<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/NCT02212691</url>
  </required_header>
  <id_info>
    <org_study_id>1211M24481</org_study_id>
    <secondary_id>U01HL117664</secondary_id>
    <nct_id>NCT02212691</nct_id>
  </id_info>
  <brief_title>Functional Neuroimaging of Pain Using EEG and fMRI</brief_title>
  <official_title>Functional Neuroimaging of Pain in Sickle Cell Disease Patients</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Minnesota</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Heart, Lung, and Blood Institute (NHLBI)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Minnesota</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The purpose of this research is to use non-invasive imaging technologies to study how the&#xD;
      human brain processes pain. The investigators will use contact heat to induce pain and record&#xD;
      data scalp EEG and functional magnetic resonance imaging (fMRI). What the investigators learn&#xD;
      from this study will help us gain insights in pain management with broad socioeconomic&#xD;
      impacts&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Functional imaging of brain networks associated with pain processing is of vital importance&#xD;
      to aid developing new pain-relief therapy and to better understand the mechanisms of brain&#xD;
      function. The pain response in the brain is a complex process, which involves multiple&#xD;
      cortical brain regions, such as primary and secondary somatosensory cortices, anterior&#xD;
      cingulate cortex, and insular cortex . Recent advancement in neuroimaging techniques suggests&#xD;
      the possibility to map the brain structure and networks that involve pain processing.&#xD;
      Electroencephalography (EEG) is a noninvasive monitoring technique, which is widely used to&#xD;
      probe neurological disorders with high temporal resolution. Few attempts have been made to&#xD;
      use EEG to map the active brain regions in pain patients. Functional MRI (fMRI) measures the&#xD;
      hemodynamic brain response and could image the active brain regions with high spatial&#xD;
      resolution. Studies have shown that fMRI is a useful tool to delineate the brain regions&#xD;
      associated with pain processing. Recent studies from simultaneous EEG and fMRI recording have&#xD;
      suggested that the EEG response to the pain may be correlated with the fMRI response, and&#xD;
      both EEG and fMRI could be used to image the brain pain processing regions, such as the&#xD;
      primary somatosensory cortex and anterior cingulate cortex.&#xD;
&#xD;
      The aim of this research is to develop and evaluate a functional neuroimaging approach using&#xD;
      EEG, fMRI and EEG-fMRI, in pain study. EEG, fMRI, or simultaneous EEG-fMRI will be collected&#xD;
      in healthy subjects who receive external thermal stimulation inducing pain. The painful&#xD;
      stimuli will be delivered at different intensity levels and the subject pain rating will be&#xD;
      collected. The imaging technique combines the EEG signal with high temporal resolution and&#xD;
      the fMRI signal with high spatial resolution to obtain a spatiotemporal imaging of the brain&#xD;
      electrophysiological and hemodynamic activity in response to different levels of pain. Cross&#xD;
      validation between this method and subject pain score will be used to quantitatively and&#xD;
      qualitatively evaluate the technique. The successful completion of the current protocol will&#xD;
      help establish an important imaging technology accessing pain level in an objective way.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>January 2012</start_date>
  <completion_date type="Actual">December 15, 2017</completion_date>
  <primary_completion_date type="Actual">December 15, 2017</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Changes in EEG power</measure>
    <time_frame>up to four years</time_frame>
    <description>The goal is to find biomarkers using EEG/fMRI to noninvasively quantify pain. The investigators will measure the differences in EEG power in patients with sickle cell disease comparing to healthy controls.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Changes in fMRI activity level</measure>
    <time_frame>up to four years</time_frame>
    <description>The goal is to find biomarkers using EEG/fMRI to noninvasively quantify pain. The investigators will measure the differences in fMRI BOLD activation in patients with sickle cell disease comparing to healthy controls.</description>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Actual">57</enrollment>
  <condition>Sickle Cell Disease</condition>
  <arm_group>
    <arm_group_label>Sickle cell disease</arm_group_label>
    <description>Patients diagnosed with sickle cell disease</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Healthy control</arm_group_label>
    <description>Healthy individuals recruited through fliers and have no history of cognitive disorders</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        Healthy subjects Sickle cell patients&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Healthy subjects with no known neurological disorders&#xD;
&#xD;
          -  Sickle cell patients with no metal implants&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Age over 65 in either group&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>16 Years</minimum_age>
    <maximum_age>65 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Bin He, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Minnesota</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Biomedical Engineering Department</name>
      <address>
        <city>Minneapolis</city>
        <state>Minnesota</state>
        <zip>55413</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <results_reference>
    <citation>Case M, Shirinpour S, Zhang H, Datta YH, Nelson SC, Sadak KT, Gupta K, He B. Increased theta band EEG power in sickle cell disease patients. J Pain Res. 2017 Dec 27;11:67-76. doi: 10.2147/JPR.S145581. eCollection 2018.</citation>
    <PMID>29343982</PMID>
  </results_reference>
  <results_reference>
    <citation>Case M, Shirinpour S, Vijayakumar V, Zhang H, Datta Y, Nelson S, Pergami P, Darbari DS, Gupta K, He B. Graph theory analysis reveals how sickle cell disease impacts neural networks of patients with more severe disease. Neuroimage Clin. 2019;21:101599. doi: 10.1016/j.nicl.2018.11.009. Epub 2018 Nov 14.</citation>
    <PMID>30477765</PMID>
  </results_reference>
  <verification_date>October 2019</verification_date>
  <study_first_submitted>August 1, 2014</study_first_submitted>
  <study_first_submitted_qc>August 7, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 8, 2014</study_first_posted>
  <last_update_submitted>October 30, 2019</last_update_submitted>
  <last_update_submitted_qc>October 30, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">November 1, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Sickle Cell</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Anemia, Sickle Cell</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>January 28, 2016</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/91/NCT02212691/Prot_SAP_000.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


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/NCT02212691
org study id: 1211M24481
secondary id: U01HL117664
nct id: NCT02212691
lead sponsor: 
collaborator: 
has dmc: Yes
The purpose of this research is to use non-invasive imaging technologies to study how the
      human brain processes pain. The investigators will use contact heat to induce pain and record
      data scalp EEG and functional magnetic resonance imaging (fMRI). What the investigators learn
      from this study will help us gain insights in pain management with broad socioeconomic
      impacts
Functional imaging of brain networks associated with pain processing is of vital importance
      to aid developing new pain-relief therapy and to better understand the mechanisms of brain
      function. The pain response in the brain is a complex process, which involves multiple
      cortical brain regions, such as primary and secondary somatosensory cortices, anterior
      cingulate cortex, and insular cortex . Recent advancement in neuroimaging techniques suggests
      the possibility to map the brain structure and networks that involve pain processing.
      Electroencephalography (EEG) is a noninvasive monitoring technique, which is widely used to
      probe neurological disorders with high temporal resolution. Few attempts have been made to
      use EEG to map the active brain regions in pain patients. Functional MRI (fMRI) measures the
      hemodynamic brain response and could image the active brain regions with high spatial
      resolution. Studies have shown that fMRI is a useful tool to delineate the brain regions
      associated with pain processing. Recent studies from simultaneous EEG and fMRI recording have
      suggested that the EEG response to the pain may be correlated with the fMRI response, and
      both EEG and fMRI could be used to image the brain pain processing regions, such as the
      primary somatosensory cortex and anterior cingulate cortex.

      The aim of this research is to develop and evaluate a functional neuroimaging approach using
      EEG, fMRI and EEG-fMRI, in pain study. EEG, fMRI, or simultaneous EEG-fMRI will be collected
      in healthy subjects who receive external thermal stimulation inducing pain. The painful
      stimuli will be delivered at different intensity levels and the subject pain rating will be
      collected. The imaging technique combines the EEG signal with high temporal resolution and
      the fMRI signal with high spatial resolution to obtain a spatiotemporal imaging of the brain
      electrophysiological and hemodynamic activity in response to different levels of pain. Cross
      validation between this method and subject pain score will be used to quantitatively and
      qualitatively evaluate the technique. The successful completion of the current protocol will
      help establish an important imaging technology accessing pain level in an objective way.
observational model: Other
time perspective: Prospective
measure: Changes in EEG power
time frame: up to four years
description: The goal is to find biomarkers using EEG/fMRI to noninvasively quantify pain. The investigators will measure the differences in EEG power in patients with sickle cell disease comparing to healthy controls.
measure: Changes in fMRI activity level
time frame: up to four years
description: The goal is to find biomarkers using EEG/fMRI to noninvasively quantify pain. The investigators will measure the differences in fMRI BOLD activation in patients with sickle cell disease comparing to healthy controls.
arm group label: Sickle cell disease
description: Patients diagnosed with sickle cell disease
arm group label: Healthy control
description: Healthy individuals recruited through fliers and have no history of cognitive disorders
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 16 Years
maximum age: 65 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Bin He, PhD
role: Principal Investigator
affiliation: University of Minnesota
facility: 
country: United States
citation: Case M, Shirinpour S, Zhang H, Datta YH, Nelson SC, Sadak KT, Gupta K, He B. Increased theta band EEG power in sickle cell disease patients. J Pain Res. 2017 Dec 27;11:67-76. doi: 10.2147/JPR.S145581. eCollection 2018.
PMID: 29343982
citation: Case M, Shirinpour S, Vijayakumar V, Zhang H, Datta Y, Nelson S, Pergami P, Darbari DS, Gupta K, He B. Graph theory analysis reveals how sickle cell disease impacts neural networks of patients with more severe disease. Neuroimage Clin. 2019;21:101599. doi: 10.1016/j.nicl.2018.11.009. Epub 2018 Nov 14.
PMID: 30477765
responsible party type: Sponsor
mesh term: Anemia, Sickle Cell
sharing ipd: No
provided document: 