Parametric Optical Diffusion Tomography

荧光光学扩散层析成像(FODT)使用扩散散射光来成像组织的深处。这种新的生物医学成像方式在癌症的早期诊断和新药物的开发方面具有巨大的潜力，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结合，以针对特定的癌症或感兴趣的生物过程；3)它是微创的，因为它只需要暴露在光中；4)它具有低成本的潜力，因为它不需要相干光源和解调。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反射的光中重建图像。这项研究为FODT技术奠定了基础，开发了能够从这种漫射散射光准确重建FODT图像的算法。这些算法基于贝叶斯逆方法和由此产生的成本泛函的多重网格优化。这项研究的关键目标是重建准确的荧光产额体积再现，直接估计药物动力学参数，形成利用调制和波长多样性来提高特异性的重建，并开发新的偏振敏感成像方法。2.努力程度声明：绩效指标将尽一切努力满足项目最初的努力范围和水平。

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.