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双源CT能谱成像在胰腺癌诊断中的应用价值 被引量:11

The application value of spectral imaging in diagnosis of pancreatic adenocarcinoma by dual source CT
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摘要 目的 探讨CT能谱成像在胰腺癌诊断中的应用价值。方法 收集经手术病理证实的33例胰腺腺癌患者的病例资料。所有患者均行双能量CT双期增强扫描,经双能软件处理得到胰腺癌能谱曲线图,并计算出曲线斜率。根据能谱曲线获得最高对比噪声比(CNR)值并与70Ke V CNR值比较。结果 本组胰腺癌动脉期和实质期胰腺癌能谱曲线斜率分别为0.769、1.076,两者差异有统计学意义(P〈0.05)。动脉期、实质期最高CNR值(73-74ke V单能量图像)分别为(3.0±1.4)、(2.18±1.1),差异有统计学意义(P〈0.05)。最佳CNR值与70Ke V CNR值差异无统计学意义(P〉0.05)。结论 CT能谱成像所得能谱曲线斜率可以半定量分析胰腺癌组织衰减特征,动脉期可以获得胰腺癌高CNR值的单能量图像,能谱成像在胰腺癌的诊断中有潜在的辅助价值。 Objective To explore the diagnostic value of spectral CT imaging in detecting pancreatic ad Methods Materials of 33 patients with pathologically proved pancreatic adenocarcinoma were analyzed. All patients underwent dualphase scan by dual-source CT. All the data were analyzed with dual energy software software to get the spectral curves and calculating the curve slope of pancreatic adenocarcinoma. The highest CNR value was obtained on the basis of the spectral curve and compared with the CNR value of 70 KeV. Results In this group, the curve slope of pancreatic adenocarcinoma was 0. 769 and 1. 076 inarterial phase and parenchymal phase, respectively. There was statistically significant difference between the two groups ( P 〈0.05). The highest CNR valueinarterial phase and parenchymal phase (73 -74 keV single energy image) were (3.0 ± 1.4) and (2.18 ± 1.1 ) respectively, the difference was significant ( P 〈 0.05 ). There was no significant difference in highest CNR value group and 70 Ke VCNR value group ( P 〉 0.05). Conclusion The spectrum curve of spectral CT can be used to the semiquantitatively analysis of the attenuation characteristic of pancreatic carcinoma. Single energy image of high CNR value of pancreatic carcinoma could be obtained in arterial phase. Spectral CT imaging may have potential auxiliary value for the diagnosis of pancreatic adenocarcinoma.
出处 《医学影像学杂志》 2016年第7期1243-1246,共4页 Journal of Medical Imaging
基金 浙江省医药卫生科技计划项目资助(2012KYB047)
关键词 胰腺癌 体层摄影术 X线计算机 能谱成像 Pancreatic adenocarcinoma Tomography, X-ray computed Spectral imaging
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