<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/NCT04478929</url>
  </required_header>
  <id_info>
    <org_study_id>REDM0227_RP01</org_study_id>
    <nct_id>NCT04478929</nct_id>
  </id_info>
  <brief_title>Early Detection of Barrett's Esophagus Through Deep Image Retrieval</brief_title>
  <official_title>Early Detection of Cancer in Cases of Barrett's Esophagus Using Robotic Endoscopy Image Analysis Through Deep Image Retrieval</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Leigh Taylor</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Cancer Research UK</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of the West of England</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>
      Barrett's oesophagus is a condition in which the area between the oesophagus and stomach no&#xD;
      longer closes, allowing acidic contents of the stomach to enter the oesophagus and damage the&#xD;
      lining. The project aims to assist clinicians by offering informed biopsy process, in which&#xD;
      the system presents the operator with clinical outcomes of patients with visually similar GI&#xD;
      tracts. The project goal is to assess the use of artificial intelligence-based similarity&#xD;
      detection systems to better inform biopsy placement, increasing the reliability of bi-yearly&#xD;
      inspections.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The project intention is to acquire secondary endoscopy captured data from clinicians to&#xD;
      create a sufficient dataset to train a learning system to achieve the stated objective. The&#xD;
      data required will feature footage (images/videos) from inside the oesophagus. The preferred&#xD;
      data would contain associated diagnosis notes and description, however, data without&#xD;
      diagnosis can still be used. All data can and will be anonymised, as personal information&#xD;
      will not be useful in this work.&#xD;
&#xD;
      The data will be labelled by either researchers, or professional clinicians and prepared&#xD;
      ready to feed into a chosen learning AI system. Through an iterative learning process, the&#xD;
      chosen AI system will learn to discriminate between severity of Barrett's oesophagus and&#xD;
      output optimal biopsy target.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date type="Anticipated">August 2020</start_date>
  <completion_date type="Anticipated">August 2021</completion_date>
  <primary_completion_date type="Anticipated">June 2021</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Control</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>gastroscopy image data set</measure>
    <time_frame>12 months</time_frame>
    <description>Images collected during routine gastroscopy with examination notes</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">300</enrollment>
  <condition>Barrett Esophagus</condition>
  <arm_group>
    <arm_group_label>gastroscopy clinic patients</arm_group_label>
    <description>NBT gastroscopy clinic invited participants. Patients are already due to attend the clinic, and we are inviting them to share their gastroscopy data with our research study.</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Gastroscopy</intervention_name>
    <description>Routine gastroscopy</description>
    <arm_group_label>gastroscopy clinic patients</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Attending NBT clinic for on OGD phase 1, then later attending NBT clinic due to suspected&#xD;
        Barrett's.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Adult&#xD;
&#xD;
          -  Attending Southmead Hospital for on OGD&#xD;
&#xD;
          -  Has capacity&#xD;
&#xD;
          -  Initially any indication, later patients with known Barrett's oesophagus&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Children (&lt;18)&#xD;
&#xD;
          -  Patients without capacity&#xD;
&#xD;
          -  Urgent and emergency procedures&#xD;
&#xD;
          -  Limited English&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Lyndon Winstone, PhD</last_name>
    <phone>+4411732 82009</phone>
    <email>Lyndon.Smith@uwe.ac.uk</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>benjamin winstone, PhD</last_name>
    <phone>07890080486</phone>
    <email>benjamin2.winstone@uwe.ac.uk</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>NBT, Southmead Hospital</name>
      <address>
        <city>Bristol</city>
        <state>Avon</state>
        <zip>BS10 5NB</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
    <contact>
      <last_name>leonard griffiths</last_name>
      <phone>0117 414 6353</phone>
      <phone_ext>6353</phone_ext>
      <email>leonard.griffiths@nbt.nhs.uk</email>
    </contact>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>July 2020</verification_date>
  <study_first_submitted>July 15, 2020</study_first_submitted>
  <study_first_submitted_qc>July 15, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 21, 2020</study_first_posted>
  <last_update_submitted>July 15, 2020</last_update_submitted>
  <last_update_submitted_qc>July 15, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 21, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>University of the West of England</investigator_affiliation>
    <investigator_full_name>Leigh Taylor</investigator_full_name>
    <investigator_title>Senior Research Officer</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Barrett Esophagus</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- 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/NCT04478929
org study id: REDM0227_RP01
nct id: NCT04478929
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Barrett's oesophagus is a condition in which the area between the oesophagus and stomach no
      longer closes, allowing acidic contents of the stomach to enter the oesophagus and damage the
      lining. The project aims to assist clinicians by offering informed biopsy process, in which
      the system presents the operator with clinical outcomes of patients with visually similar GI
      tracts. The project goal is to assess the use of artificial intelligence-based similarity
      detection systems to better inform biopsy placement, increasing the reliability of bi-yearly
      inspections.
The project intention is to acquire secondary endoscopy captured data from clinicians to
      create a sufficient dataset to train a learning system to achieve the stated objective. The
      data required will feature footage (images/videos) from inside the oesophagus. The preferred
      data would contain associated diagnosis notes and description, however, data without
      diagnosis can still be used. All data can and will be anonymised, as personal information
      will not be useful in this work.

      The data will be labelled by either researchers, or professional clinicians and prepared
      ready to feed into a chosen learning AI system. Through an iterative learning process, the
      chosen AI system will learn to discriminate between severity of Barrett's oesophagus and
      output optimal biopsy target.
observational model: Case-Control
time perspective: Prospective
measure: gastroscopy image data set
time frame: 12 months
description: Images collected during routine gastroscopy with examination notes
arm group label: gastroscopy clinic patients
description: NBT gastroscopy clinic invited participants. Patients are already due to attend the clinic, and we are inviting them to share their gastroscopy data with our research study.
intervention type: Diagnostic Test
intervention name: Gastroscopy
description: Routine gastroscopy
arm group label: gastroscopy clinic patients
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Lyndon Winstone, PhD
phone: +4411732 82009
email: Lyndon.Smith@uwe.ac.uk
last name: benjamin winstone, PhD
phone: 07890080486
email: benjamin2.winstone@uwe.ac.uk
facility: 
contact: 
country: United Kingdom
responsible party type: Sponsor-Investigator
investigator affiliation: University of the West of England
investigator full name: Leigh Taylor
investigator title: Senior Research Officer
mesh term: Barrett Esophagus
sharing ipd: No