AI in Endoscopic Transsphenoidal Surgery
ConditionPituitary Adenoma
Trial statusNot yet recruiting
Trial phaseEarly Phase 1
Trial typeInterventional
Biological sexAll
Age18+
SponsorUniversity College, London
About this trial
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).
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Adult patients (above the age of 18 years old)
Undergoing endoscopic transsphenoidal surgery
Able to provide consent
Disqualifiers
Patients less than 18 years of age
Undergoing transcranial surgery or microscopic transsphenoidal surgery
Unable to provide consent e.g., cannot understand, mental illness, or later withdrawing consent
Trial design
Design model
Single group
Treatments tested in this trial
Live intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor
DeviceLive intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor
Treatment groups
30 Participants
are divided into 1 treatment groupGroup A: Intervention ArmExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
Feasibility of live AI video analysis
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).
Time frame
Immediately after the intervention/procedure/surgerySecondary outcomes
1
Safety
* 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.
Time frame
Perioperatively/periprocedurally (surgeon distraction, team disruption); and immediately after the intervention/procedure/surgery (output accuracy, volatility and latency)2
Educational yield
To evaluate the utility of the platform for educational purposes. Via structured educational yield questionnaire of surgeons involved in each case
Time frame
Immediately after the intervention/procedure/surgery3
Surgical outcomes
* 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
Time frame
Through study completion, an average of 1 yearSponsors and contacts
Click on the lead sponsor to view all of their trials.
University College, London
Lead sponsor
University College London Hospitals
Collaborator
Source ClinicalTrials.gov
This trial is not recruiting at the moment. You can still explore other options: