Biophysical modeling of high field diffusion MRI demonstrates micro-structural aberration in chronic mild stress rat brain

Depression is one of the leading causes of disability worldwide. Immense heterogeneity in symptoms of depression causes difficulty in diagnosis, and to date, there are no established biomarkers or imaging methods to examine depression. Unpredictable chronic mild stress (CMS) induced anhedonia is considered to be a realistic model of depression in studies of animal subjects. Stereological and neuronal tracing techniques have demonstrated persistent remodeling of microstructure in hippocampus, prefrontal cortex and amygdala of CMS brains. Recent developments in diffusion MRI (d-MRI) analyses, such as neurite density and diffusion kurtosis imaging (DKI), are able to capture microstructural changes and are considered to be robust tools in preclinical and clinical imaging. The present study utilized d-MRI analyzed with a neurite density model and the DKI framework to investigate microstructure in the hippocampus, prefrontal cortex, caudate putamen and amygdala regions of CMS rat brains by comparison to brains from normal controls. To validate findings of CMS induced microstructural alteration, histology was performed to determine neurite, nuclear and astrocyte density. d-MRI based neurite density and tensor-based mean kurtosis (MKT) were significantly higher, while mean diffusivity (MD), extracellular diffusivity (Deff) and intra-neurite diffusivity(DL) were significantly lower in the amygdala of CMS rat brains. Deff was also significantly lower in the hippocampus and caudate putamen in stressed groups. Histological neurite density corroborated the d-MRI findings in the amygdala and reductions in nuclear and astrocyte density further buttressed the d-MRI results. The present study demonstrated that the d-MRI based neurite density and MKT can reveal specific microstructural changes in CMS rat brains and these parameters might have value in clinical diagnosis of depression and for evaluation of treatment efficacy.

[1]  G. Northoff,et al.  Discovering imaging endophenotypes for major depression , 2011, Molecular Psychiatry.

[2]  J. Sijbers,et al.  Constrained maximum likelihood estimation of the diffusion kurtosis tensor using a Rician noise model , 2011, Magnetic resonance in medicine.

[3]  M. Roth.  A quantitative assessment , 1987 .

[4]  C. Pariante,et al.  Molecular mechanisms in the regulation of adult neurogenesis during stress , 2015, Nature Reviews Neuroscience.

[5]  Jelle Veraart,et al.  Gibbs ringing in diffusion MRI , 2016, Magnetic resonance in medicine.

[6]  J. Helpern,et al.  MRI quantification of non‐Gaussian water diffusion by kurtosis analysis , 2010, NMR in biomedicine.

[7]  P. Willner.  Chronic Mild Stress (CMS) Revisited: Consistency and Behavioural-Neurobiological Concordance in the Effects of CMS , 2005, Neuropsychobiology.

[8]  P. Basser.  Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[9]  Jens H Jensen,et al.  Quantitative assessment of diffusional kurtosis anisotropy , 2015, NMR in biomedicine.

[10]  Masaaki Hori,et al.  Visualizing non-Gaussian diffusion: clinical application of q-space imaging and diffusional kurtosis imaging of the brain and spine. , 2012, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[11]  Els Fieremans,et al.  Revealing mesoscopic structural universality with diffusion , 2014, Proceedings of the National Academy of Sciences.

[12]  Eric J. Nestler,et al.  The molecular neurobiology of depression , 2008, Nature.

[13]  Jan Sijbers,et al.  Magnetic Resonance Imaging and Spectroscopy Reveal Differential Hippocampal Changes in Anhedonic and Resilient Subtypes of the Chronic Mild Stress Rat Model , 2011, Biological Psychiatry.

[14]  Daniel C. Alexander,et al.  NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.

[15]  Rafael Delgado y Palacios,et al.  Diffusion Kurtosis Imaging and High-Resolution MRI Demonstrate Structural Aberrations of Caudate Putamen and Amygdala after Chronic Mild Stress , 2014, PloS one.

[16]  P. Willner.  Validity, reliability and utility of the chronic mild stress model of depression: a 10-year review and evaluation , 1997, Psychopharmacology.

[17]  A. Arnsten.  Stress signalling pathways that impair prefrontal cortex structure and function , 2009, Nature Reviews Neuroscience.

[18]  Matthew D. Budde,et al.  Examining brain microstructure using structure tensor analysis of histological sections , 2012, NeuroImage.

[19]  M. Shenton,et al.  Use of Anisotropy, 3D Segmented Atlas, and Computational Analysis to Identify Gray Matter Subcortical Lesions Common to Concussive Injury from Different Sites on the Cortex , 2015, PloS one.

[20]  Ahmad Raza Khan,et al.  3D structure tensor analysis of light microscopy data for validating diffusion MRI , 2015, NeuroImage.

[21]  G. Freedman,et al.  Burden of Depressive Disorders by Country, Sex, Age, and Year: Findings from the Global Burden of Disease Study 2010 , 2013, PLoS medicine.

[22]  J. Price,et al.  Low glial numbers in the amygdala in major depressive disorder , 2002, Biological Psychiatry.

[23]  E. Duchesnay,et al.  Hyper-responsivity to stress in rats is associated with a large increase in amygdala volume. A 7T MRI study , 2015, European Neuropsychopharmacology.

[24]  Alan D. Lopez,et al.  The Global Burden of Disease Study , 2003 .

[25]  S. Jespersen,et al.  Kurtosis fractional anisotropy, its contrast and estimation by proxy , 2016, Scientific Reports.

[26]  Brian Hansen,et al.  Experimentally and computationally fast method for estimation of a mean kurtosis , 2013, Magnetic resonance in medicine.

[27]  Satterthwaite Fe.  An approximate distribution of estimates of variance components. , 1946 .

[28]  A. Simmons,et al.  Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder. , 2011, Archives of general psychiatry.

[29]  S. Russo,et al.  Structural and synaptic plasticity in stress-related disorders , 2011, Reviews in the neurosciences.

[30]  J. Scholz,et al.  Neuroanatomic Differences Associated With Stress Susceptibility and Resilience , 2016, Biological Psychiatry.

[31]  G. Moore,et al.  Neuroplasticity and cellular resilience in mood disorders , 2000, Molecular Psychiatry.

[32]  R. Kalisch,et al.  Anxiety and Hippocampus Volume in the Rat , 2006, Neuropsychopharmacology.

[33]  G. Paxinos,et al.  The Rat Brain in Stereotaxic Coordinates , 1983 .

[34]  O. Ciccarelli,et al.  Nonconventional MRI and microstructural cerebral changes in multiple sclerosis , 2015, Nature Reviews Neurology.

[35]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[36]  S. Chattarji,et al.  Effects of chronic stress on dendritic arborization in the central and extended amygdala , 2003, Brain Research.

[37]  J. Veraart,et al.  Degeneracy in model parameter estimation for multi‐compartmental diffusion in neuronal tissue , 2016, NMR in biomedicine.

[38]  G. Rajkowska,et al.  Postmortem studies in mood disorders indicate altered numbers of neurons and glial cells , 2000, Biological Psychiatry.

[39]  Leif Østergaard,et al.  Modeling dendrite density from magnetic resonance diffusion measurements , 2007, NeuroImage.

[40]  G. Cumming.  The New Statistics: Why and How , 2013 .

[41]  J. Helpern,et al.  Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[42]  Bibek Dhital,et al.  Gibbs‐ringing artifact removal based on local subvoxel‐shifts , 2015, Magnetic resonance in medicine.

[43]  James C. Overholser,et al.  Cellular changes in the postmortem hippocampus in major depression , 2004, Biological Psychiatry.

[44]  Shantanu P. Jadhav,et al.  Prolonged behavioral stress enhances synaptic connectivity in the basolateral amygdala , 2006, Neuroscience.

[45]  J. Morrison,et al.  Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex , 2004, Neuroscience.

[46]  J. Morrison,et al.  Repeated stress induces dendritic spine loss in the rat medial prefrontal cortex. , 2006, Cerebral cortex.

[47]  B. Roth,et al.  Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression∗ ∗ See accompanying Editorial, in this issue. , 1999, Biological Psychiatry.

[48]  S. Chattarji,et al.  Chronic Stress Induces Contrasting Patterns of Dendritic Remodeling in Hippocampal and Amygdaloid Neurons , 2002, The Journal of Neuroscience.

[49]  Bruce S. McEwen,et al.  Stress, memory and the amygdala , 2009, Nature Reviews Neuroscience.

[50]  M. West,et al.  A reduced number of hippocampal granule cells does not associate with an anhedonia-like phenotype in a rat chronic mild stress model of depression , 2010, Stress.

[51]  P J Basser,et al.  New Histological and Physiological Stains Derived from Diffusion‐Tensor MR Images , 1997, Annals of the New York Academy of Sciences.

[52]  Guillén Fernández,et al.  Stress-induced alterations in large-scale functional networks of the rodent brain , 2015, NeuroImage.

[53]  Shantanu P. Jadhav,et al.  Stress duration modulates the spatiotemporal patterns of spine formation in the basolateral amygdala. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[54]  M. Cuesta,et al.  [Neurobiology of depression]. , 2002, Anales del sistema sanitario de Navarra.

[55]  Joseph A. Helpern,et al.  White matter characterization with diffusional kurtosis imaging , 2011, NeuroImage.

[56]  H. Uylings,et al.  Specific configuration of dendritic degeneration in pyramidal neurons of the medial prefrontal cortex induced by differing corticosteroid regimens. , 2007, Cerebral cortex.

[57]  Lara M. Boyle.  A Neuroplasticity Hypothesis of Chronic Stress in the Basolateral Amygdala , 2013, The Yale journal of biology and medicine.

[58]  F. E. Satterthwaite.  An approximate distribution of estimates of variance components. , 1946, Biometrics.

[59]  Brian Hansen,et al.  Experimental considerations for fast kurtosis imaging , 2016, Magnetic resonance in medicine.

[60]  J. Zohar,et al.  Distinctive hippocampal and amygdalar cytoarchitectural changes underlie specific patterns of behavioral disruption following stress exposure in an animal model of PTSD , 2014, European Neuropsychopharmacology.

[61]  F. Holsboer,et al.  Stress and the brain: from adaptation to disease , 2005, Nature Reviews Neuroscience.

[62]  Janet B W Williams.  Diagnostic and Statistical Manual of Mental Disorders , 2013 .

[63]  B. Ardekani,et al.  Estimation of tensors and tensor‐derived measures in diffusional kurtosis imaging , 2011, Magnetic resonance in medicine.

[64]  M. Mallar Chakravarty,et al.  Neurite density from magnetic resonance diffusion measurements at ultrahigh field: Comparison with light microscopy and electron microscopy , 2010, NeuroImage.

[65]  O. Wiborg.  Chronic mild stress for modeling anhedonia , 2013, Cell and Tissue Research.

[66]  Brian Hansen,et al.  Diffusion-Weighted MRI and Quantitative Biophysical Modeling of Hippocampal Neurite Loss in Chronic Stress , 2011, PloS one.

[67]  Sune Nørhøj Jespersen,et al.  Erratum: Hansen, Lund, Sangill, and Jespersen. Experimentally and Computationally Fast Method for Estimation of a Mean Kurtosis. Magnetic Resonance in Medicine 69:1754–1760 (2013) , 2014 .

[68]  Aleksandra Pizurica,et al.  The effect of Gibbs ringing artifacts on measures derived from diffusion MRI , 2015, NeuroImage.

[69]  Ove Wiborg,et al.  Hippocampal Cytogenesis Correlates to Escitalopram-Mediated Recovery in a Chronic Mild Stress Rat Model of Depression , 2006, Neuropsychopharmacology.