面向血液动力学的光声显微成像技术及其应用研究

神经影像学技术是研究大脑功能的有效工具。在当前神经影像学领域内，已存在较为成熟的双光子荧光成像技术、宽场荧光成像技术、脑电技术可分别对微观、介观、宏观的神经活动直接进行成像表征，但对于大脑中的另一套重要系统——血管系统，当前较为成熟的功能性核磁共振和功能性超声技术却仅能支持对主干血管或平均血液动力学开展研究，这一方面使得人们在多种与大脑功能相关的血液输送问题上仍然存在争议，另一方面也造成神经活动信息与血液动力学信息难以在微血管层面上相互印证。因此，为了进一步揭开大脑这个复杂系统的神秘面纱，当前脑科学研究领域亟需一种针对血液动力学参数且支持微观、介观成像的新型影像学技术。
光声显微成像技术是突破这一困境的有效方案，该成像技术主要基于光声效应，通过接收由脉冲光激发发色团发出的超声信号进行成像，其具备无标记、无辐射、非侵入等多种适用于生物成像的固有特性，且成像对比度来源于发色团对激光的吸收能力，产生的光声信号幅值可直接指示与大脑活动密切相关的血红蛋白浓度；此外，该技术的成像分辨率取决于聚焦物镜的数值孔径，可达到数微米乃至纳米量级，成像速度可覆盖血液动力学波动频率，且成像视场也可覆盖小鼠大脑皮层。然而，尽管光声显微成像技术的各项性能均可满足脑功能研究需求，但其成像系统通常结构复杂、体积庞大且灵活性差，此类因素使得该技术在脑科学领域的发展较为受限。
因此，本文开展了光声显微脑成像技术研究，具体内容包含验证可行性、研制成像系统以及发展分析方法。可行性验证是所有后续研究的理论基础，其主要推导了光声信号的产生原理以及光声信号与发色团浓度间的线性关系，验证了使用光声信号反映血红蛋白浓度的可行性，以及光声成像技术与现有成熟神经影像学技术的信号同源性。基于理论研究，本文以二维扫描振镜和线聚焦超声探测器为核心器件，以新型旋转式扫描机制为成像基础，研发了适用于小鼠皮层血红蛋白成像的旋转式光学分辨率光声显微镜，相较于经典光声显微成像系统，系统集成度、使用便捷性均得到了大幅提高，可轻易实现对小鼠全皮层范围内微血管的高时空分辨率成像。此外，本文还通过在系统中添加双波长入射模块为成像系统增加了血氧饱和度成像功能，并采用光声相关光谱法为其增加了血液流速成像功能。由成像系统获得的皮层血管光声显微图像则经由结构和功能两种分析方法进行处理，可提取血管区域占比、血管长度、血管分支数、血管总数、血管直径等多种结构性指标，以及低频振幅、神经血管偶联、脑皮层功能连接等多种大脑活动功能信息，用以对皮层血管网络进行多个角度的综合分析。
基于高性能的光声显微成像系统以及与之配套的数据分析方法，本文对小鼠全局癫痫、局灶性癫痫、脑局部电刺激、脑胶质瘤、局部肢体刺激等多个动物模型开展了深入研究。具体地，本文使用功能分析展示了两种癫痫模型中大脑异常活动与功能连接的巨大差异，以及局灶性癫痫中血液动力学异常的传播路径；同时，通过对照局灶性癫痫和脑局部电刺激的大脑活动响应，揭示了脑皮层中躯体感知皮层与运动皮层的长程功能连接；此外，还定量展示了脑胶质瘤对皮层血管网络的促生长作用，对皮层血液动力学响应的干扰作用，以及对脑区功能连接和半脑功能连接的破坏作用。
综上所述，本文设计研发了一套适用于小鼠脑功能研究的光声显微成像系统，以及与之配套的多种数据分析方法，并以此对多种小鼠模型开展了脑功能研究。文中所进行的理论分析和应用研究充分证明了本文所研发的光声显微脑成像技术的脑功能研究能力，为光声成像中的成像系统进步打下了坚实的基础，也为脑科学研究提供了一项面向血液动力学的介观脑功能成像新方法。
 

[1] GHOSH A, GREENBERG M E. Calcium signaling in neurons: molecular mechanisms and cellular consequences[J]. Science, 1995, 268(5208): 239-247.
[2] GRILL-SPECTOR K, HENSON R, MARTIN A. Repetition and the brain: neural models of stimulus-specific effects[J]. Trends in Cognitive Sciences, 2006, 10(1): 14-23.
[3] LU H, LI Y, CHEN M, et al. Brain intelligence: go beyond artificial intelligence[J]. Mobile Networks and Applications, 2018, 23(2): 368-375.
[4] NICOLAS-ALONSO L F, Gomez-Gil J. Brain computer interfaces, a review[J]. Sensors, 2012, 12(2): 1211-1279.
[5] VOS T, LIM S S, ABBAFATI C, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. The Lancet, 2020, 396(10258): 1204-1222.
[6] POO M, DU J, IP N Y, et al. China brain project: basic neuroscience, brain diseases, and brain-inspired computing[J]. Neuron, 2016, 92(3): 591-596.
[7] ZHAO Z, NELSON A R, BETSHOLTZ C, et al. Establishment and dysfunction of the blood-brain barrier[J]. Cell, 2015, 163(5): 1064-1078.
[8] ROY C S, SHERRINGTON C S. On the regulation of the blood-supply of the brain[J]. The Journal of Physiology, 1890, 11(1-2): 85.
[9] KISLER K, NELSON A R, REGE S V, et al. Pericyte degeneration leads to neurovascular uncoupling and limits oxygen supply to brain[J]. Nature Neuroscience, 2017, 20(3): 406-416.
[10] JANELIDZE S, LINDQVIST D, FRANCARDO V, et al. Increased CSF biomarkers of angiogenesis in Parkinson disease[J]. Neurology, 2015, 85(21): 1834-1842.
[11] KRINGELBACH M L, CRUZAT J, CABRAL J, et al. Dynamic coupling of whole-brain neuronal and neurotransmitter systems[J]. Proceedings of the National Academy of Sciences, 2020, 117(17): 9566-9576.
[12] LUO L. Architectures of neuronal circuits[J]. Science, 2021, 373(6559): eabg7285.
[13] BIASIUCCI A, FRANCESCHIELLO B, MURRAY M M. Electroencephalography[J]. Current Biology, 2019, 29(3): R80-R85.
[14] DAITCH A L, FOSTER B L, SCHROUFF J, et al. Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition[J]. Proceedings of the National Academy of Sciences, 2016, 113(46): E7277-E7286.
[15] BALL T, KERN M, MUTSCHLER I, et al. Signal quality of simultaneously recorded invasive and non-invasive EEG[J]. Neuroimage, 2009, 46(3): 708-716.
[16] BOURDILLON P, CUCHERAT M, ISNARD J, et al. Stereo‐electroencephalography‐guided radiofrequency thermocoagulation in patients with focal epilepsy: a systematic review and meta‐analysis[J]. Epilepsia, 2018, 59(12): 2296-2304.
[17] KERTAI M D, WHITLOCK E L, AVIDAN M S. Brain monitoring with electroencephalography and the electroencephalogram-derived bispectral index during cardiac surgery[J]. Anesthesia and Analgesia, 2012, 114(3): 533.
[18] KWON M, HAN S, KIM K, et al. Super-resolution for improving EEG spatial resolution using deep convolutional neural network—feasibility study[J]. Sensors, 2019, 19(23): 5317.
[19] CHEN T W, WARDILL T J, SUN Y, et al. Ultrasensitive fluorescent proteins for imaging neuronal activity[J]. Nature, 2013, 499(7458): 295-300.
[20] RYNES M L, SURINACH D A, LINN S, et al. Miniaturized head-mounted microscope for whole-cortex mesoscale imaging in freely behaving mice[J]. Nature Methods, 2021, 18(4): 417-425.
[21] MIKAMI H, HARMON J, KOBAYASHI H, et al. Ultrafast confocal fluorescence microscopy beyond the fluorescence lifetime limit[J]. Optica, 2018, 5(2): 117-126.
[22] KÖNIG K. Multiphoton microscopy in life sciences[J]. Journal of Microscopy, 2000, 200(2): 83-104.
[23] MILLER D R, JARRETT J W, HASSAN A M, et al. Deep tissue imaging with multiphoton fluorescence microscopy[J]. Current Opinion in Biomedical Engineering, 2017, 4: 32-39.
[24] WU J, LIANG Y, CHEN S, et al. Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo[J]. Nature Methods, 2020, 17(3): 287-290.
[25] SEECK M, KOESSLER L, BAST T, et al. The standardized EEG electrode array of the IFCN[J]. Clinical Neurophysiology, 2017, 128(10): 2070-2077.
[26] BARSON D, HAMODI A S, SHEN X, et al. Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits[J]. Nature Methods, 2020, 17(1): 107-113.
[27] IADECOLA C. The neurovascular unit coming of age: a journey through neurovascular coupling in health and disease[J]. Neuron, 2017, 96(1): 17-42.
[28] OGAWA S, LEE T M, KAY A R, et al. Brain magnetic resonance imaging with contrast dependent on blood oxygenation[J]. proceedings of the National Academy of Sciences, 1990, 87(24): 9868-9872.
[29] JUNG W B, IM G H, JIANG H, et al. Early fMRI responses to somatosensory and optogenetic stimulation reflect neural information flow[J]. Proceedings of the National Academy of Sciences, 2021, 118(11): e2023265118.
[30] HAN S H, EUN S, CHO H J, et al. Improvement of sensitivity and specificity for laminar BOLD fMRI with double spin-echo EPI in humans at 7 T[J]. NeuroImage, 2021, 241: 118435.
[31] WANG D, BUCKNER R L, FOX M D, et al. Parcellating cortical functional networks in individuals[J]. Nature Neuroscience, 2015, 18(12): 1853-1860.
[32] CRADDOCK R C, JAMES G A, HOLTZHEIMER III P E, et al. A whole brain fMRI atlas generated via spatially constrained spectral clustering[J]. Human Brain Mapping, 2012, 33(8): 1914-1928.
[33] CICHY R M, OLIVA A. AM/EEG-fMRI fusion primer: resolving human brain responses in space and time[J]. Neuron, 2020, 107(5): 772-781.
[34] MACÉ E, MONTALDO G, COHEN I, et al. Functional ultrasound imaging of the brain[J]. Nature Methods, 2011, 8(8): 662-664.
[35] RABUT C, CORREIA M, FINEL V, et al. 4D functional ultrasound imaging of whole-brain activity in rodents[J]. Nature Methods, 2019, 16(10): 994-997.
[36] MACE E, MONTALDO G, OSMANSKI B F, et al. Functional ultrasound imaging of the brain: theory and basic principles[J]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2013, 60(3): 492-506.
[37] MACÉ É, MONTALDO G, TRENHOLM S, et al. Whole-brain functional ultrasound imaging reveals brain modules for visuomotor integration[J]. Neuron, 2018, 100(5): 1241-1251. e7.
[38] DIZEUX A, GESNIK M, AHNINE H, et al. Functional ultrasound imaging of the brain reveals propagation of task-related brain activity in behaving primates[J]. Nature Communications, 2019, 10(1): 1-9.
[39] DEMENE C, BARANGER J, BERNAL M, et al. Functional ultrasound imaging of brain activity in human newborns[J]. Science Translational Medicine, 2017, 9(411): eaah6756.
[40] MORONE K A, NEIMAT J S, ROE A W, et al. Review of functional and clinical relevance of intrinsic signal optical imaging in human brain mapping[J]. Neurophotonics, 2017, 4(3): 031220.
[41] PATEL K S, ZHAO M, MA H, et al. Imaging preictal hemodynamic changes in neocortical epilepsy[J]. Neurosurgical Focus, 2013, 34(4): E10.
[42] NAKAMICHI Y, OKUBO K, SATO T, et al. Optical intrinsic signal imaging with optogenetics reveals functional cortico-cortical connectivity at the columnar level in living macaques[J]. Scientific Reports, 2019, 9(1): 1-12.
[43] DUVERNOY H M, DELON S, VANNSON J L. Cortical blood vessels of the human brain[J]. Brain Research Bulletin, 1981, 7(5): 519-579.
[44] GIROUARD H, IADECOLA C. Neurovascular coupling in the normal brain and in hypertension, stroke, and Alzheimer disease[J]. Journal of Applied Physiology, 2006, 100(1): 328-335.
[45] LONGDEN T A, DABERTRAND F, KOIDE M, et al. Capillary K+-sensing initiates retrograde hyperpolarization to increase local cerebral blood flow[J]. Nature Neuroscience, 2017, 20(5): 717-726.
[46] WANG L V, YAO J. A practical guide to photoacoustic tomography in the life sciences[J]. Nature Methods, 2016, 13(8): 627-638.
[47] SARIMOLLAOGLU M, NEDOSEKIN D A, MENYAEV Y A, et al. Nonlinear photoacoustic signal amplification from single targets in absorption background[J]. Photoacoustics, 2014, 2(1): 1-11.
[48] BEARD P. Biomedical photoacoustic imaging[J]. Interface Focus, 2011, 1(4): 602-631.
[49] INSANA M F, BROWN D G. Acoustic scattering theory applied to soft biological tissues[M]//Ultrasonic scattering in biological tissues. CRC Press, 2022: 75-124.
[50] ZHOU J, ZHANG Y, CHEN J K. Non-Fourier heat conduction effect on laser-induced thermal damage in biological tissues[J]. Numerical Heat Transfer, Part A: Applications, 2008, 54(1): 1-19.
[51] KIM K, GUO Z. Thermal relaxation times in biological tissues subjected to pulsed laser irradiation[C]//9th AIAA/ASME Joint Thermophysics and Heat Transfer Conference. 2006: 2938.
[52] QI W, LI T, ZHANG C, et al. Light-controlled precise delivery of NIR-responsive semiconducting polymer nanoparticles with promoted vascular permeability[J]. Advanced Healthcare Materials, 2021, 10(19): 2100569.
[53] NASIRIAVANAKI M, XIA J, WAN H, et al. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain[J]. Proceedings of the National Academy of Sciences, 2014, 111(1): 21-26.
[54] LIN L, HU P, TONG X, et al. High-speed three-dimensional photoacoustic computed tomography for preclinical research and clinical translation[J]. Nature Communications, 2021, 12(1): 1-10.
[55] YAO J, XIA J, MASLOV K I, et al. Noninvasive photoacoustic computed tomography of mouse brain metabolism in vivo[J]. NeuroImage, 2013, 64: 257-266.
[56] GOTTSCHALK S, DEGTYARUK O, MC LARNEY B, et al. Rapid volumetric optoacoustic imaging of neural dynamics across the mouse brain[J]. Nature Biomedical Engineering, 2019, 3(5): 392-401.
[57] YAO J, WANG L, YANG J M, et al. High-speed label-free functional photoacoustic microscopy of mouse brain in action[J]. Nature Methods, 2015, 12(5): 407-410.
[58] ZHU X, HUANG Q, DISPIRITO A, et al. Real-time whole-brain imaging of hemodynamics and oxygenation at micro-vessel resolution with ultrafast wide-field photoacoustic microscopy[J]. Light: Science & Applications, 2022, 11(1): 1-15.
[59] NA S, RUSSIN J J, LIN L, et al. Massively parallel functional photoacoustic computed tomography of the human brain[J]. Nature Biomedical Engineering, 2022, 6(5): 584-592.
[60] TIAN C, ZHANG C, ZHANG H, et al. Spatial resolution in photoacoustic computed tomography[J]. Reports on Progress in Physics, 2021, 84(3): 036701.
[61] GUSEV V E, KARABUTOV A A. Laser optoacoustics[J]. Nasa Sti/recon Technical Report A, 1991, 93: 16842.
[62] DUCK F A. Physical properties of tissues: a comprehensive reference book[M]. Academic Press, 2013.
[63] ARFKEN G B, WEBER H J. Mathematical methods for physicists[J]. American Journal of Physics, 1999, 67: 165.
[64] XU M, WANG L V. Time-domain reconstruction for thermoacoustic tomography in a spherical geometry[J]. IEEE Transactions on Medical Imaging, 2002, 21(7): 814-822.
[65] KAPLAN L, CHOW B W, GU C. Neuronal regulation of the blood-brain barrier and neurovascular coupling[J]. Nature Reviews Neuroscience, 2020, 21(8): 416-432.
[66] OGAWA S, LEE T M. Magnetic resonance imaging of blood vessels at high fields: in vivo and in vitro measurements and image simulation[J]. Magnetic Resonance in Medicine, 1990, 16(1): 9-18.
[67] KRUGER R A, LAM R B, REINECKE D R, et al. Photoacoustic angiography of the breast[J]. Medical Physics, 2010, 37(11): 6096-6100.
[68] FINCH D, HALTMEIER M, RAKESH. Inversion of spherical means and the wave equation in even dimensions[J]. SIAM Journal on Applied Mathematics, 2007, 68(2): 392-412.
[69] XU Y, WANG L V. Time reversal and its application to tomography with diffracting sources[J]. Physical Review Letters, 2004, 92(3): 033902.
[70] BURGHOLZER P, MATT G J, HALTMEIER M, et al. Exact and approximative imaging methods for photoacoustic tomography using an arbitrary detection surface[J]. Physical Review E, 2007, 75(4): 046706.
[71] JEON M, KIM J, KIM C. Multiplane spectroscopic whole-body photoacoustic imaging of small animals in vivo[J]. Medical & Biological Engineering & Computing, 2016, 54: 283-294.
[72] SUN A, JI Y, LI Y, et al. Multicolor photoacoustic volumetric imaging of subcellular structures[J]. ACS Nano, 2022, 16(2): 3231-3238.
[73] LENG X, CHAPMAN W, RAO B, et al. Feasibility of co-registered ultrasound and acoustic-resolution photoacoustic imaging of human colorectal cancer[J]. Biomedical Optics Express, 2018, 9(11): 5159-5172.
[74] QI W, JIN T, RONG J, et al. Inverted multiscale optical resolution photoacoustic microscopy[J]. Journal of Biophotonics, 2017, 10(12): 1580-1585.
[75] QIN W, JIN T, GUO H, et al. Large-field-of-view optical resolution photoacoustic microscopy[J]. Optics Express, 2018, 26(4): 4271-4278.
[76] JIN T, GUO H, JIANG H, et al. Portable optical resolution photoacoustic microscopy (pORPAM) for human oral imaging[J]. Optics Letters, 2017, 42(21): 4434-4437.
[77] TANG J, XI L, ZHOU J, et al. Noninvasive high-speed photoacoustic tomography of cerebral hemodynamics in awake-moving rats[J]. Journal of Cerebral Blood Flow & Metabolism, 2015, 35(8): 1224-1232.
[78] KHOSROFIAN J M, GARETZ B A. Measurement of a Gaussian laser beam diameter through the direct inversion of knife-edge data[J]. Applied Optics, 1983, 22(21): 3406-3410.
[79] CANNON J W. Hemorrhagic shock[J]. New England Journal of Medicine, 2018, 378(4): 370-379.
[80] GUTIERREZ G, REINES H D, Wulf-Gutierrez M E. Clinical review: hemorrhagic shock[J]. Critical Care, 2004, 8(5): 1-9.
[81] GUO H, KANG H, TONG H, et al. Microvascular characteristics of lower-grade diffuse gliomas: investigating vessel size imaging for differentiating grades and subtypes[J]. European Radiology, 2019, 29: 1893-1902.
[82] SOLHEIM O, SELBEKK T, JAKOLA A S, et al. Ultrasound-guided operations in unselected high-grade gliomas—overall results, impact of image quality and patient selection[J]. Acta Neurochirurgica, 2010, 152: 1873-1886.
[83] TOZER G M, AMEER-BEG S M, BAKER J, et al. Intravital imaging of tumour vascular networks using multi-photon fluorescence microscopy[J]. Advanced drug delivery reviews, 2005, 57(1): 135-152.
[84] FRANGI A F, NIESSEN W J, VINCKEN K L, et al. Multiscale vessel enhancement filtering[C]//Medical Image Computing and Computer-Assisted Intervention-MICCAI’98: First International Conference Cambridge, MA, USA, October 11-13, 1998 Proceedings 1. Springer Berlin Heidelberg, 1998: 130-137.
[85] JUST N. Histogram analysis of the microvasculature of intracerebral human and murine glioma xenografts[J]. Magnetic Resonance in Medicine, 2011, 65(3): 778-789.
[86] LAM L, LEE S W, SUEN C Y. Thinning methodologies-a comprehensive survey[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1992, 14(09): 869-885.
[87] YOHAI. MATLAB Central File Exchange. https://www.mathworks.com/matlabcentral/fileexchange/27543-skeletonization-using-voronoi.
[88] BRANDT J W, ALGAZI V R. Continuous skeleton computation by Voronoi diagram[J]. CVGIP: Image Understanding, 1992, 55(3): 329-338.
[89] TELEA A, VAN WIJK J J. An augmented fast marching method for computing skeletons and centerlines[C]//Proceedings of the symposium on Data Visualisation 2002. 2002: 251-ff.
[90] SWEENEY M D, SAGARE A P, ZLOKOVIC B V. Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders[J]. Nature Reviews Neurology, 2018, 14(3): 133-150.
[91] Zlokovic B V. Neurovascular pathways to neurodegeneration in Alzheimer's disease and other disorders[J]. Nature Reviews Neuroscience, 2011, 12(12): 723-738.
[92] WILD R, RAMAKRISHNAN S, SEDGEWICK J, et al. Quantitative assessment of angiogenesis and tumor vessel architecture by computer-assisted digital image analysis: effects of VEGF–toxin conjugate on tumor microvessel density[J]. Microvascular Research, 2000, 59(3): 368-376.
[93] MCMAHON G. VEGF receptor signaling in tumor angiogenesis[J]. The Oncologist, 2000, 5(S1): 3-10.
[94] UNGERSMA S E, PACHECO G, HO C, et al. Vessel imaging with viable tumor analysis for quantification of tumor angiogenesis[J]. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 2010, 63(6): 1637-1647.
[95] LOGOTHETIS N K. What we can do and what we cannot do with fMRI[J]. Nature, 2008, 453(7197): 869-878.
[96] HEEGER D J, RESS D. What does fMRI tell us about neuronal activity?[J]. Nature Reviews Neuroscience, 2002, 3(2): 142-151.
[97] SONG X W, DONG Z Y, LONG X Y, et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing[J]. PloS one, 2011, 6(9): e25031.
[98] Allen Brain Atlas. http://www.brain-map.org.
[99] KIRKCALDIE M T K, WATSON C, PAXINOS G, et al. Straightening out the mouse neocortex[C]//Australian Neuroscience Society Annual Conference. 2012.
[100] LOGOTHETIS N K, PAULS J, AUGATH M, et al. Neurophysiological investigation of the basis of the fMRI signal[J]. Nature, 2001, 412(6843): 150-157.
[101] GOLDMAN R I, STERN J M, ENGEL JR J, et al. Simultaneous EEG and fMRI of the alpha rhythm[J]. Neuroreport, 2002, 13(18): 2487.
[102] YU-FENG Z, YONG H, CHAO-ZHE Z, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI[J]. Brain and Development, 2007, 29(2): 83-91.
[103] Lake E M R, Ge X, Shen X, et al. Simultaneous cortex-wide fluorescence Ca2+ imaging and whole-brain fMRI[J]. Nature methods, 2020, 17(12): 1262-1271.
[104] GUEVARA E, POULIOT P, NGUYEN D K, et al. Optical imaging of acute epileptic networks in mice[J]. Journal of Biomedical Optics, 2013, 18(7): 076021-076021.
[105] ZAPPALA A, CICERO D, SERAPIDE M F, et al. Expression of pannexin1 in the CNS of adult mouse: cellular localization and effect of 4-aminopyridine-induced seizures[J]. Neuroscience, 2006, 141(1): 167-178.
[106] LERCHE H, JURKAT-ROTT K, LEHMANN-HORN F. Ion channels and epilepsy[J]. American Journal of Medical Genetics, 2001, 106(2): 146-159.
[107] Gloor P, Fariello R G. Generalized epilepsy: some of its cellular mechanisms differ from those of focal epilepsy[J]. Trends in neurosciences, 1988, 11(2): 63-68.
[108] FARKAS T, KIS Z S, TOLDI J, et al. Activation of the primary motor cortex by somatosensory stimulation in adult rats is mediated mainly by associational connections from the somatosensory cortex[J]. Neuroscience, 1999, 90(2): 353-361.
[109] ARONOFF R, MATYAS F, MATEO C, et al. Long‐range connectivity of mouse primary somatosensory barrel cortex[J]. European Journal of Neuroscience, 2010, 31(12): 2221-2233.
[110] BORCHERS S, HIMMELBACH M, LOGOTHETIS N, et al. Direct electrical stimulation of human cortex—the gold standard for mapping brain functions?[J]. Nature Reviews Neuroscience, 2012, 13(1): 63-70.
[111] GEE M S, PROCOPIO W N, MAKONNEN S, et al. Tumor vessel development and maturation impose limits on the effectiveness of anti-vascular therapy[J]. The American Journal of Pathology, 2003, 162(1): 183-193.
[112] KIMELBERG H K, NEDERGAARD M. Functions of astrocytes and their potential as therapeutic targets[J]. Neurotherapeutics, 2010, 7(4): 338-353.
[113] WINKLER E A, BELL R D, ZLOKOVIC B V. Central nervous system pericytes in health and disease[J]. Nature Neuroscience, 2011, 14(11): 1398-1405.
[114] BOSSHARD S C, BALTES C, WYSS M T, et al. Assessment of brain responses to innocuous and noxious electrical forepaw stimulation in mice using BOLD fMRI[J]. PAIN®, 2010, 151(3): 655-663.
[115] SCHROETER A, SCHLEGEL F, SEUWEN A, et al. Specificity of stimulus-evoked fMRI responses in the mouse: the influence of systemic physiological changes associated with innocuous stimulation under four different anesthetics[J]. Neuroimage, 2014, 94: 372-384.
[116] LIAO L D, LI M L, LAI H Y, et al. Imaging brain hemodynamic changes during rat forepaw electrical stimulation using functional photoacoustic microscopy[J]. Neuroimage, 2010, 52(2): 562-570.
[117] XIONG B, LI A, LOU Y, et al. Precise cerebral vascular atlas in stereotaxic coordinates of whole mouse brain[J]. Frontiers in Neuroanatomy, 2017, 11: 128.
[118] DORR A, SLED J G, KABANI N. Three-dimensional cerebral vasculature of the CBA mouse brain: a magnetic resonance imaging and micro computed tomography study[J]. Neuroimage, 2007, 35(4): 1409-1423.
[119] PAK R W, HADJIABADI D H, SENARATHNA J, et al. Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors[J]. Journal of Cerebral Blood Flow & Metabolism, 2017, 37(11): 3475-3487.
[120] CHOW D S, HORENSTEIN C I, CANOLL P, et al. Glioblastoma induces vascular dysregulation in nonenhancing peritumoral regions in humans[J]. AJR. American Journal of Roentgenology, 2016, 206(5): 1073.
[121] FELDMAN S C, CHU D, SCHULDER M, et al. The blood oxygen level-dependent functional MR imaging signal can be used to identify brain tumors and distinguish them from Normal tissue[J]. American Journal of Neuroradiology, 2009, 30(2): 389-395.
[122] LIU C, CHEN J, ZHANG Y, et al. Five-wavelength optical-resolution photoacoustic microscopy of blood and lymphatic vessels[J]. Advanced Photonics, 2021, 3(1): 016002-016002.
[123] NING B, SUN N, CAO R, et al. Ultrasound-aided multi-parametric photoacoustic microscopy of the mouse brain[J]. Scientific Reports, 2015, 5(1): 18775.
[124] WANG X, XIE X, KU G, et al. Noninvasive imaging of hemoglobin concentration and oxygenation in the rat brain using high-resolution photoacoustic tomography[J]. Journal of Biomedical Optics, 2006, 11(2): 024015-024015-9.
[125] ZHANG H F, MASLOV K, Sivaramakrishnan M, et al. Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy[J]. Applied Physics Letters, 2007, 90(5): 053901.
[126] Tabulated Molar Extinction Coefficient for Hemoglobin in Water. https://omlc.org/spectra/hemoglobin/summary.html.
[127] LIANG Y, JIN L, GUAN B O, et al. 2 MHz multi-wavelength pulsed laser for functional photoacoustic microscopy[J]. Optics Letters, 2017, 42(7): 1452-1455.
[128] HEJAZ K, SHAYGANMANESH M, REZAEI-NASIRABAD R, et al. Modal instability induced by stimulated Raman scattering in high-power Yb-doped fiber amplifiers[J]. Optics Letters, 2017, 42(24): 5274-5277.
[129] DE LA CRUZ-MAY L, ALVAREZ-CHAVEZ J A, MEJÍA E B, et al. Raman threshold for nth-order cascade Raman amplification[J]. Optical Fiber Technology, 2011, 17(3): 214-217.
[130] CAO R, LI J, NING B, et al. Functional and oxygen-metabolic photoacoustic microscopy of the awake mouse brain[J]. Neuroimage, 2017, 150: 77-87.
[131] SCIORTINO V M, TRAN A, SUN N, et al. Longitudinal cortex-wide monitoring of cerebral hemodynamics and oxygen metabolism in awake mice using multi-parametric photoacoustic microscopy[J]. Journal of Cerebral Blood Flow & Metabolism, 2021, 41(12): 3187-3199.
[132] LYONS D G, PARPALEIX A, ROCHE M, et al. Mapping oxygen concentration in the awake mouse brain[J]. Elife, 2016, 5: e12024.
[133] FANG H, MASLOV K, WANG L V. Photoacoustic Doppler flow measurement in optically scattering media[J]. Applied Physics Letters, 2007, 91(26): 264103.
[134] Yao J, Maslov K I, Shi Y, et al. In vivo photoacoustic imaging of transverse blood flow by using Doppler broadening of bandwidth[J]. Optics letters, 2010, 35(9): 1419-1421.
[135] KOHLER R H, SCHWILLE P, WEBB W W, et al. Active protein transport through plastid tubules: velocity quantified by fluorescence correlation spectroscopy[J]. Journal of Cell Science, 2000, 113(22): 3921-3930.
[136] CHEN S L, LING T, HUANG S W, et al. Photoacoustic correlation spectroscopy and its application to low-speed flow measurement[J]. Optics Letters, 2010, 35(8): 1200-1202.
[137] BRISTER P C, KURICHETI K K, BUSCHMANN V, et al. Fluorescence correlation spectroscopy for flow rate imaging and monitoring—optimization, limitations and artifacts[J]. Lab on a Chip, 2005, 5(7): 785-791.
[138] REDDY G D, KELLEHER K, FINK R, et al. Three-dimensional random access multiphoton microscopy for fast functional imaging of neuronal activity[J]. Nature Neuroscience, 2008, 11(6): 713.
[139] PROTHERO J W, BURTON A C. The physics of blood flow in capillaires: Ii. the capillary resistance to flow[J]. Biophysical Journal, 1962, 2(2): 199-212.
[140] PRIES A R, SECOMB T W. Blood flow in microvascular networks[M]//Microcirculation. Academic Press, 2008: 3-36.
[141] MEDVEDEV A E, FOMIN V M. Two-phase blood-flow model in large and small vessels[C]//Doklady Physics. SP MAIK Nauka/Interperiodica, 2011, 56: 610-613.
[142] PRIES A R, SECOMB T W, GAEHTGENS P. Biophysical aspects of blood flow in the microvasculature[J]. Cardiovascular Research, 1996, 32(4): 654-667.
[143] BAKKER E, VERSLUIS J P, SIPKEMA P, et al. Differential structural adaptation to haemodynamics along single rat cremaster arterioles[J]. The Journal of Physiology, 2003, 548(2): 549-555.
[144] UYLINGS H B M. Optimization of diameters and bifurcation angles in lung and vascular tree structures[J]. Bulletin of Mathematical Biology, 1977, 39(5): 509-520.
[145] LI C X, PATEL S, Auerbach E J, et al. Dose-dependent effect of isoflurane on regional cerebral blood flow in anesthetized macaque monkeys[J]. Neuroscience Letters, 2013, 541: 58-62.
[146] HAI P, YAO J, MASLOV K I, et al. Near-infrared optical-resolution photoacoustic microscopy[J]. Optics Letters, 2014, 39(17): 5192-5195.
[147] DISPIRITO A, LI D, VU T, et al. Reconstructing undersampled photoacoustic microscopy images using deep learning[J]. IEEE Transactions on Medical Imaging, 2020, 40(2): 562-570.
[148] WANG H, RIVENSON Y, JIN Y, et al. Deep learning enables cross-modality super-resolution in fluorescence microscopy[J]. Nature Methods, 2019, 16(1): 103-110.