RESUMEN
In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states. The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome.
Asunto(s)
Encéfalo/citología , Encéfalo/fisiología , Conectoma/métodos , Imagen de Difusión Tensora/métodos , Aumento de la Imagen/métodos , Red Nerviosa/citología , Red Nerviosa/fisiología , Humanos , Modelos Anatómicos , Modelos NeurológicosRESUMEN
The construction of an atlas of the human brain connectome, in particular, the cartography of fiber bundles of superficial white matter (SWM) is a complex and unachieved task. Its description is essential for the understanding of human brain function and the study of several pathologies. In this work we applied an automatic white matter bundle segmentation method proposed in the literature for the analysis of the variability of a big amount of superficial white matter bundles. The method was applied to 30 subjects of a high quality HARDI database, adding several processing steps in order to improve the results. Then we calculated some indices for studying the variability of 40 SWM fiber bundles from each hemisphere, and we constructed a model of these bundles in the MNI standard space.