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Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II

Recruiting
Conditions
Bone Neoplasm
Soft Tissue Neoplasm
Registration Number
NCT04394052
Lead Sponsor
Central Hospital, Nancy, France
Brief Summary

This study aims at evaluating the value of various artificial intelligence based techniques to improve the characterization and image post-processing for patients with musculoskeletal tumors.

Detailed Description

Comparison of values relating to the texture parameters of tumors evaluated by MRI and ultra-high resolution CT between benign and malignant lesions using histological analysis as the standard of reference.

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.

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
740
Inclusion Criteria
  • Patients suspected to have a bone or soft-tissue tumor referred for imaging for initial tumors characterization and staging.
Exclusion Criteria
  • Pregnancy
  • Breast feeding patients
  • Renal insufficiency
  • Contra indications to MRI or CT
  • Prior surgery or treatment to the evaluated lesion.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Lesion benignancy or malignancyPerformed up to 6 months after CT and Magnetic Resonance (MR) imaging

Histologic determination of lesion aggressiveness (benign versus malignant) on core biopsy material

Secondary Outcome Measures
NameTimeMethod
Sarcoma FNCLCC (fédération Nationale des Centres de Lutte Contre le Cancer) gradePerformed up to 1 year after CT and MR imaging

Histologic grade of the sarcomas included in the study population with surgical resection material

Trial Locations

Locations (1)

CHU-Nancy

🇫🇷

Nancy, Lorraine, France

CHU-Nancy
🇫🇷Nancy, Lorraine, France
Pedro Gondim Teixeira, Prof
Contact
+33383852161
p.teixeira@chru-nancy.fr
Alain Blum, Prof
Contact
+33383852161
alain.blum@gmail.com

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