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/NCT05965921</url>
    </required_header>
    <id_info>
      <org_study_id>23/PR/0213</org_study_id>
      <nct_id>NCT05965921</nct_id>
    </id_info>
    <brief_title>Real-life Prospective Evaluation of Computer-aided Detection (CAD) of Barrett's Neoplasia</brief_title>
    <acronym>MetaVision</acronym>
    <official_title>Real-life Prospective Evaluation of Computer-aided Detection (CAD) of Barrett's Neoplasia: MetaVision Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Portsmouth Hospitals NHS Trust</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>St George's University Hospitals NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Brighton and Sussex University Hospitals NHS Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>University Hospitals Dorset NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Portsmouth Hospitals NHS Trust</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>
        Barrett's oesophagus is a pre-cancerous condition in which normal cells in the lining of&#xD;
        gullet undergo cell changes and this increases the risk of developing adenocarcinoma (a type&#xD;
        of cancer) of the gullet. This type of cancer is the 5th most common type of cancer in the&#xD;
        UK. To minimise this risk of developing cancer, patients with Barret's oesophagus have&#xD;
        regular gastroscopy (a small camera at the tip of the slim tube) every 2-5 years to detect&#xD;
        early cancer cell changes. During the procedure, the whole of oesophagus is carefully&#xD;
        inspected, and small tissue samples (biopsies) are taken from visible abnormal area within&#xD;
        Barrett's oesophagus and sent to the lab to check for cell changes. This is called targeted&#xD;
        biopsies. As the endoscopist cannot always tell during gastroscopy where cells are changing,&#xD;
        biopsies from each quarter of the gullet (called quadrantic biopsies) are also taken to&#xD;
        reduce the risk of pre-cancerous cells being missed. However, this process is time consuming&#xD;
        and expensive as numerous biopsies are required.&#xD;
  &#xD;
        Recently, there has been a huge development in artificial intelligence (AI). One of these&#xD;
        developments is the aid of computer to detect (called computer-aided detection - CAD) the&#xD;
        abnormal cell changes within Barrett's during gastroscopy. This system has recently been&#xD;
        trained and tested on videos and photos to prove that its performance is as good as expert&#xD;
        endoscopists. This system has been already approved to use in the UK. However, this system&#xD;
        needs to be tested further and incorporated into real life use to prove that the CAD is&#xD;
        useful in detecting cell changes during gastroscopy for targeted biopsies and therefore, the&#xD;
        random biopsies can be avoided.&#xD;
  &#xD;
        A sample of patients with Barrett's oesophagus will be invited to participate in this study.&#xD;
        Participants will have a gastroscopy as part of their usual care for Barrett's oesophagus.&#xD;
        Endoscopist will inspect Barrett's oesophagus using AI and will take both targeted biopsies&#xD;
        if clinically deemed appropriate along with quadrantic biopsies. Participants will continue&#xD;
        to receive usual care and no additional follow up or procedures will be required as part of&#xD;
        the study.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Barrett's oesophagus is precursor to oesophageal adenocarcinoma and it affects 0.5-2% of the&#xD;
        western population. It has 0.5-3% risk of yearly progression to cancer from which &lt;20% will&#xD;
        survive at 5 years after diagnosis of cancer. Diagnosing early cancer including dysplasia in&#xD;
        Barrett's oesophagus improves survival. Current surveillance practice for Barrett's neoplasia&#xD;
        includes regular gastroscopy with careful inspection of Barrett's mucosa along with&#xD;
        quadrantic biopsies every 2 cm of Barrett's length as per Seattle protocol. This practice of&#xD;
        non-targeted biopsies is labour intensive, expensive and still misses neoplasia. Recently,&#xD;
        multiple computer-aided detection (CAD) systems with the use of deep learning have been&#xD;
        developed and validated in vitro studies to detect neoplasia. However, further real-life&#xD;
        studies are required to determine the efficacy and practicality of CAD in detecting Barrett's&#xD;
        neoplasia.&#xD;
  &#xD;
        The investigators hypothesise that WISE VISION® CAD system to detect Barrett's neoplasia can&#xD;
        improve the detection rate of targeted biopsies, hence making protocol-guided biopsy&#xD;
        unnecessary.&#xD;
  &#xD;
        Study Procedure&#xD;
  &#xD;
        This will be a real-life prospective study using WISE VISION®, NEC Japan, CAD system which is&#xD;
        already validated and approved for use in the UK and EU. Gastroscopy will be performed on&#xD;
        Barrett's oesophagus patients, who are willing to participate, for surveillance or assessment&#xD;
        of neoplasia as per the clinical need.&#xD;
  &#xD;
        Necessary preparations to achieve a good mucosal view of oesophagus will be advised during&#xD;
        procedure. This may include the use mucolytic drink (simeticone + N-acetylcystine) for&#xD;
        mucosal toileting, washing with a water jet and aspiration and the use of hyoscine&#xD;
        butylbromide to reduce oesophageal contractions as it would be performed as a standard&#xD;
        practice during routine gastroscopy.&#xD;
  &#xD;
        A quick white light imaging (WLI) withdrawal of endoscope will be done to ensure that all&#xD;
        mucosa is clean and exposed. If any obvious neoplastic lesion is detected by the endoscopist,&#xD;
        this will be noted down for future targeted biopsy.&#xD;
  &#xD;
        Next will be a WLI withdrawal with the WISE VISION® CAD system to detect any neoplasia. The&#xD;
        withdrawal will be repeated with rotation of the endoscope (12 o'clock position on the screen&#xD;
        to 6 o'clock position). Areas detected by the CAD system will be biopsied as per&#xD;
        endoscopist's discretion and the endoscopist will be asked to make a call as to whether it is&#xD;
        neoplasia or non-neoplasia. Location of any targeted biopsies will be recorded. This will be&#xD;
        followed by protocol-guided quadrantic biopsies while avoiding repeat biopsies of previously&#xD;
        targeted areas.&#xD;
  &#xD;
        Participants are expected to visit once for gastroscopy as a day case as part of their&#xD;
        standard of care. No additional visits are required. The gastroscopy will be performed as per&#xD;
        standard care and as detailed above. WISE VISION® CAD system is already in use in&#xD;
        participating centres, and this has become standard of care in these centres.&#xD;
  &#xD;
        Study population&#xD;
  &#xD;
        This will be a multi-centre study led by Queen Alexandra Hospital (QAH), Portsmouth, UK,&#xD;
        which is the Sponsor site. The study population is enriched with known Barrett's oesophagus&#xD;
        who are undergoing surveillance or assessment of neoplasia in Barrett's oesophagus. The study&#xD;
        population will include local patients and tertiary referrals received by QAH.&#xD;
  &#xD;
        This study will also be open to other external sites which have an organized Barrett's&#xD;
        endoscopy service and already use and are familiar with the WISE VISION® CAD system.&#xD;
  &#xD;
        Statistical plan&#xD;
  &#xD;
        The Chief Investigator of this study is highly experienced in developing and running&#xD;
        endoscopy clinical trials, including studies on the application of AI and CAD in endoscopy.&#xD;
        All co-investigators and members of the Sponsor site research team are GCP certified and have&#xD;
        experience in running various endoscopy-based studies. From clinical experience as a tertiary&#xD;
        centre, the investigators believe that the rate of neoplasia in enriched Barrett's population&#xD;
        at any tertiary referral centre would be around 25%, Our preliminary video-based experience&#xD;
        suggests that the sensitivity and specificity of CAD in detecting neoplasia in Barrett's is&#xD;
        around 90%.&#xD;
  &#xD;
        The sample size is based on achieving a reasonably precise estimate of the percentage of&#xD;
        patients in which neoplasia would be missed by AI and detected by multiple biopsies. It is&#xD;
        estimated that 5% of patients would have a missed neoplasia. The sample size is based on&#xD;
        obtaining an estimate of this outcome that is correct to within ±6% of the population value,&#xD;
        deemed to be an acceptable level of uncertainty. Using a 95% confidence level, it is&#xD;
        calculated that 51 patients with neoplasia are required. It is estimated that only 40% of all&#xD;
        recruited patients would have one or more neoplasia. Thus, in total it is proposed to recruit&#xD;
        127 patients in total into the study.&#xD;
  &#xD;
        Data collection&#xD;
  &#xD;
        Patient data collected at baseline will include:&#xD;
  &#xD;
          -  Demographics: ethnicity and occupation, social and lifestyle factors: smoking, alcohol&#xD;
             consumption&#xD;
  &#xD;
          -  History of Barrett's including date of first diagnosis of Barrett's and subsequent&#xD;
             treatments&#xD;
  &#xD;
          -  Previous endoscopy and histology reports&#xD;
  &#xD;
          -  Current relevant medications&#xD;
  &#xD;
        The first part of the CRF will be completed before gastroscopy. Consent can be withdrawn at&#xD;
        any point. Consent will be taken by delegated, GCP certified research personnel after&#xD;
        appropriate training has been completed and once deemed competent to take consent by the PI.&#xD;
        Patients who at this point decline consent will continue to have a standard gastroscopy on&#xD;
        the research list which will not be part of the study. Reason for decline will be collected&#xD;
        and added to the screening log.&#xD;
  &#xD;
        Participants will attend hospital as outpatients for their gastroscopy. Preparation for the&#xD;
        procedure and all other activities and medications provided during the procedure will be&#xD;
        carried out according to standard clinical practice, except for the use of CAD system for&#xD;
        detection prior to biopsy during gastroscopy.&#xD;
  &#xD;
        The following data will be recorded during gastroscopy:&#xD;
  &#xD;
          -  Duration of gastroscopy&#xD;
  &#xD;
          -  Use of sedation&#xD;
  &#xD;
          -  Length of Barrett's, using the Prague criteria&#xD;
  &#xD;
          -  Presence / absence and location of islands of Barrett's (distance in cm from incisor and&#xD;
             clock face direction in endoscope neutral position)&#xD;
  &#xD;
          -  Presence of endoscopically visible inflammation&#xD;
  &#xD;
          -  For targeted biopsies&#xD;
  &#xD;
               -  Location, size, morphology, optical diagnosis of each neoplastic area (grade of&#xD;
                  dysplasia or cancer)&#xD;
  &#xD;
               -  CAD positive or negative&#xD;
  &#xD;
                    -  If positive, agreement/disagreement with endoscopist to biopsy to rule out&#xD;
                       neoplasia&#xD;
  &#xD;
                    -  If not, reason for disagreement (counted as false positive)&#xD;
  &#xD;
          -  For quadrantic biopsies&#xD;
  &#xD;
               -  Location of biopsies and indication of whether it is part of the neoplasia detected&#xD;
                  by AI and/or endoscopist&#xD;
  &#xD;
        Post procedure&#xD;
  &#xD;
        After gastroscopy, patients remain in standard care. At this point all histology results&#xD;
        (from targeted and mapping biopsies) will be processed and released as soon as possible. This&#xD;
        will result in a delay of a maximum of eight weeks for histology to become available. Cancer&#xD;
        is usually clinically obvious and it would be unlikely to be missed at gastroscopy during the&#xD;
        study, and where obvious invasive cancer is suspected, samples will be sent as urgent and&#xD;
        immediate referral for treatment made. Unexpected cancer found in histopathology specimens&#xD;
        would again result in immediate referral for treatment via the established NHS cancer&#xD;
        pathways with the patient leaving the study. Therefore, clinical care would not be&#xD;
        compromised.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">July 2023</start_date>
    <completion_date type="Anticipated">January 2025</completion_date>
    <primary_completion_date type="Anticipated">November 2024</primary_completion_date>
    <study_type>Observational [Patient Registry]</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Case-Only</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <target_duration>2 Months</target_duration>
    <primary_outcome>
      <measure>Number of additional Barrett's neoplasia found on quadrantic biopsies</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>The primary endpoint of the study is the number of additional neoplasia found on quadrantic biopsies. This will be collected and calculated from histology data of the targeted and quadrantic biopsies.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Number of neoplasia missed by WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Sensitivity of WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Specificity of WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Accuracy of WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Positive predictive value of WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Negative predictive value of WISE VISION® CAD system</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Impact of AI (WISE VISION) in real-life</measure>
      <time_frame>From enrolment to end of follow up at 2 month when histology results are available.</time_frame>
      <description>Missed rate of WISE VISION® CAD system calculated from additional neoplasia on histology results of quadrantic biopsies.</description>
    </secondary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">127</enrollment>
    <condition>Gastroscopy</condition>
    <condition>Barrett's Esophagus</condition>
    <arm_group>
      <arm_group_label>Barrett's oesophagus</arm_group_label>
      <description>Patients over 18 with known Barrett's oesophagus having gastroscopy for either surveillance or assessment of known Barrett's neoplasia</description>
    </arm_group>
    <eligibility>
      <study_pop>
        <textblock>
          Any adults of over 18 years of age with a known Barrett's oesophagus having a gastroscopy&#xD;
          for Barrett's surveillance or assessment of known Barrett's neoplasia in a local or&#xD;
          tertiary hospital.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Anyone aged 18 years and above&#xD;
  &#xD;
            -  Known Barrett's oesophagus and having a gastroscopy for Barrett's surveillance or&#xD;
               assessment of known neoplasia.&#xD;
  &#xD;
            -  Participant is willing and able to give informed consent for participation in the&#xD;
               study&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Recent ablation therapy (HALO, APC) to Barrett's oesophagus in the last 6 weeks&#xD;
  &#xD;
            -  Oesophageal disorder and patient's factors which impairs the ability of endoscopist to&#xD;
               adequately assess of Barrett's neoplasia. This includes but not just limiting to&#xD;
               severe oesophagitis, candidiasis, and poor patient tolerance.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <gender_based>Yes</gender_based>
      <gender_description>Any self-identified genders</gender_description>
      <minimum_age>N/A</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Pradeep Bhandari</last_name>
      <role>Principal Investigator</role>
      <affiliation>Queen Alexandra Hospital, Portsmouth Hospitals University NHS Trust</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Hein Htet, MBBS</last_name>
      <phone>+44 23 9228 6000</phone>
      <phone_ext>+6929</phone_ext>
      <email>hein.htet@porthosp.nhs.uk</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Laura Marshall</last_name>
      <phone>+44 23 9228 6000</phone>
      <phone_ext>5455</phone_ext>
      <email>laura.marshall2@porthosp.nhs.uk</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Queen Alexandra Hospital, Portsmouth Hospitals University NHS trust</name>
        <address>
          <city>Portsmouth</city>
          <state>Hampshire</state>
          <zip>PO6 1LY</zip>
          <country>United Kingdom</country>
        </address>
      </facility>
      <contact>
        <last_name>Michelle Baker-Moffatt</last_name>
        <phone>+44 2392 286000</phone>
        <phone_ext>5609</phone_ext>
        <email>michelle.baker-moffatt@porthosp.nhs.uk</email>
      </contact>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <reference>
      <citation>Abdelrahim M, Saiko M, Maeda N, Hossain E, Alkandari A, Subramaniam S, Parra-Blanco A, Sanchez-Yague A, Coron E, Repici A, Bhandari P. Development and validation of artificial neural networks model for detection of Barrett's neoplasia: a multicenter pragmatic nonrandomized trial (with video). Gastrointest Endosc. 2023 Mar;97(3):422-434. doi: 10.1016/j.gie.2022.10.031. Epub 2022 Oct 23. Erratum In: Gastrointest Endosc. 2023 Jul;98(1):144.</citation>
      <PMID>36283443</PMID>
    </reference>
    <verification_date>June 2023</verification_date>
    <study_first_submitted>June 8, 2023</study_first_submitted>
    <study_first_submitted_qc>July 25, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">July 28, 2023</study_first_posted>
    <last_update_submitted>July 25, 2023</last_update_submitted>
    <last_update_submitted_qc>July 25, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">July 28, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Barrett's oesophagus</keyword>
    <keyword>Artificial intelligence</keyword>
    <keyword>Endoscopy</keyword>
    <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>Undecided</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/NCT05965921
  org study id: 23/PR/0213
  nct id: NCT05965921
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  Barrett's oesophagus is a pre-cancerous condition in which normal cells in the lining of
        gullet undergo cell changes and this increases the risk of developing adenocarcinoma (a type
        of cancer) of the gullet. This type of cancer is the 5th most common type of cancer in the
        UK. To minimise this risk of developing cancer, patients with Barret's oesophagus have
        regular gastroscopy (a small camera at the tip of the slim tube) every 2-5 years to detect
        early cancer cell changes. During the procedure, the whole of oesophagus is carefully
        inspected, and small tissue samples (biopsies) are taken from visible abnormal area within
        Barrett's oesophagus and sent to the lab to check for cell changes. This is called targeted
        biopsies. As the endoscopist cannot always tell during gastroscopy where cells are changing,
        biopsies from each quarter of the gullet (called quadrantic biopsies) are also taken to
        reduce the risk of pre-cancerous cells being missed. However, this process is time consuming
        and expensive as numerous biopsies are required.
  
        Recently, there has been a huge development in artificial intelligence (AI). One of these
        developments is the aid of computer to detect (called computer-aided detection - CAD) the
        abnormal cell changes within Barrett's during gastroscopy. This system has recently been
        trained and tested on videos and photos to prove that its performance is as good as expert
        endoscopists. This system has been already approved to use in the UK. However, this system
        needs to be tested further and incorporated into real life use to prove that the CAD is
        useful in detecting cell changes during gastroscopy for targeted biopsies and therefore, the
        random biopsies can be avoided.
  
        A sample of patients with Barrett's oesophagus will be invited to participate in this study.
        Participants will have a gastroscopy as part of their usual care for Barrett's oesophagus.
        Endoscopist will inspect Barrett's oesophagus using AI and will take both targeted biopsies
        if clinically deemed appropriate along with quadrantic biopsies. Participants will continue
        to receive usual care and no additional follow up or procedures will be required as part of
        the study.
  Barrett's oesophagus is precursor to oesophageal adenocarcinoma and it affects 0.5-2% of the
        western population. It has 0.5-3% risk of yearly progression to cancer from which <20% will
        survive at 5 years after diagnosis of cancer. Diagnosing early cancer including dysplasia in
        Barrett's oesophagus improves survival. Current surveillance practice for Barrett's neoplasia
        includes regular gastroscopy with careful inspection of Barrett's mucosa along with
        quadrantic biopsies every 2 cm of Barrett's length as per Seattle protocol. This practice of
        non-targeted biopsies is labour intensive, expensive and still misses neoplasia. Recently,
        multiple computer-aided detection (CAD) systems with the use of deep learning have been
        developed and validated in vitro studies to detect neoplasia. However, further real-life
        studies are required to determine the efficacy and practicality of CAD in detecting Barrett's
        neoplasia.
  
        The investigators hypothesise that WISE VISION® CAD system to detect Barrett's neoplasia can
        improve the detection rate of targeted biopsies, hence making protocol-guided biopsy
        unnecessary.
  
        Study Procedure
  
        This will be a real-life prospective study using WISE VISION®, NEC Japan, CAD system which is
        already validated and approved for use in the UK and EU. Gastroscopy will be performed on
        Barrett's oesophagus patients, who are willing to participate, for surveillance or assessment
        of neoplasia as per the clinical need.
  
        Necessary preparations to achieve a good mucosal view of oesophagus will be advised during
        procedure. This may include the use mucolytic drink (simeticone + N-acetylcystine) for
        mucosal toileting, washing with a water jet and aspiration and the use of hyoscine
        butylbromide to reduce oesophageal contractions as it would be performed as a standard
        practice during routine gastroscopy.
  
        A quick white light imaging (WLI) withdrawal of endoscope will be done to ensure that all
        mucosa is clean and exposed. If any obvious neoplastic lesion is detected by the endoscopist,
        this will be noted down for future targeted biopsy.
  
        Next will be a WLI withdrawal with the WISE VISION® CAD system to detect any neoplasia. The
        withdrawal will be repeated with rotation of the endoscope (12 o'clock position on the screen
        to 6 o'clock position). Areas detected by the CAD system will be biopsied as per
        endoscopist's discretion and the endoscopist will be asked to make a call as to whether it is
        neoplasia or non-neoplasia. Location of any targeted biopsies will be recorded. This will be
        followed by protocol-guided quadrantic biopsies while avoiding repeat biopsies of previously
        targeted areas.
  
        Participants are expected to visit once for gastroscopy as a day case as part of their
        standard of care. No additional visits are required. The gastroscopy will be performed as per
        standard care and as detailed above. WISE VISION® CAD system is already in use in
        participating centres, and this has become standard of care in these centres.
  
        Study population
  
        This will be a multi-centre study led by Queen Alexandra Hospital (QAH), Portsmouth, UK,
        which is the Sponsor site. The study population is enriched with known Barrett's oesophagus
        who are undergoing surveillance or assessment of neoplasia in Barrett's oesophagus. The study
        population will include local patients and tertiary referrals received by QAH.
  
        This study will also be open to other external sites which have an organized Barrett's
        endoscopy service and already use and are familiar with the WISE VISION® CAD system.
  
        Statistical plan
  
        The Chief Investigator of this study is highly experienced in developing and running
        endoscopy clinical trials, including studies on the application of AI and CAD in endoscopy.
        All co-investigators and members of the Sponsor site research team are GCP certified and have
        experience in running various endoscopy-based studies. From clinical experience as a tertiary
        centre, the investigators believe that the rate of neoplasia in enriched Barrett's population
        at any tertiary referral centre would be around 25%, Our preliminary video-based experience
        suggests that the sensitivity and specificity of CAD in detecting neoplasia in Barrett's is
        around 90%.
  
        The sample size is based on achieving a reasonably precise estimate of the percentage of
        patients in which neoplasia would be missed by AI and detected by multiple biopsies. It is
        estimated that 5% of patients would have a missed neoplasia. The sample size is based on
        obtaining an estimate of this outcome that is correct to within ±6% of the population value,
        deemed to be an acceptable level of uncertainty. Using a 95% confidence level, it is
        calculated that 51 patients with neoplasia are required. It is estimated that only 40% of all
        recruited patients would have one or more neoplasia. Thus, in total it is proposed to recruit
        127 patients in total into the study.
  
        Data collection
  
        Patient data collected at baseline will include:
  
          -  Demographics: ethnicity and occupation, social and lifestyle factors: smoking, alcohol
             consumption
  
          -  History of Barrett's including date of first diagnosis of Barrett's and subsequent
             treatments
  
          -  Previous endoscopy and histology reports
  
          -  Current relevant medications
  
        The first part of the CRF will be completed before gastroscopy. Consent can be withdrawn at
        any point. Consent will be taken by delegated, GCP certified research personnel after
        appropriate training has been completed and once deemed competent to take consent by the PI.
        Patients who at this point decline consent will continue to have a standard gastroscopy on
        the research list which will not be part of the study. Reason for decline will be collected
        and added to the screening log.
  
        Participants will attend hospital as outpatients for their gastroscopy. Preparation for the
        procedure and all other activities and medications provided during the procedure will be
        carried out according to standard clinical practice, except for the use of CAD system for
        detection prior to biopsy during gastroscopy.
  
        The following data will be recorded during gastroscopy:
  
          -  Duration of gastroscopy
  
          -  Use of sedation
  
          -  Length of Barrett's, using the Prague criteria
  
          -  Presence / absence and location of islands of Barrett's (distance in cm from incisor and
             clock face direction in endoscope neutral position)
  
          -  Presence of endoscopically visible inflammation
  
          -  For targeted biopsies
  
               -  Location, size, morphology, optical diagnosis of each neoplastic area (grade of
                  dysplasia or cancer)
  
               -  CAD positive or negative
  
                    -  If positive, agreement/disagreement with endoscopist to biopsy to rule out
                       neoplasia
  
                    -  If not, reason for disagreement (counted as false positive)
  
          -  For quadrantic biopsies
  
               -  Location of biopsies and indication of whether it is part of the neoplasia detected
                  by AI and/or endoscopist
  
        Post procedure
  
        After gastroscopy, patients remain in standard care. At this point all histology results
        (from targeted and mapping biopsies) will be processed and released as soon as possible. This
        will result in a delay of a maximum of eight weeks for histology to become available. Cancer
        is usually clinically obvious and it would be unlikely to be missed at gastroscopy during the
        study, and where obvious invasive cancer is suspected, samples will be sent as urgent and
        immediate referral for treatment made. Unexpected cancer found in histopathology specimens
        would again result in immediate referral for treatment via the established NHS cancer
        pathways with the patient leaving the study. Therefore, clinical care would not be
        compromised.
  observational model: Case-Only
  time perspective: Prospective
  measure: Number of additional Barrett's neoplasia found on quadrantic biopsies
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: The primary endpoint of the study is the number of additional neoplasia found on quadrantic biopsies. This will be collected and calculated from histology data of the targeted and quadrantic biopsies.
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Number of neoplasia missed by WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Sensitivity of WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Specificity of WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Accuracy of WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Positive predictive value of WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Negative predictive value of WISE VISION® CAD system
  measure: Impact of AI (WISE VISION) in real-life
  time frame: From enrolment to end of follow up at 2 month when histology results are available.
  description: Missed rate of WISE VISION® CAD system calculated from additional neoplasia on histology results of quadrantic biopsies.
  arm group label: Barrett's oesophagus
  description: Patients over 18 with known Barrett's oesophagus having gastroscopy for either surveillance or assessment of known Barrett's neoplasia
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  gender based: Yes
  gender description: Any self-identified genders
  minimum age: N/A
  maximum age: N/A
  healthy volunteers: No
  last name: Pradeep Bhandari
  role: Principal Investigator
  affiliation: Queen Alexandra Hospital, Portsmouth Hospitals University NHS Trust
  last name: Hein Htet, MBBS
  phone: +44 23 9228 6000
  phone ext: +6929
  email: hein.htet@porthosp.nhs.uk
  last name: Laura Marshall
  phone: +44 23 9228 6000
  phone ext: 5455
  email: laura.marshall2@porthosp.nhs.uk
  facility: 
  contact: 
  country: United Kingdom
  citation: Abdelrahim M, Saiko M, Maeda N, Hossain E, Alkandari A, Subramaniam S, Parra-Blanco A, Sanchez-Yague A, Coron E, Repici A, Bhandari P. Development and validation of artificial neural networks model for detection of Barrett's neoplasia: a multicenter pragmatic nonrandomized trial (with video). Gastrointest Endosc. 2023 Mar;97(3):422-434. doi: 10.1016/j.gie.2022.10.031. Epub 2022 Oct 23. Erratum In: Gastrointest Endosc. 2023 Jul;98(1):144.
  PMID: 36283443
  responsible party type: Sponsor
  mesh term: Barrett Esophagus
  sharing ipd: Undecided