Computational system and method for modeling the heart

• US 5,947,899 A
• Filed: 08/23/1996
• Issued: 09/07/1999
• Est. Priority Date: 08/23/1996
• Status: Expired due to Fees

• Current Assignee: Physiome Sciences, Inc. (EPIX Pharmaceuticals, Inc.)
• Original Assignee: Physiome Sciences, Inc. (EPIX Pharmaceuticals, Inc.)
• Inventors: Scollan, David, Winslow, Raimond, Rounds, Donna
• Primary Examiner(s): Lateef, Marvin M.
• Assistant Examiner(s): SHAW, SHAWNA JEANNINE
• Application Number:
  US08/703,603
• Time in Patent Office: 1,110 Days
• Field of Search: 128/653.1, 128/653.2, 128/696, 128/699, 128/731, 128/920, 128/922, 128/923, 395/120, 395/924, 600/407, 600/410, 600/508, 600/512, 600/544
• US Class Current: 600/410
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: G09B 23/288 for artificial respiration or heart massage
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

A computational model for simulating and predicting the electrical and chemical dynamics of the heart. The model consists of a computerized representation of heart anatomy and a system of mathematical equations that describe the spatio-temporal behavior of biophysical quantities such as voltage at various locations throughout the heart. The computer process can present the temporal evolution of the biophysical quantities throughout the computerized anatomical model.

Claims

1. A computational model of a heart comprising:

a space defining a lattice having a set of nodes;

each of said nodes positioned in said lattice such that each node is adjacent to neighboring nodes;

whereby said lattice and node together define a three dimensional representation of at least a portion of the heart;

each node of said set of nodes representing a unit of the myocardium;

each node having a associated with it a set of state defining node equations for computing an action potential at the location of said node and for computing a node potential;

each node having associated with it a set of coupling relationships related to the anisotropic anatomic structure of the heart for computing the contribution to said node potential contributed by neighboring nodes;

whereby a total set of voltages at each of said nodes represents the global depolarization state of the heart.

23. The model of claim 1, wherein the coupling relationships related to anisotropic anatomic structure represents fiber orientation in the heart.

24. The model of claim 1, wherein the coupling relationships related to anisotropic anatomic structure represents the spatial distribution of gap junction channels.

2. A computational model of a heart comprising:

a cubic lattice having a set of N nodes;

each of said nodes positioned at a vertex of said lattice;

each node representing a biophysical computational unit of the heart;

each node having associated with it a set of state defining equations expressing state variables sufficient to compute node response at the next instant in time t+δ

t given node response at time t, said equations including at least one equation selected from biophysical processes selected from the set;

i) equations for time-varying, voltage-dependent transmembrane conductances permeable to ions, the temporal evolution of which are modeled using ordinary differential equations;

ii) equations for time-varying transmembrane ionic pump and exchanger currents, properties of which are modeled using algebraic equations;

iii) equations for time-varying Ca uptake, sequestration, and release currents modeling the regulation of intracellular Ca levels by cellular organelles, the properties of which are modeled using coupled systems of ordinary differential equations;

iv) equations for total transmembrane flux of each ionic species to which the cell membrane is permeable;

each node connection to neighboring nodes represented by an anisotropic coupling conductance, the value of which is defined by the anatomic relationship of the two nodes;

each node having a coupling current associated with it determined by the total current entering the node through all said coupling conductances defined at that node;

whereby said coupling currents and node state equations may be solved for the temporal evolution of all state variables at all nodes.

25. The model of claim 2, wherein the value of the anisotropic couple conductance represents in part the spatial distribution of gap junction channels.

32. The model of claim 2 wherein said equations for time-varying, voltage-dependent transmembrane conductances refer to sodium (Na), potassium (K), calcium (Ca), and/or chloride (CI)) ions.

3. A method for computing a model of a heart comprising the steps of:

a) defining a set of lattice nodes;

each lattice node representing a biophysical subunit of the heart;

each node having a set of biophysical equations for computing a total node current associated with ion transport in said biophysical subunit;

each node associated with at least five adjacent nodes;

each node coupled to neighboring nodes;

said coupling modeled as an anisotropic resistance;

b) solving said set of biophysical equations to determine said node currents;

c) summing said node current to determine the voltage present at each node resulting from the depolarization of each neighboring node;

d) displaying a representation of said computed voltage.

8. A method of modeling a cardiac disease state in a model of a heart as set forth in claim 3 comprising the additional steps of:

e) adjusting the lattice defining the anatomic structure of the heart such that anatomical structural changes known to occur in the heart during said disease state;

f) using said adjusted lattice to determine the magnitude of coupling conductances between nodes of the network such that the altered structure of the heart in the disease state, as represented by the adjusted lattice, is embedded in the network model;

g) adjusting parameters of the set of state defining equations, specifying properties of biochemical cellular processes defined at each node of the lattice, to reproduce changes in these parameters known to occur in said disease state;

h) adjusting initial values of state variables, the temporal evolution of which is determined by the set of equations specifying properties of biochemical cellular processes defined at each node of the lattice, in such a way as to reproduce changes in these state variables known to occur in said disease state;

i) solving for the temporal evolution of state variables, defined at each node of the lattice;

j) storing said state variables in a computer memory for graphical display and analysis.

12. A method of computing the model of claim 8 comprising the steps of:

i) partitioning the lattice into m nodes and assigning state variable computations to one of P processing units;

ii) concurrently computing state variables with the P processing units;

iii) computing the temporal evolution of all state variables and storing or displaying the results.

13. A method of computing the temporal evolution of state variables in the model of claim 3 on multiprocessor computers consisting of a set of P processors each with local memory of capacity M bytes, a communications network supporting data exchange between processors, and a global shared memory, with the method comprising the steps of:

e) partitioning the lattice into Q sets of nodes, referred to as node sets, in such a way that all state variable values at time t, parameters, and required temporary storage locations (work space) for any node set fits into the local memory available to any processing unit;

f) assignment of each node set to a specific processing unit and local memory associated with the specific processing unit;

g) inter-processor communication of any data required to compute new values of state variables for nodes positioned at the borders between different node sets;

h) concurrent execution on all P processors of the computations to compute new values of local state variables at time t+δ

t in each of the node sets that have been assigned to processing units;

i) iteration of steps b) and d) until computation of state variable values at time t+δ

t, where δ

t is small, and until all Q node sets are completed;

j) storage of the computed set of state variables on external storage devices for subsequent graphical display;

k) iteration of steps f)-j) until t+δ

t equals some end time T.

33. The method of claim 3 wherein said set of biophysical equations model the sodium (Na), potassium (K), calcium (Ca), and/or chloride (CI)) ion transport in said biophysical subunit.

4. A method for modeling a heart with a computer comprising:

a) defining a set of nodes;

each node representing a biophysical subunit of the heart;

each node having a membrane, defining an intracellular and an extracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said intracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said extracellular space;

each node having a set of biophysical equations associated with it for computing a transmembrane current between the intracellular and extracellular spaces;

b) defining a lattice including each of said nodes;

each node associated with a physical location in heart tissue;

each node connected with at least five adjacent nodes;

each node exhibiting an anisotropic coupling with neighboring nodes reflecting the anatomic relationship between such nodes;

said coupling modeled as a coupling resistance;

c) solving said set of biophysical equations to determine said node currents associated with extracellular and intracellular currents;

d) summing said node current to compute the voltage present at each node resulting from the depolarization of each node and the propagation of a depolarization wave front through each node;

e) displaying a representation of said computed voltage.

5. A model of a biological organ system comprising:

a plurality of nodes;

each node having associated therewith a set of state defining equations which take as their variables biophysical data, which are substantially local to the node itself;

each node having at least one state variable which takes as its argument parameters communicated solely from near neighbors;

a network containing all such nodes;

said network including anisotropic coupling relationships defined between each node and its near neighbor node wherein said coupling relationships are expressed as a set of state defining equations;

whereby said state defining variables can be solved iteratively and state variable values communicated to the network model, whereby said network equations can be computed for each node.

6. A method of defining a model comprising the steps of:

applying nuclear magnetic resonance imaging to a biological organ to generate a data file defining tensors associated with the distribution of water molecules within the physiologic organ;

applying said tensor dataset to a network to determine the magnitude of coupling conductances between nodes of the network such that the tensor information is reflected by the internodal conduction values of the network, thus embedding the anatomic characteristics of the organ in the model.

7. A method for using a multiple processor computer to solve for the temporal evolution of state variables defining biophysical and biochemical properties of nodes within a network model of a biological system comprising:

partitioning a lattice of nodes making up the network into N number of lattice subsets, such that each node within the network is included in at least one of said subsets;

associating state equations and state variables describing the biophysical and biochemical properties of each node in said subsets with particular processing units in the multiple processor computer such that each subset of nodes is associated with a distinct processing unit, and that all processing units are associated with at least one subset of nodes;

computing the temporal evolution of all state variables within each of the node subsets associated with distinct processing units concurrently across each of the processing units;

concurrently storing said state variables in computer memory;

displaying a sequence of said state variables.

9. A computational model of a heart comprising:

a computing device having computational and storage mechanisms;

a set of n nodes arranged in a cubic lattice stored in the storage mechanism, with each node having at least five neighbors;

each node having a set of state variable equations associated with it;

said equations describing biophysical and biochemical reactions at each node which may be solved to find the currents present at each node;

the lattice having a set of anisotropic coupling equations associated therewith defining the coupling between each node, which may be solved by the computational mechanism to determine the total voltage present at each node in the lattice to be stored in the storage mechanism.

10. A finite-difference computational model of a heart comprising:

a) a computer having memory;

b) a set of N nodes arranged in a cubic lattice stored in the memory with each node having at least five neighbors;

c) a subroutine procedure executable on the computer which uses experimentally measured data on fiber orientation within the heart for computing the connection currents between lattice nodes;

d) a multi-dimensional data array with individual elements F(N1,N2,N3, . . . S1,S2,S3, . . . SNeq) stored in the memory, the array having several position elements (N1, N2, and N3) specifying the position of each node within the cube lattice; and

state variable element Sx specifying the xth state variable for each node, and state variable value elements (S1,S2,S3, . . . SNeq) specifying the value of the SNeq variables at each node at time t;

e) a multi-dimensional data array F(N1,N2,N3,S1- S2-S3- . . . SNeq-) stored in the memory in which the variable Sx'"'"' denotes the time rate of change, dSx(t)/dt, of state variable x at time t;

f) a subroutine procedure executable on the computer which specifies an algorithm for computing elements of the multi-dimensional data array F(), with this subroutine procedure itself being composed of a number of subroutine procedures selected from a library of procedures corresponding to biophysical processes modeled at the sub-cellular level;

g) a subroutine procedure executable on the computer specifying a numerical integration algorithm for the computation of values of the state variables S1, S2, S3, . . . , SNeq at time t+δ

t given values of S1, S2, S3, . . . , Sneq and F(N1,N2,N3,S1- S2- S3- . . . SNeq) at time t.

11. A computational model of a heart comprising:

a) a computer having memory;

b) a set of n nodes arranged in a cubic lattice stored in the memory with each node having at least five neighbors;

c) each node having a set of state variable equations executable on the computer associated with it;

d) said state variable equations describing biophysical and biochemical reactions at each node which may be solved to find the currents present at each node based upon local parameters, and the voltages present at each node based upon local and near neighbor parameters;

e) the lattice having a set of anisotropic coupling equations associated therewith that are executable on the computer defining the coupling between each node, which may be solved to determine the total node voltage present at each node in the lattice.

14. A system for modeling a heart with a computer comprising:

a) a means for defining a set of nodes;

each node representing a biophysical subunit of the heart;

each node having a membrane, defining an intracellular and an extracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said intracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said extracellular space;

each node having a set of biophysical equations associated with it for computing a transmembrane current between the intracellular and extracellular spaces;

b) a means for defining a lattice including each of said nodes;

each node associated with a physical location in heart tissue;

substantially every node connected with at least five adjacent nodes;

each node exhibiting an anisotropic coupling with neighboring nodes reflecting the anatomic relationship between such nodes;

said coupling modeled as a coupling resistance;

c) a means for solving said set of biophysical equations to determine said node currents associated with extracellular and intracellular currents;

d) a means for summing said node current to compute the voltage present at each node resulting from the depolarization of each node and the propagation of a depolarization wave front through each node;

e) a means for displaying a representation of said computed voltage.

15. The system of claim 14 further comprising:

f) a means for modifying one or more of said biophysical equations to reflect the presence of a chemical input.

16. The system of claim 14 comprising:

f) a means for modifying one or more of said biophysical equations to reflect the presence of an electrical input.

17. A method for computing a model of a heart comprising the steps of:

a) defining a set of lattice nodes;

each lattice node representing a biophysical subunit of the heart;

each node having a set of biophysical equations for computing a total node current associated with ion transport in said biophysical subunit;

each node associated with at least five adjacent nodes;

each node coupled to neighboring nodes;

said coupling modeled as a resistance;

b) solving said set of biophysical equations to determine said node currents;

c) summing said node current to determine the voltage present at each node resulting from the depolarization of each neighboring node;

d) displaying a representation of said computed voltage;

e) adjusting the lattice defining the anatomic structure of the heart such that anatomical structural changes known to occur in the heart during said disease state;

f) using said adjusted lattice to determine the magnitude of coupling conductances between nodes of the network such that the altered structure of the heart in the disease state, as represented by the adjusted lattice, is embedded in the network model;

g) adjusting parameters of the set of state defining equations, specifying properties of biochemical cellular processes defined at each node of the lattice, to reproduce changes in these parameters known to occur in said disease state;

h) adjusting initial values of state variables, the temporal evolution of which is determined by the set of equations specifying properties of biochemical cellular processes defined at each node of the lattice, in such a way as to reproduce changes in these state variables known to occur in said disease state;

i) solving for the temporal evolution of state variables, defined at each node of the lattice; and

j) storing said state variables in a computer memory for graphical display and analysis.

34. The method of claim 17 wherein said set of biophysical equations for computing a total node current are associated with Na, Ca, and K ion species.

18. A method for computing a model of a heart comprising the steps of:

a) defining a set of lattice nodes;

each lattice node representing a biophysical subunit of the heart;

each node having a set of biophysical equations for computing a total node current associated with Na, Ca, and K ion transport in said biophysical subunit;

each node associated with at least five adjacent nodes;

each node coupled to neighboring nodes;

said coupling modeled as a resistance;

b) solving said set of biophysical equations to determine said node currents;

c) summing said node current to determine the voltage present at each node resulting from the depolarization of each neighboring node;

d) displaying a representation of said computed voltage;

e) adjusting the lattice defining the anatomic structure of the heart such that anatomical structural changes known to occur in the heart during said disease state;

f) using said adjusted lattice to determine the magnitude of coupling conductances between nodes of the network such that the altered structure of the heart in the disease state, as represented by the adjusted lattice, is embedded in the network model;

g) adjusting parameters of the set of state defining equations, specifying properties of biochemical cellular processes defined at each node of the lattice, to reproduce changes in these parameters known to occur in said disease state;

h) adjusting initial values of state variables, the temporal evolution of which is determined by the set of equations specifying properties of biochemical cellular processes defined at each node of the lattice, in such a way as to reproduce changes in these state variables known to occur in said disease state;

i) solving for the temporal evolution of state variables, defined at each node of the lattice;

j) storing said state variables in a computer memory for graphical display and analysis;

k) partitioning the lattice into m nodes and assigning state variable computations to one of P processing units;

l) concurrently computing state variables with the P processing units; and

m) computing the temporal evolution of all state variables and storing or displaying the results.

19. A method for computing a model of a heart on multiprocessor computers consisting of a set of P processors each with local memory of size M, a communications network supporting data exchange between processors, and a global shared memory, with the method comprising the steps of:

a) defining a set of lattice nodes;

each lattice node representing a biophysical subunit of the heart;

each node having a set of biophysical equations for computing a total node current associated with ion transport in said biophysical subunit;

each node associated with at least five adjacent nodes;

each node coupled to neighboring nodes;

said coupling modeled as a resistance;

b) solving said set of biophysical equations to determine said node currents;

c) summing said node current to determine the voltage present at each node resulting from the depolarization of each neighboring node;

d) displaying a representation of said computed voltage;

e) partitioning the lattice into Q sets of nodes, referred to as node sets, in such a way that all state variable values at time t, parameters, and required temporary storage locations for any node set fits into the local memory available to any processing unit;

f) assignment of each node set to a specific processing unit and local memory associated with the specific processing unit;

g) inter-processor communication of any data required to compute new values of state variables for nodes positioned at the borders between different node sets;

h) concurrent execution on all P processors of the computations to compute new values of local state variables at time t+δ

t in each of the node sets that have been assigned to processing units;

i) iteration of steps b) and d) until computation of state variable values at time t+δ

t, where delta t is small, and until all Q node sets are completed;

j) storage of the computed set of state variables on external storage devices for subsequent graphical display; and

k) iteration of steps f)-j) until t+δ

t equals some end time T.

20. A system for modeling a heart with a computer comprising:

a) a means for defining a set of nodes;

each node representing a biophysical subunit of the heart;

each node having a membrane, defining an intracellular and an extracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said intracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said extracellular space;

each node having a set of biophysical equations associated with it for computing a transmembrane current between the intracellular and extracellular spaces;

b) a means for defining a lattice including each of said nodes;

each node associated with a physical location in heart tissue;

substantially every node connected with at least five adjacent nodes;

each node exhibiting an anisotropic coupling with neighboring nodes reflecting the anatomic relationship between such nodes;

said coupling modeled as a coupling resistance;

c) a means for solving said set of biophysical equations to determine said node currents associated with extracellular and intracellular currents;

d) a means for summing said node current to compute the voltage present at each node resulting from the depolarization of each node and the propagation of a depolarization wave front through each node;

e) a means for displaying a representation of said computed voltage; and

f) a means for modifying one or more of said biophysical equations to reflect the presence of a chemical input.

21. A system for modeling a heart with a computer comprising:

a) a means for defining a set of nodes;

each node representing a biophysical subunit of the heart;

each node having a membrane, defining an intracellular and an extracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said intracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said extracellular space;

each node having a set of biophysical equations associated with it for computing a transmembrane current between the intracellular and extracellular spaces;

b) a means for defining a lattice including each of said nodes;

each node associated with a physical location in heart tissue;

substantially every node connected with at least five adjacent nodes;

each node exhibiting an anisotropic coupling with neighboring nodes reflecting the anatomic relationship between such nodes;

said coupling modeled as a coupling resistance;

c) a means for solving said set of biophysical equations to determine said node currents associated with extracellular and intracellular currents;

d) a means for summing said node current to compute the voltage present at each node resulting from the depolarization of each node and the propagation of a depolarization wave front through each node;

e) a means for displaying a representation of said computed voltage; and

f) a means for modifying one or more of said biophysical equations to reflect the presence of an electrical input.

22. A system for modeling a heart with a computer comprising:

a) a means for defining a set of nodes;

each node representing a biophysical subunit of the heart;

each node having a membrane, defining an intracellular and an extracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said intracellular space;

each node having set of biophysical equations associated with it for computing a coupling current associated with ion transport in said extracellular space;

each node having a set of biophysical equations associated with it for computing a transmembrane current between the intracellular and extracellular spaces;

b) a means for defining a lattice including each of said nodes;

each node associated with a physical location in heart tissue;

substantially every node connected with at least five adjacent nodes;

each node exhibiting an anisotropic coupling with neighboring nodes reflecting the anatomic relationship between such nodes;

said coupling modeled as a coupling resistance;

c) a means for solving said set of biophysical equations to determine said node currents associated with extracellular and intracellular currents;

d) a means for summing said node current to compute the voltage present at each node resulting from the depolarization of each node and the propagation of a depolarization wave front through each node;

e) a means for displaying a representation of said computed voltage; and

f) a means for modifying one or more of said biophysical equations to reflect the presence of a chemical compound input.

26. A method for computing a model of a heart comprising the steps of:

a) defining a lattice of nodes with each node representing a biophysical subunit of the heart;

b) defining a set of biophysical equations associated with ion transport in the biophysical subunit;

c) defining a set of coupling equations associated with electrical coupling between neighboring nodes;

d) adjusting the equations to reflect anatomical changes known to occur in the heart during said disease state;

e) computing voltage at each node utilizing the adjusted equations; and

f) displaying a representation of said computed voltage.

27. The method of claim 26, wherein the steps of computing voltage and displaying the computed voltage are repeated over time to represent the temporal evolution of the voltage.

28. The method of claim 26, wherein step d) further comprises adjusting the biophysical equations to reflect the changes in ion transport known to occur in the heart during the disease state.

29. The method of claim 26, wherein step d) further comprises adjusting the coupling equations to reflect the changes in electrical coupling between neighboring nodes known to occur in the heart during the disease state.

30. The method of claim 26, wherein step b) further comprises defining a first set of biophysical equations associated with ion transport between intracellular space and extracellular space and a second set of biophysical equations associated with ion transport in extracellular space.

31. A method of defining a model comprising the steps of:

applying nuclear magnetic resonance imaging to a biological organ to generate a data file defining tensors associated with the rate of diffusion of water molecules as determined by the anatomic structure of the physiologic organ;

applying said tensor dataset to a network to determine the magnitude of coupling conductances between nodes of the network such that the tensor information is reflected by the internodal conduction values of the network, thus embedding the anatomic characteristics of the organ in the model.