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1. Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism

Author

Manoj Kumar, Ravi Prakash Reddy Nanga, Gaurav Verma, Neil Wilson, Jean Christophe Brisset, Kavindra Nath, and Sanjeev Chawla

Subjects
brain tumor, chemical exchange saturation transfer (CEST), MRI and MRS, glioblastomas (GBMs), neurometabolites, two-dimensional correlation spectroscopy (2D-COSY), Neurology. Diseases of the nervous system, RC346-429
Abstract

Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.

Published
2022
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3. Contribution of diffusion-weighted imaging to distinguish herpetic encephalitis from auto-immune encephalitis at an early stage

Author

Alexandre Bani-Sadr, Marie-Camille Ruitton-Allinieu, Jean-Christophe Brisset, François Ducray, Bastien Joubert, Géraldine Picard, and François Cotton

Subjects
Radiological and Ultrasound Technology, Radiology, Nuclear Medicine and imaging, Neurology (clinical)
Abstract

To determine whether diffusion-weighted imaging (DWI) can help to distinguish early stage autoimmune (AI) and herpes simplex virus (HSV) encephalitides.This case-control study included patients from a multi-center cohort of AI encephalitides whose initial MRI including DWI was performed within ten days after symptoms onset. They were compared with patients with HSV encephalitis enrolled prospectively in a single-center from June, 2020 to December, 2020. The final diagnosis of AI encephalitis required a positive autoantibody assay, and that of HSV encephalitis required a positive HSV polymerase chain reaction based on cerebrospinal fluid. Brain MRI were evaluated for restricted diffusion, fluid-inversion recovery (FLAIR) abnormalities, lesion topography, hemorrhagic changes, and contrast enhancement.Forty-nine patients were included of which, 19 (38.8%) had AI encephalitis. Twenty-seven patients (55.1%) were males and the median age was 46.0 years (interquartile range (IQR):[22.0; 65.0]). Brain MRI were performed after a median of 4 days (IQR:[2.0; 7.0]) of symptom onset and time between symptom onset and MRI was not significantly different (p = 0.60). Twenty-six patients had restricted diffusion lesions in the medial temporal lobe, including 25/30 in the HSV encephalitis group (p 0.001). FLAIR abnormalities were observed in 36 patients, including 29/30 in the HSV encephalitis group (p 0.001). Lesion topography, hemorrhagic changes, and contrast enhancement did not differ significantly between the two groups.Our results suggest that restricted diffusion lesions in the medial temporal lobe are a hallmark of HSV encephalitis and may help distinguish it from early-stage AI encephalitis.

Published
2023
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4. Cerebral perfusion using ASL in patients with COVID-19 and neurological manifestations: A retrospective multicenter observational study

Author

François-Daniel Ardellier, Seyyid Baloglu, Magdalena Sokolska, Vincent Noblet, François Lersy, Olivier Collange, Jean-Christophe Ferré, Adel Maamar, Béatrice Carsin-Nicol, Julie Helms, Maleka Schenck, Antoine Khalil, Augustin Gaudemer, Sophie Caillard, Julien Pottecher, Nicolas Lefèbvre, Pierre-Emmanuel Zorn, Muriel Matthieu, Jean Christophe Brisset, Clotilde Boulay, Véronique Mutschler, Yves Hansmann, Paul-Michel Mertes, Francis Schneider, Samira Fafi-Kremer, Mickael Ohana, Ferhat Meziani, Nicolas Meyer, Tarek Yousry, Mathieu Anheim, François Cotton, Hans Rolf Jäger, Stéphane Kremer, Fabrice Bonneville, Gilles Adam, Guillaume Martin-Blondel, Jérémie Pariente, Thomas Geeraerts, Hélène Oesterlé, Federico Bolognini, Julien Messie, Ghazi Hmeydia, Joseph Benzakoun, Catherine Oppenheim, Jean-Marc Constans, Serge Metanbou, Adrien Heintz, Blanche Bapst, Imen Megdiche, Lavinia Jager, Patrick Nesser, Yannick Talla Mba, Thomas Tourdias, Juliette Coutureau, Céline Hemmert, Philippe Feuerstein, Nathan Sebag, Sophie Carre, Manel Alleg, Claire Lecocq, Emmanuel Schmitt, René Anxionnat, François Zhu, Géraud Forestier, Aymeric Rouchaud, Pierre-Olivier Comby, Frederic Ricolfi, Pierre Thouant, Sylvie Grand, Alexandre Krainik, Isaure de Beaurepaire, Grégoire Bornet, Audrey Lacalm, Patrick Miailhes, Julie Pique, Claire Boutet, Xavier Fabre, Béatrice Claise, Sonia Mirafzal, Laure Calvet, Hubert Desal, Jérome Berge, Grégoire Boulouis, Apolline Kazemi, Nadya Pyatigorskaya, Augustin Lecler, Suzana Saleme, Myriam Edjlali-Goujon, Basile Kerleroux, Jean-Christophe Brisset, Samir Chenaf, Les Hôpitaux Universitaires de Strasbourg (HUS), Hôpital de Hautepierre [Strasbourg], Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), University College of London [London] (UCL), Nouvel Hôpital Civil de Strasbourg, Département de Neuroradiology [Rennes], 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)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), 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), CHU Pontchaillou [Rennes], Service de Médecine Intensive et Réanimation [Strasbourg], CHU Strasbourg, Département de Radiologie [Bichat] (DR- Bichat), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg (UNISTRA), Groupe d'Analyse des Itinéraires et des Niveaux Salariaux (GAINS), Le Mans Université (UM), Les Hôptaux universitaires de Strasbourg (HUS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Centre for Integrative Biology - CBI (Inserm U964 - CNRS UMR7104 - IGBMC), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Hôpital Louis Pasteur [Colmar] (CH Colmar), Hôpital Sainte-Anne [Paris], CHU Amiens-Picardie, CHirurgie, IMagerie et REgénération tissulaire de l’extrémité céphalique - Caractérisation morphologique et fonctionnelle - UR UPJV 7516 (CHIMERE), Université de Picardie Jules Verne (UPJV), SFNR-COVID Group, CHU Henri Mondor [Créteil], Hôpital Marie Madeleine [Forbach] (CHIC Unisanté+), CHU de Bordeaux Pellegrin [Bordeaux], Centre Hospitalier Emile Muller [Mulhouse] (CH E.Muller Mulhouse), Groupe Hospitalier de Territoire Haute Alsace (GHTHA), Centre Hospitalier de Haguenau, Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Hôpital Dupuytren [CHU Limoges], Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre Hospitalier Universitaire [Grenoble] (CHU), Hôpital privé d’Antony, Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), CHU Clermont-Ferrand, and Société Française de Neuroradiologie [Paris] (SFNR)

Subjects
Multicenter Study, Radiological and Ultrasound Technology, Cerebrovascular Circulation, COVID-19, Radiology, Nuclear Medicine and imaging, Neuroimaging, Neurology (clinical), Magnetic Resonance Imaging, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Background and purpose: Cerebral hypoperfusion has been reported in patients with COVID-19 and neurological manifestations in small cohorts. We aimed to systematically assess changes in cerebral perfusion in a cohort of 59 of these patients, with or without abnormalities on morphological MRI sequences.Methods: Patients with biologically-confirmed COVID-19 and neurological manifestations undergoing a brain MRI with technically adequate arterial spin labeling (ASL) perfusion were included in this retrospective multicenter study. ASL maps were jointly reviewed by two readers blinded to clinical data. They assessed abnormal perfusion in four regions of interest in each brain hemisphere: frontal lobe, parietal lobe, posterior temporal lobe, and temporal pole extended to the amygdalo-hippocampal complex.Results: Fifty-nine patients (44 men (75%), mean age 61.2 years) were included. Most patients had a severe COVID-19, 57 (97%) needed oxygen therapy and 43 (73%) were hospitalized in intensive care unit at the time of MRI. Morphological brain MRI was abnormal in 44 (75%) patients. ASL perfusion was abnormal in 53 (90%) patients, and particularly in all patients with normal morphological MRI. Hypoperfusion occurred in 48 (81%) patients, mostly in temporal poles (52 (44%)) and frontal lobes (40 (34%)). Hyperperfusion occurred in 9 (15%) patients and was closely associated with post-contrast FLAIR leptomeningeal enhancement (100% [66.4%-100%] of hyperperfusion with enhancement versus 28.6% [16.6%-43.2%] without, p=0.002). Studied clinical parameters (especially sedation) and other morphological MRI anomalies had no significant impact on perfusion anomalies.Conclusion: Brain ASL perfusion showed hypoperfusion in more than 80% of patients with severe COVID-19, with or without visible lesion on conventional MRI abnormalities.

Published
2023
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5. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

Author

Charley Gros, Benjamin De Leener, Atef Badji, Josefina Maranzano, Dominique Eden, Sara M. Dupont, Jason Talbott, Ren Zhuoquiong, Yaou Liu, Tobias Granberg, Russell Ouellette, Yasuhiko Tachibana, Masaaki Hori, Kouhei Kamiya, Lydia Chougar, Leszek Stawiarz, Jan Hillert, Elise Bannier, Anne Kerbrat, Gilles Edan, Pierre Labauge, Virginie Callot, Jean Pelletier, Bertrand Audoin, Henitsoa Rasoanandrianina, Jean-Christophe Brisset, Paola Valsasina, Maria Assunta Rocca, Massimo Filippi, Rohit Bakshi, Shahamat Tauhid, Ferran Prados, Marios C. Yiannakas, Hugh Kearney, Olga Ciccarelli, Seth A. Smith, Constantina Andrada Treaba, Caterina Mainero, Jennifer Lefeuvre, Daniel S. Reich, Govind Nair, Vincent Auclair, Donald G. McLaren, Allan R. Martin, Michael G. Fehlings, Shahabeddin Vahdat, Ali Khatibi, Julien Doyon, Timothy M. Shepherd, Erik Charlson, Sridar Narayanan, and Julien Cohen-Adad

Published
2018

6. Critical illness-associated cerebral microbleeds for patients with severe COVID-19: etiologic hypotheses

Author

Julie Helms, Agathe Chammas, Francis Schneider, Jean-Christophe Brisset, Nicolas Meyer, Stéphane Kremer, Olivier Collange, Alexandre Willaume, François Cotton, François Lersy, Thibault Willaume, Mathieu Anheim, Les Hôpitaux Universitaires de Strasbourg (HUS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg (UNISTRA), Hôpital Claude Huriez [Lille], CHU Lille, CHU Strasbourg, Centre for Integrative Biology - CBI (Inserm U964 - CNRS UMR7104 - IGBMC), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hospices Civils de Lyon (HCL), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), univOAK, Archive ouverte, and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
medicine.medical_specialty, Neurology, Critical Illness, medicine.medical_treatment, Clinical Neurology, Kidney failure, Hypoxemia, 03 medical and health sciences, Extracorporeal Membrane Oxygenation, 0302 clinical medicine, Microhemorrhages, Intensive care, Internal medicine, medicine, Extracorporeal membrane oxygenation, Humans, 030212 general & internal medicine, Dialysis, Cerebral Hemorrhage, Original Communication, SARS-CoV-2, business.industry, Microangiopathy, COVID-19, medicine.disease, Respiratory failure, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Cardiology, Neurology (clinical), medicine.symptom, business, Complication, 030217 neurology & neurosurgery, MRI
Abstract

Background and purpose: During the COVID-19 outbreak, the presence of extensive white matter microhemorrhages was detected by brain MRIs. The goal of this study was to investigate the origin of this atypical hemorrhagic complication. Methods: Between March 17 and May 18, 2020, 80 patients with severe COVID-19 infections were admitted for acute respiratory distress syndrome to intensive care units at the University Hospitals of Strasbourg for whom a brain MRI for neurologic manifestations was performed. 19 patients (24%) with diffuse microhemorrhages were compared to 18 control patients with COVID-19 and normal brain MRI. Results: The first hypothesis was hypoxemia. The latter seemed very likely since respiratory failure was longer and more pronounced in patients with microhemorrhages (prolonged endotracheal intubation (p = 0.0002), higher FiO2 (p = 0.03), increased use of extracorporeal membrane oxygenation (p = 0.04)). A relevant hypothesis, the role of microangiopathy, was also considered, since patients with microhemorrhages presented a higher increase of the D-Dimers (p = 0.01) and a tendency to more frequent thrombotic events (p = 0.12). Another hypothesis tested was the role of kidney failure, which was more severe in the group with diffuse microhemorrhages (higher creatinine level [median of 293 µmol/L versus 112 µmol/L, p = 0.04] and more dialysis were introduced in this group during ICU stay [12 versus 5 patients, p = 0.04]). Conclusions: Blood-brain barrier dysfunction secondary to hypoxemia and high concentration of uremic toxins seems to be the main mechanism leading to critical illness-associated cerebral microbleeds, and this complication remains to be frequently described in severe COVID-19 patients. Keywords: COVID-19; Hypoxemia; Kidney failure; MRI; Microhemorrhages.

Published
2021
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7. Collicular Hyperactivation in Patients with COVID-19: A New Finding on Brain MRI and PET/CT

Author

Caroline Bund, Agathe Chammas, François Lersy, Stéphane Kremer, Jean-Christophe Brisset, Izzie Jacques Namer, F.-D. Ardellier, Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Adult, Male, 2019-20 coronavirus outbreak, Pathology, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), viruses, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 030218 nuclear medicine & medical imaging, 03 medical and health sciences, COVID-19 Testing, 0302 clinical medicine, Text mining, Positron Emission Tomography Computed Tomography, medicine, Brain mri, Humans, Radiology, Nuclear Medicine and imaging, In patient, Pandemics, Aged, Retrospective Studies, Aged, 80 and over, PET-CT, Hyperactivation, SARS-CoV-2, business.industry, Adult Brain, Brain, COVID-19, virus diseases, Middle Aged, Magnetic Resonance Imaging, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Female, Posterior Leukoencephalopathy Syndrome, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

Hyperactivation of the colliculi has been observed in some patients with coronavirus disease 2019.

Published
2021
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8. Cerebral vasculitis of medium-sized vessels as a possible mechanism of brain damage in COVID-19 patients

Author

Jean-Christophe Brisset, Mathieu Anheim, François Lersy, Thibault Willaume, Stéphane Kremer, Agathe Chammas, François Cotton, Les Hôpitaux Universitaires de Strasbourg (HUS), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Les Hôptaux universitaires de Strasbourg (HUS), CHU Strasbourg, univOAK, Archive ouverte, and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, Cerebral arteries, Magnetic Resonance Imaging (MRI), RT-PCR, reverse transcriptase-polymerase chain reaction, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Aged, 80 and over, education.field_of_study, Radiological and Ultrasound Technology, Brain, Middle Aged, Magnetic Resonance Imaging, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Radiology Nuclear Medicine and imaging, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Female, Original Article, Radiology, medicine.symptom, Vasculitis, Adult, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Population, Clinical Neurology, Neuroimaging, Brain damage, Young Adult, 03 medical and health sciences, medicine.artery, medicine, Basilar artery, Humans, Radiology, Nuclear Medicine and imaging, Vasculitis, Central Nervous System, education, ComputingMethodologies_COMPUTERGRAPHICS, Aged, Retrospective Studies, business.industry, COVID-19, medicine.disease, VZV, varicella-zoster virus, Neurology (clinical), business, Magnetic Resonance Angiography, 030217 neurology & neurosurgery, Cerebral vasculitis
Abstract

Graphical abstract, Highlights • Intracranial vessel wall imaging appears useful in COVID-19 patients. • Vasculitis seems likely as imaging demonstrated vessel wall thickening with homogeneous and concentric enhancement. • Cerebral vasculitis seems to be one of the mechanisms at the origin of brain damage related to COVID-19., Background and purpose Cerebral complications related to COVID-19 were recently reported, and the underlying mechanisms of brain damage remain uncertain, probably multifactorial. Among various hypotheses suggested, a possible vasculitis was issued but never confirmed. Herein, we aimed to describe brain MRIs focused on the intracranial vessel wall in a population of COVID-19 patients with neurologic manifestations. Materials and methods Between March 1 and May 31, 2020, 69 consecutive COVID-19 patients with neurologic manifestations underwent a brain MRI allowing the study of the intracranial vessel wall at Strasbourg University hospitals and were retrospectively included. During the same period, 25 consecutive patients, without suspicion of SARS-CoV-2 infection, underwent a brain MRI urgently, with the same imaging protocols. A vasculitis seemed likely when imaging demonstrated vessel wall thickening with homogeneous and concentric enhancement. Results Among the 69 COVID-19 patients included, 11 (16%) presented arterial vessel wall thickening with homogeneous and concentric enhancement, compatible with cerebral vasculitis. These neuroimaging findings were not found among the 25 patients without SARS-CoV-2 infection, and the difference was statistically significant (p = 0.03). Middle cerebral arteries, basilar artery, and posterior cerebral arteries were the most frequent vessels involved. For nine of them, imaging demonstrated ischemic or hemorrhagic complications. Conclusion Cerebral vasculitis of medium-sized vessels seems to be one of the mechanisms at the origin of brain damage related to COVID-19.

Published
2021
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9. Neurologic and neuroimaging findings in patients with COVID-19: A retrospective multicenter study

Author

Ghazi Hmeydia, Xavier Fabre, Géraud Forestier, Catherine Oppenheim, Manel Alleg, Julie Helms, Sophie Carré, Julien Messie, Muriel Mathieu, Grégoire Bornet, Claire Lecocq, M Edjlali-Goujon, R. Anxionnat, Jean-Christophe Brisset, Pierre-Emmanuel Zorn, Francis Schneider, Olivier Collange, Stéphane Kremer, Nadya Pyatigorskaya, François Cotton, Frédéric Ricolfi, François Lersy, Pierre-Olivier Comby, Nicolas Meyer, Jean-Christophe Ferré, Lavinia Jager, Augustin Lecler, Joseph Benzakoun, Béatrice Carsin-Nicol, Maleka Schenck, Suzana Saleme, Thibault Willaume, Emmanuelle Schmitt, Samira Fafi-Kremer, Pierre Thouant, Isaure de Beaurepaire, François Zhu, Seyyid Baloglu, Claire Boutet, Augustin Gaudemer, Federico Bolognini, Hubert Desal, Sophie Caillard, Mathieu Anheim, Jean-Marc Constans, Yannick Talla, Hélène Oesterlé, François-Daniel Ardellier, Hamid Merdji, Basile Kerleroux, Apolline Kazémi, Adel Maamar, Paul Michel Mertes, Antoine Khalil, Patrick Nesser, Mickaël Ohana, Ferhat Meziani, Jérôme Berge, Gregoire Boulouis, Les Hôptaux universitaires de Strasbourg (HUS), CHU Strasbourg, Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Nanomédecine Régénérative (NanoRegMed), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpitaux Civils de Colmar, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre hospitalier de Haguenau, Centre Hospitalier Universitaire de Nancy (CHU Nancy), Hôpital Marie-Madeleine [Forbach], Département de Radiologie [CHU de Rennes], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Institut de psychiatrie et neurosciences de Paris (IPNP - U1266 Inserm), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), CHU Pontchaillou [Rennes], CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), Centre Hospitalier de Roanne (CH Roanne), CH de Roanne, CHU Limoges, Hôpital Privé d'Antony, Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Bordeaux [Bordeaux], CHU Lille, CHU Pitié-Salpêtrière [AP-HP], 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), CHirurgie, IMagerie et REgénération tissulaire de l’extrémité céphalique - Caractérisation morphologique et fonctionnelle - UR UPJV 7516 (CHIMERE), Université de Picardie Jules Verne (UPJV), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Immuno-Rhumatologie Moléculaire, Nouvel Hôpital Civil de Strasbourg, Hospices Civils de Lyon (HCL), Ferré, Jean-Christophe, École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), 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), and Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)

Subjects
medicine.medical_specialty, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Meningoencephalitis, Retrospective cohort study, medicine.disease, 3. Good health, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Pneumonia, 0302 clinical medicine, Neurologic manifestation, Internal medicine, Corticospinal tract, Cohort, medicine, Neurology (clinical), Young adult, business, 030217 neurology & neurosurgery, Encephalitis
Abstract

ObjectiveTo describe neuroimaging findings and to report the epidemiologic and clinical characteristics of patients with coronavirus disease 2019 (COVID-19) with neurologic manifestations.MethodsIn this retrospective multicenter study (11 hospitals), we included 64 patients with confirmed COVID-19 with neurologic manifestations who underwent a brain MRI.ResultsThe cohort included 43 men (67%) and 21 women (33%); their median age was 66 (range 20–92) years. Thirty-six (56%) brain MRIs were considered abnormal, possibly related to severe acute respiratory syndrome coronavirus. Ischemic strokes (27%), leptomeningeal enhancement (17%), and encephalitis (13%) were the most frequent neuroimaging findings. Confusion (53%) was the most common neurologic manifestation, followed by impaired consciousness (39%), presence of clinical signs of corticospinal tract involvement (31%), agitation (31%), and headache (16%). The profile of patients experiencing ischemic stroke was different from that of other patients with abnormal brain imaging: the former less frequently had acute respiratory distress syndrome (p= 0.006) and more frequently had corticospinal tract signs (p= 0.02). Patients with encephalitis were younger (p= 0.007), whereas agitation was more frequent for patients with leptomeningeal enhancement (p= 0.009).ConclusionsPatients with COVID-19 may develop a wide range of neurologic symptoms, which can be associated with severe and fatal complications such as ischemic stroke or encephalitis. In terms of meningoencephalitis involvement, even if a direct effect of the virus cannot be excluded, the pathophysiology seems to involve an immune or inflammatory process given the presence of signs of inflammation in both CSF and neuroimaging but the lack of virus in CSF.ClinicalTrials.gov identifierNCT04368390.

Published
2020
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10. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord

Author

Eden, Dominique, Gros, Charley, Badji, Atef, M Dupont, Sara, De Leener, Benjamin, Maranzano, Josefina, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobias, Ouellette, Russell, Stawiarz, Leszek, Hillert, Jan, Talbott, Jason, Bannier, Elise, Kerbrat, Anne, Edan, Gilles, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Jean-Christophe, Brisset, Valsasina, Paola, A Rocca, Maria, Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Marios, Kearney, Hugh, Ciccarelli, Olga, A Smith, Seth, Andrada Treaba, Constantina, Mainero, Caterina, Lefeuvre, Jennifer, S Reich, Daniel, Nair, Govind, M Shepherd, Timothy, Charlson, Erik, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Narayanan, Sridar, Julien, Cohen-Adad, and Yasuhiko, Tachibana

Abstract

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Published
2019

11. Metastatic pancreatic cancer is dependent on oncogenic Kras in mice.

Author

Meredith A Collins, Jean-Christophe Brisset, Yaqing Zhang, Filip Bednar, Josette Pierre, Kevin A Heist, Craig J Galbán, Stefanie Galbán, and Marina Pasca di Magliano

Subjects
Medicine, Science
Abstract

Pancreatic cancer is one of the deadliest human malignancies, and its prognosis has not improved over the past 40 years. Mouse models that spontaneously develop pancreatic adenocarcinoma and mimic the progression of the human disease are emerging as a new tool to investigate the basic biology of this disease and identify potential therapeutic targets. Here, we describe a new model of metastatic pancreatic adenocarcinoma based on pancreas-specific, inducible and reversible expression of an oncogenic form of Kras, together with pancreas-specific expression of a mutant form of the tumor suppressor p53. Using high-resolution magnetic resonance imaging to follow individual animals in longitudinal studies, we show that both primary and metastatic lesions depend on continuous Kras activity for their maintenance. However, re-activation of Kras* following prolonged inactivation leads to rapid tumor relapse, raising the concern that Kras*-resistance might eventually be acquired. Thus, our data identifies Kras* as a key oncogene in pancreatic cancer maintenance, but raises the possibility of acquired resistance should Kras inhibitors become available for use in pancreatic cancer.

Published
2012
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12. Weekly enhanced T1-weighted MRI with Gadobutrol injections in MS patients: Is there a signal intensity increase in the dentate nucleus and the globus pallidus?

Author

Jean-Christophe Brisset, Salem Hannoun, Paul Jaulent, Françoise Durand-Dubief, Fabien Rollot, Sandra Vukusic, François Cotton, Gabriel Kocevar, and Dominique Sappey-Marinier

Subjects
Adult, Male, Multiple Sclerosis, Gadolinium, Contrast Media, chemistry.chemical_element, Globus Pallidus, Injections, 030218 nuclear medicine & medical imaging, Gadobutrol, White matter, 03 medical and health sciences, 0302 clinical medicine, Organometallic Compounds, medicine, Middle cerebellar peduncle, Humans, Radiology, Nuclear Medicine and imaging, Retrospective Studies, Dose-Response Relationship, Drug, medicine.diagnostic_test, business.industry, Multiple sclerosis, Magnetic resonance imaging, General Medicine, Middle Aged, medicine.disease, Magnetic Resonance Imaging, medicine.anatomical_structure, Globus pallidus, Dentate nucleus, Cerebellar Nuclei, chemistry, Disease Progression, Female, business, Nuclear medicine, 030217 neurology & neurosurgery, medicine.drug
Abstract

Background and Purpose Gadolinium-based contrast agents (GBCAs) administration have drastically improved the accuracy of Multiple Sclerosis (MS) diagnosis by highlighting any damage to the brain blood barrier, thereby differentiating between active and non-active lesions. Following multiple administrations of GBCAs, several MS studies have reported a signal intensity (SI) increase on unenhanced T1-weighted images in certain brain regions such as the dentate nucleus (DN) and the globus pallidus (GP). Our aim was therefore to determine the accumulation of macrocyclic GBCAs on enhanced T1-weighted images SI in the DN and the GP of MS patients injected eight times. Materials and Methods Five MS patients underwent eight weekly consecutive MRI scans. Enhanced 3D T1-weighted images with Gadobutrol as a macrocyclic GBCA, were acquired. A ROI-based approach was applied for the evaluation of SI in the DN to middle cerebellar peduncle (DN-MCP) and GP to semi-oval white matter (GP-SOWM) ratios. An analysis of variance on repeated measures was used for the statistical analysis of each ratio. Results No DN-MCP and GP-SOWM SI ratio differences were observed over the eight-weeks period using the macrocyclic GBCA. Conclusion Iterative and weekly injections of macrocyclic GBCAs are not associated with T1 signal increase in the DN and GP of MS patients. These results would suggest a no gadolinium accumulation in the brain using macrocyclic GBCA even after several close injections and promote the use of a macrocylcic GBCA rather than linear agents for MS patients.

Published
2018
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13. Susceptibility weighted imaging and quantitative susceptibility mapping of the cerebral vasculature using ferumoxytol

Author

E. Mark Haacke, Jean-Christophe Brisset, Jiani Hu, Yulin Ge, and Saifeng Liu

Subjects
business.industry, Cerebral arteries, Quantitative susceptibility mapping, computer.software_genre, 030218 nuclear medicine & medical imaging, Ferumoxytol, 03 medical and health sciences, Cerebral circulation, 0302 clinical medicine, Precontrast, medicine.anatomical_structure, Voxel, Susceptibility weighted imaging, medicine, Radiology, Nuclear Medicine and imaging, Nuclear medicine, business, computer, 030217 neurology & neurosurgery, Artery
Abstract

Purpose To demonstrate the potential of imaging cerebral arteries and veins with ferumoxytol using susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM). Materials and Methods The relationships between ferumoxytol concentration and the apparent susceptibility at 1.5T, 3T, and 7T were determined using phantom data; the ability of visualizing subvoxel vessels was evaluated using simulations; and the feasibility of using ferumoxytol to enhance the visibility of small vessels was confirmed in three healthy volunteers at 7T(with doses 1 mg/kg to 4 mg/kg). The visualization of the lenticulostriate arteries and the medullary veins was assessed by two raters and the contrast-to-noise ratios (CNRs) of these vessels were measured. Results The relationship between ferumoxytol concentration and susceptibility was linear with a slope 13.3 ± 0.2 ppm·mg-1·mL at 7T. Simulations showed that SWI data with an increased dose of ferumoxytol, higher echo time (TE), and higher imaging resolution improved the detection of smaller vessels. With 4 mg/kg ferumoxytol, voxel aspect ratio = 1:8, TE = 10 ms, the diameter of the smallest detectable artery was approximately 50μm. The rating score for arteries was improved from 1.5 ± 0.5 (precontrast) to 3.0 ± 0.0 (post-4 mg/kg) in the in vivo data and the apparent susceptibilities of the arteries (0.65 ± 0.02 ppm at 4 mg/kg) agreed well with the expected susceptibility (0.71 ± 0.05 ppm). Conclusion The CNR for cerebral vessels with ferumoxytol can be enhanced using SWI, and the apparent susceptibilities of the arteries can be reliably quantified using QSM. This approach improves the imaging of the entire vascular system outside the capillaries and may be valuable for a variety of neurodegenerative diseases which involve the microvasculature. Level of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017.

Published
2017
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14. New OFSEP recommendations for MRI assessment of multiple sclerosis patients: Special consideration for gadolinium deposition and frequent acquisitions

Author

Jean-Christophe Brisset, Stephane Kremer, Salem Hannoun, Fabrice Bonneville, Francoise Durand-Dubief, Thomas Tourdias, Christian Barillot, Charles Guttmann, Sandra Vukusic, Vincent Dousset, Francois Cotton, R. Ameli, R. Anxionnat, B. Audoin, A. Attye, E. Bannier, C. Barillot, D. Ben Salem, M.-P. Boncoeur-Martel, G. Bonhomme, F. Bonneville, C. Boutet, J.C. Brisset, F. Cervenanski, B. Claise, O. Commowick, J.-M. Constans, F. Cotton, P. Dardel, H. Desal, V. Dousset, F. Durand-Dubief, J.-C. Ferre, A. Gaultier, E. Gerardin, T. Glattard, S. Grand, T. Grenier, R. Guillevin, C. Guttmann, A. Krainik, S. Kremer, S. Lion, N. Menjot De Champfleur, L. Mondot, O. Outteryck, N. Pyatigorskaya, J.-P. Pruvo, S. Rabaste, J.-P. Ranjeva, J.-A. Roch, J.-C. Sadik, D. Sappey-Marinier, J. Savatovsky, B. Stankoff, J.-Y. Tanguy, A. Tourbah, T. Tourdias, B. Brochet, R. Casey, J. De Sèze, P. Douek, F. Guillemin, D. Laplaud, C. Lebrun-Frenay, L. Mansuy, T. Moreau, J. Olaiz, J. Pelletier, C. Rigaud-Bully, S. Vukusic, M. Debouverie, G. Edan, J. Ciron, C. Lubetzki, P. Vermersch, P. Labauge, G. Defer, E. Berger, P. Clavelou, O. Gout, E. Thouvenot, O. Heinzlef, A. Al-Khedr, B. Bourre, O. Casez, P. Cabre, A. Montcuquet, A. Créange, J.-P. Camdessanché, S. Bakchine, A. Maurousset, I. Patry, T. De Broucker, C. Pottier, J.-P. Neau, C. Labeyrie, C. Nifle, Hôpital de Hautepierre [Strasbourg], Nehme and Therese Tohme Multiple Sclerosis Center [Beyrouth, Liban] (AUBMC), American University of Beirut Medical Center [Beyrouth, Liban] (AUBMC), American University of Beirut [Beyrouth] (AUB)-American University of Beirut [Beyrouth] (AUB), Neuroradiologie Diagnostique et Thérapeutique [Toulouse], Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse], Hôpital neurologique et neurochirurgical Pierre Wertheimer [CHU - HCL], Hospices Civils de Lyon (HCL), INSERM, Neurocentre Magendie, U1215, Physiopathologie de la Plasticité Neuronale, F-33000 Bordeaux, France, 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 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-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 Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), 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)-Université de Rennes (UNIV-RENNES)-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 Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Center for Neurological Imaging, Departments of Radiology and Neurology, Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Service de neuroradiologie [Lyon], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Département de neuroradiologie diagnostique et thérapeutique [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Neurologie, maladies neuro-musculaires [Hôpital de la Timone - APHM], Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Service de neuroradiologie [Grenoble], CHU Grenoble, Laboratoire de Traitement de l'Information Medicale (LaTIM), Institut National de la Santé et de la Recherche Médicale (INSERM)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Service de Radiologie et Imagerie Médicale [CHU Limoges], CHU Limoges, Auteur indépendant, Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), CHU Clermont-Ferrand, CHU Amiens-Picardie, Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Hôpital des Charpennes [CHU - HCL], Centre Hospitalier Universitaire [Grenoble] (CHU), Centre hospitalier universitaire de Poitiers (CHU Poitiers), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Hôpital Pasteur [Nice] (CHU), Hôpital Roger Salengro [Lille], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Aix Marseille Université (AMU), Fondation Ophtalmologique Adolphe de Rothschild [Paris], Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Hôpital Raymond Poincaré [AP-HP], CHU de Bordeaux Pellegrin [Bordeaux], Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques (BMNST), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Union pour la lutte contre la sclérose en plaques (UNISEP), Centre d'investigation clinique [Nancy] (CIC), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Hôpital de la Timone [CHU - APHM] (TIMONE), Fondation Eugène Devic EDMUS, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hôpital Gui de Chauliac, Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), CHU Gabriel Montpied [Clermont-Ferrand], Hôpital Universitaire Carémeau [Nîmes] (CHU Nîmes), Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), centre hospitalier intercommunal de Poissy/Saint-Germain-en-Laye - CHIPS [Poissy], Hôpital Charles Nicolle [Rouen], Hôpital Pierre Zobda-Quitman [CHU de la Martinique], CHU de la Martinique [Fort de France], Hôpital Dupuytren [CHU Limoges], Hôpital Henri Mondor, Centre Hospitalier Universitaire de Reims (CHU Reims), Hôpital Bretonneau, Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Centre Hospitalier Sud Francilien, CH Evry-Corbeil, Hôpital Delafontaine, Centre Hospitalier de Saint-Denis [Ile-de-France], Centre Hospitalier René Dubos [Pontoise], AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Centre Hospitalier de Versailles André Mignot (CHV), French State, 'Investments for the Future', Eugène Devic EDMUS Foundation, ARSEP Foundation, Service Neuroradiologie Diagnostique et Thérapeutique [CHU Toulouse], Pôle imagerie médicale [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Neurocentre Magendie : Physiopathologie de la Plasticité Neuronale (U1215 Inserm - UB), Université de Bordeaux (UB)-Institut François Magendie-Institut National de la Santé et de la Recherche Médicale (INSERM), Neuroimagerie: méthodes et applications (Empenn), 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 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), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Brestois Santé Agro Matière (IBSAM), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Hôpital Gui de Chauliac [CHU Montpellier], Centre hospitalier intercommunal de Poissy/Saint-Germain-en-Laye - CHIPS [Poissy], CHU Rouen, Normandie Université (NU)-Normandie Université (NU), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), CCSD, Accord Elsevier, and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
medicine.medical_specialty, Consensus, Multiple Sclerosis, Gadolinium, chemistry.chemical_element, Contrast Media, Fluid-attenuated inversion recovery, 030218 nuclear medicine & medical imaging, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Atrophy, Quality of life, Medicine, Humans, Radiology, Nuclear Medicine and imaging, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Adverse effect, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Progressive multifocal leukoencephalopathy, Multiple sclerosis, Brain, Magnetic resonance imaging, medicine.disease, Image Enhancement, Magnetic Resonance Imaging, 3. Good health, chemistry, OFSEP, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), Radiology, business, 030217 neurology & neurosurgery
Abstract

Purpose New multiple sclerosis (MS) disease-modifying therapies (DMTs), which exert beneficial effects through prevention of relapse, limitation of disability progression, and improvement of patients’ quality of life, have recently emerged. Nonetheless, these DMTs are not without associated complications (severe adverse events like. progressive multifocal leukoencephalopathy). Patient follow-up requires regular clinical evaluations and close monitoring with magnetic resonance imaging (MRI). Detection of new T2 lesions and potential brain atrophy measurements contribute to the evaluation of treatment effectiveness. Current MRI protocols for MS recommend the acquisition of an annual gadolinium (Gd) enhanced MRI, resulting in administration of high volume of contrast agents over time and Gd accumulation in the brain. Methods A consensus report was established by neuroradiologists and neurologists from the French Observatory of MS, which aimed at reducing the number of Gd injections required during MS patient follow-up. Recommendations The French Observatory of MS recommends the use of macrocyclic Gd enhancement at time of diagnosis, when a new DMT is introduced, at 6-month re-baseline, and when previous scans are unavailable for comparison. Gd administration can be performed as an option in case of relapse or suspicion of intercurrent disease such as progressive multifocal leukoencephalopathy. Other follow-up MRIs do not require contrast enhancement, provided current and previous MRI acquisitions follow the same standardized protocol including 3D FLAIR sequences.

Published
2020
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15. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord

Author

Kouhei Kamiya, Massimo Filippi, Marios C. Yiannakas, Ferran Prados, Rohit Bakshi, Hugh Kearney, Sridar Narayanan, Pierre Labauge, Timothy M. Shepherd, Jean-Christophe Brisset, Russell Ouellette, Tobias Granberg, Ren Zhuoquiong, Caterina Mainero, Julien Cohen-Adad, Atef Badji, Jean Pelletier, Josefina Maranzano, Erik Charlson, Leszek Stawiarz, Seth A. Smith, Yasuhiko Tachibana, Yaou Liu, Charley Gros, Masaaki Hori, Dominique Eden, Olga Ciccarelli, Virginie Callot, Daniel S. Reich, Jennifer Lefeuvre, Gilles Edan, Sara M. Dupont, Govind Nair, Henitsoa Rasoanandrianina, Elise Bannier, Paola Valsasina, Jason F. Talbott, Shahamat Tauhid, Jan Hillert, Lydia Chougar, Anne Kerbrat, Constantina A. Treaba, Maria A. Rocca, Benjamin De Leener, Bertrand Audoin, École Polytechnique de Montréal (EPM), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Xuanwu Hospital of Capital, Deutsche Telekom Group, Department of Computer Science [Liverpool], University of Liverpool, Karolinska Institutet [Stockholm], Department of Radiology and Biomedical Imaging [San Francisco], University of California [San Francisco] (UC San Francisco), University of California (UC)-University of California (UC), 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), Service de Neurologie [Rennes] = Neurology [Rennes], CHU Pontchaillou [Rennes], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM), Hôpital de la Timone [CHU - APHM] (TIMONE)-Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Vita-Salute San Raffaele University and Center for Translational Genomics and Bioinformatics, Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), Translational imaging group [London] (TIG), Centre for Medical Image Computing (CMIC), University College of London [London] (UCL)-University College of London [London] (UCL)-Department of Medical Physics and Biomedical Engineering (UCL), University College of London [London] (UCL), Vanderbilt University [Nashville], Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], National Institutes of Health [Bethesda] (NIH), New York University Langone Medical Center (NYU Langone Medical Center), NYU System (NYU), National Institute of Radiological Sciences (NIRS), Juntendo University Hospital [Tokyo], McConnell Brain Imaging Centre (MNI), McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Funded by the Canada Research Chair in Quantitative Magnetic Resonance Imaging, CIHR-FDN-143263, FRQS-28826, FRQNT-2015-PR-182754, NSERC-435897–2013, QBIN, NMSS RG-1501–02840 (S.A.S.), NIH/NINDS R21 NS087465–01 (S.A.S.), NIH/NEI R01EY023240 (S.A.S.), DoD W81XWH-13–0073 (S.A.S.), the Intramural Research Program of NIH/NINDS (J.L., D.S.R., G.N.), PHRC (EMISEP), NIH/NINDS R01NS078322–02 (C.M.), ClinicalTrials.gov (NCT02117375), CNRS, 'Fondation A*midex-Investissements d’Avenir', the Stockholm County Council (ALF grant 20150166), Swedish Society for Medical Research (T.G.), Guarantors of Brain (F.P.), ANR-10-COHO-002, OFSEP, EDMUS Foundation against multiple sclerosis, UK MS Society and the National Institute for Health Research University College London Hospitals Biomedical Research Centre, EMD Serono (C.M., R.B.)., ANR-10-COHO-0002,OFSEP,Observatoire Français de la Sclérose en Plaques(2010), Bannier, Elise, Cohortes - Observatoire Français de la Sclérose en Plaques - - OFSEP2010 - ANR-10-COHO-0002 - COHO - VALID, University of California [San Francisco] (UCSF), University of California-University of California, Empenn, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM] (CEMEREM), Eden, Dominique, Gros, Charley, Badji, Atef, Dupont, Sara M, De Leener, Benjamin, Maranzano, Josefina, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobia, Ouellette, Russell, Stawiarz, Leszek, Hillert, Jan, Talbott, Jason, Kerbrat, Anne, Edan, Gille, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Brisset, Jean-Christophe, Valsasina, Paola, Rocca, Maria A, Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Mario, Kearney, Hugh, Ciccarelli, Olga, Smith, Seth A, Andrada Treaba, Constantina, Mainero, Caterina, Lefeuvre, Jennifer, Reich, Daniel S, Nair, Govind, Shepherd, Timothy M, Charlson, Erik, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Narayanan, Sridar, and Cohen-Adad, Julien

Subjects
0301 basic medicine, Adult, Male, medicine.medical_specialty, Cord, multicentre, Grey matter, multiple sclerosis, Spinal Cord Diseases, lesions, White matter, Lesion, 03 medical and health sciences, Disability Evaluation, 0302 clinical medicine, Multiple Sclerosis, Relapsing-Remitting, medicine, Humans, Gray Matter, 10. No inequality, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Spatial Analysis, Expanded Disability Status Scale, Clinically isolated syndrome, business.industry, Multiple sclerosis, Brain, Cervical Cord, spinal cord, Original Articles, Middle Aged, Multiple Sclerosis, Chronic Progressive, medicine.disease, Spinal cord, Magnetic Resonance Imaging, White Matter, 030104 developmental biology, medicine.anatomical_structure, Disease Progression, Female, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Neurology (clinical), Radiology, medicine.symptom, business, 030217 neurology & neurosurgery, MRI
Abstract

International audience; Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Published
2019
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16. Update on brain MRI for the diagnosis and follow-up of MS patients

Author

François Cotton, Sandra Vukusic, Jean-Christophe Brisset, Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Université de Lyon, Hospices Civils de Lyon (HCL), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Fondation Eugène Devic EDMUS, and GAUTHERON, Arthur

Subjects
medicine.medical_specialty, Standardization, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Contrast Media, Gadolinium, 030218 nuclear medicine & medical imaging, Multiple sclerosis, 03 medical and health sciences, Multiple Sclerosis, Relapsing-Remitting, Magnetic resonance imaging, 0302 clinical medicine, medicine, Brain mri, Humans, Registries, Intensive care medicine, Protocol (science), Precautionary principle, business.industry, Brain, General Medicine, medicine.disease, Treatment Outcome, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Round table, Radiological weapon, Practice Guidelines as Topic, OFSEP, Cohort studies, business, 030217 neurology & neurosurgery, Follow-Up Studies, Cohort study
Abstract

Over the past decades, MRI has become a major tool in the diagnosis and the follow-up of patients with multiple sclerosis (MS), especially for monitoring the effectiveness of therapy. The recent international recommendations issued for the standardization of neurological and radiological clinical practices converge on many points. In this setting, recommendations made by the “Observatoire francais de la sclerose en plaques”, the French MS registry, can be distinguished by its interdisciplinary complementarity, its longevity, its size, and its positions in direct connection with the clinic. Hence, after suspicions of gadolinium deposition in the brain, with multiple warning from the American and European health authorities, a national consultation took place and resulted in limitation to useful injections. The precautionary principle prevailing, the patient receives a limited quantity of contrast product even if no clinically harmful manifestation has been detected to date. The result of this round table bringing together neurologists and neuroradiologists from specialized centers was published in the form of a recommendation in early 2020. The interest of this project also lies in the constant improvement of the management of patients with MS and the possibility of developing advanced techniques to assist the clinician. The aim of this review is to explain to the neurologist, the interest of following this imaging protocol both in his/her clinical practice and in the possibilities that this opens up.

Published
2021
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17. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks

Author

Vincent Auclair, Ferran Prados, Jean-Christophe Brisset, Josefina Maranzano, Sridar Narayanan, Kouhei Kamiya, Constantina A. Treaba, Atef Badji, Hugh Kearney, Jean Pelletier, Pierre Labauge, Elise Bannier, Paola Valsasina, Erik Charlson, Daniel S. Reich, Olga Ciccarelli, Dominique Eden, Ren Zhuoquiong, Henitsoa Rasoanandrianina, Virginie Callot, Gilles Edan, Seth A. Smith, Marios C. Yiannakas, Jennifer Lefeuvre, Govind Nair, Allan R. Martin, Julien Cohen-Adad, Timothy M. Shepherd, Jason F. Talbott, Donald G. McLaren, Charley Gros, Masaaki Hori, Shahabeddin Vahdat, Julien Doyon, Yasuhiko Tachibana, Leszek Stawiarz, Shahamat Tauhid, Jan Hillert, Massimo Filippi, Lydia Chougar, Anne Kerbrat, Russell Ouellette, Caterina Mainero, Sara M. Dupont, Tobias Granberg, Bertrand Audoin, Ali Khatibi, Rohit Bakshi, Maria A. Rocca, Michael G. Fehlings, Benjamin De Leener, Yaou Liu, École Polytechnique de Montréal (EPM), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Department of Radiology and Biomedical Imaging [San Francisco], University of California [San Francisco] (UC San Francisco), University of California (UC)-University of California (UC), Xuanwu Hospital of Capital, Deutsche Telekom Group, Department of Computer Science [Liverpool], University of Liverpool, National Institute of Radiological Sciences (NIRS), Juntendo University Hospital [Tokyo], Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Karolinska Institutet [Stockholm], CHU Pontchaillou [Rennes], Vision, Action et Gestion d'informations en Santé (VisAGeS), 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), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [CHU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université de Montpellier (UM), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - AP-HM] (CEMEREM), Hôpital de la Timone [CHU - APHM] (TIMONE)-Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), Vita-Salute San Raffaele University and Center for Translational Genomics and Bioinformatics, Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), NMR Research Unit [London], Institute of Neurology [London], University College of London [London] (UCL)-University College of London [London] (UCL), University College of London [London] (UCL), Vanderbilt University [Nashville], Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], National Institutes of Health [Bethesda] (NIH), Biospective [Montréal], University of Toronto, Unité de Neuroimagerie Fonctionnelle [Montréal] (UNF-CRIUGM), Université de Montréal (UdeM)-Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Stanford University, McConnell Brain Imaging Centre (MNI), McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], New York University Langone Medical Center (NYU Langone Medical Center), NYU System (NYU), CIHR FDN-143263, Canadian Institutes of Health Research, International Society of Regulatory Toxicology and Pharmacology, Svenska Sällskapet för Medicinsk Forskning, IVADO, EDMUS Foundation, TransMedTech, R01 EY023240 (SAS), NIH/NEI, RG-1501-02840 (SAS), National Multiple Sclerosis Society, Intramural Research Program, Hospital Programme of Clinical Research (PHRC), NCT02117375, EMISEP project, Fondation A*midex-Investissements d'Avenir, 435897-2013, Natural Sciences and Engineering Research Council of Canada, Observatoire Français de la Sclérose en plaques (OFSEP), 13034, MOP, Canada Research Chairs, National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC), 2015-PR-182754, Fonds de Recherche du Québec - Nature et Technologies, W81XWH-13-0073 (SAS), U.S. Department of Defense, ANR-10-COHO-002, Agence Nationale de la Recherche, R21 NS087465-01 (SAS), National Institute of Neurological Disorders and Stroke, Fondation Aix-Marseille Universite, SensoriMotor Rehabilitation Research Team (SMRRT), Wings for Life, 20150166, Stockholms Läns Landsting, Centre National de la Recherche Scientifique, 28826, Fonds de Recherche du Québec - Santé, 32454, Canada Foundation for Innovation, Centre d'Exploration Métabolique par Résonance Magnétique [Hôpital de la Timone - APHM] (CEMEREM), University of California [San Francisco] (UCSF), University of California-University of California, SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-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 Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Gui de Chauliac [Montpellier]-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université Montpellier 1 (UM1)-Université de Montpellier (UM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Gros, Charley, De Leener, Benjamin, Badji, Atef, Maranzano, Josefina, Eden, Dominique, Dupont, Sara M., Talbott, Jason, Zhuoquiong, Ren, Liu, Yaou, Granberg, Tobia, Ouellette, Russell, Tachibana, Yasuhiko, Hori, Masaaki, Kamiya, Kouhei, Chougar, Lydia, Stawiarz, Leszek, Hillert, Jan, Bannier, Elise, Kerbrat, Anne, Edan, Gille, Labauge, Pierre, Callot, Virginie, Pelletier, Jean, Audoin, Bertrand, Rasoanandrianina, Henitsoa, Brisset, Jean-Christophe, Valsasina, Paola, Rocca, Maria A., Filippi, Massimo, Bakshi, Rohit, Tauhid, Shahamat, Prados, Ferran, Yiannakas, Mario, Kearney, Hugh, Ciccarelli, Olga, Smith, Seth, Treaba, Constantina Andrada, Mainero, Caterina, Lefeuvre, Jennifer, Reich, Daniel S., Nair, Govind, Auclair, Vincent, Mclaren, Donald G., Martin, Allan R., Fehlings, Michael G., Vahdat, Shahabeddin, Khatibi, Ali, Doyon, Julien, Shepherd, Timothy, Charlson, Erik, Narayanan, Sridar, and Cohen-Adad, Julien

Subjects
FOS: Computer and information sciences, Image Processing, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Neurodegenerative, computer.software_genre, Convolutional neural network, Medical and Health Sciences, Pattern Recognition, Automated, 0302 clinical medicine, Computer-Assisted, Segmentation, Voxel, Image Processing, Computer-Assisted, Medicine, Spinal Cord Injury, Observer Variation, Spinal cord, medicine.diagnostic_test, 05 social sciences, Magnetic Resonance Imaging, 3. Good health, medicine.anatomical_structure, Neurology, Neurological, Biomedical Imaging, Convolutional neural networks, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Radiology, medicine.symptom, MRI, Automated, medicine.medical_specialty, Cord, Multiple Sclerosis, Physical Injury - Accidents and Adverse Effects, Neural Networks, Cognitive Neuroscience, Bioengineering, Pattern Recognition, Sensitivity and Specificity, Autoimmune Disease, 050105 experimental psychology, Article, Lesion, Multiple sclerosis, 03 medical and health sciences, Computer, Humans, 0501 psychology and cognitive sciences, Multiple sclerosi, Traumatic Head and Spine Injury, Neurology & Neurosurgery, business.industry, Psychology and Cognitive Sciences, Neurosciences, Reproducibility of Results, Magnetic resonance imaging, medicine.disease, Brain Disorders, Neural Networks, Computer, business, computer, 030217 neurology & neurosurgery
Abstract

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. The goal of this study was to develop a fully-automatic framework, robust to variability in both image parameters and clinical condition, for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data. Scans of 1,042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n=30). Data spanned three contrasts (T1-, T2-, and T2*-weighted) for a total of 1,943 volumes. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg, a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. The proposed framework is open-source and readily available in the Spinal Cord Toolbox., Comment: 38 pages, 7 figures, 2 tables

Published
2019
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18. Multimodal imaging provides insight into targeted therapy response in metastatic prostate cancer to the bone

Author

Benjamin A, Hoff, Jean-Christophe, Brisset, Stefanie, Galbán, Marcian, Van Dort, David C, Smith, Zachery R, Reichert, Jon A, Jacobson, Gary D, Luker, Thomas L, Chenevert, and Brian D, Ross

Subjects
Original Article
Abstract

Metastatic prostate cancer to bone remains incurable, driving efforts to develop individualized, targeted therapies to improve clinical outcomes while limiting adverse side-effects. Due to the complexity in cellular signaling pathways and the interaction between cancer and its microenvironment, multiparametric imaging approaches for treatment response may improve understanding of the biological effects of therapy. An orthotopic model of castration resistant prostate cancer (CRPC) bone metastasis was treated with the tyrosine kinase inhibitor Cabozantinib (CABO). Response was assessed using CT to monitor bone volumes, 99mTc-MDP SPECT for bone metabolism, and anatomical and diffusion MRI for tumor volume and cell death. A concurrent clinical trial of CABO for CRPC patients also evaluated multimodality imaging in correlation with standard response criteria. Response in the preclinical study found significant slowing in tumor growth rate (P

Published
2018

19. INFLAM - INFLAMmation in Brain and Vessels with Iron Nanoparticles and Cell Trafficking: A Multiscale Approach of Tissue Microenvironment, Iron Nanostructure and Iron Biotransformation

Author

N. Nighoghossian, Claire Corot, Marlène Wiart, Emmanuelle Canet-Soulas, Jean-Christophe Brisset, F. Gazeau, Y. Berthezène, Cardiovasculaire, métabolisme, diabétologie et nutrition (CarMeN), Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hospices Civils de Lyon (HCL), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA), Université de Lyon (COMUE), Matière et Systèmes Complexes (MSC (UMR_7057)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Guerbet, and Centre National de la Recherche Scientifique (CNRS)

Subjects
Pathology, medicine.medical_specialty, magnetic nanoparticles, mice, [SDV]Life Sciences [q-bio], Cell, Biomedical Engineering, Biophysics, AMNP, Inflammation, 02 engineering and technology, ultrasmall superparamagnetic particles, tomography, 030218 nuclear medicine & medical imaging, neuroinflammation, 03 medical and health sciences, ischemic-stroke, 0302 clinical medicine, Engineering, Inflammation imaging, medicine, subacute, Stroke, Neuroinflammation, medicine.diagnostic_test, Bioorganic nanoparticles transformation, business.industry, Magnetic resonance imaging, 021001 nanoscience & nanotechnology, medicine.disease, Atherosclerosis, Acute stage, 3. Good health, medicine.anatomical_structure, uspio-enhanced mri, Ischemic stroke, focal ischemia, [SDV.IB]Life Sciences [q-bio]/Bioengineering, nanoparticles, oxide, Ultrasmall superparamagnetic iron oxide (USPIO), medicine.symptom, 0210 nano-technology, business, MRI
Abstract

International audience; Background: Inflammation is a share process in atherosclerosis and stroke and is thought to be a key player in the evolution of these diseases. Ten years ago, inflammation imaging with magnetic resonance imaging (MRI) was considered very promising for both pre-clinical and clinical studies of atherosclerosis and stroke. Contribution: We report here contributions to the field of inflammation imaging with USPIO-enhanced MRI. The goal was to investigate the life cycle of USPIOs in the body, and how the MRI signal has been impacted during their bio-interactions and bioprocessing. Those mechanisms were applied to pre-clinical longitudinal studies of inflammation in atherosclerosis and at the acute stage of ischemic stroke thus allowing the monitoring of treatment effects. Conclusion: This review presents the contribution of the collaborative research project under the "TecSan" grant from the French Research Agency (ANR) as well as pre-clinical and clinical perspectives of USPIO's inflammation MRI in atherosclerosis and stroke. (C) 2018 Published by Elsevier Masson SAS on behalf of AGBM.

Published
2018
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20. Diagnostic value of 3DFLAIR in clinical practice for the detection of infratentorial lesions in multiple sclerosis in regard to dual echo T2 sequences

Author

Fabrice Bonneville, François Cotton, Salem Hannoun, Charles R.G. Guttmann, Damien Heidelberg, Jean-Christophe Brisset, Vincent Dousset, Roula Hourani, Stéphane Kremer, Thi Thuy Trang Nguyen, Sylvie Grand, RMN et optique : De la mesure au biomarqueur, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Observatoire Français de la Sclérose En Plaques [Lyon] (OFSEP), American University of Beirut Medical Center, Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Service d'Imagerie par Résonance Magnétique (IRM), CHU Grenoble, Service de radiologie [Strasbourg], CHU Strasbourg-Hôpital de Hautepierre [Strasbourg], Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg (UNISTRA), Service de neuroradiologie, CHU Toulouse [Toulouse], Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Center for Neurological Imaging, Departments of Radiology and Neurology, Neuroinflammation: imagerie et thérapie de la sclérose en plaques, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Physiopathologie du système nerveux central - Institut François Magendie, Université Bordeaux Segalen - Bordeaux 2-IFR8-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de Neuroradiologie [Centre Hospitalier Lyon Sud - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), ANR-10-COHO-0002,OFSEP,Observatoire Français de la Sclérose en Plaques(2010), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Pôle Cardiovasculaire et Métabolique [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), and Université de Toulouse (UT)

Subjects
2DT2/PD, Adult, Male, medicine.medical_specialty, Multiple Sclerosis, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, education, Posterior fossa, Lesion detection, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Imaging, Three-Dimensional, Radiologists, medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective cohort study, 3DFLAIR, Neuroradiology, Observer Variation, Brain Diseases, Infratentorial region, business.industry, Multiple sclerosis, General Medicine, medicine.disease, Magnetic Resonance Imaging, Clinical Practice, Dual echo, Female, Radiology, Clinical Competence, business, Epidemiologic Methods, 030217 neurology & neurosurgery
Abstract

Background and purpose The aim of this prospective study is to investigate and evaluate in clinical practice the diagnostic impact of 3DFLAIR in regards to 2DT2/PD in terms of infratentorial lesions detection in multiple sclerosis (MS). Material and methods 164 MS patients from the OFSEP database were reviewed retrospectively. MR examinations were performed on 1.5T or 3T systems from four different centers. Infratentorial lesions were counted and allocated to different regions of the posterior fossa by three raters independently (junior resident, resident with an expertise in neuroradiology, and senior neuro-radiologist) on the 3DFLAIR and 2DT2/PD. Both sequences do not have the same spatial resolution but reflect what is recommended by most of the consensus and done in clinical practice. Results With an overall number of 528 for Rater-1 and 798 for Rater-2 infratentorial lesions, 3DFLAIR had a significantly higher number of lesions detected than 2DT2/PD (303 for Rater-1 and 370 for Rater-2). The prevalence of trigeminal lesions detected by using 3DFLAIR was also significantly higher than 2DT2/PD. ROC analysis showed 3DFLAIR to be more specific and sensitive than 2DT2/PD. An overall difference between all three Raters has been observed. The more the Rater is experienced the more lesions he detects. Conclusion Along with the radiologist ability to detect lesions based on his level of experience, the OFSEP optimized 3DFLAIR can significantly improve infratentorial lesion detection in MS compared to 2DT2/PD. This is important in MS follow-up that takes into account new lesions number to adapt patients’ treatment.

Published
2017
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21. Oncogenic Kras is required for both the initiation and maintenance of pancreatic cancer in mice

Author

Filip Bednar, N. Volkan Adsay, Stefanie Galbán, Karen S. Flannagan, Craig J. Galbán, Marina Pasca di Magliano, Jean-Christophe Brisset, Sabita Rakshit, Yaqing Zhang, and Meredith A. Collins

Subjects
Tumor suppressor gene, Cellular differentiation, Mice, Transgenic, Biology, medicine.disease_cause, Proto-Oncogene Proteins p21(ras), Mice, Paracrine signalling, Pancreatic cancer, medicine, Animals, Humans, Hedgehog Proteins, Cancer, Cell Differentiation, Epithelial Cells, General Medicine, medicine.disease, Hedgehog signaling pathway, Pancreatic Neoplasms, Survival Rate, Disease Models, Animal, Cell Transformation, Neoplastic, Pancreatitis, Cancer research, KRAS, Carcinogenesis, Research Article, Signal Transduction
Abstract

Pancreatic cancer is almost invariably associated with mutations in the KRAS gene, most commonly KRASG12D, that result in a dominant-active form of the KRAS GTPase. However, how KRAS mutations promote pancreatic carcinogenesis is not fully understood, and whether oncogenic KRAS is required for the maintenance of pancreatic cancer has not been established. To address these questions, we generated two mouse models of pancreatic tumorigenesis: mice transgenic for inducible KrasG12D, which allows for inducible, pancreas-specific, and reversible expression of the oncogenic KrasG12D, with or without inactivation of one allele of the tumor suppressor gene p53. Here, we report that, early in tumorigenesis, induction of oncogenic KrasG12D reversibly altered normal epithelial differentiation following tissue damage, leading to precancerous lesions. Inactivation of KrasG12D in established precursor lesions and during progression to cancer led to regression of the lesions, indicating that KrasG12D was required for tumor cell survival. Strikingly, during all stages of carcinogenesis, KrasG12D upregulated Hedgehog signaling, inflammatory pathways, and several pathways known to mediate paracrine interactions between epithelial cells and their surrounding microenvironment, thus promoting formation and maintenance of the fibroinflammatory stroma that plays a pivotal role in pancreatic cancer. Our data establish that epithelial KrasG12D influences multiple cell types to drive pancreatic tumorigenesis and is essential for tumor maintenance. They also strongly support the notion that inhibiting KrasG12D, or its downstream effectors, could provide a new approach for the treatment of pancreatic cancer.

Published
2012
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22. Longitudinal study of multiple sclerosis lesions using ultra-high field (7T) multiparametric MR imaging

Author

Tim Sinnecker, Jean-Christophe Brisset, Ilya Kister, Sanjeev Chawla, Jens Wuerfel, Friedemann Paul, and Yulin Ge

Subjects
Adult, Male, Longitudinal study, Multiple Sclerosis, lcsh:Medicine, 030218 nuclear medicine & medical imaging, Lesion, 03 medical and health sciences, 0302 clinical medicine, Ultra high field, medicine, Humans, Longitudinal Studies, lcsh:Science, Aged, Multidisciplinary, medicine.diagnostic_test, business.industry, Multiple sclerosis, lcsh:R, Brain, Quantitative susceptibility mapping, Magnetic resonance imaging, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Signal on, Mr imaging, Disease Progression, lcsh:Q, Female, medicine.symptom, Function and Dysfunction of the Nervous System, business, Nuclear medicine, 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

Pathophysiology of multiple sclerosis (MS) lesions is dynamic and changes over time. The purpose of this exploratory study was to determine the longitudinal changes in MS lesions over time on ultra-high field MR imaging. Nine patients with MS underwent high-resolution 3D-susceptibility weighted imaging (SWI) and 2D-gradient-echo-T2*-weighted imaging on 7T MRI at baseline and after ~2.4 years of follow-up. Morphologic imaging characteristics, signal intensity patterns and quantitative susceptibility mapping (QSM) values of lesions were recorded at both time points. Lesions were classified as "iron-laden" if they demonstrated hypointense signal on T2*-weighted images and/or SWI as well as hyperintense signal on QSM. Lesions were considered "non-iron-laden" if they were hyperintense on T2*/SWI and isointense or hyperintense on QSM. Total of 162 non-iron-laden and 29 iron-laden lesions were observed at baseline. No change in baseline lesion size during follow up was recorded in 92.7%; no change in lesion-vessel relationship in 86.5%; and no change in signal intensity pattern in 96.9% of lesions. Three lesions which were non-iron-laden at baseline, exhibited iron at follow-up. In two iron-laden lesions, redistribution of iron content was observed at follow-up. Two-thirds of these iron-laden lesions showed an increase in QSM at follow-up relative to baseline, and the remaining one-third exhibited decrease in QSM. Most of the newly formed lesions (11/13, 84.6%) at follow-up were iron-laden. 7T multiparametric MRI is a useful tool for tracking the evolution of MS lesions, especially with regard to changes in iron content.

Published
2018
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23. Early-Stage Investigations of Ultrasmall Superparamagnetic Iron Oxide-Induced Signal Change After Permanent Middle Cerebral Artery Occlusion in Mice

Author

Virginie Desestret, Jérôme Honnorat, Samir Moucharrafie, Norbert Nighoghossian, Emilie Devillard, Serge Nataf, Marlène Wiart, Jean-Christophe Brisset, and Yves Berthezène

Subjects
Male, Middle Cerebral Artery, Pathology, medicine.medical_specialty, Iron, Contrast Media, Immunoglobulins, Arterial Occlusive Diseases, Bone Marrow Cells, Inflammation, Ferric Compounds, Hippocampus, Monocytes, Cerebral Ventricles, Corpus Callosum, Brain ischemia, Mice, Phagocytosis, medicine.artery, Immunochemistry, medicine, Animals, Macrophage, Coloring Agents, Magnetite Nanoparticles, Stroke, Advanced and Specialized Nursing, medicine.diagnostic_test, business.industry, Macrophages, Monocyte, Electron Spin Resonance Spectroscopy, Dextrans, Oxides, Magnetic resonance imaging, Flow Cytometry, medicine.disease, Immunohistochemistry, Magnetic Resonance Imaging, Ferrosoferric Oxide, medicine.anatomical_structure, Ischemic Attack, Transient, Injections, Intravenous, Middle cerebral artery, Neurology (clinical), medicine.symptom, Cardiology and Cardiovascular Medicine, business
Abstract

Background and Purpose— MR signal changes after intravenous ultrasmall superparamagnetic iron oxide (USPIO) injection are related to inflammatory cells at the subacute stages after focal cerebral injury. However, at the early stages, the interpretation of USPIO-related MR signal alterations remains controversial. Here, we compared MR signal changes after intravenous USPIO injection with the histological iron and macrophage distribution during the first 24 hours in a rodent model of acute stroke. Methods— Multiparametric MRI at 7T and histological USPIO distribution were confronted from 6 to 24 hours after permanent middle cerebral artery occlusion in mice. Blood–brain barrier disruption was assessed using gadolinium MRI and immunoglobulin staining. Prussian blue staining was performed to depict the USPIO brain distribution. USPIO uptake by phagocytes was assessed by immunochemistry on brain tissue, peripheral blood cells, and monocyte cells derived from bone marrow culture. Results— After USPIO injection, 4 areas of early signal change were observed on every MRI. In all these areas, iron particles were mostly free whether detected in the vascular and cerebrospinal fluid compartments or in the interstitium. Within the first 24 hours, USPIO-loaded cells were not detected in the blood of injured mice or in cultured monocytic cells incubated with USPIO at plasmatic concentration. Conclusions— These results suggest that, in this model, early reproducible USPIO-related MR signal changes are mainly caused by passive diffusion of free USPIO after blood–brain barrier leakage and by intravascular trapping rather than by peripheral phagocyte infiltration.

Published
2009
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24. Iron and Non-Iron-Related Characteristics of Multiple Sclerosis and Neuromyelitis Optica Lesions at 7T MRI

Author

Ilya Kister, Ewart Mark Haacke, Jean-Christophe Brisset, Jens Wuerfel, Friedemann Paul, Yulin Ge, Petr Dusek, Tim Sinnecker, Saifeng Liu, and Sanjeev Chawla

Subjects
Adult, Male, Pathology, medicine.medical_specialty, Multiple Sclerosis, Adolescent, Iron, Brain mapping, Article, 030218 nuclear medicine & medical imaging, Lesion, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Electromagnetic Fields, Imaging, Three-Dimensional, Image Processing, Computer-Assisted, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Child, Brain Mapping, Neuromyelitis optica, medicine.diagnostic_test, business.industry, Multiple sclerosis, Neuromyelitis Optica, Infant, Newborn, Infant, Quantitative susceptibility mapping, Magnetic resonance imaging, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Pathophysiology, Hyperintensity, Child, Preschool, Female, Neurology (clinical), medicine.symptom, business, Nuclear medicine, 030217 neurology & neurosurgery, Algorithms
Abstract

BACKGROUND AND PURPOSE: Characterization of iron deposition associated with demyelinating lesions of multiple sclerosis and neuromyelitis optica has not been well studied. Our aim was to investigate the potential of ultra-high-field MR imaging to distinguish MS from neuromyelitis optica and to characterize tissue injury associated with iron pathology within lesions. MATERIALS AND METHODS: Twenty-one patients with MS and 21 patients with neuromyelitis optica underwent 7T high-resolution 2D-gradient-echo-T2* and 3D-susceptibility-weighted imaging. An in-house-developed algorithm was used to reconstruct quantitative susceptibility mapping from SWI. Lesions were classified as “iron-laden” if they demonstrated hypointensity on gradient-echo-T2*-weighted images and/or SWI and hyperintensity on quantitative susceptibility mapping. Lesions were considered “non-iron-laden” if they were hyperintense on gradient-echo-T2* and isointense or hyperintense on quantitative susceptibility mapping. RESULTS: Of 21 patients with MS, 19 (90.5%) demonstrated at least 1 quantitative susceptibility mapping–hyperintense lesion, and 11/21 (52.4%) had iron-laden lesions. No quantitative susceptibility mapping–hyperintense or iron-laden lesions were observed in any patients with neuromyelitis optica. Iron-laden and non-iron-laden lesions could each be further characterized into 2 distinct patterns based on lesion signal and morphology on gradient-echo-T2*/SWI and quantitative susceptibility mapping. In MS, most lesions ( n = 262, 75.9% of all lesions) were hyperintense on gradient-echo T2* and isointense on quantitative susceptibility mapping (pattern A), while a small minority ( n = 26, 7.5% of all lesions) were hyperintense on both gradient-echo-T2* and quantitative susceptibility mapping (pattern B). Iron-laden lesions ( n = 57, 16.5% of all lesions) were further classified as nodular ( n = 22, 6.4%, pattern C) or ringlike ( n = 35, 10.1%, pattern D). CONCLUSIONS: Ultra-high-field MR imaging may be useful in distinguishing MS from neuromyelitis optica. Different patterns related to iron and noniron pathology may provide in vivo insight into the pathophysiology of lesions in MS.

Published
2015

25. Impaired cerebrovascular reactivity in multiple sclerosis

Author

Hanzhang Lu, Peiying Liu, Feng Xu, Robert I. Grossman, Yulin Ge, Olga Marshall, Jean-Christophe Brisset, and Joseph Herbert

Subjects
Adult, Male, Article, Magnetic resonance angiography, Hypercapnia, Atrophy, Multiple Sclerosis, Relapsing-Remitting, medicine, Humans, Normocapnia, Gray Matter, Cerebral atrophy, medicine.diagnostic_test, Vasomotor, business.industry, Multiple sclerosis, Brain, Carbon Dioxide, Middle Aged, Multiple Sclerosis, Chronic Progressive, medicine.disease, Vasodilation, Cerebral blood flow, Anesthesia, Case-Control Studies, Cerebrovascular Circulation, Regression Analysis, Female, Neurology (clinical), medicine.symptom, business, Magnetic Resonance Angiography
Abstract

Importance Cerebrovascular reactivity (CVR) is an inherent indicator of the dilatory capacity of cerebral arterioles for a vasomotor stimulus for maintaining a spontaneous and instant increase of cerebral blood flow (CBF) in response to neural activation. The integrity of this mechanism is essential to preserving healthy neurovascular coupling; however, to our knowledge, no studies have investigated whether there are CVR abnormalities in multiple sclerosis (MS). Objective To use hypercapnic perfusion magnetic resonance imaging to assess CVR impairment in patients with MS. Design, Setting, and Participants A total of 19 healthy volunteers and 19 patients with MS underwent perfusion magnetic resonance imaging based on pseudocontinuous arterial spin labeling to measure CBF at normocapnia (ie, breathing room air) and hypercapnia. The hypercapnia condition is achieved by breathing 5% carbon dioxide gas mixture, which is a potent vasodilator causing an increase of CBF. Main Outcomes and Measures Cerebrovascular reactivity was calculated as the percent increase of normocapnic to hypercapnic CBF normalized by the change in end-tidal carbon dioxide, which was recorded during both conditions. Group analysis was performed for regional and global CVR comparison between patients and controls. Regression analysis was also performed between CVR values, lesion load, and brain atrophy measures in patients with MS. Results A significant decrease of mean (SD) global gray matter CVR was found in patients with MS (3.56 [0.81]) compared with healthy controls (5.08 [1.56]; P = .001). Voxel-by-voxel analysis showed diffuse reduction of CVR in multiple regions of patients with MS. There was a significant negative correlation between gray matter CVR and lesion volume ( R = 0.6, P = .004) and a significant positive correlation between global gray matter CVR and gray matter atrophy index ( R = 0.5, P = .03). Conclusions and Relevance Our quantitative imaging findings suggest impairment in functional cerebrovascular pathophysiology, by measuring a diffuse decrease in CVR, which may be the underlying cause of neurodegeneration in MS.

Published
2014

26. Parametric Response Mapping of CT Images Provides Early Detection of Local Bone Loss in a Rat Model of Osteoporosis

Author

Alnawaz Rehemtulla, Jennifer L. Boes, Catherine Van Poznak, Kenneth M. Kozloff, Brian D. Ross, Jon A. Jacobson, Stefanie Galbán, Craig J. Galbán, Charles R. Meyer, Jean-Christophe Brisset, Timothy D. Johnson, and Benjamin A. Hoff

Subjects
medicine.medical_specialty, Histology, Physiology, Endocrinology, Diabetes and Metabolism, Radiography, Ovariectomy, Osteoporosis, computer.software_genre, Bone resorption, Article, Rats, Sprague-Dawley, Voxel, Bone Density, medicine, Animals, Bone mineral, business.industry, Cancer, medicine.disease, Rats, Orthopedic surgery, Biomarker (medicine), Female, Radiology, business, computer
Abstract

Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss.

Published
2012

27. Quantification of iron-labeled cells with positive contrast in mouse brains

Author

Yves Berthezène, Emmanuelle Canet-Soulas, Jérôme Honnorat, Virginie Desestret, Monica Sigovan, Emilie Devillard, Monique Touret, Marlène Wiart, Serge Nataf, Adrien Riou, Norbert Nighoghossian, Fabien Chauveau, and Jean-Christophe Brisset

Subjects
Cancer Research, Relaxometry, medicine.medical_specialty, Iron, Contrast Media, Ferric Compounds, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Mice, 0302 clinical medicine, Nuclear magnetic resonance, Text mining, medicine, Image Processing, Computer-Assisted, Animals, Radiology, Nuclear Medicine and imaging, medicine.diagnostic_test, Staining and Labeling, Chemistry, business.industry, Brain, Magnetic resonance imaging, equipment and supplies, Mice, Inbred C57BL, Oncology, Positive contrast, Nanoparticles, Female, Radiology, business, Artifacts, human activities, 030217 neurology & neurosurgery
Abstract

To quantify small amounts of iron-labeled cells in mouse brains with magnetic resonance imaging (MRI).Iron-labeled cells (from 500 to 7,500) were stereotaxically transplanted into the brain of living mice that were subsequently imaged with MRI at 4.7 T. We compared four quantitative methods: (1) T2 relaxometry, (2) T2* relaxometry, (3) the volume of the cloverleaf hypointense artifact generated on T2*-weighted images, and (4) the volume of the cloverleaf hyperintense artifact generated on positive contrast images.The methods based on relaxometry, whether T2 or T2*, did not correlate with the number of injected cells. By contrast, those based on measurement of cloverleaf artifact volume, whether using negative or positive enhancement, showed a significant linear relationship for the given range of cells (R [0.92-0.95], p 0.05).T2* artifact volume imaging (negative or positive) appears promising for the quantification of magnetically labeled cells following focal injection in the brain.

Published
2010

28. Diffusion-weighted MRI for assessment of early cancer treatment response

Author

Craig J. Galbán, Jean-Christophe Brisset, Stefanie Galbán, Alnawaz Rehemtulla, Brian D. Ross, and Thomas L. Chenevert

Subjects
Oncology, medicine.medical_specialty, Pathology, Treatment response, Imaging biomarker, Pharmaceutical Science, Molecular Probe Techniques, Article, Internal medicine, Neoplasms, medicine, Effective diffusion coefficient, Humans, Tumor microenvironment, business.industry, Cancer, medicine.disease, Image Enhancement, Prognosis, Molecular Imaging, Diffusion Magnetic Resonance Imaging, Treatment Outcome, Molecular Probes, Biomarker (medicine), Molecular imaging, business, Biotechnology, Diffusion MRI
Abstract

Recent clinical practice for the management for cancer patients has begun to change from a statistical “one-size fits all” approach to medicine to more individualized care. Pre-treatment biomarkers (i.e. genetically and histologically based) have a growing role in providing guidance related to the appropriate therapy and likelihood of response; they do not take into account heterogeneity within the tumor mass. Thus, a biomarker which could be utilized to measure actual tumor response early following treatment initiation would provide an important opportunity to evaluate treatment effects on an individual patient basis. Diffusion weighted magnetic resonance imaging (DW-MRI) offers the opportunity to monitor treatment-associated alterations in tumor microenvironment using quantification of changes in tumor water diffusion values as a surrogate imaging biomarker. Results obtained thus far using DW-MRI have shown that changes in tumor diffusion values can be detected early following treatment initiation which correlate with traditional outcome measures. Sensitive imaging biomarkers are providing for the first time a means of assessing 3 dimensional tumor response early in the treatment cycle which may also provide opportunities to visualize spatial heterogeneity of response within the tumor which could open up further opportunities for spatially modulating therapy. This review highlights the development of DW-MRI and its proposed usefulness in the clinical management of cancer patients. The utility of DW-MRI for assessing therapeutic-induced response is further evaluated on tumors residing in the brain, head and neck and bone.

Published
2010

29. In vivo MRI assessment of permanent middle cerebral artery occlusion by electrocoagulation: pitfalls of procedure

Author

Marlène Wiart, Jean-Christophe Brisset, Tae-Hee Cho, Samir Moucharrafie, Yves Berthezène, Norbert Nighoghossian, Fabien Chauveau, Centre de Recherche et d'Application en Traitement de l'Image et du Signal (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-École Supérieure Chimie Physique Électronique de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Cerebrovascular Unit [Lyon], Hôpital neurologique et neurochirurgical Pierre Wertheimer [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), BMC, Ed., Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
medicine.medical_specialty, Cognitive Neuroscience, medicine.medical_treatment, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Short Report, Neuroscience (miscellaneous), Brain damage, Temporal muscle, 030218 nuclear medicine & medical imaging, Lesion, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, medicine.artery, Occlusion, medicine, Craniotomy, business.industry, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Hyperintensity, Surgery, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Middle cerebral artery, Cauterization, Radiology, medicine.symptom, business, 030217 neurology & neurosurgery
Abstract

Permanent middle cerebral artery (MCA) occlusion (pMCAO) by electrocoagulation is a commonly used model but with potential traumatic lesions. Early MRI monitoring may assess pMCAO for non-specific brain damage. The surgical steps of pMCAO were evaluated for traumatic cerebral injury in 22 Swiss mice using diffusion and T2-weighted MRI (7T) performed within 1 h and 24 h after surgery. Temporal muscle cauterization without MCA occlusion produced an early T2 hyperintensity mimicking an infarct. No lesion was visible after temporal muscle incision or craniotomy. Early MRI monitoring is useful to identify non-specific brain injury that could hamper neuroprotective drugs assessment.

Published
2010
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30. Quantitative effects of cell internalization of two types of ultrasmall superparamagnetic iron oxide nanoparticles at 4.7 T and 7 T

Author

Jean-Christophe Brisset, Marlène Wiart, F. Lagarde, Virginie Desestret, Yves Berthezène, Norbert Nighoghossian, Serge Nataf, Emilie Devillard, Fabien Chauveau, and S. Marcellino

Subjects
medicine.medical_specialty, media_common.quotation_subject, Cell, Nanoparticle, Contrast Media, Mice, Ferumoxtran-10, medicine, Animals, Radiology, Nuclear Medicine and imaging, Tissue Distribution, Whole Body Imaging, Internalization, Magnetite Nanoparticles, media_common, business.industry, Ultrasmall superparamagnetic iron oxide, Macrophages, Dextrans, General Medicine, Image Enhancement, Mr imaging, Magnetic Resonance Imaging, Ferrosoferric Oxide, Mice, Inbred C57BL, medicine.anatomical_structure, Biophysics, Nanoparticles, Female, High field, Radiology, business, Superparamagnetism
Abstract

MRI coupled with the intravenous injection of ultrasmall superparamagnetic particles of iron oxides (USPIOs) is a promising tool for the study of neuroinflammation. Quantification of the approximate number of magnetically labelled macrophages may provide an effective and efficient method for monitoring inflammatory cells. The purpose of the present study was to characterise the relaxation properties of macrophages labelled with two types of USPIOs, at 4.7 T and 7 T.USPIO-labelled bone-marrow-derived macrophage phantoms were compared with phantoms of free dispersed USPIOs with the same global iron concentration, using multi-parametric (T1, T2 and T2) quantitative MRI. The same protocol was then evaluated in living mice after intracerebral injection of iron-labelled macrophages vs free iron oxide.A linear relationship was observed among R1, R2 and R2 values and iron concentration in vitro at 4.7 T and at 7 T. At a given field, T1 and T2 relaxivities of both types of USPIOs decreased following internalisation into macrophages, while T2 relaxivities increased.There was fair overall agreement between the theoretical number of injected cells and the number estimated from T2 quantification and in vitro calibration curves, supporting the validity of the present in vitro calibration curves for in vivo investigation.

Published
2009

31. Abstract 5595: Imaging biomarker development for treatment efficacy for prostate cancer to the bone

Author

Stephanie Galban, Craig J. Galbán, Benjamin A. Hoff, Joshua S. George, Jean-Christophe Brisset, Brian D. Ross, and Alnawaz Rehemtulla

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Prostate cancer, Imaging biomarker, business.industry, Internal medicine, medicine, Urology, medicine.disease, business, Treatment efficacy
Abstract

Approximately 70% of patients with late stage cancers metastasize to the bone. RECIST identifies these tumors as “unmeasureable” for therapeutic response assessment. Cabozantinib (CABO), a tyrosine kinase inhibitor of MET and VEGFR2, has shown promise as an effective therapy for metastatic prostate cancer to the bone. Patients treated with CABO showed a reduction in [Tc99m]-bone scan signal suggesting tumor response to treatment. Nevertheless, a return in signal to pre-treatment levels was observed in these patients following therapy completion. It has yet to be determined if the response observed in bone scans results from tumor death, changes in bone metabolism or vascular alterations in the tumor-stromal microenvironment resulting in reduced transport of the imaging tracer. The study objective was to assess tumor and bone response to CABO in an animal model of bone metastasis using a quantitative multi-modal imaging approach. Twenty-seven male SCID mice were implanted with PC3 cell line in the right tibia. PC3 cells were transfected with a plasmid expressing a bioluminescence imaging (BLI) reporter for measuring apoptosis. When tumor volumes reached 10mm3 by MRI, mice were distributed into 2 groups: CABO at 30 mg/kg (N=13) and vehicle (N=14). Treatments were delivered by oral gavage once a day for three weeks. Starting pre-treatment, MRI and BLI were acquired every third day and CT every week. Tumor and bone volumes were monitored by manually contouring volumes of interest (VOI) on anatomical MRI and CT images, respectively. The apparent diffusion coefficient (ADC), an indirect measure of tumor cellularity, was calculated from diffusion MRI. Mice treated with CABO were found to have significantly higher ADC values and slower growth profile than controls (p Citation Format: Joshua S. George, Craig J. Galban, Jean-Christophe Brisset, Benjamin Hoff, Stephanie Galban, Alnawaz Rehemtulla, Brian D. Ross. Imaging biomarker development for treatment efficacy for prostate cancer to the bone. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5595. doi:10.1158/1538-7445.AM2013-5595

Published
2013
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32. Abstract 4299: Evaluation of a new multimodality voxel-based imaging biomarker for therapeutic response assessment in GBM

Author

Pia C. Sundgren, A. Rehemtulla, Brian D. Ross, Craig J. Galbán, Larry Junck, Christina Tsien, Thomas L. Chenevert, Stefanie Galbán, Timothy D. Johnson, Jennifer L. Boes, Benjamin Lemasson, Theodore S. Lawrence, Charles R. Meyer, and Jean-Christophe Brisset

Subjects
Cancer Research, Receiver operating characteristic, Imaging biomarker, business.industry, Fluid-attenuated inversion recovery, computer.software_genre, medicine.disease, Response assessment, Cerebral blood volume, Oncology, Voxel, Glioma, Medicine, Time point, Nuclear medicine, business, computer
Abstract

The purpose of this study was to evaluate the diagnostic performance of MRI based T1 and relative cerebral blood volume (rCBV) maps analyzed a multi-modality voxel-based analysis referred to as multi-parametric response mapping (mPRM) for early chemoradiation response prediction in patients diagnosed with high-grade gliomas. Patients (n=23) with Grade III/IV glioma were recruited in a prospective imaging trial. Patients underwent MRI before RT, 1 and 3 weeks after RT. The MRI protocol included fluid-attenuated inversion recovery imaging (FLAIR), quantitative T1 mapping, dynamic contrast-susceptibility T2*-weighted imaging (rCBV) and contrast-enhanced T1-weighted imaging (CE-T1w). All images were co-registered to CE-T1w images acquired before RT. Following co-registration, the tumor VOIs were manually contoured either on the CE-T1w or on the FLAIR images and applied to the rCBV and T1maps. For each patient, mid-treatment time point and VOI the percentage change, PRM and mPRM techniques were used to analyze data. Briefly, PRM was performed by calculating the difference in the rCBV values of each voxel within the tumor at mid-treatment values with respective pre-treatment values. A threshold was then applied to the absolute difference of the rCBV in a voxel and all like voxels were summed to obtain tumor volume fractions that showed significantly increasing (PRMrCBV+), decreasing (PRMrCBV-), and unchanged (PRMrCBV0) rCBV values following therapy. We used the same procedure for determining the PRM of T1 maps. mPRMs maps were computed by combining both PRMs (T1 and rCBV) in a single color map. Receiver operator characteristic analysis (ROC), assessed for 12 month survival, was used to determine the optimal cutoff for each parameter. The patient population was then stratified based on the optimal cutoffs obtained from the ROC analysis. Overall survival for each parameter was determined using Kaplan-Meier curves and the log-rank test. Standard PRM, using T1or rCBV maps (specifically PRMT1+ and PRMrCBV- metrics) and percentage change methods were found to be predictive of survival only for specific time of acquisition and VOI used. It was determined that mPRMT1+/rCBV- significantly identified patients resistant to therapy irrespective of tumor volume delineation on CE-T1w or FLAIR images and the time point mid-treatment used. Our results show that mPRM improves the sensitivity of quantitative T1 and rCBV maps to predict overall patient survival. This study introduces a new approach for analyzing and combining multi-parametric MR images into a single multi-parametric response map. The mPRM metric showed promise as an early and robust imaging biomarker of treatment response in patients diagnosed with high grade gliomas. This novel approach is a very sensitive tool for analysis of multiparametric and/or multimodal data with enhanced sensitivity for early detection of therapy response. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4299. doi:1538-7445.AM2012-4299

Published
2012
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33. Abstract 4066: Early assessment of the XL184 treatment by Diffusion-Weighted MRI in metastatic prostate cancer to the bone murine model

Author

Jean-Christophe Brisset, Benjamin A. Hoff, Brian D. Ross, Alnawaz Rehemtulla, Craig J. Galbán, Benjamin Lemasson, and Stefanie Galbán

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Pathology, Cabozantinib, Surrogate endpoint, business.industry, Cancer, medicine.disease, Metastasis, Prostate cancer, chemistry.chemical_compound, medicine.anatomical_structure, chemistry, Prostate, Internal medicine, Cancer cell, medicine, Biomarker (medicine), business
Abstract

Ninety percent of patients with advanced prostate cancer develop metastases to the bone1. At present, there is no definitive means for assessing response to therapy, with RECIST identifying tumors in the bone as “unmeasureable”. Cabozantinib (XL184) is an oral small molecular pan-tyrosine kinase inhibitor of primarily MET and vascular endothelial growth factor receptor 2 (VEGFR2). MET is known to play key roles in cellular proliferation, migration and invasion, which contribute to the survival and metastasis of cancer cells. XL184 is already in Phase 2 trials to evaluate the therapeutic benefit on castration-resistant prostate cancer metastatic to the bone. Diffusion-weighted MRI (DW-MRI) is highly sensitive to microscopic changes in tumor tissue. Our goal was to evaluate DW-MRI for detection and quantification of changes in tumor tissue following one-week XL184 treatment. MR experiments were performed on a 9.4T MRI. Human prostate cancer (PC3) cells were implanted by direct intra-tibial injection into male SCID mice, which serves as a model for prostate bone metastases2. Upon measuring tumor volume of ∼10mm3 on anatomical scans, mice were distributed into 2 groups: XL184 at 30 mg/kg (N=7) and vehicle (N=5). Treatments were delivered by oral gavage once a day for 7 days. DW-MRI was performed at days 0 (pre-treatment), 1, 4, 7, 11, 14 and twice a week after. Apparent diffusion coefficient (ADC) maps were calculated analytically from DW-MR images acquired at b-value 120 and 1200 s/mm2. End point of the study was when tumor volume reached 5x the initial measure. Unpaired Student t-test was performed to compare MRI metrics. XL184 treated mice had smaller tumor volume growth rate than control mice. Significant differences in tumor volume were not observed until 14 days post-treatment initiation (p Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4066. doi:1538-7445.AM2012-4066

Published
2012
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34. Abstract 4890: Diffusion-weighted MRI provides an early assessment of treatment response in a murine model of metastatic prostate cancer to the bone

Author

Jean-Christophe Brisset, Brian D. Ross, Kenneth J. Pienta, Craig J. Galbán, Stefanie Galbán, and Alnawaz Rehemtulla

Subjects
Cancer Research, Treatment response, Pathology, medicine.medical_specialty, business.industry, Cancer, medicine.disease, Prostate cancer, medicine.anatomical_structure, Oncology, Docetaxel, Prostate, Murine model, medicine, Effective diffusion coefficient, Nuclear medicine, business, Diffusion MRI, medicine.drug
Abstract

Ninety percent of patients with advanced prostate cancer develop metastases to the bone1. At present, there is no definitive means for assessing response to therapy, with RECIST identifying tumors in the bone as “unmeasureable”. Diffusion-weighted MRI (DW-MRI) is highly sensitive to microscopic changes in tumor tissue. Our goal is to use DW-MRI to detect and quantify changes in tumor tissue throughout therapy where the magnitude of the change could be related to the effectiveness of the treatment. Human prostate cancer (PC3) cells were implanted by direct intra-tibial injection into male SCID mice, which served as a model for prostate bone metastases. MRI experiments were performed on a 9.4T MRI. Upon identifying a tumor volume of ∼10mm3, animals were randomly distributed into 4 treatment groups: docetaxel 20 mg/kg i.p. dose once a week for 3 doses (qd7×3; N=5), fractionated radiation IR at 2 Gy/day 5x per week for 2 weeks (N=7), combined treatment (N=5) and control (N=6). Animals were imaged by DW-MRI in which the apparent diffusion coefficient was calculated from the DW images. Tumor volume and ADC measurements were acquired pre-treatment and on days 0, 1, 4, 7, and once per week after post-treatment initiation. Animals were removed from the study when the tumor reached a percent increase of 400% (5x the initial tumor volume). Group comparisons in MRI metrics were obtained using an unpaired Student t-test. Mice treated by Dox or IR had significant smaller increase in tumor volume compared to control mice. Combined treatment resulted in improved efficacy over lone therapies. This resulted in a significant decrease in tumor size. The Dox group showed an increase in ADC following the first administration and a slow decline in ADC values following day 4 post-treatment initiations regardless of additional treatments. ADC value for IR treated animals did not elevate above control until day 7. Combined treatment generated increased ADC values that were maintained throughout the treatment cycle. IR and Dox alone and in combination were effective as assessed by anatomical and DW-MRI. Those results demonstrate the potential of quantitative ADC map for assessing early response of metastatic cancer to the bone. References: 1. Carlin BI et al. Cancer. 2000;88(12):2989-2994. 2. Lee KC et al. Cancer Res. 2007;67(8):3524-3528. 3. Lee KC Neoplasia. 2007;9(12):1003-1011. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4890. doi:10.1158/1538-7445.AM2011-4890

Published
2011
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35. A nonalcoholic fatty liver disease cirrhosis model in gerbil: the dynamic relationship between hepatic lipid metabolism and cirrhosis

Author

Li, Wei, Guan, Zheng, Jean-Christophe Brisset, Shi, Qiaojuan, Lou, Qi, Ma, Yue, Suriguga, Su, Ying, Huazhong, Sa, Xiaoying, Chen, Zhenwen, Quax, Wim J., Chu, Xiaofeng, Chemical and Pharmaceutical Biology, Biopharmaceuticals, Discovery, Design and Delivery (BDDD), and Nanotechnology and Biophysics in Medicine (NANOBIOMED)

Subjects
MONGOLIAN GERBIL, INSULIN-RESISTANCE, gerbil, fibrosis, UNITED-STATES, ASSOCIATION, hepatic lipid metabolism, STEATOHEPATITIS, MICE, Cirrhosis, NAFLD, lipids (amino acids, peptides, and proteins), nonalcoholic fatty liver disease (NAFLD), DIETARY-CHOLESTEROL
Abstract

Nonalcoholic fatty liver disease (NAFLD) usually takes decades to develop into cirrhosis, which limits the longitudinal study of NAFLD. This work aims at developing a NAFLD-caused cirrhosis model in gerbil and examining the dynamic relationship between hepatic lipid metabolism and cirrhosis. We fed gerbil a high-fat and high-cholesterol diet (HFHCD) for 24 weeks, and recorded the gerbil's phenotype at 3, 6, 9, 12, 15, 18, 21, 24 weeks. The model's pathological process, lipid metabolism, oxidative stress, liver collagen deposition and presence of relevant cytokines were tested and evaluated during the full-time frame of disease onset. The gerbil model can induce nonalcoholic steatohepatitis (NASH) within 9 weeks, and can develop cirrhosis after 21 weeks induction. The model's lipids metabolism disorder is accompanied with the liver damage development. During the NAFLD progression, triglycerides (TG) and free fatty acids (FFA) have presented distinct rise and fall tendency, and the turning points are at the fibrosis stage. Besides that, the ratios of total cholesterol (CHO) to high-density lipoprotein cholesterol (HDL-C) exhibited constant growth tendency, and have a good linear relationship with hepatic stellate cells (HSC) (R-2 = 0.802, P

36. Integrated multimodal imaging of dynamic bone-tumor alterations associated with metastatic prostate cancer.

Author

Jean-Christophe Brisset, Benjamin A Hoff, Thomas L Chenevert, Jon A Jacobson, Jennifer L Boes, Stefanie Galbán, Alnawaz Rehemtulla, Timothy D Johnson, Kenneth J Pienta, Craig J Galbán, Charles R Meyer, Timothy Schakel, Klaas Nicolay, Ajjai S Alva, Maha Hussain, and Brian D Ross

Subjects
Medicine, Science
Abstract

Bone metastasis occurs for men with advanced prostate cancer which promotes osseous growth and destruction driven by alterations in osteoblast and osteoclast homeostasis. Patients can experience pain, spontaneous fractures and morbidity eroding overall quality of life. The complex and dynamic cellular interactions within the bone microenvironment limit current treatment options thus prostate to bone metastases remains incurable. This study uses voxel-based analysis of diffusion-weighted MRI and CT scans to simultaneously evaluate temporal changes in normal bone homeostasis along with prostate bone metatastsis to deliver an improved understanding of the spatiotemporal local microenvironment. Dynamic tumor-stromal interactions were assessed during treatment in mouse models along with a pilot prospective clinical trial with metastatic hormone sensitive and castration resistant prostate cancer patients with bone metastases. Longitudinal changes in tumor and bone imaging metrics during delivery of therapy were quantified. Studies revealed that voxel-based parametric response maps (PRM) of DW-MRI and CT scans could be used to quantify and spatially visualize dynamic changes during prostate tumor growth and in response to treatment thereby distinguishing patients with stable disease from those with progressive disease (p

Published
2015
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