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.

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.

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.

Patients with soft-tissue and bone tumors evaluated with MR and ultra-high resolution CT.