Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II
NCT ID: NCT04394052
Last Updated: 2020-07-21
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
740 participants
OBSERVATIONAL
2020-06-01
2030-06-01
Brief Summary
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Detailed Description
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Comparison of the diagnostic performance of texture parameters derived from different MRI sequences and ultra-high resolution CT for musculoskeletal tumor characterization.
Evaluate the impact of ultra-high resolution with respect to standard resolution on CT images Comparison of the diagnostic performance of the texture parameters for the tumor on the diagnostic performance of texture analysis derived parameters for the characterization of musculoskeletal tumors.
Evaluate the effectiveness and accuracy of automatic artificial intelligence (AI) based tumor segmentation tools.
Evaluate the use of trabecular analysis on ultra-high resolution CT images for the evaluation of tumor-bone interfaces.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Soft-tissue tumors
Benign and malignant soft tissue masses
MR imaging
Medical imaging
Bone tumors
Benign and malignant bone focal bone lesions
MR imaging
Medical imaging
Interventions
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MR imaging
Medical imaging
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Breast feeding patients
* Renal insufficiency
* Contra indications to MRI or CT
* Prior surgery or treatment to the evaluated lesion.
18 Years
ALL
No
Sponsors
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Lorraine Cancer Institute - ICL
UNKNOWN
Emille Gallé Surgical Center - CCEG
UNKNOWN
Diagnostic and Interventional Adaptative Imaging Laboratory - IADI
UNKNOWN
Central Hospital, Nancy, France
OTHER
Responsible Party
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Locations
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CHU-Nancy
Nancy, Lorraine, France
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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2019PI253
Identifier Type: -
Identifier Source: org_study_id
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