#Osirix md sorting software

Several papers and books describing the main technical issues and pitfalls related to DTI studies have been published ( Basser and Jones, 2002 Moritani et al., 2005 Le Bihan et al., 2006 Mukherjee et al., 2008b Bammer et al., 2009 Jones, 2010a, b, c Jones and Cercignani, 2010 Chung et al., 2011 Hasan et al., 2011) which are complemented by available neuroanatomical WM atlas ( Jellison et al., 2004 Wakana et al., 2004 Catani and Thiebaut De Schotten, 2008 Lawes et al., 2008 Oishi et al., 2008, 2010 Zhang et al., 2010 Bazin et al., 2011 Nowinski et al., 2012).

#Osirix md sorting software

These factors are compounded by a multitude of preprocessing and analysis methods in several software packages. However, it has a complex workflow (summarized in Figure 1) that implicates knowledge of imaging artifacts, complex MRI protocol definition, neuroanatomical complexity, and intrinsic technique limitations. Gaining increased popularity among clinicians and researchers, DTI is presently a promising tool for studying WM architecture in living humans, both in healthy conditions and in disease. Based on this assumption, Basser and colleagues (1994a, b) modeled the diffusion process by an ellipsoid, which can mathematically be represented by a 3 × 3 symmetric matrix, also known as tensor (hence DTI's name origin). Diffusion in White Matter (WM) is less restricted along the axon and tends to be anisotropic (directionally-dependent) whereas in Gray Matter (GM) is usually less anisotropic and in the Cerebrospinal fluid (CSF) is unrestricted in all directions (isotropic) ( Pierpaoli et al., 1996 Song et al., 2002 Hagmann et al., 2006). With DTI analysis it is possible to infer, in each voxel, properties such as the molecular diffusion rate, the directional preference of diffusion, the axial (diffusion rate along the main axis of diffusion), and radial (rate of diffusion in the transverse direction) diffusivity.

Summarily, the basic concept behind DTI is that water molecules diffuse differently along the tissues depending on its type, integrity, architecture, and presence of barriers, giving information about its orientation and quantitative anisotropy ( Chenevert et al., 1990 Moseley et al., 1990 Douek et al., 1991 Beaulieu, 2002). DTI principles and basic concepts have been extensively described and reviewed in the literature ( Mori and Barker, 1999 Le Bihan et al., 2001 Hagmann et al., 2006 Mori and Zhang, 2006 Mori, 2007 Nucifora et al., 2007 Assaf and Pasternak, 2008 Jones, 2008, 2010b Mukherjee et al., 2008a Johansen-Berg and Behrens, 2009 Figueiredo et al., 2011 Thomason and Thompson, 2011 Tournier et al., 2011 Yang et al., 2011). While DWI refers to the contrast of the acquired images, DTI is a specific type of modeling of the DWI datasets. The introduction of the diffusion tensor model enabled the indirect measurement of the degree of anisotropy and structural orientation that characterizes diffusion tensor imaging (DTI) ( Basser et al., 1994a, b Pierpaoli et al., 1996). It is a non-invasive method, with unparalleled sensitivity to water movements within the architecture of the tissues that uses existing MRI technology and requires no new equipment, contrast agents, or chemical tracers. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.ĭiffusion-Weighted Imaging (DWI) ( Le Bihan and Breton, 1985 Merboldt et al., 1985 Taylor and Bushell, 1985 Le Bihan et al., 1986) is a variant of conventional Magnetic Resonance Imaging based on the tissue water diffusion rate. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology.

However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. 3Department of Informatics, University of Minho, Braga, Portugalĭiffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity.2ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal.1Life and Health Science Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal.Soares 1,2*, Paulo Marques 1,2,3, Victor Alves 3 and Nuno Sousa 1,2