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1. Association of plasma YKL-40 with brain amyloid-β levels, memory performance, and sex in subjective memory complainers

Author

Andrea Vergallo, Simone Lista, Pablo Lemercier, Patrizia A. Chiesa, Henrik Zetterberg, Kaj Blennow, Marie-Claude Potier, Marie-Odile Habert, Filippo Baldacci, Enrica Cavedo, Filippo Caraci, Bruno Dubois, Harald Hampel, Hovagim Bakardjian, Habib Benali, Hugo Bertin, Joel Bonheur, Laurie Boukadida, Nadia Boukerrou, Patrizia Chiesa, Olivier Colliot, Marion Dubois, Stéphane Epelbaum, Geoffroy Gagliardi, Remy Genthon, Marion Houot, Aurélie Kas, Foudil Lamari, Marcel Levy, Christiane Metzinger, Fanny Mochel, Francis Nyasse, Catherine Poisson, Marie Revillon, Antonio Santos, Katia Santos Andrade, Marine Sole, Mohmed Surtee, Michel Thiebaut de Schotten, Nadjia Younsi, Mohammad Afshar, Lisi Flores Aguilar, Leyla Akman-Anderson, Joaquín Arenas, Jesús Ávila, Claudio Babiloni, Richard Batrla, Norbert Benda, Keith L. Black, Arun L.W. Bokde, Ubaldo Bonuccelli, Karl Broich, Francesco Cacciola, Giuseppe Caruso, Juan Castrillo†, Roberto Ceravolo, Massimo Corbo, Jean-Christophe Corvol, Augusto Claudio Cuello, Jeffrey L. Cummings, Herman Depypere, Andrea Duggento, Enzo Emanuele, Valentina Escott-Price, Howard Federoff, Maria Teresa Ferretti, Massimo Fiandaca, Richard A. Frank, Francesco Garaci, Hugo Geerts, Ezio Giacobini, Filippo S. Giorgi, Edward J. Goetzl, Manuela Graziani, Marion Haberkamp, Britta Hänisch, Karl Herholz, Felix Hernandez, Bruno P. Imbimbo, Dimitrios Kapogiannis, Eric Karran, Steven J. Kiddle, Seung H. Kim, Yosef Koronyo, Maya Koronyo-Hamaoui, Todd Langevin, Stéphane Lehéricy, Francisco Llavero, Jean Lorenceau, Alejandro Lucía, Dalila Mango, Mark Mapstone, Christian Neri, Robert Nisticò, Sid E. O’bryant, Giovanni Palermo, George Perry, Craig Ritchie, Simone Rossi, Amira Saidi, Emiliano Santarnecchi, Lon S. Schneider, Olaf Sporns, Nicola Toschi, Pedro L. Valenzuela, Bruno Vellas, Steven R. Verdooner, Nicolas Villain, Kelly Virecoulon Giudici, Mark Watling, Lindsay A. Welikovitch, Janet Woodcock, Erfan Younesi, José L. Zugaza, Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), 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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
musculoskeletal diseases, 0301 basic medicine, Apolipoprotein E, Male, Risk, Aging, medicine.medical_specialty, Amyloid, YKL-40, [SDV]Life Sciences [q-bio], Disease, 03 medical and health sciences, Alzheimer's disease, amyloid, neuroinflammation, Sex, 0302 clinical medicine, Neuroinflammation, Alzheimer Disease, Memory, Internal medicine, medicine, Premovement neuronal activity, Humans, Effects of sleep deprivation on cognitive performance, Chitinase-3-Like Protein 1, Longitudinal Studies, Inflammation, Amyloid beta-Peptides, business.industry, General Neuroscience, Neurodegeneration, Settore FIS/07, Brain, medicine.disease, 030104 developmental biology, Endocrinology, Biomarker (medicine), Female, Neurology (clinical), Geriatrics and Gerontology, business, Alzheimer’s disease, 030217 neurology & neurosurgery, Biomarkers, Developmental Biology
Abstract

Neuroinflammation, a key early pathomechanistic alteration of Alzheimer’s disease, may represent either a detrimental or a compensatory mechanism or both (according to the disease stage). YKL-40, a glycoprotein highly expressed in differentiated glial cells, is a candidate biomarker for in vivo tracking neuroinflammation in humans. We performed a longitudinal study in a monocentric cohort of cognitively healthy individuals at risk for Alzheimer’s disease exploring whether age, sex, and the apolipoprotein E e4 allele affect plasma YKL-40 concentrations. We investigated whether YKL-40 is associated with brain amyloid-β (Aβ) deposition, neuronal activity, and neurodegeneration as assessed via neuroimaging biomarkers. Finally, we investigated whether YKL-40 may predict cognitive performance. We found an age-associated increase of YKL-40 and observed that men display higher concentrations than women, indicating a potential sexual dimorphism. Moreover, YKL-40 was positively associated with memory performance and negatively associated with brain Aβ deposition (but not with metabolic signal). Consistent with translational studies, our results suggest a potentially protective effect of glia on incipient brain Aβ accumulation and neuronal homeostasis.

Published
2020
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2. Parietal Involvement in the Semantic Variant of Primary Progressive Aphasia with Alzheimer’s Disease Cerebrospinal Fluid Profile

Author

Géraldine Bera, Marie-Odile Habert, Sophie Ferrieux, Hugo Bertin, Bruno Dubois, Thibaut Michelin, Foudil Lamari, Aurélie Kas, Marc Teichmann, Raffaella Migliaccio, and Marie Nogues

Subjects
Male, 0301 basic medicine, Pathology, medicine.medical_specialty, Perfusion scanning, Disease, Primary progressive aphasia, 03 medical and health sciences, 0302 clinical medicine, Cerebrospinal fluid, Alzheimer Disease, Parietal Lobe, Humans, Medicine, Aged, Tomography, Emission-Computed, Single-Photon, business.industry, General Neuroscience, Parietal lobe, General Medicine, Middle Aged, medicine.disease, Semantics, Psychiatry and Mental health, Clinical Psychology, Aphasia, Primary Progressive, 030104 developmental biology, Posterior cingulate, Biomarker (medicine), Female, Geriatrics and Gerontology, business, Perfusion, Biomarkers, 030217 neurology & neurosurgery
Abstract

Semantic variant of primary progressive aphasia (svPPA) is typically associated with non-Alzheimer's disease (AD) pathology. However, some anatomopathological studies have found AD lesions in those patients. We compared brain perfusion SPECT of 18 svPPA patients with cerebrospinal fluid (CSF) biomarkers indicative of non-AD pathology (svPPA-nonAD) and three svPPA patients with CSF biomarkers indicative of underlying AD (svPPA-AD). All svPPA patients had severe left temporopolar hypoperfusion. SvPPA-nonAD had additional anterior cingulate and mediofrontal hypoperfusion, whereas svPPA-AD had greater left parietal and posterior cingulate involvement. Parietal damage in svPPA constitutes a biomarker for underlying Alzheimer pathology thus refining the classification of this PPA variant.

Published
2018
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3. Evaluation of amyloid status in a cohort of elderly individuals with memory complaints: validation of the method of quantification and determination of positivity thresholds

Author

Bruno Dubois, Stéphane Epelbaum, Valérie Causse-Lemercier, Kelly Martineau, Marion Houot, Marie-Odile Habert, Mamadou Hassimiou Diallo, Gaël Chételat, Jean-François Mangin, Hugo Bertin, Aurélie Kas, Mickael Labit, H. Hampel, Sullivan Marie, Hovagim Bakardjian, Institut de Mécanique et d'Ingénierie de Bordeaux (I2M), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), CATI Multicenter Neuroimaging Platform (CATI), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Neuropsychologie cognitive et neuroanatomie fonctionnelles de la mémoire humaine, Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Service de médecine nucléaire [CHU Pitié-Salpétrière], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC), Institut National de la Santé et de la Recherche Médicale (INSERM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Polytechnique de Bordeaux-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB), Service de médecine nucléaire [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Institut National de la Santé et de la Recherche Médicale (INSERM)-École pratique des hautes études (EPHE)-Université de Caen Normandie (UNICAEN), Service de neurologie 1 [CHU Pitié-Salpétrière], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [APHP], HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Institut National de la Recherche Agronomique (INRA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de Médecine nucléaire [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Normandie Université (NU)-Normandie Université (NU)-École pratique des hautes études (EPHE), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, Amyloid, medicine.medical_specialty, Population, Partial volume, Audiology, 030218 nuclear medicine & medical imaging, Correlation, 03 medical and health sciences, Cognition, 0302 clinical medicine, Memory, Reference Values, Image Processing, Computer-Assisted, medicine, Humans, Radiology, Nuclear Medicine and imaging, Young adult, 10. No inequality, Cognitive impairment, education, ComputingMilieux_MISCELLANEOUS, Aged, education.field_of_study, Aniline Compounds, medicine.diagnostic_test, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, General Medicine, Positron emission tomography, Positron-Emission Tomography, Cohort, Ethylene Glycols, Female, business, Software, 030217 neurology & neurosurgery
Abstract

Our aim is to validate the process steps implemented by the French CATI platform to assess amyloid status, obtained from 18F-Florbetapir PET scans, in a cohort of 318 cognitively normal subjects participating in the INSIGHT-preAD study. Our objective was to develop a method with partial volume effect correction (PVEC) on untransformed PET images, using an automated pipeline (“RACHEL”) adapted to large series of patients and including quality checks of results. We compared RACHEL using different options (with and without PVEC, different sets of regions of interest), to two other methods validated in the literature, referred as the “AVID” and “CAEN” methods. A standard uptake value ratio (SUVR) was obtained with the different methods for participants to another French study, IMAP, including 26 normal elderly controls (NEC), 11 patients with mild cognitive impairment (MCI) and 16 patients with Alzheimer’s disease (AD). We determined two cutoffs for RACHEL method by linear correlation with the other methods and applied them to the INSIGHT-preAD subjects. RACHEL including PVEC and a combination of the whole cerebellum and the pons as a reference region allowed the best discrimination between NEC and AD participants. A strong linear correlation was found between RACHEL and the other two methods and yielded the two cutoffs of 0.79 and 0.88. According to the more conservative threshold, 19.8% of the INSIGHT-preAD subjects would be considered amyloid positive, and 27.7% according to the more liberal threshold. With our method, we clearly discriminated between NEC with negative amyloid status and patients with clinical AD. Using a linear correlation with other validated cutoffs, we could infer our own positivity thresholds and apply them to an independent population. This method might be useful to the community, especially when the optimal cutoff could not be obtained from a population of healthy young adults or from correlation with post-mortem results.

Published
2017
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4. Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease

Author

Geoffroy Gagliardi, Roberto Ceravolo, Herman Depypere, Bruno Dubois, Fanny Mochel, Christiane Metzinger, George L. W. Perry, Marine Sole, Massimo S. Fiandaca, Amira Saidi, E. Cavedo, Patrizia Andrea Chiesa, Thiebaud de Schotten M, Juan I. Castrillo, Jean Lorenceau, Jeffrey L. Cummings, Craig W. Ritchie, Ubaldo Bonuccelli, Francesco Cacciola, Arun L.W. Bokde, F. Lamari, Keith L. Black, Marion Haberkamp, Jean-Christophe Corvol, Ann De Vos, Maya Koronyo-Hamaoui, Filippo Sean Giorgi, Todd Langevin, H. Hampel, Richard Frank, Stéphane Epelbaum, Mohmed Surtee, Remy Genthon, Nadjia Younsi, Olaf Sporns, Harald Hampel, Marion Dubois, Filippo Baldacci, Lindsay A. Welikovitch, Karl Broich, Stéphane Lehéricy, Henrik Zetterberg, M.O. Habert, Manuela Graziani, Janet Woodcock, S. Lista, Aurélie Kas, Lon S. Schneider, Katia Andrade, Robert Nisticò, Simone Rossi, Foudil Lamari, Howard J. Federoff, Francis Nyasse, Enrica Cavedo, Lisi Flores Aguilar, Erfan Younesi, M.C. Potier, Seung Hyun Kim, Karl Herholz, Nadia Boukerrou, Lucile Megret, Catherine Poisson, Claudio Babiloni, A.C. Cuello, Dalila Mango, Antonio Melo dos Santos, Norbert Benda, Marcel Levy, A. Vergallo, Patrizia A. Chiesa, Sid E. O'Bryant, Marie Revillon, Nicola Toschi, Hugo Geerts, Maria Teresa Ferretti, Mark Mapstone, Kaj Blennow, Eugeen Vanmechelen, Simone Lista, Marie-Odile Habert, Marie-Claude Potier, Eric Karran, Nicolas Villain, Laurie Boukadida, Emiliano Santarnecchi, Yosef Koronyo, Olivier Colliot, Habib Benali, Hugo Bertin, Valentina Escott-Price, Andrea Duggento, Steven Verdooner, Andrea Vergallo, Christian Neri, Joel Bonheur, Francesco Garaci, Hovagim Bakardjian, Marion Houot, Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), 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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Adaptation Biologique et Vieillissement = Biological Adaptation and Ageing (B2A), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Oncology, Epidemiology, [SDV]Life Sciences [q-bio], Simoa immunoassay, Disease, Cohort Studies, Classification and regression trees (CART), Cognition, 0302 clinical medicine, medicine.diagnostic_test, Health Policy, Amyloidosis, Settore FIS/07, Brain, Alzheimer's disease, 3. Good health, Psychiatry and Mental health, Positron emission tomography, Cohort, Female, Amyloid PET, Machine learning, Plasma amyloid β, Subjective memory complainers, medicine.medical_specialty, 03 medical and health sciences, Cellular and Molecular Neuroscience, Developmental Neuroscience, Alzheimer Disease, Memory, Internal medicine, medicine, Humans, Aged, Amyloid beta-Peptides, Receiver operating characteristic, business.industry, Clinical study design, medicine.disease, Peptide Fragments, Clinical trial, Cerebral Amyloid Angiopathy, 030104 developmental biology, Positron-Emission Tomography, Neurology (clinical), Geriatrics and Gerontology, business, Biomarkers, 030217 neurology & neurosurgery
Abstract

Introduction Blood-based biomarkers of pathophysiological brain amyloid β (Aβ) accumulation, particularly for preclinical target and large-scale interventions, are warranted to effectively enrich Alzheimer's disease clinical trials and management. Methods We investigated whether plasma concentrations of the Aβ 1–40 /Aβ 1–42 ratio, assessed using the single-molecule array (Simoa) immunoassay, may predict brain Aβ positron emission tomography status in a large-scale longitudinal monocentric cohort (N = 276) of older individuals with subjective memory complaints. We performed a hypothesis-driven investigation followed by a no-a-priori hypothesis study using machine learning. Results The receiver operating characteristic curve and machine learning showed a balanced accuracy of 76.5% and 81%, respectively, for the plasma Aβ 1–40 /Aβ 1–42 ratio. The accuracy is not affected by the apolipoprotein E ( APOE ) e4 allele, sex, or age. Discussion Our results encourage an independent validation cohort study to confirm the indication that the plasma Aβ 1–40 /Aβ 1–42 ratio, assessed via Simoa, may improve future standard of care and clinical trial design.

Published
2019
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5. Performance characteristics of silicon photomultiplier based 15-cm AFOV TOF PET/CT

Author

Jorge Uribe, Hugo Bertin, Delphine Vandendriessche, and Frank De Geeter

Subjects
lcsh:Medical physics. Medical radiology. Nuclear medicine, Point spread function, Photomultiplier, Image quality, lcsh:R895-920, Biomedical Engineering, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Silicon photomultiplier, Optics, Ordered subset expectation maximization, Silicon photomultiplier based PET/CT, Radiology, Nuclear Medicine and imaging, Time-of-flight PET/CT, Instrumentation, Image resolution, Original Research, Physics, Radiation, NEMA, business.industry, Full width at half maximum, 030220 oncology & carcinogenesis, business, Discovery MI 3-ring
Abstract

Background This paper describes the National Electrical Manufacturers Association (NEMA) system performance of the Discovery MI 3-ring PET/CT (GE Healthcare) installed in Bruges, Belgium. This time-of-flight (TOF) PET camera is based on silicon photomultipliers instead of photomultiplier tubes. Methods The NEMA NU2-2012 standard was used to evaluate spatial resolution, sensitivity, image quality (IQ) and count rate curves of the system. Timing and energy resolution were determined. Results Full width at half maximum (FWHM) of spatial resolution in radial, tangential and axial direction was 4.69, 4.08 and 4.68 mm at 1 cm; 5.58, 4.64 and 5.83 mm at 10 cm; and 7.53, 5.08 and 5.47 mm at 20 cm from the centre of the field of view (FOV) for the filtered backprojection reconstruction. For non-TOF ordered subset expectation maximization (OSEM) reconstruction without point spread function (PSF) correction, FWHM was 3.87, 3.69 and 4.15 mm at 1 cm; 4.80, 3.81 and 4.87 mm at 10 cm; and 7.38, 4.16 and 3.98 mm at 20 cm. Sensitivity was 7.258 cps/kBq at the centre of the FOV and 7.117 cps/kBq at 10-cm radial offset. Contrast recovery (CR) using the IQ phantom for the TOF OSEM reconstruction without PSF correction was 47.4, 59.3, 67.0 and 77.0% for the 10-, 13-, 17- and 22-mm radioactive spheres and 82.5 and 85.1% for the 28- and 37-mm non-radioactive spheres. Background variability (BV) was 16.4, 12.1, 9.1, 6.6, 5.1 and 3.8% for the 10-, 13-, 17-, 22-, 28- and 37-mm spheres. Lung error was 8.5%. Peak noise equivalent count rate (NECR) was 102.3 kcps at 23.0 kBq/ml with a scatter fraction of 41.2%. Maximum accuracy error was 3.88%. Coincidence timing resolution was 375.6 ps FWHM. Energy resolution was 9.3% FWHM. Q.Clear reconstruction significantly improved CR and reduced BV compared with OSEM. Conclusion System sensitivity and NECR are lower and IQ phantom’s BV is higher compared with larger axial FOV (AFOV) scanners like the 4-ring discovery MI, as expected from the smaller solid angle of the 3-ring system. The other NEMA performance parameters are all comparable with those of the larger AFOV scanners.

Published
2019

6. Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study

Author

Gaëlle Fontaine, Marie Lhomme, Arthur Tenenhaus, Stéphane Epelbaum, Laura Xicota, Inka Leroy, Marie-Claude Potier, François-Xavier Lejeune, Farid Ichou, Benoit Colsch, Bruno Dubois, Hugo Bertin, Marie-Odile Habert, Fanny Mochel, 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), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service de Pharmacologie et Immunoanalyse (SPI), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), CentraleSupélec, Université Paris-Saclay, Centre d'Acquisition et de Traitement des Images [Paris], Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre des Maladies Cognitives et Comportementales [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-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)-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)-Centre National de la Recherche Scientifique (CNRS), AvidFondation AlzheimerThis study was supported by INSERM in collaboration with Institut du Cerveau et de la Moelle Épinière (ICM), Institut Hospitalo-Universitaire-A ICM, and Pfizer, and was supported with funding from Pfizer and the Investissement d'Avenir (ANR-10-AIHU-06) that was used for the recruitment of clinical research assistants, neuropsychologists, and a study physician, ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Sorbonne Université (SU), Laboratoire d'Etude du Métabolisme des Médicaments (LEMM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Médicaments et Technologies pour la Santé (MTS), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Avid, Fondation Alzheimer, This study was supported by INSERM in collaboration with Institut du Cerveau et de la Moelle Épinière (ICM), Institut Hospitalo-Universitaire-A ICM, and Pfizer, and was supported with funding from Pfizer and the Investissement d'Avenir (ANR-10-AIHU-06) that was used for the recruitment of clinical research assistants, neuropsychologists, and a study physician, ANR-10-IAIHU-06,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2011), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU), CEA Paris Saclay, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de Pharmacologie et d'Immunoanalyse (SPI), Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Potier, Marie-Claude, Unité Matériaux et Transformations - UMR 8207 (UMET), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Nationale Supérieure de Chimie de Lille (ENSCL)-Institut National de la Recherche Agronomique (INRA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), sans affiliation, Pfizer, Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), Ministry of Research, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Gestionnaire, Hal Sorbonne Université, and Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID

Subjects
0301 basic medicine, Oncology, Male, Proteomics, Research paper, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], 050207 economics, Aged, 80 and over, Univariate analysis, [STAT.AP]Statistics [stat]/Applications [stat.AP], Multi-omics, 050208 finance, 05 social sciences, Brain, General Medicine, Genomics, 3. Good health, Asymptomatic, 030220 oncology & carcinogenesis, Area Under Curve, Cohort, Female, medicine.symptom, [STAT.ME]Statistics [stat]/Methodology [stat.ME], medicine.medical_specialty, Amyloid, Protein Aggregation, Pathological, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Metabolomics, Alzheimer Disease, Internal medicine, Lipidomics, 0502 economics and business, medicine, Humans, Alzheimer, Amyloid PET, Biomarkers, Prediction, Aged, Amyloid beta-Peptides, Receiver operating characteristic, business.industry, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Omics, 030104 developmental biology, Case-Control Studies, business
Abstract

International audience; BACKGROUND: One of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load.METHODS: We performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects.FINDINGS: Univariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p

Published
2019
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7. P3‐411: CLINICAL SIGNIFICANCE OF IN‐VIVO STAGING OF REGIONAL AMYLOID DEPOSITION IN SUBJECTIVE MEMORY COMPLAINERS

Author

Enrica Cavedo, Fatemah A. Sakr, Stéphane Lehéricy, Hugo Bertin, Michel J. Grothe, Harald Hampel, Marie-Odile Habert, Stefan J. Teipel, Maxime Locatelli, and Bruno Dubois

Subjects
Oncology, 0303 health sciences, medicine.medical_specialty, Epidemiology, business.industry, Health Policy, Subjective memory, 03 medical and health sciences, Psychiatry and Mental health, Cellular and Molecular Neuroscience, 0302 clinical medicine, Amyloid deposition, Developmental Neuroscience, In vivo, Internal medicine, medicine, Clinical significance, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, 030304 developmental biology
Published
2018
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8. Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers: An INSIGHT-preAD study

Author

Stéphane Epelbaum, M. Kilani, S. Cherif Touil, Bruno Dubois, M. Thiebaut, M.C. Potier, G. Dalla Barba, K. Santos-Andrade, R. Schindler, V. Simon, Stéphane Lehéricy, Catherine Poisson, V. Causse, Olga Uspenskaya, Fanny Mochel, H. Hewa, H. Francisque, I. Masetti, Laurie Boukadida, M. Vlaincu, Patrizia A. Chiesa, A. Mendes, Federica Cacciamani, Michael D. Greicius, Michel J. Grothe, Luisa Sambati, Aurélie Kas, A. Genin, F. Gombert, S. Lista, S. Ratovohery, S. Epelbaum, Marie-Claude Potier, B. Fontaine, J. Ly, P. Glasman, G. Gagliardi, Simone Lista, F. Poirier, Marie-Odile Habert, M.O. Habert, Marion Dubois, Stefan J. Teipel, Katrine Rojkova, Habib Benali, Harald Hampel, M. Lowrey, C. Audrain, M.C. Servera, D. Skovronsky, Francis Nyasse, Remy Genthon, Marcel Levy, Marie Revillon, R. Nait Arab, Geoffroy Gagliardi, A. Michon, Nicola Toschi, A. Dos Santos, Marion Houot, V. La Corte, M. Depaulis, Enrica Cavedo, Anne Bertrand, Olivier Colliot, A. Auffret, O. Makiese, C. Perrin, Hovagim Bakardjian, Bénédicte Batrancourt, Hugo Bertin, Filippo Baldacci, L. Seux, Christiane Metzinger, N. Jungalee, C. Letondor, F. Le Roy, I. Benakki, Teipel, Stefan J, Cavedo, Enrica, Lista, Simone, Habert, Marie-Odile, Potier, Marie-Claude, Grothe, Michel J, Epelbaum, Stephane, Sambati, Luisa, Gagliardi, Geoffroy, Toschi, Nicola, Greicius, Michael D, Dubois, Bruno, Hampel, Harald, and Dalla Barba, Gianfranco

Subjects
Male, psychology [Alzheimer Disease], Epidemiology, epidemiology [Alzheimer Disease], Hippocampus, Subjective memory, Disease, Preclinical Alzheimer's disease, 0302 clinical medicine, Cognition, pathology [Brain], Longitudinal Studies, Cholinergic basal forebrain, Aged, 80 and over, Health Policy, Settore FIS/07, 05 social sciences, Brain, metabolism [Memory Disorders], Organ Size, Amyloid PET, Longitudinal cognitive change, Psychiatry and Mental health, Cohort, Disease Progression, Educational Status, Female, Psychology, metabolism [Alzheimer Disease], Cognitive psychology, Amyloid, diagnostic imaging [Memory Disorders], 050105 experimental psychology, 03 medical and health sciences, Cellular and Molecular Neuroscience, Diagnostic Self Evaluation, Hippocampu, Atrophy, Apolipoproteins E, Developmental Neuroscience, Alzheimer Disease, Cognitive change, medicine, Humans, 0501 psychology and cognitive sciences, ddc:610, diagnostic imaging [Brain], epidemiology [Memory Disorders], Aged, metabolism [Amyloid], Memory Disorders, Protective Factors, medicine.disease, Nonlinear Dynamics, metabolism [Brain], Disease risk, genetics [Apolipoproteins E], Neurology (clinical), Geriatrics and Gerontology, diagnostic imaging [Alzheimer Disease], 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

Introduction Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals. Methods We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes. Results Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories. Discussion Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.

Published
2018
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9. Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study

Author

Foudil Lamari, Marion Houot, Habib Benali, Fanny Mochel, Christiane Metzinger, Catherine Poisson, Stéphane Epelbaum, Marcel Levy, Valentina La Corte, Claire Letondor, Agnès Michon, Geoffroy Gagliardi, Francis Nyasse, Pauline Glasman, Marie-Claude Potier, Filippo Baldacci, Valérie Simon, Alexis Genin, Olga Uspenskaya, Juliette Ly, Gaëlle Fontaine, Simone Lista, Bruno Dubois, Maya Kilani, Enrica Cavedo, Nadjia Younsi, Caroline Tandetnik, Jean-François Mangin, Alexandra Auffret, Rachel Schindler, Marie-Odile Habert, Katia Santos-Andrade, Marine Sole, Antonio Melo dos Santos, Marion Dubois, Aurélie Kas, Anne Bertrand, Katrine Rojkova, Laurie Boukadida, Marie Revillon, Laure Seux, Stanley Durrleman, Marc Teichmann, Harald Hampel, Olivier Colliot, Stephie Ratovohery, Remy Genthon, Navichka Jungalee, Federica Cacciamani, Michel Thiebaut de Shotten, Ismahane Benakki, Patrizia A. Chiesa, Perrine Roy, Hovagim Bakardjian, Ornella Makiese, Luce Dauphinot, Christelle Audrain, Hugo Bertin, Mark Lowrey, Stéphane Lehéricy, Centre des Maladies Cognitives et Comportementales [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-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 et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), IQVIA, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Biochimie Métabolique [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, 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)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), 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)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Clinical Dementia Rating, Brain Structure and Function, Neuroimaging, Neuropsychological Tests, 03 medical and health sciences, 0302 clinical medicine, Cognition, Functional neuroimaging, Alzheimer Disease, Risk Factors, Internal medicine, medicine, Humans, Longitudinal Studies, Cognitive decline, Aged, Aged, 80 and over, Amyloid beta-Peptides, business.industry, Amyloidosis, [SCCO.NEUR]Cognitive science/Neuroscience, Neuropsychology, Brain, Actigraphy, medicine.disease, Magnetic Resonance Imaging, 3. Good health, 030104 developmental biology, Positron-Emission Tomography, Female, Neurology (clinical), business, 030217 neurology & neurosurgery, Executive dysfunction
Abstract

For the INSIGHT-preAD study group; International audience; Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimer's disease. We assessed associations between brain β-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimer's disease.The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70–85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid β deposition on 18F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on 18F-fluorodeoxyglucose (18F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and 18F-FDG and 18F-florbetapir PET every 24 months. We assessed associations of amyloid β deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimer's disease was defined as an amnestic syndrome of the hippocampal type From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1–8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid β deposition and the remainder did not. The amyloid β subgroups did not differ for any psychobehavioural, cognitive, actigraphy, and structural and functional neuroimaging results after adjustment for age, sex, and level of education More participants positive for amyloid β deposition had the APOE ε4 allele (33 [38%] vs 29 [13%], p

Published
2018
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10. Multimorbidity Is Associated with Preclinical Alzheimer's Disease Neuroimaging Biomarkers

Author

Stéphane Epelbaum, Aline Mendes, Anne Bertrand, Bruno Dubois, Hugo Bertin, Sophie Tezenas du Montcel, Marie-Odile Habert, Marcel Levy, Hôpital Universitaire de Genève, Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Sorbonne Université - Faculté de Médecine (SU FM), Sorbonne Université (SU), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), 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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neuroradiologie [CHU Pitié-Salpêtrière], Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-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 et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Service de Médecine nucléaire [CHU Pitié-Salpétrière], Hôpital Universitaire de Genève = University Hospitals of Geneva (HUG), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), 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), 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)-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)-Centre National de la Recherche Scientifique (CNRS), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de médecine nucléaire [CHU Pitié-Salpétrière], Service de neurologie 1 [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Oncology, Male, medicine.medical_specialty, Amyloid, Cognitive Neuroscience, [SDV]Life Sciences [q-bio], Neuroimaging, Comorbidity, Neuroimaging biomarkers, Hippocampus, 03 medical and health sciences, 0302 clinical medicine, Cognition, Alzheimer Disease, Internal medicine, medicine, Dementia, Humans, Prospective Studies, Neurodegeneration, Prospective cohort study, Aged, Aged, 80 and over, medicine.diagnostic_test, business.industry, Neuropsychology, Multimorbidity, Alzheimer's disease, medicine.disease, 3. Good health, Obstructive sleep apnea, Psychiatry and Mental health, 030104 developmental biology, Cross-Sectional Studies, Mood disorders, Positron emission tomography, Positron-Emission Tomography, ddc:618.97, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Female, Geriatrics and Gerontology, business, Alzheimer’s disease, 030217 neurology & neurosurgery, Biomarkers
Abstract

Background: Identifying comorbidities that influence preclinical Alzheimer’s disease (AD) can give some insight into the AD early stages trajectories to allow new treatment venues and to guide public health systems to prevent subsequent dementia. Objective: To examine the association of multimorbidity with AD neuroimaging markers in cognitively normal older adults. Methods: This study had a cross-sectional design. Data regarding 14 comorbidities were obtained for all 318 adults aged 70–85 years, recruited from the community to an ongoing prospective monocentric cohort. They underwent standardized neuropsychological and neuroimaging assessment with automated methods that measured hippocampal volumes, white matter hyperintensity volumes, fluorodeoxyglucose positron emission tomography (FDG-PET) standardized uptake values (SUV) in AD signature regions, and amyloid positron emission tomography (amyloid-PET) SUV ratios. Linear regression was used to assess the association of multimorbidity with AD neuroimaging biomarkers. Results: Multimorbidity is signif icantly associated with lower hippocampal volumes (–0.03 ± 0.01; p = 0.012; R2 = 0.017) and lower FDG-PET SUV (–0.027 ± 0.009; p = 0.005; R2 = 0.022), with no association with amyloid deposition (0.001 ± 0.007; p = 0.884; R2 = 0.0001). Taken individually, obesity and excessive alcohol use are associated with lower FDG-PET values, whereas obstructive sleep apnea and mood disorders are related to lower amyloid-PET SUV ratios. Conclusion: Multimorbidity is associated with preclinical AD imaging markers of neurodegeneration, but not with amyloid.

Published
2017
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11. Yet Another ADNI Machine Learning Paper? Paving the Way Towards Fully-Reproducible Research on Classification of Alzheimer’s Disease

Author

Jorge Samper-González, Hugo Bertin, Stanley Durrleman, Sabrina Fontanella, Theodoros Evgeniou, Olivier Colliot, Marie-Odile Habert, and Ninon Burgos

Subjects
Multiple kernel learning, Computer science, business.industry, BETA (programming language), Image (category theory), Data management, Core component, 05 social sciences, Feature extraction, Disease classification, Machine learning, computer.software_genre, 050105 experimental psychology, Support vector machine, 03 medical and health sciences, 0302 clinical medicine, 0501 psychology and cognitive sciences, Artificial intelligence, business, computer, 030217 neurology & neurosurgery, computer.programming_language
Abstract

In recent years, the number of papers on Alzheimer’s disease classification has increased dramatically, generating interesting methodological ideas on the use machine learning and feature extraction methods. However, practical impact is much more limited and, eventually, one could not tell which of these approaches are the most efficient. While over 90% of these works make use of ADNI an objective comparison between approaches is impossible due to variations in the subjects included, image pre-processing, performance metrics and cross-validation procedures. In this paper, we propose a framework for reproducible classification experiments using multimodal MRI and PET data from ADNI. The core components are: (1) code to automatically convert the full ADNI database into BIDS format; (2) a modular architecture based on Nipype in order to easily plug-in different classification and feature extraction tools; (3) feature extraction pipelines for MRI and PET data; (4) baseline classification approaches for unimodal and multimodal features. This provides a flexible framework for benchmarking different feature extraction and classification tools in a reproducible manner. Data management tools for obtaining the lists of subjects in AD, MCI converter, MCI non-converters, CN classes are also provided. We demonstrate its use on all (1519) baseline T1 MR images and all (1102) baseline FDG PET images from ADNI 1, GO and 2 with SPM-based feature extraction pipelines and three different classification techniques (linear SVM, anatomically regularized SVM and multiple kernel learning SVM). The highest accuracies achieved were: 91% for AD vs CN, 83% for MCIc vs CN, 75% for MCIc vs MCInc, 94% for AD-A\(\displaystyle \beta \)+ vs CN-A\(\displaystyle \beta \)- and 72% for MCIc-A\(\displaystyle \beta \)+ vs MCInc-A\(\displaystyle \beta \)+. The code will be made publicly available at the time of the conference (https://gitlab.icm-institute.org/aramislab/AD-ML).

Published
2017
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12. P4‐154: SUSPECTED NON‐ALZHEIMER DISEASE PATHOPHYSIOLOGY (SNAP) CATEGORIZATION IN THE INSIGHT COHORT

Author

Bruno Dubois, Stéphane Epelbaum, Geoffroy Gagliardi, Hugo Bertin, Anne Bertrand, Olivier Colliot, Marcel Levy, Marie-Odile Habert, Aline Mendes, and Marc Teichmann

Subjects
medicine.medical_specialty, Epidemiology, Population, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Developmental Neuroscience, Internal medicine, medicine, Dementia, Cognitive decline, education, Psychiatry, 030304 developmental biology, 0303 health sciences, education.field_of_study, business.industry, Health Policy, Neuropsychology, Snap, medicine.disease, 3. Good health, Psychiatry and Mental health, Cohort, Neurology (clinical), Geriatrics and Gerontology, Alzheimer's disease, business, Neurocognitive, 030217 neurology & neurosurgery
Abstract

Background Suspected non-Alzheimer disease pathophysiology (SNAP) individuals are participants to studies on Alzheimer’s disease (AD) biomarkers that are considered positive for markers of neurodegeneration and negative for markers of brain amyloidosis in the absence of a major neurocognitive disorder. This concept probably encompasses numerous neurological diseases in which the mildness of symptoms is responsible for a generic term to be proposed instead of a diagnosis. Methods We categorized SNAP subjects in the INSIGHT cohort, a mono-centric French cohort at the University Salpetriere Hospital in Paris including 317 individuals with subjective cognitive decline (SCD) between 70-85 year. Standardized demographic, cognitive, MRI, 18FDG and AV45 PET imaging were performed in each subject. The SNAP population was determined based on cut-offs scores adapted from the literature. Each SNAP participant’s complete medical file was analyzed by an expert committee comprised of 3 neurologists, 1 geriatrician, 1 neuropsychologist, 1 neuroradiologist and 1 nuclear medicine MD. Diagnostic algorithms were adapted from international consensus criteria for various neurological conditions (eg Rascovsky’s criteria for Fronto-temporal dementia). Results Among the INSIGHT participants, 88 are considered amyloid (+) with a significantly increased cortical uptake of the tracer above threshold on PET imaging, and 229 are amyloid (-). The 229 amyloid negative individuals were categorized in 4 groups determined by their clinico-radiological status: Healthy control, SNAP-AD when neurodegeneration was suggestive of AD, SNAP-NONAD when the neurodegeneration was incompatible with typical AD and SNAP-MIXED in all other participants. We have then applied our diagnostic procedure in the SNAP participants to determine if this group can be divided into known neurological diseases. Conclusions This is one of the first attempts to refine the diagnostic procedure in SNAP, a frequent condition in the elderly population. Similarly to AD, a presymptomatic/early symptomatic phase of different brain affections can be diagnosed instead of using the SNAP acronym.

Published
2016
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13. Optimization of brain PET imaging for a multicentre trial: the French CATI experience

Author

Sullivan Marie, Jean-Baptiste Martini, Mamadou Hassimiou Diallo, Marie-Odile Habert, Aurélie Kas, Hugo Bertin, Regine Trebossen, Moana Reynal, Laboratoire d'Imagerie Biomédicale (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre pour l'Acquisition et le Traitement des Images (CATI), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service Hospitalier Frédéric Joliot (SHFJ), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), and d'Eggis, Gilles

Subjects
medicine.medical_specialty, PET/CT, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Biomedical Engineering, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, medicine, Radiology, Nuclear Medicine and imaging, Medical physics, Instrumentation, Original Research, PET-CT, Radiation, business.industry, Multicentre trials, Pet imaging, Quality assurance, Standardization, Large cohort, Neurology, Cohort, Test protocol, business, 030217 neurology & neurosurgery
Abstract

International audience; BackgroundCATI is a French initiative launched in 2010 to handle the neuroimaging of a large cohort of subjects recruited for an Alzheimer’s research program called MEMENTO. This paper presents our test protocol and results obtained for the 22 PET centres (overall 13 different scanners) involved in the MEMENTO cohort. We determined acquisition parameters using phantom experiments prior to patient studies, with the aim of optimizing PET quantitative values to the highest possible per site, while reducing, if possible, variability across centres.MethodsJaszczak’s and 3D-Hoffman’s phantom measurements were used to assess image spatial resolution (ISR), recovery coefficients (RC) in hot and cold spheres, and signal-to-noise ratio (SNR). For each centre, the optimal reconstruction parameters were chosen as those maximizing ISR and RC without a noticeable decrease in SNR. Point-spread-function (PSF) modelling reconstructions were discarded. The three figures of merit extracted from the images reconstructed with optimized parameters and routine schemes were compared, as were volumes of interest ratios extracted from Hoffman acquisitions. The net effect of the 3D-OSEM reconstruction parameter optimization was investigated on a subset of 18 scanners without PSF modelling reconstruction.ResultsCompared to the routine parameters of the 22 PET centres, average RC in the two smallest hot and cold spheres and average ISR remained stable or were improved with the optimized reconstruction, at the expense of slight SNR degradation, while the dispersion of values was reduced.For the subset of scanners without PSF modelling, the mean RC of the smallest hot sphere obtained with the optimized reconstruction was significantly higher than with routine reconstruction. The putamen and caudate-to-white matter ratios measured on 3D-Hoffman acquisitions of all centres were also significantly improved by the optimization, while the variance was reduced.ConclusionsThis study provides guidelines for optimizing quantitative results for multicentric PET neuroimaging trials.

Published
2015
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14. Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

Author

Junhao Wen, Ninon Burgos, Sabrina Fontanella, Michael Bacci, Marie-Odile Habert, Pascal Lu, Theodoros Evgeniou, Hugo Bertin, Jorge Samper-González, Olivier Colliot, Arnaud Marcoux, Anne Bertrand, Alexandre Routier, Jérémy Guillon, Simona Bottani, Stanley Durrleman, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-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 et de la Moëlle Epinière = Brain and Spine Institute (ICM), 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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neuroradiologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de médecine nucléaire [CHU Pitié-Salpétrière], Institut Européen d'administration des Affaires (INSEAD), Algorithms, models and methods for images and signals of the human brain ( ARAMIS ), Universit?? Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut du Cerveau et de la Mo??lle Epini??re = Brain and Spine Institute ( ICM ), Universit?? Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Sant?? et de la Recherche M??dicale ( INSERM ) -CHU Piti??-Salp??tri??re [APHP]-Centre National de la Recherche Scientifique ( CNRS ) -Universit?? Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Sant?? et de la Recherche M??dicale ( INSERM ) -CHU Piti??-Salp??tri??re [APHP]-Centre National de la Recherche Scientifique ( CNRS ) -Inria de Paris, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Service de neuro-radiologie [CHU Piti??-Salp??tri??re], Assistance publique - H??pitaux de Paris (AP-HP)-CHU Piti??-Salp??tri??re [APHP], Laboratoire d'Imagerie Biom??dicale ( LIB ), Universit?? Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Sant?? et de la Recherche M??dicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Service de m??decine nucl??aire [CHU Piti??-Salp??tri??re], Institut Europ??en d'administration des Affaires ( INSEAD ), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), 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)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Samper-Gonzalez, Jorge, and Service de Médecine nucléaire [CHU Pitié-Salpétrière]

Subjects
FOS: Computer and information sciences, Male, Computer Science - Machine Learning, Open-source, Computer science, Datasets as Topic, computer.software_genre, Machine Learning (cs.LG), 030218 nuclear medicine & medical imaging, Machine Learning, 0302 clinical medicine, Voxel, Statistics - Machine Learning, Image Processing, Computer-Assisted, Aged, 80 and over, Training set, Middle Aged, Alzheimer's disease, Classification, Reproducibility, Random forest, Neurology, Feature (computer vision), Data Interpretation, Statistical, [ SCCO.NEUR ] Cognitive science/Neuroscience, Female, Smoothing, Positron emission tomography, [ INFO ] Computer Science [cs], Cognitive Neuroscience, Feature extraction, Machine Learning (stat.ML), Neuroimaging, [INFO] Computer Science [cs], Set (abstract data type), 03 medical and health sciences, Atlases as Topic, Magnetic resonance imaging, Alzheimer Disease, Fluorodeoxyglucose F18, Humans, [INFO]Computer Science [cs], Aged, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Pattern recognition, Statistical classification, Positron-Emission Tomography, Artificial intelligence, Radiopharmaceuticals, business, computer, 030217 neurology & neurosurgery
Abstract

International audience; A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they are difficult to reproduce because different key components of the validation are often not readily available. These components include selected participants and input data, image preprocessing and cross-validation procedures. The performance of the different approaches is also difficult to compare objectively. In particular, it is often difficult to assess which part of the method (e.g. preprocessing, feature extraction or classification algorithms) provides a real improvement, if any. In the present paper, we propose a framework for reproducible and objective classification experiments in AD using three publicly available datasets (ADNI, AIBL and OASIS). The framework comprises: i) automatic conversion of the three datasets into a standard format (BIDS); ii) a modular set of preprocessing pipelines, feature extraction and classification methods, together with an evaluation framework, that provide a baseline for benchmarking the different components. We demonstrate the use of the framework for a large-scale evaluation on 1960 participants using T1 MRI and FDG PET data. In this evaluation, we assess the influence of different modalities, preprocessing, feature types (regional or voxel-based features), classifiers, training set sizes and datasets. Performances were in line with the state-of-the-art. FDG PET outperformed T1 MRI for all classification tasks. No difference in performance was found for the use of different atlases, image smoothing, partial volume correction of FDG PET images, or feature type. Linear SVM and L2-logistic regression resulted in similar performance and both outperformed random forests. The classification performance increased along with the number of subjects used for training. Classifiers trained on ADNI generalized well to AIBL and OASIS. All the code of the framework and the experiments is publicly available: general-purpose tools have been integrated into the Clinica software (www.clinica.run) and the paper-specific code is available at: https://github.com/aramis-lab/AD-ML.

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15. Biomarker-guided clustering of Alzheimer's disease clinical syndromes

Author

Toschi, Nicola, Lista, Simone, Lamari, Foudil, Genthon, Remy, Habert, Marie-Odile, Dubois, Bruno, Floris, Roberto, Garaci, Francesco, Vergallo, Andrea, Hampel, Harald, group, INSIGHT-preAD study, Initiative, Alzheimer Precision Medicine, Baldacci, Filippo, Bakardjian, Hovagim, Benali, Habib, Bertin, Hugo, Bonheur, Joel, Boukadida, Laurie, Boukerrou, Nadia, Cavedo, Enrica, Chiesa, Patrizia, Colliot, Olivier, Dubois, Marion, Epelbaum, Stéphane, Gagliardi, Geoffroy, Houot, Marion, Kas, Aurélie, Levy, Marcel, Zetterberg, Henrik, Metzinger, Christiane, Mochel, Fanny, Nyasse, Francis, Poisson, Catherine, Potier, Marie-Claude, Revillon, Marie, Santos, Antonio, Andrade, Katia Santos, Sole, Marine, Blennow, Kaj, Surtee, Mohmed, Thiebaut de Schotten, Michel, Younsi, Nadjia, Kilimann, Ingo, Teipel, Stefan J, Melo Dos Santos, Antonio, Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), 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)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CCSD, Accord Elsevier, Università degli Studi di Roma Tor Vergata [Roma], Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 APM), 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), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), University of Pisa - Università di Pisa, University of Gothenburg (GU), University of Rostock, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre pour l'Acquisition et le Traitement des Images (CATI), Eisai, and Hovagim Bakardjian, Habib Benali, Hugo Bertin, Joel Bonheur, Laurie Boukadida, Nadia Boukerrou, Enrica Cavedo, Patrizia Chiesa, Olivier Colliot, Bruno Dubois, Marion Dubois, Stéphane Epelbaum, Geoffroy Gagliardi, Remy Genthon, Marie-Odile Habert, Harald Hampel, Marion Houot, Aurélie Kas, Foudil Lamari, Marcel Levy, Simone Lista, Christiane Metzinger, Fanny Mochel, Francis Nyasse, Catherine Poisson, Marie-Claude Potier, Marie Revillon, Antonio Santos, Katia Santos Andrade, Marine Sole, Mohmed Surtee, Michel Thiebaut de Schotten, Andrea Vergallo, Nadjia Younsi

Subjects
Male, 0301 basic medicine, Oncology, Aging, [SDV]Life Sciences [q-bio], cerebrospinal fluid [Amyloid beta-Peptides], Disease, 0302 clinical medicine, Risk Factors, General Neuroscience, Precision medicine, diagnosis [Alzheimer Disease], Alzheimer's disease, Middle Aged, Pathophysiology, 3. Good health, [SDV] Life Sciences [q-bio], cerebrospinal fluid [Alzheimer Disease], cerebrospinal fluid [Cognitive Dysfunction], cerebrospinal fluid [Biomarkers], Biomarker (medicine), Female, Biomarker-guided categorization, Clustering, medicine.medical_specialty, tau Proteins, Neuropathology, 03 medical and health sciences, Settore MED/36 - Diagnostica per Immagini e Radioterapia, Alzheimer Disease, Internal medicine, medicine, Humans, Dementia, Cognitive Dysfunction, ddc:610, cerebrospinal fluid [Peptide Fragments], Cluster analysis, Aged, Amyloid beta-Peptides, business.industry, medicine.disease, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), Peptide Fragments, 030104 developmental biology, diagnosis [Cognitive Dysfunction], cerebrospinal fluid [tau Proteins], Spatial clustering, Neurology (clinical), Geriatrics and Gerontology, business, Biomarkers, 030217 neurology & neurosurgery, Developmental Biology
Abstract

International audience; Alzheimer's disease (AD) neuropathology is extremely heterogeneous, and the evolution from preclinical to mild cognitive impairment until dementia is driven by interacting genetic/biological mechanisms not fully captured by current clinical/research criteria. We characterized the heterogeneous "construct" of AD through a cerebrospinal fluid biomarker-guided stratification approach. We analyzed 5 validated pathophysiological cerebrospinal fluid biomarkers (Aβ1-42, t-tau, p-tau181, NFL, YKL-40) in 113 participants (healthy controls [N = 20], subjective memory complainers [N = 36], mild cognitive impairment [N = 20], and AD dementia [N = 37], age: 66.7 ± 10.4, 70.4 ± 7.7, 71.7 ± 8.4, 76.2 ± 3.5 years [mean ± SD], respectively) using Density-Based Spatial Clustering of Applications with Noise, which does not require a priori determination of the number of clusters. We found 5 distinct clusters (sizes: N = 38, 16, 24, 14, and 21) whose composition was independent of phenotypical groups. Two clusters showed biomarker profiles linked to neurodegenerative processes not associated with classical AD-related pathophysiology. One cluster was characterized by the neuroinflammation biomarker YKL-40. Combining nonlinear data aggregation with informative biomarkers can generate novel patient strata which are representative of cellular/molecular pathophysiology and may aid in predicting disease evolution and mechanistic drug response.

Published
2019
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