Ignite Creation Date:
2025-12-25 @ 5:01 AM
Ignite Modification Date:
2025-12-26 @ 4:02 AM
Study NCT ID:
NCT05982418
Status:
UNKNOWN
Last Update Posted:
2023-08-08
First Post:
2023-07-20
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Improvement of RARP Outcomes Via 3D Printed/Virtual Prostate Models
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011471', 'term': 'Prostatic Neoplasms'}], 'ancestors': [{'id': 'D005834', 'term': 'Genital Neoplasms, Male'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D005832', 'term': 'Genital Diseases, Male'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D011469', 'term': 'Prostatic Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NON_RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL', 'interventionModelDescription': '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.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 162}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2023-07-31', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-12', 'completionDateStruct': {'date': '2024-01-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-08-01', 'studyFirstSubmitDate': '2023-07-20', 'studyFirstSubmitQcDate': '2023-08-01', 'lastUpdatePostDateStruct': {'date': '2023-08-08', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-08-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-01-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Automated segmentation metrics', 'timeFrame': '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', 'timeFrame': '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', 'timeFrame': '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', 'timeFrame': 'Duration of the study', 'description': 'Assessed after surgery and after specimen analysis. Reported at end of study (6 months).'}], 'secondaryOutcomes': [{'measure': 'Urinary incontinence leak outcomes', 'timeFrame': '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', 'timeFrame': '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', 'timeFrame': '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', 'timeFrame': '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", 'timeFrame': '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", 'timeFrame': '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', 'timeFrame': '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', 'timeFrame': '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'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Prostate Cancer']}, 'descriptionModule': {'briefSummary': '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.', 'detailedDescription': "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.\n\nPrimary 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.\n\nSecondary outcomes Study the effect of two-intervention arms have on functional outcomes, surgeons' and patients' perspectives on using 3D prostate models.\n\nA total of 162 cases will be considered in this feasibility study stratified into 3 cohorts:\n\n* 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.\n* 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.\n* 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."}, 'eligibilityModule': {'sex': 'MALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Eligible for RARP after assessment of mp-MRI during multi-disciplinary team meetings at Guy's Hospital\n* T2b-T3 prostate cancer patients\n* Gleason's score\\>=3+4 .\n\nExclusion Criteria:\n\n* prior treatment for prostate cancer\n* patients with pre-existing urinary incontinence problems\n* patients where mp-MRI scans are not possible\n* patients participating in other studies investigating functional outcomes after surgery will be excluded. This is to avoid other studies influencing our secondary endpoints."}, 'identificationModule': {'nctId': 'NCT05982418', 'acronym': 'RARP-3D', 'briefTitle': 'Improvement of RARP Outcomes Via 3D Printed/Virtual Prostate Models', 'organization': {'class': 'OTHER', 'fullName': "Guy's and St Thomas' NHS Foundation Trust"}, 'officialTitle': 'Improvement of Robotic-assisted Radical Prostatectomy (RARP) Outcomes Via Automatedly Segmented 3D Printed and Virtual Prostate Models: a Feasibility Study', 'orgStudyIdInfo': {'id': '152847'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': '3D Printed Models', '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.', 'interventionNames': ['Device: 3D Printed Models (3D printing facilities at GSTT)']}, {'type': 'EXPERIMENTAL', 'label': '3D Virtual Models', '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.', 'interventionNames': ['Device: 3D Virtual Models (Innersight Labs)']}], 'interventions': [{'name': '3D Printed Models (3D printing facilities at GSTT)', 'type': 'DEVICE', '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.', 'armGroupLabels': ['3D Printed Models']}, {'name': '3D Virtual Models (Innersight Labs)', 'type': 'DEVICE', '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.', 'armGroupLabels': ['3D Virtual Models']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Alejandro Granados, PhD', 'role': 'CONTACT', 'email': 'alejandro.granados@kcl.ac.uk', 'phone': '07964840608'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': "Guy's and St Thomas' NHS Foundation Trust", 'class': 'OTHER'}, 'collaborators': [{'name': "King's College London", 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}