Inter- and intra-scan variability for lung imaging quantifications via CT.

Inter- and intra-scan variability for lung imaging quantifications via CT.
复制标题

通过 CT 进行肺部成像量化的扫描间和扫描内变异性。

DOI:
10.1117/12.2613191
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发表时间:
2022
期刊:
Proceedings of SPIE--the International Society for Optical Engineering
影响因子:
--
通讯作者:
Abadi,Ehsan
Abadi,Ehsan
中科院分区:
--
文献类型:
--
作者:
Shankar,SachinS;Hoffman,EricA;Atha,Jarron;Sieren,JessicaC;Samei,Ehsan;Abadi,Ehsan

文献摘要

相似文献

在临床诊断疾病时,CT成像为医生提供了有价值的见解。为了提供准确的诊断,在不同扫描仪和成像参数的CT扫描中具有高准确性和受控的可变性是很重要的。这项研究的目的是分析肺成像生物标志物在不同扫描仪和参数之间的变异性,使用带有几个实验样本插入的商业可买到的拟人化胸部幻影(京都Kagaku)的定制版本。这个模型覆盖了10台不同的CT扫描仪,总共有209种成像条件。开发了一种算法来计算不同的成像生物标志物。通过计算HU值的变异系数(CV)和标准差来分析来自同一扫描仪和来自不同扫描仪的图像的可变性。LAA-950和LAA-856生物标记物的变异性最高,而大多数其他生物标记物的变异性在扫描间和扫描内测量中都小于10HU或10%。在生物标志物测量和CTDIvol.之间没有明显的趋势。这项研究的结果证明了肺部成像CT量化的现有变异性,这促使进一步研究如何减少这种变异性。
CT imaging provides physicians valuable insights when diagnosing disease in a clinical setting. In order to provide an accurate diagnosis, is it important to have a high accuracy with controlled variability across CT scans from different scanners and imaging parameters. The purpose of this study was to analyze variability of lung imaging biomarkers across various scanners and parameters using a customized version of a commercially available anthropomorphic chest Phantom (Kyoto Kagaku) with several experimental sample inserts. The phantom was across 10 different CT scanners with a total of 209 imaging conditions. An algorithm was developed to compute different imaging biomarkers. Variability across images from the same scanner and from different scanners was analyzed by computing coefficients of variation (CV) and standard deviations of HU values. LAA -950 and LAA -856 biomarkers had the highest levels of variability, while the majority of other biomarkers had variability less than 10 HU or 10% CV in both inter and intrascan measurements. There was no clear trend present between the biomarker measurements and CTDIvol. The results of this study demonstrates the existing variability in CT quantifications for lung imaging, which prompt further studies on how to reduce such variation.