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10 p, 2.3 MB |
Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI
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Coll, Llucia (Hospital Universitari Vall d'Hebron) ;
Pareto, Deborah (Hospital Universitari Vall d'Hebron) ;
Carbonell-Mirabent, Pere (Hospital Universitari Vall d'Hebron) ;
Cobo-Calvo, Álvaro (Hospital Universitari Vall d'Hebron) ;
Arrambide, Georgina (Hospital Universitari Vall d'Hebron) ;
Vidal-Jordana, Angela (Hospital Universitari Vall d'Hebron) ;
Comabella, Manuel (Hospital Universitari Vall d'Hebron) ;
Castilló, Joaquin (Hospital Universitari Vall d'Hebron) ;
Rodríguez-Acevedo, Breogán (Hospital Universitari Vall d'Hebron) ;
Zabalza, Ana (Hospital Universitari Vall d'Hebron) ;
Galan, Ingrid (Hospital Universitari Vall d'Hebron) ;
Midaglia, Luciana (Hospital Universitari Vall d'Hebron) ;
Nos, Carlos (Hospital Universitari Vall d'Hebron) ;
Auger, Cristina (Universitat Autònoma de Barcelona. Departament de Medicina) ;
Alberich, Manel (Hospital Universitari Vall d'Hebron) ;
Río, Jordi (Hospital Universitari Vall d'Hebron) ;
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron) ;
Oliver, Arnau (Universitat de Girona) ;
Montalban, Xavier (Universitat Autònoma de Barcelona. Departament de Medicina) ;
Rovira, Alex (Hospital Universitari Vall d'Hebron) ;
Tintoré, Mar (Hospital Universitari Vall d'Hebron) ;
Lladó, Xavier (Universitat de Girona) ;
Tur, Carmen (Universitat Autònoma de Barcelona. Departament de Medicina)
Background: The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. [...]
2023 -  10.1002/jmri.29046
Journal of Magnetic Resonance Imaging
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2.
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12 p, 4.0 MB |
Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI
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Coll, Llucia (Hospital Universitari Vall d'Hebron) ;
Pareto, Deborah (Hospital Universitari Vall d'Hebron) ;
Carbonell-Mirabent, Pere (Hospital Universitari Vall d'Hebron) ;
Cobo-Calvo, Álvaro (Hospital Universitari Vall d'Hebron) ;
Arrambide, Georgina (Hospital Universitari Vall d'Hebron) ;
Vidal-Jordana, Angela (Hospital Universitari Vall d'Hebron) ;
Comabella, Manuel (Hospital Universitari Vall d'Hebron) ;
Castilló, Joaquín (Hospital Universitari Vall d'Hebron) ;
Rodríguez Acevedo, Breogán (Hospital Universitari Vall d'Hebron) ;
Zabalza, Ana (Hospital Universitari Vall d'Hebron) ;
Galan, Ingrid (Hospital Universitari Vall d'Hebron) ;
Midaglia, Luciana (Hospital Universitari Vall d'Hebron) ;
Nos, Carlos (Hospital Universitari Vall d'Hebron) ;
Salerno, Annalaura (Hospital Universitari Vall d'Hebron) ;
Auger, Cristina (Hospital Universitari Vall d'Hebron) ;
Alberich, Manel (Hospital Universitari Vall d'Hebron) ;
Río, Jordi (Hospital Universitari Vall d'Hebron) ;
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron) ;
Oliver, Arnau (Universitat de Girona. Institut de recerca en visió per computador i robòtica (VICOROB)) ;
Montalban, Xavier (Hospital Universitari Vall d'Hebron) ;
Rovira, Alex (Hospital Universitari Vall d'Hebron) ;
Tintoré, Mar (Hospital Universitari Vall d'Hebron) ;
Lladó, Xavier (Universitat de Girona. Institut de recerca en visió per computador i robòtica (VICOROB)) ;
Tur, Carmen (Hospital Universitari Vall d'Hebron) ;
Universitat Autònoma de Barcelona
The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of extracting image features not detectable through conventional methods. [...]
2023 - 10.1016/j.nicl.2023.103376
NeuroImage, Vol. 38 (march 2023)
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3.
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10 p, 509.3 KB |
Association of Early Progression Independent of Relapse Activity With Long-term Disability After a First Demyelinating Event in Multiple Sclerosis
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Tur, Carmen (Hospital Universitari Vall d'Hebron) ;
Carbonell-Mirabent, Pere (Hospital Universitari Vall d'Hebron) ;
Cobo-Calvo, Álvaro (Hospital Universitari Vall d'Hebron) ;
Otero-Romero, Susana (Hospital Universitari Vall d'Hebron) ;
Arrambide, Georgina (Hospital Universitari Vall d'Hebron) ;
Midaglia, Luciana (Hospital Universitari Vall d'Hebron) ;
Castilló, Joaquín (Hospital Universitari Vall d'Hebron) ;
Vidal-Jordana, Angela (Hospital Universitari Vall d'Hebron) ;
Rodríguez Acevedo, Breogán (Hospital Universitari Vall d'Hebron) ;
Zabalza, Ana (Hospital Universitari Vall d'Hebron) ;
Galan, Ingrid (Hospital Universitari Vall d'Hebron) ;
Nos, Carlos (Hospital Universitari Vall d'Hebron) ;
Salerno, Annalaura (Hospital Universitari Vall d'Hebron) ;
Auger, Cristina (Hospital Universitari Vall d'Hebron) ;
Pareto, Deborah (Hospital Universitari Vall d'Hebron) ;
Comabella, Manuel (Hospital Universitari Vall d'Hebron) ;
Río, Jordi (Hospital Universitari Vall d'Hebron) ;
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron) ;
Rovira, Alex (Hospital Universitari Vall d'Hebron) ;
Tintoré, Mar (Hospital Universitari Vall d'Hebron) ;
Montalban, Xavier (Hospital Universitari Vall d'Hebron) ;
Universitat Autònoma de Barcelona
This cohort study investigates the long-term outcomes of patients who develop progression independent of relapse activity after a first demyelinating event in multiple sclerosis. What are the long-term outcomes of patients developing progression independent of relapse activity (PIRA) after a first demyelinating event in multiple sclerosis? In this longitudinal cohort study including 1128 patients with a first demyelinating event in multiple sclerosis, presenting with PIRA was associated with significantly shorter times to developing severe disability compared with not presenting with PIRA. [...]
2022 - 10.1001/jamaneurol.2022.4655
JAMA Neurology, Vol. 80 (december 2022) , p. 151-160
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4.
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12 p, 2.1 MB |
The long-term outcomes of CIS patients in the Barcelona inception cohort : Looking back to recognize aggressive MS
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Tintoré, Mar (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Arrambide, Georgina (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Otero-Romero, Susana (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Carbonell-Mirabent, Pere (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Río, Jordi (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Tur, Carmen (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Comabella, Manuel (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Nos, Carlos (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Arévalo, María Jesús (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Anglada, Elisenda (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Menendez, Rebeca (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Midaglia, Luciana (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Galan, Ingrid (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Vidal-Jordana, Angela (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Castilló, Joaquín (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Mulero, P. (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Zabalza, Ana (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Rodríguez-Acevedo, Breogán (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Rodriguez, Marta (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Espejo, Carmen (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Sequeira, Joao (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Mitjana, Raquel (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
de Barros, Andrea (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Pareto, Deborah (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Auger, Cristina (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Pérez-Hoyos, Santiago (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Sastre-Garriga, Jaume (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Rovira, Alex (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Montalban, Xavier (Hospital Universitari Vall d'Hebron. Institut de Recerca) ;
Universitat Autònoma de Barcelona
To explore the long-term outcomes of patients with clinically isolated syndromes from the Barcelona cohort. We selected patients with a follow-up longer than 10 years to (1) estimate the risks of multiple sclerosis (MS) and disability accumulation according to the baseline number of T2 lesions and to compare treated versus untreated patients and early versus delayed treatment, and (2) to study baseline features of patients with aggressive MS (Expanded Disability Status Scale (EDSS) ⩾6. [...]
2019 - 10.1177/1352458519877810
Multiple sclerosis, Vol. 26 (october 2019) , p. 1658-1669
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5.
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12 p, 1.5 MB |
MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice
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Sastre-Garriga, Jaume (Centre d'Esclerosi Mútiple de Catalunya (Cemcat)) ;
Pareto, Deborah (Hospital Universitari Vall d'Hebron) ;
Battaglini, Marco (University of Siena. Department of Medicine, Surgery and Neuroscience) ;
Rocca, Maria A. (IRCCS San Raffaele Scientific Institute (Milà, Itàlia). Institute of Experimental Neurology) ;
Ciccarelli, Olga (University College London Hospitals. National Institute for Health Research Biomedical Research Centre) ;
Enzinger, Christian (Medical University of Graz. Department of Neurology and Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology) ;
Wuerfel, Jens (University of Basel. Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering) ;
Sormani, Maria P. (IRCCS, Ospedale Policlinico San Martino, Genoa) ;
Barkhof, Frederik (University College London. Institutes of Neurology and Healthcare Engineering) ;
Yousry, Tarek A. (University College London Hospitals National Hospital for Neurology and Neurosurgery, University College London Institute of Neurology. Lysholm Department of Neuroradiology) ;
De Stefano, Nicola (University of Siena. Department of Medicine, Surgery and Neuroscience) ;
Tintoré, Mar (Centre d'Esclerosi Mútiple de Catalunya (Cemcat)) ;
Filippi, Massimo (Vita-Salute San Raffaele University) ;
Gasperini, Claudio (San Camillo Forlanini Hospital) ;
Kappos, Ludwig (University Hospital Basel (Basilea, Suïssa)) ;
Río, Jordi (Universitat Autònoma de Barcelona) ;
Frederiksen, Jette (University of Copenhagen) ;
Palace, Jackie (University of Oxford. Nuffield Department of Clinical Neurosciences) ;
Vrenken, Hugo (Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC) ;
Montalban, Xavier (University of Toronto. Division of Neurology, St Michael's Hospital) ;
Rovira, Alex (Hospital Universitari Vall d'Hebron) ;
Universitat Autònoma de Barcelona ;
Hospital Universitari Vall d'Hebron ;
Centre d'Esclerosi Mútiple de Catalunya (Cemcat)
Early evaluation of treatment response and prediction of disease evolution are key issues in the management of people with multiple sclerosis (MS). In the past 20 years, MRI has become the most useful paraclinical tool in both situations and is used clinically to assess the inflammatory component of the disease, particularly the presence and evolution of focal lesions - the pathological hallmark of MS. [...]
2020 - 10.1038/s41582-020-0314-x
Nature Reviews. Neurology, Vol. 16 (february 2020) , p. 171-182
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