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

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

Status

Withdrawn

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT05376813

Acronym

SEGMENTATION

Enrollment

Registered

2022-05-17

Start date

2023-08-31

Completion date

2024-04-28

Last updated

2025-03-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Reverse Shoulder Prosthesis

Keywords

Reverse Shoulder Prosthesis, Algorithm, Automatic segmentation, Magnetic resonance imaging, Computed tomography, 3D imaging, Manual segmentation

Brief summary

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

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.

Interventions

PROCEDURECT-Scan and MRI

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

Study design

Allocation

Intervention model

SINGLE_GROUP

Primary purpose

OTHER

Masking

NONE

Intervention model description

No comparative, no control study

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

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).

Design outcomes

Primary

Measure	Time frame	Description
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).

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026