摘要
肿瘤在功能图像中表现出的非均匀特性能够一定程度上反应出其基本特性和对治疗的响应,对这一特性的数学描述和建模可为治疗和预估治疗效果提供有意义的量化参考数据.本文提出一种新的放射性同位素氟18标记的脱氧葡萄糖(18F-FDG)正电子发射断层影像(PET)中肿瘤内部非均匀性计算模型,通过图像中相邻像素的FDG标准摄取值(SUV)差异和其位置特征,可得出能描述肿瘤图像呈现的非均匀特性的参数H指数.使用矩形和高斯球模体以及3例肺癌患者数据,通过与灰度共生矩阵(GLCM)图像分析法比较研究,验证了该模型的有效性.
The intra-tumoral heterogeneity information of cancers from functional images can reflect their basic characteristics and responses to treatment. Mathematical illustration and modeling of this character- istic will provide effective ways for the quantitative analysis of the responses. A new model is proposed to assess tumor heterogeneity by summing up the voxel-wise distribution of differential standard uptake value (SUV) of fluorodeoxyglucose (FDG) from the 18F-FDG positron emission tomography(PET) image data. Based on square testing graphics, spherical phantoms and the lSF-FDG PET image data of 3 lung cancer patients, the new model with the H index was compared with a widely-used model of gray level co-occur- rence matrix (GLCM) for image texture characterization, thus verifying its effectiveness.
出处
《纳米技术与精密工程》
CAS
CSCD
2013年第3期247-251,共5页
Nanotechnology and Precision Engineering
基金
国家科技支撑计划资助项目(2012BAI15B01)