| 苏铭,尹勇,韩柱君,等.左心室肌CT影像组学特征在心跳周期中动态变化的量化分析[J].中华放射医学与防护杂志,2020,40(8):636-641.Su Ming,Yin Yong,Han Zhujun,et al.Quantitative analysis on the dynamic changes in heart beat cycle of radiomics characteristics in left ventricular myocardial CT[J].Chin J Radiol Med Prot,2020,40(8):636-641 |
| 左心室肌CT影像组学特征在心跳周期中动态变化的量化分析 |
| Quantitative analysis on the dynamic changes in heart beat cycle of radiomics characteristics in left ventricular myocardial CT |
| 投稿时间：2019-11-13 |
| DOI：10.3760/cma.j.issn.0254-5098.2020.08.011 |
| 中文关键词: 心动周期 心肌功能 评估 影像组学 |
| 英文关键词:Cardiac Cycle Myocardial function Assessment Radiomics |
| 基金项目:山东省重点研发计划（2018GSF118048，2018GSF118006） |
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| 中文摘要: |
| 目的 应用影像组学技术结合心电门控4DCT强化扫描图像，量化分析左心室肌CT影像组学特征在心动周期中的变化情况，为基于心电门控4DCT进行心脏功能动态评估提供可行方法。方法 将14例患者的4DCT强化扫描图像以心动周期5%为间隔，重建0%~95% 20个时相的图像。分别在单个时相勾画左心室肌（LVM），并在左心室心腔造影剂充盈完好区域勾画直径为13 mm的球体[心腔感兴趣区（ROI）]。利用3DSlicer软件对所有勾画的92个特征进行提取，分析CT值在心腔ROI和LVM上的分布情况，基于心腔ROI进行初步筛选（单因素方差分析）得到稳定特征，再利用稳定特征对LVM进一步筛选（单因素方差分析）得到有差异特征，然后采用Wilcoxon秩和检验量化分析特征在心跳周期中随心跳的变化情况。结果 心跳周期中心腔ROI的平均CT值变化率小于LVM，变化率分别为9.23%、17.88%。有36个稳定特征在心腔ROI上差异均无统计学意义（P>0.05）；在36个稳定特征中，对LVM分析得到20个差异有统计学意义的特征（F=1.641~6.206，P<0.05），且平均变化率达到98.63%，其中Firstorder矩阵：中值（-103.96%）、均值（123.67%）；GLDM矩阵：灰度非均匀性（99.81%）等变化率达到了99%以上，且不同心动周期中的最大值、最小值之间的差异均具有统计学意义（Z=-3.921~-3.173，P<0.05）。结论 通过结合影像组学技术和心电门控4DCT强化扫描图像可以放大心动周期中CT图像的微观变化，可为左心室肌功能的变化评估提供一个新方法，Firstorder矩阵的均值等特征更具应用潜力。 |
| 英文摘要: |
| Objective To provide a feasible method for the evaluation of cardiac function based on cardiac gated 4DCT, the radiomics technology combined with enhanced ECG gated 4DCT images were used to quantitatively analyze the changes of left ventricular CT radiomics characteristics in cardiac cycle. Methods The enhanced ECG 4DCT images of 14 patients were reconstructed at intervals of 5% of cardiac cycle. The left ventricular muscle (LVM) and the contrast agent well filled area of left ventricular were delineated with a 13 mm diameter sphere (Cardiac Region of Interest, cardiac ROI) in a single phase. 3Dslicer software was used to extract 92 features of all the sketches, analyze the distribution of CT values on the cardiac ROI and LVM, and preliminarily screen the stable features based on the cardiac ROI (one-way ANOVA).The stable features were used to further screen LVM (one-way ANOVA) to get the difference features. Wilcoxon rank sum test was used to analyze the change of characteristics with heartbeat in the heartbeat cycle. Results In the heartbeat cycle the mean CT values of cardiac cavity ROI in cardiac cavity changed less than that in LVM, with the change rates of 9.23% and 17.88%, respectively. There were 36 stable features with no significant difference in cardiac cavity ROI (P>0.05). 20 of them were statistically significant (F=1.641-6.206, P<0.05), and the average change rate was 98.63%, such as median (-103.96%) and mean (123.67%) of the first order matrix, gray level non uniformity (99.81%) of GLDM matrix and other changes reached more than 99%. The differences between the maximum and minimum values in different cardiac cycles were statistically significant (Z=-3.921--3.173, P<0.05). Conclusions With the combination of radiomics and enhanced ECG 4DCT image, the microscopic changes of CT image features in the cardiac cycle can be amplifed. A new method for the assessment of left ventricular function changes was provided. The features such as median, mean may have more application potential. |
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