Parametric Optical Diffusion Tomography

荧光光学扩散断层扫描（FODT）使用漫散射光深入组织成像。这种新的生物医学成像模式在癌症的早期诊断和新药物的开发中具有巨大的潜力，因为：1）它提供了光谱学的化学和分子特异性; 2）它还可以与荧光分子成像剂偶联以靶向特定的癌症或感兴趣的生物过程; 3）它是微创的，因为它只需要暴露于光; 4）由于它不需要相干光源和解调，因此具有低成本的潜力。然而，这项技术的一个关键障碍是创建算法，该算法可以从被看似不透明的组织漫散射的光中重建图像。本研究通过开发可以从这种漫散射光精确重建FODT图像的算法，为FODT技术奠定了基础。该算法是基于贝叶斯逆方法和多重网格优化的成本泛函。该研究的关键目标是重建准确的荧光产量体积渲染，直接估计药效学参数，形成重建，使用调制和波长多样性，以提高特异性，并开发新的偏振敏感成像方法。2.工作水平声明：PI将尽一切努力满足项目的原始范围和工作水平。

Fluorescence optical diffusion tomography (FODT) uses diffusely scattered light to image deep into tissue. This new biomedical imaging modality has tremendous potential in the early diagnosis of cancer and the development of new pharmaceuticals because: 1) it offers the chemical and molecular specificity of spectroscopy; 2) it can also be coupled to fluorescent molecular imaging agents to target specific cancers or biological processes of interest; 3) it is minimally invasive since it only requires exposure to light; 4) it has the potential to be low cost since it does not require coherent optical sources and demodulation. However, a critical barrier to this technology is the creation of algorithms which can reconstruct images from light that has been diffusely scattered by seemingly opaque tissue. This research creates the foundation for FODT technology by developing the algorithms that can accurately reconstruct FODT images from this diffusely scattered light. The algorithms are based on Bayesian inverse methods and multigrid optimization of the resulting cost functionals. Critical goals of the research are to reconstruct accurate fluorescence yield volume renderings, to directly estimate pharmaco-kinetic parameters, to form reconstructions which use modulation and wavelength diversity to improve specificity, and to develop novel polarization-sensitive imaging methods. 2. A level of effort statement: The PIs will make every attempt to meet to the original scope and level of effort of the project.