Characterization of genetic intratumoral heterogeneity of benign and malignant soft tissue tumors for prediction of genetic aberrations by machine learning.

Recruiting

• Conditions: D48.1; Connective and other soft tissue

• Registration Number: DRKS00024705
• Lead Sponsor: MU München

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Study Start: 2023-02-22
• Last Update Posted: 19 August 2024

Recruitment & Eligibility

• Status: Recruiting
• Sex: All
• Target Recruitment: 1000

Inclusion Criteria

Patients of the Tumor Orthopedics of the LMU with clinical diagnosis of a soft tissue tumor (malignant / benign) and corresponding radiological examinations as well as histopathological findings/ clinical diagnoses.

Exclusion Criteria

- Missing imaging (MRI)
- Missing histopathological findings / clinical diagnosis

Study & Design

• Study Type: observational
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
In the future, improved predictive power of benign and malignant soft tissue tumors with respect to their genetic aberrations based on imaging data (MRI images). Sensitivity and specificity will be given between artificial intelligence and histopathology/molecular genetics. A comparison of sensitivity and specificity is made using McNemar's test.

Secondary Outcome Measures

Name	Time	Method
Prediction of soft tissue tumor prognosis (survival rate, metastasis risk, recurrence rate) by artificial intelligence using image morphological criteria.