Review of CT sign combination and texture analysis in predicting hematoma enlargement of spontaneous intracerebral hemorrhage

doi:10.3877/cma.j.issn.2095-9141.2022.04.009

Abstract

Abstract:

Hematoma enlargement (HE) is an independent risk factor for deterioration and poor prognosis in patients with spontaneous intracerebral hemorrhage (SICH), so it is of great clinical significance to predict the occurrence of HE in early stage. CT as the first choice of auxiliary examination for patients with SICH, its characteristic images have been widely used to predict the occurrence of HE, but its predictive efficiency is reduced due to single signs and personal subjective judgment and other factors. In order to improve the prediction ability of CT signs to HE, the combination of multi-features and texture analysis based on CT images have become a new focus of the current research. This article reviews the research progress of CT combined signs and texture analysis in predicting early HE in patients with SICH in recent years.

Key words: CT sign combination, Texture analysis, Spontaneous intracerebral hemorrhage, Hematoma enlargement, Predict

Han Zhang, Lianshu Ding. Review of CT sign combination and texture analysis in predicting hematoma enlargement of spontaneous intracerebral hemorrhage[J]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2022, 08(04): 242-246.

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References 45

[1]	Macdonald RL. Management of intracranial hemorrhage in the anticoagulated patient[J]. Neurosurg Clin N Am, 2018, 29(4): 605-613.
[2]	Marcolini E, Stretz C, DeWitt KM. Intracranial hemorrhage and intracranial hypertension[J]. Emerg Med Clin North Am, 2019, 37(3): 529-544.
[3]	Delcourt C, Huang Y, Arima H, et al. Hematoma growth and outcomes in intracerebral hemorrhage: the INTERACT1 study[J]. Neurology, 2012, 79(4): 314-319.
[4]	Serrano E, López-Rueda A, Moreno J, et al. The new hematoma maturity score is highly associated with poor clinical outcome in spontaneous intracerebral hemorrhage[J]. Eur Radiol, 2022, 32(1): 290-299.
[5]	中华医学会神经病学分会,中华医学会神经病学分会脑血管病学组.中国脑出血诊治指南(2019)[J].中华神经科杂志, 2019, 52(12): 994-1005.
[6]	Nawabi J, Elsayed S, Kniep H, et al. Inter- and intrarater agreement of spot sign and noncontrast CT markers for early intracerebral hemorrhage expansion[J]. J Clin Med, 2020, 9(4): 1020.
[7]	Dowlatshahi D, Morotti A, Al-Ajlan FS, et al. Interrater and intrarater measurement reliability of noncontrast computed tomography predictors of intracerebral hemorrhage expansion[J]. Stroke, 2019, 50(5): 1260-1262.
[8]	Cai J, Zhu H, Yang D, et al. Accuracy of imaging markers on noncontrast computed tomography in predicting intracerebral hemorrhage expansion[J]. Neurol Res, 2020, 42(11): 973-979.
[9]	Shakya MR, Fu F, Zhang M, et al. Comparison of black hole sign, satellite sign, and iodine sign to predict hematoma expansion in patients with spontaneous intracerebral hemorrhage[J]. Biomed Res Int, 2021, 2021: 3919710.
[10]	Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis[J]. Eur J Cancer, 2012, 48(4): 441-446.
[11]	Ranjbar S, Ross Mitchell J. Chapter 8-an introduction to radiomics: an evolving cornerstone of precision medicine. Biomedical texture analysis[M]. Pittsburgh: Academic Press, 2017: 223-245.
[12]	王策,钱增辉,蔡泽豪,等.机器学习结合影像组学特征鉴别间变性胶质细胞瘤和胶质母细胞瘤[J].中华神经医学杂志, 2020, 19(3): 224-228.
[13]	Li Q, Liu QJ, Yang WS, et al. Island sign: an imaging predictor for early hematoma expansion and poor outcome in patients with intracerebral hemorrhage[J]. Stroke, 2017, 48(11): 3019-3025.
[14]	Li Q, Zhang G, Xiong X, et al. Black hole sign: novel imaging marker that predicts hematoma growth in patients with intracerebral hemorrhage[J]. Stroke, 2016, 47(7): 1777-1781.
[15]	王丹丹,王学建,潘南南. CT岛征和黑洞征及其联合征象对原发性脑出血早期血肿扩大的预测价值[J].天津医药, 2021, 49(2): 199-202.
[16]	王希,仲艳,颜伟,等. CT平扫岛征和黑洞征对原发性脑出血早期血肿扩大的预测价值[J].中华神经外科杂志, 2021, 37(6): 557-561.
[17]	Li Q, Zhang G, Huang YJ, et al. Blend sign on computed tomography: novel and reliable predictor for early hematoma growth in patients with intracerebral hemorrhage[J]. Stroke, 2015, 46(8): 2119-2123.
[18]	Huang YW, Yang MF. Combining investigation of imaging markers (island sign and blend sign) and clinical factors in predicting hematoma expansion of intracerebral hemorrhage in the basal ganglia[J]. World Neurosurg, 2018, 120: e1000-e1010.
[19]	贾维,石长青,刘亚龙,等. CT平扫岛征和混合征对自发性脑出血患者早期血肿扩大的预测作用[J].中华神经外科杂志, 2019, 35(10): 1036-1040.
[20]	Ng D, Churilov L, Mitchell P, et al. The CT swirl sign is associated with hematoma expansion in intracerebral hemorrhage[J]. AJNR Am J Neuroradiol, 2018, 39(2): 232-237.
[21]	Xiong X, Li Q, Yang WS, et al. Comparison of swirl sign and black hole sign in predicting early hematoma growth in patients with spontaneous intracerebral hemorrhage[J]. Med Sci Monit, 2018, 24: 567-573.
[22]	孙羽,郝妮娜,付乐君,等.基于倾向性评分评价漩涡征预测自发性脑出血血肿扩大的价值[J].国际医学放射学杂志, 2021, 44(4): 415-419.
[23]	周志敏,周逸飞,徐亮.岛征和漩涡征预测脑出血早期血肿扩大价值[J].中国CT和MRI杂志, 2021, 19(8): 1-4.
[24]	Barras CD, Tress BM, Christensen S, et al. Density and shape as CT predictors of intracerebral hemorrhage growth[J]. Stroke, 2009, 40(4): 1325-1331.
[25]	杨文松,李琦,王星辰,等. CT平扫混合征和黑洞征及其联合征象对脑出血患者早期血肿扩大的预测价值[J].中国脑血管病杂志, 2017, 14(11): 561-565, 579.
[26]	裴潘,郝伟伟,张敏,等.脑出血血肿扩大的危险因素及CT平扫预测血肿扩大的价值分析[J].中国临床保健杂志, 2020, 23(3): 415-418.
[27]	Shimoda Y, Ohtomo S, Arai H, et al. Satellite sign: a poor outcome predictor in intracerebral hemorrhage[J]. Cerebrovasc Dis, 2017, 44(3-4): 105-112.
[28]	王治斌.血肿周围水肿等常见CT征象对自发性脑出血早期血肿扩大的预测[D].北京:中国医学科学院北京协和医学院, 2019.
[29]	Yang H, Luo Y, Chen S, et al. The predictive accuracy of satellite sign for hematoma expansion in intracerebral hemorrhage: a meta-analysis[J]. Clin Neurol Neurosurg, 2020, 197: 106139.
[30]	宋祖华,周治明,郭大静,等.基于平扫CT的Logistic回归模型和朴素贝叶斯模型预测血肿扩大[J].中国医学影像技术, 2021, 37(1): 30-34.
[31]	傅璠, Ratna Shakya Milind,於帆,等. CT平扫预测高血压脑出血早期血肿扩大的价值[J].医学影像学杂志, 2020, 30(11): 1961-1964.
[32]	Boulouis G, Morotti A, Brouwers HB, et al. Association between hypodensities detected by computed tomography and hematoma expansion in patients with intracerebral hemorrhage[J]. JAMA Neurol, 2016, 73(8): 961-968.
[33]	Morotti A, Boulouis G, Romero JM, et al. Blood pressure reduction and noncontrast CT markers of intracerebral hemorrhage expansion[J]. Neurology, 2017, 89(6): 548-554.
[34]	陈丽芳.非增强CT征象对脑出血患者早期血肿扩大预测价值比较研究[D].福州:福建医科大学, 2019.
[35]	宋杨君. CT平扫影像学征象预测自发性脑出血患者早期血肿扩张的临床价值分析[J].中国CT和MRI杂志, 2021, 19(11): 20-22.
[36]	王少华.高血压性脑出血血肿早期增大与平扫CT征象的相关性分析[D].北京:中国医学科学院北京协和医学院, 2019.
[37]	王娟,郭龙军,李昌,等.基于CT评估脑出血征象和血肿体积、高低密度差预测血肿增大及软化灶的价值研究[J].影像科学与光化学, 2021, 39(2): 298-304.
[38]	Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine[J]. Nat Rev Clin Oncol, 2017, 14(12): 749-762.
[39]	Lubner MG, Smith AD, Sandrasegaran K, et al. CT texture analysis: definitions, applications, biologic correlates, and challenges[J]. Radiographics, 2017, 37(5): 1483-1503.
[40]	Barras CD, Tress BM, Christensen S, et al. Quantitative CT densitometry for predicting intracerebral hemorrhage growth[J]. AJNR Am J Neuroradiol, 2013, 34(6): 1139-1144.
[41]	Shen Q, Shan Y, Hu Z, et al. Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement[J]. Eur Radiol, 2018, 28(10): 4389-4396.
[42]	丁川,李小虎,王俊,等.基于CT放射组学预测高血压性脑出血血肿扩大的研究[J].安徽医科大学学报, 2022, 57(1): 161-164.
[43]	Liu Y, Fang Q, Jiang A, et al. Texture analysis based on U-Net neural network for intracranial hemorrhage identification predicts early enlargement[J]. Comput Methods Programs Biomed, 2021, 206: 106140.
[44]	彭霞,包婉秋,王磊,等. CT纹理特征在早期自发性脑出血血肿扩大的预测应用研究[J].临床放射学杂志, 2022, 41(2): 236-240.
[45]	Rodriguez-Luna D, Coscojuela P, Rodriguez-Villatoro N, et al. Multiphase CT angiography improves prediction of intracerebral hemorrhage expansion[J]. Radiology, 2017, 285(3): 932-940.

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