2017
DOI: 10.1016/j.neuroimage.2017.09.027
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In vivo magnetic resonance images reveal neuroanatomical sex differences through the application of voxel-based morphometry in C57BL/6 mice

Abstract: Behaviorally relevant sex differences are often associated with structural differences in the brain and many diseases are sexually dimorphic in prevalence and progression. Characterizing sex differences is imperative to gaining a complete understanding of behavior and disease which will, in turn, allow for a balanced approach to scientific research and the development of therapies. In this study, we generated novel tissue probability maps (TPMs) based on 30 male and 30 female in vivo C57BL/6 mouse brain magnet… Show more

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Cited by 33 publications
(34 citation statements)
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References 99 publications
(140 reference statements)
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“…Exposure of pregnant Wistar rat dams to poly (I:C) (POL) at GD15 has no effect on the total brain volume (in mm 3 ) of juvenile offspring at PD21 relative to controls (CON). Irrespective of gestation treatment brain volume did vary as a function of sex, which is consistent with published data [43, 44]. When comparing the relative volumes of 23 brain regions between CON and POL offspring at PD21, we found only subtle neuroanatomical differences in the juvenile Wister rat brain.…”
Section: Discussionsupporting
confidence: 90%
See 1 more Smart Citation
“…Exposure of pregnant Wistar rat dams to poly (I:C) (POL) at GD15 has no effect on the total brain volume (in mm 3 ) of juvenile offspring at PD21 relative to controls (CON). Irrespective of gestation treatment brain volume did vary as a function of sex, which is consistent with published data [43, 44]. When comparing the relative volumes of 23 brain regions between CON and POL offspring at PD21, we found only subtle neuroanatomical differences in the juvenile Wister rat brain.…”
Section: Discussionsupporting
confidence: 90%
“…Main effects of sex were also found for the relative volumes of 3/23 (13%) atlas ROIs, including the bed nucleus of the stria terminalis (BNST), the cerebellum and the ventricular system, although these did not survive correction for multiple comparisons ( Table 1 ). Nonetheless, these trend-level results are consistent with known sexually dimorphic regions in the rodent brain [43, 44]. A significant main effect of MIA was found for the relative volume of the diagonal domain (DD), with subtly increased volume in POL as compared to CON offspring (+4.4%; p <0.05, q <0.1; partial Ρ 2 = 0.44; Table 1 ; Figure 2 ).…”
Section: Resultssupporting
confidence: 85%
“…Total brain/tissue volume analysis is used to detect gross volumetric differences between strains and proven to be a sensitive diagnostic imaging marker of aging and hypertension related structural change in humans (Good CD et al, 2001;Salerno JA, et al, 1992;Verdelho A et al, 2010;Wiseman RM et al, 2004). We used computerized whole brain segmentation to create custom WKY-SHR tissue probability maps which greatly improved the accuracy of the tissue segmentation quality as other studies have also suggested (Dodero L et al, 2013;Meyer CE, et al, 2017;Tucci V et al, 2014). The custom WKY-SHR tissue probability maps were crucial to reveal that GM, WM, and CSF volumes were all significantly lower in SHR compared to WKY rats irrespective of age, extending the finding of a previous study reporting smaller TIVs in SHR rats compared to WKY rats in much older rats (35 weeks old) (Kaiser D et al, 2014).…”
Section: Discussionmentioning
confidence: 99%
“…MR sequences for optimal morphometric characterization of the small rodent brain should be acquired in 3D at high spatial resolution (with adequate signal-to-noise ratios) and with decent tissue contrast-to-noise ratios to accurately discriminate GM, WM and CSF (Gaser C et al, 2012;Meyer CE et al, 2017;Sumiyoshi A et al, 2014). We recently developed a 3D variable flip angle spoiled gradient echo (VFA-SPGR) imaging technique for rodents that provide a whole brain 3D proton density weighted (PDW) image as well as a longitudinal relaxation time (T1) parametric map (Lee H et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Removal of confounding effects by linear regression was performed using 1) linear/quadratic trends within each functional run, 2) realignment-based subject motion, 3) noise signals in white matter and CSF, obtained with component-based noise correction method (CompCor), and 4) 0.01-0.1 Hz band-pass filtering. FAAsegment was substituted for a tissue probability map (TPM) based on image intensity of structural MRI (Hikishima et al, 2017;Meyer et al, 2017;Nie et al, 2019;Sawiak et al, 2009). FAAsegment was used for segmenting grey matter, white matter, and cerebrospinal fluid (CSF) in CONN analysis (CompCor) because mis-assignments of nodes in grey matter to that in white matter in a TPM were noticed, e.g.…”
Section: Temporal Preprocessing Of Fmri Datamentioning
confidence: 99%