Wang Roujia, Deutsch Riley J, Sunassee Enakshi D, Crouch Brian T, Ramanujam Nirmala
Department of Biomedical Engineering, Duke University, Durham, NC, USA.
Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, USA.
BME Front. 2023 Jan 13;4:0005. doi: 10.34133/bmef.0005. eCollection 2023.
We developed a generalized computational approach to design uniform, high-intensity excitation light for low-cost, quantitative fluorescence imaging of in vitro, ex vivo, and in vivo samples with a single device. Fluorescence imaging is a ubiquitous tool for biomedical applications. Researchers extensively modify existing systems for tissue imaging, increasing the time and effort needed for translational research and thick tissue imaging. These modifications are application-specific, requiring new designs to scale across sample types. We implemented a computational model to simulate light propagation from multiple sources. Using a global optimization algorithm and a custom cost function, we determined the spatial positioning of optical fibers to generate 2 illumination profiles. These results were implemented to image core needle biopsies, preclinical mammary tumors, or tumor-derived organoids. Samples were stained with molecular probes and imaged with uniform and nonuniform illumination. Simulation results were faithfully translated to benchtop systems. We demonstrated that uniform illumination increased the reliability of intraimage analysis compared to nonuniform illumination and was concordant with traditional histological findings. The computational approach was used to optimize the illumination geometry for the purposes of imaging 3 different fluorophores through a mammary window chamber model. Illumination specifically designed for intravital tumor imaging generated higher image contrast compared to the case in which illumination originally optimized for biopsy images was used. We demonstrate the significance of using a computationally designed illumination for in vitro, ex vivo, and in vivo fluorescence imaging. Application-specific illumination increased the reliability of intraimage analysis and enhanced the local contrast of biological features. This approach is generalizable across light sources, biological applications, and detectors.
我们开发了一种通用的计算方法，用于设计均匀、高强度的激发光，以便使用单个设备对体外、离体和体内样本进行低成本的定量荧光成像。荧光成像在生物医学应用中是一种普遍使用的工具。研究人员广泛修改现有的组织成像系统，这增加了转化研究和厚组织成像所需的时间和精力。这些修改是针对特定应用的，需要新的设计才能扩展到不同类型的样本。我们实施了一个计算模型来模拟来自多个光源的光传播。使用全局优化算法和自定义成本函数，我们确定了光纤的空间定位，以生成两种照明模式。这些结果被应用于对粗针活检样本、临床前乳腺肿瘤或肿瘤衍生类器官进行成像。样本用分子探针染色，并用均匀和非均匀照明进行成像。模拟结果被忠实地转化为台式系统。我们证明，与非均匀照明相比，均匀照明提高了图像内分析的可靠性，并且与传统组织学结果一致。该计算方法用于通过乳腺窗室模型优化照明几何结构，以便对三种不同的荧光团进行成像。与使用最初为活检图像优化的照明相比，专门为活体肿瘤成像设计的照明产生了更高的图像对比度。我们证明了使用计算设计的照明进行体外、离体和体内荧光成像的重要性。特定应用的照明提高了图像内分析的可靠性，并增强了生物特征的局部对比度。这种方法可推广到不同的光源、生物应用和探测器。
