3种肺癌肿瘤模型活体成像的系统优化与技术研究

Optimization of in vivo imaging conditions and techniques for three different tumor models of lung cancer

通过优化荧光素酶的生物发光及荧光发光报告体系,结合光谱拆分技术,进一步提高活体成像技术在肿瘤检测中的灵敏性,并探寻肿瘤监测成像的最佳方法。利用建立的肺癌肿瘤转移模型、肺癌原位肿瘤模型和肺癌皮下肿瘤模型等小鼠肿瘤模型,并用小动物活体成像仪对这3种肿瘤模型小鼠进行荧光成像和生物发光成像比较。结果表明:毛发对活体成像有干扰,且对荧光成像影响较大。在小鼠肺癌转移模型和原位肿瘤模型中,荧光成像自发荧光高,信噪比低,适合用生物发光进行研究,但利用光谱拆分技术能有效去除自发荧光,可得到与生物发光成像相似的结果;而在小鼠肺癌皮下肿瘤模型中,荧光成像即可满足对肿瘤连续、动态的监测。总体而言,利用光谱拆分技术可实现荧光成像对体内不同肿瘤模型的监测。

To optimize the conditions of bioluminescence imaging and fluorescence imaging system and improve the sensitivity of imaging technology in vivo, several tumor monitoring imaging methods were investigated by using in vivo imaging system(IVIS) Spectrum combined with spectral unmixing. Three tumor models were established, including lung cancer metastasis model, in situ tumor model and subcutaneous tumor model. Then fluorescence imaging and bioluminescence imaging were performed simultaneously to compare with each other. The results showed that mouse hairs had more effects on fluorescence imaging than that on bioluminescence imaging. Fluorescence imaging had highest spontaneous fluorescence, lowest signal-to-noise ratio, while bioluminescence imaging had highest signal-to-noise ratio. Spectral unmixing could effectively eliminate spontaneous fluorescence. Due to the influence of spontaneous fluorescence, it was more suitable to use bioluminescence imaging in the lung cancer metastasis model and in situ tumor model. However, similar results were also obtained with bioluminescence imaging by using spectral unmixing. Furthermore, fluorescence imaging can be used for the continuous and dynamic monitoring of tumor growth in the subcutaneous tumor model. Therefore, spectral unmixing can be used to monitor different tumor models in vivo.