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/NCT05964660</url>
    </required_header>
    <id_info>
      <org_study_id>MATRIX-VT</org_study_id>
      <nct_id>NCT05964660</nct_id>
    </id_info>
    <brief_title>Echocardiography-based Motion Integration and Management for Substrate Characterization and STAR Therapy in Ventricular Tachycardias</brief_title>
    <acronym>MATRIX-VT</acronym>
    <official_title>New 3D-echocardiography-based Motion Integration and mAnagement for subsTrate characteRisation and Stereotactic Arrhythmia radIoablation tX in Ventricular Tachycardias- the MATRIX-VT Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University of Luebeck</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Institute for Robotics and Cognitive Systems, University of Luebeck</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>University of Luebeck</source>
    <oversight_info>
      <has_dmc>No</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>
        Prospective, observational, single center, pilot study to analyze the feasibility of motion&#xD;
        and structural data integration in patients with ventricular arrhythmia by means of&#xD;
        artificial intelligence for improved arrhythmogenic substrate characterization and motion&#xD;
        management during stereotactic arrhythmia radioablation.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        This is a prospective, observational, single center, pilot study. Data from preprocedural&#xD;
        contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic&#xD;
        echocardiography of patients receiving catheter ablation for ventricular arrhythmia will be&#xD;
        analyzed by means of artificial intelligence in order to better characterize the ventricular&#xD;
        arrhythmogenic substrate and to improve the definition methods of the planning target volume&#xD;
        during the stereotactic arrhythmia radioablation therapy by integrating the motion data into&#xD;
        volume demarcation.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">August 2023</start_date>
    <completion_date type="Anticipated">June 2024</completion_date>
    <primary_completion_date type="Anticipated">June 2024</primary_completion_date>
    <study_type>Observational</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>
    <primary_outcome>
      <measure>Feasibility of algorithm training to achieve improved arrhythmogenic substrate characterization</measure>
      <time_frame>1 month after complete data collection</time_frame>
      <description>The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the ventricular arrhythmogenic substrate in patients exhibiting ventricular arrhythmias.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Feasibility of algorithm training to improve the planning target volume definition for stereotactic arrhythmia radioablation therapy</measure>
      <time_frame>1 month after complete data collection</time_frame>
      <description>The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the planning target volume for stereotactic arrhythmia radioablation therapy</description>
    </primary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">20</enrollment>
    <condition>Ventricular Arrythmia</condition>
    <arm_group>
      <arm_group_label>VT Patients</arm_group_label>
      <description>Patients with indication for catheter ablation of ventricular arrhythmia and preprocedural contrast-enhanced cardiac computed tomography for cardiac structure characterization.</description>
    </arm_group>
    <eligibility>
      <study_pop>
        <textblock>
          A total of 20 patients with indication for catheter ablation of ventricular arrhythmia (VA)&#xD;
          (ventricular tachycardia (VT), ventricular fibrillation (VF), premature ventricular&#xD;
          contraction (PVC)) and for preprocedural contract-enhanced cardiac computed tomography (CT)&#xD;
          for cardiac structure characterization will be prospectively enrolled in the study. The&#xD;
          therapeutic approach follows the current clinical standard.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Age ≥ 18 years&#xD;
  &#xD;
            -  Indication for catheter ablation of ventricular arrhythmias (ventricular fibrillation,&#xD;
               ventricular tachycardia, premature ventricular contractions)&#xD;
  &#xD;
            -  Indication for preprocedural contrast-enhanced cardiac computed tomography for cardiac&#xD;
               structure characterization&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Platelet count &lt; 100,000 cells/mm3&#xD;
  &#xD;
            -  BMI &gt; 45 kg/m2 or &lt; 18 kg/m2&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>100 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <location>
      <facility>
        <name>Klinik für Rhythmologie</name>
        <address>
          <city>Luebeck</city>
          <state>Schleswig-Holstein</state>
          <zip>23538</zip>
          <country>Germany</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>Germany</country>
    </location_countries>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 19, 2023</study_first_submitted>
    <study_first_submitted_qc>July 27, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">July 28, 2023</study_first_posted>
    <last_update_submitted>July 27, 2023</last_update_submitted>
    <last_update_submitted_qc>July 27, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">July 28, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>University of Luebeck</investigator_affiliation>
      <investigator_full_name>Prof. Roland Richard Tilz</investigator_full_name>
      <investigator_title>Professor Dr. med.univ.</investigator_title>
    </responsible_party>
    <keyword>Ventricular arrhythmia</keyword>
    <keyword>Ventricular tachycardia</keyword>
    <keyword>Stereotactic arrhythmia radioablation</keyword>
    <keyword>Artificial intelligence</keyword>
    <keyword>Motion management</keyword>
    <keyword>Motion integration</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Arrhythmias, Cardiac</mesh_term>
      <mesh_term>Tachycardia</mesh_term>
      <mesh_term>Tachycardia, Ventricular</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/NCT05964660
  org study id: MATRIX-VT
  nct id: NCT05964660
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  Prospective, observational, single center, pilot study to analyze the feasibility of motion
        and structural data integration in patients with ventricular arrhythmia by means of
        artificial intelligence for improved arrhythmogenic substrate characterization and motion
        management during stereotactic arrhythmia radioablation.
  This is a prospective, observational, single center, pilot study. Data from preprocedural
        contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic
        echocardiography of patients receiving catheter ablation for ventricular arrhythmia will be
        analyzed by means of artificial intelligence in order to better characterize the ventricular
        arrhythmogenic substrate and to improve the definition methods of the planning target volume
        during the stereotactic arrhythmia radioablation therapy by integrating the motion data into
        volume demarcation.
  observational model: Case-Only
  time perspective: Prospective
  measure: Feasibility of algorithm training to achieve improved arrhythmogenic substrate characterization
  time frame: 1 month after complete data collection
  description: The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the ventricular arrhythmogenic substrate in patients exhibiting ventricular arrhythmias.
  measure: Feasibility of algorithm training to improve the planning target volume definition for stereotactic arrhythmia radioablation therapy
  time frame: 1 month after complete data collection
  description: The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the planning target volume for stereotactic arrhythmia radioablation therapy
  arm group label: VT Patients
  description: Patients with indication for catheter ablation of ventricular arrhythmia and preprocedural contrast-enhanced cardiac computed tomography for cardiac structure characterization.
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 100 Years
  healthy volunteers: Accepts Healthy Volunteers
  facility: 
  country: Germany
  responsible party type: Principal Investigator
  investigator affiliation: University of Luebeck
  investigator full name: Prof. Roland Richard Tilz
  investigator title: Professor Dr. med.univ.
  mesh term: Arrhythmias, Cardiac
  mesh term: Tachycardia
  mesh term: Tachycardia, Ventricular
  sharing ipd: No