Development and Validation of a Computer-aided Algorithm Using Artificial Intelligence and Deep Neural Networks for the Segmentation of Ultrasonographic Features of Lymph Nodes During Endobronchial Ultrasound
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 52
- 试验地点
- 1
- 主要终点
- Development of computer algorithm to identify lymph node ultrasonographic features
研究概览
简要总结
This study aims to determine if a deep neural artificial intelligence (AI) network (NeuralSeg) can learn how to assign the Canada Lymph Node Score to lymph nodes examined by endobronchial ultrasound transbronchial needle aspiration(EBUS-TBNA), using the technique of segmentation. Images will be created from 300 lymph nodes videos from a prospective library and will be used as a derivation set to develop the algorithm. An additional100 lymph node images will be prospectively collected to validate if NeuralSeg can correctly apply the score.
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 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •must be diagnosed with confirmed or suspected lung cancer and be undergoing EBUS diagnosis/staging
排除标准
- 未提供
结局指标
主要结局
Development of computer algorithm to identify lymph node ultrasonographic features
时间窗: From retrospective data collection to algorithm development (1 month)
Objective: to determine whether a deep neural AI network (NeuralSeg) can learn how to assign the Canada Lymph Node Score to lymph nodes examined by EBUS, using the technique of segmentation on an existing (derivation) set of lymph node videos
Validation of computer algorithm to identify lymph node ultrasonographic features
时间窗: From prospective data collection to algorithm validation (6 months)
Objective: to determine whether NeuralSeg can correctly apply the Canada Lymph Node Score to a new (validation) set of lymph node videos that it has never seen before
次要结局
- NeuralSeg prediction of lymph node malignancy(From NeuralSeg algorithm used on EBUS imaging to biopsy report (estimated up to 2-3 months))
- Accuracy and reliability of the segmentation performed by NeuralSeg(From segmentation performed by surgeon to segmentation performed by NeuralSeg (1 month))
研究者
Wael Hanna
Dr. Waël Hanna, MDCM, MBA, FRCSC
St. Joseph's Healthcare Hamilton