卒中人群脑白质病变的临床特点研究
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摘要
背景：脑白质病变(White Matter Lesions, WML)在卒中人群中的发生与卒中分型的关系目前尚无定论,其导致认知功能下降的具体机制亦未明确；不同部位白质病变的发生机制及临床特点各不相同,阐明缺血性卒中患者不同部位脑白质病变的临床特点及其与认知损害的关系有助于解决以上问题。
目的：本研究旨在寻找缺血性卒中患者不同部位脑白质病变的危险因素、探索白质病变部位与卒中病因分型间的关系；并通过比较不同部位白质高信号评分及胆碱能通路高信号评分(Cholinergic Pathways Hyperintensities Scale, CHIPS)与缺血性卒中患者认知功能得分之间的关系,探索胆碱能通路部位损伤在血管性认知功能障碍中的作用。
方法：(1)本研究纳入427例连续的住院急性缺血性卒中患者,记录其临床危险因素资料,按照改良TOAST(modified Trial of Org 10172 in Acute Stroke Treatment, modified TOAST)分型法对其进行卒中病因分型,分为大动脉粥样硬化性卒中(large-artery atherosclerosis, LAA)组、心源性脑栓塞(cardio embolism, CE)组、小动脉闭塞性卒中(small-artery occlusion, SAO)组、其他原因所致的缺血性卒中(stroke of other determinedetiologies,SOE)组及不明原因的缺血性卒中(stroke of undetermined etiologies, SUE)组；并在磁共振FLAIR(fluid-attenuated inversion recovery)加权上对脑室旁白质和深部白质高信号分别进行Fazekas及Schelten评分,根据Fazekas评分将白质病变程度分为轻或无、中度及重度三组,分别比较不同部位三组间各临床危险因素指标的差异,并将可能的危险因素纳入多因素回归模型进行统计分析；分别比较脑室旁与深部白质病变Fazekas评分在不同改良TOAST分型间的分布情况；并比较改良TOAST各分型间Schelten不同解剖部位得分的分布情况。(2)对61例住院缺血性卒中患者进行CHIPS评分、总体白质高信号Schelten评分,同时使用蒙特利尔认知量表北京版(Montreal Cognition Assessment, MoCA, Beijing Version)对患者进行认知功能评估,并随访第一次检查完成后6个月时的MoCA评分改变情况,分析影像学评分与认知评估间的相关性。
结果：(1)研究纳入427例患者年龄分布为62.99±10.68岁(40-91岁)；对于脑室旁白质病变,该人群的独立危险因素可能为年龄(OR=1.053,p<0.001)、既往卒中史(OR=2.363,p=0.007)、高血压(OR=1.612,p=0.031)；而对于深部白质病变,可能的独立危险因素为年龄(OR=1.053,p<0.001)、既往卒中史(OR=2.244,p=0.010)、高血压(OR=1.554,p=0.048)。改良TOAST各分型间脑室旁白质严重程度存在差异(p=0.032),脑室旁白质Fazekas评分LAA型(1.52±0.81)与SAO型(1.85±0.82)比较有统计学差异(p=0.002),深部白质Fazekas评分LAA型(1.39±0.81)与SAO型(1.59±0.80)比较亦有统计学差异(p=0.039)；在SAO型中脑室旁病变程度重于深部白质者占35.7%,与两部位程度相同或脑室旁较深部白质为轻者比较有显著差异(p=0.012)；在Schelten评分的各解剖部位中,脑室前角部位得分在改良TOAST不同分型间存在差异(p=0.003),且CE(1.25±0.56)与SAO型(1.22±0.62)在该部位损害较LAA型(0.95±0.62)为著(p<0.05)；SAO型额叶部白质损害较LAA型为著(p<0.05)。(2)认知研究共纳入61名研究对象(平均年龄63.98±9.13岁,45-82岁),以MoCA>22为认知功能正常,共有32人存在认知功能障碍(52.5%)。根据Schelten评分划分所得各解剖部位白质得分与MoCA得分进行相关性分析,发现额部脑室旁(r=-0.370,p=0.003)、枕部脑室旁(r=-0.344,p=0.007)、顶叶(r=-0.255,p=0.047)、枕叶白质(r=-0.262,p=0.042)病变程度与MoCA得分呈显著负相关。该群体CHIPS评分与MoCA得分间标准化回归系数B=-0.358,p=0.005,而总体白质评分Schelten评分与MoCA得分间B=-0.324,p=0.011；在视空间与执行功能、命名、注意与抽象分项目中,CHIPS与分项评分存在显著相关性(r=-0.330,p=0.010；r=-0.461,p=0.000；r=-0.390,p=0.002；r=-0.276,p=0.033)；Schelten评分与命名、注意和抽象评分亦存在显著相关性(r=-0.366,p=0.004；r=-0.456,p=0.000；r=-0.330,p=0.009),与视空间与执行功能存在相关性(r=-0.316,p=0.013)。随访27例患者MoCA的分数变化与CHIPS得分呈正相关(r=0.393,p=0.021),其中注意功能变化与CHIPS得分存在一定相关性(r=0.346,p=0.039)而总体白质评分Schelten评分与MoCA变化无明显相关性。
结论：年龄、既往卒中史、高血压病史分别为本研究人群脑室旁和深部脑白质病变的独立危险因素；不同TOAST分型患者脑室旁白质病变程度有显著差异；TOAST分型SAO型患者较LAA患者更易发生脑室旁和深部白质病变；在脑室前角和额叶部位,TOAST分型SAO患者白质病变程度较其他病因者为著。本研究中有白质病变患者较无白质病变患者认知水平受损严重,不同部位白质病变与认知功能受损程度相关性不同(其中额、枕部脑室旁、顶叶、壳核与认知功能得分呈显著负相关),胆碱能通路损伤在白质病变所致血管性认知功能障碍中起作用(基线、6个月随访均得到显著统计学差异)；其作用可能主要影响注意功能。
[Background] The relationship between White Matter Lesions(WML) and Stroke subtypes is remained uncertain in stroke patients, either is the mechanism of WML-related cognition impairment. The etiological and clinical manifestations of periventricular white matter lesions (PVWML) and deep white matter lesions (DWML) are different and so we investigated the clinical manifestation of white matter lesions in different position within stroke patients.
[Objectives] This study aimed to identify the clinical risk factors of WML in different positions and to investigate the relationship between WML position and stroke subtypes within ischemic stroke patients. By comparing both the score of WML in different position and Cholinergic Pathways Hyperintensities Scale(CHIPS) score with the cognition impair-ment of stroke patients, we aim to explore the role of cholinergic pathway lesions in vascular cognition impairment.
[Methods] (1) The clinical data of 427 patients with acute cerebral infarction were ana-lyzed retrospectively. All the patients were devided into five subtype groups according to the modified Trial of Org10172 in Acute Stroke Treatment (TOAST) criteria. The WML extent was assessed on fluid-attenuated inversion recovery (FLAIR) imaging according to Fazekas scale and Schelten scale. All the major risk factors were analyzed among WML groups de-fined by Fazekas scale in different positions and put the candidate risk factors into multire-gression model to determine the independent risk factors of PVWML and DWML. The dis-tribution of Fazekas scores of different positions (PWML/DWML; regions in Schelten scale) were compared among modified TOAST groups.
(2) 61 in-patient, middle-aged and elderly stroke individuals underwent brain MRI and MoCA examinations. The white matter lesion on fluid-attenuated inversion recovery MRI images was scored using the semiquatitative rating scale of Scheltens and CHIPS.27 of them were followed-up in 6 months after the first test.Spearman partial rank correlation coeffi-cients and standardized regression coefficients were calculated between WML scores and MoCA scores.
[Results] (1) The average age of 421 patients were 62.99±10.68 years old ranging from 40 to 91 years old. The possible indenpendent risk factors of PVWML were age(OR=1.053, p<0.001), prior-stroke(OR=2.363, p=0.007) and hypertension(OR=1.612, p=0.031). Age (OR=1.053, p<0.001), prior-stroke(OR=2.244, p=0.010) and hypertension(OR=1.554, p=0.048) were also the possible independent risk factors for DWML. PVWML scores varied among modified TOAST groups(p=0.032). The Fazekas score of PVWML in SAO group ranked higher than LAA group((p=0.002) and that of DWML did the same(p=0.039).Among the regions in Schelten scale, scores in anterior-horn varied among different TOAST groups (p=0.003) and both CE(1.25±0.56) and SAO(1.22±0.62) group ranks higher than LAA (0.95±0.62) group(p<0.05). Scores in frontal lobe ranks higher in SAO group than in LAA (p<0.05). (2) WML burdens of the 61 patients(63.98±9.13,45-82years old) had negative correlation with baseline MoCA scores(p<0.05) and so did CHIPS scores(p<0.05). CHIPS and Schelten scores had negative correlation with visuospatial/executive, naming, attention and abstraction(p<0.05). Scores in anterior and posterior horn, parietal lobe and caudate pu-tamen had significant correlation with MoC A scores(p<0.05). The CHIPS scores of the 27 patients followed-up had positive correlation with decrease of MoC A scores(p<0.05) but not did it in total WML burdens(p<0.05). The decrease in attention had significant relationship with CHIPS scores(p<0.05).
[Conclusion]Age, prior-stroke and hypertension are possible independent risk factors of both PVWML and DWML. PVWML enxent varies among different stroke subtypes while both PVWML and DWML are related to SAO subtype more than the other groups. Choliner-gic pathyway leisons play a possible role in vascular cognitive impairment which was proven in both baseline and follow-up data, especially by affecting attention function.
目的：本研究旨在寻找缺血性卒中患者不同部位脑白质病变的危险因素、探索白质病变部位与卒中病因分型间的关系；并通过比较不同部位白质高信号评分及胆碱能通路高信号评分(Cholinergic Pathways Hyperintensities Scale, CHIPS)与缺血性卒中患者认知功能得分之间的关系,探索胆碱能通路部位损伤在血管性认知功能障碍中的作用。
方法：(1)本研究纳入427例连续的住院急性缺血性卒中患者,记录其临床危险因素资料,按照改良TOAST(modified Trial of Org 10172 in Acute Stroke Treatment, modified TOAST)分型法对其进行卒中病因分型,分为大动脉粥样硬化性卒中(large-artery atherosclerosis, LAA)组、心源性脑栓塞(cardio embolism, CE)组、小动脉闭塞性卒中(small-artery occlusion, SAO)组、其他原因所致的缺血性卒中(stroke of other determinedetiologies,SOE)组及不明原因的缺血性卒中(stroke of undetermined etiologies, SUE)组；并在磁共振FLAIR(fluid-attenuated inversion recovery)加权上对脑室旁白质和深部白质高信号分别进行Fazekas及Schelten评分,根据Fazekas评分将白质病变程度分为轻或无、中度及重度三组,分别比较不同部位三组间各临床危险因素指标的差异,并将可能的危险因素纳入多因素回归模型进行统计分析；分别比较脑室旁与深部白质病变Fazekas评分在不同改良TOAST分型间的分布情况；并比较改良TOAST各分型间Schelten不同解剖部位得分的分布情况。(2)对61例住院缺血性卒中患者进行CHIPS评分、总体白质高信号Schelten评分,同时使用蒙特利尔认知量表北京版(Montreal Cognition Assessment, MoCA, Beijing Version)对患者进行认知功能评估,并随访第一次检查完成后6个月时的MoCA评分改变情况,分析影像学评分与认知评估间的相关性。
结果：(1)研究纳入427例患者年龄分布为62.99±10.68岁(40-91岁)；对于脑室旁白质病变,该人群的独立危险因素可能为年龄(OR=1.053,p<0.001)、既往卒中史(OR=2.363,p=0.007)、高血压(OR=1.612,p=0.031)；而对于深部白质病变,可能的独立危险因素为年龄(OR=1.053,p<0.001)、既往卒中史(OR=2.244,p=0.010)、高血压(OR=1.554,p=0.048)。改良TOAST各分型间脑室旁白质严重程度存在差异(p=0.032),脑室旁白质Fazekas评分LAA型(1.52±0.81)与SAO型(1.85±0.82)比较有统计学差异(p=0.002),深部白质Fazekas评分LAA型(1.39±0.81)与SAO型(1.59±0.80)比较亦有统计学差异(p=0.039)；在SAO型中脑室旁病变程度重于深部白质者占35.7%,与两部位程度相同或脑室旁较深部白质为轻者比较有显著差异(p=0.012)；在Schelten评分的各解剖部位中,脑室前角部位得分在改良TOAST不同分型间存在差异(p=0.003),且CE(1.25±0.56)与SAO型(1.22±0.62)在该部位损害较LAA型(0.95±0.62)为著(p<0.05)；SAO型额叶部白质损害较LAA型为著(p<0.05)。(2)认知研究共纳入61名研究对象(平均年龄63.98±9.13岁,45-82岁),以MoCA>22为认知功能正常,共有32人存在认知功能障碍(52.5%)。根据Schelten评分划分所得各解剖部位白质得分与MoCA得分进行相关性分析,发现额部脑室旁(r=-0.370,p=0.003)、枕部脑室旁(r=-0.344,p=0.007)、顶叶(r=-0.255,p=0.047)、枕叶白质(r=-0.262,p=0.042)病变程度与MoCA得分呈显著负相关。该群体CHIPS评分与MoCA得分间标准化回归系数B=-0.358,p=0.005,而总体白质评分Schelten评分与MoCA得分间B=-0.324,p=0.011；在视空间与执行功能、命名、注意与抽象分项目中,CHIPS与分项评分存在显著相关性(r=-0.330,p=0.010；r=-0.461,p=0.000；r=-0.390,p=0.002；r=-0.276,p=0.033)；Schelten评分与命名、注意和抽象评分亦存在显著相关性(r=-0.366,p=0.004；r=-0.456,p=0.000；r=-0.330,p=0.009),与视空间与执行功能存在相关性(r=-0.316,p=0.013)。随访27例患者MoCA的分数变化与CHIPS得分呈正相关(r=0.393,p=0.021),其中注意功能变化与CHIPS得分存在一定相关性(r=0.346,p=0.039)而总体白质评分Schelten评分与MoCA变化无明显相关性。
结论：年龄、既往卒中史、高血压病史分别为本研究人群脑室旁和深部脑白质病变的独立危险因素；不同TOAST分型患者脑室旁白质病变程度有显著差异；TOAST分型SAO型患者较LAA患者更易发生脑室旁和深部白质病变；在脑室前角和额叶部位,TOAST分型SAO患者白质病变程度较其他病因者为著。本研究中有白质病变患者较无白质病变患者认知水平受损严重,不同部位白质病变与认知功能受损程度相关性不同(其中额、枕部脑室旁、顶叶、壳核与认知功能得分呈显著负相关),胆碱能通路损伤在白质病变所致血管性认知功能障碍中起作用(基线、6个月随访均得到显著统计学差异)；其作用可能主要影响注意功能。
[Background] The relationship between White Matter Lesions(WML) and Stroke subtypes is remained uncertain in stroke patients, either is the mechanism of WML-related cognition impairment. The etiological and clinical manifestations of periventricular white matter lesions (PVWML) and deep white matter lesions (DWML) are different and so we investigated the clinical manifestation of white matter lesions in different position within stroke patients.
[Objectives] This study aimed to identify the clinical risk factors of WML in different positions and to investigate the relationship between WML position and stroke subtypes within ischemic stroke patients. By comparing both the score of WML in different position and Cholinergic Pathways Hyperintensities Scale(CHIPS) score with the cognition impair-ment of stroke patients, we aim to explore the role of cholinergic pathway lesions in vascular cognition impairment.
[Methods] (1) The clinical data of 427 patients with acute cerebral infarction were ana-lyzed retrospectively. All the patients were devided into five subtype groups according to the modified Trial of Org10172 in Acute Stroke Treatment (TOAST) criteria. The WML extent was assessed on fluid-attenuated inversion recovery (FLAIR) imaging according to Fazekas scale and Schelten scale. All the major risk factors were analyzed among WML groups de-fined by Fazekas scale in different positions and put the candidate risk factors into multire-gression model to determine the independent risk factors of PVWML and DWML. The dis-tribution of Fazekas scores of different positions (PWML/DWML; regions in Schelten scale) were compared among modified TOAST groups.
(2) 61 in-patient, middle-aged and elderly stroke individuals underwent brain MRI and MoCA examinations. The white matter lesion on fluid-attenuated inversion recovery MRI images was scored using the semiquatitative rating scale of Scheltens and CHIPS.27 of them were followed-up in 6 months after the first test.Spearman partial rank correlation coeffi-cients and standardized regression coefficients were calculated between WML scores and MoCA scores.
[Results] (1) The average age of 421 patients were 62.99±10.68 years old ranging from 40 to 91 years old. The possible indenpendent risk factors of PVWML were age(OR=1.053, p<0.001), prior-stroke(OR=2.363, p=0.007) and hypertension(OR=1.612, p=0.031). Age (OR=1.053, p<0.001), prior-stroke(OR=2.244, p=0.010) and hypertension(OR=1.554, p=0.048) were also the possible independent risk factors for DWML. PVWML scores varied among modified TOAST groups(p=0.032). The Fazekas score of PVWML in SAO group ranked higher than LAA group((p=0.002) and that of DWML did the same(p=0.039).Among the regions in Schelten scale, scores in anterior-horn varied among different TOAST groups (p=0.003) and both CE(1.25±0.56) and SAO(1.22±0.62) group ranks higher than LAA (0.95±0.62) group(p<0.05). Scores in frontal lobe ranks higher in SAO group than in LAA (p<0.05). (2) WML burdens of the 61 patients(63.98±9.13,45-82years old) had negative correlation with baseline MoCA scores(p<0.05) and so did CHIPS scores(p<0.05). CHIPS and Schelten scores had negative correlation with visuospatial/executive, naming, attention and abstraction(p<0.05). Scores in anterior and posterior horn, parietal lobe and caudate pu-tamen had significant correlation with MoC A scores(p<0.05). The CHIPS scores of the 27 patients followed-up had positive correlation with decrease of MoC A scores(p<0.05) but not did it in total WML burdens(p<0.05). The decrease in attention had significant relationship with CHIPS scores(p<0.05).
[Conclusion]Age, prior-stroke and hypertension are possible independent risk factors of both PVWML and DWML. PVWML enxent varies among different stroke subtypes while both PVWML and DWML are related to SAO subtype more than the other groups. Choliner-gic pathyway leisons play a possible role in vascular cognitive impairment which was proven in both baseline and follow-up data, especially by affecting attention function.
引文
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[36]Z..Nasreddine MD Version Novenmber 7,2004. Beijing Version 26 August,2006 translated by Wei Wang & Hengge Xie. www.mocatest.org.
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[20]Lee LJ, Kidwell CS, Alger J, et al. Impact on stroke subtype diagnosis of early diffusion-weighted magnetic resonance imaging and magnetic resonance angiography[J]. Stroke,2000,31:1081-1089.
[21]Fazekas F, Chawluk JB, Alavi A, et al. MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging[J]. AJR Am J Roentgenol,1987,149:351-356.
[22]Scheltens P, Barkhof F, Leys D, et al. A semiquantitive rating scale for the assessment of signal hyperintensities on magnetic resonance imaging[J]. J Neurol Sci,1993,114:7-12.
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[25]Lazarus R, Prettyman R, Cherryman G.White matter lesions on magnetic reso-nance imaging and their relationship with vascular risk factors inmemory clinic atten-ders[J]. Int J Geriatr Psychiatry,2005,20:274-279.
[26]De LeeuwFE, de Groot JC, BotsML,et al. Carotid atherosclerosis and cerebral white matter lesions in a population based magnetic resonance imaging study[J]. J Neurol,2000,247:291-296.
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[29]Fassbender K, Mielke O, Bertsch T, et al. Homocysteine in cerebral macroangio-graphy and microangiopathy[J]. Lancet,1999,353:1586-1587.
[30]Sachdev P, Parslow R, Salonikas C, et al.Homocysteine and the brain inmidadult life: Evidence for an increased risk of leukoaraiosis inmen[J]. Arch Neurol,2004,61:1369-1376.
[31]Hogervorst E, Ribeiro HM, Molyneux A,et al. Plasma homocysteine levels, cerebrovascular risk factors, and cerebral white matter changes (leukoaraiosis) in patients with Alzheimer disease[J]. Arch Neurol,2002,59:787-793.
[32]Hoth KF, Tate DF, Poppas A, et al. Endothelial function and white matter hyper-intensities in older adults with cardiovascular disease[J]. Stroke.,2007,38:308-312.
[33]Manolio TA, Burke GL,O'Leary DH,et al. Relationships of cerebral MRI findings to ultrasonographic carotid atherosclerosis in older adults:the Cardiovascular Health Study[J]. Arterioscler Thromb Vasc Biol,1999,19:356-365.
[34]Anna Kearney-Schwartz, Patrick Rossignol, et al.Vascular Structure and Function Is Correlated to Cognitive Performance and White Matter Hyperintensities in Older Hypertensive Patients With Subjective Memory Complaints[J]. Stroke,2009,40:1229-1236.
[35]Bohnen NI, Mu¨ller M.L.T.M.,Kuwabara H, et al. Age-associated leukoaraiosis and cortical cholinergic deafferentation[J]. Neurology,2009,72:1411-1416.
[36]Z..Nasreddine MD Version Novenmber 7,2004. Beijing Version 26 August,2006 translated by Wei Wang & Hengge Xie. www.mocatest.org.
[37]Guo QH, Cao XY, Zhou Y, et al. Application study of quick cohnitive screening test in identifying mild cognitive impairment[J]. Neurosci Bull,2010,26(1):47-57.
[38]Prins ND, vanDijk EJ, den Heijer T,et al. Cerebralwhitematter lesions and the risk of dementia[J].Arch Neurol,2004,61:1531-1534.
[39]O'Brien J, Desmond P, Ames D, et al. A magnetic resonance imaging study of white matter lesions in depression and Alzheimer's disease[J]. Br J Psychiatry,1996,168:477-485.
[40]Bracco L, Piccini C, Moretti M, et al. Alzheimer's disease:Role of size and location of white matter changes in determining cognitive deficits[J]. Dement Geriatr Cogn Disord,2005,20:358-366.
[41]De Groot JC, de LeeuwFE,OudkerkM,et al.Cerebral white matter lesions and cognitive function:The RotterdamScan Study[J]. Ann Neurol,2000,47:145-151.
[42]Prins ND, vanDijk EJ, den Heijer T, et al. Cerebralwhitematter lesions and the risk of dementia[J]. Arch Neurol,2004,61:1531-1534.
[43]De Groot JC, De Leeuw FE, Oudkerk M, et al. Periventricular cerebral white matter lesions predict rate of cognitive decline[J]. Ann Neurol,2002,52:335-341.
[44]De Leeuw FE, Korf E, Barkhof F, Scheltens P. Whitematter lesions are associated with progression of medial temporal lobe atrophy in Alzheimer disease[J]. Stroke,2006,37:2248-2252.
[45]De Groot JC, de Leeuw FE, Oudkerk M, et al. Cerebral white matter lesions and depressive symptoms in elderly adults[J]. Arch Gen Psychiatry,2000,57:1071-1076.
[46]Krishnan MS, O'Brien JT, Firbank MJ, et al. Relationship between periven-tricular and deep white matter lesions and depressive symptoms in older people. The LADIS Study[J]. Int J Geriatr Psychiatry,2006,21:983-989.
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[50]Fukui T,Hieda S,Bocti C. Do Lesions Involving the Cortical Cholinergic Path-ways Help or Hinder Efficacy of Donepezil in Patients with Alzheimer's Disease? [J]. Dement Geriatr Cogn Disord,2006,22:421-431.
[51]郭起浩,金丽琳,付建辉等.不同类型的血管性认知功能损害的执行功能障碍[J].中华神经科杂志,2009,42：314-318.
[52]Perry RJ, Hodges JR. Attention and executive deficits in Alzheimer's disease:a critical review[J]. Brain,1999,122:383-404.
[53]Swartz RH, Sahlas DJ, Black SE. Strategic involvement of cholinergic pathways and executive dysfunction[J]. J Stroke Cerebrovasc Dis,2003,12:29-36.
[54]Nordahl CW, Ranganath C, Yonelinas AP, et al. White matter changes compromise prefrontal cortex function in healthy elderly individuals[J]. J Cogn Neurosci,2006, 18:418-429.
[55]van Straaten EC, Scheltens P, Knol DL, et al. Operational definitions for the NINDS-AIREN criteria for vascular dementia[J]. Stroke,2003,34:1907-1912.
[1]Hachinski VC, Potter P, Merskey H. Leukoaraiosis[J]. Arch Neurol,1987,44(1):21- 23.
[2]Marko Inzitari, Stephenie Studensky, Caterina Rosano. Anemia Is Associated with the Progression of White Matter Disease in Older Adults with High Blood Pressure:The Cardiovascular Health Study[J].J AmGeriatr Soc,2008,56:1867-1872.
[3]Markus HS, Lythgoe DJ, Ostegaard L, O'Sullivan M, et al. Reduced white matter CBF in ischaemic leukoaraiosis demonstrated using quantitative exogenous contrast based perfusion MRI.[J].J Neurol Psychiat Neurosurg,69,48-53.
[4]Terborg C,Gora F,Weiller C, et al..Reduced vasomotor reactivity in cerebral microangiopathy:a study with nearinfrared spectroscopy and transcranial Doppler sonography[J]. Stroke,31,924-929.
[5]Cupini LM, DiomediM, Placidi F, et al. Cerebrovascular reactivityand subcortical infarctions[J]. Arch Neurol,2001,58:577-581.
[6]Kuwabara Y, Ichiya Y, SasakiM, et al. Cerebral blood flow and vascular response to hypercapnia in hypertensive patientswith leukoaraiosis[J]. Ann NuclMed,1996,10:293-298.
[7]Fu JH, Lu CZ, Hong Z, Dong Q, Ding D, Wong KS.Relationship between cerebral vasomotor reactivity and white matter lesions in elderly subjects without large artery occlusive disease[J].J Neuroimaging,2006,16:120-125.
[8]O'Sullivan M, Lythgoe DJ, Pereira AC, et al. Patterns of cerebral blood flow reduction in patients with ischemic leukoaraiosis[J]. Neurology,2002,59:321-6.
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