Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II

  • STATUS
    Recruiting
  • End date
    Jun 1, 2030
  • participants needed
    740
  • sponsor
    Central Hospital, Nancy, France
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Updated on 5 August 2020
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imaging techniques

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.

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.

Details
Condition Bone Cancer, Soft tissue tumor
Age 18years - 100years
Treatment MR imaging
Clinical Study IdentifierNCT04394052
SponsorCentral Hospital, Nancy, France
Last Modified on5 August 2020

Eligibility

 Yes No Not Sure

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
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