Functionality Assessment of RadiSpine, an Artificial Intelligence Software as Medical Device for Lumbar Spine Quantification System
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 150
- 试验地点
- 1
- 主要终点
- Segmentation accuracy (Mean)
研究概览
简要总结
Spinal degeneration and its associated clinical diseases are common ailments in aging societies. With the advent of a super-aging society, the importance of assistive technologies for spinal image interpretation is increasingly significant to enhance care efficiency and reduce medical personnel expenditure. Recently, due to the rapid development of artificial intelligence (AI) algorithm, AI-based computer-assisted detection (CADe) devices gradiually become a convenient method for spinal anatomy measurement. However, the accuracy of these devices has not been fully established. This study aims to validate the performance of RadiSpine (an application program) in spinal anatomy segmentation and measurement.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 22 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •The subjects should be aged 20 or older and younger than 75, with an equal gender distribution of 50% male and 50% female. From this group, 150 subjects with reasonable datavalues will be selected, with a requirement that at least 30% of them are male and at least 30% are female.
排除标准
- •With history of spinal surgery
- •Spinal trauma
- •Spinal osteoporosis
- •Spinal metastasis or infection
结局指标
主要结局
Segmentation accuracy (Mean)
时间窗: 30 mins per individual
The minimum Mean Dice Coefficient (MDC), defined as the lower limit of the 95% confidence interval (CI) for MDC, is above a predetermined allowable limit equal to 0.8
次要结局
- Measurement accuracy(30 mins per individual)