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/NCT05990218</url>
    </required_header>
    <id_info>
      <org_study_id>031/2566</org_study_id>
      <nct_id>NCT05990218</nct_id>
    </id_info>
    <brief_title>Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Different Operator Experience</brief_title>
    <official_title>Efficacy of Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Operators With Different Endoscopic Experience: A Randomized Control Trial</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Rajavithi Hospital</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Rajavithi Hospital</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>
        Colonoscopy is the gold standard modality for the detection of colonic polyp. However, miss&#xD;
        polyp occurs especially in right sided colon. Artificial intelligence (AI) is one of the&#xD;
        modality to improve polyp detection but the benefit of AI in operators with different&#xD;
        endoscopic experience is still limited. This study aimed to evaluate the efficacy of AI in&#xD;
        the detection of right sided colonic polyp in operators with different endoscopic experience&#xD;
        by using double insertion of right side colon, back-to-back basis.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Recruiting</overall_status>
    <start_date type="Actual">February 13, 2023</start_date>
    <completion_date type="Anticipated">February 28, 2026</completion_date>
    <primary_completion_date type="Anticipated">February 12, 2026</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>Randomized</allocation>
      <intervention_model>Parallel Assignment</intervention_model>
      <intervention_model_description>Patients randomized to 4 arms: control with experienced operator, control with beginner operator, AI with experienced operator, AI with beginner operator</intervention_model_description>
      <primary_purpose>Screening</primary_purpose>
      <masking>Single (Participant)</masking>
      <masking_description>The patients were masked from being randomized to operator and endoscopic method</masking_description>
    </study_design_info>
    <primary_outcome>
      <measure>polyp detection rate</measure>
      <time_frame>during endoscopy</time_frame>
      <description>the number of polyp detected during endoscopy</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>type of polyp</measure>
      <time_frame>during endoscopy</time_frame>
      <description>the type of polyp detected during endoscopy</description>
    </secondary_outcome>
    <number_of_arms>4</number_of_arms>
    <enrollment type="Anticipated">240</enrollment>
    <condition>Colon Polyp</condition>
    <arm_group>
      <arm_group_label>control, experienced</arm_group_label>
      <arm_group_type>Active Comparator</arm_group_type>
      <description>Patients received colonoscopy with double insertion of right sided colon under white light by experienced endoscopist</description>
    </arm_group>
    <arm_group>
      <arm_group_label>control, beginner</arm_group_label>
      <arm_group_type>Active Comparator</arm_group_type>
      <description>Patients received colonoscopy with double insertion of right sided colon under white light by beginner endoscopist</description>
    </arm_group>
    <arm_group>
      <arm_group_label>AI, experience</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>Patients received colonoscopy with double insertion of right sided colon under AI by experienced endoscopist</description>
    </arm_group>
    <arm_group>
      <arm_group_label>AI, beginner</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>Patients received colonoscopy with double insertion of right sided colon under AI by beginner endoscopist</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>Artificial intellegence. CADe syste,</intervention_name>
      <description>The patient received endoscopy under CADe system for polyp detection during second endoscopic withdrawal.</description>
      <arm_group_label>AI, beginner</arm_group_label>
      <arm_group_label>AI, experience</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>control</intervention_name>
      <description>The patient received endoscopy under conventional white light for polyp detection during second endoscopic withdrawal.</description>
      <arm_group_label>control, beginner</arm_group_label>
      <arm_group_label>control, experienced</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  participants age 40-80 years&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  History of colonic surgery (except appendectomy)&#xD;
  &#xD;
            -  Lower gastrointestinal bleeding&#xD;
  &#xD;
            -  unstable vital sign during endoscopy of pregnancy&#xD;
  &#xD;
            -  history of inflammatory bowel disease, polyposis syndrome, colon cancer, colonic&#xD;
               stricture, abnormal coaglulation, organ failure&#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>
    <location>
      <facility>
        <name>Rajavithi Hospital</name>
        <address>
          <city>Bangkok</city>
          <country>Thailand</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Tanyaporn Chantarojanasiri, MD</last_name>
        <phone>0898104033</phone>
        <email>chtunya@gmail.com</email>
      </contact>
      <investigator>
        <last_name>Tanyaporn Chantarojanasiri, MD</last_name>
        <role>Principal Investigator</role>
      </investigator>
    </location>
    <location_countries>
      <country>Thailand</country>
    </location_countries>
    <reference>
      <citation>Kamba S, Tamai N, Saitoh I, Matsui H, Horiuchi H, Kobayashi M, Sakamoto T, Ego M, Fukuda A, Tonouchi A, Shimahara Y, Nishikawa M, Nishino H, Saito Y, Sumiyama K. Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial. J Gastroenterol. 2021 Aug;56(8):746-757. doi: 10.1007/s00535-021-01808-w. Epub 2021 Jul 3.</citation>
      <PMID>34218329</PMID>
    </reference>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 6, 2023</study_first_submitted>
    <study_first_submitted_qc>August 6, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 14, 2023</study_first_posted>
    <last_update_submitted>August 6, 2023</last_update_submitted>
    <last_update_submitted_qc>August 6, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 14, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>colon polyp</keyword>
    <keyword>artificial intellegence</keyword>
    <keyword>colonoscopy</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Polyps</mesh_term>
      <mesh_term>Colonic Polyps</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/NCT05990218
  org study id: 031/2566
  nct id: NCT05990218
  lead sponsor: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  Colonoscopy is the gold standard modality for the detection of colonic polyp. However, miss
        polyp occurs especially in right sided colon. Artificial intelligence (AI) is one of the
        modality to improve polyp detection but the benefit of AI in operators with different
        endoscopic experience is still limited. This study aimed to evaluate the efficacy of AI in
        the detection of right sided colonic polyp in operators with different endoscopic experience
        by using double insertion of right side colon, back-to-back basis.
  allocation: Randomized
  intervention model: Parallel Assignment
  intervention model description: Patients randomized to 4 arms: control with experienced operator, control with beginner operator, AI with experienced operator, AI with beginner operator
  primary purpose: Screening
  masking: Single (Participant)
  masking description: The patients were masked from being randomized to operator and endoscopic method
  measure: polyp detection rate
  time frame: during endoscopy
  description: the number of polyp detected during endoscopy
  measure: type of polyp
  time frame: during endoscopy
  description: the type of polyp detected during endoscopy
  arm group label: control, experienced
  arm group type: Active Comparator
  description: Patients received colonoscopy with double insertion of right sided colon under white light by experienced endoscopist
  arm group label: control, beginner
  arm group type: Active Comparator
  description: Patients received colonoscopy with double insertion of right sided colon under white light by beginner endoscopist
  arm group label: AI, experience
  arm group type: Experimental
  description: Patients received colonoscopy with double insertion of right sided colon under AI by experienced endoscopist
  arm group label: AI, beginner
  arm group type: Experimental
  description: Patients received colonoscopy with double insertion of right sided colon under AI by beginner endoscopist
  intervention type: Device
  intervention name: Artificial intellegence. CADe syste,
  description: The patient received endoscopy under CADe system for polyp detection during second endoscopic withdrawal.
  arm group label: AI, beginner
  arm group label: AI, experience
  intervention type: Device
  intervention name: control
  description: The patient received endoscopy under conventional white light for polyp detection during second endoscopic withdrawal.
  arm group label: control, beginner
  arm group label: control, experienced
  criteria: 
  gender: All
  minimum age: 40 Years
  maximum age: 80 Years
  healthy volunteers: Accepts Healthy Volunteers
  facility: 
  status: Recruiting
  contact: 
  investigator: 
  country: Thailand
  citation: Kamba S, Tamai N, Saitoh I, Matsui H, Horiuchi H, Kobayashi M, Sakamoto T, Ego M, Fukuda A, Tonouchi A, Shimahara Y, Nishikawa M, Nishino H, Saito Y, Sumiyama K. Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial. J Gastroenterol. 2021 Aug;56(8):746-757. doi: 10.1007/s00535-021-01808-w. Epub 2021 Jul 3.
  PMID: 34218329
  responsible party type: Sponsor
  mesh term: Polyps
  mesh term: Colonic Polyps
  sharing ipd: No