摘要
目的研究能谱CT最佳单能量图像联合多平面重组技术(MPR)在腰骶部周围神经检查中的应用。方法回顾性分析我院52例怀疑腰骶部周围神经病变的患者,均行能谱CT检查,应用能谱CT最佳单能量分析软件,寻找腰骶部神经与邻近组织具有最佳对比噪声比(CNR)时的最佳单能量(keV)值,每位患者测量3次,计算平均值作为显示的最佳单能量值。由两位高年资影像医师采用双盲法阅片,应用最佳单能量图像和常规混合能量(约70 keV)图像分别联合MPR技术对腰骶部周围神经病变的显示及其图像质量进行分析和对照,评价能谱两种技术方法对腰骶部周围神经显示的图像质量及能力,同时客观测量最佳keV图像和常规CT(约70 keV)图像腰骶部神经和周围肌肉的CNR。结果能谱CT最佳keV[(63.64±1.36)keV]图像联合MPR同层显示技术能明显提高腰骶部周围神经及病变的显示,能谱CT最佳keV图像联合MPR技术显示腰骶部神经的图像质量主观评分明显优于混合能量图像(P=0.03;z=-2.12);最佳单能量和混合能量图像的CNR分别为0.81±0.37和0.44±0.26(P=0.02)。能谱CT最佳单能量成像能较清晰显示周围神经束的正常走行、解剖变异、神经受压、黏连及与邻近组织的关系。结论能谱CT最佳单能量图像联合MPR重组技术能改善图像质量,还提供了一种显示腰骶部周围神经病变的新方式。
Objective To assess the value of virtual monochromatic images at optimal energy level in dual-energy spectral CT(DECT)with multiplanar reformation(MPR)for diagnosing lumbosacral peripheral neuropathy.Methods DECT of 52 patients with suspected lumbosacral peripheral neuropathy was retrospectively analyzed.From the set of virtual monochromatic images,an optimal energy level was selected to obtain the highest contrast-to-noise ratio for the lumbosacral nerves of each patient.Two experienced radiologists evaluated in a double-blind manner the clarity of the peripheral nerves and neuropathy on both the DECT and conventional kVp CT MPR images.Results The display clarity of the normal peripheral nerve bundles and anatomical variants in relationship with adjacent soft tissue or bones as well as any neural compression was better on DECT MPR reconstruction at the optimal energy level of(63.64±1.36)keV than conventional CT images(P=0.02).Conclusion DECT at the optimal energy level with MPR can improve image quality and depiction of lumbosacral peripheral nerves and neuropathy.
作者
杨创勃
于楠
马光明
段海峰
于勇
张喜荣
段小艺
贾永军
YANG Chuang-bo;YU Nan;MA Guang-ming;DUAN Hai-feng;YU Yong;ZHANG Xi-rong;DUAN Xiao-yi;JIA Yong-jun(Department of Radiology,Affiliated Hospital of Shaanxi University of Chinese Medicine,Shaanxi 712000,China)
出处
《影像诊断与介入放射学》
2020年第5期356-360,共5页
Diagnostic Imaging & Interventional Radiology
基金
国家自然科学基金资助项目(81701691)
陕西中医药大学校级科研课题国家基金面上培育项目(2020GP10)
陕西中医药大学学科创新团队建设项目(2019-QN09)。
关键词
体层摄影术
X线计算机
周围神经
能谱成像
Tomography,X-ray computed
Peripheral nerve
Energy spectrum imaging
