NCT03746561

Automatic Diagnosis of Spinal Stenosis on CT

Automatic Diagnosis of Spinal Stenosis on CT With Deep Learning

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: Shanghai 10th People's Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

MRI is a common tool for radiographic diagnosis of spinal stenosis, but it is expensive and requires long scanning time. CT is also a useful tool to diagnose spinal stenosis, yet interpretation can be time-consuming with high inter-reader variability even among the most specialized radiologists. In this study, the investigators aim to develop a deep-learning algorithm to automatically detect and classify lumbar spinal stenosis.

Detailed description

MRI is a common tool for radiographic diagnosis of spinal stenosis, but it is expensive and requires long scanning time. CT is also a useful tool to diagnose spinal stenosis, yet interpretation can be time-consuming with high inter-reader variability even among the most specialized radiologists. In this study, the investigators aim to develop a deep-learning algorithm to automatically detect and classify lumbar spinal stenosis. It would be a time-saving workflow if the software can assist the radiologists to detect and locate the suspected lesion.

Conditions

• Spinal Stenosis

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	deep learning	detect and classify spinal stenosis by deep learning

Timeline

• Start date: 2018-11-01
• Primary completion: 2019-04-01
• Completion: 2019-05-01
• First posted: 2018-11-19
• Last updated: 2018-11-19