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NCT Number: NCT07568366

AI in Endoscopic Transsphenoidal Surgery

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).

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Key information

Conditions

Pituitary Adenoma Brain Diseases Brain Neoplasms Central Nervous System Diseases Central Nervous System Neoplasms Endocrine Gland Neoplasms Endocrine System Diseases Hypothalamic Diseases Hypothalamic Neoplasms Neoplasms Neoplasms by Site Nervous System Diseases Nervous System Neoplasms Pituitary Diseases Pituitary Neoplasms Supratentorial Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Early Phase 1

Primary location

National Hospital for Neurology and Neurosurgery

London, United Kingdom

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

The inclusion criteria will be:

  • Adult patients (above the age of 18 years old)
  • Undergoing endoscopic transsphenoidal surgery
  • Able to provide consent

The exclusion criteria will be:

  • 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

Treatment and study plan

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

Device

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

Primary outcomes

  1. 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).

Secondary outcomes

  1. 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.

  2. 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

  3. 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

Sponsors and collaborators

Lead sponsor

University College, London

Other

Collaborators

  • University College London Hospitals

Registry information

Official study title

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

Important dates

Study start
2026
Primary completion
2028
Study completion
2029
First posted
May 5, 2026
Registry last updated
May 5, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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