Fábio Ferreira

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

Background: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Objective: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). Method: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately – using standard univariate VBM - and simultaneously, with multivariate analyses. Results: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. Conclusion: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Structure-function correlations in Retinitis Pigmentosa patients with partially preserved vision: a voxel-based morphometry study

Retinitis Pigmentosa is a group of hereditary retinal dystrophy disorders associated with progressive peripheral visual field loss. The impact of this retinal loss in cortical gray matter volume has not been addressed before in Retinitis Pigmentosa patients with low vision. Voxel-based morphometry was applied to study whole brain gray matter volume changes in 27 Retinitis Pigmentosa patients with partially preserved vision and 38 age- and gender-matched normally sighted controls to determine whether peripheral visual loss can lead to changes in gray matter volume. We found significant reductions in gray matter volume that were restricted to the occipital cortex of patients. The anteromedial pattern of reduced gray matter volume in visual primary and association cortices was significantly correlated with the extent of the peripheral visual field deficit in this cohort. Moreover, this pattern was found to be associated with the extent of visual field loss. In summary, we found specific visual cortical gray matter loss in Retinitis Pigmentosa patients associated with their visual function profile. The spatial pattern of gray matter loss is consistent with disuse-driven neuronal atrophy which may have clinical implications for disease management, including prosthetic restoration strategies.