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| Name | Class |
|---|---|
| King's College London | OTHER |
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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:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 3D Printed Models | Experimental | This cohort will consist of 54 prospective cases whereby patient-specific 3D printed models will be available to the surgeon during RARP for manipulation. |
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| 3D Virtual Models | Experimental | 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 3D Printed Models (3D printing facilities at GSTT) | Device | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Automated segmentation metrics | Automated segmentation metrics in relation to the accuracy of predicted masks of prostate gland and lesions | Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months). |
| Patient recruitment rate | Patient recruitment rate will be captured throughout the study to measure effectiveness in preparation for a follow-up randomised control trial. | Assessed throughout the study for each patient. Reported at end of study (6 months). |
| Percentage of cases that led to successful model deployment to the theatre | 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. | Assessed throughout the study for each patient. Reported at end of study (6 months). |
| Positive resection margins | Assessed after surgery and after specimen analysis. Reported at end of study (6 months). | Duration of the study |
| Measure | Description | Time Frame |
|---|---|---|
| Urinary incontinence leak outcomes | These are captured via questionnaires (ICIQ-UI) answered by patients in relation to urinary leaks. | Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months) |
| Urinary incontinence pad weights outcomes |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Alejandro Granados, PhD | Contact | 07964840608 | alejandro.granados@kcl.ac.uk |
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| ID | Term |
|---|---|
| D011471 | Prostatic Neoplasms |
| ID | Term |
|---|---|
| D005834 | Genital Neoplasms, Male |
| D014565 | Urogenital Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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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.
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| 3D Virtual Models (Innersight Labs) | Device | 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. |
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These are captured via questionnaires (EPROM) answered by patients in relation to urinary incontinence measured by pad weights. |
| Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months) |
| Urinary incontinence quality of life outcomes | These are captured via questionnaires (ICIQ-LUTS-QoL) answered by patients in relation to quality of life resulting from urinary incontinence. | Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months) |
| Erectile dysfunction functional outcomes | These are captured via questionnaires (IIEF, and erectile hardness score) answered by patients in relation to erectile dysfunction. | Assessed at 6 weeks and 3 months after surgery. Reported at end of study (6 months) |
| Surgeon's perspectives | Surgeon's perspectives on the use of patient-specific 3D printed and virtual prostate models during surgery will be captured after surgery | Assessed only once after surgery and once surgeon has participated in both arms. Reported at end of study (6 months) |
| Patient's perspectives | 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 | Assessed after surgery and after first clinical follow-up at 6 weeks. Reported at end of study (6 months). |
| Accuracy metrics for the automated segmentation of other structures | Accuracy metrics of a model that will automatically identify neurovascular bundles, urethra, and external sphincter based on manually identified masks on mp-MRI | Assessed after mp-MRI of patient is available and before surgery (RARP). Reported at end of study (6 months). |
| Surgical phase and action recognition | Surgical phase and action recognition accuracy metrics of RARP endoscopic videos to understand the actions done leading to the reported complications | Assessed and reported at end of study (6 months). |
| D005832 |
| Genital Diseases, Male |
| D000091662 | Genital Diseases |
| D000091642 | Urogenital Diseases |
| D011469 | Prostatic Diseases |
| D052801 | Male Urogenital Diseases |