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活体 micro-CT 重复性肺部测量中常规质量控制的重要性。

The importance of routine quality control for reproducible pulmonary measurements by in vivo micro-CT.

机构信息

Department of Veterinary Science, University of Parma, Parma, Italy.

Department of Medicine and Surgery, University of Parma, Parma, Italy.

出版信息

Sci Rep. 2022 Jun 11;12(1):9695. doi: 10.1038/s41598-022-13477-7.

Abstract

Micro-computed tomography (CT) imaging provides densitometric and functional assessment of lung diseases in animal models, playing a key role either in understanding disease progression or in drug discovery studies. The generation of reliable and reproducible experimental data is strictly dependent on a system's stability. Quality controls (QC) are essential to monitor micro-CT performance but, although QC procedures are standardized and routinely employed in clinical practice, detailed guidelines for preclinical imaging are lacking. In this work, we propose a routine QC protocol for in vivo micro-CT, based on three commercial phantoms. To investigate the impact of a detected scanner drift on image post-processing, a retrospective analysis using twenty-two healthy mice was performed and lung density histograms used to compare the area under curve (AUC), the skewness and the kurtosis before and after the drift. As expected, statistically significant differences were found for all the selected parameters [AUC 532 ± 31 vs. 420 ± 38 (p < 0.001); skewness 2.3 ± 0.1 vs. 2.5 ± 0.1 (p < 0.001) and kurtosis 4.2 ± 0.3 vs. 5.1 ± 0.5 (p < 0.001)], confirming the importance of the designed QC procedure to obtain a reliable longitudinal quantification of disease progression and drug efficacy evaluation.

摘要

微计算机断层扫描(CT)成像为动物模型中的肺部疾病提供了密度和功能评估,在理解疾病进展或药物发现研究中起着关键作用。可靠和可重复的实验数据的生成严格依赖于系统的稳定性。质量控制(QC)对于监测微 CT 性能至关重要,但尽管 QC 程序在临床实践中已经标准化和常规使用,但缺乏针对临床前成像的详细指南。在这项工作中,我们基于三个商业体模,提出了一种用于体内微 CT 的常规 QC 方案。为了研究检测到的扫描仪漂移对图像后处理的影响,对 22 只健康小鼠进行了回顾性分析,并使用肺密度直方图比较漂移前后曲线下面积(AUC)、偏度和峰度。正如预期的那样,所有选定的参数都存在统计学上的显著差异 [AUC:532 ± 31 对 420 ± 38(p < 0.001);偏度:2.3 ± 0.1 对 2.5 ± 0.1(p < 0.001)和峰度:4.2 ± 0.3 对 5.1 ± 0.5(p < 0.001)],证实了设计的 QC 程序对于获得可靠的疾病进展和药物疗效评估的纵向定量的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ac7/9188608/79b1512b74bf/41598_2022_13477_Fig1_HTML.jpg

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