Accuracy of CAD Eye in the Detection of Colonic Remaining Lesions After Endoscopic Mucosal Resection: a Pilot Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 60
- 试验地点
- 2
- 主要终点
- Lesions recurrence after EMR
研究概览
简要总结
In the last decade, many innovative systems have been developed to support and improve the diagnosis accuracy during endoscopic studies. CAD-Eye™ (Fujifilm, Tokyo, Japan) is a computer-assisted diagnostic (CADx) system that uses artificial intelligence for the detection and characterization of polyps during colonoscopy. However, the accuracy of CAD-Eye™ in the recognition of remaining lesions after endoscopic mucosal resection (EMR) has not been broadly evaluated.
Finally, based on the importance of complete resection of the colonic mucosal lesions, namely suspicious high-grade dysplasia or early invasive cancer, the investigators aimed to assess the accuracy of CAD-Eye™ in the detection of remaining lesions after the procedure.
详细描述
Nowadays, the increased polyp and adenoma detection rate, and its early treatment have reduced considerably colorectal cancer-related mortality. For lesions suspicious of high-grade dysplasia or early invasive cancer, the endoscopic mucosal resection (EMR), along with snare polypectomy, is now considered one of the established standard treatments. However, there are many ´difficult-to-treat lesions´ such as the large and fibrotic ones, which can lead to incomplete resections.
Based on the above, many newly diagnostic techniques guided by artificial intelligence (AI), currently proposed to improve the polyp detection rate during colonoscopy, can be applied for the detection of remaining lesions after endoscopic treatment.
CAD-Eye™ is CADx for polyp detection and characterization. It improves polyp visualization by using techniques such as blue-laser imaging (BLI-LASER), blue-light imaging (BLI-LED), and linked-color imaging (LCI). This device aimed to improve real-time polyp detection, helping experts identify multiple polyps simultaneously and common inadvertently missed lesions (flat lesions, polyps in difficult areas).
CAD-Eye™ had demonstrated in previous studies an accuracy of 89% to 91.7% in polyp detection. However, few studies had demonstrated its performance in the detection of remaining lesions after EMR. The investigators aimed to take advantage of this system in the detection of remaining lesions immediately after EMR and in its endoscopic control after three months.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non 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 90 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients referred to our center with an indication of colonoscopy and EMR for the treatment of lesions suspicious of high-grade dysplasia and early invasive cancer.
- •Patients who authorize EMR and colonoscopy.
- •Signed informed consent
排除标准
- •Any clinical condition which makes EMR inviable.
- •Poor bowel preparation score defined as the total Boston bowel preparation score (BBPS) <6 and the right-segment score <2
- •Patients with more than one previous EMR
- •Lost on a three-month follow-up after EMR
- •Pregnancy or nursing
结局指标
主要结局
Lesions recurrence after EMR
时间窗: up to 1 week
Detection of remaining lesions immediately after EMR procedure based on endoscopist expertise (EMR without CAD-Eye™ group) or CAD-Eye™ (EMR + CAD-Eye™ group). Lesions will be confirmed by biopsy. Data will be summarized as frequencies.
Lesions recurrence in a three-month follow-up after EMR
时间窗: up to 3 months
Evaluation of CAD-Eye™ in the detection of recurrent lesions after EMR procedure. Remaining lesions detected by CAD-Eye™ in the three-month follow-up. Lesions will be confirmed by biopsy. Data will be summarized as frequencies.
次要结局
- Recurrence risk after EMR(up to 1 week)
研究者
Carlos Robles-Medranda
Head of the Endoscopy Division
Instituto Ecuatoriano de Enfermedades Digestivas