<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/NCT04416776</url>
  </required_header>
  <id_info>
    <org_study_id>SIDS-2020</org_study_id>
    <nct_id>NCT04416776</nct_id>
  </id_info>
  <brief_title>Validation of the Utility of Strabismus Intelligent Diagnostic System</brief_title>
  <official_title>Validation of the Utility of Strabismus Intelligent Diagnostic System: A Clinical Trial</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Sun Yat-sen University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Sun Yat-sen University</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>
      Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age&#xD;
      of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious&#xD;
      and highly dependent on the experience of the specialist and the cooperation of the patients.&#xD;
      Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the&#xD;
      investigators use deep learning to develop an artificial intelligence (AI) platform&#xD;
      consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and&#xD;
      propose a surgical plan based on corneal light-reflection photos. The investigator also&#xD;
      conduct clinical trial to validate its versatility in clinical practice.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">September 1, 2019</start_date>
  <completion_date type="Anticipated">June 10, 2020</completion_date>
  <primary_completion_date type="Anticipated">June 10, 2020</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>The proportion of accurate, mistaken and miss detection of the diagnostic system.</measure>
    <time_frame>up to 3 years</time_frame>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">323</enrollment>
  <condition>Ophthalmological Disorder</condition>
  <condition>Strabismus</condition>
  <arm_group>
    <arm_group_label>Eligible patients for AI test</arm_group_label>
    <description>Device: strabismus diagnostic system.</description>
  </arm_group>
  <intervention>
    <intervention_type>Drug</intervention_type>
    <intervention_name>Strabismus diagnostic system.</intervention_name>
    <description>An AI platform based on corneal light-reflection photos to facilitate the diagnosis and angle evaluation of strabismus and to provide advice for surgical planning.</description>
    <arm_group_label>Eligible patients for AI test</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        A prospective study to validate the accuracy of the strabismus intelligent diagnostic&#xD;
        system in the clinical practice.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients in the outpatient clinic of strabismus department.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patients or their parents diagree to participate in the trial.&#xD;
&#xD;
          -  Patients with blepharoptosis.&#xD;
&#xD;
          -  Patients can't facing forward or lacking fixation.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Keli Mao, M.D</last_name>
    <phone>87330493</phone>
    <email>maokl@mail2.sysu.edu.cn</email>
  </overall_contact>
  <location>
    <facility>
      <name>Zhongshan Ophthalmic Center, Sun Yat-sen University</name>
      <address>
        <city>Guangzhou</city>
        <state>Guangdong</state>
        <zip>510080</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Keli Mao, M.D.</last_name>
      <phone>87330493</phone>
      <email>maokl@mail2.sysu.edu.cn</email>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>June 2020</verification_date>
  <study_first_submitted>June 2, 2020</study_first_submitted>
  <study_first_submitted_qc>June 2, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 4, 2020</study_first_posted>
  <last_update_submitted>June 2, 2020</last_update_submitted>
  <last_update_submitted_qc>June 2, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">June 4, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Sun Yat-sen University</investigator_affiliation>
    <investigator_full_name>Haotian Lin</investigator_full_name>
    <investigator_title>Clinical Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Strabismus</mesh_term>
    <mesh_term>Eye Diseases</mesh_term>
  </condition_browse>
  <!-- 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/NCT04416776
org study id: SIDS-2020
nct id: NCT04416776
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age
      of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious
      and highly dependent on the experience of the specialist and the cooperation of the patients.
      Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the
      investigators use deep learning to develop an artificial intelligence (AI) platform
      consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and
      propose a surgical plan based on corneal light-reflection photos. The investigator also
      conduct clinical trial to validate its versatility in clinical practice.
observational model: Cohort
time perspective: Prospective
measure: The proportion of accurate, mistaken and miss detection of the diagnostic system.
time frame: up to 3 years
arm group label: Eligible patients for AI test
description: Device: strabismus diagnostic system.
intervention type: Drug
intervention name: Strabismus diagnostic system.
description: An AI platform based on corneal light-reflection photos to facilitate the diagnosis and angle evaluation of strabismus and to provide advice for surgical planning.
arm group label: Eligible patients for AI test
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Keli Mao, M.D
phone: 87330493
email: maokl@mail2.sysu.edu.cn
facility: 
status: Recruiting
contact: 
country: China
responsible party type: Principal Investigator
investigator affiliation: Sun Yat-sen University
investigator full name: Haotian Lin
investigator title: Clinical Professor
mesh term: Strabismus
mesh term: Eye Diseases