Combined assessment of progressive apraxia of speech brain microstructure by diffusion tensor imaging tractography and multishell neurite orientation dispersion and density imaging

Abstract

Background: Progressive apraxia of speech (PAOS) is characterized by difficulties with motor speech programming and planning. PAOS targets gray matter (GM) and white matter (WM) microstructure that can be assessed using diffusion tensor imaging (DTI) and multishell applications, such as neurite orientation dispersion and density imaging (NODDI). In this study, we aimed to apply DTI and NODDI to add further insight into PAOS tissue microstructure.

Methods: Twenty-two PAOS patients and 26 age- and sex-matched controls, recruited by the Neurodegenerative Research Group (NRG) at Mayo Clinic, underwent diffusion MRI on 3T MRI. Brain maps of fractional anisotropy (FA) and mean diffusivity (MD) from DTI and intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) from NODDI were generated. Global WM and GM, and specific WM tracts were identified using tractography and lobar GM regions.

Results: Global WM differences between PAOS and controls were greatest for ICVF, and global GM differences were greatest for MD and IsoVF. Abnormalities in key WM tracts involved in PAOS, including the body of the corpus callosum and frontal aslant tract, were identified with FA, MD, and ICVF, with excellent differentiation of PAOS from controls (area under the receiver operating characteristic curves >.90). MD and ICVF identified abnormalities in arcuate fasciculus, thalamic radiations, and corticostriatal tracts. Significant correlations were identified between an index of articulatory errors and DTI and NODDI metrics from the arcuate fasciculus, frontal aslant tract, and inferior longitudinal fasciculus.

Conclusions: DTI and NODDI represent different aspects of brain tissue microstructure, increasing the number of potential biomarkers for PAOS.

Keywords: 4R tauopathies; diffusion tensor imaging; neurite orientation dispersion density imaging; progressive apraxia of speech; tractography.

FIGURE 1

Segmented global white matter (WM) and gray matter (GM) regions from progressive apraxia of speech (PAOS) patient. (A) Segmented whole‐brain WM regions from intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) brain maps. (B) GM segmentations on ICVF and iso‐VF maps.

FIGURE 2

Coregistration of neurite orientation dispersion and density imaging (NODDI) brain maps and diffusion tensor imaging (DTI)‐based tractography. (A) Fractography projection on intracellular volume fraction (ICVF) maps on a patient with progressive apraxia of speech (PAOS). Three different segments from the corpus callosum (CC) were reconstructed (cc‐minor, cc‐body, and cc‐mayor). Additional transcortical tracts such as the arcuate fasciculus (AF) and frontal aslant tracts (FAT) as well as inferior longitudinal fasciculus (ILF) were considered. (B) Isotropic volume fraction (IsoVF) maps are displayed with previously described tracts as well as anterior thalamic radiations (Thal_ant.) and corticostriatal anterior (Cst_sup).

FIGURE 3

Automated anatomical labeling atlas 2 (AAL2)‐based gray matter (GM) segmentation on individual space from a progressive apraxia of speech (PAOS) patient. Each GM region of interest (ROI) is projected on an intracellular volume fraction (ICVF) (A) and isotropic volume fraction (IsoVF) maps (B). GM subregions were combined into three main GM regions: (1) a frontal region, from a combination of seven subregions—frontal inferior operculum, frontal inferior pars triangularis, frontal middle gyrus, frontal superior gyrus, frontal superior medial gyrus, precentral gyrus, and supplementary motor area (SMA) (blue); (2) a temporal region, combining three subregions—temporal inferior, temporal middle, and temporal superior gyrus (green); and (3) a parietal region, which combines four subregions—parietal inferior, parietal superior, supramarginal, and postcentral gyrus (pink). The right and left areas were analyzed separately. Note that although the SMA has been included in the frontal regions (red), it was also analyzed separately.

FIGURE 4

Global white matter (WM) and gray matter (GM) analysis obtained from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters. (A) DTI analysis using fractional anisotropy (FA) and mean diffusivity (MD) outputs demonstrated a significant decrease in FA and an increase in MD in WM and GM regions from progressive apraxia of speech (PAOS) patients. Larger differences were observed in MD in the PAOS group (GM > WM). (B) NODDI calculation has shown a significant decrease in intracellular volume fraction (ICVF) in the PAOS group but not significant in whole‐brain GM (gm_global). Isotropic volume fraction (IsoVF) was significantly increased in whole‐brain WM (wm_global) (p < .05) and gm_global (p < .001) in PAOS patients. *p < .05; **p < .01; ***p < .001.

FIGURE 5

Diffusion tensor imaging (DTI) outputs extracted from tractography reconstructions and neurite orientation dispersion and density imaging (NODDI) region of interest (ROI) projections. Three main groups of tracts were interrogated: (1) commissural tracts, such as the minor, body, and major portion of the corpus callosum (CC); (2) right and left corticocortical tracts, such as the arcuate fasciculus (ArcF), the frontal aslant tract (FAT), and the inferior longitudinal fasciculus (ILF); and (3) right and left corticosubcortical tracts, including the thalamic anterior radiation (Thal_Ant) as well as the corticostriatal superior tract (Cstr_Sup). (A) Fractional anisotropy (FA) and mean diffusivity (MD) from white matter (WM) tracts are analyzed. There was a significantly larger difference between controls and progressive apraxia of speech (PAOS) groups in MD measurements across commissural, corticocortical, and corticosubcortical tracts. (B) NODDI WM tract ROI projections demonstrate a significantly larger difference between groups in intracellular volume fraction (ICVF) compared to isotropic volume fraction (IsoVF) in all three groups of WM tracts.

FIGURE 6

Evaluation of gray matter (GM) regions of interest (ROIs) by diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) algorithms. (A) Mean diffusivity (MD) analysis shows larger differences between groups across frontal, supplementary motor area (SMA), temporal, and parietal regions. (B) In the NODDI analysis, a large increase in isotropic volume fraction (IsoVF) was seen in the progressive apraxia of speech (PAOS) groups compared to the intracellular volume fraction (ICVF) analysis.

FIGURE 7

Correlative analysis of white matter (WM) tracts involved in language and clinical parameters. (A) Correlative analysis between diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters shows significant correlations between articulatory error score total percentage of error (AES_tt_pct_err), with the left arcuate fasciculus (ArcF_L). Additional correlation can be obtained between NODDI parameters (intracellular volume fraction [ICVF] and isotropic volume fraction [IsoVF]) from the left frontal aslant tract (FAT_L) and AES_tt_pct_err scores. No large differences in rho were observed independently of diffusion magnetic resonance imaging (dMRI) techniques used (DTI vs. NODDI). (B) Additional significant correlations between Western Aphasia Battery (WAB) animal fluency (WAB_animal_fluency) were seen between fractional anisotropy (FA) (right) and mean diffusivity (MD) (left) from the ArcF_L and WAB_animal_fluency.