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首页> 外文期刊>Investigative radiology >Computed Tomography Perfusion Using First Pass Methods for Lung Nodule Characterization.
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Computed Tomography Perfusion Using First Pass Methods for Lung Nodule Characterization.

机译:使用首过方法进行肺部结核表征的计算机断层扫描灌注。

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OBJECTIVE:: To evaluate computed tomography (CT) perfusion using first pass methods for lung nodule characterization. METHODS:: Fifty-seven patients with 51 malignant and 6 benign nodules underwent first-pass, dynamic contrast-enhanced-CT (50 mL, 3-5 mL/s.). Kinetic analysis tools were CT Perfusion 3 (GEMS, Milwaukee, WI), a distributed parameter model approach, yielding blood volume (BV; mL/100 g), blood flow (BF; mL/min/100 g), mean transit time (1/s), and permeability surface area (mL/min/100 g), and an in-house Patlak-style analysis yielding fractional BV (mL/100 g) and an estimate of extraction (Kps, mL/100 g/min). RESULTS:: CT Perfusion 3 parameters in malignant and benign nodules were: mean transit time 10.1 +/- 0.9 1/s versus 11.1 +/- 3.1 1/s (ns), permeability surface 23.3 +/- 9.1 mL/min/100 g versus 19.6 +/- 10.3 mL/min/100 g (ns), BF 111.3 +/- 8.7 mL/min/100 g versus 39.1+/- 5.7 mL/min/100 g (P < 0.001), BV 9.3+/- 0.7 mL/100 g versus 4.1 +/- 1.1 mL/100 g (P < 0.002); Patlak parameters were: Kps 13.3 +/- 1.2 mL/100 g/min versus 3.9 +/- 0.8 mL/100 g/min (P < 0.001), BV 8.4 +/- 0.8 mL/100 g versus 3.6 +/- 1.3 mL/100 g (P < 0.01). The two kinetic methods show good agreement for BV estimation (Bland-Altman plot). The limits of agreement (bias +/-2 standard deviation of bias) were 1.2 +/- 5.3 mL/100 g. CONCLUSION:: CT Perfusion using first pass modeling appears feasible for lung nodule characterization. Given the short acquisition duration used, weaknesses of the modeling methods are exposed. Nonetheless, microvascular characterization in terms of BF, BV, or Kps appears useful in distinguishing malignant from benign nodules.
机译:目的:使用肺过结节特征的首过方法评估计算机断层扫描(CT)灌注。方法:57例51例恶性和6例良性结节患者接受了动态,动态增强CT(50 mL,3-5 mL / s)的首过检查。动力学分析工具为CT灌注3(GEMS,Milwaukee,WI),一种分布式参数模型方法,产生血量(BV; mL / 100 g),血流(BF; mL / min / 100 g),平均通过时间( 1 / s),渗透率表面积(mL / min / 100 g)和内部Patlak式分析,得出分数BV(mL / 100 g)和提取率估算值(Kps,mL / 100 g / min) )。结果::恶性和良性结节的CT灌注3参数为:平均通过时间10.1 +/- 0.9 1 / s与11.1 +/- 3.1 1 / s(ns),通透性表面23.3 +/- 9.1 mL / min / 100 g对19.6 +/- 10.3 mL / min / 100 g(ns),BF 111.3 +/- 8.7 mL / min / 100 g与39.1 +/- 5.7 mL / min / 100 g(P <0.001),BV 9.3+ /-0.7 mL / 100 g对比4.1 +/- 1.1 mL / 100 g(P <0.002); Patlak参数为:Kps 13.3 +/- 1.2 mL / 100 g / min与3.9 +/- 0.8 mL / 100 g / min(P <0.001),BV 8.4 +/- 0.8 mL / 100 g与3.6 +/- 1.3毫升/ 100克(P <0.01)。两种动力学方法显示出BV估计的良好一致性(Bland-Altman图)。一致性极限(偏差的偏差+/- 2标准偏差)为1.2 +/- 5.3 mL / 100 g。结论:CT灌注使用首过建模似乎可行肺结节表征。考虑到使用的采集时间短,暴露出建模方法的弱点。尽管如此,以BF,BV或Kps表示的微血管表征似乎对区分恶性结节和良性结节很有用。

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