The noise navigator for MRI-guided radiotherapy: an independent method to detect physiological motion.


Journal

Physics in medicine and biology
ISSN: 1361-6560
Titre abrégé: Phys Med Biol
Pays: England
ID NLM: 0401220

Informations de publication

Date de publication:
18 06 2020
Historique:
pubmed: 25 4 2020
medline: 21 10 2020
entrez: 25 4 2020
Statut: epublish

Résumé

Motion is problematic during radiotherapy as it could lead to potential underdosage of the tumor, and/or overdosage in organs-at-risk. A solution is adaptive radiotherapy guided by magnetic resonance imaging (MRI). MRI allows for imaging of target volumes and organs-at-risk before and during treatment delivery with superb soft tissue contrast in any desired orientation, enabling motion management by means of (real-time) adaptive radiotherapy. The noise navigator, which is independent of the MR signal, could serve as a secondary motion detection method in synergy with MR imaging. The feasibility of respiratory motion detection by means of the noise navigator was demonstrated previously. Furthermore, from electromagnetic simulations we know that the noise navigator is sensitive to tissue displacement and thus could in principle be used for the detection of various types of motion. In this study we demonstrate the detection of various types of motion for three anatomical use cases of MRI-guided radiotherapy, i.e. torso (bulk movement and variable breathing), head-and-neck (swallowing) and cardiac. Furthermore, it is shown that the noise navigator can detect bulk movement, variable breathing and swallowing on a hybrid 1.5 T MRI-linac system. Cardiac activity detection through the noise navigator seems feasible in an MRI-guided radiotherapy setting, but needs further optimization. The noise navigator is a versatile and fast (millisecond temporal resolution) motion detection method independent of MR signal that could serve as an independent verification method to detect the occurrence of motion in synergy with real-time MRI-guided radiotherapy.

Identifiants

pubmed: 32330921
doi: 10.1088/1361-6560/ab8cd8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

12NT01

Auteurs

R J M Navest (RJM)

Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands. Computational Imaging Group for MRI Diagnostics & Therapy, Centre for Image Sciences, Universiy Medical Center Utrecht, Utrecht, Netherlands.

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Classifications MeSH