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Massively parallel functional photoacoustic computed tomography of the human brain

Na, Shuai and Russin, Jonathan J. and Lin, Li and Yuan, Xiaoyun and Hu, Peng and Jann, Kay B. and Yan, Lirong and Maslov, Konstantin and Shi, Junhui and Wang, Danny J. and Liu, Charles Y. and Wang, Lihong V. (2021) Massively parallel functional photoacoustic computed tomography of the human brain. Nature Biomedical Engineering . ISSN 2157-846X. doi:10.1038/s41551-021-00735-8. (In Press) https://resolver.caltech.edu/CaltechAUTHORS:20210601-125253304

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Abstract

Blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging of the human brain requires bulky equipment for the generation of magnetic fields. Photoacoustic computed tomography obviates the need for magnetic fields by using light and sound to measure deoxyhaemoglobin and oxyhaemoglobin concentrations to then quantify oxygen saturation and blood volumes. Yet, the available imaging speeds, fields of view (FOV), sensitivities and penetration depths have been insufficient for functional imaging of the human brain. Here, we show that massively parallel ultrasonic transducers arranged hemispherically around the human head can produce tomographic images of the brain with a 10-cm-diameter FOV and spatial and temporal resolutions of 350 µm and 2 s, respectively. In patients who had a hemicraniectomy, a comparison of functional photoacoustic computed tomography and 7 T BOLD functional magnetic resonance imaging showed a strong spatial correspondence in the same FOV and a high temporal correlation between BOLD signals and photoacoustic signals, with the latter enabling faster detection of functional activation. Our findings establish the use of photoacoustic computed tomography for human brain imaging.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1038/s41551-021-00735-8DOIArticle
https://rdcu.be/clIFYPublisherFree ReadCube access
https://doi.org/10.5061/dryad.sxksn0310DOIData
https://doi.org/10.5281/zenodo.4615721DOICode
ORCID:
AuthorORCID
Na, Shuai0000-0003-2083-0047
Lin, Li0000-0002-0517-8436
Yuan, Xiaoyun0000-0002-7914-3658
Hu, Peng0000-0002-2933-1239
Maslov, Konstantin0000-0003-3408-8840
Shi, Junhui0000-0002-5741-2781
Wang, Danny J.0000-0002-0840-7062
Liu, Charles Y.0000-0001-6423-8577
Wang, Lihong V.0000-0001-9783-4383
Additional Information:© 2021 Nature Publishing Group. Received 10 August 2020; Accepted 21 April 2021; Published 31 May 2021. We thank G. Corral-Leyva for patient care and Y. Luo for discussion on the potential of artificial intelligence in advancing PACT. This work was sponsored by the US National Institutes of Health (NIH) grants R35 CA220436 (Outstanding Investigator Award), U01 NS099717 (BRAIN Initiative), R01 NS102213, R01 NS114382 and R01 EB028297, and by Caltech internal funds (PPF0021). Data availability: The main data supporting the results in this study are available within the paper and its Supplementary Information. 3D functional image stacks of fMRI and fPACT for participant 3 (FT and LP session 1) are available online (https://doi.org/10.5061/dryad.sxksn0310). Other data are too large to be publicly shared, yet they are available for research purposes from the corresponding authors on reasonable request. Code availability: The fMRI data were processed using the freely available software package SPM12. The codes used to extract the fPACT function are available online (https://doi.org/10.5281/zenodo.4615721). The reconstruction codes based on the universal backprojection algorithm, the system control software and the data collection software are proprietary and used in licensed technologies, yet they are available from the corresponding authors on reasonable request. These authors contributed equally: Shuai Na, Jonathan J. Russin, Li Lin, Xiaoyun Yuan. Author Contributions: L.V.W., C.Y.L., S.N. and J.J.R. conceived the project. S.N., J.J.R., C.Y.L. and L.V.W. designed the study. L.L., S.N., K.M. and J.S. built the system hardware. S.N. developed the system software. S.N., X.Y. and J.J.R. performed the PACT experiments. K.B.J. and L.Y. performed the MRI experiments. P.H., X.Y. and S.N. developed the reconstruction algorithms. X.Y., S.N., K.B.J., J.J.R., C.Y.L., D.J.W. and L.V.W. analysed and interpreted the data. J.J.R. and C.Y.L. recruited the participants. S.N., J.J.R. and X.Y. wrote the manuscript with input from all of the authors. L.V.W., C.Y.L. and D.J.W. supervised the study. Competing interests: L.V.W. has a financial interest in Microphotoacoustics Inc., CalPACT LLC and Union Photoacoustic Technologies Ltd., which, however, did not support this work. K.M. has a financial interest in Microphotoacoustics, Inc. The other authors declare no competing interests. Peer review information: Nature Biomedical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.
Funders:
Funding AgencyGrant Number
NIHR35 CA220436
NIHU01 NS099717
NIHR01 NS102213
NIHR01 NS114382
NIHR01 EB028297
CaltechPPF0021
Subject Keywords:Biomedical engineering; Electrical and electronic engineering; Imaging and sensing; Imaging techniques; Neuroscience
DOI:10.1038/s41551-021-00735-8
Record Number:CaltechAUTHORS:20210601-125253304
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210601-125253304
Official Citation:Na, S., Russin, J.J., Lin, L. et al. Massively parallel functional photoacoustic computed tomography of the human brain. Nat Biomed Eng (2021). https://doi.org/10.1038/s41551-021-00735-8
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109327
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:01 Jun 2021 20:22
Last Modified:01 Jun 2021 20:22

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