Development of a Computer-aided Polypectomy Decision Support
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 发起方
- 试验地点
- 1
- 主要终点
- Completeness of polypectomy
研究概览
简要总结
Quality components of colonoscopy include the detection and complete removal of colorectal polyps, which are precursors to CRC. However, endoscopic ablation may be incomplete, posing a risk for the development of "interval cancers". The investigators propose to develop a solution based on artificial intelligence (AI) (CADp computer-aided decision support polypectomy) to solve this problem.This research project aims to develop CADp, a computer decision support solution (CDS) for the ablation of colorectal polyps from 1 to 20 mm.
详细描述
This research project aims to develop CADp, a computer-based decision support (CDS) solution for the removal of colorectal polyps ranging from 1-20 mm. The investigators will use a video and image dataset of polypectomy procedures to train the CADp model; thus, it can provide real-time overlaid video feedback for polypectomy procedures based on five specific metrics: 1) estimation of polyp size; 2) prediction of morphology and histology; 3) suggestion of an appropriate resection accessory and technical approach based on the characteristics, size, and histology of the polyp according to current guidelines; 4) image overlay, based on semantic image segmentation technology, showing the extent of the lesion and suggestion of an appropriate resection margin contour around the polyp to ensure its complete removal; 5) post-resection analysis to identify any remnant polyp tissue or insufficient resection margin that may increase this risk.
The investigators will collect a set of images and video data from live polypectomy procedures to leverage recent advances in AI technology to train deep learning models. This dataset will be obtained prospectively from a cohort of adults (ages 45-80) undergoing screening, diagnostic, or surveillance colonoscopies. To train the CADp solution, the investigators will obtain the corresponding completeness of resection status using the yield of post-resection margin biopsies. The dataset will be divided into two groups, the training, and the CADp test, respectively.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Supportive Care
- 盲法
- None
入排标准
- 年龄范围
- 45 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Signed informed consent
- •Age 45-80 years
- •Indication to undergo a lower GI endoscopy.
排除标准
- •Known inflammatory bowel disease
- •Active colitis
- •Coagulopathy
- •Familial polyposis syndrome;
- •Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3
- •Emergency colonoscopies
结局指标
主要结局
Completeness of polypectomy
时间窗: 1 month
We will evaluate the agreement between the different subjective and objective ways of assessing the completeness of the polypectomy : evaluation of margins (presence or not, measurement of margins) by endoscopists self-assessment, and by expert consensus.
Validity of the choice of primary outcome
时间窗: 1 month
Based on the results and comparison of the different assessment methods, we will perform sensitivity analyses to assess the validity and robustness of the choice of primary outcome.
Accuracy of the CADp system
时间窗: 3 weeks
accuracy with which the CADp system predicts completeness of polypectomy in the test set with the reference standard for completeness being determined by the histology of post-polypectomy margin biopsies; if free from any polyp tissue (adenomatous, serrated or hyperplastic), the resection will be considered complete. If remnant polyp tissue is detected in any one or more of the margin biopsies the resection is deemed incomplete
Training CADp
时间窗: 1 month
Evaluation of the concordance of data on polyp size, extension of margins around the polyp, quality of resection between clinical data (endoscopists' self-assessment and experts' assessments) and CADp prediction.
次要结局
未报告次要终点