AI in Endoscopic Transsphenoidal Surgery

April 30, 2026 updated by: University College, London

The Application of Artificial Intelligence to Patients Undergoing Endoscopic Transsphenoidal Surgery: a Single-site Prospective Feasibility and Exploratory Study (IDEAL Stage 1 and 2a)

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).

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

30

Phase

  • Early Phase 1

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United Kingdom
      • London, United Kingdom
        • National Hospital For Neurology and Neurosurgery

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention Arm
Device: Live 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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Feasibility of live AI video analysis
Time Frame: 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).
Immediately after the intervention/procedure/surgery

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Safety
Time Frame: 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.
Perioperatively/periprocedurally (surgeon distraction, team disruption); and immediately after the intervention/procedure/surgery (output accuracy, volatility and latency)
Educational yield
Time Frame: 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
Immediately after the intervention/procedure/surgery
Surgical outcomes
Time Frame: 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
Through study completion, an average of 1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University College, London

Collaborators

University College London Hospitals

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

June 1, 2026

Primary Completion (Estimated)

August 1, 2028

Study Completion (Estimated)

January 31, 2029

Study Registration Dates

First Submitted

March 30, 2026

First Submitted That Met QC Criteria

April 30, 2026

First Posted (Actual)

May 5, 2026

Study Record Updates

Last Update Posted (Actual)

May 5, 2026

Last Update Submitted That Met QC Criteria

April 30, 2026

Last Verified

April 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 127474

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Available upon formal reasonable request

IPD Sharing Time Frame

To be specific in data transfer agreement

IPD Sharing Access Criteria

To be specific in data transfer agreement

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • ICF
  • CSR

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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