Ling Fang¹, Matthew C. Murphy², Qiuxia Luo¹, Xiaodong Chen³, Linqi Zhang¹, Bingjun He¹, Jun Chen², Jonathan M. Scott², Meng Yin², Kevin J. Glaser², Richard L. Ehman², Wei Qiu³, and Jin Wang^1
1Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China, ²Department of Radiology, Mayo Clinic, Rochester, MN, United States, ³Department of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) characterized by demyelination, axonal loss and neurodegeneration. Because of overlapping clinical and imaging features, it is a challenge to distinguish MS from Neuromyelitis optica spectrum disorders (NMOSDs) for which the treatment is different. 3D MR Elastography (MRE) is a potential method to evaluate brain tissue damage in autoimmune diseases of the CNS. By measuring the viscoelasticity of the centrum ovale with 3D MRE, we found significantly decreased damping ratio and loss modulus in MS compared with NMOSDs, suggesting possible diagnostic utility for 3D MRE in MS.

Jackie Yik^1,2, Pierre Becquart³, Jasmine Gill³, Shannon H. Kolind^1,2,4,5, Virginia Devonshire⁵, Ana-Luiza Sayao⁵, Alice Schabas⁵, Robert Carruthers⁵, Anthony Traboulsee⁵, G.R. Wayne Moore^2,3, David K.B. Li^4,5, Sophie Stukas³, Cheryl Wellington³, Jacqueline A. Quandt³, Irene M. Vavasour^2,4, and Cornelia Laule^1,2,3,4
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ²International Collaboration on Repair Discoveries, Vancouver, BC, Canada, ³Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada, ⁴Radiology, University of British Columbia, Vancouver, BC, Canada, ⁵Medicine, University of British Columbia, Vancouver, BC, Canada

Neurofilaments, particularly the light subunit (NfL), have become a biomarker of interest in multiple sclerosis (MS) and can be measured in blood serum after neuronal damage. NfL has been studied in MS prognosis and treatment monitoring, but little is known about the relationship between NfL and advanced quantitative MRI measures. This exploratory study characterizes the relationship between NfL and myelin water fraction and diffusion measures in different brain regions through regression models. We found NfL to correlate with myelin and axonal damage measures in the whole brain and normal appearing white matter but only to myelin water fraction in lesions.

Eva Heckova¹, Alexandra Lipka¹, Assunta Dal-Bianco², Bernhard Strasser¹, Gilbert Hangel^1,3, Paulus Rommer², Petra Hnilicová⁴, Ema Kantorová⁵, Lukas Hingerl¹, Stanislav Motyka¹, Fritz Leutmezer², Stephan Gruber¹, Siegfried Trattnig^1,6, and Wolfgang Bogner^1
1High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ²Department of Neurology, Medical University of Vienna, Vienna, Austria, ³Department of Neurosurgery, Medical University of Vienna, Vienna, Austria, ⁴Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia, ⁵Clinic of Neurology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia, ⁶Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria

To enhance the detection of diffuse pathological alterations associated with multiple sclerosis, high-resolution MR spectroscopic imaging was performed at 7T, together with clinical MRI, in 68 MS patients with different levels of clinical disability and 20 healthy controls. Increased myo-inositol, a marker of neuroinflammation-induced astrogliosis, was found in white matter regions appearing normal on clinical MRI, even in subgroup of MS patients with no evidence of clinical disability. Myo-inositol/N-acetylaspartate ratio in the NAWM and cortical gray matter correlated with EDSS, suggesting that reactive astrogliosis and axonal injury play important role in the evolution of MS-related disability.

Oun Al-iedani^1,2, Saadallah Ramadan^2,3, Karen Ribbons², Rodney Lea², and Jeannette Lechner-Scott^2,4,5
1School of Health Sciences, University of Newcastle, Newcastle, Australia, ²Hunter Medical Research Institute, Newcastle, Australia, ³Faculty of Health and Medicine, University of Newcastle, Newcastle, Australia, ⁴Department of Neurology, John Hunter Hospital, Newcastle, Australia, ⁵School of Medicine and Public Health, University of Newcastle, Newcastle, Australia

This novel study compares the neurometabolic effects of different DMTs on the MS brain. We evaluated volumetric and neurometabolic changes in RRMS patients on fingolimod(N=52), injectables(N=46) and HCs cohort(N=51). MRS was acquired from PCG and PFC. Compared to HCs, a significant reduction in NAA/tCr were detected in both locations and cohorts. Clinical parameters, MR-volumetrics and neurometabolic concentrations showed no statistically significant differences between RRMS cohorts. MRI metrics and neurometabolites from both locations, showed moderate correlations with cognition, fatigue and memory. This the first study demonstrating that fingolimod and injectable DMTs influence volumetric and neurometabolic profiles of MS-brain similarly.

Antonio Maria Chiarelli¹, Daniele Mascali¹, Nikolaos Petsas², Carlo Pozzilli², Richard Geoffrey Wise¹, and Valentina Tomassini^1
1Department of Neuroscience, Imaging and Clinical Sciences, University G. D'Annunzio of Chieti Pescara, Chieti Scalo, Italy, ²Department of Neurology and Psychiatry, Sapienza University, Rome, Italy

The cerebrovascular system is altered in MS. Using breath-hold BOLD-MRI, we tested whether pharmacological modulation of MS inflammation influences alteration in cerebrovascular reactivity (CVR). We found that CVR increased with immunomodulation and this increase was negatively correlated with pre-treatment CVR, suggesting that cerebrovascular alteration reflects disease activity. Moreover, lower CVR in the pre-treatment phase was associated with lower grey matter volume and this correlation was lost with immunomodulation, indicating an involvement of brain vasculature in neurodegeneration. Given the multiparametric characteristic of BOLD, further studies are warranted to clarify the vascular origin of our findings.      

Till Huelnhagen^1,2,3, Omar Al Louzi⁴, Mário João Fartaria^1,2,3, Lynn Daboul⁴, Pietro Maggi^5,6, Cristina Granziera^7,8,9, Meritxell Bach Cuadra^2,3,10, Jonas Richiardi², Daniel S Reich⁴, Tobias Kober^1,2,3, and Pascal Sati^4,11
1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³Signal Processing Laboratory (LTS 5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, United States, ⁵Department of Neurology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁶Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium, ⁷Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, ⁸Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, ⁹Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland, ¹⁰Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), University of Lausanne, Lausanne, Switzerland, ¹¹Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States

The fraction of white matter lesions exhibiting the central vein sign (CVS) has shown promise as a biomarker in the diagnosis of multiple sclerosis. As manual CVS assessment is not clinically feasible, automated solutions have been proposed to perform this task. A deep-learning-based method called “CVSnet” demonstrated effective and accurate discrimination of MS from its mimics but required manual pre-selection. This work extends CVSnet to allow fully automated CVS assessment without manual interaction. High-quality, expert-reviewed segmentations of almost 6300 lesions were used for training and testing. The proposed method achieved accuracies between 75% and 80% in an unseen testing set.

Paola Valsasina¹, Milagros Hidalgo de la Cruz¹, Alessandro Meani¹, Claudio Gobbi^2,3, Antonio Gallo⁴, Chiara Zecca^2,3, Alvino Bisecco⁴, Maria A. Rocca^1,5,6, and Massimo Filippi^1,5,6,7,8
1Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy, ²Multiple Sclerosis Center, Department of Neurology, Neurocenter of Southern Switzerland, Civic Hospital, Lugano, Switzerland, ³Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland, ⁴Department of Advanced Medical and Surgical Sciences, and 3T MRI Center, University of Campania “Luigi Vanvitelli”, Naples, Italy, ⁵Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy, ⁶Vita-Salute San Raffaele University, Milan, Italy, ⁷Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy, ⁸Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy

Here, we assessed damage of cortex, deep grey matter, cerebellum and cervical cord to determine their relative contributions to the main clinical disability (EDSS) milestones in a multicentre cohort of 198 multiple sclerosis (MS) patients. The main determinants of EDSS=3.0 were cervical cord and thalamic atrophy, and brain lesion burden. The EDSS=4.0 milestone was better explained by cortical atrophy, together with cord and cerebellar damage, while the only predictor of EDSS=6.0 was cervical cord damage. This study is shading light on the differential weight of inflammatory and neurodegenerative processes leading to disability accumulation across various MS disease phases.

Riccardo Galbusera^1,2,3, Erik Bahn⁴, Matthias Weigel^2,3,5, Po-Jui Lu^1,2,3, Muhamed Barakovic^1,2,3, Reza Rahmanzadeh^1,2,3, Peter Dechent⁶, Antoine Lutti⁷, Govind Bhagavatheeshwaran⁸, Ludwig Kappos^2,3, Wolfgang Brück⁴, Christine Stadelmann-Nessler⁴, and Cristina Granziera^1,2,3
1Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, Basel, Switzerland, ²Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, Basel, Switzerland, ³Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland, Basel, Switzerland, ⁴Institute of Neuropathology, University Medical Center, Göttingen, Germany, Göttingen, Germany, ⁵Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, CH, Basel, Switzerland, ⁶Department of Cognitive Neurology, MR-Research in Neurosciences, University Medical Center Göttingen, Göttingen, Germany, Göttingen, Germany, ⁷Centre for Research in Neuroscience - Department of Clinical Neurosciences, Laboratoire de recherche en neuroimagerie (LREN) University Hospital and University of Lausanne, Lausanne, Switzerland, Lausanne, Switzerland, ⁸National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA, Bethesda, MD, United States

We have identified the imaging correlates of multiple sclerosis lesion subtypes by exploiting post-mortem multiparametric quantitative MRI and histopathological analysis. Remyelinated lesions showed distinct MRI characteristics compared to other MS lesions, and a remarkable resemblance to normal-appearing tissue properties. Our findings suggest that multiparametric quantitative MRI may well help to identify specific focal lesion types in vivo in MS patients.

Sara Bosticardo¹, Simona Schiavi¹, Sabine Schaedelin², Po-Jui Lu^3,4, Muhamed Barakovic^2,3, Matthias Weigel^2,3,5, Ludwig Kappos^3,4, Jens Kuhle^3,4, Alessandro Daducci¹, and Cristina Granziera^2,3,4
1Department of Computer Science, University of Verona, Verona, Italy, ²Departments of Medicine, Clinical Research and Biomedical Engineering, Neurology, University Hospital Basel and University of Basel, Basel, Switzerland, ³Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Neurologic Clinic and Policlinic, Translational Imaging in Neurology (ThINk), Basel, Switzerland, ⁴Research Center for Clinical Neuroimmunology and Neuroscience, Basel, Switzerland, ⁵Department of Radiology, Division of Radiological Physics, University Hospital Basel, Basel, Switzerland

Graph measures derived from structural connectomes are widely used to study neurodegenerative diseases such as multiple sclerosis (MS). Usually, the connection strength is assessed by counting the number of streamlines connecting pairs of grey-matter regions. Here we used different ways to weight the edges to compare the sensitivity to MS structural disruptions of three diffusion-based microstructural models and their derived maps combined with network analysis. We found that the most sensitive are those whose derived maps are associated to intra-axonal signal fraction. Moreover, the segregation of the network appeared to be the most important in explaining clinical motor disability.

Jianpan Huang¹, Jiadi Xu^2,3, Joseph H. C. Lai¹, Henry K. F. Mak⁴, Koon Ho Chan⁵, and Kannie W. Y. Chan^1,3,6
1Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States, ³Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁴Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China, ⁵Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China, ⁶City University of Hong Kong Shenzhen Research Institute, Shenzhen, China

Multiple sclerosis (MS) is demyelinating disease of the central nervous system (CNS), which affects more than two million people globally. Here we applied our optimized pulsed-CEST MRI method to acquire relayed nuclear Overhauser effect weighted (rNOEw) images for detecting the pathology changes regarding myelin lipid/protein in human brain with neuromyelitis optica (NMO) and MS on clinical 3T scanner. We found that rNOEw signal of MS brains was significantly lower than that of NMO and NC brains. Our proposed rNOEw imaging method has great potential to assist MS diagnosis and specifically identify MS patients from NMO patients.