植入式荧光内窥显微技术及其在活体脑成像中的应用（特邀）创刊五十周年特邀
The neurovascular unit (NVU), a critical component of the brain, regulates almost all physiological process. The precision of the morphology and function presentation regarding the NVU provides hope for advancing research on basic neuroscience, as well as diagnosing brain diseases, which are common desires of the “Brain Project” worldwide. Accordingly, high temporal and spatial resolution visualization techniques are required. Fluorescence microscopic imaging technology has significant advantages in terms of specificity, diversity, image contrast, and spatio-temporal resolution; however, due to the limited penetration depth of light in tissue, use of noninvasive fluorescence imaging to obtain high-resolution structural and functional information of NVU is difficult in deep brain regions in vivo. As a result, fluorescence endoscopic microscopy imaging technologies based on micro probes are becoming more popular among brain science researchers.
Over the last two decades, a series of neurobehavioral studies in vivo have been conducted using fluorescence endoscopic microscopy. With endoscopic probes implanted into the brain, the NVU in most deep regions can be observed clearly in living mice, including the hippocampus, dorsal striatum, amygdaloid nucleus, and epithalamus. Incorporating an upright microscope or a head-mounted mini microscope, gradient refractive index (GRIN) lenses have been widely employed as an implantable probe, with the advantage of excellent stability, high resolution, and low cost. In addition, a potential strategy for implantable imaging of the brain in vivo involves using a single multimode fiber, based on modulation of the light field, to focus and scan spot at the end of multimode fiber. This reduces tissue damage, with resolution at the cellular level. Herein, the recent progression of implantable fluorescence endoscopic microscopy is reviewed based on both GRIN lens and a single multimode fiber, besides application research in vivo including blood velocity, neurons growth, calcium ion conduction, and so on. Finally, fluorescence endoscopic microscopy imaging technologies for clinical diagnosis of brain tumors are also introduced, demonstrating that these advanced optical imaging methods expand the toolbox for brain science research and disease diagnosis.
Endoscopic probes have been miniaturized, providing greater flexibility while maintaining high performance; thus, probes can be implanted at different depths in the living brain to carry out functional modulation studies in specific deep brain regions. With micromachining or adaptive optics technologies, GRIN lens provides an effective method to obtain high resolution images. Although the nonmechanical scan imaging through a single multimode fiber is a relatively new exploration for brain research in vivo, it has already exhibited the unique advantages of minimally invasive and flexibility. In future, the following considerations are worth exploring: (1) development of a high-performance multimode fiber with enhanced anti-interference ability to external disturbances; (2) processing of a microlens on the face of multimode fiber with precise 3D printing technology, to optimize imaging resolution, depth of field, and field of view; (3) introduction of fluorescence polarization and fluorescence lifetime imaging modes to analyze neuronal physiological information, such as protein dipoles and cellular microenvironment.
1 引言
大脑是人体最重要、最复杂的器官。对大脑的研究可以追溯到公元前17世纪，但时至今日，人类对大脑的认识还只是冰山一角。Science杂志与上海交通大学联合公布的125个最前沿的科学问题中［1］，有16个与脑科学领域有关，足以看出脑科学研究在前沿学科中的重要性。欧盟组织以及美国（2013年）、日本（2014年）和澳大利亚（2016年）等陆续开启了各自的脑科学研究计划，“中国脑计划”于2016年全面布局，明确了以揭示大脑认知功能原理、研究重大脑疾病诊疗新手段和发展脑机智能新技术为目标，三者相辅相成的“一体两翼”发展战略［2］。北京和上海相继于2018年成立了脑科学与类脑研究中心，率先拉开了脑科学研究的序幕，随后，2021年，“中国脑计划”正式启动。推进脑科学研究的重要意义不仅在于对未知大脑机制的探索，更是要为脑疾病寻找精准的早期诊断方案和高效的治疗策略。
大脑通过在神经元细胞之间传导生物电信号来发挥其调控功能［3］，而脑血管为神经元网络维持正常生理状态提供所需的氧气和营养，并且是清除有毒代谢产物的重要途径。由神经元、血管、胶质细胞、血脑屏障和细胞外基质共同构成的神经血管单元（NVU）是大脑的基本构成部分［4］，它会产生与大脑健康和疾病相关的各种功能反应，包括调节血脑屏障的通透性、血管生成、血流动力学反应、神经炎症和干细胞活性等［5-6］。“工欲善其事，必先利其器”，随着脑科学研究的深入，研究人员越来越重视在活体水平获取大脑的NVU结构和功能信息，因为组织微环境、体液循环和细胞相互作用等正常生理条件对NVU调控体内特定功能至关重要，而这离不开高时空分辨可视化技术。
包括计算机断层扫描成像、磁共振成像、正电子发射断层成像等在内的临床脑影像技术，是研究活体大脑结构和功能的手段，但它们的空间分辨率通常只有微米至亚毫米量级，且耗时较长［7-9］，难以满足活体NVU成像的需求。荧光显微成像技术在研究目标的特异性和多样性、图像对比度和时空分辨率等方面具有显著优势，正逐渐成为实现活体脑成像的新手段。然而，非常有限的成像深度一直是荧光成像技术在活体应用中面临的巨大挑战。
由于生物组织对光的吸收和散射作用，激发光斑在深层组织中会发生弥散，导致激发效率降低，同时，产生的荧光在经过组织后无法全部被物镜收集［10］。近红外波段（NIR）的光可以更有效地穿透生物组织［11-12］，因此，近红外成像更适合活体应用。在一项针对小鼠大脑衰减系数的研究中（
图 1. 小鼠颅骨、皮肤以及大脑皮层（新鲜组织）对不同波长光的衰减系数［13］
Fig. 1. Light attenuation coefficient in mouse skull bone, skin, and brain cortex (fresh tissues)[13]
虽然这些荧光成像技术可以在不侵入脑组织的情况下进行活体NVU结构和功能的高时空分辨成像，但它们的成像深度局限于脑表层至浅层海马区［
图 2. 植入式荧光内窥显微成像技术。（a）该技术对活体小鼠脑成像的深度范围；（b）以GRIN透镜（左）和单根多模光纤（右）作为植入介质的荧光内窥显微成像技术
Fig. 2. Implantable fluorescence endoscopic microscopy. (a) Imaging depth of the microscopy used in in vivo mouse brain imaging; (b) the fluorescence endoscopic microscopy using a GRIN lens (left) or single multimode fiber (right) as implantation medium
2 基于GRIN透镜的植入式内窥活体脑成像
GRIN透镜是一种折射率分布沿径向渐变的柱状光学透镜，其折射率分布沿径向方向逐渐减小，从而使得沿轴向传输的光线产生连续折射，出射光线平滑且连续地会聚成一个衍射极限的光斑。通过设计折射率和节距，可以较灵活地调整GRIN透镜的长度和数值孔径（NA）。因此，GRIN透镜具有直径小、结构简单、装配方便、成本低以及NA相对较大（通常不小于0.5）等优点。在进行活体脑成像时，为突破光在脑组织中的传播深度限制，研究人员通常将GRIN透镜［17-20］作为植入式内窥探头，以增加普通显微镜［21］或微型显微镜［22］的工作距离，从而实现对深层（甚至贯穿全脑［19］）NVU的高时空分辨内窥成像。用于内窥脑成像的GRIN透镜的直径通常控制在1 mm以内，但仍会不可避免地对大脑造成损伤，成像时需要吸除目标脑区上层组织。因此，这种内窥成像技术目前主要用于对啮齿类动物模型的活体研究中。虽然这种成像方式有时容易造成出血和炎症反应，但成像实验通常会设计在植入GRIN透镜3~4周之后进行［23］，这样可以有效地降低炎症反应对小鼠行为以及NVU结构和功能成像的影响［24］，并且可以对特定脑区中相同的NVU进行长时间观测，因而对于研究神经元的发育和脑疾病的进程十分有利。
为了保持GRIN透镜在活体脑成像中的长期稳定性，通常需要设计、加工内径尺寸与GRIN透镜直径匹配的生物相容性套管，并将其与GRIN透镜一同植入目标脑区（套管另一端的基座固定于颅骨上）。此外，套管也能保护侧面的脑组织免受GRIN透镜边缘的损伤。Bocarsly等［20］设计了一种聚酰亚胺引导套管，并用其对GRIN透镜进行固定。埋植手术4周之后，脑组织中的炎症反应几乎可以忽略不计。他们对外侧下丘脑和纹状体中的神经元分别进行了长达16 d和36 d的观测，观测期间神经元结构保持着较好的稳定性［如
图 3. GRIN透镜植入后的长期活体内窥脑成像研究。（a）GRIN透镜套管的设计以及外侧下丘脑和纹状体神经元成像［20］，标尺为20 μm；（b）用于脑损伤模型研究的GRIN透镜套管及神经元成像［25］，标尺为10 μm
Fig. 3. In vivo long term endoscopic brain imaging after GRIN lens implantation. (a) GRIN lens cannula design and imaging of neurons in the lateral hypothalamus and striatum[20], scale bar: 20 μm; (b) GRIN lens cannula design for brain injury model and neurons imaging results[25], scale bar: 10 μm
基于GRIN透镜的植入式内窥显微技术可以在不干扰NVU结构和功能的前提下成像，因此该技术被广泛应用于脑微血管血流动力学与脑疾病发展机制的研究。Jung等［17］利用荧光素钠对血浆进行标记，并充分利用宽场显微成像速度的优势，通过实时视频记录了小鼠和大鼠海马体内单个红细胞在毛细血管中的流动过程。结果显示，血流速度在30~350 μm/s之间变化。脑部微血管中血流速度的减慢，被认为与神经退行性疾病有关［29］。Jung及其团队的研究为在体检测深层脑区血流动力学提供了新的方向。脑癌，尤其是高侵袭性和耐药性的脑胶质瘤，一直是全球最棘手的癌症之一［30］，其更易患于深层脑区［31］，术后5年内的复发率几乎可达100%，死亡率极高［32-33］。为了研究原位胶质瘤小鼠模型中肿瘤生长、血管增生、血流速度之间的关系，Barretto等［34］进行了同一肿瘤视野的长期荧光内窥成像研究。结果表明：随着海马体中肿瘤细胞的增多，其周围毛细血管的直径逐渐扩大，但相比于对侧正常的海马体，血流速度明显降低。同时，正常血管形态和锥体神经元结构在很长的一段时期均稳定，这一发现对于人们更好地理解脑胶质瘤微环境重塑具有重要的推动作用，并展示了长期荧光内窥技术在脑病模型研究中的重要价值。近些年来，人们还进行了关于不同脑区神经元调控动物行为机制的研究，例如眶额皮层神经元调控的食物摄取行为［21］、内侧杏仁核神经元调控的社交行为［22］，以及前内侧丘脑神经元调控的长期记忆［35］等。
虽然通过在小鼠大脑内植入GRIN透镜可以实现对NVU精细结构的成像，但常见的商用GRIN透镜一般具有非平面特性，其主光轴周围存在明显的像差（由其类抛物线的折射率分布决定），这会导致成像系统的视场和空间分辨率降低。为了解决这个问题，可以将GRIN透镜与其他光学元件结合进行优化设计，例如增加平凸微透镜［36］、黏合带有负球差的盖玻片［37］，或者通过3D打印在盖玻片上加工非球面微透镜［如
图 4. 补偿GRIN透镜内窥成像系统像差的方法及成像结果。（a）在盖玻片上加工非球面微透镜［38］；（b）基于HiLo-AO的波前校正［42］
Fig. 4. Compensation methods of aberration in GRIN lens-based endoscopic imaging systems and their imaging results. (a) Processing an aspheric microlens on a coverslip[38]; (b) HiLo-AO-based wavefront correction[42]
双光子成像技术具有天然的光学层析成像能力，其与GRIN透镜相结合，可以在无须移动透镜的情况下实现高分辨率z轴扫描。飞秒脉冲光在GRIN透镜中的色散程度较小（相较于光纤），这使得系统无须附加色散补偿器件。2004年，Webb团队［43］验证了在双光子荧光成像系统中引入GRIN透镜进行活体内窥脑成像的可行性。他们设计了一个16 mm长的复合GRIN透镜探头，其中继部分的NA为0.1，末端部分的NA为0.6。这样的设计既降低了由脉冲光在探头中聚焦引起的荧光背景和自相位调制，又提高了成像的空间分辨率。通过调节GRIN透镜在样品端的工作距离，可以实现0~95 μm的z轴扫描。他们采用该探头对活体小鼠大脑皮层V和海马体CA1神经元进行了亚细胞分辨率成像。随着飞秒激光整形技术的发展，近几年报道了多种通过调控光场来提高双光子GRIN透镜内窥成像性能的方法，而且这些方法在活体小鼠脑成像中得到了应用。Moretti等［44］采用空间光调制器（SLM）对飞秒光束进行调制，生成了多焦点或图案光照明。将GRIN透镜植入海马体后，他们先使用振镜进行全视场双光子扫描成像，然后根据视场中神经元的分布选择多个感兴趣区域，并通过加载SLM特定的相位图案调制光场，对感兴趣区域进行选择性光照并记录Ca2+信号的变化，实现了对功能性神经元网络的快速非扫描成像，如
图 5. 双光子荧光显微镜与GRIN透镜结合的活体内窥脑成像研究。（a）SLM调控光场实现多焦点或图案照明［44］，标尺为100 μm；（b）基于贝塞尔光束的快速神经元高分辨体成像［45］，标尺为20 μm；（c）基于查找表和直接波前探测AO校正的锥体神经元成像［46］，标尺为5 μm
Fig. 5. In vivo endoscopic brain imaging with a two-photon fluorescence microscope and a GRIN lens. (a) SLM regulates the light field to achieve multi focus or pattern illumination[44], scale bar: 100 μm; (b) fast volume imaging of neurons with high resolution based on Bessel beam[45], scale bar: 20 μm; (c) cone neuron imaging based on lookup table and direct wavefront detection for AO correction[46], scale bar: 5 μm
为了提高双光子体成像的时间分辨率，Meng等［45］将聚焦于GRIN透镜末端的高斯光束调制成贝塞尔光束，这样便可在保持突触分辨的同时，对海马体神经元的树突棘和轴突末梢实现370 µm×370 µm×45 µm的高通量成像，如
考虑到GRIN透镜的工作距离通常为几十至几百微米，为了最大程度地利用其性能进行百微米级高分辨率体成像，香港科技大学的瞿佳男教授团队［46］提出了一种AO校正策略：首先对GRIN透镜在不同视场位置的固有像差进行预校准，并将其存储于查找表（LUT）中；进行活体脑成像时，在LUT中快速加载对应位置的补偿相位，使荧光信号得以增强；将荧光信号作为内在引导星，用Shack-Hartman传感测量残余像差，之后通过变形镜调制激发光以补偿脑组织引起的聚焦光斑失真。相比于以往的高分辨内窥脑成像研究，该方法在纵向深度方面有明显提升，实现了50 µm×50 µm×300 µm范围内海马体CA1锥体神经元突触级别的结构成像，如
随着微纳加工和微机电技术的快速发展，微型化显微镜逐渐受到研究人员的关注。这种显微镜的质量通常在几克至十几克之间，能够通过光纤传输激发光并收集荧光信号，部分显微镜甚至集成了微型LED和CCD。微型显微镜的问世［48］标志着活体脑成像已经不再局限于在成像过程中将小动物颅窗固定，现在已经可以在小动物自由活动的同时实时动态获取NVU成像数据，这为研究脑功能如何影响动物行为提供了有力工具［49］。经过20多年的发展，微型显微镜已经能够实现活体脑成像，包括使用单光子［50］、双光子［48， 51-52］和三光子［53-54］荧光，使得人们能够在不干扰小鼠的前提下观察鼠脑表面至海马体CA1浅层的神经元活动［54］。当然，将GRIN透镜嵌入微型显微镜可以实现内窥脑成像，也就能够观察到更深的大脑区域，提供自由活动的小动物的实时大脑功能数据［22， 55-58］。Flusberg等［59］设计了一种质量仅为3.9 g的基于复合GRIN透镜的微型双光子内窥显微镜，它采用光子晶体光纤传输超短脉冲光，并利用压电驱动光纤进行Lissajous扫描，可以实现海马体以下约80 μm的血管成像。Grewe等［55］将一个直径为600 μm的GRIN透镜埋入自由活动小鼠的大脑基底和外侧杏仁核（BLA），并在颅窗上安装了Inscopix公司开发的微型显微镜nVista HD，以便长期观测BLA神经元的Ca2+响应，从而解析神经元如何编码条件和非条件刺激之间的关系。Barbera等［56］在微型内窥显微镜中添加了可变焦液体透镜，因此在进行信号同步时能够在每帧图像之间切换焦点。在这种背景下研究自由活动小鼠大脑中不同深度处神经元信号的传导时，使用液体透镜更为合适［59］。他们展示了内侧前额叶皮层中不同深度处神经元之间Ca2+信号的成像结果（如
图 6. 基于微型显微镜的GRIN透镜活体内窥神经元功能成像［56］
Fig. 6. In vivo endoscopic neuron functional imaging using a miniaturized head-mounted microscope combined a GRIN lens[56]
研究跨脑区神经元之间的Ca2+信号关联性，对于理解生物的复杂行为至关重要。清华大学的戴琼海院士团队［60］开发的实时超大视场高分辨率成像平台为研究小鼠全脑上皮层神经元关联性提供了有力工具。该平台利用特制的大孔径物镜和35个sCMOS相机组成的成像阵列，每秒可产生51亿像素的数据，可以实现对不同脑皮层区域神经元集群的高通量功能成像，但仍面临着深层脑区成像难题。随着GRIN透镜内窥脑成像的普及，人们发展了一些低成本针对跨脑区神经元的成像方法。这些方法利用多个置于目标脑区上方的GRIN透镜实现快速成像。Yang等［61］设计了一种多区域双光子实时内窥成像技术（MATRIEX）：在常规激光扫描显微镜中，采用低倍物镜将光耦合至不同脑区的GRIN透镜，这些透镜的长度不同，以确保其像面始终与物镜焦平面重合。通过这种两级放大和多轴耦合的方法，他们分别实现了对活体小鼠初级视觉皮层（V1）、初级运动皮层（M1）和海马体CA1三个不同脑区神经元集群在麻醉与清醒状态下的功能成像，每个视场的直径为200 μm，间距都超过了2 mm，如
图 7. 基于MATRIEX技术的多脑区神经元内窥成像［61］
Fig. 7. MATRIEX technology used for in vivo multiarea endoscopic brain imaging[61]
3 基于单根多模光纤的植入式内窥活体脑成像
多模光纤能够传播数千个独立的光学模式，每一个模式都含有丰富的信息，具有极大的信息传输带宽。在活体内窥脑成像中，使用单根多模光纤作为内窥探头是近几年发展起来的一种新方法。与GRIN透镜相比，多模光纤的优势在于其直径极小，一般为50~125 μm（与一根头发的直径相当），插入脑组织时能轻易地绕开主要血管，减少对周边神经元的伤害，实现极微创内窥脑成像。然而，不同的光学模式在多模光纤中传输时存在模式色散、模式干涉和模式耦合，导致出射光场强度和相位在空间上随机分布，形成光学散斑，限制了其在高分辨率图像传输和活体成像中的应用。
与散射介质中的成像相同，基于多模光纤的高分辨率内窥成像可以通过传输矩阵（表示光纤输入和输出光场之间的对应关系）测量［63-64］和波前整形［65-67］等方法实现。随着SLM和数字微镜装置（DMD）等光学调制器件的日益成熟，研究人员现已能调控多模光纤输出光场的偏振和相位分布，也能调节多模光纤内部光的非线性效应，如受激拉曼散射、四波混频等［68］，使激发光经过多模光纤后能形成接近光学衍射极限的聚焦光斑［64， 69-70］。在实际的生物组织成像中，基于传输矩阵测量的多模光纤成像是目前应用最广泛的方法。该方法通过标定多模光纤的传输矩阵并据此控制不同的入射波前，可以实现光斑在光纤末端的快速扫描。荧光信号通过相同的光纤传回输入端，实现高分辨成像。因此，成像系统中除光场调制和荧光成像模块外，通常还会增加相机和参考光的校正模块，用于记录散斑的强度和复振幅信息。
尽管多模光纤成像方法早些年已有报道［71］，但其在内窥应用中的分辨率和视场等成像指标会受到光纤加工工艺的影响，工作环境的扰动也会直接影响其传输矩阵，导致其成像质量下降。因此，在过去的10余年，研究人员开发出了许多方法来提升多模光纤成像系统的性能。2010年，Popoff等［72］使用SLM和相机进行了单色光经过厚随机散射样品后的全场干涉测量，成功验证了经过随机介质后光束重聚焦的可行性，为基于多模光纤的高分辨成像提供了重要思路（
图 8. 光束经过散射介质之后的重聚焦调控研究［72］
Fig. 8. The beam was refocused after passing through the scattering medium[72]
图 9. 几种赋予多模光纤成像动态校准能力的方法。（a）引入虚拟信标［74］；（b）在光纤远端加工部分反射器［75］；（c）加工超表面结构［76］；（d）引入引导星［77］；（e）通过神经网络CNN模型辅助提取散斑信息［81］
Fig. 9. Several methods for providing dynamic calibration capabilities to multimode fiber-based fluorescence microscopy. (a) Introducing a virtual beacon[74]; (b) processing a part reflector on the fiber’s distal end[75]; (c) machining metasurface structures[76]; (d) introducing a guide star[77]; (e) using a CNN model to help extract speckle information[81]
随着光纤制作技术、光学调制设备性能以及光学计算能力的进步，多模光纤成像技术逐渐走向成熟，并开始在活体深层脑成像中得到应用。SLM的优点在于它高的光能量利用率，配合开源的GPU加速插件运行Gerchberg-Saxton和Yang-Gu算法，可以实现接近视频速率（约20 frame/s）的图像控制［84］。2018年，Vasquez-Lopez等［85］采用该方法实现了活体大鼠背侧纹状体脑区神经元树突和树突棘的三维成像（
图 10. 基于SLM调制的多模光纤内窥脑成像［85］。（a）成像装置示意图；（b）成像脑区以及点扫描示意图；（c）活体背侧纹状体脑区的神经元成像结果，标尺为10 μm；（d）光纤在脑皮层的植入路径，如白色虚线所示；（e）离体脑切片神经元内Ca2+信号的动态表征；（f）受到声音刺激时，活体丘脑区听觉神经元内Ca2+信号的波动（单像素）
Fig. 10. Single multimode fiber endoscopic brain imaging using SLM[85]. (a) Schematic diagram of imaging device; (b) imaging brain regions and scanning diagrams; (c) in vivo imaging results of neurons in the dorsal striatum, scale bar: 10 μm; (d) implantation path of fiber in the cerebral cortex is shown by the white dashed line; (e) dynamic characterization of Ca2+ signals in neurons of isolated brain slices; (f) fluctuations in Ca2+ signals of auditory neurons in the thalamic region when stimulated by sound (single pixel)
图 11. 基于DMD调制的多模光纤内窥脑成像［86］。（a）成像装置示意图，右下角为实验光纤的光镜图。（b）上：初级视觉皮层神经元胞体；中：海马齿状回区域抑制性神经元突触结；下：血管破裂后血细胞流动。从左至右图像的时间间隔为0.57 s
Fig. 11. DMD-based endoscopic brain imaging with single multimode fiber[86]. (a) Schematic diagram of the imaging device, the lower right corner is the optical microscopy image of the experimental fiber. (b) Upper: primary visual cortex neuron soma; middle: inhibitory neuronal synaptic nodes in the dentate gyrus; down: blood cells flow after vascular rupture. The time interval from left to right is 0.57 s
图 12. 侧视多模光纤在活体脑成像中的应用研究［89］。（a）成像装置和侧视光纤示意图；（b）活体鼠脑成像结果，绿色为GFP（绿色荧光蛋白）标记的神经元，红色为染料标记的血管，标尺为20 μm；（c）神经元中Ca2+信号和血流动力学的动态表征结果
Fig. 12. Application of sideview multimode fiber for in vivo brain imaging[89]. (a) Schematic diagram of imaging device and sideview multimode fiber; (b) mouse brain imaging results in vivo, green represents the GFP labeled neurons, red represents the blood vessels marked with dye, scale bar: 20 μm; (c) dynamic characterization results of Ca2+ signals in neurons and hemodynamics
4 荧光内窥脑成像技术在临床上的应用
活体荧光内窥脑成像技术在小动物模型应用中取得了许多令人振奋的研究成果，解决了其他技术无法同时实现大成像深度和高时空分辨率的难题。在临床研究中，尤其是在脑肿瘤的术中实时诊断方面，荧光内窥成像技术发挥着重要作用。神经外科医生借助带有手持式探头的内窥显微镜和荧光示踪剂，如荧光素（FN）［92-93］、吲哚菁绿（ICG）［94］和5-氨基乙酰丙酸（5-ALA）［95］等，能够在微观尺度上对脑组织中的肿瘤残余进行术中检查。美国巴罗神经学研究所的医生团队在这方面进行了许多开创性的尝试［96-98］，有效改善了脑肿瘤的手术治疗效果。Charalampaki等［99］的报道展示了荧光内窥成像技术在临床脑膜瘤手术中的应用。在介观级别的宽场成像中，肿瘤组织摄取ICG后荧光明显增强；而在微观级别的共聚焦成像中，存在大砂粒体的脑膜瘤细胞结构清晰可见。这进一步验证了肿瘤组织的存在，H&E染色也验证了对切除肿瘤的判断，如
图 13. 内窥脑成像技术在临床脑肿瘤诊断中的应用。（a）ICG标记的脑膜瘤组织的宽场和共聚焦内窥成像，以及术后组织切片的H&E染色结果［99］；（b）无标记的FLIM内窥成像在鉴别坏死脑组织中的应用［111］
Fig. 13. Application of endoscopic brain imaging technology in clinical brain tumor diagnosis. (a) Wide-field and confocal endoscopic imaging of ICG-labeled meningioma tissues and H&E staining result of postoperative tissue section[99]; (b) label-free FLIM endoscopic imaging in the identification of necrotic brain tissue[111]
荧光寿命显微成像（FLIM）是一种对微环境极为敏感的技术，利用组织之间的荧光寿命差异来提供对比度更高的图像［101-103］。由于肿瘤细胞的有氧呼吸水平和代谢特征异常，内源性荧光分子（如NADH和FAD等）的荧光寿命存在差异［104-105］，因此，荧光寿命内窥显微成像技术在临床脑肿瘤手术中也已经有了初步探索性应用，比如辅助对肿瘤组织进行无标记识别［106］。加州大学的Marcu教授团队［107-111］在使用时间分辨光谱技术和FLIM进行脑肿瘤区域的快速鉴别方面积累了多年临床经验。他们将带有光纤探头的FLIM内窥系统与手术显微镜集成，在术中操作光纤扫描可疑区域，监视器实时显示扫描区域的荧光寿命。如
5 总结与展望
21世纪被誉为光的世纪，我们正身处其中，有幸借此契机解锁大脑的神秘面纱。在这个过程中，植入式荧光内窥显微成像技术作为一种集深度和分辨率于一体的技术，正在最前沿的脑科学研究领域发挥着重要作用，目前已实现了包括杏仁核、丘脑和纹状体等深层脑区的在体显微成像（
在接下来的研究中，可以考虑对基于单根多模光纤的方法进行以下探索：1） 研制模式更为稳定的全新多模光纤，增强光纤对外部扰动的抗干扰能力；2） 采用精细的3D打印技术在多模光纤端面上加工不超过光纤纤芯直径的透镜组，以优化成像的分辨率、景深和视场；3） 增加荧光偏振和荧光寿命成像模态，以便解析神经元的生理信息，如蛋白偶极子和细胞微环境等。
此外，随着新型探针、高性能激光器、高灵敏度光子探测器的不断发展，以及计算成像和人工智能等日新月异的发展，荧光内窥脑成像技术必将出现全新的突破，而这必将极大地推进脑科学研究，加速人们对大脑的深层理解和揭秘，助力遗传疾病的治疗和预防，最终造福全人类。
表 1. 应用于活体小动物脑成像的植入式荧光内窥显微技术指标对比
Table 1. Comparison of implantable fluorescence endoscopy microscopy for brain imaging in living small animals
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[2] Poo M M, Du J L, Ip N Y, et al. China brain project: basic neuroscience, brain diseases, and brain-inspired computing[J]. Neuron, 2016, 92(3): 591-596.
[3] Inoue M. Genetically encoded calcium indicators to probe complex brain circuit dynamics in vivo[J]. Neuroscience Research, 2021, 169: 2-8.
[4] Iadecola C. The neurovascular unit coming of age: a journey through neurovascular coupling in health and disease[J]. Neuron, 2017, 96(1): 17-42.
[5] 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.
[6] Petrovskaya A, Tverskoi A, Medvedeva A, et al. Is blood-brain barrier a probable mediator of non-invasive brain stimulation effects on Alzheimer’s disease?[J]. Communications Biology, 2023, 6: 416.
[7] Dumoulin S O, Fracasso A, van der Zwaag W, et al. Ultra-high field MRI: advancing systems neuroscience towards mesoscopic human brain function[J]. NeuroImage, 2018, 168: 345-357.
[8] Miyaoka R S, Lehnert A L. Small animal PET: a review of what we have done and where we are going[J]. Physics in Medicine and Biology, 2020, 65(24): 24TR04.
[9] Keklikoglou K, Arvanitidis C, Chatzigeorgiou G, et al. Micro-CT for biological and biomedical studies: a comparison of imaging techniques[J]. Journal of Imaging, 2021, 7(9): 172.
[10] Helmchen F, Denk W. Deep tissue two-photon microscopy[J]. Nature Methods, 2005, 2(12): 932-940.
[11] Hong G S, Diao S, Chang J L, et al. Through-skull fluorescence imaging of the brain in a new near-infrared window[J]. Nature Photonics, 2014, 8(9): 723-730.
[12] Liu H J, Deng X Q, Tong S, et al. In vivo deep-brain structural and hemodynamic multiphoton microscopy enabled by quantum dots[J]. Nano Letters, 2019, 19(8): 5260-5265.
[13] Golovynskyi S, Golovynska I, Stepanova L I, et al. Optical windows for head tissues in near-infrared and short-wave infrared regions: approaching transcranial light applications[J]. Journal of Biophotonics, 2018, 11(12): e201800141.
[14] Xia F, Gevers M, Fognini A, et al. Short-wave infrared confocal fluorescence imaging of deep mouse brain with a superconducting nanowire single-photon detector[J]. ACS Photonics, 2021, 8(9): 2800-2810.
[15] 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.
[16] 王子川, 张伟, 郭飞, 等. 跨尺度光学内窥成像技术[J]. 中国光学(中英文), 2022, 15(6): 1287-1301.
[17] Jung J C, Mehta A D, Aksay E, et al. In vivo mammalian brain imaging using one-and two-photon fluorescence microendoscopy[J]. Journal of Neurophysiology, 2004, 92(5): 3121-3133.
[18] Huland D M, Brown C M, Howard S S, et al. In vivo imaging of unstained tissues using long gradient index lens multiphoton endoscopic systems[J]. Biomedical Optics Express, 2012, 3(5): 1077-1085.
[19] Kim J K, Choi J W, Yun S H A. 350-μm side-view optical probe for imaging the murine brain in vivo from the cortex to the hypothalamus[J]. Journal of Biomedical Optics, 2013, 18(5): 050502.
[20] Bocarsly M E, Jiang W C, Wang C, et al. Minimally invasive microendoscopy system for in vivo functional imaging of deep nuclei in the mouse brain[J]. Biomedical Optics Express, 2015, 6(11): 4546-4556.
[21] Jennings J H, Kim C K, Marshel J H, et al. Interacting neural ensembles in orbitofrontal cortex for social and feeding behaviour[J]. Nature, 2019, 565(7741): 645-649.
[22] Li Y, Mathis A, Grewe B F, et al. Neuronal representation of social information in the medial amygdala of awake behaving mice[J]. Cell, 2017, 171(5): 1176-1190.
[23] Butiaeva L I, Kokoeva M V. High-resolution intravital imaging of the murine hypothalamus using GRIN lenses and confocal microscopy[J]. STAR Protocols, 2022, 3(1): 101193.
[24] Lee S A, Holly K S, Voziyanov V, et al. Gradient index microlens implanted in prefrontal cortex of mouse does not affect behavioral test performance over time[J]. PLoS One, 2016, 11(1): e0146533.
[25] Pernici C D, Kemp B S, Murray T A. Time course images of cellular injury and recovery in murine brain with high-resolution GRIN lens system[J]. Scientific Reports, 2019, 9: 7946.
[26] Hsiao Y T, Wang A Y C, Lee T Y, et al. Using baseplating and a miniscope preanchored with an objective lens for calcium transient research in mice[J]. Journal of Visualized Experiments: JoVE, 2021(172): e62611.
[27] Carrier-Ruiz A, Sugaya Y, Kumar D, et al. Calcium imaging of adult-born neurons in freely moving mice[J]. STAR Protocols, 2021, 2(1): 100238.
[28] Zhang L F, Liang B, Barbera G, et al. Miniscope GRIN lens system for calcium imaging of neuronal activity from deep brain structures in behaving animals[J]. Current Protocols in Neuroscience, 2019, 86(1): e56.
[29] 李佳帅, 朱路文, 叶涛, 等. 神经血管单元与神经退行性疾病关系研究进展[J]. 中国康复理论与实践, 2018, 24(3): 287-289.
Li J S, Zhu L W, Ye T, et al. Relationship of neurovascular units and neurodegenerative diseases(review)[J]. Chinese Journal of Rehabilitation Theory and Practice, 2018, 24(3): 287-289.
[30] Chen Z H, Hambardzumyan D. Immune microenvironment in glioblastoma subtypes[J]. Frontiers in Immunology, 2018, 9: 1004.
[31] Larjavaara S, Mäntylä R, Salminen T, et al. Incidence of gliomas by anatomic location[J]. Neuro-Oncology, 2007, 9(3): 319-325.
[32] Venkataramani V, Yang Y, Schubert M C, et al. Glioblastoma hijacks neuronal mechanisms for brain invasion[J]. Cell, 2022, 185(16): 2899-2917.
[33] Elisaveta S, Jorg D, Cole Andrew J. The complexities underlying epilepsy in people with glioblastoma[J]. The Lancet Neurology, 2023, 22(6): 505-516.
[34] Barretto R P J, Ko T H, Jung J C, et al. Time-lapse imaging of disease progression in deep brain areas using fluorescence microendoscopy[J]. Nature Medicine, 2011, 17(2): 223-228.
[35] Toader A C, Regalado J M, Li Y R, et al. Anteromedial thalamus gates the selection and stabilization of long-term memories[J]. Cell, 2023, 186(7): 1369-1381.
[36] Barretto R P J, Messerschmidt B, Schnitzer M J. In vivo fluorescence imaging with high-resolution microlenses[J]. Nature Methods, 2009, 6(7): 511-512.
[37] Teresa A M, Michael J L. Singlet gradient index lens for deep in vivo multiphoton microscopy[J]. Journal of Biomedical Optics, 2012, 17(2): 021106.
[38] Antonini A, Sattin A, Moroni M, et al. Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness[J]. eLife, 2020, 9: e58882.
[39] Lee W M, Yun S H. Adaptive aberration correction of GRIN lenses for confocal endomicroscopy[J]. Optics Letters, 2011, 36(23): 4608-4610.
[40] Wang C, Ji N. Pupil-segmentation-based adaptive optical correction of a high-numerical-aperture gradient refractive index lens for two-photon fluorescence endoscopy[J]. Optics Letters, 2012, 37(11): 2001-2003.
[41] Wang C, Ji N. Characterization and improvement of three-dimensional imaging performance of GRIN-lens-based two-photon fluorescence endomicroscopes with adaptive optics[J]. Optics Express, 2013, 21(22): 27142-27154.
[42] Zhang Q R, Pan D S, Ji N. High-resolution in vivo optical-sectioning widefield microendoscopy[J]. Optica, 2020, 7(10): 1287-1290.
[43] Levene M J, Dombeck D A, Kasischke K A, et al. In vivo multiphoton microscopy of deep brain tissue[J]. Journal of Neurophysiology, 2004, 91(4): 1908-1912.
[44] Moretti C, Antonini A, Bovetti S, et al. Scanless functional imaging of hippocampal networks using patterned two-photon illumination through GRIN lenses[J]. Biomedical Optics Express, 2016, 7(10): 3958-3967.
[45] Meng G H, Liang Y J, Sarsfield S, et al. High-throughput synapse-resolving two-photon fluorescence microendoscopy for deep-brain volumetric imaging in vivo[J]. eLife, 2019, 8: e40805.
[46] Qin Z Y, Chen C P, He S C, et al. Adaptive optics two-photon endomicroscopy enables deep-brain imaging at synaptic resolution over large volumes[J]. Science Advances, 2020, 6(40): eabc6521.
[47] Chien Y F, Lin J Y, Yeh P T, et al. Dual GRIN lens two-photon endoscopy for high-speed volumetric and deep brain imaging[J]. Biomedical Optics Express, 2020, 12(1): 162-172.
[48] Helmchen F, Fee M S, Tank D W, et al. A miniature head-mounted two-photon microscope: high-resolution brain imaging in freely moving animals[J]. Neuron, 2001, 31(6): 903-912.
[49] Kerr J N, Nimmerjahn A. Functional imaging in freely moving animals[J]. Current Opinion in Neurobiology, 2012, 22(1): 45-53.
[50] Ghosh K K, Burns L D, Cocker E D, et al. Miniaturized integration of a fluorescence microscope[J]. Nature Methods, 2011, 8(10): 871-878.
[51] Sawinski J, Denk W. Miniature random-access fiber scanner for in vivo multiphoton imaging[J]. Journal of Applied Physics, 2007, 102(3): 034701.
[52] Zong W J, Wu R L, Li M L, et al. Fast high-resolution miniature two-photon microscopy for brain imaging in freely behaving mice[J]. Nature Methods, 2017, 14(7): 713-719.
[53] Klioutchnikov A, Wallace D J, Sawinski J, et al. A three-photon head-mounted microscope for imaging all layers of visual cortex in freely moving mice[J]. Nature Methods, 2023, 20(4): 610-616.
[54] Zhao C Z, Chen S Y, Zhang L F, et al. Miniature three-photon microscopy maximized for scattered fluorescence collection[J]. Nature Methods, 2023, 20(4): 617-622.
[55] Grewe B F, Gründemann J, Kitch L J, et al. Neural ensemble dynamics underlying a long-term associative memory[J]. Nature, 2017, 543(7647): 670-675.
[56] Barbera G, Jun R, Zhang Y, et al. A miniature fluorescence microscope for multi-plane imaging[J]. Scientific Reports, 2022, 12: 16686.
[57] Zong W J, Obenhaus H A, Skytøen E R, et al. Large-scale two-photon calcium imaging in freely moving mice[J]. Cell, 2022, 185(7): 1240-1256.
[58] Shekhtmeyster P, Carey E M, Duarte D, et al. Multiplex translaminar imaging in the spinal cord of behaving mice[J]. Nature Communications, 2023, 14: 1427.
[59] Flusberg B A, Jung J C, Cocker E D, et al. In vivo brain imaging using a portable 3.9 gram two-photon fluorescence microendoscope[J]. Optics Letters, 2005, 30(17): 2272-2274.
[60] Fan J T, Suo J L, Wu J M, et al. Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution[J]. Nature Photonics, 2019, 13(11): 809-816.
[61] Yang M K, Zhou Z Q, Zhang J X, et al. MATRIEX imaging: multiarea two-photon real-time in vivo explorer[J]. Light: Science & Applications, 2019, 8: 109.
[62] Pochechuev M S, Solotenkov M A, Fedotov I V, et al. Multisite cell-and neural-dynamics-resolving deep brain imaging in freely moving mice with implanted reconnectable fiber bundles[J]. Journal of Biophotonics, 2020, 13(11): e202000081.
[63] Choi Y, Yoon C, Kim M, et al. Scanner-free and wide-field endoscopic imaging by using a single multimode optical fiber[J]. Physical Review Letters, 2012, 109(20): 203901.
[64] Bianchi S, di Leonardo R. A multi-mode fiber probe for holographic micromanipulation and microscopy[J]. Lab on a Chip, 2012, 12(3): 635-639.
[65] Vellekoop I M, Mosk A P. Focusing coherent light through opaque strongly scattering media[J]. Optics Letters, 2007, 32(16): 2309-2311.
[66] Mosk A P, Lagendijk A, Lerosey G, et al. Controlling waves in space and time for imaging and focusing in complex media[J]. Nature Photonics, 2012, 6(5): 283-292.
[67] Horstmeyer R, Ruan H W, Yang C. Guidestar-assisted wavefront-shaping methods for focusing light into biological tissue[J]. Nature Photonics, 2015, 9(9): 563-571.
[68] Tzang O, Caravaca-Aguirre A M, Wagner K, et al. Adaptive wavefront shaping for controlling nonlinear multimode interactions in optical fibres[J]. Nature Photonics, 2018, 12(6): 368-374.
[69] Amitonova L V, de Boer J F. Endo-microscopy beyond the abbe and Nyquist limits[J]. Light: Science & Applications, 2020, 9: 81.
[70] Caravaca-Aguirre A M, Piestun R. Single multimode fiber endoscope[J]. Optics Express, 2017, 25(3): 1656-1665.
[71] Fischer B, Sternklar S. Image transmission and interferometry with multimode fibers using self-pumped phase conjugation[J]. Applied Physics Letters, 1985, 46(2): 113-114.
[72] Popoff S M, Lerosey G, Carminati R, et al. Measuring the transmission matrix in optics: an approach to the study and control of light propagation in disordered media[J]. Physical Review Letters, 2010, 104(10): 100601.
[73] Čižmár T, Dholakia K. Exploiting multimode waveguides for pure fibre-based imaging[J]. Nature Communications, 2012, 3: 1027.
[74] Farahi S, Ziegler D, Papadopoulos I N, et al. Dynamic bending compensation while focusing through a multimode fiber[J]. Optics Express, 2013, 21(19): 22504-22514.
[75] Gu R Y, Mahalati R N, Kahn J M. Design of flexible multi-mode fiber endoscope[J]. Optics Express, 2015, 23(21): 26905-26918.
[76] Gordon G S D, Gataric M, Ramos A G C P, et al. Characterizing optical fiber transmission matrices using metasurface reflector stacks for lensless imaging without distal access[J]. Physical Review X, 2019, 9(4): 041050.
[77] Li S H, Horsley S A R, Tyc T, et al. Memory effect assisted imaging through multimode optical fibres[J]. Nature Communications, 2021, 12: 3751.
[79] Shen B L, Liu S W, Li Y P, et al. Deep learning autofluorescence-harmonic microscopy[J]. Light, Science & Applications, 2022, 11(1): 76.
[80] Liao J H, Zhang C S, Xu X C, et al. Deep-MSIM: fast image reconstruction with deep learning in multifocal structured illumination microscopy[J]. Advanced Science, 2023, 10(27): e2300947.
[81] Fan P F, Zhao T R, Su L. Deep learning the high variability and randomness inside multimode fibers[J]. Optics Express, 2019, 27(15): 20241-20258.
[82] Fan P F, Wang Y F, Ruddlesden M, et al. Deep learning enabled scalable calibration of a dynamically deformed multimode fiber[J]. Advanced Photonics Research, 2022, 3(10): 2100304.
[83] Nicholas B, Tristan K, Lamb Erin S, et al. Transfer learning and generalization of a neural-network-based multimode fiber position and imaging sensor under thermal perturbations[J]. Optical Fiber Technology, 2022, 70: 102855.
[84] Plöschner M, Čižmár T. Compact multimode fiber beam-shaping system based on GPU accelerated digital holography[J]. Optics Letters, 2015, 40(2): 197-200.
[85] Vasquez-Lopez S A, Turcotte R, Koren V, et al. Subcellular spatial resolution achieved for deep-brain imaging in vivo using a minimally invasive multimode fiber[J]. Light: Science & Applications, 2018, 7: 110.
[86] Turtaev S, Leite I T, Altwegg-Boussac T, et al. High-fidelity multimode fibre-based endoscopy for deep brain in vivo imaging[J]. Light: Science & Applications, 2018, 7: 92.
[87] Shay O, Antonio C A, Rafael P, et al. Minimally invasive multimode optical fiber microendoscope for deep brain fluorescence imaging[J]. Biomedical Optics Express, 2018, 9(4): 1492-1509.
[88] Silveira B M, Pikálek T, Stibůrek M, et al. Side-view holographic endomicroscopy via a custom-terminated multimode fibre[J]. Optics Express, 2021, 29(15): 23083-23095.
[89] Stibůrek M, Ondráčková P, Tučková T, et al. 110 μm thin endo-microscope for deep-brain in vivo observations of neuronal connectivity, activity and blood flow dynamics[J]. Nature Communications, 2023, 14: 1897.
[90] Wen Z, Dong Z Y, Deng Q L, et al. Single multimode fibre for in vivo light-field-encoded endoscopic imaging[J]. Nature Photonics, 2023, 17(8): 679-687.
[91] Sato M, Motegi Y, Yagi S, et al. Fast varifocal two-photon microendoscope for imaging neuronal activity in the deep brain[J]. Biomedical Optics Express, 2017, 8(9): 4049-4060.
[92] Sanai N, Eschbacher J, Hattendorf G, et al. Intraoperative confocal microscopy for brain tumors: a feasibility analysis in humans[J]. Operative Neurosurgery, 2011, 68: 282-290.
[93] Martirosyan N L, Eschbacher J M, Kalani M Y S, et al. Prospective evaluation of the utility of intraoperative confocal laser endomicroscopy in patients with brain neoplasms using fluorescein sodium: experience with 74 cases[J]. Neurosurgical Focus, 2016, 40(3): E11.
[94] Teng C W, Huang V, Arguelles G R, et al. Applications of indocyanine green in brain tumor surgery: review of clinical evidence and emerging technologies[J]. Neurosurgical Focus, 2021, 50(1): E4.
[95] Ritz R, Feigl G C, Schuhmann M U, et al. Use of 5-ALA fluorescence guided endoscopic biopsy of a deep-seated primary malignant brain tumor[J]. Journal of Neurosurgery, 2011, 114(5): 1410-1413.
[96] Leroy H A, Vermandel M, Lejeune J P, et al. Fluorescence guided resection and glioblastoma in 2015: a review[J]. Lasers in Surgery and Medicine, 2015, 47(5): 441-451.
[97] Pavlov V, Meyronet D, Meyer-Bisch V, et al. Intraoperative probe-based confocal laser endomicroscopy in surgery and stereotactic biopsy of low-grade and high-grade gliomas: a feasibility study in humans[J]. Neurosurgery, 2016, 79(4): 604-612.
[98] Breuskin D, Szczygielski J, Urbschat S, et al. Confocal laser endomicroscopy in neurosurgery: an alternative to instantaneous sections?[J]. World Neurosurgery, 2017, 100: 180-185.
[99] Charalampaki P, Nakamura M, Athanasopoulos D, et al. Confocal-assisted multispectral fluorescent microscopy for brain tumor surgery[J]. Frontiers in Oncology, 2019, 9: 583.
[100] Irakliy A, Park M T, Gooldy T C, et al. Real-time intraoperative surgical telepathology using confocal laser endomicroscopy[J]. Neurosurgical Focus, 2022, 52(6): E9.
[101] Levchenko S M, Pliss A, Peng X, et al. Fluorescence lifetime imaging for studying DNA compaction and gene activities[J]. Light: Science & Applications, 2021, 10: 224.
[102] Lin F R, Zhang C S, Zhao Y H, et al. In vivo two-photon fluorescence lifetime imaging microendoscopy based on fiber-bundle[J]. Optics Letters, 2022, 47(9): 2137-2140.
[103] Liu Y F, Al-salihi M, Guo Y, et al. Halogen-doped phosphorescent carbon dots for grayscale patterning[J]. Light: Science & Applications, 2022, 11: 163.
[104] Chia T H, Williamson A, Spencer D D, et al. Multiphoton fluorescence lifetime imaging of intrinsic fluorescence in human and rat brain tissue reveals spatially distinct NADH binding[J]. Optics Express, 2008, 16(6): 4237-4249.
[105] Berezin M Y, Achilefu S. Fluorescence lifetime measurements and biological imaging[J]. Chemical Reviews, 2010, 110(5): 2641-2684.
[106] Kantelhardt S R, Kalasauskas D, König K, et al. In vivo multiphoton tomography and fluorescence lifetime imaging of human brain tumor tissue[J]. Journal of Neuro-Oncology, 2016, 127(3): 473-482.
[107] Butte P V, Mamelak A N, Nuno M, et al. Fluorescence lifetime spectroscopy for guided therapy of brain tumors[J]. NeuroImage, 2011, 54(Suppl 1): S125-S135.
[108] Fang Q Y, Papaioannou T, Jo J A, et al. Time-domain laser-induced fluorescence spectroscopy apparatus for clinical diagnostics[J]. Review of Scientific Instruments, 2004, 75(1): 151-162.
[109] Sun Y H, Hatami N, Yee M, et al. Fluorescence lifetime imaging microscopy for brain tumor image-guided surgery[J]. Journal of Biomedical Optics, 2010, 15(5): 056022.
[110] Marcu L, Hartl B A. Fluorescence lifetime spectroscopy and imaging in neurosurgery[J]. IEEE Journal of Selected Topics in Quantum Electronics, 2012, 18(4): 1465-1477.
[111] Alfonso-Garcia A, Bec J, Sridharan Weaver S, et al. Real-time augmented reality for delineation of surgical margins during neurosurgery using autofluorescence lifetime contrast[J]. Journal of Biophotonics, 2020, 13(1): e201900108.
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