肺癌筛查的影像技术进展  

Advances of imaging technology in lung cancer screening

作　　者：吴杰芳[1] 秦耿耿[1] 陈卫国[1] 

机构地区：[1]南方医科大学南方医院放射科,广州510515

出　　处：《国际医学放射学杂志》2017年第4期432-436,共5页International Journal of Medical Radiology

基　　金：广东科技计划面上项目(2016ZC0058)

摘　　要：肺癌的发病率很高,早期肺癌影像上常表现为小结节,但多无临床症状。普通X线胸片是最简便、常用的肺癌筛查手段,但对肺内小结节的敏感性及特异性不高。数字化断层融合技术空间分辨力较高,辐射剂量较CT低,相对于X线胸片能明显提高肺内小结节的检出率。与常规CT相比低剂量CT可作为早期肺癌筛查的一种首选检查方法。双能减影技术能获得单一软组织像和骨组织像,可提高肺内小结节检出率。基于神经网络学习的骨抑制技术能够在不需要额外增加辐射剂量和机器设备情况下提高早期肺癌的检出率。Lung cancer has a high incidence rate. In the early stage, the lesion usually manifests as small nodules radiogically, and no symptoms clinically. Chest X-ray is the most simple, commonly means of screening, but with a low sensitivity and specificity in detecting small lung nodules. Digital tomosynthesis has advantages of high spacial resolution and relatively low-radiation dose compared to CT, it largely improves the ability in detecting small nodules compared to conventional radiography. Compared to CT, low-dose CT is considered to be the first line of tool in screening. Dual-energy subtraction can simultaneously obtain both soft tissue and bony images, and can increase the detection rate. Bone suppression based on neural network learning can improve the detection rate of early lung cancer without additional radiation dose and additional equipment.

关 键 词：肺癌 胸片 低剂量CT 数字化断层融合技术 双能减影 基于神经网络学习的骨抑制技术 

分 类 号：R445[医药卫生—影像医学与核医学] R734.2[医药卫生—诊断学]