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临床试验/NCT04607083
NCT04607083已完成不适用

Impact of Computer-aided Optical Diagnosis (CAD) in Predicting Histology of Diminutive Rectosigmoid Polyps: a Multicenter Prospective Trial (Artificial Intelligence BLI Characterization - ABC Study).

Valduce Hospital1 个研究点 分布在 1 个国家目标入组 1,134 人开始时间: 2020年10月22日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
1,134
试验地点
1
主要终点
Agreement of combined prediction with PIVI I statement

研究概览

简要总结

Recently, a CNN-based artificial intelligence (AI) system for polyp characterization has been developed by Fujifilm Co., Tokyo, Japan. It works in conjunction with BLI system. In the present study we prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve > 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps having histopathology as reference standard. Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected are included. During endoscopic procedures all polyps identified by the endoscopist are documented for size, location and morphology. All diminutive polyps are characterized by a three sequential steps process: I) endoscopist prediction: the endoscopist evaluates the polyp by using BLI through the BASIC classification; the confidence level (high vs. low) in histology prediction is recorded; II) AI prediction: the AI system is switched on and the output of the automatic evaluation is recorded; this outcome is rated as stable or unstable, depending of the consistency over time of the outcome; III) combined prediction: a final classification is provided by endoscopist in light of the results of the first and of the second step; the confidence level is recorded. All polyps are resected and retrieved in separate jars and sent for pathology assessment. Only polyps characterized with high confidence will be included in the per-polyp analysis; the high-confidence characterization rate will be also calculated; the rate of polyps characterized with a CAD stable outcome will be calculated. Operative characteristics (sensitivity, specificity, positive and negative predictive value and accuracy) in distinguishing adenomatous from non-adenomatous polyps, evaluated with high confidence, will be calculated for each diminutive polyp and for each diminutive rectosigmoid polyp, having histopathology report as reference standard. The post-polypectomy surveillance intervals will be calculated on the basis of polyp histology (reference standard) in all patients according to both USMSTF and ESGE guidelines.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 85 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Consecutive adult outpatients undergoing elective colonoscopy, in which at least one diminutive (<5 mm) rectosigmoid polyp is detected.

排除标准

  • patients with CRC history or hereditary polyposis syndromes or hereditary non-polyposis colorectal cancer
  • patients with inadequate bowel preparation
  • patients scheduled for partial examinations
  • polyps could not be resected due to ongoing anticoagulation preventing resection and pathologic assessment
  • patients undergoing urgent colonoscopy

结局指标

主要结局

Agreement of combined prediction with PIVI I statement

时间窗: 6 months

To prospectively evaluate whether the evaluation of the endoscopist combined with the CAD system output achieve \> 90% accuracy in characterization (i.e. as adenomas or non-adenomas) of diminutive rectosigmoid polyps (i.e. PIVI I threshold) having histopathology as reference standard.

次要结局

  • Endoscopist prediction(6 months)
  • Agreement of combined prediction with PIVI II statement(6 months)
  • Ai prediction(6 months)

研究者

发起方
Valduce Hospital
申办方类型
Other
责任方
Principal Investigator
主要研究者

Franco Radaelli

Head of Gastroenterology Unit

Valduce Hospital

研究点 (1)

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