AI in Endoscopic Transsphenoidal Surgery

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

Qualifiers

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

Treatments tested in this trial

  • Live intra-op AI analysis of endoscopic video feed, with output displayed on supplementary monitor

Treatment groups

30 Participants
are divided into 1 treatment group

Sponsors and collaborators

University College, London

Lead sponsor

University College London Hospitals

Collaborator