切换至 "中华医学电子期刊资源库"

中华脑血管病杂志(电子版) ›› 2024, Vol. 18 ›› Issue (03) : 197 -201. doi: 10.11817/j.issn.1673-9248.2024.03.001

述评

颅内动静脉畸形破裂出血预测中的若干问题
张绍森1, 王基源2, 张东1,()   
  1. 1. 100730 北京医院神经外科,国家老年医学中心,中国医学科学院老年医学研究院
    2. 100070 首都医科大学附属北京天坛医院神经外科
  • 收稿日期:2024-04-08 出版日期:2024-06-01
  • 通信作者: 张东
  • 基金资助:
    国家科技支撑计划(2021YFC2500502)

Several issues in predicting intracranial arteriovenous malformation rupture and hemorrhage

Shaosen Zhang1, Jiyuan Wang2, Dong Zhang1,()   

  1. 1. Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, P. R. China, Beijing 100730, China
    2. Department of Neurosurgery, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing 100070, China
  • Received:2024-04-08 Published:2024-06-01
  • Corresponding author: Dong Zhang
引用本文:

张绍森, 王基源, 张东. 颅内动静脉畸形破裂出血预测中的若干问题[J/OL]. 中华脑血管病杂志(电子版), 2024, 18(03): 197-201.

Shaosen Zhang, Jiyuan Wang, Dong Zhang. Several issues in predicting intracranial arteriovenous malformation rupture and hemorrhage[J/OL]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2024, 18(03): 197-201.

颅内动静脉畸形(AVM)是一种先天血管畸形,一般认为终身出血风险为50%,因此平衡手术风险和出血风险是AVM诊疗中最重要的问题。如何准确预测破裂出血风险一直是AVM研究中的核心课题。目前,随着影像检查和人工智能技术的进步,许多研究者在预测AVM出血的研究中不断取得进展。本文对目前一些公认的AVM破裂出血相关的危险因素进行了评述,并分析了目前国际上若干较高水平的AVM风险预测模型的优势和不足,为AVM破裂风险预测提供参考。

Intracranial arteriovenous malformation (AVM) is a congenital vascular malformation with an estimated lifetime rupture risk of 50%. Striking the right balance between the risks of surgical intervention and rupture is a critical consideration in the diagnosis and treatment of AVM. The accurate prediction of rupture risk is a major focus of AVM research. Recent advancements in imaging techniques and artificial intelligence have contributed to progress in predicting AVM rupture. This article reviews the recognized risk factors for rupture, and evaluates AVM risk prediction models to assist in predicting AVM rupture risk globally.

1
Lawton MT, Rutledge WC, Kim H, et al. Brain arteriovenous malformations [J]. Nat Rev Dis Primers, 2015, 1: 15008.
2
Osbun JW, Reynolds MR, Barrow DL. Arteriovenous malformations: epidemiology, clinical presentation, and diagnostic evaluation [J]. Handb Clin Neurol, 2017, 143: 25-29.
3
Yang W, Feghali J, Sattari SA, et al. The natural history of hemorrhage in brain arteriovenous malformations-poisson regression analysis of 1066 patients in a single institution [J]. Neurosurgery, 2024, 94(2): 389-398.
4
Mohr JP, Parides MK, Stapf C, et al. Medical management with or without interventional therapy for unruptured brain arteriovenous malformations (ARUBA): a multicentre, non-blinded, randomised trial [J]. Lancet, 2014, 383(9917): 614-621.
5
Yamada S, Takagi Y, Nozaki K, et al. Risk factors for subsequent hemorrhage in patients with cerebral arteriovenous malformations [J]. J Neurosurg, 2007, 107(5): 965-972.
6
Karlsson B, Lindquist C, Johansson A, et al. Annual risk for the first hemorrhage from untreated cerebral arteriovenous malformations [J]. Minim Invasive Neurosurg, 1997, 40(2): 40-46.
7
Hermanto Y, Takagi Y, Yoshida K, et al. Histopathological features of brain arteriovenous malformations in Japanese patients [J]. Neurol Med Chir (Tokyo), 2016, 56(6): 340-344.
8
Tao W, Li S, Zeng C, et al. Machine learning models for brain arteriovenous malformations presenting with hemorrhage based on clinical and angioarchitectural characteristics [J]. Acad Radiol, 2024, 31(4): 1583-1593.
9
Stapf C, Mast H, Sciacca RR, et al. Predictors of hemorrhage in patients with untreated brain arteriovenous malformation [J]. Neurology, 2006, 66(9): 1350-1355.
10
Qureshi AM, Muthusami P, Krings T, et al. Clinical and angioarchitectural features of hemorrhagic brain arterio-venous malformations in adults and children: contrasts and implications on outcome [J]. Neurosurgery, 2021, 89(4): 645-652.
11
Garzelli L, Shotar E, Blauwblomme T, et al. Risk factors for early brain AVM rupture: cohort study of pediatric and adult patients [J]. AJNR Am J Neuroradiol, 2020, 41(12): 2358-2363.
12
Kim H, Sidney S, Mcculloch CE, et al. Racial/Ethnic differences in longitudinal risk of intracranial hemorrhage in brain arteriovenous malformation patients [J]. Stroke, 2007, 38(9): 2430-2437.
13
Goldberg J, Raabe A, Bervini D. Natural history of brain arteriovenous malformations: systematic review [J]. J Neurosurg Sci, 2018, 62(4): 437-443.
14
Hernesniemi JA, Dashti R, Juvela S, et al. Natural history of brain arteriovenous malformations: a long-term follow-up study of risk of hemorrhage in 238 patients [J]. Neurosurgery, 2008, 63(5): 823-829, discussion 829-831.
15
De Liyis BG, Arini A, Karuniamaya CP, et al. Risk of intracranial hemorrhage in brain arteriovenous malformations: a systematic review and meta-analysis [J]. J Neurol, 2024, 271(5): 2274-2284.
16
Mendoza-Elias N, Shakur SF, Charbel FT, et al. Cerebral arteriovenous malformation draining vein stenosis is associated with atherosclerotic risk factors [J]. J Neurointerv Surg, 2018, 10(8): 788-790.
17
Yu JF, Nicholson AD, Nelson J, et al. Predictors of intracranial hemorrhage volume and distribution in brain arteriovenous malformation [J]. Interv Neuroradiol, 2018, 24(2): 183-188.
18
Sahlein DH, Mora P, Becske T, et al. Features predictive of brain arteriovenous malformation hemorrhage: extrapolation to a physiologic model [J]. Stroke, 2014, 45(7): 1964-1970.
19
Nataf F, Meder JF, Roux FX, et al. Angioarchitecture associated with haemorrhage in cerebral arteriovenous malformations: a prognostic statistical model [J]. Neuroradiology, 1997, 39(1): 52-58.
20
Miyasaka Y, Yada K, Ohwada T, et al. An analysis of the venous drainage system as a factor in hemorrhage from arteriovenous malformations [J]. J Neurosurg, 1992, 76(2): 239-243.
21
Shi X, Wang Z, Yu C. An analysis of the correlation between angiographic and clinical findings in cerebral arteriovenous malformations [J]. Chin Med Sci J, 1993, 8(1): 35-37.
22
Albert P, Salgado H, Polaina M, et al. A study on the venous drainage of 150 cerebral arteriovenous malformations as related to haemorrhagic risks and size of the lesion [J]. Acta Neurochir (Wien), 1990, 103(1-2): 30-34.
23
De Castro-Afonso LH, Vanzim JR, Trivelato FP, et al. Association between draining vein diameters and intracranial arteriovenous malformation hemorrhage: a multicentric retrospective study [J]. Neuroradiology, 2020, 62(11): 1497-1505.
24
Li R, Chen P, Han H, et al. Association of nidus size and rupture in brain arteriovenous malformations: insight from angioarchitecture and hemodynamics [J]. Neurosurg Rev, 2023, 46(1): 216.
25
Mosteiro A, Pedrosa L, Torne R, et al. Venous tortuosity as a novel biomarker of rupture risk in arteriovenous malformations: ARI score [J]. J Neurointerv Surg, 2022, 14(12): 1220-1225.
26
Hung AL, Yang W, Jiang B, et al. The effect of flow-related aneurysms on hemorrhagic risk of intracranial arteriovenous malformations [J]. Neurosurgery, 2019, 85(4): 466-475.
27
Langer DJ, Lasner TM, Hurst RW, et al. Hypertension, small size, and deep venous drainage are associated with risk of hemorrhagic presentation of cerebral arteriovenous malformations [J]. Neurosurgery, 1998, 42(3): 481-486, discussion 487-489.
28
Spetzler RF, Hargraves RW, Mccormick PW, et al. Relationship of perfusion pressure and size to risk of hemorrhage from arteriovenous malformations [J]. J Neurosurg, 1992, 76(6): 918-923.
29
Rustici A, Vari F, Sturiale C, et al. The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture? [J]. Neuroradiol J, 2023, 36(4): 427-434.
30
Stefani MA, Porter PJ, Terbrugge KG, et al. Large and deep brain arteriovenous malformations are associated with risk of future hemorrhage [J]. Stroke, 2002, 33(5): 1220-1224.
31
Mine S, Hirai S, Ono J, et al. Risk factors for poor outcome of untreated arteriovenous malformation [J]. J Clin Neurosci, 2000, 7(6): 503-506.
32
Zhang S, Sun S, Zhai Y, et al. Development and validation of a model for predicting the risk of brain arteriovenous malformation rupture based on three-dimensional morphological features [J]. Front Neurol, 2022, 13: 979014.
33
Khaw AV, Mohr JP, Sciacca RR, et al. Association of infratentorial brain arteriovenous malformations with hemorrhage at initial presentation [J]. Stroke, 2004, 35(3): 660-663.
34
Chalil A, Raupp EF, Duckwiler GR, et al. Hemodynamic and anatomical factors in arteriovenous malformation clinical presentation: 45 case studies [J]. Can J Neurol Sci, 2023, 50(1): 37-43.
35
Raoult H, Bannier E, Maurel P, et al. Hemodynamic quantification in brain arteriovenous malformations with time-resolved spin-labeled magnetic resonance angiography [J]. Stroke, 2014, 45(8): 2461-2464.
36
Lin TM, Yang HC, Lee CC, et al. Stasis index from hemodynamic analysis using quantitative DSA correlates with hemorrhage of supratentorial arteriovenous malformation: a cross-sectional study [J]. J Neurosurg, 2019, 132(5): 1574-1582.
37
Zhu H, Liu L, Chang Y, et al. Quantitative evaluation of the subsequent hemorrhage with arteriography-derived hemodynamic features in patients with untreated cerebral arteriovenous malformation [J]. Front Neurol, 2023, 14: 1174245.
38
Chen Y, Chen P, Li R, et al. Rupture-related quantitative hemodynamics of the supratentorial arteriovenous malformation nidus [J]. J Neurosurg, 2023, 138(3): 740-749.
39
Guo Y, Saunders T, Su H, et al. Silent intralesional microhemorrhage as a risk factor for brain arteriovenous malformation rupture [J]. Stroke, 2012, 43(5): 1240-1246.
40
Feghali J, Yang W, Xu R, et al. R(2)eD AVM score [J]. Stroke, 2019, 50(7): 1703-1710.
41
Taweel BA, Gillespie CS, Richardson GE, et al. External validation of brain arteriovenous malformation haemorrhage scores, AVICH, ICH and R2eD [J]. Acta Neurochir (Wien), 2022, 164(6): 1685-1692.
42
Rangwala SD, Albanese JS, Slingerland AL, et al. External validation of the R2eD AVM scoring system to assess rupture risk in pediatric AVM patients [J]. J Neurosurg Pediatr, 2023, 31(5): 469-475.
43
Chen Y, Han H, Meng X, et al. Development and validation of a scoring system for hemorrhage risk in brain arteriovenous malformations [J]. JAMA Netw Open, 2023, 6(3): e231070.
44
Zhang S, Wang J, Sun S, et al. CT angiography radiomics combining traditional risk factors to predict brain arteriovenous malformation rupture: a machine learning, multicenter study [J]. Transl Stroke Res, 2023. Online ahead of print.
[1] 洪玮, 叶细容, 刘枝红, 杨银凤, 吕志红. 超声影像组学联合临床病理特征预测乳腺癌新辅助化疗完全病理缓解的价值[J/OL]. 中华医学超声杂志(电子版), 2024, 21(06): 571-579.
[2] 陈晓玲, 钟永洌, 刘巧梨, 李娜, 张志奇, 廖威明, 黄桂武. 超高龄髋膝关节术后谵妄及心血管并发症风险预测[J/OL]. 中华关节外科杂志(电子版), 2024, 18(05): 575-584.
[3] 奚玲, 仝瀚文, 缪骥, 毛永欢, 沈晓菲, 杜峻峰, 刘晔. 基于肌少症构建的造口旁疝危险因素预测模型[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(01): 48-51.
[4] 屈勤芳, 束方莲. 盆腔器官脱垂患者盆底重建手术后压力性尿失禁发生的影响因素及列线图预测模型构建[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 606-612.
[5] 周正阳, 陈凯, 仇多良, 邵乐宁, 吴浩荣, 钟丰云. 腹腔镜腹股沟疝修补术后出血原因分析及处理[J/OL]. 中华疝和腹壁外科杂志(电子版), 2024, 18(06): 660-664.
[6] 杭轶, 杨小勇, 李文美, 薛磊. 可控性低中心静脉压技术在肝切除术中应用的最适中心静脉压[J/OL]. 中华肝脏外科手术学电子杂志, 2024, 13(06): 813-817.
[7] 公宇, 廖媛, 尚梅. 肝细胞癌TACE术后复发影响因素及预测模型建立[J/OL]. 中华肝脏外科手术学电子杂志, 2024, 13(06): 818-824.
[8] 王贝贝, 崔振义, 王静, 王晗妍, 吕红芝, 李秀婷. 老年股骨粗隆间骨折患者术后贫血预测模型的构建与验证[J/OL]. 中华老年骨科与康复电子杂志, 2024, 10(06): 355-362.
[9] 孙晗, 于冰, 武侠, 周熙朗. 基于循环肿瘤DNA 甲基化的结直肠癌筛查预测模型的构建与验证[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 500-506.
[10] 吴广迎, 张延娟, 秦鹏, 卢艳丽. 经颈静脉肝内门体静脉分流术预防上消化道出血的临床研究[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(06): 545-548.
[11] 韦巧玲, 黄妍, 赵昌, 宋庆峰, 陈祖毅, 黄莹, 蒙嫦, 黄靖. 肝癌微波消融术后中重度疼痛风险预测列线图模型构建及验证[J/OL]. 中华临床医师杂志(电子版), 2024, 18(08): 715-721.
[12] 蔡晓雯, 李慧景, 丘婕, 杨翼帆, 吴素贤, 林玉彤, 何秋娜. 肝癌患者肝动脉化疗栓塞术后疼痛风险预测模型的构建及验证[J/OL]. 中华临床医师杂志(电子版), 2024, 18(08): 722-728.
[13] 王誉英, 刘世伟, 王睿, 曾娅玲, 涂禧慧, 张蒲蓉. 老年乳腺癌新辅助治疗病理完全缓解的预测因素分析[J/OL]. 中华临床医师杂志(电子版), 2024, 18(07): 641-646.
[14] 董晟, 郎胜坤, 葛新, 孙少君, 薛明宇. 反向休克指数乘以格拉斯哥昏迷评分对老年严重创伤患者发生急性创伤性凝血功能障碍的预测价值[J/OL]. 中华临床医师杂志(电子版), 2024, 18(06): 541-547.
[15] 黄圣楷, 许斌, 苏健, 孙龙. 海南省2010~2020年乙型肝炎流行趋势的时间序列分析及预测[J/OL]. 中华临床医师杂志(电子版), 2024, 18(06): 555-561.
阅读次数
全文


摘要