Smart Bone: An Intelligent Fracture Risk Capture and Management System
试验速览
- 阶段
- 不适用
- 入组人数
- 1,500
- 试验地点
- 1
- 主要终点
- Concordance rate
研究概览
简要总结
This project aims to develop and validate an automatic detection and classification system for vertebral compression fractures on computer tomography (CT) images using an artificial intelligence (AI) system (named Smart Bone) by Quanta.
详细描述
A computer search of CT scans (2010.01.01-2018.09.30) was performed in Wan Fang Hospital. Those CT images that were retrospectively reviewed by experienced radiologists. The CT scans of 1000-1500 subjects aged 50 and above with and without thoracic or lumbar compression fractures were included in this project for machine learning and deep learning. The control group included those without compression fractures while the patient group were those with compression fractures. Subjects that did not meet the inclusion criteria were excluded.
The cortical layer of the T12-L5 spine images were manually labelled with the labeling software by the the technologists and confirmed the correctness of the image by an experienced radiologist. All the de-linked and completed images were provided to Quanta Computer Inc. for subsequent classification and analysis of AI machines for deep learning to facilitate the development of a system for automatic detection of pressure fractures by CT. This newly developed automatic system will be of valuable clinical impact in assisting radiologists to detect and classify vertebral compression fractures precisely and accurately.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 50 Years 至 90 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Cases with CT examinations acquired between 2010.01-2018.09
- •Cases with CT examinations performed with one of the following protocol: whole body, abdomen, and spine
- •Cases must be >/= 50 years of age
- •Cases with reports from CT examinations ditched as positive or negative compression fractures within a search range from T12 to L5 vertebrae.
- •CT images with raw data that are allowed to be reconstructed in axial view with a slice thickness of 1.3 mm
- •CT images with raw data that are allowed to be reconstructed in sagittal view with a slice thickness of 2.5 mm
排除标准
- •CT images with imaging artifacts, foreign bodies, or implants
- •Cases with comorbid conditions, such as infection, cancer metastasis, chronic osteomyelitis, or other nonosteoporotic compression fracture
结局指标
主要结局
Concordance rate
时间窗: 2019.06 to 2020.03
CT Imaging Reporting and Data System descriptors suggested by Smart Bone are in good agreement with those selected by experts. In other words, the CT Imaging Reporting and Data System generated by Smart Bone are not statistically different from the consensus of experts. CT Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, Smart Bone displays the assessment description. Grade 0: Normal Vertebrae Grade 1: Mild Fracture, 20-25% Grade 2: Moderate Fracture, 26-40% Grade 3: Severe Fracture, \>40%
次要结局
- Accuracy(2019.06 to 2020.03)
研究者
Wing P Chan
Professor and Chief, Department of Radiology, Wan Fang Hospital, Taipei Medical University
Taipei Medical University WanFang Hospital