Optimizing 4-dimensional magnetic resonance imaging data sampling for respiratory motion analysis of pancreatic tumors
DENIS DE SENNEVILLE, Baudouin
Institut de Mathématiques de Bordeaux [IMB]
Image sciences institute - University of Utrecht [ISI]
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Institut de Mathématiques de Bordeaux [IMB]
Image sciences institute - University of Utrecht [ISI]
DENIS DE SENNEVILLE, Baudouin
Institut de Mathématiques de Bordeaux [IMB]
Image sciences institute - University of Utrecht [ISI]
< Réduire
Institut de Mathématiques de Bordeaux [IMB]
Image sciences institute - University of Utrecht [ISI]
Langue
en
Article de revue
Ce document a été publié dans
International Journal of Radiation Oncology, Biology, Physics. 2015, vol. 91, n° 3, p. 571–578
Elsevier
Résumé en anglais
Purpose: To determine the optimum sampling and binning strategy for retrospective reconstruction of 4D-MR data for non-rigid motion characterization of tumor and organs at risk for radiotherapy purposes. Material and ...Lire la suite >
Purpose: To determine the optimum sampling and binning strategy for retrospective reconstruction of 4D-MR data for non-rigid motion characterization of tumor and organs at risk for radiotherapy purposes. Material and Methods: For optimization, we compared two surrogate signals (external respiratory bellows and internal MR navigator), three binning methods (absolute amplitude, phase and a hybrid method, relative amplitude binning) and two MR sampling strategies (cartesian and radial) in terms of efficiency, image quality and robustness. Using the optimized protocol, three pancreatic cancer patients were scanned to calculate the 4D motion. ROI analysis was performed to characterize the respiratory induced motion of the tumor and organs at risk simultaneously.Results: The MRI navigator was found to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Relative amplitude binning offered the best binning in terms of filling efficiency and intra-phase amplitude variation. Radial sampling is most benign for undersampling artifacts and intra-view motion. Motion characterization revealed inter-organ and inter-patient variation, as well as heterogeneity within the tumor. Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in pancreatic cancer patients.< Réduire
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