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Abstract
A feature issue is being presented by a team of guest editors containing papers based on contributed submissions including studies presented at Optics and the Brain, held April 24-27, 2023 as part of Optica Biophotonics Congress: Optics in the Life Sciences, in Vancouver, Canada
© 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
We introduce the Biomedical Optics Express feature issue for Optics and the Brain, held April 24-27, 2023 as part of Optica Biophotonics Congress: Optics in the Life Sciences, in Vancouver, Canada. This meeting served as a forum for discussion of existing and emerging techniques as well as future directions to shed new light on the healthy and diseased brain. Optics offers a unique toolkit for multiscale imaging of the living and intact brain from the microscopic to macroscopic scale. At the same time, genetic labeling strategies provide optical contrast to image neural function, and optogenetics permits the control of cellular function with light. To cover the expertise needed to achieve these diverse goals, the meeting brings together engineers, optical and medical scientists, biologists, chemists and physicians. The articles within this special issue represent the broad scope of the community that participates in Optics and the Brain.
Diffuse optics can probe centimeters deep in human tissue with near-infrared light, to reach the living brain non-invasively. A review article [1] highlights the measurement of oxidized cytochrome-c-oxidase using a non-invasive optical imaging method of near-infrared spectroscopy (NIRS) in adults and neonates. Another study [2] using conventional hemoglobin NIRS shows that a virtual reality game task can modulate brain functional networks better than simple grasping movements. This finding has implications for the recovery of grasping abilities in post-stroke patients with hand paralysis.
Optical methods also elucidate structural and biochemical composition of brain tissue. In cancer diagnostics, another study [3] investigated the use of laser-induced breakdown spectroscopy (LIBS) and electrical spark-assisted laser-induced breakdown spectroscopy (SA-LIBS) in differentiating glioblastoma (GBM) and oligodendroglioma (OG) against non-tumor infiltrated brain tissues. The authors showed advantages of SA-LIBS in discriminating tumorous tissues, as well as multiparameter characterization. In another work [4], a two-photon microendoscope intended for label-free imaging in stereotactic neurosurgery was demonstrated. The device was small enough to fit in a surgical cannula. Another work [5] demonstrated label-free imaging of myelin in a block of human brain tissue using serial-sectioning polarization sensitive optical coherence tomography and quantitative birefringence microscopy. These technologies will aid in understanding the brain’s complex fiber architecture over microscopic to mesoscopic scales. Finally, reminding us that ‘optics’ extends to the x-ray regime, another study [6] showed the viability of speckle-based phase contrast imaging and demonstrated the potential benefit of the dark-field modality for virtual histology of brain tissue.
With the advent of optogenetics, advanced optical systems can now control and image brain circuits with high spatiotemporal precision in 3D. One study [7] demonstrated an improvement to Fast Light Targeting (FLiT), a technique previously developed for 3D holographic patterning with rapid temporal sub-millisecond switching that is not limited by the refresh rate of the spatial light modulator. The authors’ novel design shows better performance with reduced aberrations. Another work [8] demonstrated a simple design for two-photon optogenetic holographic stimulation with multiple laser wavelengths, a fiber bundle, and spatial light modulator. The simplified approach can be used to perform scanless two-photon imaging combined with optogenetic stimulation to modulate and record activity at the individual neuron-level.
Overall this special issue highlights the breadth of technologies and applications represented by the Optics and the Brain community, and the wide range of spatial scales and brain observables that can be measured or modulated by optical methods. The articles in this special issue represent a just small sample of the high-quality brain-related research published in Biomedical Optics Express recently [1–46]. We thank the Optica editorial board and staff for supporting this effort, and we express gratitude to the community at large for providing high quality submissions and reviews for this special issue.
Disclosures
Optovue, Inc. (VJS).
References
1. G. Leadley, T. Austin, G. Bale, et al., “Review of measurements and imaging of cytochrome-c-oxidase in humans using near-infrared spectroscopy: an update,” Biomed. Opt. Express 15(1), 162–184 (2024). [CrossRef]
2. G. Shao, G. Xu, C. Huo, et al., “Effect of the VR-guided grasping task on the brain functional network,” Biomed. Opt. Express 15(1), 77–94 (2024). [CrossRef]
3. P. Mohammadimatin, P. Parvin, A. Jafargholi, et al., “Signal enhancement in spark-assisted laser-induced breakdown spectroscopy for discrimination of glioblastoma and oligodendroglioma lesions,” Biomed. Opt. Express 14(11), 5795–5816 (2023). [CrossRef]
4. T. A. Welton, N. M. George, B. N. Ozbay, et al., “Two-photon microendoscope for label-free imaging in stereotactic neurosurgery,” Biomed. Opt. Express 14(7), 3705–3725 (2023). [CrossRef]
5. N. Blanke, S. Chang, A. Novoseltseva, et al., “Multiscale label-free imaging of myelin in human brain tissue with polarization-sensitive optical coherence tomography and birefringence microscopy,” Biomed. Opt. Express 14(11), 5946–5964 (2023). [CrossRef]
6. S. Savatović, M.-C. Zdora, F. De Marco, et al., “Multi-resolution X-ray phase-contrast and dark-field tomography of human cerebellum with near-field speckles,” Biomed. Opt. Express 15(1), 142–161 (2024). [CrossRef]
7. C. Telliez, V. De Sars, V. Emiliani, et al., “Descanned fast light targeting (deFLiT) two-photon optogenetics,” Biomed. Opt. Express 14(12), 6222–6232 (2023). [CrossRef]
8. A. Lorca-Camara, C. Tourain, V. de Sars, et al., “Multicolor two-photon light-patterning microscope exploiting the spatio-temporal properties of a fiber bundle,” Biomed. Opt. Express 15(4), 2094–2109 (2024). [CrossRef]
9. A. Afshari, R. B. Saager, D. Burgos, et al., “Evaluation of the robustness of cerebral oximetry to variations in skin pigmentation using a tissue-simulating phantom,” Biomed. Opt. Express 13(5), 2909–2928 (2022). [CrossRef]
10. M. Chourrout, H. Rositi, E. Ong, et al., “Brain virtual histology with X-ray phase-contrast tomography Part I: whole-brain myelin mapping in white-matter injury models,” Biomed. Opt. Express 13(3), 1620–1639 (2022). [CrossRef]
11. M. Chourrout, M. Roux, C. Boisvert, et al., “Brain virtual histology with X-ray phase-contrast tomography Part II:3D morphologies of amyloid-beta plaques in Alzheimer's disease models,” Biomed. Opt. Express 13(3), 1640–1653 (2022). [CrossRef]
12. G. de Vito, L. Turrini, C. Müllenbroich, et al., “Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy,” Biomed. Opt. Express 13(3), 1516–1536 (2022). [CrossRef]
13. E. J. Galvez, B. Sharma, F. K. Williams, et al., “Decoherence of photon entanglement by transmission through brain tissue with Alzheimer's disease,” Biomed. Opt. Express 13(12), 6621–6630 (2022). [CrossRef]
14. F. C. Hsu, C.-Y. Lin, Y. Y. Hu, et al., “Light-field microscopy with temporal focusing multiphoton illumination for scanless volumetric bioimaging,” Biomed. Opt. Express 13(12), 6610–6620 (2022). [CrossRef]
15. Y. Hu, B. Lafci, A. Luzgin, et al., “Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging,” Biomed. Opt. Express 13(9), 4817–4833 (2022). [CrossRef]
16. N. Katta, A. D. Estrada, A. B. McErloy, et al., “Fiber-laser platform for precision brain surgery,” Biomed. Opt. Express 13(4), 1985–1994 (2022). [CrossRef]
17. D. Li, L. Deng, Z. Hu, et al., “Optical clearing imaging assisted evaluation of urokinase thrombolytic therapy on cerebral vessels with different sizes,” Biomed. Opt. Express 13(6), 3243–3258 (2022). [CrossRef]
18. Y. Li, T. Ren, J. Li, et al., “Multi-perspective label based deep learning framework for cerebral vasculature segmentation in whole-brain fluorescence images,” Biomed. Opt. Express 13(6), 3657–3671 (2022). [CrossRef]
19. Z. Liang, Y. Wang, H. Tian, et al., “Spatial complexity method for tracking brain development and degeneration using functional near-infrared spectroscopy,” Biomed. Opt. Express 13(3), 1718–1736 (2022). [CrossRef]
20. C. J. Liu, W. Ammon, R. J. Jones, et al., “Refractive-index matching enhanced polarization sensitive optical coherence tomography quantification in human brain tissue,” Biomed. Opt. Express 13(1), 358–372 (2022). [CrossRef]
21. M. Malivert, F. Harms, C. Veilly, et al., “Active image optimization for lattice light sheet microscopy in thick samples,” Biomed. Opt. Express 13(12), 6211–6228 (2022). [CrossRef]
22. A. A. Moiseev, K. A. Achkasova, E. B. Kiseleva, et al., “Brain white matter morphological structure correlation with its optical properties estimated from optical coherence tomography (OCT) data,” Biomed. Opt. Express 13(4), 2393–2413 (2022). [CrossRef]
23. C. S. Poon, D. S. Langri, B. Rinehart, et al., “First-in-clinical application of a time-gated diffuse correlation spectroscopy system at 1064 nm using superconducting nanowire single photon detectors in a neuro intensive care unit,” Biomed. Opt. Express 13(3), 1344–1356 (2022). [CrossRef]
24. S. Skyrman, G. Burström, M. Lai, et al., “Diffuse reflectance spectroscopy sensor to differentiate between glial tumor and healthy brain tissue: a proof-of-concept study,” Biomed. Opt. Express 13(12), 6470–6483 (2022). [CrossRef]
25. O. D. Supekar, A. Sias, S. R. Hansen, et al., “Miniature structured illumination microscope for in vivo 3D imaging of brain structures with optical sectioning,” Biomed. Opt. Express 13(4), 2530–2541 (2022). [CrossRef]
26. M. A. Volynsky, O. V. Mamontov, A. V. Osipchuk, et al., “Study of cerebrovascular reactivity to hypercapnia by imaging photoplethysmography to develop a method for intraoperative assessment of the brain functional reserve,” Biomed. Opt. Express 13(1), 184–196 (2022). [CrossRef]
27. J. Wahl, E. Klint, M. Hallbeck, et al., “Impact of preprocessing methods on the Raman spectra of brain tissue,” Biomed. Opt. Express 13(12), 6763–6777 (2022). [CrossRef]
28. Y. Wang, R. Zhang, Q. Chen, et al., “Visualization of blood-brain barrier disruption with dual-wavelength high-resolution photoacoustic microscopy,” Biomed. Opt. Express 13(3), 1537–1550 (2022). [CrossRef]
29. S. Wojtkiewicz, K. Bejm, A. Liebert, et al., “Lock-in functional near-infrared spectroscopy for measurement of the haemodynamic brain response,” Biomed. Opt. Express 13(4), 1869–1887 (2022). [CrossRef]
30. L. Wu, Y. Wang, B. Liao, et al., “Temperature dependent terahertz spectroscopy and imaging of orthotopic brain gliomas in mouse models,” Biomed. Opt. Express 13(1), 93–104 (2022). [CrossRef]
31. M. M. Wu, K. Perdue, S.-T. Chan, et al., “Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models,” Biomed. Opt. Express 13(3), 1131–1151 (2022). [CrossRef]
32. H. Ye, X. Xu, J. Wang, et al., “Polarization effects on the fluorescence emission of zebrafish neurons using light-sheet microscopy,” Biomed. Opt. Express 13(12), 6733–6744 (2022). [CrossRef]
33. E. Baria, F. Giordano, R. Guerrini, et al., “Dysplasia and tumor discrimination in brain tissues by combined fluorescence, Raman, and diffuse reflectance spectroscopies,” Biomed. Opt. Express 14(3), 1256–1275 (2023). [CrossRef]
34. C. Chen, Y. Tang, Y. Tan, et al., “Three-dimensional cerebral vasculature topological parameter extraction of transgenic zebrafish embryos with a filling-enhancement deep learning network,” Biomed. Opt. Express 14(2), 971–984 (2023). [CrossRef]
35. L. Felger, O. Rodríguez-Núñez, R. Gros, et al., “Robustness of the wide-field imaging Mueller polarimetry for brain tissue differentiation and white matter fiber tract identification in a surgery-like environment: an ex vivo study,” Biomed. Opt. Express 14(5), 2400–2415 (2023). [CrossRef]
36. R. M. Forti, L. J. Hobson, E. J. Benson, et al., “Non-invasive diffuse optical monitoring of cerebral physiology in an adult swine-model of impact traumatic brain injury,” Biomed. Opt. Express 14(6), 2432–2448 (2023). [CrossRef]
37. M. Ge, Y. Wang, T. Wu, et al., “Serum-based Raman spectroscopic diagnosis of blast-induced brain injury in a rat model,” Biomed. Opt. Express 14(7), 3622–3634 (2023). [CrossRef]
38. S. Mahler, Y. X. Huang, M. Liang, et al., “Assessing depth sensitivity in laser interferometry speckle visibility spectroscopy (iSVS) through source-to-detector distance variation and cerebral blood flow monitoring in humans and rabbits,” Biomed. Opt. Express 14(9), 4964–4978 (2023). [CrossRef]
39. W. Ren, X. L. Deán-Ben, Z. Skachokova, et al., “Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography,” Biomed. Opt. Express 14(3), 1192–1204 (2023). [CrossRef]
40. T. Shan, H. Yang, S. Jiang, et al., “Monitoring neonatal brain hemorrhage progression by photoacoustic tomography,” Biomed. Opt. Express 14(1), 118–127 (2023). [CrossRef]
41. T. M. Urner, K. R. Cowdrick, R. O. Brothers, et al., “Normative cerebral microvascular blood flow waveform morphology assessed with diffuse correlation spectroscopy,” Biomed. Opt. Express 14(7), 3635–3653 (2023). [CrossRef]
42. N. Wang, C.-Y. Lee, H.-C. Park, et al., “Deep learning-based optical coherence tomography image analysis of human brain cancer,” Biomed. Opt. Express 14(1), 81–88 (2023). [CrossRef]
43. G. Xu, C. Huo, J. Yin, et al., “Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients,” Biomed. Opt. Express 14(8), 4217–4236 (2023). [CrossRef]
44. F. Yang, W. Ding, X. Fu, et al., “Photoacoustic elasto-viscography and optical coherence microscopy for multi-parametric ex vivo brain imaging,” Biomed. Opt. Express 14(11), 5615–5628 (2023). [CrossRef]
45. Y. Zhang, D. Liu, T. Li, et al., “CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface,” Biomed. Opt. Express 14(6), 2934–2954 (2023). [CrossRef]
46. Y. Zhu, J. Shi, T. E. G. Alvarez-Arenas, et al., “Noncontact longitudinal shear wave imaging for the evaluation of heterogeneous porcine brain biomechanical properties using optical coherence elastography,” Biomed. Opt. Express 14(10), 5113–5126 (2023). [CrossRef]