Automatic Diagnosis of Spinal Stenosis on CT

Automatic Diagnosis of Spinal Stenosis on CT With Deep Learning

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.

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.

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).