A tensor based morphometry study of longitudinal gray matter contraction in FTD

Abstract

Frontotemporal dementia (FTD) is a neurodegenerative disease characterized by progressive behavioural abnormalities and frontotemporal atrophy. Here we used tensor based morphometry (TBM) to identify regions of longitudinal progression of gray matter atrophy in FTD compared to controls. T1-weighted MRI images were acquired at presentation and 1-year follow-up from 12 patients with mild to moderate FTD and 12 healthy controls. Using TBM as implemented in SPM2, a voxel-wise estimation of regional tissue volume change was derived from the deformation field required to warp a subject's late to early anatomical images. A whole brain analysis was performed, in which a level of significance of p<0.05 corrected for multiple comparisons (family wise error-FWE) was accepted. Based on prior studies, a region of interest (ROI) analysis was also performed, including in the search area bilateral medial and orbital frontal regions, anterior cingulate gyrus, insula, amygdala and hippocampus. Within this ROI a level of significance of p<0.001 uncorrected was accepted. In the whole brain analysis, the anterior cingulate/paracingulate gyri were the only regions that showed significant atrophy change over 1 year. In the ROI analysis, the left ventromedial frontal cortex, right medial superior frontal gyrus, anterior insulae and left amygdala/ hippocampus showed significant longitudinal changes. In conclusion, limbic and paralimbic regions showed detectable gray matter contraction over 1 year in FTD, confirming the susceptibility of these regions to the disease and the consistency with their putative role in causing typical presenting behaviours. These results suggest that TBM might be useful in tracking progression of regional atrophy in FTD.

Atrophy progression in semantic dementia with asymmetric temporal involvement: A tensor-based morphometry study

“…TBM is a recently introduced technique that was successful at identifying patterns of atrophy progression typical of various neurodegenerative disorders (Brambati et al, 2007;Chan et al, 2001a,b;Fox et al, 2000Fox et al, , 2001Fox et al, , 1999Fox and Freeborough, 1997;Freeborough et al, 1996;Kipps et al, 2005;Leow et al, 2006;Studholme et al, 2001), including classic SD (Cardenas and Studholme, 2004;Whitwell et al, 2004). Here, we showed that the automated, whole-brain TBM technique as implemented in SPM, could detect differential patterns of longitudinal gray matter atrophy in two variants of the same disease.…”

“…Both spatial pre-processing and statistical analysis were implemented in SPM2. Details regarding TBM image pre-processing are described in previous studies (Brambati et al, 2007;Kipps et al, 2005) (Fig. 1).…”

Reduced Precuneus Deactivation during Object Naming in Patients with Mild Cognitive Impairment, Alzheimer’s Disease, and Frontotemporal Lobar Degeneration

“…Depending on the variant of the disease, atrophy associated with FTLD has been described as involving diverse regions of the brain [30,31] . In a recent study using cortical thickness analyses, GM atrophy of the posterior midline cortex was found in FTLD patients [10] , but it was not described in other studies that have applied VBM [32][33][34][35] . Consistent with the latter studies, in the current study significant PREC/PCC atrophy was observed in AD, MCI, and bvFTLD, but not PPA patients.…”

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

“…It has been recently shown that, compared to the traditional volumetric method, TBM yields more statistical power to associate structure with other biological and demographic variables (Lee et al, 2007). It was also demonstrated that the method is well suited to track longitudinal changes of individual brains (e.g., Brambati et al, 2007;Cardenas, Studholme, Gazdzinski, Durazzo, & Meyerhoff, 2007;Leow et al, 2006). Second, to further enhance the accuracy and sensitivity of TBM protocol, a novel algorithm, symmetric normalization (SyN ; Avants, Epstein, Grossman, & Gee, in press;Avants, Schoenemann, & Gee, 2006) was employed for the inter-subject image normalization.…”