دورية أكاديمية
Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort
| العنوان: | Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort |
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| المؤلفون: | Cury, Claire, Durrleman, Stanley, Cash, David, Lorenzi, Marco, Nicholas, Jennifer, M, Bocchetta, Martina, van Swieten, John, C., Borroni, Barbara, Galimberti, Daniela, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James, Graff, Caroline, Tagliavini, Fabrizio, Frisoni, Giovanni, B., Laforce, Robert, Finger, Elizabeth, de Mendonça, Alexandre, Sorbi, Sandro, Ourselin, Sébastien, Rohrer, Jonathan, Modat, Marc, Andersson, Christin, Archetti, Silvana, Arighi, Andrea, Benussi, Luisa, Black, Sandra, Cosseddu, Maura, Fallstrm, Marie, Ferreira, Carlos, G., Fenoglio, Chiara, Fox, Nick, Freedman, Morris, Fumagalli, Giorgio, Gazzina, Stefano, Ghidoni, Robert, Grisoli, Marina, Jelic, Vesna, Jiskoot, Lize, Keren, Ron, Lombardi, Gemma, Maruta, Carolina, Meeter, Lieke, van Minkelen, Rick, Nacmias, Benedetta, Ijerstedt, Linn, Padovani, Alessandro, Panman, Jessica, Pievani, Michela, Polito, Cristina, Premi, Enrico, Prioni, Sara, Rademakers, Rosa, Redaelli, Veronica, Rogaeva, Ekaterina, Rossi, Giacomina, Rossor, Martin, Scarpini, Elio, Tang-Wai, David, Thonberg, Hakan, Tiraboschi, Pietro, Verdelho, Ana, Warren, Jason |
| المساهمون: | Department of Medical Physics and Biomedical Engineering (UCL), University College of London London (UCL), Dementia Research Centre London (DRC), Neuroimagerie: méthodes et applications (Empenn), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain ICM Paris (ARAMIS), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), London School of Hygiene and Tropical Medicine (LSHTM), Erasmus University Medical Center Rotterdam (Erasmus MC), Università degli Studi di Brescia = University of Brescia (UniBs), Centro Dino Ferrari Milano, Università degli Studi di Milano = University of Milan (UNIMI)-Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, Sunnybrook Research Institute Toronto (SRI), Sunnybrook Health Sciences Centre Toronto (Sunnybrook), Tanz Center Research in Neurodegenerative Diseases Toronto, University of Toronto, University of Cambridge UK (CAM), Karolinska Institutet Stockholm, Karolinska University Hospital Stockholm, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Centro San Giovanni di Dio, Fatebenefratelli, Brescia (IRCCS), Université Laval Québec (ULaval), University of Western Ontario (UWO), Faculdade de Medicina Lisboa, Universidade de Lisboa = University of Lisbon (ULISBOA), Università degli Studi di Firenze = University of Florence = Université de Florence (UniFI), Imaging Sciences and Biomedical Engineering Division London, Guy's and St Thomas' Hospital London -King‘s College London, Civic Hospital of Brescia, Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, IRCCS Fatebenefratelli - Brescia, Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), UCL Queen Square Institute of Neurology, Toronto Western Hospital, Neuroimaging and Telemedicine (LENITEM), Mayo Clinic Jacksonville, Marco Lorenzi received funding from the EPSRC (EP/J020990/1). Jennifer Nicholas is supported by UK Medical Research Council (grant MR/M023664/1). David Cash is supported by grants from the Alzheimer Society(AS-PG-15-025), Alzheimers Research UK (ARUK-PG2014-1946) and Medical Research Council UK (MR/M023664/1). JBR is supported by the Wellcome Trust (103838). Jonathan D. Rohrer is an MRC Clinician Scientist and has received funding from the NIHR Rare Diseases Translational Research Collaboration. Se361 bastien Ourselin receives funding from the EPSRC (EP/H046410/1, EP/K005278), the MRC (MR/J01107X/1), the NIHR Biomedical Research Unit (Dementia) at UCL and the National Institute for Health Research University College London Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact Initiative- BW.mn.BRC10269). Marc Modat is supported by the UCL Leonard Wolfson Experimental Neurology Centre, ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), ANR-15-IDEX-0001,UCA JEDI,Idex UCA JEDI(2015), European Project: 601055,EC:FP7:ICT,FP7-ICT-2011-9,VPH-DARE@IT(2013), European Project: 666992,H2020 Pilier Societal Challenges,H2020-PHC-2015-two-stage,EuroPOND(2016), European Project: 678304,H2020 ERC,ERC-2015-STG,LEASP(2016) |
| المصدر: | ISSN: 1053-8119. |
| بيانات النشر: | HAL CCSD Elsevier |
| سنة النشر: | 2019 |
| المجموعة: | HAL Université Côte d'Azur |
| مصطلحات موضوعية: | Clustering, Thalamus, Spatiotemporal geodesic regression, Parallel transport, Computational anatomy, Shape analysis, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] |
| الوصف: | International audience ; Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimer's disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure.In this paper we propose a spatiotemporal analysis pipeline based on Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects.We found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| العلاقة: | info:eu-repo/semantics/altIdentifier/pmid/30529631; info:eu-repo/grantAgreement/EC/FP7/601055/EU/VPH Dementia Research Enabled by IT/VPH-DARE@IT; info:eu-repo/grantAgreement//666992/EU/Data-driven models for Progression Of Neurological Disease/EuroPOND; info:eu-repo/grantAgreement//678304/EU/Learning spatiotemporal patterns in longitudinal image data sets of the aging brain/LEASP; inserm-01958916; https://inserm.hal.science/inserm-01958916Test; https://inserm.hal.science/inserm-01958916/documentTest; https://inserm.hal.science/inserm-01958916/file/Spatio_temporal_analysis_GENFI_lastSub_black.pdfTest; PUBMED: 30529631 |
| DOI: | 10.1016/j.neuroimage.2018.11.063 |
| الإتاحة: | https://doi.org/10.1016/j.neuroimage.2018.11.063Test https://inserm.hal.science/inserm-01958916Test https://inserm.hal.science/inserm-01958916/documentTest https://inserm.hal.science/inserm-01958916/file/Spatio_temporal_analysis_GENFI_lastSub_black.pdfTest |
| حقوق: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.572FE032 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.neuroimage.2018.11.063 |
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