能谱CT成像区别不同溶液的可行性研究  

Feasibility study of discriminating different solutions using spectral CT imaging

作　　者：张迎[1] 邢立红 武莹莹[1] 秦文[1] 李锋坦[1] 张敬[1] 

机构地区：[1]天津医科大学总医院放射科,天津300052

出　　处：《实用放射学杂志》2014年第5期838-840,847,共4页Journal of Practical Radiology

摘　　要：目的：探讨宝石能谱 CT 成像（gemstone spectral imaging,GSI）技术区分不同成分和浓度溶液的可行性。方法配置5%、10%、15%、20% g/mL 的葡萄糖溶液（glucose solution,GS）,对上述溶液和0.9%生理盐水（normal saline,NS）同时进行 GSI模式扫描。使用能谱分析软件获得各溶液的单能下（40－140 keV）CT 值的能谱曲线。3 d 后重复扫描和测量。采用可靠性分析（reliability analysis）中的组内相关系数（intra-class correlation coefficient,ICC）评价2次扫描结果的一致性。非线性回归分析获得各溶液能谱曲线的回归方程。单因素方差分析比较各溶液能谱曲线的斜率、渐近值、截距,确定曲线形态与成分和浓度的关系。结果各溶液2次扫描所得能谱曲线一致性均好（ICC〉0.9）。各溶液回归方程为：f（keV-40）=α-（α-β）×e[-（keV-40）×ρ],f（keV-40）为各 keV 下的 CT 值,α、β及ρ分别代表能谱曲线渐近值、截距及斜率。NS 曲线的斜率与各浓度 GS 曲线斜率均有显著性差异（P 〈0.05）,各浓度 GS 曲线斜率无显著性差异（P 〉0.05）,认为不同成分溶液能谱曲线形态不同。不同浓度 GS 曲线的渐近值及截距均有显著性差异（P 〈0.05）,曲线位置随浓度增加而增高。结论 GSI 能谱曲线技术可区分 NS 和 GS,以及不同浓度的 GS,在在体体液分析方面有较好的应用前景。Objective To investigate the feasibility of discriminating different solutions and solutions with different concentrations using gemstone spectral imaging （GSI）.Methods Glucose solutions （GSs）with different concentrations （5%,10%,15%,20% g/mL）and 0.9% normal saline（NS）were scanned at a CT scanner with GSI model.Spectral analysis software was used to generate spectral curves of different solutions,representing as CT values on monochromatic images（40-140keV）.The same procedure was repeated 3 days later.Reliability analysis with intra-class correlation coefficient （ICC）was used to evaluate the agreement between the twice CT scans.Nonlinear regression analysis was used to generate the regression equation of spectral curves of each solution.One-way ANO-VA was performed to compare the slopes,asymptotes and intercepts of each solution.Results Reliability analysis showed excellent agreements between the twice CT scans for each solution （ICC〉0.9）.The regression equation was expressed as：f（keV-40）=α-（α-β）×e [-（keV-40）×ρ],where f（keV-40）represented CT values on each monochromatic images,αrepresented asymptotes,βrepre-sented intercepts,ρrepresented slopes of each solution.Statistical differences were found among the slopes of NS and those of GSs with different concentrations （P〈0.05）,while no statistical differences were found among the slopes of different GSs （P 〉0.05）. The result was highly suggestive that different ingredient solutions demonstrated different shapes of spectral curves.The asymptotes and intercepts of GSs with different concentrations were statistically different （P 〈0.05）.The heights of the spectral curves of GSs elevated with the increase of the concentration.Conclusion Spectral curve with GSI model can be used to discriminate between NS and GSs,or even GSs with different concentrations.It provided a promising potential for in vivo body fluid analyses.

关 键 词：能谱成像 葡萄糖浓度 溶液 计算机体层成像 

分 类 号：R814.42[医药卫生—影像医学与核医学] R814.49[医药卫生—放射医学]