Spectral Diffusion Analysis

Definition: 'Spectral diffusion analysis' is an advanced MRI-based computational method that decomposes diffusion-weighted signals into frequency components to estimate tissue-specific microstructural properties.

This technique allows quantification of compartmentalized diffusion behaviors—such as intracellular, interstitial, and restricted diffusion—by analyzing the diffusion spectrum rather than assuming a single apparent diffusion coefficient (ADC).

Purpose and Utility:

• Estimates surrogate markers for:
  1. Interstitial fluid volume fraction (F_int)
  2. Interstitial diffusivity (D_int)
• Differentiates between tissue compartments (cellular vs. extracellular)
• Detects subtle alterations in microstructural water dynamics
• Enhances diagnostic sensitivity in conditions like:
  1. Idiopathic normal pressure hydrocephalus (iNPH)
  2. White matter pathology
  3. Brain tumors

Methodological Principles:

• Uses multi-b-value and/or multi-diffusion time datasets
• Applies Fourier or inverse Laplace transforms to diffusion signals
• Generates a diffusion spectrum, characterizing signal contributions from various mobility ranges
• Allows non-invasive inference of tissue complexity and fluid dynamics

Advantages:

• More sensitive than conventional ADC to subtle microstructural changes
• Enables modeling of fluid mobility and volume fraction in interstitial compartments
• Provides physiologically interpretable parameters

Limitations:

• Requires high-quality multi-shell or multi-tensor diffusion MRI
• Computationally intensive
• Interpretation may depend on model assumptions

Clinical Relevance:

• In iNPH, increased F_int and altered D_int may reflect glymphatic dysfunction and extracellular space expansion
• Helps in evaluating response to shunt surgery or fluid clearance impairment