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能谱CT定量分析对孤立性肺结节/肿块鉴别诊断的初步研究
引用本文:江德胜,韦炜,李丹,许实成,李君君,江帆,张晓云,袁家长,邓克学.能谱CT定量分析对孤立性肺结节/肿块鉴别诊断的初步研究[J].安徽医科大学学报,2017,52(3).
作者姓名:江德胜  韦炜  李丹  许实成  李君君  江帆  张晓云  袁家长  邓克学
作者单位:安徽医科大学附属省立医院影像科,合肥,230001;安徽省六安市世立医院影像科,六安,237000
摘    要:目的 探讨能谱电子计算机断层扫描(CT)成像定量分析对肺结节、肿块诊断的应用价值.方法 选取129例肺结节/肿块的患者,进行宝石能谱成像模式三期增强扫描,利用其后处理功能,分别测量动脉期(30 s)、静脉期(60 s)及延迟期(90 s)病灶的标准化碘浓度(NIC)、(40 keV)CT值以及能谱曲线斜率,比较各参数间的差异并进行统计学分析.结果 125例患者经手术或纤维支气管镜病理证实,4例炎性病变患者由随访证实;共分为3组,肺癌99例(肺癌组),炎性病变19例(炎性组),肺结核11例(结核组).动脉期、 静脉期及延迟期3组病变NIC值、(40 keV)CT值以及能谱曲线斜率(40~80 keV)基本为炎性组最高,均为结核组最低.结核组与其他两组比较,病灶在三期扫描中NIC值、(40 keV)CT值及能谱曲线斜率差异均有统计学意义(P<0.05);炎性组与肺癌组比较,仅在延迟期NIC值及(40 keV)CT值差异有统计学意义(P<0.05).结论 能谱CT成像定量分析对肺结节、肿块的鉴别诊断有较大应用价值.

关 键 词:肺结节  体层摄影术  X线计算机  诊断  鉴别

Preliminary study of spectral CT imaging in the differential diagnosis of solitary pulmonary nodules and masses
Abstract:Objective To investigate the diagnostic value of spectral CT imaging in differentiating of pulmonary nodules and masses.Methods 129 patients with pulmonary nodules or mass received triphasic pulmonary enhanced CT scan in GSI mode on Discovery CT750 HD.All raw data was sent to AW4.6 workstation and processed by the software of GSI work station.Normalized iodine concentration (NIC), CT value at 40 keV and slope rate of spectral curve were measured and compared.All the parameters were analyzed among three phases.Results 125 cases were proved by pathology through surgery or bronchoscopy, 4 cases were proved by follow-up (pneumonia 19, lung cancer 99 and tuberculosis 11).NIC, CT value at 40 keV and slope rate of spectral curve were found the highest in pneumonia, and lowest in tuberculosis.The above mentioned parameters were found significant difference in the three parameters either between tuberculosis and pneumonia or between tuberculosis and lung cancer in three phases.There was significant difference in NIC and CT value at 40 keV between pneumonia and lung cancer only in delayed phase.Conclusion Spectral CT imaging demonstrated the potential in diagnosing of pulmonary nodules and masses.
Keywords:pulmonary nodule  tomography  X-ray computed  diagnosis  identification
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