AI and Safety in Laparoscopic Cholecystectomy: A Randomized Controlled Trial

Официальное название

Evaluating the Clinical Impact of Artificial Intelligence on Safety in Laparoscopic Cholecystectomy: A Randomized Controlled Trial

Обзор

Today, the majority of gallbladder removals surgeries are done using minimally invasive techniques through small cuts to help patients recover faster. However, these procedures are technically more challenging because surgeons have a restricted view of the patient's anatomy, which can increase the risk of serious complications. Artificial intelligence (AI) tools have been developed to guide surgeons during surgery and help them make safer decisions that reduce the risk of injury to the patient. This study will use a randomized controlled trial to compare outcomes between surgeries with AI assistance and standard procedures without AI. Primary Objective: To determine whether the AI improves surgeons' ability to achieve the Critical View of Safety, a key step for safe gallbladder removal, compared to standard procedures. Secondary Objectives: * Determine whether the AI helps the surgeon perform more safe dissections compared to the standard procedures. * Collect surgeon feedback on the use of AI during the procedure

Подробное описание

To measure the clinical impact of artificial intelligence (AI) guidance on the achievement of safety milestones in laparoscopic cholecystectomy compared to standard care, the study team will conduct a randomized controlled trial of 10 surgeons or fellows and 50 patients undergoing laparoscopic cholecystectomy procedures at two hospital sites part of the University Health Network in Toronto, Ontario, Canada (Toronto General Hospital and Toronto Western Hospital). Surgeons or fellows randomized to the intervention group (AI) will each perform 5 procedures using two AI models that provide real-time feedback to guide safe dissections and the achievement of the critical view of safety. Surgeons or fellows randomized to the control group will each perform 5 procedures using the standard care approach. Internal laparoscopic recordings will be collected from both the intervention and control groups for post-operative outcome analysis by blinded expert surgeon reviewers.

The research team will evaluate whether the use of AI during the procedure improves the achievement rate of the Critical View of Safety as compared to standard procedures.

Additionally, secondary outcomes will be assessed including the proportion of dissections that occurred above the line of safety, surgeon feedback on the use of AI during the procedure, observational notes recorded by the research coordinator present during each procedure, and 30-day post operation chart review.

Вмешательства

• Устройство Artificial Intelligence Guidance Models
  The intervention will involve the use of two artificial intelligence (AI) models to provide surgical guidance during laparoscopic cholecystectomy procedures. The AI models will provide real-time feedback based on the live surgical feed (internal patient anatomy captured by laparoscopic camera) displayed on an operating room monitor. The GoNoGoNet model identifies safe and unsafe zones of dissection. This is done by showcasing a green overlay over safe zones of dissection, and a red overlay over

Первичные конечные точки

• Critical View of Safety Achievement Rate [Срок оценки: Post-procedure through study completion (up to 1 year)]

Вторичные конечные точки (4)

• Dissections above Line of Safety [Срок оценки: Post-procedure through study completion (up to 1 year)]
• Surgeon-reported outcomes [Срок оценки: Immediately after the procedure]
• Observer-reported outcomes [Срок оценки: During the procedure]
• Post-operative chart review [Срок оценки: Up to 30 days post-procedure.]

Критерии участия

Критерии включения

• Surgeon participants: Attending surgeons or fellows that perform laparoscopic cholecystectomy at University Health Network.
• Patients participants: Adults 18 years of age and over, scheduled for laparoscopic cholecystectomy surgery.

Критерии исключения

• Surgeon participants: Anyone who is not a surgeon or fellow at University Health Network or that does not perform laparoscopic cholecystectomies.
• Patient participants: Any patient who is not having a laparoscopic cholecystectomy surgery.

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

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Двойное слепое

Основная цель

Профилактика

Центры проведения

Канада · 2 центра

• Toronto General Hospital — Toronto
• Toronto Western Hospital — Toronto

Идентификаторы

NCT: NCT07186803 · 25-5053

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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