Quantitative susceptibility mapping of the rat brain after traumatic brain injury

The primary lesion arising from the initial insult after traumatic brain injury (TBI) triggers a cascade of secondary tissue damage, which may also progress to connected brain areas in the chronic phase. The aim of this study was, therefore, to investigate variations in the susceptibility distribution related to these secondary tissue changes in a rat model after severe lateral fluid percussion injury. We compared quantitative susceptibility mapping (QSM) and R2* measurements with histological analyses in white and grey matter areas outside the primary lesion but connected to the lesion site. We demonstrate that susceptibility variations in white and grey matter areas could be attributed to reduction in myelin, accumulation of iron and calcium, and gliosis. QSM showed quantitative changes attributed to secondary damage in areas located rostral to the lesion site that appeared normal in R2* maps. However, combination of QSM and R2* was informative in disentangling the underlying tissue changes such as iron accumulation, demyelination, or calcifications. Therefore, combining QSM with R2* measurement can provide a more detailed assessment of tissue changes and may pave the way for improved diagnosis of TBI, and several other complex neurodegenerative diseases.

[1]  K. Shmueli,et al.  An optimized and highly repeatable MRI acquisition and processing pipeline for quantitative susceptibility mapping in the head‐and‐neck region , 2020, Magnetic resonance in medicine.

[2]  Ferdinand Schweser,et al.  Visualization of thalamic calcium influx with quantitative susceptibility mapping as a potential imaging biomarker for repeated mild traumatic brain injury , 2019, NeuroImage.

[3]  Amit Agrawal,et al.  Estimating the global incidence of traumatic brain injury. , 2019, Journal of neurosurgery.

[4]  Anita Karsa,et al.  Optimising MRI magnetic susceptibility mapping for applications in challenging regions of the body , 2018 .

[5]  A. Pitkänen,et al.  Detection of Hyperexcitability by Functional Magnetic Resonance Imaging after Experimental Traumatic Brain Injury. , 2018, Journal of neurotrauma.

[6]  Oliver Speck,et al.  A robust multi-scale approach to quantitative susceptibility mapping , 2018, NeuroImage.

[7]  Alan H Wilman,et al.  Quantitative Susceptibility Mapping for Following Intracranial Hemorrhage. , 2018, Radiology.

[8]  S. Kolakowsky-Hayner,et al.  Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping , 2018, American Journal of Neuroradiology.

[9]  Alejandra Sierra,et al.  Nuclei‐specific deposits of iron and calcium in the rat thalamus after status epilepticus revealed with quantitative susceptibility mapping (QSM) , 2018, Journal of magnetic resonance imaging : JMRI.

[10]  Yi Wang,et al.  Quantitative susceptibility mapping to evaluate the early stage of Alzheimer's disease☆ , 2017, NeuroImage: Clinical.

[11]  Li Guo,et al.  Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge , 2017, Magnetic resonance in medicine.

[12]  Ferdinand Schweser,et al.  Overview of quantitative susceptibility mapping , 2017, NMR in biomedicine.

[13]  Yi Wang,et al.  The clinical utility of QSM: disease diagnosis, medical management, and surgical planning , 2017, NMR in biomedicine.

[14]  Ferdinand Schweser,et al.  An illustrated comparison of processing methods for phase MRI and QSM: removal of background field contributions from sources outside the region of interest , 2017, NMR in biomedicine.

[15]  Alejandra Sierra,et al.  Magnetization transfer SWIFT MRI consistently detects histologically verified myelin loss in the thalamocortical pathway after a traumatic brain injury in rat , 2017, NMR in biomedicine.

[16]  K Scheffler,et al.  Evaluation of transmit efficiency and SAR for a tight fit transceiver human head phased array at 9.4 T , 2017, NMR in biomedicine.

[17]  Justin A. Long,et al.  Spatiotemporal changes in diffusion, T2 and susceptibility of white matter following mild traumatic brain injury , 2016, NMR in biomedicine.

[18]  Wei Liu,et al.  Imaging Cerebral Microhemorrhages in Military Service Members with Chronic Traumatic Brain Injury. , 2016, Radiology.

[19]  Kemin Chen,et al.  Region‐specific disturbed iron distribution in early idiopathic Parkinson's disease measured by quantitative susceptibility mapping , 2015, Human brain mapping.

[20]  Hongjiang Wei,et al.  Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications , 2015, Tomography.

[21]  Yi Wang,et al.  Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: Interpreting positive susceptibility and the presence of iron , 2015, Magnetic resonance in medicine.

[22]  P. Garred,et al.  Systemic and Ocular Long Pentraxin 3 in Patients with Age-Related Macular Degeneration , 2015, PloS one.

[23]  Luning Wang,et al.  Improved Visualization of Cartilage Canals Using Quantitative Susceptibility Mapping , 2015, PloS one.

[24]  E Mark Haacke,et al.  Quantifying brain iron deposition in patients with Parkinson's disease using quantitative susceptibility mapping, R2 and R2. , 2015, Magnetic resonance imaging.

[25]  Y Wang,et al.  Usefulness of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson Disease , 2015, American Journal of Neuroradiology.

[26]  Teemu Laitinen,et al.  Diffusion tensor imaging detects chronic microstructural changes in white and gray matter after traumatic brain injury in rat , 2015, Front. Neurosci..

[27]  Anton J. M. Loonen,et al.  Circuits regulating pleasure and happiness: the evolution of reward-seeking and misery-fleeing behavioral mechanisms in vertebrates , 2015, Front. Neurosci..

[28]  Jian-Qiang Lu,et al.  Validation of quantitative susceptibility mapping with Perls' iron staining for subcortical gray matter , 2015, NeuroImage.

[29]  Yi Wang,et al.  Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker , 2014, Magnetic resonance in medicine.

[30]  G. Allan Johnson,et al.  Quantitative magnetic susceptibility of the developing mouse brain reveals microstructural changes in the white matter , 2014, NeuroImage.

[31]  Y. Lui,et al.  The presence and role of iron in mild traumatic brain injury: an imaging perspective. , 2014, Journal of neurotrauma.

[32]  Ravi S. Menon,et al.  Origins of R2∗ orientation dependence in gray and white matter , 2013, Proceedings of the National Academy of Sciences.

[33]  Douglas H. Smith,et al.  Axonal pathology in traumatic brain injury , 2013, Experimental Neurology.

[34]  Ferdinand Schweser,et al.  Toward online reconstruction of quantitative susceptibility maps: Superfast dipole inversion , 2013, Magnetic resonance in medicine.

[35]  Margit Jehna,et al.  Quantitative susceptibility mapping in multiple sclerosis. , 2013, Radiology.

[36]  Ferdinand Schweser,et al.  Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study , 2012, NeuroImage.

[37]  Alejandra Sierra,et al.  Detection of calcifications in vivo and ex vivo after brain injury in rat using SWIFT , 2012, NeuroImage.

[38]  Julien Cohen-Adad,et al.  T2* mapping and B0 orientation-dependence at 7T reveal cyto- and myeloarchitecture organization of the human cortex , 2012, NeuroImage.

[39]  Jeff H. Duyn,et al.  The contribution of myelin to magnetic susceptibility-weighted contrasts in high-field MRI of the brain , 2012, NeuroImage.

[40]  Yi Wang,et al.  Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map , 2012, NeuroImage.

[41]  Bing Wu,et al.  Magnetic susceptibility anisotropy of human brain in vivo and its molecular underpinnings , 2012, NeuroImage.

[42]  Christian Langkammer,et al.  Susceptibility induced gray–white matter MRI contrast in the human brain , 2012, NeuroImage.

[43]  J. Reichenbach,et al.  Detection of Cerebral Microbleeds with Quantitative Susceptibility Mapping in the Arcabeta Mouse Model of Cerebral Amyloidosis , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[44]  O. Benavente,et al.  Cerebral Microbleeds: Histopathological Correlation of Neuroimaging , 2011, Cerebrovascular Diseases.

[45]  Yi Wang,et al.  A novel background field removal method for MRI using projection onto dipole fields (PDF) , 2011, NMR in biomedicine.

[46]  Bing Wu,et al.  High-field (9.4T) MRI of brain dysmyelination by quantitative mapping of magnetic susceptibility , 2011, NeuroImage.

[47]  J. Reichenbach,et al.  Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. , 2010, Medical physics.

[48]  Teemu Laitinen,et al.  Diffusion tensor MRI of axonal plasticity in the rat hippocampus , 2010, NeuroImage.

[49]  M. Fukunaga,et al.  Layer-specific variation of iron content in cerebral cortex as a source of MRI contrast , 2010, Proceedings of the National Academy of Sciences.

[50]  Pascal Spincemaille,et al.  Nonlinear Regularization for Per Voxel Estimation of Magnetic Susceptibility Distributions From MRI Field Maps , 2010, IEEE Transactions on Medical Imaging.

[51]  Carlo Caltagirone,et al.  Characterization of white matter fiber bundles with T  2* relaxometry and diffusion tensor imaging , 2009, Magnetic resonance in medicine.

[52]  Evandro T. Martins,et al.  Psychiatric disorders and traumatic brain injury , 2008, Neuropsychiatric disease and treatment.

[53]  R. Bullock,et al.  Moderate and severe traumatic brain injury in adults , 2008, The Lancet Neurology.

[54]  Alejandra Sierra,et al.  Manganese enhanced MRI detects mossy fiber sprouting rather than neurodegeneration, gliosis or seizure-activity in the epileptic rat hippocampus , 2008, NeuroImage.

[55]  D. Corbett,et al.  Coaccumulation of Calcium and β-Amyloid in the Thalamus after Transient Middle Cerebral Artery Occlusion in Rats , 2008, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[56]  Jeff H. Duyn,et al.  High-field MRI of brain cortical substructure based on signal phase , 2007, Proceedings of the National Academy of Sciences.

[57]  K. Coburn,et al.  Neuropsychiatric complications of traumatic brain injury: a critical review of the literature (a report by the ANPA Committee on Research). , 2007, The Journal of neuropsychiatry and clinical neurosciences.

[58]  A. Pitkänen,et al.  A model of posttraumatic epilepsy induced by lateral fluid-percussion brain injury in rats , 2006, Neuroscience.

[59]  A. Newberg,et al.  Neuroimaging in traumatic brain imaging , 2005, NeuroRX.

[60]  John A Butman,et al.  Comparison of MRI and CT for detection of acute intracerebral hemorrhage. , 2004, JAMA.

[61]  C. J. Wall,et al.  Diffuse axonal injury in children: Clinical correlation with hemorrhagic lesions , 2004, Annals of neurology.

[62]  M. Robson,et al.  Magic angle effects in MR neurography. , 2004, AJNR. American journal of neuroradiology.

[63]  Yimei Zhu,et al.  Fast phase unwrapping algorithm for interferometric applications. , 2003, Optics letters.

[64]  M. Garrosa,et al.  Selective calcification of rat brain lesions caused by systemic administration of kainic acid. , 2003, Histology and histopathology.

[65]  Helen M. Bramlett,et al.  Quantitative structural changes in white and gray matter 1 year following traumatic brain injury in rats , 2002, Acta Neuropathologica.

[66]  P. Kochanek,et al.  One-year study of spatial memory performance, brain morphology, and cholinergic markers after moderate controlled cortical impact in rats. , 1999, Journal of neurotrauma.

[67]  J. Trojanowski,et al.  Experimental Brain Injury Induces Regionally Distinct Apoptosis during the Acute and Delayed Post-Traumatic Period , 1998, The Journal of Neuroscience.

[68]  J. Trojanowski,et al.  Enduring cognitive, neurobehavioral and histopathological changes persist for up to one year following severe experimental brain injury in rats , 1998, Neuroscience.

[69]  J. Schenck.  The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds. , 1996, Medical physics.

[70]  E. Haacke,et al.  Theory of NMR signal behavior in magnetically inhomogeneous tissues: The static dephasing regime , 1994, Magnetic resonance in medicine.

[71]  Harvey S. Levin,et al.  Magnetic resonance imaging and computerized tomography in relation to the neurobehavioral sequelae of mild and moderate head injuries. , 1987, Journal of neurosurgery.

[72]  M J Campbell,et al.  An immunohistochemical characterization of somatostatin‐28 and somatostatin‐281–12 in monkey prefrontal cortex , 1986, The Journal of comparative neurology.

[73]  E. Haacke,et al.  Quantitative susceptibility mapping: current status and future directions. , 2015, Magnetic resonance imaging.

[74]  S. Okubo,et al.  Cerebral hemorrhage, brain edema, and heme oxygenase-1 expression after experimental traumatic brain injury. , 2013, Acta neurochirurgica. Supplement.

[75]  C. J. Wall,et al.  Susceptibility weighted imaging: neuropsychologic outcome and pediatric head injury. , 2005, Pediatric neurology.

[76]  E. Haacke,et al.  Imaging iron stores in the brain using magnetic resonance imaging. , 2005, Magnetic resonance imaging.

[77]  N. Yamada,et al.  Intracranial calcification on gradient-echo phase image: depiction of diamagnetic susceptibility. , 1996, Radiology.

[78]  O. Alonso,et al.  Early microvascular and neuronal consequences of traumatic brain injury: a light and electron microscopic study in rats. , 1994, Journal of neurotrauma.