In vivo Macroscopic Fluorescence Lifetime Molecular Optical Imaging

在体宏观荧光寿命分子光学成像 摘要 仍然非常需要在体内更好地表征新的靶向疗法，特别是在临床应用之前。 翻译.在这方面，临床前分子成像是靶向药物开发管道中的核心工具。 然而，目前仍缺乏能够实现纵向（多个时间点） 和复杂指纹的空间分辨监测，包括分子、代谢和功能 在同一肿瘤/受试者中的签名。这一新的综合多路成像平台将发挥至关重要的作用 在开发下一代靶向药物和阐明（多）耐药机制方面。 最近，我们已经证明了光学成像在定量受体靶点方面的独特能力。 通过利用荧光寿命参与活体受试者。这一优异成绩实现了 由于仪器、算法和生物化学创新的结合，第一次， 基于用于2D或3D Förster共振能量的结构光的全身时间分辨光学成像 转移（FRET）成像。在此，我们将进一步影响光学临床前成像领域， 通过1）集成尖端的高分辨率、时间分辨SPAD阵列成像仪， 提高光子收集效率，空间分辨率和便携性; 2）我们将利用最新的 深度学习（DL）的发展，用于超快速，定量，但拟合/迭代逆解算器免费图像 形成，在2D和3D中提供图像形成/处理解决方案以促进多路复用成像; 3） 我们将在我们的成像平台中实现新的功能， 多种临床相关的靶-受体相互作用（例如，HER受体家族成员参与许多靶-受体相互作用）。 癌症）以及在活的完整动物中整个肿瘤区域的代谢和功能状态。

In vivo Macroscopic Fluorescence Lifetime Molecular Optical Imaging ABSTRACT There is still great need in better characterizing new targeted therapies in vivo, especially prior to clinical translation. In this regard, preclinical molecular imaging is a central tool in the targeted drug development pipeline. However, there is still a lack of integrated imaging platforms that can enable longitudinal (multiple time points) and spatially-resolved monitoring of complex fingerprints including molecular, metabolic and functional signatures in the same tumor/subject. This new integrated multiplexing imaging platform will play a crucial role in the development of the next generation of targeted drugs and elucidating (multi-) drug resistance mechanisms. Recently, we have demonstrated the unique capabilities of optical imaging in quantifying receptor-target engagement in live subjects by leveraging fluorescence lifetime. This outstanding achievement was realized thanks to the combination of instrumental, algorithmic and biochemical innovations to enable, for the first time, whole-body time-resolved optical imaging based on structured light for 2D or 3D Förster resonance energy transfer (FRET) imaging in live subjects. Herein, we will further impact the field of optical preclinical imaging and drug delivery assessment by 1) integrating a cutting-edge high-resolution, time-resolved SPAD array imager for improved photon collection efficiency, spatial resolution, and portability; 2) we will harness the latest developments in Deep Learning (DL) for ultra-fast, quantitative, but fitting/iterative inverse solver-free image formation, in both 2D and 3D providing image formation/processing solutions to facilitate multiplexed imaging; 3) we will implement new functionalities in our imaging platform to enable the concurrent longitudinal imaging of multiple clinically relevant target-receptor interactions (e.g. HER receptor family members involved in many cancers) as well as metabolic and functional status across the whole-tumor region in live intact animals.