Modeling the photon propagation for optical molecular imaging

描述(申请人提供)：基于荧光和生物发光的光学分子层析成像已经成为生物医学成像的一个主要领域。它有助于在人类疾病的小动物模型中定位和量化分子和细胞特征，并有助于监测病理变化，评估治疗反应，并促进药物研究和开发。光学分子成像捕捉通过生物组织的扩散光子。光子在这类介质中的输运主要表现为吸收和散射。辐射输运方程在理论上是准确的，但在计算上是不切实际的。最流行的生物医学光学模型是近似描述光子与生物组织相互作用的扩散近似，但它只有在某些条件下才能很好地工作，如在高散射和弱吸收介质中。由于扩散近似与物理现实之间的不匹配，这一限制严重影响了多光谱光学分子成像。例如，生物发光成像涉及的光谱范围[400 nm，600 nm]，在此范围内，小鼠实体器官有相对较大的吸收，使得扩散近似相当不准确。此外，在荧光分子成像中使用的高频模式下，扩散近似是有问题的。在解决不适定光学层析成像问题时，模型失配对图像质量的影响最大。目前，还没有一个完善的光学分子成像的光子传播模型。我们这个项目的总体目标是开发一个相位近似模型来取代用于光学分子成像的扩散近似模型。新模型基于广义相函数，使扩散近似成为一种特例，在数学上等价于辐射输运方程，在计算上与扩散近似模型相当。我们的初步数据表明，在生物相关的光学参数的广泛范围内，我们的相位近似与辐射传输方程一样准确。具体目标是(1)系统地建立稳态、频率和时间分辨模式下的光子注量率和通量矢量的相位近似模型；(2)开发基于相位近似的实用算法来描述小鼠解剖结构中的光子传输；(3)进行数值模拟和体模实验，以评估和验证基于相位近似的算法在强吸收、近光源、跨边界和高频模式下的有效性。本项目完成后，与蒙特卡罗数据和实验数据相比，在任何一组生物相关的光学参数下，从相位近似模型得到的光子注量率和通量矢量的相对误差将被验证为&lt；5%，对于反照率而言，扩散近似模型的精度提高了30%。据估计，相位近似模型的计算成本将比扩散近似模型增加&lt；20%。所提出的技术将显著增强光学分子成像，用于广泛的临床前成像应用。在这个项目中，我们将开发一种新的光子输运模型--相位近似模型来取代在生物光子学领域流行了几十年的、专门用于光学分子层析的扩散近似模型。在广泛的生物相关光学参数范围内，新模型的结果将一致地比扩散近似模型更准确，而计算成本与扩散近似模型相当。所提出的技术将显著提高光学生物医学成像在临床前的广泛应用。

DESCRIPTION (provided by applicant): Optical molecular tomography based on fluorescence and bioluminescence has emerged as a major area of biomedical imaging. It is instrumental for localizing and quantifying molecular and cellular features in small animal models of human diseases, and helps monitor pathological changes, evaluate therapeutic responses, and facilitate drug research and development. Optical molecular imaging captures diffusive photons through the biological tissue. The photon transport in such media is mainly characterized by absorption and scattering. The radiative transport equation is theoretically accurate but computationally impractical. The most popular model for biomedical optics is the diffusion approximation that approximately describes the interaction of photons with the biological tissue but it only works well under certain conditions such as in highly scattering and weakly absorbing media. This limitation significantly compromises multi- spectral optical molecular imaging due to the mismatch between the diffusion approximation and the physical reality. For example, bioluminescence imaging involves a spectral range [400nm, 600nm] over which there is relatively large absorption in solid mouse organs, rendering the diffusion approximation quite inaccurate. Moreover, the diffusion approximation is problematic in the high frequency mode as used in fluorescence molecular imaging. The model mismatch would have the most adverse effect on image quality in solving ill-posed optical tomography problems. Currently, there is no photon propagation model that is well-rounded for optical molecular imaging. Our overall goal of this project is to develop a phase approximation model to replace the diffusion approximation model for optical molecular imaging. The new model is based on a generalized phase function, make the diffusion approximation a special case, mathematically equivalent to the radiative transport equation and computationally comparable to the diffusion approximation model. Our preliminary data show that our phase approximation works as accurately as the radiative transport equation over a broad range of biologically relevant optical parameters. The specific aims are to (1) formulate the phase approximation model systematically with respect to the photon fluence rate and flux vector in the steady-state, frequency and time-resolved modes respectively, (2) develop practical algorithms based on the phase approximation to describe the photon transport in the mouse anatomy, (3) perform numerical simulation and phantom experiments to evaluate and validate the phase approximation based algorithms with strong absorbers, near light sources, across boundaries, and in the high frequency mode. Upon completion of this project, the relative errors of the photon fluence rate and flux vector obtained from the phase approximation model will have been validated as <5% as compared with the Monte Carlo data and experimental data over any set of biologically relevant optical parameters, and >30% accuracy improvement been made against the diffusion approximation model for albedo <10. The computational cost of the phase approximation model will have been evaluated as <20% increment than that of the diffusion approximation model. The proposed techniques will significantly enhance optical molecular imaging for a wide variety of pre-clinical imaging applications. In this project, we will develop a novel photon transport model - the phase approximation model to replace the diffusion approximation model that has been popular in the bio-photonics field for decades and exclusively used for optical molecular tomography. Over a broad range of biologically relevant optical parameters, the new model will produce results consistently more accurate than the diffusion approximation model at a computational cost comparable to the diffusion approximation counterpart. The proposed techniques will significantly improve optical biomedical imaging for a wide variety of pre-clinical applications.