Extraction of vector field-based motion signatures from 4D (CB)CT image sequences and correlation with local control of lung and liver metastases after SBRT

• Applicant: Professor Dr. René Werner
• Subject Area: Epidemiology and Medical Biometry/Statistics ; Medical Physics, Biomedical Technology
• Term: from 2017 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 390567362

4D CT imaging is a cornerstone of radiation therapy planning of thoracic and abdominal tumors. However, artifacts in 4D CT and 4D cone beam (CB) CT image data result in erroneous motion estimates and target volume definition uncertainties. In the first funding period, it was shown that the occurrence of artifacts in 4D CT radiation planning data correlates with reduced local control of lung and liver metastases after stereotactic body radiation therapy (SBRT). Therefore, procedures were developed to reduce 4D CT and 4D CBCT artifacts. It was further demonstrated that improved image quality was associated with reduced non-linear registration-based motion field estimation errors. The proposed project continuation is directly based on the project results: It will be investigated whether specific breathing patterns, their interfractional changes and/or intrafractional breathing variability - which causes 4D-CT artifacts - correlates with reduced local control. A prerequisite addressed in the project is the consistent registration-based motion field estimation in the artifact-reduced 4D-CT and 4D-CBCT image data recorded during the course of therapy. Based on resulting motion fields and during treatment respiratory signals, low-dimensional motion signatures will be defined and applied dose distributions and associated dose indices estimated. Respective data will then be used for a significantly expanded patient population for detailed correlation and Kaplan-Meier analyses of signatures and indices in relation to metastasis recurrence after SBRT.

• DFG Programme: Research Grants