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/NCT05969691</url>
    </required_header>
    <id_info>
      <org_study_id>MINGGE-SW-00003-V1-01</org_study_id>
      <nct_id>NCT05969691</nct_id>
    </id_info>
    <brief_title>Radiomics-Based Visualization and Quantitative Validation of IDH1 Heterogeneity in Gliomas</brief_title>
    <official_title>Radiomics-Based Visualization and Quantitative Validation of Isocitrate Dehydrogenase 1 Heterogeneity in Gliomas</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Mingge LLC</agency>
        <agency_class>Industry</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Huashan Hospital</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Fudan University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Mingge LLC</source>
    <oversight_info>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this clinical trail is to non-invasively visualise and quantitatively validate an&#xD;
        radiomics model of genetic heterogeneity in adult patients with diffuse glioma to help&#xD;
        clinicians better guide surgical resection and treatment options. It aims to answer are:&#xD;
  &#xD;
          1. To overcome the limitations of the existing genetic diagnostic process in terms of&#xD;
             equipment and technology requirements, high costs and long timelines, and to enable&#xD;
             quantitative studies of isocitrate dehydrogenase 1 (IDH1) mutations, thus allowing&#xD;
             refined patient stratification and further exploration of the role of molecular markers&#xD;
             in improving patient prognosis.&#xD;
  &#xD;
          2. To achieve non-invasive diagnosis of gene mutations within tumours by taking advantage&#xD;
             of artificial intelligence and medical images, and to test the clinical feasibility of&#xD;
             the model through typical target puncture, gene sequencing and quantitative gene&#xD;
             expression analysis.&#xD;
  &#xD;
        Participants will read an informed consent agreement before surgery and voluntarily decide&#xD;
        whether or not to join the experimental group. They will undergo preoperative magnetic&#xD;
        resonance imaging, intraoperative brain puncture of typical tumour sites, and postoperative&#xD;
        genotype identification. Their imaging data, genotype data, clinical history data, and&#xD;
        pathology data will be used for the experimental study.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        BACKGROUND&#xD;
  &#xD;
        The WHO 2016 officially introduced molecular markers into the pathological diagnosis of&#xD;
        gliomas, marking a step into the era of molecular diagnosis of gliomas. Among them,&#xD;
        isocitrate dehydrogenase 1 (IDH1) mutation is considered to be the 'backbone' in the&#xD;
        development of gliomas, and affects the treatment plan and prognosis of patients. However,&#xD;
        the clinical use of this molecular biomarker is still controversial, which is rooted in the&#xD;
        lack of quantitative studies on IDH1 mutations. The spatial heterogeneity of gliomas has been&#xD;
        demonstrated in existing studies, i.e., tumor tissues in different parts of the same glioma&#xD;
        belong to different genetic subtypes. This implies that IDH1-mutant tumors do not indicate&#xD;
        the presence of mutations in all tumor cells, thus further exacerbating the problems in&#xD;
        clinical genetic diagnosis.&#xD;
  &#xD;
        OBJECTIVE&#xD;
  &#xD;
        To quantify gene mutations in tumours, we plan to use radiomics model with artificial&#xD;
        intelligence and clinical big data, and verify its accuracy by tissue puncture. In this way,&#xD;
        we can overcome the challenges of multisite sampling and second-generation sequencing, such&#xD;
        as high equipment and technology requirements, high cost and long time, and thus&#xD;
        theoretically realise the visualisation and quantification of genetic heterogeneity within&#xD;
        gliomas.&#xD;
  &#xD;
        PROCESS&#xD;
  &#xD;
        Participants will read an informed consent agreement before surgery and voluntarily decide&#xD;
        whether or not to join the experimental group.&#xD;
  &#xD;
          1. Modelling of visualisation of genetic heterogeneity&#xD;
  &#xD;
             Before surgery, participants first Routine imaging and the resulting images will be used&#xD;
             to build a radiomics model. The model will non-invasively predict IDH1 mutations in&#xD;
             gliomas.&#xD;
  &#xD;
          2. Typical site puncture&#xD;
  &#xD;
             After the enrolled participants were anaesthetised and craniotomised, clinicians&#xD;
             selected typical tumor sites for puncture based on the model outputs.&#xD;
  &#xD;
          3. Histopathological diagnosis&#xD;
  &#xD;
             The specimen from the same puncture site is divided into two parts, and the first part&#xD;
             is routinely formalin-fixed for paraffin embedding and finally H&amp;E-stained sections. The&#xD;
             pathologist first reads the H&amp;E sections and makes a histological diagnosis, describing&#xD;
             the pathological morphology and characteristics, especially the tumor cell content and&#xD;
             distribution.&#xD;
  &#xD;
          4. IDH1 single nucleotide sequencing&#xD;
  &#xD;
             Another part of the sample is used for liquid nitrogen preservation. The Qiagen DNA/RNA&#xD;
             Extraction Kit is used to extract DNA from the liquid nitrogen preserved tumour tissue,&#xD;
             which is purified and subjected to the IDH1 polymerase chain reaction (PCR). The PCR&#xD;
             product is purified and subjected to sequencing, and the sequencing product is detected&#xD;
             on an ABI 7200 sequencer to determine whether IDH1 is mutated or not.&#xD;
  &#xD;
          5. Mass spectrometry analysis of 2-Hydroxyglutarate (2-HG) expression levels&#xD;
  &#xD;
             The presence and expression of 2-HG in glioma samples is detected and analysed by mass&#xD;
             spectrometry.&#xD;
  &#xD;
          6. Validation of the radiomics-based IDH1 mutation prediction model. The 2-HG detection&#xD;
             results were numerically compared with the model results.&#xD;
  &#xD;
        This is a single centre validation study. Compared with the routine glioma surgical&#xD;
        procedure, this study adds intraoperative tumor-typical sits puncture to validate the&#xD;
        predictive accuracy of the radiomics model and collects corresponding MRI images, tumour&#xD;
        histology diagnosis, molecular pathology diagnosis. The radiomics model is built based on&#xD;
        preoperative clinical data and is a non-invasive and rapid tool for quantitative analysis and&#xD;
        visualisation of tumor genes.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Active, not recruiting</overall_status>
    <start_date type="Actual">March 15, 2019</start_date>
    <completion_date type="Anticipated">December 15, 2026</completion_date>
    <primary_completion_date type="Anticipated">December 15, 2025</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>N/A</allocation>
      <intervention_model>Single Group Assignment</intervention_model>
      <primary_purpose>Other</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>accuracy</measure>
      <time_frame>End of study (24 weeks)</time_frame>
      <description>The ratio of correct model predictions to all predictions is calculated by comparing the results with the puncture results.</description>
    </primary_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Actual">18</enrollment>
    <condition>Glioma, Malignant</condition>
    <condition>Computer-Assisted</condition>
    <arm_group>
      <arm_group_label>Validation of IDH1 mutations from the radiomics model</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>In this experiment, we validate the accuracy of radiomics model for IDH1 prediction by puncturing typical targets of gliomas, gene sequencing and quantitative gene analysis.</description>
    </arm_group>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Validation of IDH1 mutations from the radiomics model</intervention_name>
      <description>During surgery, clinicians will select several typical target sites for puncture based on the preoperative model outputs. After surgery, the acquired tumour tissues will be subjected to histological diagnosis and pathological diagnosis by professional pathologists, and the results will be compared with the model output to verify its accuracy.</description>
      <arm_group_label>Validation of IDH1 mutations from the radiomics model</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Patients aged 18-70 years, male or female;&#xD;
  &#xD;
            -  Patients with complete preoperative magnetic resonance imaging and were initially&#xD;
               diagnosed with glioma based on the magnetic resonance imaging results;&#xD;
  &#xD;
            -  Patients who were proposed for craniectomy without contraindications to surgery and&#xD;
               who had signed an informed consent form by themselves or their proxy;&#xD;
  &#xD;
            -  Patients with confirmed diagnosis of glioma by postoperative pathological diagnosis.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Patients to be admitted for a simple puncture biopsy;&#xD;
  &#xD;
            -  Patients with a combination of serious medical conditions and those who cannot&#xD;
               tolerate surgery;&#xD;
  &#xD;
            -  Patients with a bleeding tendency or abnormal coagulation function, or those who have&#xD;
               not discontinued long-term use of anticoagulants such as aspirin and clopidogrel;&#xD;
  &#xD;
            -  Pregnant and breastfeeding women;&#xD;
  &#xD;
            -  Patients participate in other clinical trials during the same period.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>80 Years</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Ying Mao, DM</last_name>
      <role>Study Chair</role>
      <affiliation>Huashan Hospital</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Zhifeng Shi, DM</last_name>
      <role>Study Director</role>
      <affiliation>Huashan Hospital</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Jinhua Yu, DE</last_name>
      <role>Study Director</role>
      <affiliation>Fudan University</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Zengxin Qi, DM</last_name>
      <role>Principal Investigator</role>
      <affiliation>Huashan Hospital</affiliation>
    </overall_official>
    <location>
      <facility>
        <name>Huashan Hospital, Fudan University</name>
        <address>
          <city>Shanghai</city>
          <state>Shanghai</state>
          <zip>200433</zip>
          <country>China</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>China</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>July 23, 2023</study_first_submitted>
    <study_first_submitted_qc>July 23, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 1, 2023</study_first_posted>
    <last_update_submitted>August 4, 2023</last_update_submitted>
    <last_update_submitted_qc>August 4, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 8, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Genetic Heterogeneity</keyword>
    <keyword>Gliomas</keyword>
    <keyword>Computer-Assisted Diagnosis</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Glioma</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>All patient information collected by the Huashan Hospital will be kept strictly confidential. We will share the results and findings of the study with other researchers.</ipd_description>
    </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/NCT05969691
  org study id: MINGGE-SW-00003-V1-01
  nct id: NCT05969691
  lead sponsor: 
  collaborator: 
  collaborator: 
  is fda regulated drug: No
  is fda regulated device: No
  The goal of this clinical trail is to non-invasively visualise and quantitatively validate an
        radiomics model of genetic heterogeneity in adult patients with diffuse glioma to help
        clinicians better guide surgical resection and treatment options. It aims to answer are:
  
          1. To overcome the limitations of the existing genetic diagnostic process in terms of
             equipment and technology requirements, high costs and long timelines, and to enable
             quantitative studies of isocitrate dehydrogenase 1 (IDH1) mutations, thus allowing
             refined patient stratification and further exploration of the role of molecular markers
             in improving patient prognosis.
  
          2. To achieve non-invasive diagnosis of gene mutations within tumours by taking advantage
             of artificial intelligence and medical images, and to test the clinical feasibility of
             the model through typical target puncture, gene sequencing and quantitative gene
             expression analysis.
  
        Participants will read an informed consent agreement before surgery and voluntarily decide
        whether or not to join the experimental group. They will undergo preoperative magnetic
        resonance imaging, intraoperative brain puncture of typical tumour sites, and postoperative
        genotype identification. Their imaging data, genotype data, clinical history data, and
        pathology data will be used for the experimental study.
  BACKGROUND
  
        The WHO 2016 officially introduced molecular markers into the pathological diagnosis of
        gliomas, marking a step into the era of molecular diagnosis of gliomas. Among them,
        isocitrate dehydrogenase 1 (IDH1) mutation is considered to be the 'backbone' in the
        development of gliomas, and affects the treatment plan and prognosis of patients. However,
        the clinical use of this molecular biomarker is still controversial, which is rooted in the
        lack of quantitative studies on IDH1 mutations. The spatial heterogeneity of gliomas has been
        demonstrated in existing studies, i.e., tumor tissues in different parts of the same glioma
        belong to different genetic subtypes. This implies that IDH1-mutant tumors do not indicate
        the presence of mutations in all tumor cells, thus further exacerbating the problems in
        clinical genetic diagnosis.
  
        OBJECTIVE
  
        To quantify gene mutations in tumours, we plan to use radiomics model with artificial
        intelligence and clinical big data, and verify its accuracy by tissue puncture. In this way,
        we can overcome the challenges of multisite sampling and second-generation sequencing, such
        as high equipment and technology requirements, high cost and long time, and thus
        theoretically realise the visualisation and quantification of genetic heterogeneity within
        gliomas.
  
        PROCESS
  
        Participants will read an informed consent agreement before surgery and voluntarily decide
        whether or not to join the experimental group.
  
          1. Modelling of visualisation of genetic heterogeneity
  
             Before surgery, participants first Routine imaging and the resulting images will be used
             to build a radiomics model. The model will non-invasively predict IDH1 mutations in
             gliomas.
  
          2. Typical site puncture
  
             After the enrolled participants were anaesthetised and craniotomised, clinicians
             selected typical tumor sites for puncture based on the model outputs.
  
          3. Histopathological diagnosis
  
             The specimen from the same puncture site is divided into two parts, and the first part
             is routinely formalin-fixed for paraffin embedding and finally H&E-stained sections. The
             pathologist first reads the H&E sections and makes a histological diagnosis, describing
             the pathological morphology and characteristics, especially the tumor cell content and
             distribution.
  
          4. IDH1 single nucleotide sequencing
  
             Another part of the sample is used for liquid nitrogen preservation. The Qiagen DNA/RNA
             Extraction Kit is used to extract DNA from the liquid nitrogen preserved tumour tissue,
             which is purified and subjected to the IDH1 polymerase chain reaction (PCR). The PCR
             product is purified and subjected to sequencing, and the sequencing product is detected
             on an ABI 7200 sequencer to determine whether IDH1 is mutated or not.
  
          5. Mass spectrometry analysis of 2-Hydroxyglutarate (2-HG) expression levels
  
             The presence and expression of 2-HG in glioma samples is detected and analysed by mass
             spectrometry.
  
          6. Validation of the radiomics-based IDH1 mutation prediction model. The 2-HG detection
             results were numerically compared with the model results.
  
        This is a single centre validation study. Compared with the routine glioma surgical
        procedure, this study adds intraoperative tumor-typical sits puncture to validate the
        predictive accuracy of the radiomics model and collects corresponding MRI images, tumour
        histology diagnosis, molecular pathology diagnosis. The radiomics model is built based on
        preoperative clinical data and is a non-invasive and rapid tool for quantitative analysis and
        visualisation of tumor genes.
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Other
  masking: None (Open Label)
  measure: accuracy
  time frame: End of study (24 weeks)
  description: The ratio of correct model predictions to all predictions is calculated by comparing the results with the puncture results.
  arm group label: Validation of IDH1 mutations from the radiomics model
  arm group type: Experimental
  description: In this experiment, we validate the accuracy of radiomics model for IDH1 prediction by puncturing typical targets of gliomas, gene sequencing and quantitative gene analysis.
  intervention type: Diagnostic Test
  intervention name: Validation of IDH1 mutations from the radiomics model
  description: During surgery, clinicians will select several typical target sites for puncture based on the preoperative model outputs. After surgery, the acquired tumour tissues will be subjected to histological diagnosis and pathological diagnosis by professional pathologists, and the results will be compared with the model output to verify its accuracy.
  arm group label: Validation of IDH1 mutations from the radiomics model
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 80 Years
  healthy volunteers: No
  last name: Ying Mao, DM
  role: Study Chair
  affiliation: Huashan Hospital
  last name: Zhifeng Shi, DM
  role: Study Director
  affiliation: Huashan Hospital
  last name: Jinhua Yu, DE
  role: Study Director
  affiliation: Fudan University
  last name: Zengxin Qi, DM
  role: Principal Investigator
  affiliation: Huashan Hospital
  facility: 
  country: China
  responsible party type: Sponsor
  mesh term: Glioma
  sharing ipd: No
  ipd description: All patient information collected by the Huashan Hospital will be kept strictly confidential. We will share the results and findings of the study with other researchers.