Improved feedback loop control for ultrasound-assisted blood-brain barrier opening in non-human primates based on the discrimination between intra- and extra-cerebral cavitation.
Paul Mondou, Gwenaël Pagé, Corentin Cornu, Clémentine Morisset, Elias Djaballah, Audrey Fayard, Sophie Lecourtois, Marion Gay, Maxime Roustan, Julien Flament, Alexandre Vignaud, Sébastien Mériaux, Qi Zhu, Romina Aron Badin, Anthony Novell, Benoit Larrat
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引用次数: 0
Abstract
Objective. Temporary, non-invasive, and localized permeabilization of the blood-brain barrier (BBB) can be achieved through focused ultrasound and microbubbles (MB). This technique has been extensively employed in rodent and non-human primate (NHP) studies for testing various drugs but requires precise control of ultrasonic pressure. However, controlling cavitation in NHP is challenging due to their thicker skull inducing strong ultrasonic attenuation. Furthermore, extra-cranial cavitation may occur masking the cavitation signal at the focal region (cerebral cavitation). Particularly in larger male NHP, temporal muscles are highly perfused and filled with MB.Approach. This study proposes a feedback loop control strategy to distinguish between intra- and extra-cerebral cavitation by analyzing broadband noise recorded by passive cavitation detection sensors.Main results. The frequency-dependent low-pass filtering effect by the skull allows differentiation of distinct frequency components, providing insights into cavitation origin. The present study involved 17 BBB opening experiments in NHP.Significance. Although successful BBB disruption can be achieved in NHP with thin temporal muscles (<5 mm) using a regular feedback loop algorithm, NHP having thicker muscles (>15 mm) require the use of an optimized algorithm able to specifically extract the signature of intra-cerebral cavitation.
期刊介绍:
The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry