Department of Physics, East Carolina University, Greenville, North Carolina 27858, USA.
Med Phys. 2007 Jul;34(7):2939-48. doi: 10.1118/1.2745241.
Reflectance imaging of biological tissues with visible and near-infrared light has the significant potential to provide a noninvasive and safe imaging modality for diagnosis of dysplastic and malignant lesions in the superficial tissue layers. The difficulty in the extraction of optical and structural parameters lies in the lack of efficient methods for accurate modeling of light scattering in biological tissues of turbid nature. We present a parallel Monte Carlo method for accurate and efficient modeling of reflectance images from turbid tissue phantoms. A parallel Monte Carlo code has been developed with the message passing interface and evaluated on a computing cluster with 16 processing elements. The code was validated against the solutions of the radiative transfer equation on the bidirectional reflection and transmission functions. With this code we investigated numerically the dependence of reflectance image on the imaging system and phantom parameters. The contrasts of reflectance images were found to be nearly independent of the numerical aperture (NA) of the imaging camera despite the fact that reflectance depends on the NA. This enables efficient simulations of the reflectance images using an NA at 1.00. Using heterogeneous tissue phantoms with an embedded region simulating a lesion, we investigated the correlation between the reflectance image profile or contrast and the phantom parameters. It has been shown that the image contrast approaches 0 when the single-scattering albedos of the two regions in the heterogeneous phantoms become matched. Furthermore, a zone of detection has been demonstrated for determination of the thickness of the embedded region and optical parameters from the reflectance image profile and contrast. Therefore, the utility of the reflectance imaging method with visible and near-infrared light has been firmly established. We conclude from these results that the optical parameters of the embedded region can be determined inversely from reflectance images acquired with full-field illumination at multiple incident angles or multiple wavelengths.
利用可见近红外光对生物组织进行反射成像，具有提供一种非侵入式和安全的诊断方法的巨大潜力，可用于诊断浅表组织层的发育不良和恶性病变。提取光学和结构参数的难点在于缺乏用于准确模拟混浊生物组织中光散射的有效方法。我们提出了一种用于混浊组织模型反射图像的精确和高效建模的并行蒙特卡罗方法。已经使用消息传递接口开发了并行蒙特卡罗代码，并在具有 16 个处理元件的计算集群上进行了评估。该代码已针对双向反射和传输函数的辐射传输方程的解进行了验证。通过此代码，我们数值研究了反射图像对成像系统和模型参数的依赖性。尽管反射取决于数值孔径（NA），但发现反射图像的对比度几乎与成像相机的 NA 无关。这使得可以使用 1.00 的 NA 有效地模拟反射图像。使用具有嵌入区域的不均匀组织模型来模拟病变，我们研究了反射图像轮廓或对比度与模型参数之间的相关性。已经表明，当不均匀模型中两个区域的单次散射反照率匹配时，图像对比度趋近于 0。此外，已经证明了从反射图像轮廓和对比度确定嵌入区域的厚度和光学参数的检测区域。因此，利用可见近红外光进行反射成像的方法的实用性已经得到了充分的证明。我们从这些结果得出结论，从使用全视野照明在多个入射角或多个波长下获取的反射图像中，可以反演嵌入区域的光学参数。
