基于分子靶向和多模融合的肝癌边界精准定位方法关键技术研究

The border of hepatocellular carcinoma is an urgent medical problem related to the success of liver cancer surgery. The development of molecular imaging technology especially multi-modality molecular imaging promote the study on this problem. In the project, a great effort is devoted to developing a three dimensional reconstruction method of liver cancer distribution based on the fusion of bioluminescent tomography,fluorescent tomography technology and computed tomography. First, a high sensitivity and specificity dual modality probe was developed for accurate targeting the liver cancer cells based on the antigen-antibodies binding reaction; Second, an accurate rapid fluorescent tomography reconstruction techniques were studies based on background noise filtering technology under real biological environment, and a bioluminescence tomography technique was studied based on adaptive finite element; furthermore, a multimode fusion algorithm was developed to improve the accuracy of reconstruction based on the above two technologies and an image technology based on threshold will be used to extract the boundary of orthotopic liver carcinoma . Third, a registration method between the reconstructed three dimensional liver cancer distribution and two dimensional pathology image will be developed to achieve mutual authentication and feedback. The project will use molecular targeting biotechnology and multimode fusion imaging techniques to achieve accurate three dimensional liver cancer distribution and the border of the orthotopic cancer will be extract using the image segmentation method based on threshold. The research results of the project are hoped to promote the development of application of multimodality molecular imaging in liver cancer surgery in the near future.

肝癌边界的精准定位是一个挑战性问题，关系着肝癌手术成功与否，多模分子影像技术推动了该问题的研究。本课题以肝癌边界的准确定位为研究目标，以自发荧光断层重建（BLT）和激发荧光断层（FMT）重建的多模融合方法为手段，重点开展以下几个关键问题的研究。首先，构建带有SM5-1抗体、RLuc氨基端的激发荧光和自发荧光双模态探针，实现探针对肝癌细胞的准确靶向；其次，研究在真实生物环境、复杂噪声背景下的基于背景去除的激发荧光和基于衰减校正的自发荧光及计算机断层重建（Micro-CT）的融合技术，重建肝癌的三维图像，利用阈值分割提取肝癌边界的三维分布；第三,为了用金标准的病理图像评估肝癌边界分布的准确性，研究二者之间的配准方法，进一步改进肝癌边界的定位精度。概括而言，本项目将利用分子靶向的探针技术和多模融合的成像技术对肝癌进行定量的三维分布重建和边界提取，推动肝癌手术导航的发展。

本项目围绕着肝癌边界的精准定位问题，研究了以下几个关键科学问题，首先，构建了带有SM5-1抗体、RLuc氨基端的激发荧光和自发荧光双模态探针，进行了肝癌的诊断和治疗实验，确定了抗体的靶向作用，在国际高水平SCI期刊发表了多篇论文，包括在生物材料的权威期刊Biomaterials、Current Molecular Medicine等上；研究了真实生物环境、复杂噪声北京下的基于背景去除的激发荧光和基于衰减校正的自发荧光及计算机断层重建的融合技术，重建肝癌的三维图像，利于阈值分割提取肝癌边界的三维分布，相关的研究成果发表在了医学图像的国际SCI期刊IEEE Transactions on Medical Imaging, Advanced Functional Materials等上；同时，我们也用金标准的病理图像评估肝癌边界分布的准确性，研究二者之间的配准方法，进一步改善了肝癌边界的定位精度。概括而言，我们初步完成了本项目立项时的既定目标，发表了9篇SCI国际期刊论文。