Model-based navigation of transcranial focused ultrasound neuromodulation in humans: Application to targeting of the amygdala and thalamus.

Transcranial focused ultrasound (tFUS) acoustic modeling hybrid angular spectrum low intensity focused ultrasound pulsation (LIFUP) neuronavigation

Journal

Brain stimulation
ISSN: 1876-4754
Titre abrégé: Brain Stimul
Pays: United States
ID NLM: 101465726

Informations de publication

Date de publication:
31 Jul 2024
Historique:
received: 21 02 2024
revised: 22 07 2024
accepted: 29 07 2024
medline: 3 8 2024
pubmed: 3 8 2024
entrez: 2 8 2024
Statut: aheadofprint

Résumé

Transcranial focused ultrasound (tFUS) neuromodulation has shown promise in animals but is challenging to translate to humans because of the thicker skull that heavily scatters ultrasound waves. We develop and disseminate a model-based navigation (MBN) tool for acoustic dose delivery in the presence of skull aberrations that is easy to use by non-specialists. We pre-compute acoustic beams for thousands of virtual transducer locations on the scalp of the subject under study. We use the hybrid angular spectrum solver mSOUND, which runs in ∼4 seconds per solve per CPU yielding pre-computation times under one hour for scalp meshes with up to 4,000 faces and a parallelization factor of 5. We combine this pre-computed set of beam solutions with optical tracking, thus allowing real-time display of the tFUS beam as the operator freely navigates the transducer around the subject' scalp. We assess the impact of MBN versus line-of-sight targeting (LOST) positioning in simulations of 13 subjects. Our navigation tool has a display refresh rate of ∼10 Hz. In our simulations, MBN increased the acoustic dose in the thalamus and amygdala by 8-67% compared to LOST and avoided complete target misses that affected 10-20% of LOST cases. MBN yields a lower variability of the deposited dose across subjects than LOST. MBN may yield greater and more consistent (less variable) ultrasound dose deposition than transducer placement with line-of-sight targeting, and thus may become a helpful tool to improve the efficacy of tFUS neuromodulation.

Sections du résumé

BACKGROUND BACKGROUND
Transcranial focused ultrasound (tFUS) neuromodulation has shown promise in animals but is challenging to translate to humans because of the thicker skull that heavily scatters ultrasound waves.
OBJECTIVE OBJECTIVE
We develop and disseminate a model-based navigation (MBN) tool for acoustic dose delivery in the presence of skull aberrations that is easy to use by non-specialists.
METHODS METHODS
We pre-compute acoustic beams for thousands of virtual transducer locations on the scalp of the subject under study. We use the hybrid angular spectrum solver mSOUND, which runs in ∼4 seconds per solve per CPU yielding pre-computation times under one hour for scalp meshes with up to 4,000 faces and a parallelization factor of 5. We combine this pre-computed set of beam solutions with optical tracking, thus allowing real-time display of the tFUS beam as the operator freely navigates the transducer around the subject' scalp. We assess the impact of MBN versus line-of-sight targeting (LOST) positioning in simulations of 13 subjects.
RESULTS RESULTS
Our navigation tool has a display refresh rate of ∼10 Hz. In our simulations, MBN increased the acoustic dose in the thalamus and amygdala by 8-67% compared to LOST and avoided complete target misses that affected 10-20% of LOST cases. MBN yields a lower variability of the deposited dose across subjects than LOST.
CONCLUSIONS CONCLUSIONS
MBN may yield greater and more consistent (less variable) ultrasound dose deposition than transducer placement with line-of-sight targeting, and thus may become a helpful tool to improve the efficacy of tFUS neuromodulation.

Identifiants

pubmed: 39094682
pii: S1935-861X(24)00134-7
doi: 10.1016/j.brs.2024.07.019
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Competing Interest none

Auteurs

Mohammad Daneshzand (M)

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA; Harvard Medical School, Boston MA USA.

Bastien Guerin (B)

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA; Harvard Medical School, Boston MA USA. Electronic address: bguerin@mgh.harvard.edu.

Parker Kotlarz (P)

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA; Harvard Medical School, Boston MA USA.

Tina Chou (T)

Harvard Medical School, Boston MA USA; Department of Psychiatry, Massachusetts General Hospital, Charlestown MA USA.

Darin D Dougherty (DD)

Harvard Medical School, Boston MA USA; Department of Psychiatry, Massachusetts General Hospital, Charlestown MA USA.

Brian L Edlow (BL)

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA; Harvard Medical School, Boston MA USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston MA USA.

Aapo Nummenmaa (A)

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA; Harvard Medical School, Boston MA USA.

Classifications MeSH