头颅CT纹理特征评价心搏骤停后患者复苏后脑损伤研究

黄云苑; 叶浩翊; 刘志锋; 杨正飞; 张洁

doi:10.13201/j.issn.1009-5918.2022.11.001

头颅CT纹理特征评价心搏骤停后患者复苏后脑损伤研究

- 1.
  中山大学孙逸仙纪念医院急诊科(广州，510000)
- 2.
  广州医科大学附属第四医院影像科

详细信息

通讯作者: 张洁，E-mail：41115299@qq.com

中图分类号: R541.78

收稿日期: 2022-07-16

刊出日期: 2022-11-10

Texture features on brain computed tomography to evaluate the brain injury in post-cardiac arrest patients

- 1.
  Department of Emergency, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510000, China
- 2.
  Department of Radiology, the Fourth Affiliated Hospital of Guangzhou Medical University

More Information

Corresponding author: ZHANG Jie, E-mail: 41115299@qq.com

Received Date: 16 July 2022

Publish Date: 10 November 2022

摘要

摘要: 目的探讨基于头颅CT平扫图像的纹理特征对评估心搏骤停(CA)复苏成功患者脑损伤的可行性。方法回顾性分析2016年1月—2021年6月我院收治的13例心搏骤停复苏成功后缺血缺氧性脑病患者，将每例患者CA后早期(7 d内)头颅CT纳入心肺复苏组；对照组则选用同时期体检的同龄健康人的头颅CT，两两配对分析头颅CT图像纹理特征。利用Omni-Kinetics软件提取两组研究者头颅CT图像的区域纹理特征进行比较，取小脑最大层面及海马最大层面纹理特征并测量提值，对比两组纹理特征结果的差异。运用ROC曲线评价有差异的纹理特征在CA后脑损伤中的诊断效能。结果两组间的纹理特征[体积数(VolumeCount)、体素值(VoxelValueSum)、频度(FrequencySize)]之间比较，差异有统计学意义(P < 0.05)，且心肺复苏组3个参数值均低于对照组(P < 0.05)。其ROC曲线下面积为0.787。结论头颅CT纹理特征参数可反映CA后患者的脑损伤。
- 头颅 CT /
- 纹理特征 /
- 心搏骤停
Abstract: ObjectiveTo explore the feasibility of evaluating brain injury in cardiac arrest(CA) survivors based on texture features of brain CT images.MethodsA total of 13 CA patients who were diagnosed as hypoxic-ischemic encephalopathy in our hospital between January 2016 and June 2021 were included in this retrospective study. The patients who had brain CT scans within 7 days of resuscitation were included in the cardiopulmonary resuscitation group, while the healthy people of the same age who underwent physical examination at the same time were selected in the control group, and the texture features of head CT images were analyzed in pairs. The Omni-Kinetics software was used to extract the regional texture features of the head CT images of the two groups of patients for comparison. The texture features of the largest layer of cerebellum and hippocampus were taken and measured, and the difference of the texture feature results between the two groups were compared. ROC curve was used to evaluate the diagnostic efficacy of brain injury after CA in different texture features.ResultsThe differences of texture features VolumeCount, VoxelValueSum and FrequencySize between the two groups were statistically significant(P < 0.05), and the three parameter values of cardiopulmonary resuscitation group were lower than those of the control group(P < 0.05). The area under the ROC curve is 0.787.ConclusionCT texture feature parameters can evaluate brain injury in patients after CA.
- brain CT /
- texture features /
- cardiac arrest

HTML全文

图 1 纹理分析过程图

下载: 全尺寸图片幻灯片

图 2 小脑勾画ROI示意图

下载: 全尺寸图片幻灯片

图 3 心肺复苏组和对照组头颅 CT 纹理特征 VoxelValueSum、VolumeCount、FrequencySize 结果对比

下载: 全尺寸图片幻灯片

图 4 VolumeCount、VoxelValueSum、FrequencySize 的 ROC 曲线图

下载: 全尺寸图片幻灯片

表 1 采用Pearson进行参数间相关性检验

检验指标	r	P
VolumeCount与VoxelValueSum	0.962	< 0.001
FrequencySize与VoxelValueSum	0.962	< 0.001
FrequencySize与VolumeCount	1	< 0.001

下载: 导出CSV

参考文献(25)

[1]	Callaway CW, Donnino MW, Fink EL, et al. Part 8: Post-Cardiac Arrest Care: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care[J]. Circulation, 2015, 132(18 Suppl 2): S465-482.
[2]	胡鑫, 唐曦. 医学影像纹理分析在软组织肿瘤中的研究进展[J]. 医学影像学杂志, 2022, 32(1): 167-169. https://www.cnki.com.cn/Article/CJFDTOTAL-XYXZ202201043.htm
[3]	岑永义, 鲍保成, 梁克, 等. CT或MRI纹理分析在肝局灶性病变中的研究进展[J]. 影像研究与医学应用, 2021, 5(13): 3-5. doi: 10.3969/j.issn.2096-3807.2021.13.002
[4]	Perkins GD, Callaway CW, Haywood K, et al. Brain injury after cardiac arrest[J]. Lancet(London, England), 2021, 398(10307): 1269-1278.
[5]	心肺复苏后昏迷患者早期神经功能预后评估专家共识组. 心肺复苏后昏迷患者早期神经功能预后评估专家共识[J]. 中华急诊医学杂志, 2019, 28(2): 156-162.
[6]	Sandroni C, Cronberg T, Sekhon M. Brain injury after cardiac arrest: pathophysiology, treatment, and prognosis[J]. Int Care Med, 2021, 47(12): 1393-1414. doi: 10.1007/s00134-021-06548-2
[7]	王淦楠, 张劲松. 头颅CT对心肺复苏后昏迷患者神经功能预后的判断价值研究进展[J]. 中华急诊医学杂志, 2022, 31(1): 124-128. doi: 10.3760/cma.j.issn.1671-0282.2022.01.027
[8]	Fusco R, Granata V, Grazzini G, et al. Radiomics in medical imaging: pitfalls and challenges in clinical management[J]. Japan J Radiol, 2022, 40(9): 919-929. doi: 10.1007/s11604-022-01271-4
[9]	An H, Wang Y, Wong EMF, et al. 卵巢上皮癌组织学分型的CT纹理分析[J]. 国际医学放射学杂志, 2021, 44(5) : 610. https://www.cnki.com.cn/Article/CJFDTOTAL-GWLC202105067.htm
[10]	马永青, 王志璐, 王帝, 等. CT纹理分析对结直肠癌与炎症性结直肠壁增厚的鉴别诊断价值[J]. 中国医学影像学杂志, 2021, 29(12) : 1222-1226. doi: 10.3969/j.issn.1005-5185.2021.12.011
[11]	Zhang YM, Gong GZ, Qiu QT, et al. Radiomics for Diagnosis and Radiotherapy of Nasopharyngeal Carcinoma[J]. Front Oncol, 2022, 11: 767134. doi: 10.3389/fonc.2021.767134
[12]	刘欣, 郑伊能, 钟毅, 等. CT纹理分析对醛固酮腺瘤与皮质醇腺瘤的鉴别诊断价值[J]. 中国中西医结合影像学杂志, 2021, 19(1): 60-64. https://www.cnki.com.cn/Article/CJFDTOTAL-JHYX202101017.htm
[13]	董婷宇, 汤林梦, 杨飞, 等. CT影像纹理分析在胃肠道间质瘤中的研究进展[J]. 国际医学放射学杂志, 2022, 45(1): 84-88. https://www.cnki.com.cn/Article/CJFDTOTAL-GWLC202201017.htm
[14]	Wei W, Hu XW, Cheng Q, et al. Identification of common and severe COVID-19: the value of CT texture analysis and correlation with clinical characteristics[J]. Euro Radiol, 2020, 30(12): 6788-6796.
[15]	包婉秋, 彭霞, 向橙, 等. 影像组学在神经系统非肿瘤性疾病中的应用及研究进展[J]. 中国中西医结合影像学杂志, 2021, 19(4): 395-397. https://www.cnki.com.cn/Article/CJFDTOTAL-JHYX202104023.htm
[16]	江瑞信, 叶浩翊, 刘志锋, 等. 基于CT平扫图像纹理分析预测高血压脑出血早期血肿扩大的可行性研究[J]. 岭南现代临床外科, 2021, 21(3): 337-340. https://www.cnki.com.cn/Article/CJFDTOTAL-LNWK202103018.htm
[17]	Sarioglu O, Sarioglu FC, Capar AE, et al. The role of CT texture analysis in predicting the clinical outcomes of acute ischemic stroke patients undergoing mechanical thrombectomy[J]. Eur Radiol, 2021, 31(8): 6105-6115.
[18]	Colombi D, Bodini FC, Rossi B, et al. Computed Tomography Texture Analysis of Carotid Plaque as Predictor of Unfavorable Outcome after Carotid Artery Stenting: A Preliminary Study[J]. Diagnostics, 2021, 11(12): 2214.
[19]	Shan Y, Li Y, Wu X, et al. Evaluation of Intracranial Hypertension in Patients With Hypertensive Intracerebral Hemorrhage Using Texture Analysis[J]. Front Neurol, 2022, 13: 832234.
[20]	包婉秋, 彭霞, 张春霞, 等. 非增强CT纹理特征对超急性期脑梗死溶栓后出血转化的预测价值[J]. 中国中西医结合影像学杂志, 2022, 20(2): 122-127. https://www.cnki.com.cn/Article/CJFDTOTAL-JHYX202202005.htm
[21]	许倩. 基于磁共振的多模态成像技术鉴别脑胶质瘤复发与治疗后反应[D]. 南京医科大学, 2018.
[22]	唐庆昆, 朱建国, 李海歌, 等. 甲状腺乳头状癌的术前诊断和预测分期: 基于CT直方图分析的研究[J]. 临床放射学杂志, 2020, 39(12): 2388-2393. https://www.cnki.com.cn/Article/CJFDTOTAL-LCFS202012009.htm
[23]	张懿, 丁建平. CT纹理分析对卵巢上皮肿瘤的鉴别诊断[J]. 医学影像学杂志, 2021, 31(2): 293-296, 301. https://www.cnki.com.cn/Article/CJFDTOTAL-XYXZ202102033.htm
[24]	苏晟, 朱建国, 曹波, 等. 透明细胞肾癌的诊断和病理相关分析: 一项基于CT直方图的初步研究[J]. 临床放射学杂志, 2021, 40(3): 541-546. https://www.cnki.com.cn/Article/CJFDTOTAL-LCFS202103028.htm
[25]	陈东, 史彬, 郑明雪, 等. ADC值联合基于T_(2) WI脂肪抑制图像的纹理特征预测软组织良恶性肿瘤的价值[J]. 中华放射学杂志, 2021, 55(3): 282-287. https://www.cnki.com.cn/Article/CJFDTOTAL-GWLC202205003.htm