50 results on '"Guttmann, C. R. G."'
Search Results
2. Integrated Medical Image Registration, Patient Positioning, and Patient Monitoring for Cranial BNCT
- Author
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Palmer, M. R., Kiger, W. S., Zuo, C., Panych, L. P., Guttmann, C. R. G., Zamenhof, R. G., Busse, P. M., Hawthorne, M. Frederick, editor, Shelly, Kenneth, editor, and Wiersema, Richard J., editor
- Published
- 2001
- Full Text
- View/download PDF
3. Multiple sclerosis susceptibility loci do not alter clinical and MRI outcomes in clinically isolated syndrome
- Author
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Kalincik, T, Guttmann, C R G, Krasensky, J, Vaneckova, M, Lelkova, P, Tyblova, M, Seidl, Z, De Jager, P L, Havrdova, E, and Horakova, D
- Published
- 2013
- Full Text
- View/download PDF
4. Corrigendum: Perivascular Unit: This Must Be the Place. The Anatomical Crossroad Between the Immune, Vascular and Nervous System (Frontiers in Neuroanatomy, (2020), 14, 10.3389/fnana.2020.00017)
- Author
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Troili, F., Cipollini, V., Moci, M., Morena, E., Palotai, M., Rinaldi, V., Romano, C., Ristori, G., Giubilei, F., Salvetti, M., Orzi, F., Guttmann, C. R. G., and Cavallari, M.
- Subjects
amyloid ,aquaporin (AQP)-4 ,blood brain barrier (BBB) ,glymphatic system ,neurodegenaration ,neuroinflammation ,perivascular space (PVS) - Published
- 2020
5. Evidence of axonal damage in cerebellar peduncles without T2-lesions in multiple sclerosis
- Author
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Salem Hannoun, Kocevar, G., Durand-Dubief, F., Stamile, C., Naji, A., Cotton, F., Cavallari, M., Guttmann, C. R. G., Sappey-Marinier, D., RMN et optique : De la mesure au biomarqueur, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), American University of Beirut [Beyrouth] (AUB), Service de Neurologie à l'Hôpital neurologique de Lyon, Hôpital neurologique et neurochirurgical Pierre Wertheimer [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Département de Neuroradiologie [Centre Hospitalier Lyon Sud - HCL], Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Center for Neurological Imaging, Departments of Radiology and Neurology, Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)
- Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
- Published
- 2018
6. A distributed platform for making large scale manual reference datasets for MS lesion segmentation
- Author
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Damangir, S., de Sitter, A., Brouwer, I., Guttmann, C. R. G., Pareto, Deborah, Rovira, Alex, Barkhof, F., Vrenken, H., Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Neuroinfection & -inflammation, and CCA - Cancer biology and immunology
- Published
- 2018
7. Creating accurate reference segmentations of deep GM structures in MS patients by fast semi-automated outlining
- Author
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Sitter, A., Bartel, F., Palotai, M., Burggraaff, J., Liu, Y., Simoes, J., Ruggieri, S., Schregel, K., Pinzon, A. Morales, Ropele, S., Rocca, M. A., Gasperini, C., Gallo, A., Schoonheimm, M., Amann, M., Yiannakas, M., Wattjes, M. P., Sastre-Garriga, J., Kappos, L., Massimo Filippi, Enzinger, C., Ciccarelli, O., Frederiksen, J., Barkhof, F., Guttmann, C. R. G., Munck, J. C., Vrenken, H., Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Neurology, Medical psychology, Other Research, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Neuroinfection & -inflammation, CCA - Cancer biology and immunology, and Amsterdam Neuroscience - Neurovascular Disorders
- Published
- 2018
8. A Novel Nonrigid Registration Algorithm and Applications
- Author
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Rexilius, J., primary, Warfield, S. K., additional, Guttmann, C. R. G., additional, Wei, X., additional, Benson, R., additional, Wolfson, L., additional, Shenton, M., additional, Handels, H., additional, and Kikinis, R., additional
- Published
- 2001
- Full Text
- View/download PDF
9. A Longitudinal Study of Callosal Atrophy and Interhemispheric Dysfunction in Relapsing-Remitting Multiple Sclerosis
- Author
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Pelletier, J., Suchet, L., Witjas, T., Habib, M., Guttmann, C. R. G., Salamon, G., Lyon-Caen, O., and Chérif, A. Ali
- Published
- 2001
10. Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods.
- Author
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de Sitter, A., Visser, M., Brouwer, I., Cover, K. S., van Schijndel, R. A., Eijgelaar, R. S., Müller, D. M. J., Ropele, S., Kappos, L., Rovira, Á., Filippi, M., Enzinger, C., Frederiksen, J., Ciccarelli, O., Guttmann, C. R. G., Wattjes, M. P., Witte, M. G., de Witt Hamer, P. C., Barkhof, F., and Vrenken, H.
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FACE ,IMAGE analysis ,PRIVACY ,FAILURE analysis ,ALZHEIMER'S disease ,COMPUTERS in medicine ,BRAIN ,MULTIPLE sclerosis ,FERRANS & Powers Quality of Life Index ,RESEARCH evaluation ,ANTHROPOMETRY ,MAGNETIC resonance imaging ,GLIOMAS ,DIAGNOSTIC imaging ,MEDICAL ethics ,COMMUNICATION ,IMPACT of Event Scale ,RESEARCH funding ,NEURORADIOLOGY ,ALGORITHMS - Abstract
Background: Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants' privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups.Methods: FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer's Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired t tests.Results: Automated analysis methods failed in 0-19% of cases in FFR-processed images versus 0-2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (p = 0.003) and WMLV (p ≤ 0.001). GBV was lower after QuickShear and Defacing (both p < 0.001).Conclusions: All three outcome measures were affected differently by FFR, including failure of analysis methods and both "random" variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants' privacy.Key Points: • Protecting participants' privacy when sharing MRI data is important. • Impact of three facial features removal methods on subsequent analysis was assessed in three clinical groups. • Removing facial features degrades performance of image analysis methods. [ABSTRACT FROM AUTHOR]- Published
- 2020
- Full Text
- View/download PDF
11. New insight in perivenular lesion formation in multiple sclerosis on weekly susceptibility weighted images
- Author
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Mure, S., Guttmann, C. R. G., Grenier, T., Benoit-Cattin, H., Cotton, F., Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Center for Neurological Imaging, Departments of Radiology and Neurology, and RMN et optique : De la mesure au biomarqueur
- Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging - Abstract
International audience; In this paper, we take advantage of a unique longitudinal MRI dataset acquired at weekly intervals on untreated multiple sclerosis patients. We study the signal dynamics of relapsing-remitting multiple sclerosis lesions on SWI MRI and show, thanks to an unsupervised spatiotemporal clustering algorithm, that specific signal intensity behaviors exist between the veins and the lesions that are synchronous with contrast enhancement on gadolinium-enhanced T1-weighted MRI. Our study shows that vein narrowing depicted on SWI is an early event that appears to precede blood-brain barrier disruption signified by contrast-enhancement.
- Published
- 2016
12. Associations of global and regional white matter lesion load with anxiety and fatigue in multiple sclerosis
- Author
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Palotai, M., Mike, A., Cavallari, M., Strammer, E., Orsi, G., Illes, Z., and Guttmann, C. R. G.
- Published
- 2015
13. Lesion Effects on Cerebellar Peduncles DTI Metrics in MS Patients
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Salem Hannoun, Durand-Dubief, F., Ibarrola, D., Cavallari, C., Confavreux, C., Guttmann, C. R. G., Sappey Marinier, D., RMN et optique : De la mesure au biomarqueur, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Center for Neurological Imaging, and Departments of Radiology and Neurology
- Subjects
[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
- Published
- 2014
14. Lesions effects on cerebellar peduncles DTI metrics in MS patients
- Author
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Salem Hannoun, Sappey Marinier, D., Durand-Dubief, F., Ibarrola, D., Confavreux, C., Cavallari, C., Cotton, F., Guttmann, C. R. G., RMN et optique : De la mesure au biomarqueur, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Service de Radiologie, Hospices Civils de Lyon (HCL), Center for Neurological Imaging, and Departments of Radiology and Neurology
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[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
- Published
- 2013
15. Long-Interval T2-Weighted Subtraction Magnetic Resonance Imaging A Powerful New Outcome Measure in Multiple Sclerosis Trials
- Author
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Moraal, B., Den Elskamp, I. J., Knol, D. L., Bernard Uitdehaag, Geurts, J. J. G., Vrenken, H., Pouwels, P. J. W., Schijndel, R. A., Meier, D. S., Guttmann, C. R. G., Barkhof, F., Radiology and nuclear medicine, Epidemiology and Data Science, Neurology, Pathology, Anatomy and neurosciences, Physics and medical technology, NCA - Multiple Sclerosis and Other Neuroinflammatory Diseases, NCA - Neurodegeneration, Neuroscience Campus Amsterdam - Neurodegeneration, and Neuroscience Campus Amsterdam - Multiple Sclerosis and Other Neuroinflammatory Diseases
- Subjects
SDG 3 - Good Health and Well-being - Abstract
Objective: To compare long-interval T2-weighted subtraction (T2w-Sub) imaging with monthly gadolinium-enhanced. T1-weighted (Gd-T1w) imaging for (1) detection of active lesions, (2) assessment of treatment efficacy, and (3) statistical power, in a multiple sclerosis (MS), phase 2, clinical trial setting. Methods: Magnetic resonance imaging (MRI) data over 9 months from 120 patients (61 treatment, 59 placebo) from the oral temsirolimus trial were used. T2w-Sub images were scored for active lesions, independent of the original reading of the monthly Gd-T1w images. Treatment efficacy was evaluated using the nonparametric Mann-Whitney U test, and parametric negative binomial (NB)-regression and power calculations were conducted. Results: Datasets from 116 patients (58 treatment, 58 placebo) were evaluated. The mean number of T2w-Sub lesions in the treatment group was 3.0 (±4.6) versus 5.9 (±8.8) for placebo; the mean cumulative number of new Gd-T1w lesions in the treatment group was 5.5(±9.1) versus 9.1(±17.2) for placebo. T2w-Sub imaging showed increased power to assess treatment efficacy compared with Gd-T1w imaging, when evaluated by Mann-Whitney U test (p = 0.017 vs p = 0.177), or NB-regression without (p = 0.011 vs p = 0.092) or with baseline adjustment (p < 0.001 vs p = 0.002). Depending on the magnitude of the simulated treatment effect, sample size calculations showed reductions of 22 to 34% in the number of patients (translating into reductions of 81-83% in the number of MRI scans) needed to detect a significant treatment effect in favor of T2w-Sub imaging. Interpretation: Compared with monthly Gd-T1w imaging, long-interval T2w-Sub MRI exhibited increased power to assess treatment efficacy, and could greatly increase the cost-effectiveness of phase 2 MS trials by limiting the number of patients, contrast injections, and MRI scans needed. © 2010 American Neurological Association.
- Published
- 2010
16. MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information
- Author
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Milles, J., Zhu, Y. M., Gimenez, G., Guttmann, C. R. G., Magnin, I. E., Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Laboratoire Creatis, Compte Général
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[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing ,[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,[INFO.INFO-IM] Computer Science [cs]/Medical Imaging ,[SPI.MECA.MEFL] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] ,[SPI.MECA.MEMA] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph] ,[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] ,[PHYS.MECA.MEMA]Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph] ,[PHYS.MECA.MEMA] Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph] ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,[SPI.MECA.BIOM] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] ,[SPI.MECA.MEMA]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph] ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging ,[PHYS.MECA.MEFL] Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph] ,[PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph] ,[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing ,[SDV.IB] Life Sciences [q-bio]/Bioengineering ,[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph] ,[SPI.ACOU] Engineering Sciences [physics]/Acoustics [physics.class-ph] ,[PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Mechanics of the fluids [physics.class-ph] ,[PHYS.MECA.BIOM] Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph] ,[SPI.MECA.BIOM]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,[PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph] ,[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging ,[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV] ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation ,[PHYS.MECA.ACOU] Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph] ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
article
- Published
- 2007
17. Computation of Transmitted and Received B1 Fields in Magnetic Resonance Imaging
- Author
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Milles, J., Zhu, Y. M., Chen, N., Panych, L., Gimenez, G., Guttmann, C. R. G., Laboratoire Creatis, Compte Général, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing ,[INFO.INFO-IM] Computer Science [cs]/Medical Imaging ,[SPI.MECA.MEFL] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] ,[SPI.MECA.MEMA] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph] ,[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] ,[PHYS.MECA.MEMA]Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph] ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,[PHYS.MECA.MEMA] Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph] ,[SPI.MECA.BIOM] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] ,[SPI.MECA.MEMA]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph] ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging ,[PHYS.MECA.MEFL] Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph] ,[PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph] ,[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing ,[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph] ,[SDV.IB] Life Sciences [q-bio]/Bioengineering ,[SPI.ACOU] Engineering Sciences [physics]/Acoustics [physics.class-ph] ,[PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Mechanics of the fluids [physics.class-ph] ,[PHYS.MECA.BIOM] Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph] ,[SPI.MECA.BIOM]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,[PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph] ,[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging ,[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV] ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation ,[PHYS.MECA.ACOU] Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph] ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
article
- Published
- 2006
18. Rapid Buildup of Brain White Matter Hyperintensities Over 4 Years Linked to Ambulatory Blood Pressure, Mobility, Cognition, and Depression in Old Persons
- Author
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Wolfson, L., primary, Wakefield, D. B., additional, Moscufo, N., additional, Kaplan, R. F., additional, Hall, C. B., additional, Schmidt, J. A., additional, Guttmann, C. R. G., additional, and White, W. B., additional
- Published
- 2013
- Full Text
- View/download PDF
19. One year activity on subtraction MRI predicts subsequent 4 year activity and progression in multiple sclerosis
- Author
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Liguori, M., primary, Meier, D. S., additional, Hildenbrand, P., additional, Healy, B. C., additional, Chitnis, T., additional, Baruch, N. F., additional, Khoury, S. J., additional, Weiner, H. L., additional, Bakshi, R., additional, Barkhof, F., additional, and Guttmann, C. R. G., additional
- Published
- 2011
- Full Text
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20. Seasonal prevalence of MS disease activity
- Author
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Meier, D. S., primary, Balashov, K. E., additional, Healy, B., additional, Weiner, H. L., additional, and Guttmann, C. R. G., additional
- Published
- 2010
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21. HLA B*44: Protective effects in MS susceptibility and MRI outcome measures
- Author
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Healy, B. C., primary, Liguori, M., additional, Tran, D., additional, Chitnis, T., additional, Glanz, B., additional, Wolfish, C., additional, Gauthier, S., additional, Buckle, G., additional, Houtchens, M., additional, Stazzone, L., additional, Khoury, S., additional, Hartzmann, R., additional, Fernandez-Vina, M., additional, Hafler, D. A., additional, Weiner, H. L., additional, Guttmann, C. R. G., additional, and De Jager, P. L., additional
- Published
- 2010
- Full Text
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22. White matter abnormalities in mobility-impaired older persons
- Author
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Guttmann, C. R. G., primary, Benson, R., additional, Warfield, S. K., additional, Wei, X., additional, Anderson, M. C., additional, Hall, C. B., additional, Abu-Hasaballah, K., additional, Mugler, J. P., additional, and Wolfson, L., additional
- Published
- 2000
- Full Text
- View/download PDF
23. Serial Neuropsychological Assessment and Magnetic Resonance Imaging Analysis in Multiple Sclerosis
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Hohol, M. J., primary, Guttmann, C. R. G., additional, Orav, J., additional, Mackin, G. A., additional, Kikinis, R., additional, Khoury, S. J., additional, Jolesz, F. A., additional, and Weiner, H. L., additional
- Published
- 1997
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24. Triexponential decomposition of spin - lattice relaxation decay curves of paramagnetically doped red cell suspensions at 7 T
- Author
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Mulkern, R V, primary, Bowers, J L, additional, Heff, A, additional, Guttmann, C R G, additional, and Sadowski, R H, additional
- Published
- 1996
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25. Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis.
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Glanz, B. I., Holland, C. M., Gauthier, S. A., Amunwa, E. L., Liptak, Z., Houtchens, M. K., Sperling, R. A., Khoury, S. J., Guttmann, C. R. G., and Weiner, H. L.
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MULTIPLE sclerosis diagnosis ,MAGNETIC resonance imaging ,MEDICAL imaging systems ,VIRUS diseases ,COGNITION disorders - Abstract
Cognitive dysfunction is common in patients with multiple sclerosis (MS), and has been associated with MRI measures of lesion burden and atrophy. Little is known about the prevalence of cognitive impairment in patients with early MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course are also unclear. This study used a brief battery of cognitive tests to determine the prevalence and pattern of cognitive impairment in patients with clinically isolated syndromes or newly diagnosed MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course were also examined. Ninety-two patients with clinically isolated syndromes or the diagnosis of MS within the last 3 years participating in the CLIMB study underwent a neurologic examination, neuropsychological evaluation and MRI at 1.5T. Forty-nine percent of patients were impaired on one or more cognitive measures. There were no significant correlations between cognitive scores and MRI measures of disease severity including total T2 lesion volume, normal appearing white matter volume, grey matter volume, and brain parenchymal fraction. These findings suggest that cognitive impairment may predate the appearance of gross structural abnormalities on MRI and serve as an early marker of disease activity in MS. [ABSTRACT FROM AUTHOR]
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- 2007
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26. Older people with impaired mobility have specific loci of periventricular abnormality on MRI.
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Benson, R R, Guttmann, C R G, Wei, X, Warfield, S K, Hall, C, Schmidt, J A, Kikinis, R, and Wolfson, L I
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- 2002
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27. Multi-centre assessment of artificially generated MRI for cortical and juxtacortical multiple sclerosis lesion detection
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Bouman, P. M., Noteboom, S., Santos, F. A. Nobrega, Beck, E. S., Bliault, G., Marco Castellaro, Calabrese, M., Chard, D. T., Eichinger, P., Filippi, M., Inglese, M., Lapucci, C., Marciniak, A., Moraal, B., Pinzon, A. Moralez, Muehlau, M., Preziosa, P., Reich, D. S., Rocca, M. A., Schoonheim, M. M., Twisk, J. W., Wiestler, B., Jonkman, L. E., Guttmann, C. R. G., Geurts, J. J. G., and Steenwijk, M. D.
28. Regional magnetic resonance imaging lesion burden and cognitive function in multiple sclerosis: A longitudinal study
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Sperling, R. A., Guttmann, C. R. G., Hohol, M. J., Simon Warfield, Jakab, M., Parente, M., Diamond, E. L., Daffner, K. R., Olek, M. J., Orav, E. J., Kikinis, R., Jolesz, F. A., and Weiner, H. L.
29. Sensitive Detection of Caudate and Thalamic Alterations in Multiple Sclerosis Patients by Diffusion Tensor Imaging
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Sappey Marinier, D., Salem Hannoun, Durand-Dubief, F., Ibarrola, D., Confavreux, C., Guttmann, C. R. G., RMN et optique : De la mesure au biomarqueur, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Center for Neurological Imaging, and Departments of Radiology and Neurology
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[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,ComputingMilieux_MISCELLANEOUS - Abstract
International audience
30. Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods
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Jette L. Frederiksen, Mike P. Wattjes, Ana Rovira, Charles R.G. Guttmann, P. C. de Witt Hamer, I. Brouwer, R.A. van Schijndel, Hugo Vrenken, Marjolein Visser, Massimo Filippi, L Kappos, Marnix G. Witte, Olga Ciccarelli, Stefan Ropele, Frederik Barkhof, A. de Sitter, Keith S. Cover, Roelant S Eijgelaar, Alzheimer’s Disease Neuroimaging Initiative, Christian Enzinger, D. M. J. Müller, de Sitter, A, Visser, M, Brouwer, I, Cover, K S, van Schijndel, R A, Eijgelaar, R S, Müller, D M J, Ropele, S, Kappos, L, Rovira, Á, Filippi, M, Enzinger, C, Frederiksen, J, Ciccarelli, O, Guttmann, C R G, Wattjes, M P, Witte, M G, de Witt Hamer, P C, Barkhof, F, Vrenken, H, MAGNIMS Study Group and Alzheimer’s Disease Neuroimaging, Initiative, Rocca, M. A., Biophotonics and Medical Imaging, LaserLaB - Biophotonics and Microscopy, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, AGEM - Endocrinology, metabolism and nutrition, APH - Aging & Later Life, APH - Health Behaviors & Chronic Diseases, Neurosurgery, and Other Research
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Male ,medicine.medical_specialty ,Multiple Sclerosis ,Outcome measurements ,Neuroimaging ,030218 nuclear medicine & medical imaging ,Database ,03 medical and health sciences ,Magnetic resonance imaging ,0302 clinical medicine ,Alzheimer Disease ,Image Interpretation, Computer-Assisted ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Magnetic Resonance ,Ethic ,Analysis method ,Aged ,Neuroradiology ,Aged, 80 and over ,Ethics ,Lesion segmentation ,medicine.diagnostic_test ,Information Dissemination ,business.industry ,Outcome measures ,Brain ,Reproducibility of Results ,General Medicine ,Middle Aged ,medicine.disease ,Tumor Burden ,Privacy ,Face ,Female ,Radiology ,Glioblastoma ,business ,Algorithms ,Confidentiality ,030217 neurology & neurosurgery - Abstract
Background Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants’ privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups. Methods FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer’s Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired t tests. Results Automated analysis methods failed in 0–19% of cases in FFR-processed images versus 0–2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (p = 0.003) and WMLV (p ≤ 0.001). GBV was lower after QuickShear and Defacing (both p Conclusions All three outcome measures were affected differently by FFR, including failure of analysis methods and both “random” variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants’ privacy. Key Points • Protecting participants’ privacy when sharing MRI data is important. • Impact of three facial features removal methods on subsequent analysis was assessed in three clinical groups. • Removing facial features degrades performance of image analysis methods.
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- 2019
31. Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis: Towards accelerated semi-automated references
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Massimo Filippi, Jessica Burggraaff, Jette L. Frederiksen, Claudio Gasperini, Jaume Sastre-Garriga, Frederik Barkhof, Marios C. Yiannakas, Christian Enzinger, Mike P. Wattjes, Menno M. Schoonheim, Bernard M. J. Uitdehaag, Maria A. Rocca, Antonio Gallo, Serena Ruggieri, Deborah Pareto, Hugo Vrenken, Yaou Liu, Ludwig Kappos, Alexandra de Sitter, Michael Amann, Miklos Palotai, Charles R.G. Guttmann, Stefan Ropele, Jorge Simoes, Fabian Bartel, Katharina Schregel, Radiology and nuclear medicine, Neurology, Amsterdam Neuroscience - Neuroinfection & -inflammation, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Other Research, de Sitter, A., Burggraaff, J., Bartel, F., Palotai, M., Liu, Y., Simoes, J., Ruggieri, S., Schregel, K., Ropele, S., Rocca, M. A., Gasperini, C., Gallo, A., Schoonheim, M. M., Amann, M., Yiannakas, M., Pareto, D., Wattjes, M. P., Sastre-Garriga, J., Kappos, L., Filippi, M., Enzinger, C., Frederiksen, J., Uitdehaag, B., Guttmann, C. R. G., Barkhof, F., and Vrenken, H.
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Atrophy ,Deep grey matter ,MRI ,Multiple Sclerosis ,Reference set ,Segmentation ,Jaccard index ,Computer science ,Cognitive Neuroscience ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Reproducibility of Result ,Grey matter ,050105 experimental psychology ,03 medical and health sciences ,0302 clinical medicine ,Thalamus ,Multiple Sclerosi ,medicine ,Humans ,0501 psychology and cognitive sciences ,Radiology, Nuclear Medicine and imaging ,Gray Matter ,RC346-429 ,Thalamu ,Reliability (statistics) ,Protocol (science) ,Reproducibility ,business.industry ,Multiple sclerosis ,05 social sciences ,Reproducibility of Results ,Regular Article ,Pattern recognition ,medicine.disease ,Magnetic Resonance Imaging ,medicine.anatomical_structure ,Neurology ,Manual segmentation ,Neurology. Diseases of the nervous system ,Neurology (clinical) ,Artificial intelligence ,business ,030217 neurology & neurosurgery ,Human - Abstract
Background Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. Objectives This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). Methods A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. Results All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. Conclusions The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.
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- 2021
32. Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study
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Burggraaff, Jessica, Liu, Yao, Prieto, Juan C., Simoes, Jorge, de Sitter, Alexandra, Ruggieri, Serena, Brouwer, Iman, Lissenberg-Witte, Birgit I., Rocca, Mara A., Valsasina, Paola, Ropele, Stefan, Gasperini, Claudio, Gallo, Antonio, Pareto, Deborah, Sastre-Garriga, Jaume, Enzinger, Christian, Filippi, Massimo, De Stefano, Nicola, Ciccarelli, Olga, Hulst, Hanneke E., Wattjes, Mike P., Barkhof, Frederik, Uitdehaag, Bernard M. J., Vrenken, Hugo, Guttmann, Charles R. G., Universitat Autònoma de Barcelona, Neurology, Amsterdam Neuroscience - Neuroinfection & -inflammation, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Epidemiology and Data Science, Anatomy and neurosciences, Other Research, APH - Methodology, UCL - (SLuc) Centre du cancer, UCL - (SLuc) Service de chirurgie et transplantation abdominale, UCL - SSS/IREC/CHEX - Pôle de chirgurgie expérimentale et transplantation, Institut Català de la Salut, [Burggraaff J, Simoes J] Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. [Liu Y, de Sitter A] Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, De Boelelaan 1117, 1118, 1081 HV Amsterdam, The Netherlands. [Prieto JC] Center for Neurological Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 1249 Boylston Street, Boston, MA 02215, USA. [Ruggieri S] Department of Human Neurosciences, 'Sapienza' University of Rome, Piazzale Aldo Moro, 5, 00185 Roma RM, Italy. Department of Neurosciences, San Camillo Forlanini Hospital, Circonvallazione Gianicolense, 87, 00152 Roma RM, Italy. [Pareto D] Secció de Neuroradiologia, Unitat de Ressonància Magnètica, Departament de Radiologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. [Sastre-Garriga J] Servei de Neurologia, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain, Vall d'Hebron Barcelona Hospital Campus, Burggraaff, J., Liu, Y., Prieto, J. C., Simoes, J., de Sitter, A., Ruggieri, S., Brouwer, I., Lissenberg-Witte, B. I., Rocca, M. A., Valsasina, P., Ropele, S., Gasperini, C., Gallo, A., Pareto, D., Sastre-Garriga, J., Enzinger, C., Filippi, M., De Stefano, N., Ciccarelli, O., Hulst, H. E., Wattjes, M. P., Barkhof, F., Uitdehaag, B. M. J., Vrenken, H., and Guttmann, C. R. G.
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WLG, Word List Generation ,SPM12, Statistical Parametric Mapping 12 ,Audiology ,Tàlem - Imatgeria ,Etiv, estimated total intracranial volume ,lcsh:RC346-429 ,Otros calificadores::Otros calificadores::/complicaciones [Otros calificadores] ,GIF, Geodesic Information Flows ,0302 clinical medicine ,Cognition ,Segmentation ,Thalamus ,CP, cognitively preserved ,NBV, Normalized brain volume ,Multiple Sclerosi ,Other subheadings::/diagnosis [Other subheadings] ,Neuropsychological assessment ,Cognitive decline ,Generalized estimating equation ,WMV, white matter volume ,ICC, intraclass correlation coefficient ,medicine.diagnostic_test ,05 social sciences ,Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis [DISEASES] ,sistema nervioso::sistema nervioso central::encéfalo::prosencéfalo::diencéfalo::tálamo [ANATOMÍA] ,Regular Article ,Neuropsychological test ,HC, healthy control ,SDMT, Symbol Digit Modalities Test ,Magnetic Resonance Imaging ,Neurology ,PASAT, Paced Auditory Serial Addition Test ,enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple [ENFERMEDADES] ,lcsh:R858-859.7 ,VolBrain, MRI Brain Volumetry System ,SRT, Selective Reminding Test ,Human ,MRI ,Esclerosi múltiple - Complicacions ,medicine.medical_specialty ,CNR, contrast-to-noise ratio ,Multiple Sclerosis ,Cognitive Neuroscience ,RRMS, Relapsing-Remitting Multiple Sclerosis ,Otros calificadores::/diagnóstico [Otros calificadores] ,Nervous System::Central Nervous System::Brain::Prosencephalon::Diencephalon::Thalamus [ANATOMY] ,10/36 SRT, 10/36 Spatial Recall Test ,lcsh:Computer applications to medicine. Medical informatics ,NGMV, Normalized grey matter volume ,050105 experimental psychology ,SD, standard deviations ,CII, cognitive impairment index ,EDSS, Expanded Disability Status Scale ,WCST, Wisconsin Card Sorting Test ,03 medical and health sciences ,Atrophy ,medicine ,Humans ,0501 psychology and cognitive sciences ,Radiology, Nuclear Medicine and imaging ,WM, white matter ,lcsh:Neurology. Diseases of the nervous system ,Thalamu ,CI, cognitively impaired and preserved (CP) ,BRB-N, Brief Repeatable Battery of Neuropsychological Tests ,business.industry ,Multiple sclerosis ,FSL-FIRST, FMRIB Integrated Registration and Segmentation Tool ,eTIV, estimated total intracranial volume ,CAT12, Computational Anatomy Toolbox for Statistical Parametric Mapping 12 ,GM, grey matter ,medicine.disease ,Deep grey matter ,NWMV, Normalized white matter volume ,MS, Multiple Sclerosis ,GMV, grey matter volume ,IPS, information processing speed ,Neurology (clinical) ,business ,030217 neurology & neurosurgery ,Other subheadings::Other subheadings::/complications [Other subheadings] - Abstract
Highlights • Thalamus atrophy is associated with cognitive impairment in multiple sclerosis. • This was confirmed by automated and manual segmentations, but effect sizes varied. • The algorithms work in a multi-center setting. • Automated techniques exhibit proportional bias with respect to thalamus size. • Differences between vendors can affect the robustness of these associations., Background and rationale Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values
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- 2021
33. Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis : an evaluation of four automated methods against manual reference segmentations in a multi-center cohort
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de Sitter, Alexandra, Verhoeven, Tom, Burggraaff, Jessica, Liu, Yaou, Simoes, Jorge, Ruggieri, Serena, Palotai, Miklos, Brouwer, Iman, Versteeg, Adriaan, Wottschel, Viktor, Ropele, Stefan, Rocca, Mara A., Gasperini, Claudio, Gallo, Antonio, Yiannakas, Marios C., Rovira, Alex, Enzinger, Christian, Filippi, Massimo, De Stefano, Nicola, Kappos, Ludwig, Frederiksen, Jette L., Uitdehaag, Bernard M. J., Barkhof, Frederik, Guttmann, Charles R. G., Vrenken, Hugo, Universitat Autònoma de Barcelona, de Sitter, Alexandra, Verhoeven, Tom, Burggraaff, Jessica, Liu, Yaou, Simoes, Jorge, Ruggieri, Serena, Palotai, Miklo, Brouwer, Iman, Versteeg, Adriaan, Wottschel, Viktor, Ropele, Stefan, Rocca, Mara A, Gasperini, Claudio, Gallo, Antonio, Yiannakas, Marios C, Rovira, Alex, Enzinger, Christian, Filippi, Massimo, De Stefano, Nicola, Kappos, Ludwig, Frederiksen, Jette L, Uitdehaag, Bernard M J, Barkhof, Frederik, Guttmann, Charles R G, Vrenken, Hugo, de Sitter, A., Verhoeven, T., Burggraaff, J., Liu, Y., Simoes, J., Ruggieri, S., Palotai, M., Brouwer, I., Versteeg, A., Wottschel, V., Ropele, S., Rocca, M. A., Gasperini, C., Gallo, A., Yiannakas, M. C., Rovira, A., Enzinger, C., Filippi, M., De Stefano, N., Kappos, L., Frederiksen, J. L., Uitdehaag, B. M. J., Barkhof, F., Guttmann, C. R. G., Vrenken, H., Radiology and nuclear medicine, Neurology, and Amsterdam Neuroscience - Brain Imaging
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Correlation coefficient ,Caudate nucleus ,Grey matter ,030218 nuclear medicine & medical imaging ,Multiple sclerosis ,03 medical and health sciences ,0302 clinical medicine ,Atrophy ,Automated segmentation methods ,Deep grey matter ,Medicine ,Humans ,Segmentation ,Multiple sclerosi ,Gray Matter ,Neuroradiology ,Original Communication ,business.industry ,Putamen ,Brain ,medicine.disease ,Magnetic Resonance Imaging ,medicine.anatomical_structure ,Neurology ,Brain size ,Automated segmentation method ,Neurology (clinical) ,business ,Nuclear medicine ,030217 neurology & neurosurgery ,Human - Abstract
Background Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.
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- 2020
34. Assessing clinical utility of machine learning and artificial intelligence approaches to analyze speech recordings in multiple sclerosis: A pilot study.
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Svoboda E, Bořil T, Rusz J, Tykalová T, Horáková D, Guttmann CRG, Blagoev KB, Hatabu H, and Valtchinov VI
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- Artificial Intelligence, Humans, Machine Learning, Pilot Projects, Multiple Sclerosis, Speech
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Background: An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria., Method: The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve., Results: The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant., Conclusion: Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations., (Copyright © 2022 Elsevier Ltd. All rights reserved.)
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- 2022
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35. The impact of lesion in-painting and registration methods on voxel-based morphometry in detecting regional cerebral gray matter atrophy in multiple sclerosis.
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Ceccarelli A, Jackson JS, Tauhid S, Arora A, Gorky J, Dell'Oglio E, Bakshi A, Chitnis T, Khoury SJ, Weiner HL, Guttmann CR, Bakshi R, and Neema M
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- Adult, Atrophy, Female, Humans, Male, Middle Aged, Brain pathology, Image Enhancement, Image Processing, Computer-Assisted, Magnetic Resonance Imaging methods, Multiple Sclerosis, Relapsing-Remitting pathology
- Abstract
Background and Purpose: VBM has been widely used to study GM atrophy in MS. MS lesions lead to segmentation and registration errors that may affect the reliability of VBM results. Improved segmentation and registration have been demonstrated by WM LI before segmentation. DARTEL appears to improve registration versus the USM. Our aim was to compare the performance of VBM-DARTEL versus VBM-USM and the effect of LI in the regional analysis of GM atrophy in MS., Materials and Methods: 3T T1 MR imaging scans were acquired from 26 patients with RRMS and 28 age-matched NC. LI replaced WM lesions with normal-appearing WM intensities before image segmentation. VBM analysis was performed in SPM8 by using DARTEL and USM with and without LI, allowing the comparison of 4 VBM methods (DARTEL + LI, DARTEL - LI, USM + LI, and USM - LI). Accuracy of VBM was assessed by using NMI, CC, and a simulation analysis., Results: Overall, DARTEL + LI yielded the most accurate GM maps among the 4 methods (highest NMI and CC, P < .001). DARTEL + LI showed significant GM loss in the bilateral thalami and caudate nuclei in patients with RRMS versus NC. The other 3 methods overestimated the number of regions of GM loss in RRMS versus NC. LI improved the accuracy of both VBM methods. Simulated data suggested the accuracy of the results provided from patient MR imaging analysis., Conclusions: We introduce a pipeline that shows promise in limiting segmentation and registration errors in VBM analysis in MS.
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- 2012
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36. Diffusion tensor-MRI evidence for extra-axonal neuronal degeneration in caudate and thalamic nuclei of patients with multiple sclerosis.
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Hannoun S, Durand-Dubief F, Confavreux C, Ibarrola D, Streichenberger N, Cotton F, Guttmann CR, and Sappey-Marinier D
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- Adult, Evidence-Based Medicine, Female, Humans, Male, Reproducibility of Results, Sensitivity and Specificity, Caudate Nucleus pathology, Diffusion Magnetic Resonance Imaging methods, Multiple Sclerosis pathology, Neurons pathology, Thalamic Nuclei pathology
- Abstract
Background and Purpose: MS is an inflammatory demyelinating disease affecting both WM and GM. While WM lesions are easily visualized by conventional MR imaging, the detection of GM alterations remains challenging. This diffusion tensor MR imaging study aimed to detect and characterize diffuse microscopic alterations in 2 deep GM structures, the caudate nucleus and the thalamus, in patients with RR and SP MS. The relationship between diffusivity markers, and atrophy of the caudate and the thalamus, as well as brain lesion load and clinical status of the patients was also explored., Materials and Methods: Twenty-three RR and 18 SP patients, along with 27 healthy controls, underwent MR imaging examination including anatomic and DTI acquisitions. Volumes, mean FA, and MD of the caudate and the thalamus, as well as WM lesion volumes, were assessed., Results: FA was significantly (P < .001) increased in the caudate and the thalamus of patients with MS compared with controls, and was higher in SP compared with RR patients. Increased FA was associated with volume decreases of caudate (r = -0.712; P < .001) and thalamus (r = -0.407; P < .01) in patients with MS. WM T2 lesion load was significantly associated with caudate (r = 0.611; P < .001) and thalamic (r = 0.354; P < .05) FA. Caudate FA, and, to a lesser extent, thalamic FA, were associated with functional deficits, as measured by EDSS and MSFC., Conclusions: Increased FA in the caudate and the thalamus may constitute a sensitive marker of MS pathologic processes, such as loss of dendrites and/or swelling of neuronal cell bodies.
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- 2012
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37. A 3T MR imaging investigation of the topography of whole spinal cord atrophy in multiple sclerosis.
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Klein JP, Arora A, Neema M, Healy BC, Tauhid S, Goldberg-Zimring D, Chavarro-Nieto C, Stankiewicz JM, Cohen AB, Buckle GJ, Houtchens MK, Ceccarelli A, Dell'Oglio E, Guttmann CR, Alsop DC, Hackney DB, and Bakshi R
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- Adolescent, Adult, Atrophy pathology, Female, Humans, Male, Middle Aged, Young Adult, Magnetic Resonance Imaging methods, Multiple Sclerosis pathology, Spinal Cord pathology
- Abstract
Background and Purpose: Spinal cord atrophy is a common feature of MS. However, it is unknown which cord levels are most susceptible to atrophy. We performed whole cord imaging to identify the levels most susceptible to atrophy in patients with MS versus controls and also tested for differences among MS clinical phenotypes., Materials and Methods: Thirty-five patients with MS (2 with CIS, 27 with RRMS, 2 with SPMS, and 4 with PPMS phenotypes) and 27 healthy controls underwent whole cord 3T MR imaging. The spinal cord contour was segmented and assigned to bins representing each C1 to T12 vertebral level. Volumes were normalized, and group comparisons were age-adjusted., Results: There was a trend toward decreased spinal cord volume at the upper cervical levels in PPMS/SPMS versus controls. A trend toward increased spinal cord volume throughout the cervical and thoracic cord in RRMS/CIS versus controls reached statistical significance at the T10 vertebral level. A statistically significant decrease was found in spinal cord volume at the upper cervical levels in PPMS/SPMS versus RRMS/CIS., Conclusions: Opposing pathologic factors impact spinal cord volume measures in MS. Patients with PPMS demonstrated a trend toward upper cervical cord atrophy. However patients with RRMS showed a trend toward increased volume at the cervical and thoracic levels, which most likely reflects inflammation or edema-related cord expansion. With the disease causing both expansion and contraction of the cord, the specificity of spinal cord volume measures for neuroprotective therapeutic effect may be limited.
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- 2011
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38. Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging.
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Mike A, Glanz BI, Hildenbrand P, Meier D, Bolden K, Liguori M, Dell'Oglio E, Healy BC, Bakshi R, and Guttmann CR
- Subjects
- Adult, Humans, Reproducibility of Results, Sensitivity and Specificity, Brain pathology, Magnetic Resonance Imaging methods, Multiple Sclerosis pathology, Nerve Fibers, Myelinated pathology
- Abstract
Background and Purpose: Histopathologic studies have reported widespread cortical lesions in MS; however, in vivo detection by using routinely available pulse sequences is challenging. We investigated the relative frequency and subtypes of cortical lesions and their relationships to white matter lesions and cognitive and physical disability., Materials and Methods: Cortical lesions were identified and classified on the basis of concurrent review of 3D FLAIR and 3D T1-weighted IR-SPGR 3T MR images in 26 patients with MS. Twenty-five patients completed the MACFIMS battery. White matter lesion volume, cortical lesion number, and cortical lesion volume were assessed., Results: Overall, 249 cortical lesions were detected. Cortical lesions were present in 24/26 patients (92.3%) (range per patient, 0-30; mean, 9.6 ± 8.8). Most (94.4%, n = 235) cortical lesions were classified as mixed cortical-subcortical (type I); the remaining 5.6% (n = 14) were classified as purely intracortical (type II). Subpial cortical lesions (type III) were not detected. White matter lesion volume correlated with cortical lesion number and cortical lesion volume (r(S) = 0.652, r(S) = 0.705, respectively; both P < .001). After controlling for age, depression, and premorbid intelligence, we found that all MR imaging variables (cortical lesion number, cortical lesion volume, white matter lesion volume) correlated with the SDMT score (R(2) = 0.513, R(2) = 0.449, R(2) = 0.418, respectively; P < .014); cortical lesion number also correlated with the CVLT-II scores (R(2) = 0.542-0.461, P < .043). The EDSS scores correlated with cortical lesion number and cortical lesion volume (r(S) = 0.472, r(S) = 0.404, respectively; P < .05), but not with white matter lesion volume., Conclusions: Our routinely available imaging method detected many cortical lesions in patients with MS and was useful in their precise topographic characterization in the context of the gray matter-white matter junction. Routinely detectable cortical lesions were related to physical disability and cognitive impairment.
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- 2011
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39. Regional white matter atrophy--based classification of multiple sclerosis in cross-sectional and longitudinal data.
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Sampat MP, Berger AM, Healy BC, Hildenbrand P, Vass J, Meier DS, Chitnis T, Weiner HL, Bakshi R, and Guttmann CR
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- Atrophy pathology, Female, Humans, Longitudinal Studies, Male, Middle Aged, Anatomy, Cross-Sectional methods, Brain pathology, Magnetic Resonance Imaging methods, Multiple Sclerosis pathology, Nerve Fibers, Myelinated pathology
- Abstract
Background and Purpose: The different clinical subtypes of multiple sclerosis (MS) may reflect underlying differences in affected neuroanatomic regions. Our aim was to analyze the effectiveness of jointly using the inferior subolivary medulla oblongata volume (MOV) and the cross-sectional area of the corpus callosum in distinguishing patients with relapsing-remitting multiple sclerosis (RRMS), secondary-progressive multiple sclerosis (SPMS), and primary-progressive multiple sclerosis (PPMS)., Materials and Methods: We analyzed a cross-sectional dataset of 64 patients (30 RRMS, 14 SPMS, 20 PPMS) and a separate longitudinal dataset of 25 patients (114 MR imaging examinations). Twelve patients in the longitudinal dataset had converted from RRMS to SPMS. For all images, the MOV and corpus callosum were delineated manually and the corpus callosum was parcellated into 5 segments. Patients from the cross-sectional dataset were classified as RRMS, SPMS, or PPMS by using a decision tree algorithm with the following input features: brain parenchymal fraction, age, disease duration, MOV, total corpus callosum area and areas of 5 segments of the corpus callosum. To test the robustness of the classification technique, we applied the results derived from the cross-sectional analysis to the longitudinal dataset., Results: MOV and central corpus callosum segment area were the 2 features retained by the decision tree. Patients with MOV >0.94 cm(3) were classified as having RRMS. Patients with progressive MS were further subclassified as having SPMS if the central corpus callosum segment area was <55.12 mm(2), and as having PPMS otherwise. In the cross-sectional dataset, 51/64 (80%) patients were correctly classified. For the longitudinal dataset, 88/114 (77%) patient time points were correctly classified as RRMS or SPMS., Conclusions: Classification techniques revealed differences in affected neuroanatomic regions in subtypes of multiple sclerosis. The combination of central corpus callosum segment area and MOV provides good discrimination among patients with RRMS, SPMS, and PPMS.
- Published
- 2009
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40. Incidence and factors associated with treatment failure in the CLIMB multiple sclerosis cohort study.
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Gauthier SA, Glanz BI, Mandel M, Tsagkaropoulos A, Neema M, Stankiewicz J, Arora A, Duan Y, Liptak Z, Egorova S, Buckle GJ, Bakshi R, Guttmann CR, Khoury SJ, and Weiner HL
- Subjects
- Adult, Contrast Media, Disease Progression, Female, Follow-Up Studies, Gadolinium, Glatiramer Acetate, Humans, Incidence, Interferon beta-1a, Interferon beta-1b, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Relapsing-Remitting pathology, Prospective Studies, Risk Factors, Treatment Failure, Young Adult, Immunologic Factors therapeutic use, Interferon-beta therapeutic use, Multiple Sclerosis, Relapsing-Remitting drug therapy, Peptides therapeutic use
- Abstract
Objective: To determine the rate of treatment failure in patients outside of a controlled treatment trial and to ascertain the factors physicians used to make this decision., Methods: One hundred and thirty four patients with the diagnosis of relapsing-remitting (RR) multiple sclerosis (MS) or clinically isolated symptom (CIS) enrolled in the CLIMB study (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital) were treated with either interferon beta or glatiramer acetate as their initial treatment for MS., Results: The probability of failing initial treatment within 3 years was 30%. Clinical activity, defined as relapses and/or progression in disability, determined treatment failure in 35.7% (n=10) of nonresponders. New T2 hyperintense or gadolinium-enhancing lesions on MRI was used to define treatment failure in 28.6% (n=8) and new MRI lesions were used in combination with clinical activity in 35.7% (n=10). Treatment failures had a higher T2 hyperintense lesion volume (p=0.015) and number of gadolinium-enhancing lesions (p=0.0001) on the enrollment MRI than responders., Conclusions: These observations demonstrate that treating physicians use both clinical and MRI parameters to define a response to treatment and initiation of a treatment change and that baseline MRI identified those with increased risk of treatment failure.
- Published
- 2009
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41. Spinal cord lesions and clinical status in multiple sclerosis: A 1.5 T and 3 T MRI study.
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Stankiewicz JM, Neema M, Alsop DC, Healy BC, Arora A, Buckle GJ, Chitnis T, Guttmann CR, Hackney D, and Bakshi R
- Subjects
- Adult, Cervical Vertebrae, Cohort Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Phenotype, Severity of Illness Index, Thoracic Vertebrae, Walking, Young Adult, Multiple Sclerosis pathology, Multiple Sclerosis physiopathology, Spinal Cord pathology
- Abstract
Objective: Assess the relationship between spinal cord T2 hyperintense lesions and clinical status in multiple sclerosis (MS) with 1.5 and 3 T MRI., Methods: Whole cord T2-weighted fast spin-echo MRI was performed in 32 MS patients [Expanded Disability Status Scale (EDSS) score (mean+/-SD: 2+/-1.9), range 0-6.5]. Protocols at 1.5 T and 3 T were optimized and matched on voxel size., Results: Moderate correlations were found between whole cord lesion volume and EDSS score at 1.5 T (r(s)=.36, p=0.04), but not at 3 T (r(s)=0.13, p=0.46). Pyramidal Functional System Score (FSS) correlated with thoracic T2 lesion number (r(s)=.46, p=0.01) and total spinal cord lesion number (r(s)=0.37, p=0.04) and volume (r(s)=0.37, p=0.04) at 1.5 T. Bowel/bladder FSS correlated with T2 lesion volume and number in the cervical, thoracic, and total spine at 1.5 T (r(s) 0.40-0.57, all p<0.05). These MRI-FSS correlations were non-significant at 3 T. However, these correlation coefficients did not differ significantly between platforms (Choi's test p>0.05). Correlations between whole cord lesion volume and timed 25-foot walk were non-significant at 1.5 T and 3 T (p>0.05). Lesion number and volume did not differ between MRI platforms in the MS group (p>0.05)., Conclusions: Despite the use of higher field MRI strength, the link between spinal lesions and MS disability remains weak. The 1.5 T and 3 T protocols yielded similar results for many comparisons.
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- 2009
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42. Temporoparietal MR imaging measures of atrophy in subjects with mild cognitive impairment that predict subsequent diagnosis of Alzheimer disease.
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Desikan RS, Cabral HJ, Fischl B, Guttmann CR, Blacker D, Hyman BT, Albert MS, and Killiany RJ
- Subjects
- Aged, Alzheimer Disease epidemiology, Atrophy, Cognition Disorders epidemiology, Entorhinal Cortex pathology, Female, Follow-Up Studies, Humans, Male, Multivariate Analysis, Neuropsychological Tests, Predictive Value of Tests, Proportional Hazards Models, Risk Factors, Severity of Illness Index, Alzheimer Disease pathology, Cognition Disorders pathology, Magnetic Resonance Imaging, Parietal Lobe pathology, Temporal Lobe pathology
- Abstract
Background and Purpose: Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer disease (AD). Our goal was to determine if specific temporoparietal regions can predict the time to progress from MCI to AD., Materials and Methods: MR images from 129 individuals with MCI were analyzed to identify the volume of 14 neocortical and 2 non-neocortical brain regions, comprising the temporal and parietal lobes. In addition, 3 neuropsychological test scores were included to determine whether they would provide independent information. After a mean follow-up time of 5 years, 44 of these individuals had progressed to a diagnosis of AD., Results: Cox proportional hazards models demonstrated significant effects for 6 MR imaging regions with the greatest differences being the following: the entorhinal cortex (hazard ratio [HR] = 0.54, P < .001), inferior parietal lobule (hazard ratio [HR] = 0.64, P < .005), and middle temporal gyrus (HR = 0.64, P < .004), indicating decreased risk with larger volumes. A multivariable model showed that a combination of the entorhinal cortex (HR = 0.60, P < .001) and the inferior parietal lobule (HR = 0.62, P < .01) was the best predictor of time to progress to AD. A multivariable model reiterated the importance of including both MR imaging and neuropsychological variables in the final model., Conclusions: These findings reaffirm the importance of the entorhinal cortex and present evidence for the importance of the inferior parietal lobule as a predictor of time to progress from MCI to AD. The inclusion of neuropsychological performance in the final model continues to highlight the importance of using these measures in a complementary fashion.
- Published
- 2009
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43. CTLA4Ig treatment in patients with multiple sclerosis: an open-label, phase 1 clinical trial.
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Viglietta V, Bourcier K, Buckle GJ, Healy B, Weiner HL, Hafler DA, Egorova S, Guttmann CR, Rusche JR, and Khoury SJ
- Subjects
- Abatacept, Brain pathology, Cohort Studies, Dose-Response Relationship, Drug, Humans, Immune System drug effects, Immunoconjugates adverse effects, Immunoconjugates therapeutic use, Immunosuppressive Agents adverse effects, Immunosuppressive Agents therapeutic use, Interferon-gamma antagonists & inhibitors, Magnetic Resonance Imaging, Multiple Sclerosis, Relapsing-Remitting diagnosis, Multiple Sclerosis, Relapsing-Remitting physiopathology, Myelin Basic Protein antagonists & inhibitors, Time Factors, Immunoconjugates administration & dosage, Immunosuppressive Agents administration & dosage, Multiple Sclerosis, Relapsing-Remitting drug therapy
- Abstract
Background: The modulation of costimulatory pathways represents an original therapeutic approach to regulate T cell-mediated autoimmune diseases by preventing or reducing autoantigen-driven T-cell activation in humans. Autoreactive CD4(+) T cells play a critical role in initiating the immune response leading to the chronic inflammation and demyelination characteristic of multiple sclerosis (MS)., Methods: We used IV infusions of CTLA4Ig to block the CD28/B7 T-cell costimulatory pathway in a phase 1 dose-escalation study in MS. Sixteen patients with relapsing-remitting MS received a single CTLA4Ig infusion and were monitored for up to 3 months after treatment. In an extension study, four additional subjects received four doses of CTLA4Ig., Results: CTLA4Ig was well tolerated in patients with MS, and most adverse events were rated as mild. Immunologic assessment of the patients showed a reduction in myelin basic protein (MBP) proliferation within 2 months of infusion and decreased interferon-gamma production by MBP-specific lines., Conclusions: Inhibiting costimulatory molecule interactions by using CTLA4Ig seems safe in multiple sclerosis (MS), and the immunologic effects suggest that it may be a promising approach to regulate the inflammatory process associated with MS.
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- 2008
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44. MRI measures of temporoparietal regions show differential rates of atrophy during prodromal AD.
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Desikan RS, Fischl B, Cabral HJ, Kemper TL, Guttmann CR, Blacker D, Hyman BT, Albert MS, and Killiany RJ
- Subjects
- Aged, Alzheimer Disease metabolism, Atrophy, Female, Follow-Up Studies, Humans, Magnetic Resonance Imaging standards, Male, Parietal Lobe metabolism, Research Design standards, Temporal Lobe metabolism, Time Factors, Alzheimer Disease pathology, Magnetic Resonance Imaging methods, Parietal Lobe pathology, Temporal Lobe pathology
- Abstract
Background: MRI studies have demonstrated differential rates of atrophy in the entorhinal cortex and hippocampus during the prodromal phase of Alzheimer disease (AD). The current study was designed to determine whether a broader set of temporoparietal regions show differential rates of atrophy during the evolution of AD., Methods: Sixteen regions of interest (ROIs) were analyzed on MRI scans obtained at baseline and follow-up in 66 subjects comprising three groups: controls = individuals who were cognitively normal at both baseline and follow-up; nonconverters = subjects with mild cognitive impairment (MCI) at both baseline and follow-up; converters had MCI at baseline but had progressed to AD at follow-up., Results: Annualized percent change was analyzed with multivariate analysis of variance (MANOVA), covaried for age. The MANOVA demonstrated an effect of group (p = 0.004). Post hoc comparisons demonstrated greater rates of atrophy for converters vs nonconverters for six ROIs: hippocampus, entorhinal cortex, temporal pole, middle temporal gyrus, fusiform gyrus, and inferior temporal gyrus. Converters showed differentially greater rates of atrophy than controls in five of the same ROIs (and inferior parietal lobule). Rates of change in clinical status were correlated with the atrophy rates in these regions. Comparisons between controls and nonconverters demonstrated no differences., Conclusion: These results demonstrate that temporoparietal regions show differential rates of atrophy on MRI during prodromal Alzheimer disease (AD). MRI data correlate with measures of clinical severity and cognitive decline, suggesting the potential of these regions of interest as antemortem markers of prodromal AD.
- Published
- 2008
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45. Medulla oblongata volume: a biomarker of spinal cord damage and disability in multiple sclerosis.
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Liptak Z, Berger AM, Sampat MP, Charil A, Felsovalyi O, Healy BC, Hildenbrand P, Khoury SJ, Weiner HL, Bakshi R, and Guttmann CR
- Subjects
- Adult, Female, Humans, Male, Middle Aged, Multiple Sclerosis complications, Prognosis, Reproducibility of Results, Sensitivity and Specificity, Spinal Cord Injuries complications, Imaging, Three-Dimensional methods, Magnetic Resonance Imaging methods, Medulla Oblongata pathology, Multiple Sclerosis pathology, Spinal Cord pathology, Spinal Cord Injuries pathology
- Abstract
Background and Purpose: While brain MR imaging is routinely performed, the MR imaging assessment of spinal cord pathology in multiple sclerosis (MS) is less frequent in clinical practice. The purpose of this study was to determine whether measurements of medulla oblongata volume (MOV) on routine brain MR imaging could serve as a biomarker of spinal cord damage and disability in MS., Materials and Methods: We identified 45 patients with MS with both head and cervical spinal cord MR imaging and 29 age-matched and sex-matched healthy control subjects with head MR imaging. Disability was assessed by the expanded disability status scale (EDSS) and ambulation index (AI). MOV and upper cervical cord volume (UCCV) were manually segmented; semiautomated segmentation was used for brain parenchymal fraction (BPF). These measures were compared between groups, and linear regression models were built to predict disability., Results: In the patients, MOV correlated significantly with UCCV (r = 0.67), BPF (r = 0.45), disease duration (r = -0.64), age (r = -0.47), EDSS score (r = -0.49) and AI (r = -0.52). Volume loss of the medulla oblongata was -0.008 cm(3)/year of age in patients with MS, but no significant linear relationship with age was found for healthy control subjects. The patients had a smaller MOV (mean +/- SD, 1.02 +/- 0.17 cm(3)) than healthy control subjects (1.15 +/- 0.15 cm(3)), though BPF was unable to distinguish between these 2 groups. MOV was smaller in patients with progressive MS (secondary- progressive MS, 0.88 +/- 0.19 cm(3) and primary-progressive MS, 0.95 +/- 0.30 cm(3)) than in patients with relapsing-remitting MS (1.08 +/- 0.15 cm(3)). A model including both MOV and BPF better predicted AI than BPF alone (P = .04). Good reproducibility in MOV measurements was demonstrated for intrarater (intraclass correlation coefficient, 0.97), interrater (0.79), and scan rescan data (0.81)., Conclusion: MOV is associated with disability in MS and can serve as a biomarker of spinal cord damage.
- Published
- 2008
- Full Text
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46. Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis.
- Author
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Duan Y, Hildenbrand PG, Sampat MP, Tate DF, Csapo I, Moraal B, Bakshi R, Barkhof F, Meier DS, and Guttmann CR
- Subjects
- Adult, Atrophy diagnosis, Female, Humans, Male, Reproducibility of Results, Sensitivity and Specificity, Brain pathology, Image Interpretation, Computer-Assisted methods, Imaging, Three-Dimensional methods, Magnetic Resonance Imaging methods, Multiple Sclerosis diagnosis, Subtraction Technique
- Abstract
Background and Purpose: Lesion volume change (LVC) assessment is essential in monitoring MS progression. LVC is usually measured by independently segmenting serial MR imaging examinations. Subtraction imaging has been proposed for improved visualization and characterization of lesion change. We compare segmentation of subtraction images (SSEG) with serial single time-point conventional segmentation (CSEG) by assessing the LVC relationship to brain atrophy and disease duration, as well as scan-rescan reproducibility and annual rates of lesion accrual., Materials and Methods: Pairs of scans were acquired 1.5 to 4.7 years apart in 21 patients with multiple sclerosis (MS). Scan-rescan MR images were acquired within 30 minutes in 10 patients with MS. LVC was measured with CSEG and SSEG after coregistration and normalization. Coefficient of variation (COV) and Bland-Altman analyses estimated method reproducibility. Spearman rank correlations probed associations between LVC and other measures., Results: Atrophy rate and net LVC were associated for SSEG (R = -0.446; P < .05) but not when using CSEG (R = -0.180; P = .421). Disease duration did not show an association with net lesion volume change per year measured by CSEG (R = -0.360; P = .11) but showed an inverse correlation with SSEG-derived measurements (R = -0.508; P < .05). Scan-rescan COV was lower for SSEG (0.98% +/- 1.55%) than for CSEG (8.64% +/- 9.91%)., Conclusion: SSEG unveiled a relationship between T2 LVC and concomitant brain atrophy and demonstrated significantly higher measurement reproducibility. SSEG, a promising tool providing detailed analysis of subtle alterations in lesion size and intensity, may provide critical outcome measures for clinical trials of novel treatments, and may provide further insight into progression patterns in MS.
- Published
- 2008
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47. MR imaging intensity modeling of damage and repair in multiple sclerosis: relationship of short-term lesion recovery to progression and disability.
- Author
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Meier DS, Weiner HL, and Guttmann CR
- Subjects
- Atrophy, Contrast Media, Disease Progression, Gadolinium DTPA, Humans, Image Processing, Computer-Assisted, Brain pathology, Magnetic Resonance Imaging, Multiple Sclerosis pathology
- Abstract
Background and Purpose: Formation of lesions in multiple sclerosis (MS) shows pronounced short-term fluctuation of MR imaging hyperintensity and size, a qualitatively known but poorly characterized phenomenon. With the use of time-series modeling of MR imaging intensity, our study relates the short-term dynamics of new T2 lesion formation to those of contrast enhancement and markers of long-term progression of disease., Materials and Methods: We analyzed 915 examinations from weekly to monthly MR imaging in 40 patients with MS using a time-series model, emulating 2 opposing processes of T2 prolongation and shortening, respectively. Patterns of activity, duration, and residual hyperintensity within new T2 lesions were measured and evaluated for relationships to disability, atrophy, and clinical phenotype in long-term follow-up., Results: Significant T2 activity was observed for 8 to 10 weeks beyond contrast enhancement, which suggests that T2 MR imaging is sensitive to noninflammatory processes such as degeneration and repair. Larger lesions showed longer subacute phases but disproportionally more recovery. Patients with smaller average peak lesion size showed trends toward greater disability and proportional residual damage. Higher rates of disability or atrophy were associated with subjects whose lesions showed greater residual hyperintensity., Conclusion: Smaller lesions appeared disproportionally more damaging than larger lesions, with lesions in progressive MS smaller and of shorter activity than in relapsing-remitting MS. Associations of lesion dynamics with rates of atrophy and disability and clinical subtype suggest that changes in lesion dynamics may represent a shift from inflammatory toward degenerative disease activity and greater proximity to a progressive stage, possibly allowing staging of the progression of MS earlier, before atrophy or disability develops.
- Published
- 2007
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48. Thalamic atrophy and cognition in multiple sclerosis.
- Author
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Houtchens MK, Benedict RH, Killiany R, Sharma J, Jaisani Z, Singh B, Weinstock-Guttman B, Guttmann CR, and Bakshi R
- Subjects
- Adult, Age Factors, Atrophy etiology, Atrophy physiopathology, Cognition Disorders physiopathology, Disability Evaluation, Female, Humans, Immunologic Factors therapeutic use, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis physiopathology, Neuropsychological Tests, Predictive Value of Tests, Regression Analysis, Sex Factors, Thalamus physiopathology, Third Ventricle pathology, Atrophy diagnosis, Cognition Disorders etiology, Cognition Disorders pathology, Multiple Sclerosis complications, Multiple Sclerosis pathology, Thalamus pathology
- Abstract
Objectives: Recent studies have indicated that brain atrophy is more closely associated with cognitive impairment in multiple sclerosis (MS) than are conventional MRI lesion measures. Enlargement of the third ventricle shows a particularly strong correlation with cognitive impairment, suggesting clinical relevance of damage to surrounding structures, such as the thalamus. Previous imaging and pathology studies have demonstrated thalamic involvement in MS. In this study, we tested the hypothesis that thalamic volume is lower in MS than in normal subjects, and that thalamic atrophy in MS correlates with cognitive function., Methods: We studied 79 patients with MS and 16 normal subjects. A subgroup of 31 MS subjects underwent cognitive testing. The thalamus was segmented in whole from three-dimensional MRI scans. We also determined whole brain atrophy (brain parenchymal fraction), third ventricular width, and whole brain T2-weighted (fluid-attenuated inversion recovery) hyperintense, T1 hypointense, and gadolinium-enhanced lesion volumes., Results: Normalized thalamic volume was 16.8% lower in the MS group (p < 0.0001) vs controls. Cognitive performance in all domains was moderately to strongly related to thalamic volume in the MS group (r = 0.506 to 0.724, p < 0.005), and thalamic volume entered and remained in all regression models predicting cognitive performance. Thalamic volume showed a weak relationship to physical disability score (r = -0.316, p = 0.005)., Conclusion: These findings suggest that thalamic atrophy is a clinically relevant biomarker of the neurodegenerative disease process in multiple sclerosis.
- Published
- 2007
- Full Text
- View/download PDF
49. Predicting short-term disability in multiple sclerosis.
- Author
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Gauthier SA, Mandel M, Guttmann CR, Glanz BI, Khoury SJ, Betensky RA, and Weiner HL
- Subjects
- Adult, Brain physiopathology, Disease Progression, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Markov Chains, Middle Aged, Models, Statistical, Predictive Value of Tests, Prognosis, Prospective Studies, Time Factors, Brain pathology, Disability Evaluation, Multiple Sclerosis diagnosis, Multiple Sclerosis epidemiology
- Abstract
Objective: To develop covariate specific short-term disability curves to demonstrate the probability of progressing by Expanded Disability Status Scale (EDSS) at semiannual visits., Methods: Semiannual EDSS scores were prospectively collected in 218 relapsing-remitting (RR) and clinically isolated syndrome (CIS) patients as part of the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB) study. Baseline brain parenchymal fraction (BPF) and T2 lesion volume were available on 205 patients. A partial proportional odds model determined the influence of covariates on the change in EDSS score at subsequent visits. A discrete second order Markov transitional model was fit and generated a probability matrix for each subject; the 6-month probabilities of EDSS change were graphically represented., Results: The univariate analysis demonstrated the lowest baseline BPF quartile (OR 1.99; p = 0.0203) and the highest T2 lesion volume quartile (OR 2.19; p = 0.0130) were associated with progression in EDSS. Covariate specific disability curves demonstrated the effect of BPF and T2 lesion volume on short-term progression. In subjects with a 6-month EDSS of 2, the probability of a sustained progression of an EDSS of 3 within 3 years was 0.277 for a subject with low BPF and a high T2 lesion volume vs 0.055 for a subject with high BPF and a low T2 lesion volume., Conclusions: Markov transitional models allow for the comparison of covariate specific short-term disability changes among groups of patients with multiple sclerosis.
- Published
- 2007
- Full Text
- View/download PDF
50. A highly immunogenic trivalent T cell receptor peptide vaccine for multiple sclerosis.
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Bourdette DN, Edmonds E, Smith C, Bowen JD, Guttmann CR, Nagy ZP, Simon J, Whitham R, Lovera J, Yadav V, Mass M, Spencer L, Culbertson N, Bartholomew RM, Theofan G, Milano J, Offner H, and Vandenbark AA
- Subjects
- Adult, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis pathology, Peptide Fragments immunology, T-Lymphocytes immunology, Vaccines, Subunit adverse effects, Multiple Sclerosis immunology, Multiple Sclerosis therapy, Receptors, Antigen, T-Cell immunology, Vaccines, Subunit administration & dosage, Vaccines, Subunit immunology
- Abstract
Background: T cell receptor (TCR) peptide vaccination is a novel approach to treating multiple sclerosis (MS). The low immunogenicity of previous vaccines has hindered the development of TCR peptide vaccination for MS., Objective: To compare the immunogenicity of intramuscular injections of TCR BV5S2, BV6S5 and BV13S1 CDR2 peptides in incomplete Freunds adjuvant (IFA) with intradermal injections of the same peptides without IFA., Methods: MS subjects were randomized to receive TCR peptides/IFA, TCR peptides/saline or IFA alone. Subjects were on study for 24 weeks., Results: The TCR peptides/IFA vaccine induced vigorous T cell responses in 100% of subjects completing the 24-week study (9/9) compared with only 20% (2/10) of those receiving the TCR peptides/saline vaccine (P =0.001). IFA alone induced a weak response in only one of five subjects. Aside from injection site reactions, there were no significant adverse events attributable to the treatment., Conclusions: The trivalent TCR peptide in IFA vaccine represents a significant improvement in immunogenicity over previous TCR peptide vaccines and warrants investigation of its ability to treat MS.
- Published
- 2005
- Full Text
- View/download PDF
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