood pressure increments in the first vessel network model.

6. A non-transitory computer-readable medium storing a program for execution by a computer including a first processor and a plurality of second processors , each of the first and the second processors being coupled to a storage device, the program causing the computer to perform a procedure comprising:
storing a geometric model representing a shape of a heart as a collection of elements formed from a plurality of nodes and a plurality of connections among the nodes in the storage device;
receiving a first vessel network model representing a network of first vessels whose diameters are larger than or equal to a specified threshold, wherein the first vessel network model is a macro model;
storing the first vessel network model in the storage device;
receiving a plurality of second vessel network models each representing a network of second vessels whose diameters are smaller than the specified threshold, the plurality of second vessel network models being independent of each other, wherein one or more of the second vessel network models are connected to each of the nodes, wherein the second vessel network models are micro models;
storing the plurality of second vessel network models in the storage device;
first analyzing, by the first processor, first he

Assignees

• Fujitsu Ltd
• Univ Tokyo

Inventors

• Iwamura Takashi
• Hisada Toshiaki
• Sugiura Seiryo
• Washio Takumi
• Okada Junichi

Classifications

• G16H50/50 Primary

  for simulation or modelling of medical disorders · CPC title

• G06F30/23 Primary

  using finite element methods [FEM] or finite difference methods [FDM] · CPC title

• G06F19/3437 Primary

  Physics · mapped topic

• G06F17/5018

  Physics · mapped topic