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/NCT06039098</url>
    </required_header>
    <id_info>
      <org_study_id>317751</org_study_id>
      <nct_id>NCT06039098</nct_id>
    </id_info>
    <brief_title>Investigating the Relationship Between Intracranial Pressure and Cerebral Blood Flow Using Near-infrared Diffuse Correlation Spectroscopy</brief_title>
    <acronym>ICP-CBF</acronym>
    <official_title>Investigating the Relationship Between Intracranial Pressure and Cerebral Blood Flow Using Near-infrared Diffuse Correlation Spectroscopy</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Queen Mary University of London</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Barts &amp; The London NHS Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>CoMind</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Queen Mary University of London</source>
    <oversight_info>
      <has_dmc>Yes</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>
        We aim to acquire data using DCS on patients who are undergoing invasive ICP and ABP&#xD;
        monitoring on ITU as part of their normal treatment.&#xD;
  &#xD;
        Data will then be correlated to derive various parameters including CBF and BFI.&#xD;
  &#xD;
        All interventions are entirely non-invasive.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Cerebral Autoregulation (CA) is the complex process whereby the body maintains constant blood&#xD;
        flow to the brain (cerebral blood flow, CBF) over a wide range of mean arterial pressures&#xD;
        (MAP) in order to provide constant oxygenation and nutrition supply to cerebral tissue. By&#xD;
        balancing blood and cerebrospinal fluid (CSF) pressures, CA dynamically stabilises cerebral&#xD;
        perfusion pressure (CPP) and hence blood flow. Disordered CA may result in reduced oxygen and&#xD;
        nutrient delivery to the brain tissue leading to hypoxic and ischaemic damage resulting in&#xD;
        significant morbidity and mortality.&#xD;
  &#xD;
        High intracranial pressure (ICP) is frequently associated with failing CA. Hence ICP is&#xD;
        routinely monitored in patients suffering from traumatic brain injury (TBI) and other&#xD;
        conditions which may result in CA failure. Raised ICP contributes to the majority of&#xD;
        mortalities following severe TBI. All currently available ICP monitoring systems require&#xD;
        insertion of an electrical or pneumatic transducer into the cranial cavity, usually sited&#xD;
        within the brain parenchyma but occasionally into the subdural space (between the brain and&#xD;
        the skull) or into the ventricles. This is currently only performed by neurosurgeons and&#xD;
        carries a small but significant risk of haemorrhage or infection.&#xD;
  &#xD;
        Non-invasive ICP and hence CA monitoring would eliminate the risk of complications, could be&#xD;
        used by all healthcare professionals, would extend the use to outside a hospital settings and&#xD;
        may extend the range of conditions to benefit from ICP monitoring.&#xD;
  &#xD;
        This project pilots an approach to expand our understanding of the basic physiological&#xD;
        interplay between intracranial pressure, arterial blood pressure, and cerebral blood flow in&#xD;
        adult in-patients.&#xD;
  &#xD;
        A recently-developed form of near-infrared (NIR) optical sensing known as Diffuse Correlation&#xD;
        Spectroscopy (DCS) offers an opportunity to investigate cerebral blood flow at the bed-side&#xD;
        continuously. DCS measures blood flow in the microvasculature of the brain by determining a&#xD;
        blood flow index (BFi).&#xD;
  &#xD;
        A similar technology based on near-infrared spectroscopy (NIRS), was recently successfully&#xD;
        applied by the Chief Investigator in the same population in the same manner as in the current&#xD;
        proposal (IRAS ID: 219476, approved by the East of England - Cambridge Central Research&#xD;
        Ethics Committee (18/EE/0276) on 14/02/19). We therefore have extensive experience working&#xD;
        with optical instruments in these patient groups.&#xD;
  &#xD;
        In this proposal we will use a custom DCS research instrument. This research instrument is&#xD;
        designed to measure microvascular cerebral blood flow for neuroscience and neurological&#xD;
        research applications. While this device is a bespoke instrument, built with this study in&#xD;
        mind, it is based on established research technologies and has been tested successfully in&#xD;
        more than 20 healthy volunteers and in a range of quality-control experiments to date. It&#xD;
        uses a forehead-mounted optical probe that contains near-infrared light sources that can&#xD;
        illuminate the brain tissue non-invasively and continuously. The light's path within brain&#xD;
        tissue is modulated by the flow of blood in the cerebral microvasculature and it is&#xD;
        ultimately absorbed or backscattered. The backscattered light is collected at a different&#xD;
        point within the probe.&#xD;
  &#xD;
        The interplay between mean arterial blood (MAP) (measured by means of an intra-arterial&#xD;
        catheter (part of normal medical care for patients on ITU) or a non-invasive finger-cuff) and&#xD;
        ICP affects the morphology of the pulsatile flow in the cerebral microvascular, so the&#xD;
        analysis of these signals in unison will help us better understand the relationship between&#xD;
        ICP (which is measured clinically), MAP (which is measured clinically) and cerebral blood&#xD;
        flow (which is not). This in turn could help support new research into head injury&#xD;
        management, notably ICP-targeted treatment regimes. Ultimately this could lead to significant&#xD;
        improvements in secondary injury-related mortality, length of hospital stay and reduced&#xD;
        post-trauma disability. In addition the non-invasive nature of the monitor could extend the&#xD;
        range of medical conditions that may benefit from ICP and CA monitoring including stroke,&#xD;
        brain tumour surveillance, hydrocephalus, pre-hospital care of trauma patients, routine&#xD;
        anaesthetic and ICU monitoring systems and screening of patients with headache in primary&#xD;
        care.&#xD;
  &#xD;
        In addition, if successfully developed, this technology is likely to be extremely relevant to&#xD;
        low and middle income countries where access to neurosurgeons (and hence ICP monitoring) is&#xD;
        extremely limited.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Recruiting</overall_status>
    <start_date type="Actual">January 5, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2023</completion_date>
    <primary_completion_date type="Anticipated">December 31, 2023</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>DCS signal acquisition</measure>
      <time_frame>12 months</time_frame>
      <description>Successful acquisition of DCS signals from brain tissue</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Correlation of DCS signals with routine physiological data measurements</measure>
      <time_frame>10 months</time_frame>
      <description>Correlation of DCS signals with routine physiological data measurements</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>ML approach to derive secondary parameters</measure>
      <time_frame>10 months</time_frame>
      <description>Machine learning approach to derive additional parameters non-invasively</description>
    </secondary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">50</enrollment>
    <condition>Traumatic Brain Injury</condition>
    <condition>Intracranial Hypertension</condition>
    <arm_group>
      <arm_group_label>Participants</arm_group_label>
      <description>Participants are patients who are undergoing invasive ICP and ABP measurement as part of their normal medical treatment.</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>DCS</intervention_name>
      <description>DCS monitoring of brain</description>
      <arm_group_label>Participants</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          The largest demographic of patients undergoing ICP monitoring is trauma, therefore the&#xD;
          study population is patients who have suffered TBI and are undergoing ICP monitoring on&#xD;
          ITU.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Invasive monitoring of ICP and ABP as part of normal treatment&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Not meeting inclusion criteria.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>16 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <location>
      <facility>
        <name>Royal London Hospital</name>
        <address>
          <city>London</city>
          <country>United Kingdom</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Chris E Uff, PhD</last_name>
        <phone>02035942799</phone>
        <email>c.uff@qmul.ac.uk</email>
      </contact>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <verification_date>January 2023</verification_date>
    <study_first_submitted>September 8, 2023</study_first_submitted>
    <study_first_submitted_qc>September 8, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 15, 2023</study_first_posted>
    <last_update_submitted>September 8, 2023</last_update_submitted>
    <last_update_submitted_qc>September 8, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 15, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Brain Injuries</mesh_term>
      <mesh_term>Brain Injuries, Traumatic</mesh_term>
      <mesh_term>Intracranial Hypertension</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>Yes</sharing_ipd>
      <ipd_description>Data will be shared with organizations / individuals upon reasonable request.</ipd_description>
      <ipd_info_type>Study Protocol</ipd_info_type>
      <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
      <ipd_info_type>Clinical Study Report (CSR)</ipd_info_type>
      <ipd_time_frame>Once data have been acquired</ipd_time_frame>
      <ipd_access_criteria>Upon reasonable request to be determined by the CI.</ipd_access_criteria>
    </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/NCT06039098
  org study id: 317751
  nct id: NCT06039098
  lead sponsor: 
  collaborator: 
  collaborator: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  We aim to acquire data using DCS on patients who are undergoing invasive ICP and ABP
        monitoring on ITU as part of their normal treatment.
  
        Data will then be correlated to derive various parameters including CBF and BFI.
  
        All interventions are entirely non-invasive.
  Cerebral Autoregulation (CA) is the complex process whereby the body maintains constant blood
        flow to the brain (cerebral blood flow, CBF) over a wide range of mean arterial pressures
        (MAP) in order to provide constant oxygenation and nutrition supply to cerebral tissue. By
        balancing blood and cerebrospinal fluid (CSF) pressures, CA dynamically stabilises cerebral
        perfusion pressure (CPP) and hence blood flow. Disordered CA may result in reduced oxygen and
        nutrient delivery to the brain tissue leading to hypoxic and ischaemic damage resulting in
        significant morbidity and mortality.
  
        High intracranial pressure (ICP) is frequently associated with failing CA. Hence ICP is
        routinely monitored in patients suffering from traumatic brain injury (TBI) and other
        conditions which may result in CA failure. Raised ICP contributes to the majority of
        mortalities following severe TBI. All currently available ICP monitoring systems require
        insertion of an electrical or pneumatic transducer into the cranial cavity, usually sited
        within the brain parenchyma but occasionally into the subdural space (between the brain and
        the skull) or into the ventricles. This is currently only performed by neurosurgeons and
        carries a small but significant risk of haemorrhage or infection.
  
        Non-invasive ICP and hence CA monitoring would eliminate the risk of complications, could be
        used by all healthcare professionals, would extend the use to outside a hospital settings and
        may extend the range of conditions to benefit from ICP monitoring.
  
        This project pilots an approach to expand our understanding of the basic physiological
        interplay between intracranial pressure, arterial blood pressure, and cerebral blood flow in
        adult in-patients.
  
        A recently-developed form of near-infrared (NIR) optical sensing known as Diffuse Correlation
        Spectroscopy (DCS) offers an opportunity to investigate cerebral blood flow at the bed-side
        continuously. DCS measures blood flow in the microvasculature of the brain by determining a
        blood flow index (BFi).
  
        A similar technology based on near-infrared spectroscopy (NIRS), was recently successfully
        applied by the Chief Investigator in the same population in the same manner as in the current
        proposal (IRAS ID: 219476, approved by the East of England - Cambridge Central Research
        Ethics Committee (18/EE/0276) on 14/02/19). We therefore have extensive experience working
        with optical instruments in these patient groups.
  
        In this proposal we will use a custom DCS research instrument. This research instrument is
        designed to measure microvascular cerebral blood flow for neuroscience and neurological
        research applications. While this device is a bespoke instrument, built with this study in
        mind, it is based on established research technologies and has been tested successfully in
        more than 20 healthy volunteers and in a range of quality-control experiments to date. It
        uses a forehead-mounted optical probe that contains near-infrared light sources that can
        illuminate the brain tissue non-invasively and continuously. The light's path within brain
        tissue is modulated by the flow of blood in the cerebral microvasculature and it is
        ultimately absorbed or backscattered. The backscattered light is collected at a different
        point within the probe.
  
        The interplay between mean arterial blood (MAP) (measured by means of an intra-arterial
        catheter (part of normal medical care for patients on ITU) or a non-invasive finger-cuff) and
        ICP affects the morphology of the pulsatile flow in the cerebral microvascular, so the
        analysis of these signals in unison will help us better understand the relationship between
        ICP (which is measured clinically), MAP (which is measured clinically) and cerebral blood
        flow (which is not). This in turn could help support new research into head injury
        management, notably ICP-targeted treatment regimes. Ultimately this could lead to significant
        improvements in secondary injury-related mortality, length of hospital stay and reduced
        post-trauma disability. In addition the non-invasive nature of the monitor could extend the
        range of medical conditions that may benefit from ICP and CA monitoring including stroke,
        brain tumour surveillance, hydrocephalus, pre-hospital care of trauma patients, routine
        anaesthetic and ICU monitoring systems and screening of patients with headache in primary
        care.
  
        In addition, if successfully developed, this technology is likely to be extremely relevant to
        low and middle income countries where access to neurosurgeons (and hence ICP monitoring) is
        extremely limited.
  observational model: Cohort
  time perspective: Prospective
  measure: DCS signal acquisition
  time frame: 12 months
  description: Successful acquisition of DCS signals from brain tissue
  measure: Correlation of DCS signals with routine physiological data measurements
  time frame: 10 months
  description: Correlation of DCS signals with routine physiological data measurements
  measure: ML approach to derive secondary parameters
  time frame: 10 months
  description: Machine learning approach to derive additional parameters non-invasively
  arm group label: Participants
  description: Participants are patients who are undergoing invasive ICP and ABP measurement as part of their normal medical treatment.
  intervention type: Device
  intervention name: DCS
  description: DCS monitoring of brain
  arm group label: Participants
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 16 Years
  maximum age: N/A
  healthy volunteers: No
  facility: 
  status: Recruiting
  contact: 
  country: United Kingdom
  responsible party type: Sponsor
  mesh term: Brain Injuries
  mesh term: Brain Injuries, Traumatic
  mesh term: Intracranial Hypertension
  sharing ipd: Yes
  ipd description: Data will be shared with organizations / individuals upon reasonable request.
  ipd info type: Study Protocol
  ipd info type: Statistical Analysis Plan (SAP)
  ipd info type: Clinical Study Report (CSR)
  ipd time frame: Once data have been acquired
  ipd access criteria: Upon reasonable request to be determined by the CI.