Pituitary Adenoma
Conditions
Keywords
Artificial intelligence, computer vision, surgical technology, technology translation, pituitary adenoma, endoscopic surgery
Brief summary
This study focuses on bringing artificial intelligence into the operating room to assist with pituitary tumour surgeries performed through the nose. These procedures are technically demanding, and training new surgeons is often inconsistent. To address this, researchers at the National Hospital for Neurology and Neurosurgery are testing AI systems that "watch" surgical videos in real-time to identify anatomy, instruments, and the specific phase of the operation. The core goal of the prospective trial is to improve education and team coordination without interfering with the surgery itself. The AI displays its analysis on tablets positioned for the surgical residents and nurses, rather than the lead surgeon. This setup allows the team to follow the procedure's progress, key anatomy and anticipate next steps without the surgeon needing to stop and explain. Because hospital internet can be unreliable, the study is prioritizing specialized hardware from NVIDIA that processes data locally. This "edge computing" approach ensures the AI is fast and doesn't require a live cloud connection to function. This trial will assess the device feasibility (IDEAL Stage 1 study, \ 6 cases), followed by early safety and system technical refinement (IDEAL 2a study, \ 20-30 cases).
Interventions
DEVICELive intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor
Live intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor
Sponsors
University College, London
University College London Hospitals
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE
Intervention model description
Staged single centre non-comparative case series - IDEAL Stage 1 and 2a, evaluating feasibility and early safety respectively
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
The inclusion criteria will be: 1. Adult patients (above the age of 18 years old) 2. Undergoing endoscopic transsphenoidal surgery 3. Able to provide consent The
Exclusion criteria
will be: 1. Patients less than 18 years of age 2. Undergoing transcranial surgery or microscopic transsphenoidal surgery 3. Unable to provide consent e.g., cannot understand, mental illness, or later withdrawing consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility of live AI video analysis | Immediately after the intervention/procedure/surgery | The primary objective of this study is to evaluate the feasibility of the TouchSurgery platform or NVIDIA AGx/IGx based platforms for prospective AI-based surgical video analysis (via observation, validated implementation assessment and human factors questionnaires; and semi-structured interviews of surgical team members). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Safety | Perioperatively/periprocedurally (surgeon distraction, team disruption); and immediately after the intervention/procedure/surgery (output accuracy, volatility and latency) | * observation for operating surgeon distraction: recorded as discrete instances of unplanned disruption of primary surgeon workflow per surgery, as observed by observer from research team * wider surgical team workflow disruption : recorded as discrete instances of unplanned disruption of wider surgical team workflow per surgery, as observed by observer from research team * AI output inaccuracy and volatility: measured via sampling of 3-5x clips (30-60sec at 5fps) during which surgical scene is static (i.e. during routine anatomical verification checks), and calculating DICE scores (vs groundtruth segmentations) for accuracy estimation and DICE/sec for volatility estimatipon. * AI output latency: measured as discrete instances of unacceptably elevated latency (\>200ms) of the AI output display vs the primary direct surgical feed, as observed by observer from research team. |
| Educational yield | Immediately after the intervention/procedure/surgery | To evaluate the utility of the platform for educational purposes. Via structured educational yield questionnaire of surgeons involved in each case |
| Surgical outcomes | Through study completion, an average of 1 year | * Surgical performance vs matched cohort: measured via modified OSATS on independent surgical video review * Surgical outcomes vs matched cohort: measured via comparative analysis of standardised outcome set |
Countries
United Kingdom
Outcome results
None listed