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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04179812
Other study ID # KneeMod ( 29BRC18.0235)
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date March 16, 2019
Est. completion date July 31, 2021

Study information

Verified date June 2021
Source University Hospital, Brest
Contact STINDEL Eric
Phone +33 (0)2 98 22 38 58
Email eric.stindel@chu-brest.fr
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The trial will contribute to the development of an innovative algorithm that aims to simplify and improve preoperative knee surgical decision. This will be made by automatically extracting anatomical informations from different images acquired on the patient (scanner, MRI, radiography).


Description:

The source population will consist of at least 50 patients whose following modalities of images of the leg are present in the database: scanner, MRI, radiography. No restrictions on age or gender are required. A dedicated algorithm adapting statistical models of appearance to the specific morphology of the patient acquired through an MRI and / or scanner and radios will then be developed.


Recruitment information / eligibility

Status Recruiting
Enrollment 210
Est. completion date July 31, 2021
Est. primary completion date July 31, 2021
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group N/A and older
Eligibility Inclusion Criteria: - Patients having the 3 modality of images : scanner, MRI, radiography - Patients having osteoarthritis or knee trauma - Images showing the articualtion of the knee - having formulated his non opposition Exclusion Criteria: - Presentation of a partial view of the knee or any view that does not allow a good segmentation of the total knee joint. - Refusal to participate

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
France CHRU de Brest Brest

Sponsors (1)

Lead Sponsor Collaborator
University Hospital, Brest

Country where clinical trial is conducted

France, 

Outcome

Type Measure Description Time frame Safety issue
Primary Obtaining a similar knee segmentation for all patient regardless of the input image (MRI, CT or radiography) Creation of an algorithm that will automatically segment and provide the same knee anatomical informations for all patients studied regardless of the input image.
This multimodal modeling will be carried out via the exploitation of an active model of appearance type algorithm.
Inclusion - Day 0
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