Convolutional Neural Network for the Detection of Cervical Myelomalacia

Study Overview
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Brief Summary
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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
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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.

Official Title
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Convolutional Neural Network for the Detection of Cervical Myelomalacia on Magnetic Resonance Imaging

Conditions
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Cervical Myelopathy

Intervention / Treatment
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* Diagnostic Test: Convolutional Neural Network


Participation Criteria
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Eligibility Criteria
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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) .

Ages Eligible for Study
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Minimum Age: 32 Years
Maximum Age: 77 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| cervical myelopathy<br>MR images of patients with cervical myelopathy | Diagnostic Test: Convolutional Neural Network<br>* Convolutional 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. Deep learning (DL) is a multi-layered neural network in which feature extraction is done automatically. It extends traditional neural networks by adding more hidden layers to the network architecture between the input and output layers to model more complex and nonlinear relationships.<br>|
| normal<br>normal section of the MRI of patients with cervical myelopathy | Diagnostic Test: Convolutional Neural Network<br>* Convolutional 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. Deep learning (DL) is a multi-layered neural network in which feature extraction is done automatically. It extends traditional neural networks by adding more hidden layers to the network architecture between the input and output layers to model more complex and nonlinear relationships.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The value of confusion matrix accuracy for sagittal views | It is a specific table layout that allows visualization of the performance of an algorithm. | 1 day | 
| The value of confusion matrix accuracy for axial views | It is a specific table layout that allows visualization of the performance of an algorithm. | 1 day | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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neural network, deep learning, cervical myelopathy