AI in Endoscopic Transsphenoidal Surgery

Официальное название

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

Обзор

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).

Вмешательства

• Устройство 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

Первичные конечные точки

• Feasibility of live AI video analysis [Срок оценки: Immediately after the intervention/procedure/surgery]

Вторичные конечные точки (3)

• Safety [Срок оценки: Perioperatively/periprocedurally (surgeon distraction, team disruption); and immediately after the intervention/procedure/surgery (output accuracy, volatility and latency)]
• Educational yield [Срок оценки: Immediately after the intervention/procedure/surgery]
• Surgical outcomes [Срок оценки: Through study completion, an average of 1 year]

Критерии участия

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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Не применимо

Модель

Одна группа

Маскирование

Открытое

Основная цель

Другое

Центры проведения

Великобритания · 1 центр

• National Hospital for Neurology and Neurosurgery — London

Публикации

• Valetopoulou A, Newall N, Khan DZ, Borg A, Bouloux PMG, Bremner F, Buchfelder M, Cudlip S, Dorward N, Drake WM, Fernandez-Miranda JC, Fleseriu M, Geltzeiler M, Ginn J, Gurnell M, Harris S, Jaunmuktane Z, Korbonits M, Kosmin M, Koulouri O, Horsfall HL, Mamelak AN, Mannion R, McBride P, McCormack AI, Melmed S, Miszkiel KA, Raverot G, Santarius T, Schwartz TH, Serrano I, Zada G, Baldeweg SE, Marcus H PMID 40702372
• Newall N, Khan DZ, Hanrahan JG, Booker J, Borg A, Davids J, Nicolosi F, Sinha S, Dorward N, Marcus HJ. High fidelity simulation of the endoscopic transsphenoidal approach: Validation of the UpSurgeOn TNS Box. Front Surg. 2022 Dec 6;9:1049685. doi: 10.3389/fsurg.2022.1049685. eCollection 2022. PMID 36561572
• Khan DZ, Newall N, Koh CH, Das A, Aapan S, Layard Horsfall H, Baldeweg SE, Bano S, Borg A, Chari A, Dorward NL, Elserius A, Giannis T, Jain A, Stoyanov D, Marcus HJ. Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching. World Neurosurg. 2024 Oct;190:e797-e808. doi: 10.1016/j.wneu.2024.07.219. Epub 2024 Aug 8. PMID 39127380
• Khan DZ, Valetopoulou A, Das A, Hanrahan JG, Williams SC, Bano S, Borg A, Dorward NL, Barbarisi S, Culshaw L, Kerr K, Luengo I, Stoyanov D, Marcus HJ. Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery. NPJ Digit Med. 2024 Nov 9;7(1):314. doi: 10.1038/s41746-024-01273-8. PMID 39521895
• Hirst A, Philippou Y, Blazeby J, Campbell B, Campbell M, Feinberg J, Rovers M, Blencowe N, Pennell C, Quinn T, Rogers W, Cook J, Kolias AG, Agha R, Dahm P, Sedrakyan A, McCulloch P. No Surgical Innovation Without Evaluation: Evolution and Further Development of the IDEAL Framework and Recommendations. Ann Surg. 2019 Feb;269(2):211-220. doi: 10.1097/SLA.0000000000002794. PMID 29697448

Идентификаторы

NCT: NCT07568366 · 127474

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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