xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT05976971</url>
    </required_header>
    <id_info>
      <org_study_id>RCAPHM22_0397</org_study_id>
      <secondary_id>ID-RCB</secondary_id>
      <nct_id>NCT05976971</nct_id>
    </id_info>
    <brief_title>Microstructural and Sodium 7 Tesla Brain MRI in Idiopathic REM Sleep Behaviour Disorder</brief_title>
    <acronym>SODISLEEP</acronym>
    <official_title>Microstructural Brain MRI Biomarkers in Patients With Idiopathic REM Sleep Behaviour Disorder at 7 Tesla</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Assistance Publique Hopitaux De Marseille</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Aix Marseille Université</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Assistance Publique Hopitaux De Marseille</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        By 2030 the number of patients with Parkinson's Disease (PD) would increase by 56% affecting&#xD;
        1 out of 120 people older than 45 years-old. It is known that 10-15 years before the onset&#xD;
        motor symptoms such as tremor, rigidity and akinesia, patients often experience a specific&#xD;
        sleep trouble called REM sleep behaviour disorder (RBD). Follow-up of those subjects showed&#xD;
        there was a conversion rate to PD and related disorders (called synucleinopathies) over 80%.&#xD;
  &#xD;
        The pathophysiology of RBD is poorly understood. The development of cutting-edge technologies&#xD;
        such as 7 Tesla MRI and the optimisation of image processing methods made it possible to&#xD;
        non-invasively explore in vivo small brain structures involved in sleep and movement&#xD;
        disorders.&#xD;
  &#xD;
        The investigators hypothesize that brain and brainstem microstructure, composition, sodium&#xD;
        homeostasis and connectivity may change in 15 isolated RBD (iRBD) subjects compared with 15&#xD;
        healthy controls and that these changes may be correlated with clinical scores.&#xD;
  &#xD;
        This study would help fill the gap in early diagnosis of synucleinopathies, by contributing&#xD;
        to better targeting patients who could be included in therapeutic trials with a&#xD;
        neuroprotective effect. Besides, the exploration of original pathophysiological pathways such&#xD;
        as sodium homeostatis could provide the necessary arguments for the development of new target&#xD;
        therapeutics.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">October 1, 2023</start_date>
    <completion_date type="Anticipated">September 30, 2025</completion_date>
    <primary_completion_date type="Anticipated">September 30, 2025</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>Non-Randomized</allocation>
      <intervention_model>Parallel Assignment</intervention_model>
      <primary_purpose>Diagnostic</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>3D cartography the rate of difference of atrophy between the idiopathic REM Sleep Behaviour Disorder (iRBD) and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Voxel based morphometry evaluated with Matlab and SnPM</description>
    </primary_outcome>
    <primary_outcome>
      <measure>3D cartography difference of neuromelanin between the iRBD and control subjects with T1 sequence</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Neuromelanin contrast ratio</description>
    </primary_outcome>
    <primary_outcome>
      <measure>3D cartography difference of neuromelanin between the iRBD and control subjects with Magnetization transfert sequence</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Magnetization transfert contrast ratio</description>
    </primary_outcome>
    <primary_outcome>
      <measure>3D cartography the rate of difference of Quantitative Susceptibility Mapping between the iRBD and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Iron load evaluation in ppb</description>
    </primary_outcome>
    <primary_outcome>
      <measure>3D cartography difference of Mean diffusivity between the iRBD and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Mean diffusivity in mm2/s</description>
    </primary_outcome>
    <primary_outcome>
      <measure>3D cartography difference of Fractional anisotropy between the iRBD and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Fractional anisotropy between 0 and 1</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>3D cartography difference of total sodium concentration between the iRBD and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>total sodium concentration in mmol/L acquired with a specificic MRI coil</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>3D cartography difference of structural brain connectivity between the iRBD and control subjects</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>A network-based statistics analysis will be performed: from Diffusion tensor imaging, a connectivity matrix will be populated for each subject. A t-test contrasting the two groups (iRBD and control subjects) will then be computed for each pairwise association. Finally, permutation testing will be used to ascribe a p-value controlled for the family-wise error rate to each connected component based on its size.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and demographic data</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the age and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and demographic data</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the sex and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and demographic data</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the laterality and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and demographic data, clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the MDS-UPDRS I (Movement disorders society - Unified Parkinson's Disease Rating Scale) scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the MDS-UPDRS II scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the MDS-UPDRS III scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the SCOPA-AUT scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the HAD scale (Hospital Anxiety and Depression scale) and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the RBD (Rem sleep behaviour disorder) and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and demographic data, clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the Pittsburgh sleep quality index and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the Starkstein motivation scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the non motor fluctuation scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the MoCA scale and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the phonemic and category fluencies and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the Benton judgement of lines and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the quality of life SF-36 and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the Miami Hallucinations questionnaire and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the treatement intake and MRI parameters</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Rate of Dependency between MRI parameters and clinical scores/questionnaires</measure>
      <time_frame>Time of the Inclusion</time_frame>
      <description>Pearson, Spearman or logistic regression, depending on the blood pressure test and MRI parameters</description>
    </secondary_outcome>
    <number_of_arms>2</number_of_arms>
    <enrollment type="Anticipated">32</enrollment>
    <condition>REM Sleep Behaviour Disorder</condition>
    <arm_group>
      <arm_group_label>Patients with REM Sleep Behaviour Disorder</arm_group_label>
      <arm_group_type>Other</arm_group_type>
    </arm_group>
    <arm_group>
      <arm_group_label>Healthy volunteers</arm_group_label>
      <arm_group_type>Other</arm_group_type>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>7T MRI</intervention_name>
      <description>Subjects will have a 7T MRI and questionnaires on the only day of clinical study.</description>
      <arm_group_label>Healthy volunteers</arm_group_label>
      <arm_group_label>Patients with REM Sleep Behaviour Disorder</arm_group_label>
      <other_name>Questionnaires</other_name>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria for patients with REM Sleep Behaviour Disorder :&#xD;
  &#xD;
            -  Patient aged between 40 and 80 years old&#xD;
  &#xD;
            -  Patient fulfilling the diagnostic criteria for RBD (International Classification of&#xD;
               Sleep Disorders version 3, American Academy of Sleep Medicine, 2014) with&#xD;
               polysomnographic confirmation (which will be carried out as part of the routine&#xD;
               work-up);&#xD;
  &#xD;
            -  UPDRS Part III score under or equal to 5&#xD;
  &#xD;
            -  The patient is enrolled in the French social security system&#xD;
  &#xD;
            -  The patient understood and signed the consent to participate in the study.&#xD;
  &#xD;
          Inclusion Criteria for control group :&#xD;
  &#xD;
            -  Patient aged between 40 and 80 years old&#xD;
  &#xD;
            -  Score under or equal 4 for the RBD screening questionnaire&#xD;
  &#xD;
            -  UPDRS Part III score under or equal 5&#xD;
  &#xD;
            -  The patient is enrolled in the French social security system&#xD;
  &#xD;
            -  The patient understood and signed the consent to participate in the study.&#xD;
  &#xD;
          Exclusion Criteria :&#xD;
  &#xD;
            -  Patient / Subject with a history of central nervous system disease (e.g. PD,&#xD;
               Alzheimer's disease, stroke, brain tumour, multiple sclerosis, amyotrophic lateral&#xD;
               sclerosis, etc.). If a doubt exist, this criterion will be left to the judgement of&#xD;
               the principal investigator, who is a neurologist.&#xD;
  &#xD;
            -  Contraindications to 7T MRI: presence of a metal in the body or in the eye, patient&#xD;
               with a pacemaker or neurostimulator, cochlear implants or any implanted electronic&#xD;
               medical equipment in general, metallic heart valve, aneurysm clips.&#xD;
  &#xD;
            -  Claustrophobia.&#xD;
  &#xD;
            -  Montreal Cognitive Assessment Test (MOCA) &lt; 25/30&#xD;
  &#xD;
            -  Pregnant or breast-feeding woman or protected person (under guardianship, curatorship,&#xD;
               deprived of liberty).&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>40 Years</minimum_age>
      <maximum_age>80 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Francois Cremieux</last_name>
      <role>Study Director</role>
      <affiliation>Assistance Publique - Hôpitaux de Marseille</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Alexandre Eusebio, MD, PhD</last_name>
      <phone>0491384360</phone>
      <phone_ext>33</phone_ext>
      <email>alexandre.eusebio@ap-hm.fr</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Grimaldi Stephan</last_name>
      <email>stephan.grimaldi@ap-hm.fr</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Assistance - Publique Hôpitaux de Marseille</name>
        <address>
          <city>Marseille</city>
          <zip>13005</zip>
          <country>France</country>
        </address>
      </facility>
      <contact>
        <last_name>Alexandre Eusebio</last_name>
        <email>Alexandre.eusebio@ap-hm.fr</email>
      </contact>
      <contact_backup>
        <last_name>Stephan Grimaldi</last_name>
        <email>stephan.grimaldi@ap-hm.fr</email>
      </contact_backup>
    </location>
    <location_countries>
      <country>France</country>
    </location_countries>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 12, 2023</study_first_submitted>
    <study_first_submitted_qc>July 27, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 4, 2023</study_first_posted>
    <last_update_submitted>July 27, 2023</last_update_submitted>
    <last_update_submitted_qc>July 27, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 4, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>7T MRI</keyword>
    <keyword>Parkinson's disease</keyword>
    <keyword>synucleinopathies</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>REM Sleep Behavior Disorder</mesh_term>
      <mesh_term>Mental Disorders</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT05976971
  org study id: RCAPHM22_0397
  secondary id: ID-RCB
  nct id: NCT05976971
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  By 2030 the number of patients with Parkinson's Disease (PD) would increase by 56% affecting
        1 out of 120 people older than 45 years-old. It is known that 10-15 years before the onset
        motor symptoms such as tremor, rigidity and akinesia, patients often experience a specific
        sleep trouble called REM sleep behaviour disorder (RBD). Follow-up of those subjects showed
        there was a conversion rate to PD and related disorders (called synucleinopathies) over 80%.
  
        The pathophysiology of RBD is poorly understood. The development of cutting-edge technologies
        such as 7 Tesla MRI and the optimisation of image processing methods made it possible to
        non-invasively explore in vivo small brain structures involved in sleep and movement
        disorders.
  
        The investigators hypothesize that brain and brainstem microstructure, composition, sodium
        homeostasis and connectivity may change in 15 isolated RBD (iRBD) subjects compared with 15
        healthy controls and that these changes may be correlated with clinical scores.
  
        This study would help fill the gap in early diagnosis of synucleinopathies, by contributing
        to better targeting patients who could be included in therapeutic trials with a
        neuroprotective effect. Besides, the exploration of original pathophysiological pathways such
        as sodium homeostatis could provide the necessary arguments for the development of new target
        therapeutics.
  allocation: Non-Randomized
  intervention model: Parallel Assignment
  primary purpose: Diagnostic
  masking: None (Open Label)
  measure: 3D cartography the rate of difference of atrophy between the idiopathic REM Sleep Behaviour Disorder (iRBD) and control subjects
  time frame: Time of the Inclusion
  description: Voxel based morphometry evaluated with Matlab and SnPM
  measure: 3D cartography difference of neuromelanin between the iRBD and control subjects with T1 sequence
  time frame: Time of the Inclusion
  description: Neuromelanin contrast ratio
  measure: 3D cartography difference of neuromelanin between the iRBD and control subjects with Magnetization transfert sequence
  time frame: Time of the Inclusion
  description: Magnetization transfert contrast ratio
  measure: 3D cartography the rate of difference of Quantitative Susceptibility Mapping between the iRBD and control subjects
  time frame: Time of the Inclusion
  description: Iron load evaluation in ppb
  measure: 3D cartography difference of Mean diffusivity between the iRBD and control subjects
  time frame: Time of the Inclusion
  description: Mean diffusivity in mm2/s
  measure: 3D cartography difference of Fractional anisotropy between the iRBD and control subjects
  time frame: Time of the Inclusion
  description: Fractional anisotropy between 0 and 1
  measure: 3D cartography difference of total sodium concentration between the iRBD and control subjects
  time frame: Time of the Inclusion
  description: total sodium concentration in mmol/L acquired with a specificic MRI coil
  measure: 3D cartography difference of structural brain connectivity between the iRBD and control subjects
  time frame: Time of the Inclusion
  description: A network-based statistics analysis will be performed: from Diffusion tensor imaging, a connectivity matrix will be populated for each subject. A t-test contrasting the two groups (iRBD and control subjects) will then be computed for each pairwise association. Finally, permutation testing will be used to ascribe a p-value controlled for the family-wise error rate to each connected component based on its size.
  measure: Rate of Dependency between MRI parameters and demographic data
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the age and MRI parameters
  measure: Rate of Dependency between MRI parameters and demographic data
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the sex and MRI parameters
  measure: Rate of Dependency between MRI parameters and demographic data
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the laterality and MRI parameters
  measure: Rate of Dependency between MRI parameters and demographic data, clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the MDS-UPDRS I (Movement disorders society - Unified Parkinson's Disease Rating Scale) scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the MDS-UPDRS II scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the MDS-UPDRS III scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the SCOPA-AUT scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the HAD scale (Hospital Anxiety and Depression scale) and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the RBD (Rem sleep behaviour disorder) and MRI parameters
  measure: Rate of Dependency between MRI parameters and demographic data, clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the Pittsburgh sleep quality index and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the Starkstein motivation scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the non motor fluctuation scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the MoCA scale and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the phonemic and category fluencies and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the Benton judgement of lines and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the quality of life SF-36 and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the Miami Hallucinations questionnaire and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the treatement intake and MRI parameters
  measure: Rate of Dependency between MRI parameters and clinical scores/questionnaires
  time frame: Time of the Inclusion
  description: Pearson, Spearman or logistic regression, depending on the blood pressure test and MRI parameters
  arm group label: Patients with REM Sleep Behaviour Disorder
  arm group type: Other
  arm group label: Healthy volunteers
  arm group type: Other
  intervention type: Other
  intervention name: 7T MRI
  description: Subjects will have a 7T MRI and questionnaires on the only day of clinical study.
  arm group label: Healthy volunteers
  arm group label: Patients with REM Sleep Behaviour Disorder
  other name: Questionnaires
  criteria: 
  gender: All
  minimum age: 40 Years
  maximum age: 80 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Francois Cremieux
  role: Study Director
  affiliation: Assistance Publique - Hôpitaux de Marseille
  last name: Alexandre Eusebio, MD, PhD
  phone: 0491384360
  phone ext: 33
  email: alexandre.eusebio@ap-hm.fr
  last name: Grimaldi Stephan
  email: stephan.grimaldi@ap-hm.fr
  facility: 
  contact: 
  contact backup: 
  country: France
  responsible party type: Sponsor
  mesh term: REM Sleep Behavior Disorder
  mesh term: Mental Disorders
  sharing ipd: No