TRD1: Functional Imaging

项目摘要 TRD 1 TRD 1的首要主题是为功能成像开发强大的新工具：具体来说， 采用先进的后处理方法，1）增强偏振敏感图像的内源对比度 OCT组织偏振测量，以及2）将OCT血管造影术从伪三维技术转变为全三维技术， 从而大大提高其截面质量和深度分辨率。OCT偏振测量中的后处理技术 （PS-OCT）和血管造影术（OCTA）会造成显著的分辨率损失-大约是一个量级- 与原始OCT数据相比，以较差的空间分辨率产生对比度。我们需要一个过程- 使用能够保持空间分辨率的技术，以实现广泛的应用， 目前OCT技术无法达到。本项目将开发一个概率处理框架 基于光散射和OCT图像形成的物理原理，利用函数的相似性， 典型地存在于生物样本断层图像中的信号。这一框架将允许估计 底层结构和相关的对比度-或功能-而不影响空间分辨率。 目的1解决了需要高分辨率的横截面偏振成像的生活视网膜。前- 双向PS-OCT提供了一种新的途径来保持原始硬件的分辨率， 增加的光学分辨率，受人和动物瞳孔大小的限制，并伴随着不切实际的重复， 在景深的情况下。这种新的功能，结合PS-OCT硬件配备自适应运算， tics将能够确定视网膜中单个轴突束的偏振参数。它将 允许PS-OCT在体内灵敏地跟踪视网膜轴突变性，从而加速视网膜变性的发展。 用于治疗多发性硬化症的神经保护剂，其依赖于该疾病的啮齿动物模型。 目标2解决了在临床前和临床中提高OCTA的空间分辨率和质量的需求 通过进一步将概率框架扩展到OCT信号动态特性，可以更好地分析OCT应用。OCTA还显示- 在眼科学中具有重要的前景，可用于疾病的早期诊断和监测 包括青光眼和糖尿病视网膜病变;临床前使用包括成像动物模型，以改善 肿瘤生物学的地位。然而，其较差的横截面质量和分辨率限制了OCTA的伪 3D成像技术，深度分辨率通常比原始成像技术差4到8倍。 OCT断层扫描，因此在几乎所有应用中将血管造影分析限制为面投影和层投影。 OCTA可能会改善常规OCTA深度分辨率不足的问题， 小毛细血管和真实血管尺寸的扭曲，目前破坏口径和血管， 在眼科学中具有重大临床意义的大网络定量度量。OCTA具有高横截面质量， 它将放大其在理解三维肿瘤微环境中的效用，并解开 体积血管网络指标在临床前和临床应用中的作用。

Project Summary TRD 1 The overarching theme of TRD 1 is to develop powerful new tools for functional imaging: specifically, the devel- opment of advanced post-processing methods to 1) enhance endogenous contrast in polarization-sensitive OCT tissue polarimetry, and 2) transform OCT angiography from a pseudo- to a fully-3D technique by dramati- cally improving its cross-sectional quality and depth resolution. Current post-processing in OCT polarimetry (PS-OCT) and angiography (OCTA) imparts significant resolution loss—roughly one order of magnitude—gen- erating contrast with poor spatial resolution compared to the originating OCT data. There is a need for process- ing techniques capable of preserving spatial resolution to enable a broad range of applications that are presently outside the reach of OCT technology. This project will develop a probabilistic processing framework based on the physics of light scattering and OCT image formation that leverages from the similarity of func- tional signals typically present in biological sample tomograms. This framework will allow for estimation of the underlying structure and associated contrast—or function—without compromising spatial resolution. Aim 1 addresses the need for high-resolution cross-sectional polarimetric imaging of the living retina. Proba- bilistic PS-OCT offers a new pathway to preserve the originating hardware’s resolution, alleviating the need for increased optical resolution, limited by pupil size in human and animals and accompanied by an impractical re- duction in the depth of field. This novel capability, combined with PS-OCT hardware equipped with adaptive op- tics, will enable the determination of polarimetric parameters of individual axonal bundles in the retina. It will permit PS-OCT to sensitively track retinal axonal degeneration in vivo, thus accelerating the development of neuroprotective agents for the treatment of multiple sclerosis that rely on rodent models of this disease. Aim 2 addresses the need to improve the spatial resolution and quality of OCTA in both preclinical and clinical applications by further extending the probabilistic framework to the OCT signal dynamics. OCTA is also show- ing significant promise in ophthalmology for the potential use in the early diagnosis and monitoring of diseases including glaucoma and diabetic retinopathy; preclinical use include imaging animal models to improve under- standing of tumor biology. However, its poor cross-sectional quality and resolution restricts OCTA to a pseudo- 3D imaging technique, with a depth resolution most commonly four to eight times poorer than in the originating OCT tomogram, thus limiting angiographic analysis to en face and layer projections in virtually all applications. Probabilistic OCTA will improve the lacking depth resolution of conventional OCTA, overcoming the insensitivity to small capillaries and the distortion of true vessel dimensions, which currently undermine caliber and vascu- lar-network quantitative metrics of great clinical interest in ophthalmology. OCTA with high cross-sectional qual- ity would amplify its utility in the understanding of the three-dimensional tumor microenvironment, and unlock the power of volumetric vascular-network metrics in preclinical and clinical applications.