Feasibility and Utility of Artificial Intelligence (AI) / Machine Learning (ML) - Driven Advanced Intraoperative Visualization and Identification of Critical Anatomic Structures and Procedural Phases in Laparoscopic Cholecystectomy
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 120
- 试验地点
- 2
- 主要终点
- Precision and accuracy
研究概览
简要总结
The goal of this study is to evaluate the utility and efficacy of an artificial intelligence (AI) model at identifying structures and phases of surgery compared to traditional white light assessment by trained surgeons. Surgeons will perform the procedure in their standard practice, while the AI model analyzes data from the laparoscopic camera. Surgeons will be asked to audibly state when they identify structures and enter different phases of the surgical procedure.
The AI will not alter the surgeon's view or be visible to the surgeon, and the surgeon will perform the procedure in the exact same fashion as they typically do.
详细描述
Bile duct injury (BDI) during cholecystectomy is a serious surgical complication with increased risk of early death, serious ongoing morbidities including multiple reinterventions requiring prolonged and repeated hospital stay, and over a billion dollars in additional healthcare costs in US each year. The introduction laparoscopic approach has progressively increased overall laparoscopic cholecystectomy procedure volume, for clearly proven benefits of minimally invasive approach. However, despite the benefits, minimally invasive approach has resulted in increased and persistent incidence of BDI up to 4-folds in some reports.
Most major biliary injuries result from unrecognized or unintended perception, either misidentification or misinterpretation of the common bile or hepatic duct as the cystic duct or misidentification of an aberrant bile duct. It is increasingly clear that the routine use of intraoperative cholangiography (IOC) has a significant association with decreased and earlier intraoperative detection of BDI. The recent 'state of the art consensus conference on prevention of bile duct injury during cholecystectomy' in 2018 strongly recommended that documenting the critical view of safety (CVoS) and a liberal use of IOC in anticipated difficult cholecystectomy are highly recommended steps that can potentially mitigate the risk of BDI during laparoscopic cholecystectomy (LC) in patients especially with uncertain anatomy or difficult dissection.
Performing traditional IOC laparoscopically under fluoroscopic guidance however can challenge surgeons' skills, is time-consuming, and requires a learning curve to interpret images. Despite well-known and accepted risk factors for difficult cholecystectomies and potential for BDI, the use of advanced imaging for IOC however remains variable and highly user dependent. The rationale for selective use of IOC is attributable to the fact that the prevalence and incidence of BDI are low that an individual practitioner would infrequently encounter such complication in their daily practice or lifetime of a surgeon to justify a routine use. This is further compounded by the fact that radiation-based fluoroscopic IOC are cumbersome to efficient workflow, utility and cost (need for contrast reagent preparation and injection, potential adverse allergic reactions, risk of radiation exposure, training requirement, need for large capital equipment, space and cost), and variability in proficient analysis.
Recent randomized controlled trials using near-infrared fluorescent cholangiography (NIFC) using indocyanine green (ICG) demonstrated significantly superior visualization of extrahepatic biliary structures during laparoscopic cholecystectomy to white light (WLI) alone. Pre-dissection surgeon detection rates on naked eye were significantly higher (> 1.8 - 3.1 folds) with NIFC use for all 7 biliary structures than traditional WLI alone. However, although similar intergroup differences were observed for all structures, addition of NIFC did not improve additional detection of cystic duct and cystic duct/gallbladder junction after dissection has been done. In addition, increased body mass index was associated with reduced detection of most structures in both groups, especially before dissection. Interestingly, only 2 patients, both in the WLI group, sustained a biliary duct injury.
ActivSightTM is an FDA-cleared device that combines ICG fluorescence for extrahepatic biliary visualization and laser speckle contrast imaging (LSCI) for perfusion detection in a laparoscopic form factor. ActivSightTM allows augmented visualization to any current WLI laparoscopic visualization system displaying both extrahepatic biliary ICG and microperfusion over cystic duct and artery. As a non-significant risk device, ActivSightTM has been used in well over 150 patients for laparoscopic cholecystectomies and bariatric, esophageal, and colorectal procedures, with proven safety and utility. Moreover, ActivSightTM allows raw infrared visualization data for advanced analysis and AI/ML model development.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- 未提供
排除标准
- 未提供
研究组 & 干预措施
Non-Indocyanine Green (Non-ICG)
The surgeon will perform the procedure in their standard fashion without the use of ICG.
ActivInsight artificial intelligence will be used to analyze the surgical video in real time to identify anatomic structures and phases of surgery.
结局指标
主要结局
Precision and accuracy
时间窗: Immediately after each procedure
Precision and accuracy of AI/ML model at identifying procedural phases and critical anatomic structures in laparoscopic cholecystectomy (LC). Precision will be calculated as True Positives / (True Positives + False Positives) Accuracy will be calculated as (True Positives + True Negatives) / Total Samples "True Positive" will be when the AI correctly identifies a procedural phase or critical anatomic structure. "False Positive" will be when it incorrectly labels a procedural phase or critical anatomic structure as the phase or structure of interest. "True Negatives" will be when the AI model correctly labels the phase or structure as not the label of interest. Accuracy and precision will be determined for each of the following labels: * each of three procedural phases (pre-, intra-, and post-gallbladder dissection) * each of seven biliary structures: gallbladder, cystic duct, common hepatic duct, common bile duct, cystic artery, region of interest, danger zone
次要结局
- Length of procedure(Immediately after each procedure)
- Conversion rate to open procedure(Immediately after each procedure)
- Complication rate(One month after each procedure)
- Length of hospital stay(One month after each procedure)
