An Algorithm Creation by Automated Segmentation by MRI for Bone and Muscles of Shoulder

Study Overview
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Brief Summary
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The primary objective of the study is to develop an algorithm of automated segmentation of shoulder by MRI examinations.

Detailed Description
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This is a national monocentric study which will be conducted in Ambroise Paré hospital of APHP, in orthopaedics department (for enrollment) and radiological department (for CT-scan and MRI examinations) respectively. Manual segmentations of 5 muscles and 2 bones of shoulder by MRI with automated segmentation of shoulders corresponding to CT-scan imagings. 3D imagings of each shoulder by manual segmentations from MRI and automated segmentation from computed tomography will provide to build a network. The perspective of the elaborated algorithm should lead to an automated 3D-reconstruction of patients' shoulder as a routine care in surgery.

Official Title
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Elaboration of an Algorithm of Automated Segmentation by Magnetic Resonance Imaging for Bone and Muscles of Shoulder

Conditions
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Reverse Shoulder Prosthesis

Intervention / Treatment
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* Procedure: CT-Scan and MRI


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Healthy volunteer > 18 years, presenting any symptom nor history of shoulder pathology; Affiliated to social security scheme. Exclusion Criteria: Symptoms or history of shoulder pathologies; Claustrophobia; Pregnant woman; Patient covered by AME system; Contre-indication to perform MRI examination (implant, less 6-months stent implantation, recent surgery, renal insufficiency, pace maker implantation, cardiac defibrillator, cardiovascular catheter, neurostimulation, implantable electronic pompe for automatic injection of medications).

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Other
Intervention Model: Single Group Assignment
Interventional Model Description: No comparative, no control study
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Experimental arm<br>All participants are healthy volunteers | Procedure: CT-Scan and MRI<br>* CT-Scan and MRI examination for shoulder will be performed on healthy volunteers.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Algorithm developement | The developement for automatic segmentation algorithm: uses method with a convolutional neural networks (convolutional neural network - CNN). | through study completion, an average of 8 month | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Reverse Shoulder Prosthesis, Algorithm, Automatic segmentation, Magnetic resonance imaging, Computed tomography, 3D imaging, Manual segmentation