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Longitudinal diffusion tensor imaging in frontotemporal dementia.

Mahoney CJ, Simpson IJ, Nicholas JM, Fletcher PD, Downey LE, Golden HL, Clark CN, Schmitz N, Rohrer JD, Schott JM, Zhang H, Ourselin S, Warren JD, Fox NC - Ann. Neurol. (2014)

Bottom Line: MAPT carriers had the greatest change within left uncinate fasciculus (FA: -7.9%/yr, p < 0.001; MD: 10.9%/yr, p < 0.001); sporadic bvFTD and C9ORF72 carriers had the greatest change within right paracallosal cingulum (sporadic bvFTD, FA: -6.7%/yr, p < 0.001; MD: 3.8%/yr, p = 0.001; C9ORF72, FA: -6.8%/yr, p = 0.004).Sample size estimates using FA change were substantially lower than neuropsychological or whole brain measures of change.Serial DTI scans may be useful for measuring disease progression in bvFTD, with particular trajectories of WM damage emerging.

View Article: PubMed Central - PubMed

Affiliation: Dementia Research Centre, UCL Institute of Neurology, University College London, London, United Kingdom.

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Overview of processing pipeline for longitudinal diffusion tensor imaging analysis. AX = axial diffusivity; DT = diffusion tensor; FA = fractional anisotropy; GW = group-wise; MD = mean diffusivity; RD = radial diffusivity. [Color figure can be viewed in the online issue, which is available at http://www.annalsofneurology.org.]
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fig01: Overview of processing pipeline for longitudinal diffusion tensor imaging analysis. AX = axial diffusivity; DT = diffusion tensor; FA = fractional anisotropy; GW = group-wise; MD = mean diffusivity; RD = radial diffusivity. [Color figure can be viewed in the online issue, which is available at http://www.annalsofneurology.org.]

Mentions: Registration of DTI images was carried out using a previously published method carried out on the same magnetic resonance scanner (see Fig 1 for an overview).14 This method has also been shown to have good reproducibility of DTI metrics when performing repeated DTI measurements on the same subject. Tensor-based registration was performed using the DTI-TK (http://dti-tk.sourceforge.net) software package,15 which uses the full diffusion tensor information to drive the registration and improve the alignment of white matter structures.16 Within-subject DTI templates are created using an iterative process of initial rigid registration, followed by nonlinear registration. This process is repeated using the intrasubject templates to create an intersubject groupwise template. A single deformation field was estimated for each original image to the groupwise template by combining the deformations fields from the intra- and intersubject registration stages. This facilitates a single interpolation of the original DTI images to the intersubject groupwise mean. Maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AX), and radial diffusivity (RD) were then created for each registered diffusion tensor image in the groupwise space.


Longitudinal diffusion tensor imaging in frontotemporal dementia.

Mahoney CJ, Simpson IJ, Nicholas JM, Fletcher PD, Downey LE, Golden HL, Clark CN, Schmitz N, Rohrer JD, Schott JM, Zhang H, Ourselin S, Warren JD, Fox NC - Ann. Neurol. (2014)

Overview of processing pipeline for longitudinal diffusion tensor imaging analysis. AX = axial diffusivity; DT = diffusion tensor; FA = fractional anisotropy; GW = group-wise; MD = mean diffusivity; RD = radial diffusivity. [Color figure can be viewed in the online issue, which is available at http://www.annalsofneurology.org.]
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4305215&req=5

fig01: Overview of processing pipeline for longitudinal diffusion tensor imaging analysis. AX = axial diffusivity; DT = diffusion tensor; FA = fractional anisotropy; GW = group-wise; MD = mean diffusivity; RD = radial diffusivity. [Color figure can be viewed in the online issue, which is available at http://www.annalsofneurology.org.]
Mentions: Registration of DTI images was carried out using a previously published method carried out on the same magnetic resonance scanner (see Fig 1 for an overview).14 This method has also been shown to have good reproducibility of DTI metrics when performing repeated DTI measurements on the same subject. Tensor-based registration was performed using the DTI-TK (http://dti-tk.sourceforge.net) software package,15 which uses the full diffusion tensor information to drive the registration and improve the alignment of white matter structures.16 Within-subject DTI templates are created using an iterative process of initial rigid registration, followed by nonlinear registration. This process is repeated using the intrasubject templates to create an intersubject groupwise template. A single deformation field was estimated for each original image to the groupwise template by combining the deformations fields from the intra- and intersubject registration stages. This facilitates a single interpolation of the original DTI images to the intersubject groupwise mean. Maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AX), and radial diffusivity (RD) were then created for each registered diffusion tensor image in the groupwise space.

Bottom Line: MAPT carriers had the greatest change within left uncinate fasciculus (FA: -7.9%/yr, p < 0.001; MD: 10.9%/yr, p < 0.001); sporadic bvFTD and C9ORF72 carriers had the greatest change within right paracallosal cingulum (sporadic bvFTD, FA: -6.7%/yr, p < 0.001; MD: 3.8%/yr, p = 0.001; C9ORF72, FA: -6.8%/yr, p = 0.004).Sample size estimates using FA change were substantially lower than neuropsychological or whole brain measures of change.Serial DTI scans may be useful for measuring disease progression in bvFTD, with particular trajectories of WM damage emerging.

View Article: PubMed Central - PubMed

Affiliation: Dementia Research Centre, UCL Institute of Neurology, University College London, London, United Kingdom.

Show MeSH
Related in: MedlinePlus