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Robotic surgery is now widely adopted in urology, and the da Vinci Single-Port (SP) platform enables complex procedures through a single multichannel incision, with favorable perioperative and outpatient outcomes in selected patients. However, single-port access and AI implementation also introduce unique ergonomic and cognitive challenges for surgeons and operating room staff. Quantifying intraoperative workload has become crucial to understand how new technologies affect performance, safety and training.
The National Aeronautics and Space Administration Task Load Index (NASA-TLX) is a validated multidimensional instrument for subjective workload assessment and has been increasingly applied to surgical and specifically urologic practice. In parallel, augmented reality and artificial intelligence (AI) are emerging as tools to enhance intraoperative visualization and anatomical understanding during robot-assisted urologic procedures. The da Vinci TilePro multi-image display already allows simultaneous viewing of auxiliary imaging, but evidence on how real-time AI overlays integrated via TilePro affect cognitive workload in single-port urologic surgery is lacking. This prospective pilot study evaluates the impact of different TilePro visualization strategies on surgeon and bedside assistant workload, measured by weighted NASA-TLX scores, and explores associations with operative metrics in elective SP urologic procedures.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Continuous AI visualization | Active Comparator | the AI overlay was displayed continuously throughout the entire surgical procedure. |
|
| Intermittent AI visualization | Active Comparator | The operator selectively activated the AI visualization during key surgical phases according to preference |
|
| No AI visualization | No Intervention | No AI visualization use |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Yolo | Other | The AI system employed in this study was based on a convolutional neural network (CNN) architecture implemented via the YOLO (You Only Look Once) framework, specifically designed for real-time instance segmentation of intraoperative anatomical structures. |
| Measure | Description | Time Frame |
|---|---|---|
| NASA Task Load Index (NASA-TLX) questionnaire | The National Aeronautics and Space Administration Task Load Index (NASA-TLX) is a validated multidimensional instrument for subjective workload assessment and has been increasingly applied to surgical and specifically urologic practice | 30 minutes after completing the surgey |
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Inclusion Criteria: Urology surgeon or urology resident -
Exclusion Criteria: not urology surgeon or not urology resident
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UI Health | Chicago | Illinois | 60612 | United States |
The NASA Task Load Index (NASA-TLX) questionnaire administered within 30 minutes
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The urology single port surgeries are categorized into three AI visualization modes according to the use of the TilePro display:
Continuous AI visualization (n = 10): the AI overlay was displayed continuously throughout the entire surgical procedure.
Intermittent AI visualization (n = 10): the first operator selectively activated the AI visualization during key surgical phases according to preference.
Control cases with no AI (n = 10): TilePro off and a full-screen image of the operative field.
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| ID | Term |
|---|---|
| D000098432 | Detection Algorithms |
| ID | Term |
|---|---|
| D000465 | Algorithms |
| D055641 | Mathematical Concepts |
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