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/NCT06006338</url>
    </required_header>
    <id_info>
      <org_study_id>ZYH-CX-001</org_study_id>
      <nct_id>NCT06006338</nct_id>
    </id_info>
    <brief_title>3D Printed Models for Liver Surgery</brief_title>
    <official_title>The Clinical Value of 3D Self-healing Elastic Liver Model for Surgical Training and Preoperative Planning: a Preliminary Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Zhejiang Cancer Hospital</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Zhejiang Cancer Hospital</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>
        Comprehensive preoperative planning and real-time intraoperative guidance are essential&#xD;
        prerequisites for achieving precise liver resection. In pursuit of this goal, the&#xD;
        investigators have developed innovative 3D printed liver models utilizing a physically&#xD;
        crosslinked self-healing elastomer created through the copolymerization of&#xD;
        4-acryloylmorpholine (ACMO) and methoxy poly (ethylene glycol) acrylate (mPEGA). These&#xD;
        printed models exhibit exceptional healing capabilities, efficiently restoring their&#xD;
        structure within minutes at room temperature, and rapidly recovering within moments after&#xD;
        being incised.&#xD;
  &#xD;
        Herein, the investigators aim to assess the viability of employing these 3D printed liver&#xD;
        models as instrumental tools in designing the optimal surgical approach through an iterative&#xD;
        trial-and-error methodology. Concurrently, the investigators aim to determine whether the&#xD;
        integration of these 3D printed models into conventional methods (contrast-enhanced CT or&#xD;
        MRI) can enhance the safety, ease, and efficiency of hepatic resection procedures.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Recruiting</overall_status>
    <start_date type="Anticipated">September 1, 2023</start_date>
    <completion_date type="Anticipated">February 29, 2024</completion_date>
    <primary_completion_date type="Anticipated">December 31, 2023</primary_completion_date>
    <phase>Phase 1</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>Device Feasibility</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>R0 resection rate</measure>
      <time_frame>10 days</time_frame>
      <description>The proportion of patients who achieved pathological negative surgical margin</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Injury of vital vascular structures</measure>
      <time_frame>Immediately after the surgery.</time_frame>
      <description>The Injury of vital vascular structures, such as portal veins or hepatic veins.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Operation time</measure>
      <time_frame>Immediately after the surgery.</time_frame>
      <description>Time length (minute) between the beginning and the end of the surgery.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Blood loss</measure>
      <time_frame>Immediately after the surgery.</time_frame>
      <description>The amount of lost blood (ml) in the operation.</description>
    </secondary_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Anticipated">5</enrollment>
    <condition>Liver Cancer</condition>
    <arm_group>
      <arm_group_label>Experimental arm</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>3D Printed Model for preoperative planning</intervention_name>
      <description>Besides conventional preoperative planning based on contrast-enhanced CT/MRI, the investigator refers to a 3D printed model to determine the optimal surgical approach via a trial-and-error method. Specifically, a personalized 3D printed model is fabricated. By referring to the printed model and CT/MRI images, a preliminary surgical trace is determined. Then, a simulation surgery is performed on the model, and surgical margin and the potential injury of vital vascular structures are evaluated. This assessment leads to the adjustment of the surgical path as necessary. The refined surgical route is then validated through a second simulation surgery performed on the healed 3D model. This iterative process is repeated multiple times, allowing for a comprehensive exploration of various approaches until the optimal surgical strategy crystallizes. Next, the investigator proceeds to execute the real surgery on the participant, meticulously adhering to the determined optimal surgical approach.</description>
      <arm_group_label>Experimental arm</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            1. 18-80 years old;&#xD;
  &#xD;
            2. Patients with a resectable tumor in the liver;&#xD;
  &#xD;
            3. Eastern Cooperative Oncology Group Performance status score: 0;&#xD;
  &#xD;
            4. Child-Pugh classification: A;&#xD;
  &#xD;
            5. The Laboratory test results meet the following criteria and patients can tolerate&#xD;
               surgery: Haemoglobin≥90g/L, Neutrophil count≥1.5×10⁹/L, Platelet count≥100×10⁹/L,&#xD;
               Aspartate or alanine aminotransferase≤5 upper limits of normal(ULN）, alkaline&#xD;
               phosphatase≤2.5 ULN, Serum albumin≥30g/L, serum creatinine&lt;1.5 ULN, International&#xD;
               normalized ratios（INR）≤2 or Prothrombin time（PT）exceed ULN≤6s, Creatinine clearance≥60&#xD;
               mL/min.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            1. Patients with extra-hepatic metastasis;&#xD;
  &#xD;
            2. Anti-cancer therapy or surgery such as radiotherapy, radiofrequency ablation in 28&#xD;
               days prior to the surgery;&#xD;
  &#xD;
            3. Clinically significant bleeding or bleeding tendencies within 3 months prior to&#xD;
               enrollment or on thrombolytic or anticoagulant therapy;&#xD;
  &#xD;
            4. Severe lung disease (eg, acute lung disease, pulmonary fibrosis that affects lung&#xD;
               function, interstitial lung disease), uncontrolled diabetes mellitus (fasting blood&#xD;
               glucose ≥10 mmol/L);&#xD;
  &#xD;
            5. There are other unsuitable candidates for clinical trials, such as mental illness or&#xD;
               alcohol dependence.&#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>Yuhua Zhang</last_name>
      <role>Study Chair</role>
      <affiliation>Zhejiang Cancer Hospital</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Chaoqun Fei</last_name>
      <phone>+086-0571-88122564</phone>
      <email>ec@zjcc.org.cn</email>
    </overall_contact>
    <location>
      <facility>
        <name>1# Banshan East Rd. Zhejiang cancer hospital</name>
        <address>
          <city>Hangzhou</city>
          <state>Zhejiang</state>
          <zip>310022</zip>
          <country>China</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Yuhua Zhang, M.D.</last_name>
        <phone>+86-0571-88128058</phone>
        <email>drzhangyuhua@126.com</email>
      </contact>
      <contact_backup>
        <last_name>Xing Chen</last_name>
        <phone>+86-19858152505</phone>
        <email>chenxing@zjcc.org.cn</email>
      </contact_backup>
    </location>
    <location_countries>
      <country>China</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 16, 2023</study_first_submitted>
    <study_first_submitted_qc>August 22, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 23, 2023</study_first_posted>
    <last_update_submitted>August 23, 2023</last_update_submitted>
    <last_update_submitted_qc>August 23, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 24, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>Zhejiang Cancer Hospital</investigator_affiliation>
      <investigator_full_name>Yuhua Zhang, MD</investigator_full_name>
      <investigator_title>Vice director of Hepatobiliary and Pancreatic Surgery, Zhejiang Cancer Hospital</investigator_title>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Liver Neoplasms</mesh_term>
    </condition_browse>
    <!-- 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/NCT06006338
  org study id: ZYH-CX-001
  nct id: NCT06006338
  lead sponsor: 
  is fda regulated drug: No
  is fda regulated device: No
  Comprehensive preoperative planning and real-time intraoperative guidance are essential
        prerequisites for achieving precise liver resection. In pursuit of this goal, the
        investigators have developed innovative 3D printed liver models utilizing a physically
        crosslinked self-healing elastomer created through the copolymerization of
        4-acryloylmorpholine (ACMO) and methoxy poly (ethylene glycol) acrylate (mPEGA). These
        printed models exhibit exceptional healing capabilities, efficiently restoring their
        structure within minutes at room temperature, and rapidly recovering within moments after
        being incised.
  
        Herein, the investigators aim to assess the viability of employing these 3D printed liver
        models as instrumental tools in designing the optimal surgical approach through an iterative
        trial-and-error methodology. Concurrently, the investigators aim to determine whether the
        integration of these 3D printed models into conventional methods (contrast-enhanced CT or
        MRI) can enhance the safety, ease, and efficiency of hepatic resection procedures.
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Device Feasibility
  masking: None (Open Label)
  measure: R0 resection rate
  time frame: 10 days
  description: The proportion of patients who achieved pathological negative surgical margin
  measure: Injury of vital vascular structures
  time frame: Immediately after the surgery.
  description: The Injury of vital vascular structures, such as portal veins or hepatic veins.
  measure: Operation time
  time frame: Immediately after the surgery.
  description: Time length (minute) between the beginning and the end of the surgery.
  measure: Blood loss
  time frame: Immediately after the surgery.
  description: The amount of lost blood (ml) in the operation.
  arm group label: Experimental arm
  arm group type: Experimental
  intervention type: Other
  intervention name: 3D Printed Model for preoperative planning
  description: Besides conventional preoperative planning based on contrast-enhanced CT/MRI, the investigator refers to a 3D printed model to determine the optimal surgical approach via a trial-and-error method. Specifically, a personalized 3D printed model is fabricated. By referring to the printed model and CT/MRI images, a preliminary surgical trace is determined. Then, a simulation surgery is performed on the model, and surgical margin and the potential injury of vital vascular structures are evaluated. This assessment leads to the adjustment of the surgical path as necessary. The refined surgical route is then validated through a second simulation surgery performed on the healed 3D model. This iterative process is repeated multiple times, allowing for a comprehensive exploration of various approaches until the optimal surgical strategy crystallizes. Next, the investigator proceeds to execute the real surgery on the participant, meticulously adhering to the determined optimal surgical approach.
  arm group label: Experimental arm
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 80 Years
  healthy volunteers: No
  last name: Yuhua Zhang
  role: Study Chair
  affiliation: Zhejiang Cancer Hospital
  last name: Chaoqun Fei
  phone: +086-0571-88122564
  email: ec@zjcc.org.cn
  facility: 
  status: Recruiting
  contact: 
  contact backup: 
  country: China
  responsible party type: Principal Investigator
  investigator affiliation: Zhejiang Cancer Hospital
  investigator full name: Yuhua Zhang, MD
  investigator title: Vice director of Hepatobiliary and Pancreatic Surgery, Zhejiang Cancer Hospital
  mesh term: Liver Neoplasms