001 058 002 059 003 060 004 061 005 062 006 063 007 064 008 065 009 066 010 067 011 068 012 069 013 070 014 071 015 072 016 073 017 074 018 075 019 076 020 077 021 078 022 079 023 080 024 081 025 082 026 083 027 084 028 085 029 086 030 087 031 088 032 089 033 090 034 091 035 092 036 093 037 094 038 095 039 096 040 097 041 098 042 099 043 100 044 101 045 102 046 103 047 104 048 105 049 106 050 107 051 108 052 109 053 110 054 111 055 112 056 113 057 114 NEUROINFORMATICS METHODS ARTICLE published: xx November

Abstract

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

Anesthesia with Dexmedetomidine and Low-dose Isoflurane Increases Solute Transport via the Glymphatic Pathway in Rat Brain When Compared with High-dose Isoflurane

“…Individual T1 maps were segmented into GM, WM and CSF probability maps using an unified segmentation algorithm in SPM12 (http://www.fil.ion.ucl.ac.uk/spm/) 27 using the in vivo rat tissue probability maps 28 as spatially resolved tissue priors. Segmented GM and WM tissue probability maps in native space were then thresholded and summed for calculating total volumes in each compartment.…”

Waxholm Space atlas of the Sprague Dawley rat brain

“…This approach has produced a series of volumetric atlasing templates for the mouse (Aggarwal et al, 2009; Chuang et al, 2011; Johnson et al, 2010; Kovacevic et al, 2005; Ma et al, 2005; Ma et al, 2008) and rat brain (Johnson et al, 2012; Lu et al, 2010; Nie et al, 2013; Rumple et al, 2013; Schwarz et al, 2006; Schweinhardt et al, 2003; Valdes-Hernandez et al, 2011; Veraart et al, 2011). In MRI/DTI datasets, cranial landmarks are not readily recognizable or not present (skull removed), and thus coordinate systems based on in-brain landmarks have been proposed (Kovacevic et al, 2005).…”

Interleaved imaging of cerebral hemodynamics and blood flow index to monitor ischemic stroke and treatment in rat by volumetric diffuse optical tomography

“…Based on a 3D rat head atlas (Fig. 3A) generated by T2-weighted MRI (Valdes-Hernandez et al, 2011), we identified the boundaries of three main regions of interest (ROI), namely, the skin/muscle, skull, and brain, respectively, and further segmented them using multi-level Otsu’s thresholding technique (Liao et al, 2001). Each of the segmented 2D images was stacked in sequence together to form a 3D volume model as shown in Fig.…”

“…(A) T2-weighted MR image of a rat head (Valdes-Hernandez et al, 2011). Iso-surface figures of segmented rat head tissues showing (B) skin/muscle, (C) skull (coded as yellow), and (D) brain (coded as light blue).…”