Chih-Liang Chin

MRI diffusion coefficients in spinal cord correlate with axon morphometry.

Following spinal cord injury, diffusion MRI (DWI) has been shown to detect injury and functionally significant neuroprotection following treatment that otherwise would go undetected with conventional MRI. The underlying histologic correlates to directional apparent diffusion coefficients (ADC) obtained with DWI have not been determined, however, and we address this issue by directly correlating ADC values with corresponding axon morphometry in the normal rat cervical spinal cord. ADC values transverse (perpendicular) and longitudinal (parallel) to axons both correlate with axon counts, however each directional ADC reflects distinct histologic parameters. DWI may therefore be capable of providing specific histologic data regarding the integrity of white matter.

An image‐based finite difference model for simulating restricted diffusion

Water diffusion in tissues is generally restricted and often anisotropic. Neural tissue is of particular interest, since it is well known that injury alters diffusion in a characteristic manner. Both Monte Carlo simulations and approximate analytical models have previously been reported in attempts to predict water diffusion behavior in the central nervous system. These methods have relied on axonal models, which assume simple geometries (e.g., ellipsoids, cylinders, and square prisms) and ignore the thickness of the myelin sheath. The current work describes a method for generating models using synthetic images. The computations are based on a 3D finite difference (FD) approximation of the diffusion equation. The method was validated with known analytic solutions for diffusion in a cylindrical pore and in a hexagonal array of cylinders. Therefore, it is envisioned that, by exploiting histologic images of neuronal tissues as input model, current method allows investigating the water diffusion behavior inside biological tissues and potentially assessing the status of neural injury and regeneration. Magn Reson Med 50:373–382, 2003.

Assessment of axonal fiber tract architecture in excised rat spinal cord by localized NMR q-space imaging: Simulations and experimental studies†

NMR q‐space imaging is a method designed to obtain information from porous materials where diffusion‐diffraction phenomena were observed from which pore size was derived. Recently, the technique has been applied to the study of biological structures as well. Although diffusive diffraction has so far not been observed in multicellular systems, displacement profiles have been used with some success as a means to estimate structure size. However, there have been no quantitative correlations of the retrieved structure sizes with histology. Clearly, the complexity of tissue architecture poses significant challenges to the interpretation of q‐space data. In this work, simulations were first performed on a two‐compartment model to demonstrate the effects of interference of the diffraction patterns arising from intra and extra‐axonal compartments and finite boundary permeability on q‐space data. Second, q‐space echo attenuation was simulated on the basis of histologic images of various rat spinal cord fiber tracts and the information obtained from the displacement profiles were compared with structural parameters computed from the histologic images. The results show that calculated mean displacements and kurtosis parallel mean axon size and axonal density. Finally, spatially localized q‐space measurements were carried out at the locations where simulations had previously been performed, resulting in displacement data that support those obtained by simulation. The data suggest the NMR q‐space approach has potential for nondestructive analysis of the axonal architecture in the mammalian spinal cord. Magn Reson Med 52:733–740, 2004.

Feasibility of probing boundary morphology of structured materials by 2D NMR q-space imaging

It is well known that one-dimensional (1D) q-space imaging allows retrieval of structural information at cellular resolution. Here we demonstrate by simulation that boundary morphology of structured materials can be derived from 2D q-space mapping. Based on a finite-difference model for restricted diffusion, 2D q-space maps obtained from water diffusion inside apertures at various levels of asperity were simulated. The results indicate that the observed ring patterns (diffraction minima) reveal the boundary profiles of the apertures but become blurred in the case of significant variation in aperture size. For uniform size distribution of apertures, a quantitative measure of surface roughness can be established by means of spatial autocorrelation analysis. The results suggest that 2D q-space imaging may allow probing of the boundary morphology of structured materials and possibly biological cells.