Insights into smouldering MS brain pathology with multimodal diffusion tensor and PET imaging

Objective: To evaluate in vivo the co-occurrence of microglial activation and microstructural white matter damage in multiple sclerosis (MS) brain, and to examine their association with clinical disability. Methods: 18-kDa translocator protein (TSPO) brain PET imaging was performed for evaluation of microglial activation by using the radioligand [11C](R)-PK11195. TSPO-binding was evaluated as the distribution volume ratio (DVR) from dynamic PET images. Diffusion tensor imaging (DTI) and conventional MRI were performed at the same time. Mean fractional anisotropy (FA) and mean (MD), axial (AD) and radial (RD) diffusivities were calculated within the whole normal appearing white matter (NAWM) and segmented NAWM regions appearing normal in conventional MRI. 55 MS patients and 15 healthy controls were examined. Results: Microstructural damage was observed in the NAWM of MS brain. DTI parameters of MS patients were significantly altered in the NAWM, when compared to an age- and sex-matched healthy control group: mean FA was decreased, and MD, AD and RD were increased. These structural abnormalities correlated with increased TSPO binding in the whole NAWM and in the temporal NAWM (p<0.05 for all correlations; p<0.01 for RD in the temporal NAWM). Both compromised WM integrity and increased microglial activation in the NAWM correlated significantly with higher clinical disability measured with expanded disability status scale (EDSS). Conclusions: Widespread structural disruption in the NAWM is linked to neuroinflammation, and both phenomena associate with clinical disability. Multimodal PET and DTI imaging allows in vivo evaluation of widespread MS pathology not visible using conventional MRI.

[1]  R. Parkkola,et al.  Microglial activation, white matter tract damage, and disability in MS , 2018, Neurology: Neuroimmunology & Neuroinflammation.

[2]  H. Lassmann Multiple Sclerosis Pathology. , 2018, Cold Spring Harbor perspectives in medicine.

[3]  Simon Hametner,et al.  Loss of ‘homeostatic’ microglia and patterns of their activation in active multiple sclerosis , 2017, Brain : a journal of neurology.

[4]  P. Matthews,et al.  Pro-inflammatory activation of primary microglia and macrophages increases 18 kDa translocator protein expression in rodents but not humans , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[5]  W. Brück,et al.  Relationship of acute axonal damage, Wallerian degeneration, and clinical disability in multiple sclerosis , 2017, Journal of Neuroinflammation.

[6]  Manoj Kumar,et al.  INGE GRUNDKE-IQBAL AWARD FOR ALZHEIMER’S RESEARCH: NEUROTOXIC REACTIVE ASTROCYTES ARE INDUCED BY ACTIVATED MICROGLIA , 2019, Alzheimer's & Dementia.

[7]  W. Schwindt,et al.  Early silent microstructural degeneration and atrophy of the thalamocortical network in multiple sclerosis , 2016, Human brain mapping.

[8]  N. Schuff,et al.  Multimodal imaging in Alzheimer's disease: validity and usefulness for early detection , 2015, The Lancet Neurology.

[9]  Alard Roebroeck,et al.  General overview on the merits of multimodal neuroimaging data fusion , 2014, NeuroImage.

[10]  Richard B. Banati,et al.  The 18 kDa Translocator Protein, Microglia and Neuroinflammation , 2014, Brain pathology.

[11]  R. Parkkola,et al.  In Vivo Detection of Diffuse Inflammation in Secondary Progressive Multiple Sclerosis Using PET Imaging and the Radioligand 11C-PK11195 , 2014, The Journal of Nuclear Medicine.

[12]  P. Pantano,et al.  DTI Measurements in Multiple Sclerosis: Evaluation of Brain Damage and Clinical Implications , 2013, Multiple sclerosis international.

[13]  Susumu Mori,et al.  Effects of b-value and echo time on magnetic resonance diffusion tensor imaging-derived parameters at 1.5 t: A voxel-wise study , 2013 .

[14]  Philippe Hantraye,et al.  Reactive Astrocytes Overexpress TSPO and Are Detected by TSPO Positron Emission Tomography Imaging , 2012, The Journal of Neuroscience.

[15]  M. Onu,et al.  Diffusion abnormality maps in demyelinating disease: correlations with clinical scores. , 2012, European journal of radiology.

[16]  Bernhard Hemmer,et al.  An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis , 2012, NeuroImage.

[17]  B. Tavitian,et al.  Current paradigm of the 18-kDa translocator protein (TSPO) as a molecular target for PET imaging in neuroinflammation and neurodegenerative diseases , 2011, Insights into Imaging.

[18]  G. Comi,et al.  Thalamic Damage Predicts the Evolution of Primary-Progressive Multiple Sclerosis at 5 Years , 2011, American Journal of Neuroradiology.

[19]  Alexander Leemans,et al.  The B‐matrix must be rotated when correcting for subject motion in DTI data , 2009, Magnetic resonance in medicine.

[20]  Aristide Merola,et al.  Demyelination, Inflammation, and Neurodegeneration in Multiple Sclerosis Deep Gray Matter , 2009, Journal of neuropathology and experimental neurology.

[21]  Hans Lassmann,et al.  The relation between inflammation and neurodegeneration in multiple sclerosis brains , 2009, Brain : a journal of neurology.

[22]  Frederik Barkhof,et al.  Regional DTI differences in multiple sclerosis patients , 2009, NeuroImage.

[23]  Bruce Fischl,et al.  Regional white matter volume differences in nondemented aging and Alzheimer's disease , 2009, NeuroImage.

[24]  Tetsuya Suhara,et al.  Phase-dependent roles of reactive microglia and astrocytes in nervous system injury as delineated by imaging of peripheral benzodiazepine receptor , 2007, Brain Research.

[25]  Massimo Filippi,et al.  Conventional MRI in Multiple Sclerosis , 2007, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[26]  T. Guilarte,et al.  Imaging the peripheral benzodiazepine receptor response in central nervous system demyelination and remyelination. , 2006, Toxicological sciences : an official journal of the Society of Toxicology.

[27]  Derek K. Jones,et al.  RESTORE: Robust estimation of tensors by outlier rejection , 2005, Magnetic resonance in medicine.

[28]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[29]  Vincent J. Cunningham,et al.  Parametric Imaging of Ligand-Receptor Binding in PET Using a Simplified Reference Region Model , 1997, NeuroImage.

[30]  W. L. Benedict,et al.  Multiple Sclerosis , 2007, Journal - Michigan State Medical Society.