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Enabling automated magnetic resonance imaging-based targeting assessment during dipole field navigation
Author(s) -
Maxime Latulippe,
Ouajdi Felfoul,
Pierre E. Dupont,
Sylvain Martel
Publication year - 2016
Publication title -
applied physics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.182
H-Index - 442
eISSN - 1077-3118
pISSN - 0003-6951
DOI - 10.1063/1.4941925
Subject(s) - scanner , computer science , magnetic resonance imaging , navigation system , computer vision , artificial intelligence , medicine , radiology
The magnetic navigation of drugs in the vascular network promises to increase the efficacy and reduce the secondary toxicity of cancer treatments by targeting tumors directly. Recently, dipole field navigation (DFN) was proposed as the first method achieving both high field and high navigation gradient strengths for whole-body interventions in deep tissues. This is achieved by introducing large ferromagnetic cores around the patient inside a magnetic resonance imaging (MRI) scanner. However, doing so distorts the static field inside the scanner, which prevents imaging during the intervention. This limitation constrains DFN to open-loop navigation, thus exposing the risk of a harmful toxicity in case of a navigation failure. Here, we are interested in periodically assessing drug targeting efficiency using MRI even in the presence of a core. We demonstrate, using a clinical scanner, that it is in fact possible to acquire, in specific regions around a core, images of sufficient quality to perform this task. ...

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