Subject-specific assessment of neurological disorders with biochemical propagation mechanisms

A method for subject-specific assessment of neurological disorders, the method comprising:

• receiving 3D image data representative of a subject's brain, wherein the 3D image data comprises (i) structural data representative of structures in the subject's brain and (ii) diffusion data representative of diffusion of fluid through the subject's brain;
• identifying subject-specific anatomical structures in the 3D image data;
• identifying a plurality of subject-specific anatomical connections in the subject's brain using the diffusion data;
• generating a surface mesh of the subject's brain based on the 3D image data;
• applying an inflation process to the surface mesh to yield an inflated mesh;
• applying a flattening process to the inflated mesh to yield the flattened representation of the subject's brain;
• imposing a grid on the flattened representation of the subject's brain using the subject-specific anatomical structures, wherein the grid comprises a plurality of grid nodes and a plurality of edges connecting the grid nodes;
• weighing the edges of the grid based on the subject-specific anatomical connections, thereby yielding a weighted grid;
• generating a subject-specific model for electrical dynamics using the weighted grid, wherein the subject-specific model for electrical dynamics utilizes one or more Lattice Boltzmann methods;
• dividing the grid into a plurality of blocks;
• using a parallel computing platform to compute one or more functional indicators of neurological disorder by executing multiple copies of the subject-specific model for electrical dynamics in parallel, wherein each respective copy corresponds to one of the plurality of blocks.

A system for calculating electrical wave propagation across a subject's brain, the system comprising:

• one or more imaging devices configured to acquire 3D image data representative of a subject's brain, wherein the 3D image data comprises (i) structural data representative of structures in the subject's brain and (ii) diffusion data representative of diffusion of fluid through the subject's brain;
• a modeling computing system operably coupled to the imaging devices and configured to use a plurality of processors to simulate electrical dynamics across the subject's brain, the processors performing the modeling computing system comprising system memory storing instructions, which instructions are configures to perform a method comprising:
• identifying subject-specific anatomical structures in the 3D image data,
• identifying a plurality of subject-specific anatomical connections in the subject's brain using the diffusion data,
• using the 3D image data to perform surface based analysis of the subject's brain, yielding a flattened representation of the subject's brain,
• imposing a grid on the flattened representation of the subject's brain using the subject-specific anatomical structures and the subject-specific anatomical connections, wherein the grid comprises a plurality of grid nodes and a plurality of edges connecting the grid nodes,
• weighing the edges of the grid based on the subject-specific anatomical connections, thereby yielding a weighted grid;
• creating a subject-specific model for electrical dynamics based on the weighted grid, wherein the subject-specific model for electrical dynamics utilizes one or more Lattice Boltzmann methods, and
• calculating electrical wave propagation from an initial spreading point using the subject-specific model for electrical dynamics, wherein the Lattice Boltzmann methods are used to parallelize at least a portion of computations performed by the subject-specific model across the processors.