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Modeling daily changes in organ-at-risk anatomy in a cohort of pancreatic cancer patients

Authors :
Alba Magallon-Baro
Andras Zolnay
M. Milder
Patrick V. Granton
Joost J. Nuyttens
Mauro Loi
Mischa S. Hoogeman
Radiotherapy
Source :
Radiotherapy and Oncology, 134, 127-134. Elsevier Ireland Ltd
Publication Year :
2019

Abstract

Purpose To characterize daily geometrical variations of gastrointestinal organs with respect to pancreatic tumors, through a population-based statistical model. Materials and methods The study included 131 CT scans from 35 pancreatic cancer patients treated with Stereotactic Body Radiotherapy (SBRT). For each patient, day-to-day anatomical variations of the stomach, the duodenum and the bowel were assessed from the deformation vector fields (DVF) obtained by non-rigidly registering the contours of the fractions to the planning CT scans. For the whole population, day-to-day motion-deformation patterns were abstracted using principal component analysis (PCA) on the set of DVFs mapped on a reference patient. Based on these geometrical variations, anatomies were generated to create population-based dose-volume histograms (DVH) per patient, which were also compared to clinical values. Results Through PCA, the most dominant directions of daily deformations were localized in the abdominal organs. Common patterns were found, such as stomach contraction–expansion in the anterior–posterior direction ranging from 5 to 13 mm, and superior-inferior deformations on the bowel from 7 to 14 mm. The duodenum resulted to move laterally, but in a lesser extent (4–8 mm). The population-based DVHs derived from the model mostly included the daily DVHs observed in the clinic (in >90% of the cases). Conclusions Anatomical variations influence the delivered doses to healthy organs during SBRT. A motion model was successfully built and explored to extract the larger directions of movement of the gastrointestinal organs. Day-to-day motion modeling can potentially be used to account for geometrical uncertainties in future plan optimization and in online adaptive strategies.

Details

ISSN :
01678140
Volume :
134
Database :
OpenAIRE
Journal :
Radiotherapy and Oncology
Accession number :
edsair.doi.dedup.....288a8f01fab9c74e24a66c393f8429a7