Automatic Diagnosis of Spinal Stenosis on CT (ASSIST)

Tongji University

Status: Unknown

Conditions: Spinal Stenosis

Treatments: Diagnostic Test: deep learning

Study type: Observational

Funder types: Other

Identifiers

NCT03746561

SHSY181022

Details and patient eligibility

About

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.

Full 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.

Enrollment: 500 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age >18 years
• with radiologists' CT reports on cervical, thoracic and lumbar stenosis

Exclusion criteria

• not applicable (only specific levels with extensive infections, fractures, tumor, high-grade spondylolisthesis would be excluded for analysis).

Trial design

500 participants in 1 patient group

spinal stenosis

Description:

Spinal stenosis is a narrowing of the spaces within your spine, which can put pressure on the nerves that travel through the spine. Spinal stenosis occurs most often in the lower back and the neck.

Treatment:

Diagnostic Test: deep learning