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NCT Number: NCT04394052

Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II

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.

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Key information

Conditions

Soft Tissue Neoplasm Bone Diseases Bone Neoplasm Bone Neoplasms Musculoskeletal Diseases Neoplasms Neoplasms by Site Soft Tissue Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

MR imaging

Diagnostic Test

Medical imaging

Other names: Ultra-high resolution CT

Primary outcomes

  1. Lesion benignancy or malignancy

    Time frame: Performed up to 6 months after CT and Magnetic Resonance (MR) imaging

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

Secondary outcomes

  1. Sarcoma FNCLCC (fédération Nationale des Centres de Lutte Contre le Cancer) grade

    Time frame: Performed up to 1 year after CT and MR imaging

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

Study contacts

Contact information is provided by the study sponsor or research team.

Gabriela Hossu, PhD

CONTACT

[email protected]

+33 3 83 15 50 96

Pedro Gondim Teixieira, PhD

CONTACT

[email protected]

+33 3 83 85 21 61

Sponsors and collaborators

Lead sponsor

Central Hospital, Nancy, France

Other

Collaborators

  • Diagnostic and Interventional Adaptative Imaging Laboratory - IADI
  • Emille Gallé Surgical Center - CCEG
  • Lorraine Cancer Institute - ICL

Registry information

Official study title

Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II: Texture Analysis and Artificial Intelligence

Acronym: TUMOSTEO II

Important dates

Study start
2020
Primary completion
2026
Study completion
2030
First posted
May 19, 2020
Registry last updated
Jul 21, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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