Convolutional Neural Network for the Detection of Cervical Myelomalacia on Magnetic Resonance Imaging
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Istanbul University
- Enrollment
- 125
- Locations
- 1
- Primary Endpoint
- The value of confusion matrix accuracy for sagittal views
Study Overview
Brief Summary
Deep learning technology has been used increasingly in spine surgery as well as in many medical fields. However, it is noticed that most of the studies about this subject in the literature have been conducted except of the cervical spine. In this study, we aimed to demonstrate the effectiveness of the deep learning algorithm in the diagnosis of cervical myelomalacia compared to conventional diagnostic methods.
Artificial neural networks, a machine learning technique, have been used in several industrial and research fields increasingly. The development of computational units and the increasing amount of data led to the development of new methods on artificial neural networks
Detailed Description
Cervical myelopathy (CM) is a frequent degenerative disease of the cervical spine that occurs as a result of compression of the spinal cord. In evaluating of this disease and determining treatment options, the patient's clinic and radiological modalities should be evaluated together.
The current imaging procedures for CM are plain roentgenograms, computed tomography and magnetic resonance imaging (MRI). However, MRI in CM is more valuable in evaluating of the disc, spinal cord and other soft tissues compared to other imaging methods. Artificial intelligence technologies also used in many health applications such as medical image analysis, biological signal analysis, etc. In this study, we aimed to demonstrate the effectiveness of the deep learning algorithm in the diagnosis of cervical myelomalacia compared to conventional diagnostic methods.
Study Design
- Study Type
- Observational
- Observational Model
- Other
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 32 Years to 77 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •the patients with classical cervical myelomalacia sypmtoms such as neck pain and stiffness, weakness and clumsiness at the upper extremities or gait difficulties and radiological findings of spinal compression
- •30-80 years age.
Exclusion Criteria
- •Patients with a previous history of cervical spinal surgery and has a systematic disease (rheumatologic or neural disease) .
Outcomes
Primary Outcomes
The value of confusion matrix accuracy for sagittal views
Time Frame: 1 day
It is a specific table layout that allows visualization of the performance of an algorithm.
The value of confusion matrix accuracy for axial views
Time Frame: 1 day
It is a specific table layout that allows visualization of the performance of an algorithm.
Secondary Outcomes
No secondary outcomes reported
Investigators
Merve Damla Korkmaz
Principle investigator
Istanbul University