Automatic Diagnosis of Spinal Stenosis on CT — ASSIST  

Spinal Stenosis Clinical Trial

Official title: Automatic Diagnosis of Spinal Stenosis on CT With Deep Learning

Status Not yet recruiting

Clinical Trial 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.

Clinical Trial 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. ;

Related Conditions & MeSH terms

• Constriction, Pathologic
• Spinal Stenosis

• NCT number: NCT03746561
• Study type: Observational
• Source: Shanghai 10th People's Hospital
• Contact: Shisheng He, MD
• Phone: 021-66307580
• Email: TJHSS7418@TONGJI.EDU.CN
• Status: Not yet recruiting
• Start date: November 2018
• Completion date: May 2019