MRI signatures of brain macrostructural atrophy and microstructural degradation in frontotemporal lobar degeneration subtypes

Abstract

Brain magnetic resonance imaging (MRI) studies have demonstrated regional patterns of brain macrostructural atrophy and white matter microstructural alterations separately in the three major subtypes of frontotemporal lobar degeneration (FTLD), which includes behavioral variant frontotemporal dementia (bvFTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). This study was to investigate to what extent the pattern of white matter microstructural alterations in FTLD subtypes mirrors the pattern of brain atrophy, and to compare the ability of various diffusion tensor imaging (DTI) indices in characterizing FTLD patients, as well as to determine whether DTI measures provide greater classification power for FTLD than measuring brain atrophy. Twenty-five patients with FTLD (13 with bvFTD, 6 with SD, and 6 with PNFA) and 19 healthy age-matched control subjects underwent both structural MRI and DTI scans. Measurements of regional brain atrophy were based on T1-weighted MRI data and voxel-based morphometry. Measurements of regional white matter degradation were based on voxelwise as well as regions-of-interest tests of DTI variations, expressed as fractional anisotropy, axial diffusivity, and radial diffusivity. Compared to controls, bvFTD, SD, and PNFA patients each exhibited characteristic regional patterns of brain atrophy and white matter damage. DTI overall provided significantly greater accuracy for FTLD classification than brain atrophy. Moreover, radial diffusivity was more sensitive in assessing white matter damage in FTLD than other DTI indices. The findings suggest that DTI in general and radial diffusivity in particular are more powerful measures for the classification of FTLD patients from controls than brain atrophy.

Fig. 1

Comparison between bvFTD and CN, row 1–2: regions of significant gray and white matter atrophy (in blue-green color) superimposed on the T1-weighted image; row 3: regions of significant FA reduction (in red-yellow color) superimposed on the FA template; row 4: regions of significantly increased DR (in red color) and increased DA (in blue color) superimposed on the FA template. Statistical map-derived ROI was determined by the largest-sized cluster that showed significant (p = 0.001) on each paired-group comparison. ROI_1 indicates the anatomical locations of these statistical map-derived ROIs superimposed on a rendered brain.

Fig. 2

Comparison between SD and CN, row 1–2: regions of significant gray and white matter atrophy (in blue-green color) superimposed on the T1-weighted image; row 3: the regions of significant FA reduction (in red-yellow color) superimposed on the FA template; row 4: regions of significantly increased DR (in red color) and increased DA (in blue color) superimposed on the FA template. Statistical map-derived ROI was determined by the largest-sized cluster that showed significant (p = 0.001) on each paired group comparison. ROI_2 indicates the anatomical locations of these statistical map-derived ROIs superimposed on a rendered brain.

Fig. 3

Comparison between PNFA and CN, row 1–2: gray and white matter atrophy (in blue-green color) superimposed on the T1-weighted image; row 3: the regions of significant FA reduction (in red-yellow color) superimposed on the FA template; row 4: regions of significantly increased DR (in red color) and increased DA (in blue color) superimposed on the FA template. Statistical map-derived ROI was determined by the largest-sized cluster that showed significant (p = 0.001) on each paired-group comparison. ROI_3 indicates the anatomical locations of these statistical map-derived ROIs superimposed on a rendered brain.

Fig. 4

Mean and standard deviation of GMV, WMV, FA, DR, and DA measures that standardized as Z-scores from three ROI sets derived from the largest cluster shown on the statistical maps. Z-scores of increased DR and DA are reversed to negative scores to be comparable to the other measurements. In the FTLD group, the subtypes are pooled.