White-Matter Biomarker Modeling for Neurodegenerative Disease Staging

The patent introduces multiple intermediary computational models and processing steps between the raw diffusion MRI data and the final white matter microstructure quantification. These include diffusion tensor modeling, fiber orientation distribution functions, and multi-compartment models that act as intermediaries to translate imaging data into meaningful biological metrics, thereby resolving the gap between imaging capability and measurement precision

The patent replaces direct mechanical/physical measurement of white matter microstructure with computational and mathematical modeling approaches. Instead of directly measuring axonal density or myelin content, the system uses diffusion MRI signal processing, tensor analysis, and algorithmic reconstruction to infer these properties, substituting physical measurement limitations with computational analysis capabilities

The patent segments the complex analysis process into distinct modular components: data acquisition, preprocessing, diffusion modeling, fiber tractography, and biomarker calculation. Each module handles a specific aspect of the analysis, making the overall complex system manageable while maintaining high quantification capability through specialized processing at each stage

The patent transforms the analysis from simple visual or basic metric assessment to multi-parameter quantitative evaluation. It introduces and calculates multiple diffusion parameters (FA, MD, axial diffusivity, radial diffusivity) and derives composite biomarkers that provide comprehensive white matter characterization, changing the parameter space from simple to complex in a controlled manner