Optimizing 4-dimensional magnetic resonance imaging data sampling for respiratory motion analysis of pancreatic tumors.

Autor:	Stemkens B; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: b.stemkens@umcutrecht.nl., Tijssen RH; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., de Senneville BD; Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands; L'Institut de Mathématiques de Bordeaux, Unité Mixte de Recherche 5251, Centre National de la Recherche Scientifique/University of Bordeaux, Bordeaux, France., Heerkens HD; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., van Vulpen M; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., Lagendijk JJ; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., van den Berg CA; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
Jazyk:	angličtina
Zdroj:	International journal of radiation oncology, biology, physics [Int J Radiat Oncol Biol Phys] 2015 Mar 01; Vol. 91 (3), pp. 571-8. Date of Electronic Publication: 2015 Jan 13.
DOI:	10.1016/j.ijrobp.2014.10.050
Abstrakt:	Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest 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. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient 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 a small number of pancreatic cancer patients. (Copyright © 2015 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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