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1. Ambroxol as a disease-modifying treatment to reduce the risk of cognitive impairment in GBA-associated Parkinson’s disease: a multicentre, randomised, double-blind, placebo-controlled, phase II trial. The AMBITIOUS study protocol

Author

Matteo Gastaldi, Diego Franciotta, Mario Cirillo, Sara Prioni, Micol Avenali, Fabrizio Esposito, Chiara Reale, Valentina Leta, Enza Maria Valente, Anna Pichiecchio, Barbara Garavaglia, Roberto Eleopra, Marina Grisoli, Roberto Cilia, Luigi Romito, Maria Grazia Bruzzone, Alessandro Tessitore, Ilaria Palmieri, Giada Cuconato, Fabiana Colucci, Pierfrancesco Mitrotti, Rosita De Micco, Marco Fusar Poli, Silvia Cerri, Mario Stanziano, Ana Bacila, Valentina Franco, Cristina Ghezzi, Antonio Emanuele Elia, Grazia Devigili, Nico Golfrè Andreasi, Federico Cazzaniga, Caterina Galandra, Giancarlo Germani, Gerardo Ongari, Marta Picascia, Mattia Verri, Federica Di Nardo, Simone Aloisio, Mattia Siciliano, Paolo Amami, Sylvie Piacentini, and Fabio Moda

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Background Heterozygous mutations in the GBA gene, encoding the lysosomal enzyme β-glucocerebrosidase (GCase), are the most frequent genetic risk factor for Parkinson’s disease (PD). GBA-related PD (GBA-PD) patients have higher risk of dementia and reduced survival than non-carriers. Preclinical studies and one open-label trial in humans demonstrated that the chaperone ambroxol (ABX) increases GCase levels and modulates α-synuclein levels in the blood and cerebrospinal fluid (CSF).Methods and analysis In this multicentre, double-blind, placebo-controlled, phase II clinical trial, we randomise patients with GBA-PD in a 1:1 ratio to either oral ABX 1.2 g/day or placebo. The duration of treatment is 52 weeks. Each participant is assessed at baseline and weeks 12, 26, 38, 52 and 78. Changes in the Montreal Cognitive Assessment score and the frequency of mild cognitive impairment and dementia between baseline and weeks 52 are the primary outcome measures. Secondary outcome measures include changes in validated scales/questionnaires assessing motor and non-motor symptoms. Neuroimaging features and CSF neurodegeneration markers are used as surrogate markers of disease progression. GCase activity, ABX and α-synuclein levels are also analysed in blood and CSF. A repeated-measures analysis of variance will be used for elaborating results. The primary analysis will be by intention to treat.Ethics and dissemination The study and protocols have been approved by the ethics committee of centres. The study is conducted according to good clinical practice and the Declaration of Helsinki. The trial findings will be published in peer-reviewed journals and presented at conferences.Trial registration numbers NCT05287503, EudraCT 2021-004565-13.

Published
2023
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2. Dynamic magnetic resonance imaging of muscle contraction in facioscapulohumeral muscular dystrophy

Author

Xeni Deligianni, Francesco Santini, Matteo Paoletti, Francesca Solazzo, Niels Bergsland, Giovanni Savini, Arianna Faggioli, Giancarlo Germani, Mauro Monforte, Enzo Ricci, Giorgio Tasca, and Anna Pichiecchio

Subjects
Medicine, Science
Abstract

Abstract Quantitative muscle MRI (water-T2 and fat mapping) is being increasingly used to assess disease involvement in muscle disorders, while imaging techniques for assessment of the dynamic and elastic muscle properties have not yet been translated into clinics. In this exploratory study, we quantitatively characterized muscle deformation (strain) in patients affected by facioscapulohumeral muscular dystrophy (FSHD), a prevalent muscular dystrophy, by applying dynamic MRI synchronized with neuromuscular electrical stimulation (NMES). We evaluated the quadriceps muscles in 34 ambulatory patients and 13 healthy controls, at 6-to 12-month time intervals. While a subgroup of patients behaved similarly to controls, for another subgroup the median strain decreased over time (approximately 57% over 1.5 years). Dynamic MRI parameters did not correlate with quantitative MRI. Our results suggest that the evaluation of muscle contraction by NMES-MRI is feasible and could potentially be used to explore the elastic properties and monitor muscle involvement in FSHD and other neuromuscular disorders.

Published
2022
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3. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Author

Julien Cohen-Adad, Eva Alonso-Ortiz, Mihael Abramovic, Carina Arneitz, Nicole Atcheson, Laura Barlow, Robert L. Barry, Markus Barth, Marco Battiston, Christian Büchel, Matthew Budde, Virginie Callot, Anna J. E. Combes, Benjamin De Leener, Maxime Descoteaux, Paulo Loureiro de Sousa, Marek Dostál, Julien Doyon, Adam Dvorak, Falk Eippert, Karla R. Epperson, Kevin S. Epperson, Patrick Freund, Jürgen Finsterbusch, Alexandru Foias, Michela Fratini, Issei Fukunaga, Claudia A. M. Gandini Wheeler-Kingshott, Giancarlo Germani, Guillaume Gilbert, Federico Giove, Charley Gros, Francesco Grussu, Akifumi Hagiwara, Pierre-Gilles Henry, Tomáš Horák, Masaaki Hori, James Joers, Kouhei Kamiya, Haleh Karbasforoushan, Miloš Keřkovský, Ali Khatibi, Joo-Won Kim, Nawal Kinany, Hagen H. Kitzler, Shannon Kolind, Yazhuo Kong, Petr Kudlička, Paul Kuntke, Nyoman D. Kurniawan, Slawomir Kusmia, René Labounek, Maria Marcella Laganà, Cornelia Laule, Christine S. Law, Christophe Lenglet, Tobias Leutritz, Yaou Liu, Sara Llufriu, Sean Mackey, Eloy Martinez-Heras, Loan Mattera, Igor Nestrasil, Kristin P. O’Grady, Nico Papinutto, Daniel Papp, Deborah Pareto, Todd B. Parrish, Anna Pichiecchio, Ferran Prados, Àlex Rovira, Marc J. Ruitenberg, Rebecca S. Samson, Giovanni Savini, Maryam Seif, Alan C. Seifert, Alex K. Smith, Seth A. Smith, Zachary A. Smith, Elisabeth Solana, Y. Suzuki, George Tackley, Alexandra Tinnermann, Jan Valošek, Dimitri Van De Ville, Marios C. Yiannakas, Kenneth A. Weber II, Nikolaus Weiskopf, Richard G. Wise, Patrik O. Wyss, and Junqian Xu

Subjects
Science
Abstract

Measurement(s) spinal cord Technology Type(s) magnetic resonance imaging Factor Type(s) manufacturer • site Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Canada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14052269

Published
2021
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4. Pilot Study on Quantitative Cervical Cord and Muscular MRI in Spinal Muscular Atrophy: Promising Biomarkers of Disease Evolution and Treatment?

Author

Giovanni Savini, Carlo Asteggiano, Matteo Paoletti, Stefano Parravicini, Elena Pezzotti, Francesca Solazzo, Shaun I. Muzic, Francesco Santini, Xeni Deligianni, Alice Gardani, Giancarlo Germani, Lisa M. Farina, Niels Bergsland, Claudia A. M. Gandini Wheeler-Kingshott, Angela Berardinelli, Stefano Bastianello, and Anna Pichiecchio

Subjects
spinal muscular atrophy, muscle MRI, nusinersen (spinraza), motor neuron degeneration, spinal cord atrophy and degeneration, muscle fat fraction, Neurology. Diseases of the nervous system, RC346-429
Abstract

Introduction: Nusinersen is a recent promising therapy approved for the treatment of spinal muscular atrophy (SMA), a rare disease characterized by the degeneration of alpha motor neurons (αMN) in the spinal cord (SC) leading to progressive muscle atrophy and dysfunction. Muscle and cervical SC quantitative magnetic resonance imaging (qMRI) has never been used to monitor drug treatment in SMA. The aim of this pilot study is to investigate whether qMRI can provide useful biomarkers for monitoring treatment efficacy in SMA.Methods: Three adult SMA 3a patients under treatment with nusinersen underwent longitudinal clinical and qMRI examinations every 4 months from baseline to 21-month follow-up. The qMRI protocol aimed to quantify thigh muscle fat fraction (FF) and water-T2 (w-T2) and to characterize SC volumes and microstructure. Eleven healthy controls underwent the same SC protocol (single time point). We evaluated clinical and imaging outcomes of SMA patients longitudinally and compared SC data between groups transversally.Results: Patient motor function was stable, with only Patient 2 showing moderate improvements. Average muscle FF was already high at baseline (50%) and progressed over time (57%). w-T2 was also slightly higher than previously published data at baseline and slightly decreased over time. Cross-sectional area of the whole SC, gray matter (GM), and ventral horns (VHs) of Patients 1 and 3 were reduced compared to controls and remained stable over time, while GM and VHs areas of Patient 2 slightly increased. We found altered diffusion and magnetization transfer parameters in SC structures of SMA patients compared to controls, thus suggesting changes in tissue microstructure and myelin content.Conclusion: In this pilot study, we found a progression of FF in thigh muscles of SMA 3a patients during nusinersen therapy and a concurrent slight reduction of w-T2 over time. The SC qMRI analysis confirmed previous imaging and histopathological studies suggesting degeneration of αMN of the VHs, resulting in GM atrophy and demyelination. Our longitudinal data suggest that qMRI could represent a feasible technique for capturing microstructural changes induced by SMA in vivo and a candidate methodology for monitoring the effects of treatment, once replicated on a larger cohort.

Published
2021
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5. Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Author

Julien Cohen-Adad, Eva Alonso-Ortiz, Mihael Abramovic, Carina Arneitz, Nicole Atcheson, Laura Barlow, Robert L. Barry, Markus Barth, Marco Battiston, Christian Büchel, Matthew Budde, Virginie Callot, Anna J. E. Combes, Benjamin De Leener, Maxime Descoteaux, Paulo Loureiro de Sousa, Marek Dostál, Julien Doyon, Adam Dvorak, Falk Eippert, Karla R. Epperson, Kevin S. Epperson, Patrick Freund, Jürgen Finsterbusch, Alexandru Foias, Michela Fratini, Issei Fukunaga, Claudia A. M. Gandini Wheeler-Kingshott, Giancarlo Germani, Guillaume Gilbert, Federico Giove, Charley Gros, Francesco Grussu, Akifumi Hagiwara, Pierre-Gilles Henry, Tomáš Horák, Masaaki Hori, James Joers, Kouhei Kamiya, Haleh Karbasforoushan, Miloš Keřkovský, Ali Khatibi, Joo-Won Kim, Nawal Kinany, Hagen H. Kitzler, Shannon Kolind, Yazhuo Kong, Petr Kudlička, Paul Kuntke, Nyoman D. Kurniawan, Slawomir Kusmia, René Labounek, Maria Marcella Laganà, Cornelia Laule, Christine S. Law, Christophe Lenglet, Tobias Leutritz, Yaou Liu, Sara Llufriu, Sean Mackey, Eloy Martinez-Heras, Loan Mattera, Igor Nestrasil, Kristin P. O’Grady, Nico Papinutto, Daniel Papp, Deborah Pareto, Todd B. Parrish, Anna Pichiecchio, Ferran Prados, Àlex Rovira, Marc J. Ruitenberg, Rebecca S. Samson, Giovanni Savini, Maryam Seif, Alan C. Seifert, Alex K. Smith, Seth A. Smith, Zachary A. Smith, Elisabeth Solana, Y. Suzuki, George Tackley, Alexandra Tinnermann, Jan Valošek, Dimitri Van De Ville, Marios C. Yiannakas, Kenneth A. Weber II, Nikolaus Weiskopf, Richard G. Wise, Patrik O. Wyss, and Junqian Xu

Subjects
Science
Published
2021
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6. Specific Patterns of White Matter Alterations Help Distinguishing Alzheimer's and Vascular Dementia

Author

Fulvia Palesi, Andrea De Rinaldis, Paolo Vitali, Gloria Castellazzi, Letizia Casiraghi, Giancarlo Germani, Sara Bernini, Nicoletta Anzalone, Matteo Cotta Ramusino, Federica M. Denaro, Elena Sinforiani, Alfredo Costa, Giovanni Magenes, Egidio D'Angelo, Claudia A. M. Gandini Wheeler-Kingshott, and Giuseppe Micieli

Subjects
Alzheimer's disease, vascular dementia, DTI, splenium of corpus callosum, genu of corpus callosum, parahippocampal gyri, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls—HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.

Published
2018
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7. Variable echo time imaging for detecting the short T2* components of the sciatic nerve: a validation study

Author

Oliver Bieri, Francesco Santini, Giancarlo Germani, Matteo Paoletti, Paolo Florent Felisaz, Xeni Deligianni, Andrea Cortese, Niels Bergsland, Eugenio Belatti, Stefano Bastianello, Anna Pichiecchio, Elisa Vegezzi, and Francesca Solazzo

Subjects
Adult, Male, Biophysics, Thigh, 030218 nuclear medicine & medical imaging, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Peripheral nerves, Reproducibility, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Echo time, Echo (computing), Reproducibility of Results, Validation study, Magnetic resonance imaging, Repeatability, Middle Aged, Short t2, Magnetic Resonance Imaging, Sciatic Nerve, Fibrosis, medicine.anatomical_structure, Female, Sciatic nerve, business, Nuclear medicine, 030217 neurology & neurosurgery, Research Article
Abstract

Objective The aim of this study was to develop and validate an MRI protocol based on a variable echo time (vTE) sensitive to the short T2* components of the sciatic nerve. Materials and methods 15 healthy subjects (M/F: 9/6; age: 21–62) were scanned at 3T targeting the sciatic nerve at the thigh bilaterally, using a dual echo variable echo time (vTE) sequence (based on a spoiled gradient echo acquisition) with echo times of 0.98/5.37 ms. Apparent T2* (aT2*) values of the sciatic nerves were calculated with a mono-exponential fit and used for data comparison. Results There were no significant differences in aT2* related to side, sex, age, and BMI, even though small differences for side were reported. Good-to-excellent repeatability and reproducibility were found for geometry of ROIs (Dice indices: intra-rater 0.68–0.7; inter-rater 0.70–0.72) and the related aT2* measures (intra-inter reader ICC 0.95–0.97; 0.66–0.85) from two different operators. Side-related signal-to-noise-ratio non-significant differences were reported, while contrast-to-noise-ratio measures were excellent both for side and echo. Discussion Our study introduces a novel MR sequence sensitive to the short T2* components of the sciatic nerve and may be used for the study of peripheral nerve disorders.

Published
2020
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8. Substantia Nigra Volumetry with 3-T MRI in De Novo and Advanced Parkinson Disease

Author

Giancarlo Germani, Arianna Faggioli, Roberta Zangaglia, Marina I Pan, Paolo Vitali, Fulvia Palesi, Claudio Pacchetti, Pietro Francaviglia, Brigida Minafra, Claudia A. M. Wheeler-Kingshott, Nicoletta Anzalone, Vitali, P., Pan, M. I., Palesi, F., Germani, G., Faggioli, A., Anzalone, N., Francaviglia, P., Minafra, B., Zangaglia, R., Pacchetti, C., and Wheeler-Kingshott, C. A. M. G.

Subjects
Male, business.industry, Parkinson Disease, Substantia nigra, Mean age, Disease, Middle Aged, Magnetic Resonance Imaging, Volumetric measurement, Mean difference, Substantia Nigra, Clinical diagnosis, Healthy control, Humans, Medicine, Female, Radiology, Nuclear Medicine and imaging, Prospective Studies, Nuclear medicine, business, Prospective cohort study, Aged
Abstract

Background Magnetization transfer-prepared T1-weighted MRI can depict a hyperintense subregion of the substantia nigra involved in the degeneration process of Parkinson disease. Purpose To evaluate quantitative measurement of substantia nigra volume by using MRI to support clinical diagnosis and staging of Parkinson disease. Materials and Methods In this prospective study, a high-spatial-resolution magnetization transfer-prepared T1-weighted volumetric sequence was performed with a 3-T MRI machine between January 2014 and October 2015 for participants with de novo Parkinson disease, advanced Parkinson disease, and healthy control participants. A reproducible semiautomatic quantification analysis method that entailed mesencephalic intensity as an internal reference was used for hyperintense substantia nigra volumetry normalized to intracranial volume. A general linear model with age and sex as covariates was used to compare the three groups. Results Eighty participants were evaluated: 20 healthy control participants (mean age ± standard deviation, 56 years ± 11; 11 women), 29 participants with de novo Parkinson disease (64 years ± 10; 19 men), and 31 participants with advanced Parkinson disease (60 years ± 9; 16 women). Volumetric measurement of hyperintense substantia nigra from magnetization transfer-prepared T1-weighted MRI helped differentiate healthy control participants from participants with advanced Parkinson disease (mean difference for ipsilateral side, 64 mm3 ± 14, P < .001; mean difference for contralateral side, 109 mm3 ± 14, P < .001) and helped distinguish healthy control participants from participants with de novo Parkinson disease (mean difference for ipsilateral side, 45 mm3 ± 15, P < .01; mean difference for contralateral side, 66 mm3 ± 15, P < .001) and participants with de novo Parkinson disease from those with advanced Parkinson disease (mean difference for ipsilateral side, 20 mm3 ± 13, P = .40; mean difference for contralateral side, 43 mm3 ± 13, P = .004). Conclusion Magnetization transfer-prepared T1-weighted MRI volumetry of the substantia nigra helped differentiate the stages of Parkinson disease. © RSNA, 2020 Online supplemental material is available for this article.

Published
2020
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9. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Author

Alexandra Tinnermann, Dimitri Van De Ville, Cornelia Laule, Sean Mackey, Robert L. Barry, Benjamin De Leener, Anna Pichiecchio, Eva Alonso-Ortiz, Giancarlo Germani, Ali Khatibi, Nico Papinutto, Marc J. Ruitenberg, René Labounek, Nawal Kinany, Francesco Grussu, Michela Fratini, Petr Kudlička, Christophe Lenglet, Kouhei Kamiya, Pierre-Gilles Henry, Julien Cohen-Adad, Richard G. Wise, Deborah Pareto, Tomáš Horák, Jürgen Finsterbusch, Alex Rovira, Todd B. Parrish, Y. Suzuki, George Tackley, Junqian Xu, Falk Eippert, Virginie Callot, Daniel Papp, Laura Barlow, Karla R. Epperson, Charley Gros, Nicole Atcheson, Akifumi Hagiwara, Jan Valošek, Yaou Liu, Patrick Freund, Maria Marcella Laganà, James M. Joers, Marco Battiston, Markus Barth, Adam V. Dvorak, Masaaki Hori, Joo Won Kim, Miloš Keřkovský, Paulo Loureiro de Sousa, Sara Llufriu, Mihael Abramovic, Igor Nestrasil, Kenneth A. Weber, Christine S. Law, Paul Kuntke, Elisabeth Solana, Kristin P. O’Grady, Alexandru Foias, Slawomir Kusmia, Claudia A. M. Wheeler-Kingshott, Hagen H. Kitzler, Alex K. Smith, Nyoman D. Kurniawan, Shannon H. Kolind, Marios C. Yiannakas, Seth A. Smith, Zachary A. Smith, Federico Giove, Tobias Leutritz, Matthew D. Budde, Rebecca S. Samson, Christian Büchel, Kevin S. Epperson, Marek Dostál, Giovanni Savini, Issei Fukunaga, Haleh Karbasforoushan, Loan Mattera, Nikolaus Weiskopf, Guillaume Gilbert, Yazhuo Kong, Ferran Prados, Maryam Seif, Anna J.E. Combes, Julien Doyon, P Wyss, Alan C. Seifert, Carina Arneitz, Eloy Martinez-Heras, Maxime Descoteaux, Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Universitat Oberta de Catalunya (UOC), Universitat Oberta de Catalunya. eHealth Center, Institut Català de la Salut, [Cohen-Adad J] NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada. Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada. Mila - Quebec AI Institute, Montreal, QC, Canada. [Alonso-Ortiz E] NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada. [Abramovic M, Arneitz C] Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland. [Atcheson N] Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia. [Barlow L] Department of Radiology, University of British Columbia, Vancouver, BC, Canada. [Grussu F] NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK. Radiomics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain. Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Pareto D, Rovira À] Secció de Neuroradiologia, Vall d’Hebron Hospital Universitri, Barcelona, Spain, Vall d'Hebron Barcelona Hospital Campus, Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM] (CEMEREM), Hôpital de la Timone [CHU - APHM] (TIMONE)-Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Statistics and Probability, Data Descriptor, medicine.medical_specialty, Sciences du Vivant [q-bio]/Neurosciences [q-bio.NC], Investigació - Avaluació, Nervous System::Central Nervous System::Spinal Cord [ANATOMY], databases, Computer science, Science, of-the-art, Spinal cord diseases, Spinal Cord Diseases, Imaging techniques, Library and Information Sciences, 030218 nuclear medicine & medical imaging, Education, Databases, 03 medical and health sciences, 0302 clinical medicine, Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT], Investigative Techniques::Epidemiologic Methods::Epidemiologic Research Design::Reproducibility of Results [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT], medicine, Medical physics, diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], Other subheadings::Other subheadings::/diagnostic imaging [Other subheadings], Protocol (science), Reproducibility, Extramural, Otros calificadores::Otros calificadores::/diagnóstico por imagen [Otros calificadores], técnicas de investigación::métodos epidemiológicos::diseño de la investigación epidemiológica::reproducibilidad de los resultados [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], white, Spinal cord, spinal cord diseases, Toolbox, imaging techniques, matter, Computer Science Applications, magnetization-transfer, medicine.anatomical_structure, Imatgeria per ressonància magnètica, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], sistema nervioso::sistema nervioso central::médula espinal [ANATOMÍA], Statistics, Probability and Uncertainty, Medul·la espinal - Malalties - Imatgeria, 030217 neurology & neurosurgery, Information Systems
Abstract

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord., Measurement(s)spinal cordTechnology Type(s)magnetic resonance imagingFactor Type(s)manufacturer • siteSample Characteristic - OrganismHomo sapiensSample Characteristic - LocationCanada • Switzerland • Australia • United States of America • United Kingdom • Germany • French Republic • Czech Republic • Italy • Japan • Kingdom of Spain • China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14052269

Published
2021
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10. Impact of the inversion time on regional brain perfusion estimation with clinical arterial spin labeling protocols

Author

Giancarlo Germani, Elisa Rognone, Renato Borgatti, Claudia A. M. Wheeler-Kingshott, Fulvia Palesi, Francesco Sanvito, Leonardo Barzaghi, Ludovica Pasca, Valentina De Giorgis, and Anna Pichiecchio

Subjects
Radiological and Ultrasound Technology, Adolescent, business.industry, Biophysics, Brain, Transit time, Perfusion scanning, Inversion Time, Arteries, Grey matter, Insular cortex, Magnetic Resonance Imaging, Perfusion, medicine.anatomical_structure, Cerebral blood flow, Cerebrovascular Circulation, Arterial spin labeling, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Spin Labels, business, Nuclear medicine, Child
Abstract

Objective Evaluating the impact of the Inversion Time (TI) on regional perfusion estimation in a pediatric cohort using Arterial Spin Labeling (ASL). Materials and methods Pulsed ASL (PASL) was acquired at 3 T both at TI 1500 ms and 2020 ms from twelve MRI-negative patients (age range 9–17 years). A volume of interest (VOIs) and a voxel-wise approach were employed to evaluate subject-specific TI-dependent Cerebral Blood Flow (CBF) differences, and grey matter CBF Z-score differences. A visual evaluation was also performed. Results CBF was higher for TI 1500 ms in the proximal territories of the arteries (PTAs) (e.g. insular cortex and basal ganglia — P P P P Z-scores and at a visual inspection. Conclusions TI influences ASL perfusion estimates with a region-dependent effect. The presence of intraluminal arterial signal in PTAs and the longer arterial transit time in the DTAs (including watershed areas) may account for the TI-dependent differences. Watershed areas exhibiting a lower perfusion signal at short TIs (~ 1500 ms) should not be misinterpreted as focal hypoperfused areas.

Published
2021

11. White matter microstructure characterisation in temporal lobe epilepsy

Author

Paul Summers, Fulvia Palesi, Elena Tartara, Isabella Giachetti, Claudia Am Gandini Wheeler-Kingshott, Laura Tassi, Egidio D'Angelo, Nicolò Rolandi, Paolo Vitali, Valeria Mariani, Francesco Padelli, Domenico Aquino, and Giancarlo Germani

Subjects
business.industry, Brain tract, Anatomy, medicine.disease, behavioral disciplines and activities, White matter microstructure, nervous system diseases, Temporal lobe, White matter, Epilepsy, medicine.anatomical_structure, nervous system, Kurtosis, Medicine, In patient, business, psychological phenomena and processes, Diffusion MRI
Abstract

Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy. Parameters of microstructural abnormalities derived from diffusion tensor imaging(DTI) have been reported to be helpful in differentiating between Left and Right TLE (L-TLE and R-TLE) but few of them compared L-TLE and R-TLE with a voxelwise approach. In this study, a whole brain tract based spatial statistical analysis was performed on DTI, diffusion kurtosis and NODDI derived parameters of 88 subjects to identify specific white matter patterns of alteration in patient affected by L-TLE and R-TLE with respect to healthy controls. Our findings demonstrated the presence of specific patterns of white matter alterations, with L-TLE more widely affected both in cerebral and cerebellar regions. This result supports the need to consider patients separately, according to the side of their pathology.

Published
2021
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12. Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Author

Ferran Prados, Alex Rovira, Ali Khatibi, Nico Papinutto, George Tackley, Maria Marcella Laganà, Akifumi Hagiwara, Kristin P. O’Grady, René Labounek, Nawal Kinany, Joo Won Kim, Loan Mattera, Christine S. Law, Seth A. Smith, Daniel Papp, Todd B. Parrish, Julien Cohen-Adad, Robert L. Barry, Nyoman D. Kurniawan, Sara Llufriu, Giancarlo Germani, Slawomir Kusmia, Miloš Keřkovský, Eloy Martinez-Heras, Matthew D. Budde, Richard G. Wise, Claudia A. M. Wheeler-Kingshott, P Wyss, Rebecca S. Samson, Karla R. Epperson, Y. Suzuki, Haleh Karbasforoushan, Issei Fukunaga, Igor Nestrasil, Virginie Callot, Maxime Descoteaux, Yazhuo Kong, Paul Kuntke, Kenneth A. Weber, Alexandru Foias, Marco Battiston, Hagen H. Kitzler, Charley Gros, Giovanni Savini, Michela Fratini, Guillaume Gilbert, Alan C. Seifert, Anna J.E. Combes, Carina Arneitz, Julien Doyon, Tobias Leutritz, Zachary A. Smith, Laura Barlow, James M. Joers, Kevin S. Epperson, Pierre-Gilles Henry, Markus Barth, Francesco Grussu, Deborah Pareto, Christophe Lenglet, Jürgen Finsterbusch, Shannon H. Kolind, Christian Büchel, Sean Mackey, Marios C. Yiannakas, Petr Kudlička, Mihael Abramovic, Benjamin De Leener, Elisabeth Solana, Anna Pichiecchio, Eva Alonso-Ortiz, Nikolaus Weiskopf, Kouhei Kamiya, Alexandra Tinnermann, Jan Valošek, Patrick Freund, Junqian Xu, Marek Dostál, Dimitri Van De Ville, Alex K. Smith, Federico Giove, Marc J. Ruitenberg, Falk Eippert, Nicole Atcheson, Paulo Loureiro de Sousa, Tomáš Horák, Masaaki Hori, Yaou Liu, Maryam Seif, Adam V. Dvorak, and Cornelia Laule

Subjects
Adult, Male, Statistics and Probability, Data descriptor, Science, MEDLINE, Spinal cord diseases, Neuroimaging, Spinal Cord Diseases, Imaging techniques, Library and Information Sciences, GeneralLiterature_MISCELLANEOUS, Education, Databases, Text mining, Image Processing, Computer-Assisted, Humans, Medicine, Author Correction, Reproducibility, business.industry, MT protocol, Reproducibility of Results, Spinal cord, Magnetic Resonance Imaging, Computer Science Applications, medicine.anatomical_structure, Spinal Cord, Female, Statistics, Probability and Uncertainty, business, Cartography, Information Systems
Abstract

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/ . The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.

Published
2021

13. Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy

Author

Anna Pichiecchio, Paolo Florent Felisaz, Xeni Deligianni, Giulia Colelli, Giancarlo Germani, Mauro Monforte, Matteo Paoletti, Elena Ballante, Silvia Figini, Enzo Ricci, Giorgio Tasca, Francesco Santini, Francesca Solazzo, Niels Bergsland, and Stefano Bastianello

Subjects
Texture (music), Machine learning, computer.software_genre, 030218 nuclear medicine & medical imaging, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Lasso regression, Medicine, Facioscapulohumeral muscular dystrophy, Humans, Radiology, Nuclear Medicine and imaging, Texture, Fat fraction, FSHD, business.industry, Disease progression, Thigh muscle, Water, General Medicine, medicine.disease, Magnetic Resonance Imaging, Muscular Dystrophy, Facioscapulohumeral, Random forest, Support vector machine, Settore MED/26 - NEUROLOGIA, Thigh, 030220 oncology & carcinogenesis, Muscle, Artificial intelligence, business, computer, MRI, Quantitative
Abstract

Purpose Quantitative MRI (qMRI) plays a crucial role for assessing disease progression and treatment response in neuromuscular disorders, but the required MRI sequences are not routinely available in every center. The aim of this study was to predict qMRI values of water T2 (wT2) and fat fraction (FF) from conventional MRI, using texture analysis and machine learning. Method Fourteen patients affected by Facioscapulohumeral muscular dystrophy were imaged at both thighs using conventional and quantitative MR sequences. Muscle FF and wT2 were calculated for each muscle of the thighs. Forty-seven texture features were extracted for each muscle on the images obtained with conventional MRI. Multiple machine learning regressors were trained to predict qMRI values from the texture analysis dataset. Results Eight machine learning methods (linear, ridge and lasso regression, tree, random forest (RF), generalized additive model (GAM), k-nearest-neighbor (kNN) and support vector machine (SVM) provided mean absolute errors ranging from 0.110 to 0.133 for FF and 0.068 to 0.115 for wT2. The most accurate methods were RF, SVM and kNN to predict FF, and tree, RF and kNN to predict wT2. Conclusion This study demonstrates that it is possible to estimate with good accuracy qMRI parameters starting from texture analysis of conventional MRI.

Published
2020

14. Intra- and Extracranial MR Venography: Technical Notes, Clinical Application, and Imaging Development

Author

Giancarlo Germani, Paolo Zamboni, Matteo Paoletti, Carlo Asteggiano, Stefano Bastianello, and R De Icco

Subjects
Diagnostic Imaging, medicine.medical_specialty, Article Subject, Socio-culturale, Neurosciences. Biological psychiatry. Neuropsychiatry, Magnetic resonance angiography, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Neuropsychology and Physiological Psychology, Neurology (clinical), Neurology, medicine, Medical imaging, Humans, Mr venography, Mri scan, medicine.diagnostic_test, Cerebrospinal fluid leak, Cerebrospinal Fluid Leak, business.industry, Magnetic resonance imaging, General Medicine, Phlebography, medicine.disease, Magnetic Resonance Imaging, Chronic cerebrospinal venous insufficiency, Venous Insufficiency, Flow quantification, Radiology, business, 030217 neurology & neurosurgery, Magnetic Resonance Angiography, RC321-571, Research Article
Abstract

Scientific debate over chronic cerebrospinal venous insufficiency (CCSVI) has drawn attention to venous system involvement in a series of pathologic brain conditions. In the last few decades, the MRI venography (MRV) field has developed a number of valuable sequences to better investigate structural anatomy, vessel patency, and flow characteristics of venous drainage in the intra- and extracranial systems. A brief two-tier protocol is proposed to encompass the study of intra- and extracranial venous drainage with and without contrast administration, respectively. Contrast-enhanced protocol is based on time-resolved contrast-enhanced MRV of the whole region plus extracranial flow quantification through 2D Cine phase contrast (PC); non-contrast-enhanced protocol includes intracranial 3D PC, extracranial 2D time of flight (TOF), and 2D Cine PC flow quantification. Total scanning time is reasonable for clinical applications: approximately seven minutes is allocated for the contrast protocol (most of which is due to 2D Cine PC), while the noncontrast protocol accounts for around twenty minutes. We believe that a short though exhaustive MRI scan of the whole intra- and extracranial venous drainage system can be valuable for a variety of pathologic conditions, given the possible venous implication in several neurological conditions.

Published
2016

15. Enzyme replacement therapy in adult-onset glycogenosis II: Is quantitative muscle MRI helpful?

Author

Alessandra Repetto, Sabrina Ravaglia, Giancarlo Germani, Eleonora Tavazzi, Michela Ponzio, Cesare Danesino, Arrigo Moglia, Stefano Bastianello, D Maranzana, Alfredo Costa, Anna Pichiecchio, and Gu Poloni

Subjects
medicine.medical_specialty, Pathology, Muscle mri, medicine.diagnostic_test, Physiology, business.industry, Adipose tissue, Magnetic resonance imaging, Enzyme replacement therapy, Surgery, Clinical trial, Cellular and Molecular Neuroscience, Physiology (medical), medicine, Neurology (clinical), business, Mri findings
Abstract

Although it has been shown that muscle magnetic resonance imaging (MRI) improves the phenotypic characterization of patients with neuromuscular disorders and allows accurate quantification of muscle and adipose tissue distribution, to date quantitative MRI has not been used to assess the therapeutic response in clinical trials of neuromuscular diseases. We discuss quantitative MRI findings after a 6-month course of enzyme replacement therapy administered to nine patients with adult-onset glycogenosis II.

Published
2009
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16. Spectroscopic magnetic resonance imaging of the brain: voxel localisation and tissue segmentation in the follow up of brain tumour

Author

Guy, Poloni, S, Bastianello, Angela, Vultaggio, S, Pozzi, Gloria, Maccabelli, Giancarlo, Germani, Patrizia, Chiarati, and Anna, Pichiecchio

Subjects
Adult, Male, Aspartic Acid, Magnetic Resonance Spectroscopy, Brain Neoplasms, Brain, Middle Aged, Creatine, Magnetic Resonance Imaging, Choline, Imaging, Three-Dimensional, Humans, Female, Protons, Algorithms, Aged, Follow-Up Studies
Abstract

The field of application of magnetic resonance spectroscopy (MRS) in biomedical research is expanding all the time and providing opportunities to investigate tissue metabolism and function. The data derived can be integrated with the information on tissue structure gained from conventional and non-conventional magnetic resonance imaging (MRI) techniques. Clinical MRS is also strongly expected to play an important role as a diagnostic tool. Essential for the future success of MRS as a clinical and research tool in biomedical sciences, both in vivo and in vitro, is the development of an accurate, biochemically relevant and physically consistent and reliable data analysis standard. Stable and well established analysis algorithms, in both the time and the frequency domain, are already available, as is free commercial software for implementing them. In this study, we propose an automatic algorithm that takes into account anatomical localisation, relative concentrations of white matter, grey matter, cerebrospinal fluid and signal abnormalities and inter-scan patient movement. The endpoint is the collection of a series of covariates that could be implemented in a multivariate analysis of covariance (MANCOVA) of the MRS data, as a tool for dealing with differences that may be ascribed to the anatomical variability of the subjects, to inaccuracies in the localisation of the voxel or slab, or to movement, rather than to the pathology under investigation. The aim was to develop an analysis procedure that can be consistently and reliably applied in the follow up of brain tumour. In this study, we demonstrate that the inclusion of such variables in the data analysis of quantitative MRS is fundamentally important (especially in view of the reduced accuracy typical of MRS measures compared to other MRI techniques), reducing the occurrence of false positives.

Published
2009

17. Generic acquisition protocol for quantitative MRI of the spinal cord

Author

René Labounek, Nawal Kinany, Michela Fratini, Laura Barlow, Markus Barth, P Wyss, Marco Battiston, Sean Mackey, Nyoman D. Kurniawan, Deborah Pareto, Kenneth A. Weber, Guillaume Gilbert, Robert L. Barry, Anna Pichiecchio, Eva Alonso-Ortiz, Matthew D. Budde, Mihael Abramovic, Alexandra Tinnermann, Giancarlo Germani, Dimitri Van De Ville, Falk Eippert, Anna J.E. Combes, Igor Nestrasil, Marios C. Yiannakas, Haleh Karbasforoushan, Julien Doyon, Cornelia Laule, Nicole Atcheson, Ali Khatibi, Nico Papinutto, Karla R. Epperson, Marek Dostál, Yazhuo Kong, Loan Mattera, Charley Gros, Paulo Loureiro de Sousa, Pierre-Gilles Henry, Alan C. Seifert, Richard G. Wise, Issei Fukunaga, Alexandru Foias, Shannon H. Kolind, Todd B. Parrish, Akifumi Hagiwara, Daniel Papp, Carina Arneitz, Virginie Callot, Christian Büchel, Maria Marcella Laganà, Tobias Leutritz, Slawomir Kusmia, Ferran Prados, Kevin S. Epperson, Marc J. Ruitenberg, Nikolaus Weiskopf, Kouhei Kamiya, Benjamin De Leener, Adam V. Dvorak, Giovanni Savini, Christine S. Law, Petr Kudlička, Paul Kuntke, Julien Cohen-Adad, Alex Rovira, Jan Valošek, Patrick Freund, George Tackley, Zachary A. Smith, Eloy Martinez-Heras, Maxime Descoteaux, Yaou Liu, Miloš Keřkovský, Joo Won Kim, Kristin P. O’Grady, Elisabeth Solana, Rebecca S. Samson, Junqian Xu, Alex K. Smith, Federico Giove, Maryam Seif, Claudia A. M. Wheeler-Kingshott, Tomáš Horák, James M. Joers, Francesco Grussu, Christophe Lenglet, Jürgen Finsterbusch, Sara Llufriu, Hagen H. Kitzler, Masaaki Hori, Yuichi Suzuki, Seth A. Smith, École Polytechnique de Montréal (EPM), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Mila - Quebec AI Institute, Swiss Paraplegic Research = Schweizer Paraplegiker-Stiftung, University of Queensland [Brisbane], University of British Columbia (UBC), Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), Massachusetts Institute of Technology (MIT), University College of London [London] (UCL), Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), Medical College of Wisconsin [Milwaukee] (MCW), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Vanderbilt University Medical Center [Nashville], Vanderbilt University [Nashville], CHU Sainte Justine [Montréal], Université de Sherbrooke (UdeS), Centre d'Imagerie Moléculaire de Sherbrooke, Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Masaryk University and University Hospital Brno, McGill University = Université McGill [Montréal, Canada], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Stanford University School of Medicine [CA, USA], Universität Zürich [Zürich] = University of Zurich (UZH), IRCCS Santa Lucia Foundation, Juntendo University School of Medicine [Tokyo, Japan], University of Pavia, IRCCS Mondino Foundation, Philips Healthcare [Markham], Museo Storico della Fisica e Centro di Studi e Ricerche 'Enrico Fermi', Roma, Vall d'Hebron University Hospital [Barcelona], Center for Magnetic Resonance Research [Minneapolis] (CMRR), University of Minnesota Medical School, University of Minnesota System-University of Minnesota System, Central European Institute of Technology [Brno] (CEITEC MU), Brno University of Technology [Brno] (BUT), Toho University Omori Medical Center [Tokyo], The University of Tokyo (UTokyo), Northwestern University Feinberg School of Medicine, Stanford University, University of Birmingham [Birmingham], Icahn School of Medicine at Mount Sinai [New York] (MSSM), Ecole Polytechnique Fédérale de Lausanne (EPFL), University of Geneva [Switzerland], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Chinese Academy of Sciences [Beijing] (CAS), University of Chinese Academy of Sciences [Beijing] (UCAS), University of Oxford [Oxford], University of Southern Queensland (USQ), Cardiff University, Epilepsy Society [Buckinghamshire] (MRI Unit), Departments of Ophthalmology and Pediatrics, University of Minnesota, Minneapolis, MN, University of Minnesota [Twin Cities] (UMN), University Hospital Olomouc [Czech Republic], Capital University of Medical Sciences [Beijing] (CUMS), Universitat de Barcelona (UB), University of California [San Francisco] (UCSF), University of California, Feinberg School of Medicine, Northwestern University [Evanston], Universitat Oberta de Catalunya [Barcelona] (UOC), University of Oklahoma Health Sciences Center (OUHSC), Palacky University Olomouc, Leipzig University, University 'G. d'Annunzio' of Chieti-Pescara [Chieti and Pescara, Italy], Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM] (CEMEREM), Hôpital de la Timone [CHU - APHM] (TIMONE)-Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Masaryk University [Brno] (MUNI), Università degli Studi di Pavia = University of Pavia (UNIPV), Enrico Fermi Center for Study and Research | Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Université de Genève = University of Geneva (UNIGE), University of Oxford, University of California [San Francisco] (UC San Francisco), University of California (UC), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), and Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Adult, Male, medicine.medical_specialty, Computer science, Neuroimaging, Article, General Biochemistry, Genetics and Molecular Biology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Image Processing, Computer-Assisted, medicine, Humans, NeuroPoly, Medical physics, health care economics and organizations, Protocol (science), medicine.diagnostic_test, technology, industry, and agriculture, Healthy subjects, Magnetic resonance imaging, Spinal cord, Magnetic Resonance Imaging, White matter microstructure, humanities, 3. Good health, Acquisition Protocol, medicine.anatomical_structure, Spinal Cord, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], 030217 neurology & neurosurgery, Diffusion MRI
Abstract

Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.

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