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/NCT05982418</url>
    </required_header>
    <id_info>
      <org_study_id>152847</org_study_id>
      <nct_id>NCT05982418</nct_id>
    </id_info>
    <brief_title>Improvement of RARP Outcomes Via 3D Printed/Virtual Prostate Models</brief_title>
    <acronym>RARP-3D</acronym>
    <official_title>Improvement of Robotic-assisted Radical Prostatectomy (RARP) Outcomes Via Automatedly Segmented 3D Printed and Virtual Prostate Models: a Feasibility Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Guy's and St Thomas' NHS Foundation Trust</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>King's College London</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Guy's and St Thomas' NHS Foundation 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>
        Study the effect 3D printed or 3D virtual prostate models of a patient, when manipulated by&#xD;
        surgeons during RARP, has on positive surgical margins and functional outcomes of patients.&#xD;
        Our main hypothesis is that there is a reduction of positive resection margins and functional&#xD;
        outcomes of patients undergoing RARP when surgeons are presented with 3D printed or 3D&#xD;
        virtual patient-specific prostate models during surgery. Specifically, we hypothesize that&#xD;
        the anatomical knowledge of surgeons that results from the manipulation of 3D printed/virtual&#xD;
        models constructed from automated segmentations reduces positive resection margins and&#xD;
        functional outcomes.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        This is a parallel group research feasibility study consisting of two intervention arms (3D&#xD;
        printed and 3D virtual models) and a control group (standard practice). Intervention groups&#xD;
        are prospective; control group is retrospective. Prospective patients, complying with the&#xD;
        inclusion criteria, will randomly be allocated to only one intervention group.&#xD;
  &#xD;
        Primary outcomes Study the effect of two-intervention arms (3D printed and virtual prostate&#xD;
        models) have on the improvement of positive resection margins after RARP, validate the&#xD;
        accuracy of automated methods when identifying masks of the prostate gland and, cancer&#xD;
        lesions urethra, neurovascular bundles, and external sphincter, and validate the&#xD;
        effectiveness of an automated deployment pipeline with the goal of setting groundwork in&#xD;
        preparation for a randomise control trial in a subsequent study.&#xD;
  &#xD;
        Secondary outcomes Study the effect of two-intervention arms have on functional outcomes,&#xD;
        surgeons' and patients' perspectives on using 3D prostate models.&#xD;
  &#xD;
        A total of 162 cases will be considered in this feasibility study stratified into 3 cohorts:&#xD;
  &#xD;
          -  Control group. The control group will consist of 54 retrospective case-matched dataset&#xD;
             whereby mp-MRI, positive resection margins, and functional outcomes will be collected&#xD;
             and used as a baseline. Automated segmentation of prostate gland and lesions will be&#xD;
             done on mp-MRI.&#xD;
  &#xD;
          -  Intervention arm 1 - 3D printed models. This cohort will consist of 54 prospective cases&#xD;
             whereby patient-specific 3D printed models will be available to the surgeon during RARP&#xD;
             for manipulation.&#xD;
  &#xD;
          -  Intervention arm 2 - 3D virtual models. This cohort will consist of 54 prospective cases&#xD;
             whereby 3D virtual models will be available to the surgeon during RARP for manipulation&#xD;
             using Innersight Labs platform.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">July 31, 2023</start_date>
    <completion_date type="Anticipated">January 31, 2024</completion_date>
    <primary_completion_date type="Anticipated">January 31, 2024</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>Non-Randomized</allocation>
      <intervention_model>Parallel Assignment</intervention_model>
      <intervention_model_description>A total of 108 patients will be recruited prospectively, i.e. 54 patients for intervention arm 1 (3D printed models), and 54 patients for intervention arm 2 (3D virtual models). An additional set of 54 patients will be obtained retrospectively.</intervention_model_description>
      <primary_purpose>Treatment</primary_purpose>
      <masking>Single (Participant)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Automated segmentation metrics</measure>
      <time_frame>Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months).</time_frame>
      <description>Automated segmentation metrics in relation to the accuracy of predicted masks of prostate gland and lesions</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Patient recruitment rate</measure>
      <time_frame>Assessed throughout the study for each patient. Reported at end of study (6 months).</time_frame>
      <description>Patient recruitment rate will be captured throughout the study to measure effectiveness in preparation for a follow-up randomised control trial.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Percentage of cases that led to successful model deployment to the theatre</measure>
      <time_frame>Assessed throughout the study for each patient. Reported at end of study (6 months).</time_frame>
      <description>Percentage of cases that led to successful model deployment to the theatre will be captured throughout the study to measure effectiveness in preparation for a follow-up randomised control trial.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Positive resection margins</measure>
      <time_frame>Duration of the study</time_frame>
      <description>Assessed after surgery and after specimen analysis. Reported at end of study (6 months).</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Urinary incontinence leak outcomes</measure>
      <time_frame>Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)</time_frame>
      <description>These are captured via questionnaires (ICIQ-UI) answered by patients in relation to urinary leaks.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Urinary incontinence pad weights outcomes</measure>
      <time_frame>Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)</time_frame>
      <description>These are captured via questionnaires (EPROM) answered by patients in relation to urinary incontinence measured by pad weights.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Urinary incontinence quality of life outcomes</measure>
      <time_frame>Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)</time_frame>
      <description>These are captured via questionnaires (ICIQ-LUTS-QoL) answered by patients in relation to quality of life resulting from urinary incontinence.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Erectile dysfunction functional outcomes</measure>
      <time_frame>Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)</time_frame>
      <description>These are captured via questionnaires (IIEF, and erectile hardness score) answered by patients in relation to erectile dysfunction.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Surgeon's perspectives</measure>
      <time_frame>Assessed only once after surgery and once surgeon has participated in both arms. Reported at end of study (6 months)</time_frame>
      <description>Surgeon's perspectives on the use of patient-specific 3D printed and virtual prostate models during surgery will be captured after surgery</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Patient's perspectives</measure>
      <time_frame>Assessed after surgery and after first clinical follow-up at 6 weeks. Reported at end of study (6 months).</time_frame>
      <description>Patient's perspectives on the use of their patient-specific 3D printed and virtual prostate model after surgery will be captured after surgery during clinic review</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Accuracy metrics for the automated segmentation of other structures</measure>
      <time_frame>Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months).</time_frame>
      <description>Accuracy metrics of a model that will automatically identify neurovascular bundles, urethra, and external sphincter based on manually identified masks on mp-MRI</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Surgical phase and action recognition</measure>
      <time_frame>Assessed and reported at end of study (6 months).</time_frame>
      <description>Surgical phase and action recognition accuracy metrics of RARP endoscopic videos to understand the actions done leading to the reported complications</description>
    </secondary_outcome>
    <number_of_arms>2</number_of_arms>
    <enrollment type="Anticipated">162</enrollment>
    <condition>Prostate Cancer</condition>
    <arm_group>
      <arm_group_label>3D Printed Models</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>This cohort will consist of 54 prospective cases whereby patient-specific 3D printed models will be available to the surgeon during RARP for manipulation.</description>
    </arm_group>
    <arm_group>
      <arm_group_label>3D Virtual Models</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>This cohort will consist of 54 prospective cases whereby 3D virtual models will be available to the surgeon during RARP for manipulation using Innersight Labs platform.</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>3D Printed Models (3D printing facilities at GSTT)</intervention_name>
      <description>3D patient-specific printed models are given to the surgeon before the start of RARP on a given patient. These 3D models are generated using automatic segmentation in MONAI followed by validation by a radiologist, and then post-processed for 3D printing.</description>
      <arm_group_label>3D Printed Models</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>3D Virtual Models (Innersight Labs)</intervention_name>
      <description>3D patient-specific virtual models loaded into Innersight Labs platform are given to the surgeon before the start of RARP on a given patient. These 3D models are generated using automatic segmentation in MONAI followed by validation by a radiologist, and then post-processed for 3D visualisation.</description>
      <arm_group_label>3D Virtual Models</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Eligible for RARP after assessment of mp-MRI during multi-disciplinary team meetings&#xD;
               at Guy's Hospital&#xD;
  &#xD;
            -  T2b-T3 prostate cancer patients&#xD;
  &#xD;
            -  Gleason's score&gt;=3+4 .&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  prior treatment for prostate cancer&#xD;
  &#xD;
            -  patients with pre-existing urinary incontinence problems&#xD;
  &#xD;
            -  patients where mp-MRI scans are not possible&#xD;
  &#xD;
            -  patients participating in other studies investigating functional outcomes after&#xD;
               surgery will be excluded. This is to avoid other studies influencing our secondary&#xD;
               endpoints.&#xD;
        </textblock>
      </criteria>
      <gender>Male</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_contact>
      <last_name>Alejandro Granados, PhD</last_name>
      <phone>07964840608</phone>
      <email>alejandro.granados@kcl.ac.uk</email>
    </overall_contact>
    <verification_date>December 2022</verification_date>
    <study_first_submitted>July 20, 2023</study_first_submitted>
    <study_first_submitted_qc>August 1, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 8, 2023</study_first_posted>
    <last_update_submitted>August 1, 2023</last_update_submitted>
    <last_update_submitted_qc>August 1, 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>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Prostatic Neoplasms</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/NCT05982418
  org study id: 152847
  nct id: NCT05982418
  lead sponsor: 
  collaborator: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  Study the effect 3D printed or 3D virtual prostate models of a patient, when manipulated by
        surgeons during RARP, has on positive surgical margins and functional outcomes of patients.
        Our main hypothesis is that there is a reduction of positive resection margins and functional
        outcomes of patients undergoing RARP when surgeons are presented with 3D printed or 3D
        virtual patient-specific prostate models during surgery. Specifically, we hypothesize that
        the anatomical knowledge of surgeons that results from the manipulation of 3D printed/virtual
        models constructed from automated segmentations reduces positive resection margins and
        functional outcomes.
  This is a parallel group research feasibility study consisting of two intervention arms (3D
        printed and 3D virtual models) and a control group (standard practice). Intervention groups
        are prospective; control group is retrospective. Prospective patients, complying with the
        inclusion criteria, will randomly be allocated to only one intervention group.
  
        Primary outcomes Study the effect of two-intervention arms (3D printed and virtual prostate
        models) have on the improvement of positive resection margins after RARP, validate the
        accuracy of automated methods when identifying masks of the prostate gland and, cancer
        lesions urethra, neurovascular bundles, and external sphincter, and validate the
        effectiveness of an automated deployment pipeline with the goal of setting groundwork in
        preparation for a randomise control trial in a subsequent study.
  
        Secondary outcomes Study the effect of two-intervention arms have on functional outcomes,
        surgeons' and patients' perspectives on using 3D prostate models.
  
        A total of 162 cases will be considered in this feasibility study stratified into 3 cohorts:
  
          -  Control group. The control group will consist of 54 retrospective case-matched dataset
             whereby mp-MRI, positive resection margins, and functional outcomes will be collected
             and used as a baseline. Automated segmentation of prostate gland and lesions will be
             done on mp-MRI.
  
          -  Intervention arm 1 - 3D printed models. This cohort will consist of 54 prospective cases
             whereby patient-specific 3D printed models will be available to the surgeon during RARP
             for manipulation.
  
          -  Intervention arm 2 - 3D virtual models. This cohort will consist of 54 prospective cases
             whereby 3D virtual models will be available to the surgeon during RARP for manipulation
             using Innersight Labs platform.
  allocation: Non-Randomized
  intervention model: Parallel Assignment
  intervention model description: A total of 108 patients will be recruited prospectively, i.e. 54 patients for intervention arm 1 (3D printed models), and 54 patients for intervention arm 2 (3D virtual models). An additional set of 54 patients will be obtained retrospectively.
  primary purpose: Treatment
  masking: Single (Participant)
  measure: Automated segmentation metrics
  time frame: Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months).
  description: Automated segmentation metrics in relation to the accuracy of predicted masks of prostate gland and lesions
  measure: Patient recruitment rate
  time frame: Assessed throughout the study for each patient. Reported at end of study (6 months).
  description: Patient recruitment rate will be captured throughout the study to measure effectiveness in preparation for a follow-up randomised control trial.
  measure: Percentage of cases that led to successful model deployment to the theatre
  time frame: Assessed throughout the study for each patient. Reported at end of study (6 months).
  description: Percentage of cases that led to successful model deployment to the theatre will be captured throughout the study to measure effectiveness in preparation for a follow-up randomised control trial.
  measure: Positive resection margins
  time frame: Duration of the study
  description: Assessed after surgery and after specimen analysis. Reported at end of study (6 months).
  measure: Urinary incontinence leak outcomes
  time frame: Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)
  description: These are captured via questionnaires (ICIQ-UI) answered by patients in relation to urinary leaks.
  measure: Urinary incontinence pad weights outcomes
  time frame: Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)
  description: These are captured via questionnaires (EPROM) answered by patients in relation to urinary incontinence measured by pad weights.
  measure: Urinary incontinence quality of life outcomes
  time frame: Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)
  description: These are captured via questionnaires (ICIQ-LUTS-QoL) answered by patients in relation to quality of life resulting from urinary incontinence.
  measure: Erectile dysfunction functional outcomes
  time frame: Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months)
  description: These are captured via questionnaires (IIEF, and erectile hardness score) answered by patients in relation to erectile dysfunction.
  measure: Surgeon's perspectives
  time frame: Assessed only once after surgery and once surgeon has participated in both arms. Reported at end of study (6 months)
  description: Surgeon's perspectives on the use of patient-specific 3D printed and virtual prostate models during surgery will be captured after surgery
  measure: Patient's perspectives
  time frame: Assessed after surgery and after first clinical follow-up at 6 weeks. Reported at end of study (6 months).
  description: Patient's perspectives on the use of their patient-specific 3D printed and virtual prostate model after surgery will be captured after surgery during clinic review
  measure: Accuracy metrics for the automated segmentation of other structures
  time frame: Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months).
  description: Accuracy metrics of a model that will automatically identify neurovascular bundles, urethra, and external sphincter based on manually identified masks on mp-MRI
  measure: Surgical phase and action recognition
  time frame: Assessed and reported at end of study (6 months).
  description: Surgical phase and action recognition accuracy metrics of RARP endoscopic videos to understand the actions done leading to the reported complications
  arm group label: 3D Printed Models
  arm group type: Experimental
  description: This cohort will consist of 54 prospective cases whereby patient-specific 3D printed models will be available to the surgeon during RARP for manipulation.
  arm group label: 3D Virtual Models
  arm group type: Experimental
  description: This cohort will consist of 54 prospective cases whereby 3D virtual models will be available to the surgeon during RARP for manipulation using Innersight Labs platform.
  intervention type: Device
  intervention name: 3D Printed Models (3D printing facilities at GSTT)
  description: 3D patient-specific printed models are given to the surgeon before the start of RARP on a given patient. These 3D models are generated using automatic segmentation in MONAI followed by validation by a radiologist, and then post-processed for 3D printing.
  arm group label: 3D Printed Models
  intervention type: Device
  intervention name: 3D Virtual Models (Innersight Labs)
  description: 3D patient-specific virtual models loaded into Innersight Labs platform are given to the surgeon before the start of RARP on a given patient. These 3D models are generated using automatic segmentation in MONAI followed by validation by a radiologist, and then post-processed for 3D visualisation.
  arm group label: 3D Virtual Models
  criteria: 
  gender: Male
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Alejandro Granados, PhD
  phone: 07964840608
  email: alejandro.granados@kcl.ac.uk
  responsible party type: Sponsor
  mesh term: Prostatic Neoplasms
  sharing ipd: No