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Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture.

ABSTRACT: Diffusion tensor imaging (DTI) consistently detects increased mean diffusivity and decreased fractional anisotropy with advancing age in regions of primarily single white matter (WM) fiber populations, but findings have been inconsistent in regions of more complex fiber architecture. Given that DTI remains more common for characterizing aging WM than advanced diffusion MRI models due to DTI's simplicity, robustness, and efficiency, it is critical to strive to maximize the information extracted from DTI across the entire WM. The present study uses an orthogonal diffusion tensor decomposition based on the 3 eigenvalue moments (mean diffusivity, norm of anisotropy, and mode of anisotropy), yielding clear voxelwise degeneration patterns across the WM, including regions of complex fiber architecture. This indicates that the previous challenges of DTI in these regions were due to the choice of tensor decomposition rather than the DTI model itself. This study therefore presents a revised view of DTI of aging WM and indicates how age-related degeneration in complex fiber architecture can manifest in forms other than decreased fractional anisotropy.

SUBMITTER: Chad JA

PROVIDER: S-EPMC10902820 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture.

Chad Jordan A JA Pasternak Ofer O Chen J Jean JJ

Neurobiology of aging 20210203

Diffusion tensor imaging (DTI) consistently detects increased mean diffusivity and decreased fractional anisotropy with advancing age in regions of primarily single white matter (WM) fiber populations, but findings have been inconsistent in regions of more complex fiber architecture. Given that DTI remains more common for characterizing aging WM than advanced diffusion MRI models due to DTI's simplicity, robustness, and efficiency, it is critical to strive to maximize the information extracted f ...[more]

PMID: 33610963

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Project description:Spinal diffusion tensor imaging (sDTI) is still a challenging technique for selectively evaluating anatomical areas like the pyramidal tracts (PT), dorsal columns (DC), and anterior horns (AH) in clinical routine and for reliably quantifying white matter anisotropy and diffusivity. In neurodegenerative diseases, the value of sDTI is promising but not yet well understood. The objective of this prospective, single-center study was to evaluate the long fiber tract degeneration within the spinal cord in normal aging (n = 125) and to prove its applicability in pathologic conditions as in patients with molecular genetically confirmed hereditary spastic paraplegias (HSP; n = 40), a prototypical disease of the first motor neuron and in some genetic variants with affection of the dorsal columns. An optimized monopolar Stejskal-Tanner sequence for high-resolution, axial sDTI of the cervical spinal cord at 3.0 T with advanced standardized evaluation methods was developed for a robust DTI value estimation of PT, DC, and AH in both groups. After sDTI measurement at C2, an automatic motion correction and an advanced semi-automatic ROI-based, standardized evaluation of white matter anisotropy and diffusivity was performed to obtain regional diffusivity measures for PT, DC, and AH. Reliable and stable sDTI values were acquired in a healthy population without significant decline between age 20 and 65. Reference values for PT, DC, and AH for fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) were established. In HSP patients, the decline of the long spinal fiber tracts could be demonstrated by diffusivity abnormalities in the pyramidal tracts with significantly reduced PTFA (p < 0.001), elevated PTRD (p = 0.002) and reduced PTMD (p = 0.003) compared to healthy controls. Furthermore, FA was significantly reduced in DCFA (p < 0.001) with no differences in AH. In a genetically homogeneous subgroup of SPG4 patients (n = 12) with affection of the dorsal columns, DCRD significantly correlated with the overall disease severity as measured by the Spastic Paraplegia Rating Scale (SPRS) (r = - 0.713, p = 0.009). With the most extensive sDTI study in vivo to date, we showed that axial sDTI combined with motion correction and advanced data post-processing strategies enables robust measurements and is ready to use, allowing recognition and quantification of disease- and age-related changes of the PT, DC, and AH. These results may also encourage the usage of sDTI in other neurodegenerative diseases with spinal cord involvement to explore its capability as selective biomarkers.

Project description:Microstructure imaging techniques based on tensor-valued diffusion encoding have gained popularity within the MRI research community. Unlike conventional diffusion encoding-applied along a single direction in each shot-tensor-valued encoding employs diffusion encoding along multiple directions within a single preparation of the signal. The benefit is that such encoding may probe tissue features that are not accessible by conventional encoding. For example, diffusional variance decomposition (DIVIDE) takes advantage of tensor-valued encoding to probe microscopic diffusion anisotropy independent of orientation coherence. The drawback is that tensor-valued encoding generally requires gradient waveforms that are more demanding on hardware; it has therefore been used primarily in MRI systems with relatively high performance. The purpose of this work was to explore tensor-valued diffusion encoding on clinical MRI systems with varying performance to test its technical feasibility within the context of DIVIDE. We performed whole-brain imaging with linear and spherical b-tensor encoding at field strengths between 1.5 and 7 T, and at maximal gradient amplitudes between 45 and 80 mT/m. Asymmetric gradient waveforms were optimized numerically to yield b-values up to 2 ms/μm2. Technical feasibility was assessed in terms of the repeatability, SNR, and quality of DIVIDE parameter maps. Variable system performance resulted in echo times between 83 to 115 ms and total acquisition times of 6 to 9 minutes when using 80 signal samples and resolution 2×2×4 mm3. As expected, the repeatability, signal-to-noise ratio and parameter map quality depended on hardware performance. We conclude that tensor-valued encoding is feasible for a wide range of MRI systems-even at 1.5 T with maximal gradient waveform amplitudes of 33 mT/m-and baseline experimental design and quality parameters for all included configurations. This demonstrates that tissue features, beyond those accessible by conventional diffusion encoding, can be explored on a wide range of MRI systems.

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Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture.

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Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture.

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