4D Medical Image Computing for Image-based Risk Assessment in Radiation Therapy of Moving Tumors

Second phase of the DFG-funded project „4D Medical Image Computing for Model-based Analysis of Respiratory Tumor and Organ Motion“

Respiratory organ and tumor motion is a significant source of error in radiation therapy of the thorax and upper abdomen. In recent years, a variety of technical solutions has been developed to explicitly account for breathing motion during radiation treatment. Methods in clinical use are e. g. so-called gating techniques or respiratory-triggered dose delivery. This means that radiation is only delivered during specified phases of the patients’ breathing cycle. The phases are usually determined using external breathing signals and breathing motion indicators like abdominal bellows or camera-based tracking of surface/skin motion.

External signals, however, are only indicators or surrogates of the inner body tumor motion. Considering especially the risk of intra- and interfractional variations of respiratory motion patterns (and the relationship between tumor motion and breathing signals, respectively) this project aims at investigating the suitability of different motion indicators for predicting tumor motion. Based on 4D CT and 4D MRT image sequences of lung tumor patients acquired over the course of treatment we further intend to quantify dosimetric influences of intra- and interfractional motion variability in standard and gated radiation therapy. Dosimetric consequences in gated radiation therapy are studied simulating the use of different motion indicators – with the final goal of establishing an indicator-specific risk assessment and the development of strategies for combination and optimization of typical breathing motion surrogates (fig. 1).
 
The project is funded by the German Research Foundation (Deutsche Forschungsgemeinschaft (DFG), HA 2355/9-2).

 

 

Fig. 1: Results of a correlation analysis between skin and tumor motion for a lung tumor patient (red: high correlation, green: low correlation). The correlation analysis was based on a 4D CT image se-quence of the patient and the results are used to determine optimal scanline positions of a line laser when applied as a breathing motion indicator in e. g. respiratory-triggered radiation therapy.

Project Team:

M.Sc. Matthias Wilms
Dipl-Inf. Dipl.-Phys. René Werner
Dr. Jan Ehrhardt
Prof. Dr. Heinz Handels

Cooperation Partners:

Prof. Dr. H.-P. Schlemmer, Dr. M. Eichinger / Dr. R. Floca
Abteilung Radiologie / AG Software Development for Integrated Diagnostic and Therapy
Deutsches Krebsforschungszentrum (DKFZ) Heidelberg, Germany

Prof. Dr. Dr. J. Debus, Dr. Dr. C. Thieke
Klinik für Radio-Onkologie und Strahlentherapie
Universitätsklinikum Heidelberg, Germany

Prof. Dr. C. Petersen, Dr. F. Cremers
Klinik und Poliklinik für Strahlentherapie und Radioonkologie
Universitätsklinikum Hamburg-Eppendorf (UKE), Germany

 

 

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Created at February 20, 2012 - 12:40pm by Kulbe. Last modified at February 21, 2012 - 11:36am.

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