Imaging outcome measures of neuroprotection and repair in MS: A consensus statement from NAIMS

Objective To summarize current and emerging imaging techniques that can be used to assess neuroprotection and repair in multiple sclerosis (MS), and to provide a consensus opinion on the potential utility of each technique in clinical trial settings. Methods Clinicians and scientists with expertise in the use of MRI in MS convened in Toronto, Canada, in November 2016 at a North American Imaging in Multiple Sclerosis (NAIMS) Cooperative workshop meeting. The discussion was compiled into a manuscript and circulated to all NAIMS members in attendance. Edits and feedback were incorporated until all authors were in agreement. Results A wide spectrum of imaging techniques and analysis methods in the context of specific study designs were discussed, with a focus on the utility and limitations of applying each technique to assess neuroprotection and repair. Techniques were discussed under specific themes, and included conventional imaging, magnetization transfer ratio, diffusion tensor imaging, susceptibility-weighted imaging, imaging cortical lesions, magnetic resonance spectroscopy, PET, advanced diffusion imaging, sodium imaging, multimodal techniques, imaging of special regions, statistical considerations, and study design. Conclusions Imaging biomarkers of neuroprotection and repair are an unmet need in MS. There are a number of promising techniques with different strengths and limitations, and selection of a specific technique will depend on a number of factors, notably the question the trial seeks to answer. Ongoing collaborative efforts will enable further refinement and improved methods to image the effect of novel therapeutic agents that exert benefit in MS predominately through neuroprotective and reparative mechanisms.

[1]  F. Paul,et al.  Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders , 2020, Frontiers in Neurology.

[2]  R. Schmidt,et al.  In vivo evolution of biopsy‐proven inflammatory demyelination quantified by R2t* mapping , 2020, Annals of clinical and translational neurology.

[3]  P. Calabresi,et al.  Remyelination alters the pattern of myelin in the cerebral cortex , 2020, bioRxiv.

[4]  Peter A. Calabresi,et al.  TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis , 2019, NeuroImage: Clinical.

[5]  D. Ontaneda,et al.  Diagnosis and Management of Progressive Multiple Sclerosis , 2019, Biomedicines.

[6]  Nico Papinutto,et al.  The NAIMS cooperative pilot project: Design, implementation and future directions , 2018, Multiple sclerosis.

[7]  Christian Kames,et al.  Rapid two-step dipole inversion for susceptibility mapping with sparsity priors , 2018, NeuroImage.

[8]  D. Pelletier,et al.  Thalamic atrophy in multiple sclerosis: A magnetic resonance imaging marker of neurodegeneration throughout disease , 2018, Annals of neurology.

[9]  Julien Cohen-Adad,et al.  In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis , 2017, Brain : a journal of neurology.

[10]  D. Ramasamy,et al.  Leptomeningeal contrast enhancement is associated with progression of cortical atrophy in MS: A retrospective, pilot, observational longitudinal study , 2017, Multiple sclerosis.

[11]  Anthony Traboulsee,et al.  Susceptibility‐sensitive MRI of multiple sclerosis lesions and the impact of normal‐appearing white matter changes , 2017, NMR in biomedicine.

[12]  D. Reich,et al.  Volumetric Analysis from a Harmonized Multisite Brain MRI Study of a Single Subject with Multiple Sclerosis , 2017, American Journal of Neuroradiology.

[13]  Yi Wang,et al.  Rapid whole brain myelin water content mapping without an external water standard at 1.5T. , 2017, Magnetic resonance imaging.

[14]  Jerry L Prince,et al.  Disease-modifying therapies modulate retinal atrophy in multiple sclerosis , 2017, Neurology.

[15]  Siegfried Trattnig,et al.  Slow expansion of multiple sclerosis iron rim lesions: pathology and 7 T magnetic resonance imaging , 2016, Acta Neuropathologica.

[16]  D. Arnold,et al.  MTR recovery in brain lesions in the BECOME study of glatiramer acetate vs interferon β-1b , 2016, Neurology.

[17]  Massimo Filippi,et al.  Persistent 7-tesla phase rim predicts poor outcome in new multiple sclerosis patient lesions. , 2016, The Journal of clinical investigation.

[18]  Peter R Luijten,et al.  Increased cortical grey matter lesion detection in multiple sclerosis with 7 T MRI: a post-mortem verification study. , 2016, Brain : a journal of neurology.

[19]  J. Sedlacik,et al.  Heterogeneity of Multiple Sclerosis Lesions in Multislice Myelin Water Imaging , 2016, PloS one.

[20]  Jennifer A McNab,et al.  Characterization of Axonal Disease in Patients with Multiple Sclerosis Using High-Gradient-Diffusion MR Imaging. , 2016, Radiology.

[21]  Russell T. Shinohara,et al.  Relating multi-sequence longitudinal intensity profiles and clinical covariates in incident multiple sclerosis lesions , 2015, NeuroImage: Clinical.

[22]  A. Dibernardo,et al.  The natural history of brain volume loss among patients with multiple sclerosis: A systematic literature review and meta-analysis , 2015, Journal of the Neurological Sciences.

[23]  G. Mangeat,et al.  Multivariate combination of magnetization transfer, T2* and B0 orientation to study the myelo-architecture of the in vivo human cortex , 2015, NeuroImage.

[24]  Susan A. Gauthier,et al.  Measuring longitudinal myelin water fraction in new multiple sclerosis lesions , 2015, NeuroImage: Clinical.

[25]  D. Reich,et al.  Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis , 2015, Neurology.

[26]  Snehashis Roy,et al.  Optical coherence tomography reflects brain atrophy in multiple sclerosis: A four‐year study , 2015, Annals of neurology.

[27]  D. Arnold,et al.  Normalization of White Matter Intensity on T1‐Weighted Images of Patients with Acquired Central Nervous System Demyelination , 2015, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[28]  B. Trapp,et al.  Pathological mechanisms in progressive multiple sclerosis , 2015, The Lancet Neurology.

[29]  Jerry L Prince,et al.  Relationships between quantitative spinal cord MRI and retinal layers in multiple sclerosis , 2015, Neurology.

[30]  Kesshi M Jordan,et al.  Spinal cord gray matter atrophy correlates with multiple sclerosis disability , 2014, Annals of neurology.

[31]  C. Crainiceanu,et al.  Statistical normalization techniques for magnetic resonance imaging , 2014, NeuroImage: Clinical.

[32]  Zografos Caramanos,et al.  Surface‐based analysis reveals regions of reduced cortical magnetization transfer ratio in patients with multiple sclerosis: A proposed method for imaging subpial demyelination , 2014, Human brain mapping.

[33]  Yi Wang,et al.  Quantitative s usceptibility Mapping of Multiple s clerosis lesions at Various ages 1 , 2014 .

[34]  D. Miller,et al.  Sample sizes for lesion magnetisation transfer ratio outcomes in remyelination trials for multiple sclerosis. , 2014, Multiple sclerosis and related disorders.

[35]  Jurgen W. A. Sijbesma,et al.  PET imaging of demyelination and remyelination in the cuprizone mouse model for multiple sclerosis: A comparison between [11C]CIC and [11C]MeDAS , 2013, NeuroImage.

[36]  B. Mädler,et al.  Multicenter measurements of myelin water fraction and geometric mean T2: Intra‐ and intersite reproducibility , 2013, Journal of magnetic resonance imaging : JMRI.

[37]  Simon Hametner,et al.  Iron and neurodegeneration in the multiple sclerosis brain , 2013, Annals of neurology.

[38]  J. Ranjeva,et al.  Sodium imaging as a marker of tissue injury in patients with multiple sclerosis. , 2013, Multiple sclerosis and related disorders.

[39]  Thomas Benner,et al.  Contribution of cortical lesion subtypes at 7T MRI to physical and cognitive performance in MS , 2013, Neurology.

[40]  Anthony Traboulsee,et al.  Magnetic resonance frequency shifts during acute MS lesion formation , 2013, Neurology.

[41]  R. Franklin,et al.  Neuroprotection and repair in multiple sclerosis , 2012, Nature Reviews Neurology.

[42]  J. Debbins,et al.  A Validation Study of Multicenter Diffusion Tensor Imaging: Reliability of Fractional Anisotropy and Diffusivity Values , 2012, American Journal of Neuroradiology.

[43]  Heidi Johansen-Berg,et al.  Myelin water imaging reflects clinical variability in multiple sclerosis , 2012, NeuroImage.

[44]  Daniel S Reich,et al.  Evolution of the blood–brain barrier in newly forming multiple sclerosis lesions , 2011, Annals of neurology.

[45]  M. Horsfield,et al.  A multicenter assessment of cervical cord atrophy among MS clinical phenotypes , 2011, Neurology.

[46]  S. Lehéricy,et al.  Imaging central nervous system myelin by positron emission tomography in multiple sclerosis using [methyl‐11C]‐2‐(4′‐methylaminophenyl)‐ 6‐hydroxybenzothiazole , 2011, Annals of neurology.

[47]  M. Lowe,et al.  Measuring Myelin Repair and Axonal Loss with Diffusion Tensor Imaging , 2010, American Journal of Neuroradiology.

[48]  L. Gjerstad,et al.  Cost of disorders of the brain in Norway , 2010, Acta neurologica Scandinavica. Supplementum.

[49]  I. Allen,et al.  Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. , 2010, Brain : a journal of neurology.

[50]  Helene Ratiney,et al.  MR spectroscopic imaging of glutathione in the white and gray matter at 7 T with an application to multiple sclerosis. , 2010, Magnetic resonance imaging.

[51]  Yi Wang,et al.  Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: Validation and application to brain imaging , 2010, Magnetic resonance in medicine.

[52]  L. Kappos,et al.  Black holes in multiple sclerosis: definition, evolution, and clinical correlations , 2009, Acta neurologica Scandinavica.

[53]  R. A. Brown,et al.  Normalization of Magnetization Transfer Ratio MRI For Multicentre Clinical Trials , 2010 .

[54]  David H. Miller,et al.  Imaging outcomes for neuroprotection and repair in multiple sclerosis trials , 2009, Nature Reviews Neurology.

[55]  Sridar Narayanan,et al.  Measuring demyelination and remyelination in acute multiple sclerosis lesion voxels. , 2009, Archives of neurology.

[56]  D. Arnold,et al.  Magnetization transfer ratio evolution with demyelination and remyelination in multiple sclerosis lesions , 2008, Annals of neurology.

[57]  P. Narayana,et al.  Improved Identification of Intracortical Lesions in Multiple Sclerosis with Phase-Sensitive Inversion Recovery in Combination with Fast Double Inversion Recovery MR Imaging , 2007, American Journal of Neuroradiology.

[58]  Frederik Barkhof,et al.  Extensive Hippocampal Demyelination in Multiple Sclerosis , 2007, Journal of neuropathology and experimental neurology.

[59]  David H. Miller,et al.  Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain , 2004, Annals of neurology.

[60]  P. Matthews,et al.  Thalamic neurodegeneration in multiple sclerosis , 2002, Annals of neurology.

[61]  P M Matthews,et al.  Proton MR spectroscopy in multiple sclerosis. , 2000, Neuroimaging clinics of North America.

[62]  Alan C. Evans,et al.  PK11195 binding to the peripheral benzodiazepine receptor as a marker of microglia activation in multiple sclerosis and experimental autoimmune encephalomyelitis , 1997, Journal of neuroscience research.

[63]  A. MacKay,et al.  In vivo visualization of myelin water in brain by magnetic resonance , 1994, Magnetic resonance in medicine.