Automated Radiotherapy Treatment planning and Interactive Segmentation Tools

Automated Radiotherapy Treatment planning and Interactive Segmentation Tools - ARTIST

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00039723

Enrollment

600

Registered

2026-04-20

Start date

2026-10-01

Completion date

Unknown

Last updated

2026-08-03

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

Conditions

C00-C97

Interventions

Group 1: In the standard (control) group, target volume (GTV) and organs-at-risk (OAR) delineation during the initial treatment planning are performed using conventional manual contouring methods as p

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients undergoing MR-guided radiotherapy for lesions in the thorax, abdomen or pelvis at the Department of Radiation Oncology of the LMU University Hospital and providing informed written consent will be included in this study.

Exclusion criteria

Exclusion criteria: None.

Design outcomes

Primary

Measure	Time frame
The primary outcome is the reduction in the time required to reach clinically acceptable delineations during treatment planning in MR-guided radiotherapy compared to standard manual methods.	—

Secondary

Measure	Time frame
Quantitative agreement between AI-assissted generated and final physician-approved OAR segmentations (Dice Similarity Coefficient (DSC), surface distances, surface DSC, normalized added path length), as well as user satisfaction assessed using the System Usability Scale (SUS).	—

Countries

Germany

Contacts

Public ContactStefanie Corradini

LMU Klinikum

Stefanie.Corradini@med.uni-muenchen.de+49 89 4400 77520

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Aug 10, 2026