视网膜血管分形分析在青光眼和脑卒中患者中应用的临床研究

doi:10.3877/cma.j.issn.2095-2007.2025.03.003

目的

探讨青光眼和脑卒中患者视网膜血管分形的改变。

方法

选取2020年4月至2020年10月在首都医科大学附属北京同仁医院就诊的青光眼95例(95只眼)患者、同期于神经科诊治脑卒中患者97例(97只眼)及体检的健康对照组受试者100例(100只眼)。其中，青光眼组男性患者51例(51只眼)，女性44例(44只眼)；年龄46～69岁，平均年龄为(55.6±7.8)岁。脑卒中组男性患者63例(63只眼)，女性34例(34只眼)；年龄58～73岁，平均年龄为(64.7±5.6)岁。对照组男性受试者50例(50只眼)，女性50例(50只眼)；年龄40～60岁，平均年龄为(52.4±6.4)岁。所有受试者都进行常规眼科检查、眼底照相、视野及光学相干断层扫描检查，应用计算机辅助图像分析和测量视网膜血管管径宽度、血管弯曲度及血管分形维数。视网膜神经纤维层(RNFL)厚度和视网膜血管参数的测量值采用Kolmogorov－Smirnov方法检验符合正态分布，以±s表示，多组间比较采用单因素方差分析，当差异有统计学意义时，进一步采用LSD两两比较。视网膜血管参数与RNFL厚度的关系采用Pearson相关性分析。

结果

青光眼组、脑卒中组患者及对照组受试者平均RNFL厚度分别为(75.3±12.6)μm、(89.5±8.7)μm及(103.6±6.2)μm，差异有统计学意义(F＝148.516，P<0.05)。青光眼和脑卒中组患者平均盘周RNFL厚度降低，青光眼组和脑卒中组患者分别与对照组受试者比较差异有统计学意义(t＝－4.362，－3.216；P<0.05)。对照组、青光眼组及脑卒中组患者的Zone B＋C区动静脉宽度比、Zone B区动静脉宽度比、位于Zone B＋C区的较大6个动脉宽度、位于Zone B区的较大6个动脉动脉宽度、位于Zone B＋C区的较大6个静脉宽度、位于Zone B区的较大6个静脉宽度、全部血管简单弯曲度、全部血管曲率弯曲度、动脉简单弯曲度、动脉曲率弯曲度、静脉简单弯曲度、静脉曲率弯曲度、全部血管分形维数、动脉分形维数及静脉分形维数分别为0.552±0.216、0.530±0.137、(8.491±2.039)像素、(8.804±2.136)像素、(15.959±2.138)像素、(15.934±2.962)像素、1.057±0.984、0.033±0.002、1.083±0.169、0.027±0.026、1.069±0.187、0.042±0.006、1.527±0.148、1.295±0.065、1.344±0.058、0.558±0.111、0.567±0.104、(8.852±1.931)像素、(8.923±1.872)像素、(16.015±2.787)像素、(15.891±2.921)像素、1.069±0.251、0.003±0.001、1.044±0.021、0.003±0.001、1.068±0.041、0.044±0.002、1.529±0.032、1.286±0.051、1.342±0.049、0.609±0.108、0.774±0.143、(10.082±2.151)像素、(10.417±2.223)像素、(16.548±2.885)像素、(16.739±2.768)像素、1.221±1.378、0.331±0.024、1.262±1.605、0.029±0.015、1.082±0.209、1.932±0.137、1.544±0.156、1.331±0.039及1.367±0.035，差异均有统计学意义(F＝108.973、117.136，104.762，119.531，113.538，121.539，119.968，134.472，125.162，104.167，76.106，136.262，109.421，116.632，43.279；P<0.05)。青光眼组患者Zone B＋C区较大6个动静脉宽度比、Zone B＋C动脉宽度、Zone B区视网膜动脉宽度、Zone B＋C视网膜静脉宽度、Zone B区视网膜静脉宽度、视网膜血管的简单弯曲度、视网膜全部血管曲率弯曲度、视网膜动脉简单弯曲度、视网膜静脉曲率弯曲度、视网膜血管分形维数及视网膜动脉分形维数与对照组比较，差异均有统计学意义(t＝－3.326，－3.761，－3.964，－2.237，－2.453，－2.447，－3.895，－2.963，－3.871，－2.037，－2.363；P<0.05)。青光眼组患者视网膜血管分形维数与盘周RNFL厚度呈正相关，其相关性具有统计学意义(r＝0.783，P<0.05)。脑卒中组患者Zone B＋C区较大6个视网膜动静脉宽度比、Zone B＋C动脉宽度、Zone B区动脉宽度、Zone B＋C视网膜静脉宽度、Zone B区视网膜静脉宽度、视网膜血管简单弯曲度、视网膜全部血管曲率弯曲度、视网膜动脉简单弯曲度、视网膜静脉曲率弯曲度、视网膜血管分形维数及视网膜动脉分形维数与对照组比较，差异有统计学意义(t＝－2.741，－3.153，－2.930，－2.041，－2.726，－2.323，－3.881，－3.267，－2.965，－2.024，－2.473；P<0.05)。脑卒中组患者视网膜血管分形维数与盘周RNFL厚度呈正相关，其相关性具有统计学意义(r＝0.645，P<0.05)。脑卒中患者视网膜血管分形维数越低，平均盘周RNFL厚度越低。

结论

青光眼和脑卒中患者的视网膜血管管径变窄和血管弯曲度降低，视网膜血管分形维数降低，脑卒中患者的视网膜血管改变出现与青光眼变化趋势相近，青光眼患者视网膜血管分形维数与青光眼严重程度相关，较低的视网膜血管分形维数和较低的RNFL厚度与脑卒中相关。

关键词: 血管分形分析, 视网膜血管, 视网膜神经纤维层, 青光眼, 脑卒中

Objective

The aim of this study is to explore the changes in retinal vascular fractal dimension in patients with glaucoma and stroke.

Methods

From April 2020 to October 2020, 95 patients (95 eyes) with glaucoma who were treated at Beijing Tongren Hospital affiliated to Capital Medical University, 97 patients (97 eyes) with stroke who were diagnosed in the Neurology Department of Beijing Tongren Hospital, 100 healthy subjects (100 eyes) were recruited in the same period. Among them, there were 51 male patients (51 eyes) and 44 female patients (44 eyes) with an average age of (55.6±7.8) years (ranging from 46 to 69 years) in the glaucoma group; 63 male patients (63 eyes) and 34 female patients (34 eyes) with an average age of (64.7±5.6) years (ranging 58 to 73 years) in the stroke group; 50 male cases (50 eyes) and 50 female cases (50 eyes) with an average age of (52.4±6.4) years (ranging from 40 to 60 years) in the control group. All subjects underwent routine ophthalmic examinations, fundus photography, visual field and optical coherence tomography examinations, and computer-aided image analysis and measurements of retinal vessel diameter width, vessel curvature, and vessel fractal dimension were applied. The measurement values of retinal nerve fiber layer (RNFL) thickness and retinal vascular parameters were tested using Kolmogorov Smirnov method to conform normal distribution, expressed as ±s, and compared between multiple groups using one-way analysis of variance. When the differences were statistically significant, LSD was further used for comparison between two groups. The relationship between retinal vascular parameters and RNFL thickness was analyzed using Pearson correlation analysis.

Results

The average RNFL thickness in the glaucoma group, stroke group, and control group was (75.3±12.6) μm, (89.5±8.7) μm, and (103.6±6.2) μm, respectively, with statistically significant differences (F=148.516, P<0.05). The average RNFL thickness around the disc decreased in glaucoma group and stroke group, there was statistically significant difference between the glaucoma group and the stroke group compared to the control group (t=-4.362, -3.216; P<0.05). The arterial to venous width ratio in Zone B+ C, arterial to venous width ratio in Zone B, 6 larger arterial widths located in Zone B+ C, 6 larger arterial widths located in Zone B, 6 larger venous widths located in Zone B+ C, 6 larger venous widths located in Zone B, all vessel simple bending, all vessel curvature bending, arterial simple bending, arterial curvature bending, venous simple bending, venous curvature bending, all vessel fractal dimension, arterial fractal dimension, and venous fractal dimension were 0.552±0.216, 0.530±0.137, (8.491±2.039) pixels, (8.804±2.136) pixels, respectively, for the control group, glaucoma group, and stroke group (15.959±2.138) pixels, (15.934±2.962) pixels, 1.057±0.984, 0.033±0.002, 1.083±0.169, 0.027±0.026, 1.069±0.187, 0.042±0.006, 1.527±0.148, 1.295±0.065, 1.344±0.058, 0.558±0.111, 0.567±0.104, (8.852±1.931) pixels, (8.923±1.872) pixels, (16.015±2.787) pixels, (15.891±2.921) pixels, 1.069±0.251, 0.003±0.001 1.044±0.021, 0.003±0.001, 1.068±0.041, 0.044±0.002, 1.529±0.032, 1.286±0.051, 1.342±0.049, 0.609±0.108, 0.774±0.143, (10.082±2.151) pixels, (10.417±2.223) pixels, (16.548±2.885) pixels, (16.739±2.768) pixels, 1.221±1.378, 0.331±0.024, 1.262±1.605, 0.029±0.015, 1.082±0.209, 1.932±0.137 1.544±0.156, 1.331±0.039, and 1.367±0.035, showed statistically significant differences (F=108.973, 117.136, 104.762, 119.531, 113.538, 121.539, 119.968, 134.472, 125.162, 104.167, 76.106, 136.262, 109.421, 116.632, 43.279; P<0.05). Compared between the glaucoma group and the control group, vascular parameters of retinal arteriovenous width ratio (Zone B+ C), arterial width in Zone B+ C, arterial width in Zone B, retinal vein width in Zone B+ C, retinal vein width in Zone B, simple bending of all retinal blood vessels, curvature bending of all retinal blood vessels, simple bending of retinal arteries, curvature bending of retinal veins, fractal dimension of retinal blood vessels, and fractal dimension of retinal arteries, had shown that the differences were statistically significant (t=-3.326, -3.761, -3.964, -2.237, -2.453, -2.447, -3.895, -2.963, -3.871, -2.037, -2.363; P<0.05). The fractal dimension of retinal blood vessels in glaucoma patients was positively correlated with the thickness of RNFL around the disc, and the correlation was statistically significant (r=0.783, P<0.05). Compared between the stroke group and the control group, vascular parameters of retinal arteriovenous width ratio (Zone B+ C), arterial width in Zone B+ C, arterial width in Zone B, retinal vein width in Zone B+ C, retinal vein width in Zone B, simple bending of all retinal blood vessels, curvature bending of all retinal blood vessels, simple bending of retinal arteries, curvature bending of retinal veins, fractal dimension of retinal blood vessels, and fractal dimension of retinal arteries, had shown that the differences were statistically significant (t=-2.741, -3.153, -2.930, -2.041, -2.726, -2.323, -3.881, -3.267, -2.965, -2.024, -2.473; P<0.05). The fractal dimension of retinal blood vessels in stroke patients was positively correlated with the thickness of RNFL around the disc, and the correlation is statistically significant (r=0.645, P<0.05). The lower the fractal dimensionality of retinal vascular analysis in stroke patients, the lower the average RNFL thickness.

Conclusions

Patients with glaucoma and patients with stroke have narrower retinal vessel diameter, decreased retianl vascular bending, and decreased retinal vascular fractal dimension. The parameters of retinal vascular in stroke patients show a trend similar to glaucoma patients. The fractal dimension of retinal vascular in glaucoma is correlated with the severity of glaucoma, lower retinal vascular fractal dimension and RNFL thickness are associated with stroke.

Key words: Fractal dimension, Retinal vascular, Retinal nerve fiber layer, Glaucoma, Stroke

图3 裂隙灯显微镜下彩色眼底像视网膜血管动静脉宽度测量的方法图　图3A示裂隙灯显微镜下彩色眼底像视网膜血管测量区域选取较大的6个动脉和静脉，蓝色显示静脉，红色显示动脉(×16)；图3B示颞上视网膜动脉和静脉宽度；图3C示颞下视网膜动脉和静脉宽度

图5 脑卒中患者眼底照相及颅脑磁共振和磁共振血管成像　图5A示裂隙灯显微镜下患者的彩色眼底照相(×16)，可见右眼视网膜线状出血和棉絮斑(箭头)，视网膜动脉管径变细，动脉硬化；图5B示裂隙灯显微镜下彩色眼底像(×16)，可见左眼视网膜中央动脉阻塞，视网膜灰白水肿，视网膜动脉弥漫性缩窄，视网膜静脉迂曲扩张；图5C示颅脑磁共振影像，T2WI相显示右侧丘脑梗塞灶(箭头)；图5D示磁共振血管成像显示右侧大脑后动脉明显缩窄和动脉硬化征象(箭头)

表1 视网膜血管测量参数的量化指标及其意义

参数类型	参数意义
视盘视杯参数
视盘直径	视盘直径像素值
视杯直径	视杯直径像素值
杯盘比	视杯与视盘直径比值
视网膜血管宽度参数
动脉宽度	在Zone B＋C区和Zone B区测量较大的6个动脉宽度像素值
静脉宽度	在Zone B＋C区和Zone B区测量较大的6个静脉宽度像素值
动静脉宽度比	在Zone B＋C区和Zone B区测量较大的6个动脉与静脉宽度比值
视网膜血管弯曲度参数
简单弯曲度	图2A区域里全部血管(动脉和静脉)的简单弯曲度
曲率弯曲度	图2A区域里全部血管(动脉和静脉)的曲率弯曲度
动脉简单弯曲度	图2A区域里全部动脉的简单弯曲度
动脉曲率弯曲度	图2A区域里全部动脉的曲率弯曲度
静脉简单弯曲度	图2A区域里全部静脉的简单弯曲度
静脉曲率弯曲度	图2A区域里全部静脉的曲率弯曲度
血管分形参数
血管分形维数	应用sandbox方法，测量图2A区域里的全部血管分形维数
动脉分形维数	应用sandbox方法，测量图2A区域里的全部动脉分形维数
静脉分形维数	应用sandbox方法，测量图2A区域里的全部静脉分形维数

表1 视网膜血管测量参数的量化指标及其意义

参数类型	参数意义
视盘视杯参数
视盘直径	视盘直径像素值
视杯直径	视杯直径像素值
杯盘比	视杯与视盘直径比值
视网膜血管宽度参数
动脉宽度	在Zone B＋C区和Zone B区测量较大的6个动脉宽度像素值
静脉宽度	在Zone B＋C区和Zone B区测量较大的6个静脉宽度像素值
动静脉宽度比	在Zone B＋C区和Zone B区测量较大的6个动脉与静脉宽度比值
视网膜血管弯曲度参数
简单弯曲度	图2A区域里全部血管(动脉和静脉)的简单弯曲度
曲率弯曲度	图2A区域里全部血管(动脉和静脉)的曲率弯曲度
动脉简单弯曲度	图2A区域里全部动脉的简单弯曲度
动脉曲率弯曲度	图2A区域里全部动脉的曲率弯曲度
静脉简单弯曲度	图2A区域里全部静脉的简单弯曲度
静脉曲率弯曲度	图2A区域里全部静脉的曲率弯曲度
血管分形参数
血管分形维数	应用sandbox方法，测量图2A区域里的全部血管分形维数
动脉分形维数	应用sandbox方法，测量图2A区域里的全部动脉分形维数
静脉分形维数	应用sandbox方法，测量图2A区域里的全部静脉分形维数

[1]	Wang J, Chen T, Wang J, et al. Retinal vascular geometry and its association to silent brain infarction[J]. BMC Ophthalmol, 2025, 25(1): 36.
[2]	Zeng R, Garg I, Bannai D, et al. Retinal microvasculature and vasoreactivity changes in hypertension using optical coherence tomography－angiography[J]. Graefes Arch Clin Exp Ophthalmol, 2022, 260(11): 3505-3515.
[3]	Shi C, Chen Y, Kwapong WR, et al. Characterization by fractal dimension analysis of the retinal capillary network in Parkinson disease[J]. Retina, 2020, 40(8): 1483-1491.
[4]	Chua J, Hu Q, Ke M, et al. Retinal microvasculature dysfunction is associated with Alzheimer′s disease and mild cognitive impairment[J]. Alzheimers Res Ther, 2020, 12(1): 161.
[5]	Girach Z, Sarian A, Maldonado－García C, et al. Retinal imaging for the assessment of stroke risk: a systematic review[J]. J Neurol, 2024, 271(5): 2285-2297.
[6]	Dinesen S, Jensen PS, Bloksgaard M, et al. Retinal vascular fractal dimensions and their association with macrovascular cardiac disease[J]. Ophthalmic Res, 2021, 64(4): 561-566.
[7]	Liu F, Chen X, Wang Q, et al. Correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 diabetic nephropathy[J]. Clin Kidney J, 2024, 17(8): sfae204.
[8]	Dong X, Zou Y, Li X, et al. Novel 2D/3D vascular biomarkers reveal association between fundus changes and coronary heart disease[J]. Microvasc Res, 2025, 159(5): 104793.
[9]	Biffi E, Turple Z, Chung J, et al. Retinal biomarkers of cerebral small vessel disease: a systematic review[J]. PLoS One, 2022,17(4): e0266974.
[10]	Foster PJ, Buhrmann R, Quigley HA, et al. The definition and classification of glaucoma in prevalence surveys[J]. Br J Ophthalmol, 2002, 86 (2): 238-242.
[11]	Feigin VL, Owolabi MO; World Stroke Organization－Lancet Neurology Commission Stroke Collaboration Group. Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization－Lancet Neurology Commission[J]. Lancet Neurol, 2023, 22(12): 1160-1206.
[12]	Deepika V, JeyaLakshmi V, Latha P, et al. Relationship of fractal analysis in retinal microvascularity with demographic and diagnostic parameters[J]. Microvasc Res, 2022, 139(1): 104237.
[13]	Kiyota N, Shiga Y, Omodaka K, et al. Time－course changes in optic nerve head blood flow and retinal nerve fiber layer thickness in eyes with open－angle glaucoma[J]. Ophthalmology, 2021, 128(5): 663-671.
[14]	Caprioli J, Coleman AL. Blood pressure, perfusion pressure, and glaucoma[J]. Am J Ophthalmol, 2010, 149(5): 704-712.
[15]	GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990—2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet Neurol, 2021, 20(10): 795-820.
[16]	张莉，徐亮，杨桦，等. 眼底指标改变与脑卒中患病的相关性[J]. 眼科，2015,24(1):13-18.
[17]	Liew G, Gopinath B, White AJ, et al. Retinal vasculature fractal and stroke mortality[J]. Stroke, 2021, 52(4): 1276-1282.
[18]	Gao Y, Xu L, He N, et al. A narrative review of retinal vascular parameters and the applications (Part Ⅱ): Diagnosis in stroke[J]. Brain Circ, 2023, 9(3): 129-134.
[19]	Mankoo A, Roy S, Davies A, et al. The role of the autonomic nervous system in cerebral blood flow regulation in stroke: A review[J]. Auton Neurosci, 2023, 246(5): 103082.
[20]	Di－Marco E, Aiello F, Lombardo M, et al. A literature review of hypertensive retinopathy: systemic correlations and new technologies[J]. Eur Rev Med Pharmacol Sci, 2022, 26(18): 6424-6443.
[21]	Colcombe J, Solli E, Kaiser A, et al. The use of retinal imaging including fundoscopy, OCT, and OCTA for cardiovascular risk stratification and the detection of subclinical atherosclerosis[J]. Curr Atheroscler Rep, 2025, 27(1): 23.
[22]	Zhang JF, Wiseman S, Valdés－Hernández MC, et al. The application of optical coherence tomography angiography in cerebral small vessel disease, ischemic stroke, and dementia: a systematic review[J]. Front Neurol, 2020, 11(9): 1009.
[23]	Girach Z, Sarian A, Maldonado－García C, et al. Retinal imaging for the assessment of stroke risk: a systematic review[J]. J Neurol, 2024, 271(5): 2285-2297.
[24]	Kunicki AC, Oliveira AJ, Mendonça MB, et al. Can the fractal dimension be applied for the early diagnosis of non－proliferative diabetic retinopathy[J]? Braz J Med Biol Res, 2009, 42(10): 930-934.
[25]	Grauslund J, Green A, Kawasaki R, et al. Retinal vascular fractals and microvascular and macrovascular complications in type 1 diabetes[J]. Ophthalmology, 2010, 117(7): 1400-1405.
[26]	Raichlen DA, Klimentidis YC, Hsu CH, et al. Fractal complexity of daily physical activity patterns differs with age over the life span and is associated with mortality in older adults[J]. J Gerontol A Biol Sci Med Sci, 2019, 74(9): 1461-1467.
[27]	Chiquet C, Gavard O, Arnould L, et al. Retinal vessel phenotype in patients with primary open－angle glaucoma[J]. Acta Ophthalmol, 2020, 98(1): e88-e93.
[28]	Moore NA, Harris A, Wentz S, et al. Baseline retrobulbar blood flow is associated with both functional and structural glaucomatous progression after 4 years[J]. Br J Ophthalmol, 2017, 101(3): 305-308.
[29]	Giorgio A, Zhang J, Costantino F, et al. Diffuse brain damage in normal tension glaucoma[J]. Hum Brain Mapp, 2018, 39(1): 532-541.
[30]	Nucci C, Garaci F, Altobelli S, et al. Diffusional kurtosis imaging of white matter degeneration in glaucoma[J]. J Clin Med, 2020, 9(10): 3122.
[31]	Kim HM, Han JW, Park YJ, et al. Association between retinal layer thickness and cognitive decline in older adults[J]. JAMA Ophthalmol, 2022, 140(7): 683-690.
[32]	Ge YJ, Xu W, Ou YN, et al. Retinal biomarkers in Alzheimer′s disease and mild cognitive impairment: A systematic review and meta－analysis[J]. Ageing Res Rev, 2021, 69(8): 101361.
[33]	Apte RS. Retinal imaging as a predictor of cognitive impairment[J]. JAMA Ophthalmol, 2022, 140(7): 691.
[34]	Xue J, Zhu Y, Liu Z, et al. Demyelination of the optic nerve: an underlying factor in glaucoma[J]. Front Aging Neurosci, 2021, 13(11): 701322.
[35]	Marin MA, Carmichael ST. Mechanisms of demyelination and remyelination in the young and aged brain following white matter stroke[J]. Neurobiol Dis, 2019,126(1): 5-12.
[36]	Khalafi P, Morsali S, Hamidi S, et al. Artificial intelligence in stroke risk assessment and management via retinal imaging[J]. Front Comput Neurosci, 2025,19(2): 1490603.

[1]	韩秋霞, 朱晗玉, 段颖洁, 田明威, 朱凯怡, 马丽洁, 孙倩美. 维持性血液透析患者单核细胞/高密度脂蛋白胆固醇比值和血小板/高密度脂蛋白胆固醇比值与脑卒中风险的相关性[J/OL]. 中华肾病研究电子杂志, 2025, 14(03): 140-145.
[2]	张莉, 左晓玲, 王宁利. 青光眼患者视神经形态结构变化与血流密度及血氧代谢改变关系的临床研究[J/OL]. 中华眼科医学杂志(电子版), 2025, 15(02): 78-86.
[3]	王晓丽, 王晓媛, 孙洪涛. 老年急性缺血性脑卒中伴房颤患者预后的影响因素分析[J/OL]. 中华神经创伤外科电子杂志, 2025, 11(02): 111-116.
[4]	王珊珊, 王文, 杨启亮, 张文朝, 崔宁宁, 李婷. 虚拟现实技术对脑卒中患者认知和负性情绪影响的Meta分析[J/OL]. 中华脑科疾病与康复杂志(电子版), 2025, 15(03): 161-170.
[5]	王永清, 马小花, 张晓玲, 张赛赛, 张娜丽. 老年脑卒中患者健康素养、社会支持与卒中复发风险感知的关系及其影响因素研究[J/OL]. 中华脑科疾病与康复杂志(电子版), 2025, 15(03): 180-186.
[6]	李娇娇, 回雪, 杨美荣, 周红军. 穴位电刺激联合中药脐部热熨辅助治疗脑卒中后便秘患者的疗效研究[J/OL]. 中华消化病与影像杂志(电子版), 2025, 15(01): 69-72.
[7]	杨墨, 曹月洲, 吕朋华, 丁鸭锁, 刘振生, 贾振宇, 赵林波, 徐川, 施海彬, 刘圣. 溶栓时间窗内动脉粥样硬化性基底动脉闭塞桥接治疗与直接取栓的多中心对照研究[J/OL]. 中华介入放射学电子杂志, 2025, 13(02): 104-109.
[8]	光雪珂, 刘承云, 卢伟琳. 线粒体功能障碍与老年人缺血性脑卒中相关信号通路关系研究进展[J/OL]. 中华老年病研究电子杂志, 2025, 12(01): 41-47.
[9]	陈娜娜, 韩莹, 胥青芝. 基于文献计量学的脑卒中吞咽障碍康复护理研究进展与临床热点趋势分析[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(02): 100-108.
[10]	庞淇丹, 崔玮, 唐涛, 姜德春, 李深. 检测脑缺血再灌注损伤的探针及技术进展[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(02): 149-154.
[11]	国家卫生健康委加强脑卒中防治工作减少百万新发残疾工程专家委员会, 吉训明. 国家脑卒中防治与百万减残工程工作进展[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(01): 1-5.
[12]	张丽华, 张炜, 薛海丽, 朱向阳. 脑心健康管理师主导的认知行为疗法对脑卒中后焦虑、抑郁的影响[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(01): 19-24.
[13]	马一茁, 胡叶文. 脑卒中患者营养风险筛查与评估工具的研究进展[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(01): 54-57.
[14]	游洪, 乔杉, 张宇. 脑卒中患者居家延续护理模式的研究新进展[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(01): 63-67.
[15]	李芳, 郭廷昊, 程峙娟, 涂江龙. 卒中后检测到的心房颤动研究进展[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(01): 68-73.

阅读次数

全文

摘要

选择文件类型/文献管理软件名称

选择包含的内容

Analysis of retinal vascular fractal dimension in glaucoma and stroke

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

Analysis of retinal vascular fractal dimension in glaucoma and stroke