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

Sponsor

Assistance Publique - Hôpitaux de Paris (Other)

Overall Status

Not yet recruiting

CT.gov ID

NCT05376813

Collaborator

(none)

100

Enrollment

Location

Arm

Anticipated Duration (Months)

12.4

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

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

Condition or Disease	Intervention/Treatment	Phase
Reverse Shoulder Prosthesis	Procedure: CT-Scan and MRI	N/A

Detailed Description

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.

Study Design

Study Type:

Interventional

Anticipated Enrollment :

100 participants

Allocation:

N/A

Intervention Model:

Single Group Assignment

Intervention Model Description:

No comparative, no control studyNo comparative, no control study

Masking:

None (Open Label)

Primary Purpose:

Other

Official Title:

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

Anticipated Study Start Date :

May 1, 2022

Anticipated Primary Completion Date :

Jan 1, 2023

Anticipated Study Completion Date :

Jan 1, 2023

Arms and Interventions

Arm	Intervention/Treatment
Experimental: Experimental arm All participants are healthy volunteers	Procedure: CT-Scan and MRI CT-Scan and MRI examination for shoulder will be performed on healthy volunteers.

Arm

Intervention/Treatment

Experimental: Experimental arm

All participants are healthy volunteers

Procedure: CT-Scan and MRI

CT-Scan and MRI examination for shoulder will be performed on healthy volunteers.

Outcome Measures

Primary Outcome Measures

Algorithm developement [through study completion, an average of 8 month]
The developement for automatic segmentation algorithm: uses method with a convolutional neural networks (convolutional neural network - CNN).

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Yes

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).