Diffusion MRI combined with biophysical modeling allows for the description Fesoterodine

Diffusion MRI combined with biophysical modeling allows for the description Fesoterodine fumarate (Toviaz) of a white matter (WM) fiber bundle in terms of compartment specific white matter tract integrity (WMTI) metrics which include intra-axonal diffusivity (investigations of WM microstructural integrity (Basser 1995 Jones 2010 DTI quantifies the Gaussian part of the probability distribution of molecular displacement in terms of the overall diffusion tensor from which derived metrics such as the mean radial and axial diffusivities (MD measures only provide an indirect characterization of microstructure. of specific tissue properties still remains uncertain. Indeed it is imperative to distinguish between mathematical models representing the diffusion signal (e.g. the cumulant expansion (Kiselev 2010 mono- bi- and stretched exponential models (Assaf and Cohen 1998 Bennett et al. 2003 Niendorf et al. 1996 and mean apparent propagator (?zarslan et al. 2013 and true biophysical models taking into account actual neuronal structure as described below for WM. The former (e.g. DTI and DKI) are applicable in all brain voxels and do not make assumptions about the underlying microstructure whereas the latter are specifically tailored to model the effects of microstructure on diffusion in certain regions of the brain. Hence such biophysical Fesoterodine fumarate (Toviaz) models are especially useful to gain insight into the underlying pathological processes and to increase the pathophysiological specificity. In modeling WM diffusion the common practice has been to model axons as zero radius infinitely long impermeable tubes and cylinders (Assaf and Basser 2005 Assaf et al. 2004 Kroenke et al. 2004 or sticks (Behrens et al. 2003 Another common assumption is to neglect the water exchange through the myelin sheath surrounding axons. As a result the diffusion signal in the WM contains at least two components which correspond to the intra- and extra-axonal spaces. While these assumptions seem plausible and form the basis for most current diffusion models of WM in the brain (Alexander et al. 2010 Assaf and Basser 2005 Assaf et al. 2004 Basser et al. 2007 Jespersen et al. 2007 Nilsson et al. 2013 Panagiotaki et al. 2009 Panagiotaki et al. 2012 Wang et al. 2011 Zhang et al. 2012 further validation remains warranted. Based on the assumptions of a Rabbit Polyclonal to DLGP1. two non-exchanging compartments model we recently showed that for a single WM fiber bundle a minimum set of two shells in = 0 are sufficient to discern between intra- and extra-axonal water and allow for the description of compartment specific white matter tract integrity (WMTI) metrics from the diffusion and kurtosis tensor (Fieremans et al. 2011 Fieremans et al. 2010 Specifically as shown in Fig. 1 these include intra-axonal diffusivity (relationship between these WMTI parameters and concentrations of the metabolites the axons. The relationship between FA and NAA Cr and Cho has been evaluated in the WM of healthy adults in a previous study which showed that NAA concentrations explained most of the variance in FA (Wijtenburg et al. 2012 Here we evaluate the relationship between DTI DKI model-specific WMTI parameters and 1H-MRS metabolites (NAA Cr Cho and mI absolute concentrations) in a cohort of Fesoterodine fumarate (Toviaz) patients with mild traumatic brain injury (MTBI). This cohort has already been compared to age-matched controls using DTI (Grossman et al. 2013 DKI (Grossman et al. 2013 and 1H-MRS (Kirov et al. Fesoterodine fumarate (Toviaz) 2013 Kirov et al. 2013 By combining the results from both diffusion and spectroscopy measurements in MTBI we aim (i) to investigate the specificity of diffusion parameters for 1H-MRS-detectable metabolites; and (ii) to elucidate specific biophysical mechanisms that influence structural and metabolic changes following MTBI. 2 METHODS 2.1 Subjects Approval for the study was obtained from the Institutional Review Board of the New York University School of Medicine and all participants provided informed written consent. Twenty-five adult patients with MTBI (20 male 5 female; mean age = 33.6 years ± 11.2) prospectively recruited in our previous studies (Grossman et al. 2013 Kirov et al. 2013 were examined retrospectively. Patients had been included if they were within 1 month following injury (mean interval = 21.2 days ± 14.3) and classified with MTBI using diagnostic criteria developed by the Mild Traumatic Brain Injury Interdisciplinary Special Interest Group of the American Fesoterodine fumarate (Toviaz) Congress of Rehabilitation Medicine (Esselman and Uomoto 1995 Enrollment was permitted only in cases in which there existed no other history of brain damage or disorders of the central nervous system no history of systemic illness and no history of alcoholism or drug dependency. Patient demographics and clinical data are summarized in Table 1. Nineteen.