On-line MR imaging for dose validation of abdominal radiotherapy. (4th November 2015)

• Record Type: Journal Article
• Authors: Glitzner, M; Crijns, S P M; de Senneville, B Denis; Kontaxis, C; Prins, F M; Lagendijk, J J W; Raaymakers, B W
• Is Part Of: Physics in medicine & biology. Volume 60:Number 22(2015:Nov.)
• Page Start: 8869
• Page End: 8883
• Publication Date: 2015-11-04
• Subjects: dose reconstruction -- respiratory motion compensation -- adaptive radiotherapy -- hypofractionated treatment -- local deformations -- MR guidance; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/0031-9155/60/22/8869
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: For quality assurance and adaptive radiotherapy, validation of the actual delivered dose is crucial. Intrafractional anatomy changes cannot be captured satisfactorily during treatment with hitherto available imaging modalitites. Consequently, dose calculations are based on the assumption of static anatomy throughout the treatment. However, intra- and interfraction anatomy is dynamic and changes can be significant. In this paper, we investigate the use of an MR-linac as a dose tracking modality for the validation of treatments in abdominal targets where both respiratory and long-term peristaltic and drift motion occur. The on-line MR imaging capability of the modality provides the means to perform respiratory gating of both delivery and acquisition yielding a model-free respiratory motion management under free breathing conditions. In parallel to the treatment, the volumetric patient anatomy was captured and used to calculate the applied dose. Subsequently, the individual doses were warped back to the planning grid to obtain the actual dose accumulated over the entire treatment duration. Ultimately, the planned dose was validated by comparison with the accumulated dose. Representative for a site subject to breathing modulation, two kidney cases (25 Gy target dose) demonstrated the working principle on volunteer data and simulated delivery. The proposed workflow successfully showed its ability to track local dosimetric changes. Integration of the on-line anatomy information could reveal local dose variations −2.3–1.5 Gy in the target volume of a volunteer dataset. In the adjacent organs at risk, high local dose errors ranging from −2.5 to 1.9 Gy could be traced back.