"Characterization of Bone Tumors in Computed Tomography and in Magnetic Resonance Imaging by Machine Learning"

"Characterization of Bone Tumors in Computed Tomography and in Magnetic Resonance Imaging by Machine Learning" - Bone tumor - AI study

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00024574

Enrollment

2000

Registered

2023-02-27

Start date

2021-04-28

Completion date

Unknown

Last updated

2025-10-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

D48.9

Interventions

Group 1: retrospective analysis The clinical diagnosis, the image data, essential epidemiological data and the corresponding histopathological findings are checked for completeness via the database on

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Patients in tumor orthopedics at the LMU with a clinical diagnosis of a bone tumor (malignant/benign) and corresponding radiological examinations as well as histopathological findings/clinical diagnoses

Exclusion criteria

Exclusion criteria: missing images (X-ray, MRI, CT) lack of histopathological findings / clinical diagnosis

Design outcomes

Primary

Measure	Time frame
Comparison of the sensitivity/specificity regarding the detected bone tumors by the artificial intelligence compared to the results of the histopathology. The results of the histopathology correspond to the reference standard.	—

Secondary

Measure	Time frame
Comparison of sensitivity and specificity of radiology (resident, fellow, expert) versus artificial intelligence	—

Countries

Germany

Contacts

Public ContactJens Ricke

LMU München

Jens.ricke@med.uni-muenchen.de+4989440076642

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026