Functional Time Domain Diffuse Correlation Spectroscopy.

cerebral blood flow diffuse correlation spectroscopy (DCS) fNIRS (functional near infrared spectroscopy) neuroimaging (anatomic and functional) optical neuroimaging

Journal

Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481

Informations de publication

Date de publication:
2022
Historique:
received: 29 04 2022
accepted: 23 06 2022
entrez: 18 8 2022
pubmed: 19 8 2022
medline: 19 8 2022
Statut: epublish

Résumé

Time-domain diffuse correlation spectroscopy (TD-DCS) offers a novel approach to high-spatial resolution functional brain imaging based on the direct quantification of cerebral blood flow (CBF) changes in response to neural activity. However, the signal-to-noise ratio (SNR) offered by previous TD-DCS instruments remains a challenge to achieving the high temporal resolution needed to resolve perfusion changes during functional measurements. Here we present a next-generation optimized functional TD-DCS system that combines a custom 1,064 nm pulse-shaped, quasi transform-limited, amplified laser source with a high-resolution time-tagging system and superconducting nanowire single-photon detectors (SNSPDs). System characterization and optimization was conducted on homogenous and two-layer intralipid phantoms before performing functional CBF measurements in six human subjects. By acquiring CBF signals at over 5 Hz for a late gate start time of the temporal point spread function (TPSF) at 15 mm source-detector separation, we demonstrate for the first time the measurement of blood flow responses to breath-holding and functional tasks using TD-DCS.

Identifiants

pubmed: 35979338
doi: 10.3389/fnins.2022.932119
pmc: PMC9377452
doi:

Types de publication

Journal Article

Langues

eng

Pagination

932119

Subventions

Organisme : NINDS NIH HHS
ID : F31 NS118753
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS100750
Pays : United States
Organisme : NIBIB NIH HHS
ID : U01 EB028660
Pays : United States

Informations de copyright

Copyright © 2022 Ozana, Lue, Renna, Robinson, Martin, Zavriyev, Carr, Mazumder, Blackwell, Franceschini and Carp.

Déclaration de conflit d'intérêts

MAF has a financial interest in 149 Medical, Inc., a company developing DCS technology for assessing and monitoring cerebral blood flow in newborn infants. MAF’s interests were reviewed and managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflicts of interest policies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Nisan Ozana (N)

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

Niyom Lue (N)

Massachusetts Institute of Technology Lincoln Laboratory, Lexington, MA, United States.

Marco Renna (M)

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

Mitchell B Robinson (MB)

Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Massachusetts Institute of Technology, Health Sciences and Technology Program, Cambridge, MA, United States.

Alyssa Martin (A)

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

Alexander I Zavriyev (AI)

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

Bryce Carr (B)

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

Dibbyan Mazumder (D)

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

Megan H Blackwell (MH)

Massachusetts Institute of Technology Lincoln Laboratory, Lexington, MA, United States.

Maria A Franceschini (MA)

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

Stefan A Carp (SA)

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

Classifications MeSH