Published online before print August 7, 2008, doi: 10.1161/STROKEAHA.108.516112
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Stroke. 2008;39:3323.)
© 2008 American Heart Association, Inc.
Original Contributions |
Brain Microbleeds and Global Cognitive Function in Adults Without Neurological Disorder
From the Division of Neurology, Department of Internal Medicine (Y.Y., M.E., Y.N., K.Y.), Department of Radiology (A.U.), Department of Preventive Medicine (M.H.), and Center for Comprehensive Community Medicine (E.H.), Faculty of Medicine, Saga University, Saga, Japan; and Yuai-Kai Oda Hospital (M.N, S.Y., T.H., J.N.), Kashima, Saga, Japan.
Correspondence to Yusuke Yakushiji, Division of Neurology, Department of Internal Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan. E-mail yakushij{at}cc.saga-u.ac.jp
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background and Purpose— Increasing attention has been paid to associations between cognitive dysfunction and brain microbleeds (MBs). Because all previous studies have investigated patients with neurological disorders, we examined subjects without neurological disorder in order to clarify pathogenic relationships.
Methods— A total of 518 consecutive adults without neurological disorder who had undergone health-screening tests of the brain were studied prospectively. Gradient-echo T2*-weighted MRI using a 1.5-T system was used to detect MBs. The Mini-Mental State Examination (MMSE) was administered to determine cognitive functions. MMSE scores <27 or >1.5 SDs below the age-related mean were regarded as subnormal.
Results— MBs were found in 35 subjects (6.8%). MMSE score <27 was found in 25 subjects (4.8%), with MMSE score >1.5 SDs below the age-related mean in 34 subjects (6.6%). Univariate analysis showed presence and number of MBs, short duration of education, and severe white matter hyperintensities as significantly associated with subnormal scores. In logistic regression analysis, presence of MBs (odds ratio [OR], 5.44; 95% CI, 1.83 to 16.19) and number of MBs (OR, 1.32; 95% CI, 1.04 to 1.68) still displayed significant associations with MMSE score <27. Logistic regression analysis revealed a significant relationship between presence (OR, 3.93; 95% CI, 1.44 to 10.74) and number (OR, 1.26; 95% CI, 1.01 to 1.59) of MBs and MMSE score >1.5 SDs below the age-related mean. Among MMSE subscores, "attention and calculation" was significantly lower in MB-positive subjects (P=0.017).
Conclusions— MBs appear to be primarily associated with global cognitive dysfunction.
Key Words: brain microbleeds • small-vessel diseases • magnetic resonance imaging • cognitive dysfunction • Mini-Mental State Examination
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Vascular dementia is the most common cause of age-related dementia and is preventable. Small-vessel disease (SVDs), particularly of an ischemic nature, is generally accepted as a major risk factor for vascular dementia.1–3 Increasing attention has been paid to associations between cognitive dysfunction and brain microbleeds (MBs) on gradient-echo T2*-weighted MRI (GE-MRI).4 MBs, which are characterized histologically by the presence of hemosiderin around small vessels,5,6 display several presentations, mainly as hypertensive arteriopathy or amyloid angiopathy.5 Strong associations are considered to exist between MBs and SVDs (such as leukoaraiosis and a lacunar state), which can themselves cause ischemic or hemorrhagic cerebrovascular damage, due to shared risk factors such as chronic hypertension,7–11 increasing age,12 and ischemic8,13–15 and hemorrhagic stroke.6,10,16–19 MBs are often detected in demented individuals, such as patients with Alzheimer disease,20 cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL),21,22 subcortical vascular dementia,23 or memory loss.24 In patients with lobar intracranial hemorrhage, cognitive decline has been shown to be more severe in subjects with larger numbers of MBs at baseline.18 A hospital-based study also showed an association between MBs and cognitive dysfunction.25 If MBs are primarily involved in cognitive impairment, MBs may also be detected in certain subjects with no history of neurological disorder, but with cognitive impairment.
The present study, therefore, analyzed relationships between MBs and global cognitive function in a sample of independently living adults without neurological disorder.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Subjects
A total of 678 consecutive adults underwent health-screening tests of the brain in our center at their own expense between December 2005 and November 2007. The same system of health-screening tests for the brain was described in a previous study.26 These individuals were considered as potential subjects for this study. To be included, subjects had to meet the following criteria: (1) age
30 years; (2) no disability in instrumental activities of daily living; (3) ability to independently make visits for current health-screening tests of the brain; and (4) voluntary provision of written informed consent. Exclusion criteria were: (1) inability to undergo cerebral MRI; (2) history of neurological disorder or brain injury; and (3) abnormality in neurological examination. All protocols were approved by the institutional review board. Of the initial 678 potential subjects, 112 individuals refused to enroll and 5 had a history of neurological disorder or brain injury. Among the remaining 561 subjects, 4 subjects displayed motion artifacts on MRI and data required for analysis were incomplete in 39 subjects (incomplete MRI, n=32; incomplete MMSE, n=4; incomplete laboratory data, n=3). As a result, we were able to prospectively study 518 subjects (251 men, 267 women; age, 33 to 85 years).
Baseline Assessment
We recorded age, gender, years of education, past history of ischemic heart diseases, family history of stroke, smoking status, and presence of hypertension, diabetes mellitus and hyperlipidemia as baseline clinical characteristics. Hypertension was defined as systolic blood pressure (SBP) >140 mm Hg and/or diastolic blood pressure >90 mm Hg or use of antihypertensive medication. Diabetes mellitus was defined as fasting serum glucose level 126 mg/dL, hemoglobin A1c levels 6.5% or use of antidiabetic medication. Hyperlipidemia was defined as fasting serum total cholesterol level 220 mg/dL and/or fasting serum triglyceride levels 200 mg/dL and/or use of antihyperlipidemic agents. Patients who were smokers at the time of analysis were classified as current smokers. Past history of ischemic heart disease, family history of stroke, and duration of education were obtained from each subject.
Clinical Assessment
All subjects were at first examined by a general physician. Subjects with suspected neurological deficits or abnormal findings on MRI subsequently underwent neurological examination by a certified neurosurgeon or neurologist.
Assessment of Cognitive Function
Global cognitive function was assessed using the Mini-Mental State Examination (MMSE).27 We defined subnormal MMSE scores by 2 methods. First, according to the latest MMSE guideline,28 total scores <27 were defined as subnormal. Second, MMSE scores >1.5 SDs below the mean for each given age were judged as subnormal. This second method was based on one of the diagnostic criteria used in previous studies of mild cognitive impairment.29
Magnetic Resonance Imaging
MRI was performed using a 1.5-T scanner (EXCELART Vantage, version 7.0; Toshiba Medical Systems). GE-MRI was performed in the axial plane with the following parameters: repetition time (TR), 735 ms; echo time (TE), 20 ms; flip angle (FA), 30°; section thickness, 7 mm; gap width, 1.4 mm; matrix, 224x320; field of view (FOV) 220x220 mm2. Conventional MRI such as axial T1-weighted imaging (T1WI; TR, 550 ms; TE, 15 ms), axial fluid-attenuated inversion recovery (FLAIR) imaging (TR, 10,000 ms; TI, 2500 ms; TE, 96 ms), and axial fast spin-echo T2-weighted imaging (T2WI; TR, 4000 ms; TE, 108 ms) was also obtained using the same section thickness and matrix.
MBs were defined on GE-MRI as rounded areas of signal loss, 2 to 10 mm in diameter. Two investigators (Y.Y., A.U.) who were blinded to subject data reviewed the number and location of MBs. Symmetrical hypointensities in the globus pallidum caused by calcification and flow void artifacts of pial vessels were carefully excluded. White matter hyperintensities (WMH), periventricular hyperintensities (PVH), and lacunae were independently reviewed by 2 of the authors (M.E., Y.N.) who were blinded to subject data. Severity of WMH or PVH on T2WI and FLAIR imaging was rated according to the Fazekas scale (WMH: grade 1, punctuate; grade 2, early confluence; and grade 3, confluent; and PVH: grade 1, caps or lining; grade 2, bands; and grade 3, irregular extension into the deep white matter).30 Grades 2 in the Fazekas scale were regarded as severe WMH or PVH. Lacunae were defined as focal, sharply demarcated lesions >3 mm in diameter showing high intensity on T2WI and low intensity on T1WI.
Each value of inter-rater reliability for MRI findings, expressed as Cohen 
, was within the range of 0.60 to 0.75. Each value of intrarater reliability for MRI findings was determined from 50 randomly selected scans that were scored twice, again expressed as Cohen . Each value was within the range of 0.65 to 0.86.
Using a computer-assisted processing system (Image J version 1.38; National Institutes of Health) and the methods of Koga et al,31 we calculated percentage brain value (%Brain) as an index of cerebral atrophy. Briefly, the area of cerebral parenchyma quantified on T2WI in 2 slices above the pineal body was divided by the area inside the skull at the same level.31
Statistics
Statistical analysis was performed using the Statistical Package for the Social Sciences version 11.0 software (SPSS). To compare baseline characteristics and MRI findings between 2 groups, the 
2 test and Mann–Whitney U test were used as appropriate. Clinical variables with P<0.20 in univariate analysis, in addition to age and gender, were entered into multiple logistic regression analysis for the determination of significant, independent factors contributing to low MMSE score. Comparisons of total MMSE score and subscores between MB-positive and MB-negative groups were also performed. Values of P<0.05 were considered statistically significant.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
MBs were detected in the brain for 35 of 518 subjects (6.8%). Of these 35 subjects, 28 displayed only supratentorial MBs and 4 showed only infratentorial MBs, with 3 subjects exhibiting MBs in both areas. We detected 78 MBs in the cerebrum, 7 in the brain stem and 4 in the cerebellum. In the cerebrum, 19 MBs were located in the basal ganglia, 19 in the thalamus, and 40 in the cortex, subcortex or deep white matter, of which 15 (37.5%) were located in the frontal lobe, 6 (15%) in the parietal lobe, 9 (22.5%) in the temporal lobe, and 10 (25%) in the occipital lobe.
Mean MMSE score was 29.36±1.32 (range, 22 to 30). MMSE scores <27 were found in 25 subjects (4.8%; MMSE score 26, n=11; 25, n=6; 24, n=3; 23, n=4; and 22, n=1). MMSE scores >1.5 SD below the mean for each given age were found in 34 subjects (6.6%; Table 1). Differences in baseline characteristics and MRI findings between subnormal and normal MMSE score groups are shown in Table 2. In both analyses of cognitive function, subnormal MMSE scores were significantly associated with shorter duration of education, presence and number of MBs, and presence of severe WMH (Table 2).
|
|
Because both presence and number of MBs were significantly associated with subnormal MMSE scores on univariate analysis, we then examined whether both factors were independently associated with subnormal MMSE scores. Logistic regression analysis was adjusted for age, male gender, duration of education, SBP and severe WMH. Because a strong correlation existed between SBP and diastolic BP (DBP; Spearman correlation coefficient (r), 0.75) and SBP displayed a lower probability value than DBP, SBP was used for multivariate analysis. As a result, both presence and number of MBs were significantly associated with subnormal MMSE scores (Table 3; comparison by MMSE score <27: presence of MBs (odds ratio [OR]), 5.44; 95% CI, 1.83 to 16.19) and number of MBs (OR, 1.32; 95% CI, 1.04 to 1.68); comparison by MMSE score >1.5 SD below mean for each given age: presence of MBs (OR, 3.93; 95% CI, 1.44 to 10.74) and number of MBs (OR, 1.26; 95% CI, 1.01 to 1.59). Shorter duration of education was significantly associated with subnormal MMSE scores in all logistic regression analyses (Models 1 to 4), but presence of severe WMH was significantly associated with subnormal MMSE scores only in Models 3 and 4.
|
Differences in MMSE total score and subscores between MB-positive (n=35) and MB-negative groups (n=483) are shown in Table 4. In unadjusted analysis, total MMSE score and "attention and calculation" score were lower in the MB-positive group than in the MB-negative group (P=0.015 and P=0.006, respectively). Adjustment for age, gender, duration of education, SBP and severe WMH did not affect the significant association between MB-positive result and low "attention and calculation" score (P=0.017).
|
We also analyzed the relationship between MB locations (basal ganglia, thalamus, and cortex, subcortex or deep white matter) and MMSE score (Table 5). Relationships were analyzed both unadjusted and adjusted by gender, age, duration of education, SBP, and severe WMH. Adjusted analysis revealed that presence of MBs in basal ganglia was associated with reduced "attention and calculation" score (P=0.014), whereas presence of thalamic MBs was independently associated with reduced total (P=0.036) and "orientation" (P=0.012) MMSE score. No significant differences in MMSE scores were seen between subjects with MBs in the cortex, subcortex or deep white matter and subjects without MBs in these areas.
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Presence of MBs is reportedly significantly associated with cognitive dysfunction.23–25 However, subjects in these studies were patients with neurological disorders. We first studied the relationship between MBs and global cognitive function in adults without neurological disorder. All subjects enrolled in this study were living independently with no history of neurological disorder and displayed normal results on neurological examination. Both the presence and number of MBs were found to be significantly associated with subnormal MMSE scores in these subjects. That is, the effect of MBs on global cognitive function appears to be independent of neurological disorders and coexisting clinical risk factors for cerebrovascular disease or cognitive impairment. The mechanisms underlying the pathological association between MBs and cognitive dysfunction remain unclear. However, a histopathologic study on MBs in patients with primary cerebral hemorrhage has shown that the presence of MBs indicated widespread damage of arterioles by hypertension or amyloid deposition, or both.5 The presence of MBs may thus imply much more severe disruption of the neural network between cortical and subcortical structures than ischemic SVDs.
Although the number of subjects with MBs was small, at 35 (6.8%), the incidence of MBs in adults without neurological disorder was compatible with results from previous cohorts with no cerebrovascular disease (4.7 to 7.7%).9,12,32 As for the location, in common with previous studies, MBs were frequently located in the basal ganglia as well as in the frontal, parieto-occipital and temporal lobes. Such characteristic topographical distributions would partially explain our subanalysis data of relationships between MMSE subscores and MB locations. Patients with Parkinson disease and dementia have been shown to display significantly poor performance on "attention and calculation" tasks in the MMSE.33 The prominent attention deficit in these conditions is considered to result from severe dysfunction of cholinergic pathways in the frontal-subcortical circuits.34,35 Predominant occurrence of MBs in the frontal lobe and basal ganglia may thus cause executive dysfunction.25
In addition, thalamic MBs were also frequently found and might also be involved in the development of cognitive dysfunction. The thalamus is considered part of a neuronal network integrally involved in cognitive function.36 Previous neuroimaging studies on patients with CADASIL have shown associations between microstructural alterations in the thalamus and low MMSE score37 and executive dysfunction.38
Hypertension reportedly represents a risk factor for cognitive impairment,39,40 and some reports have shown that lowering blood pressure can reduce the incidence of cognitive impairments.41,42 MBs have been considered as one of the types of organ damage caused by chronic hypertension,43 implying that control of hypertension can reduce both formation of MBs and cognitive dysfunction.
Because our subjects comprised adults who wished to receive health-screening tests of the brain at their own expense, possible selection bias may have existed toward individuals with a relatively high degree of financial affluence or concern for their own health. Such bias might have been influenced by educational background. In addition, we used the MMSE alone as a method to assess cognitive function. The MMSE reportedly offers relatively low sensitivity for the assessment of cognitive function in patients with SVD.44 However, MMSE is used worldwide as a cognitive assessment tool, and we studied a relatively large sample of 518 subjects and assessed cognitive function using 2 methods to lessen the implication of bias.
In conclusion, this study offers the first evidence that MBs are significantly associated with global cognitive dysfunction in adults without neurological disorder, indicating that MBs should be regarded as one of the residual effects of SVD relevant to vascular dementia.
|
Acknowledgments |
|---|
We would like to thank Mitsuko Uematsu, Koji Miyazaki, and Mai Miyamoto, and medical staff of Yuai-Kai Oda Hospital for their help with medical interviews, acquisition of imaging data and data entry.
Sources of Funding
The present study was supported in part by a Grant-in-Aid for University Reform from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
Disclosures
None.
Received February 8, 2008; revision received April 30, 2008; accepted May 28, 2008.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. de Groot JC, de Leeuw FE, Oudkerk M, van Gijn J, Hofman A, Jolles J, Breteler MM. Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study. Ann Neurol. 2000; 47: 145–151.[CrossRef][Medline] [Order article via Infotrieve]
2. van der Flier WM, van Straaten EC, Barkhof F, Verdelho A, Madureira S, Pantoni L, Inzitari D, Erkinjuntti T, Crisby M, Waldemar G, Schmidt R, Fazekas F, Scheltens P. Small vessel disease and general cognitive function in nondisabled elderly: the LADIS study. Stroke. 2005; 36: 2116–2120.
3. Garde E, Mortensen EL, Krabbe K, Rostrup E, Larsson HB. Relation between age-related decline in intelligence and cerebral white-matter hyperintensities in healthy octogenarians: a longitudinal study. Lancet. 2000; 356: 628–634.[CrossRef][Medline] [Order article via Infotrieve]
4. Schneider JA. Brain microbleeds and cognitive function. Stroke. 2007; 38: 1730–1731.
5. Fazekas F, Kleinert R, Roob G, Kleinert G, Kapeller P, Schmidt R, Hartung HP. Histopathologic analysis of foci of signal loss on gradient-echo T2*-weighted MR images in patients with spontaneous intracerebral hemorrhage: evidence of microangiopathy-related microbleeds. AJNR Am J Neuroradiol. 1999; 20: 637–642.
6. Tanaka A, Ueno Y, Nakayama Y, Takano K, Takebayashi S. Small chronic hemorrhages and ischemic lesions in association with spontaneous intracerebral hematomas. Stroke. 1999; 30: 1637–1642.
7. Chan S, Kartha K, Yoon SS, Desmond DW, Hilal SK. Multifocal hypointense cerebral lesions on gradient-echo MR are associated with chronic hypertension. AJNR Am J Neuroradiol. 1996; 17: 1821–1827.[Abstract]
8. Kwa VI, Franke CL, Verbeeten B Jr, Stam J; Amsterdam Vascular Medicine Group. Silent intracerebral microhemorrhages in patients with ischemic stroke. Ann Neurol. 1998; 44: 372–377.[CrossRef][Medline] [Order article via Infotrieve]
9. Roob G, Schmidt R, Kapeller P, Lechner A, Hartung HP, Fazekas F. MRI evidence of past cerebral microbleeds in a healthy elderly population. Neurology. 1999; 52: 991–994.
10. Roob G, Lechner A, Schmidt R, Flooh E, Hartung HP, Fazekas F. Frequency and location of microbleeds in patients with primary intracerebral hemorrhage. Stroke. 2000; 31: 2665–2669.
11. Tsushima Y, Aoki J, Endo K. Brain microhemorrhages detected on T2*-weighted gradient-echo MR images. AJNR Am J Neuroradiol. 2003; 24: 88–96.
12. Jeerakathil T, Wolf PA, Beiser A, Hald JK, Au R, Kase CS, Massaro JM, DeCarli C. Cerebral microbleeds: prevalence and associations with cardiovascular risk factors in the Framingham Study. Stroke. 2004; 35: 1831–1835.
13. Kato H, Izumiyama M, Izumiyama K, Takahashi A, Itoyama Y. Silent cerebral microbleeds on T2*-weighted MRI: correlation with stroke subtype, stroke recurrence, and leukoaraiosis. Stroke. 2002; 33: 1536–1540.
14. Kinoshita T, Okudera T, Tamura H, Ogawa T, Hatazawa J. Assessment of lacunar hemorrhage associated with hypertensive stroke by echo-planar gradient-echo T2*-weighted MRI. Stroke. 2000; 31: 1646–1650.
15. Werring DJ, Coward LJ, Losseff NA, Jager HR, Brown MM. Cerebral microbleeds are common in ischemic stroke but rare in TIA. Neurology. 2005; 65: 1914–1918.
16. Offenbacher H, Fazekas F, Schmidt R, Koch M, Fazekas G, Kapeller P. MR of cerebral abnormalities concomitant with primary intracerebral hematomas. AJNR Am J Neuroradiol. 1996; 17: 573–578.[Abstract]
17. Greenberg SM, Finklestein SP, Schaefer PW. Petechial hemorrhages accompanying lobar hemorrhage: detection by gradient-echo MRI. Neurology. 1996; 46: 1751–1754.
18. Greenberg SM, Eng JA, Ning M, Smith EE, Rosand J. Hemorrhage burden predicts recurrent intracerebral hemorrhage after lobar hemorrhage. Stroke. 2004; 35: 1415–1420.
19. Lee SH, Bae HJ, Kwon SJ, Kim H, Kim YH, Yoon BW, Roh JK. Cerebral microbleeds are regionally associated with intracerebral hemorrhage. Neurology. 2004; 62: 72–76.
20. Hanyu H, Tanaka Y, Shimizu S, Takasaki M, Abe K. Cerebral microbleeds in Alzheimer’s disease. J Neurol. 2003; 250: 1496–1497.[CrossRef][Medline] [Order article via Infotrieve]
21. Lesnik Oberstein SA, van den Boom R, van Buchem MA, van Houwelingen HC, Bakker E, Vollebregt E, Ferrari MD, Breuning MH, Haan J. Cerebral microbleeds in CADASIL. Neurology. 2001; 57: 1066–1070.
22. Dichgans M, Holtmannspotter M, Herzog J, Peters N, Bergmann M, Yousry TA. Cerebral microbleeds in CADASIL: a gradient-echo magnetic resonance imaging and autopsy study. Stroke. 2002; 33: 67–71.
23. Won Seo S, Hwa Lee B, Kim EJ, Chin J, Sun Cho Y, Yoon U, Na DL. Clinical significance of microbleeds in subcortical vascular dementia. Stroke. 2007; 38: 1949–1951.
24. Cordonnier C, van der Flier WM, Sluimer JD, Leys D, Barkhof F, Scheltens P. Prevalence and severity of microbleeds in a memory clinic setting. Neurology. 2006; 66: 1356–1360.
25. Werring DJ, Frazer DW, Coward LJ, Losseff NA, Watt H, Cipolotti L, Brown MM, Jager HR. Cognitive dysfunction in patients with cerebral microbleeds on T2*-weighted gradient-echo MRI. Brain. 2004; 127: 2265–2275.
26. Kobayashi S, Okada K, Koide H, Bokura H, Yamaguchi S. Subcortical silent brain infarction as a risk factor for clinical stroke. Stroke. 1997; 28: 1932–1939.
27. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state": a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12: 189–198.[CrossRef][Medline] [Order article via Infotrieve]
28. Folstein MF, Folstein SE, Fanjiang G. Mini-Mental State Examination Clinical Guide. Lutz, Fla: Psychological Assessment Resources, Inc; 2001.
29. Apostolova LG, Cummings JL. Neuropsychiatric manifestations in mild cognitive impairment: a systematic review of the literature. Dement Geriatr Cogn Disord. 2008; 25: 115–126.[Medline] [Order article via Infotrieve]
30. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol. 1987; 149: 351–356.
31. Koga H, Yuzuriha T, Yao H, Endo K, Hiejima S, Takashima Y, Sadanaga F, Matsumoto T, Uchino A, Ogomori K, Ichimiya A, Uchimura H, Tashiro N. Quantitative MRI findings and cognitive impairment among community dwelling elderly subjects. J Neurol Neurosurg Psychiatry. 2002; 72: 737–741.
32. Horita Y, Imaizumi T, Niwa J, Yoshikawa J, Miyata K, Makabe T, Moriyama R, Kurokawa K, Mikami M, Nakamura M. [Analysis of dot-like hemosiderin spots using brain dock system]. No Shinkei Geka. 2003; 31: 263–267.[Medline] [Order article via Infotrieve]
33. Bronnick K, Emre M, Lane R, Tekin S, Aarsland D. Profile of cognitive impairment in dementia associated with Parkinson’s disease compared with Alzheimer’s disease. J Neurol Neurosurg Psychiatry. 2007; 78: 1064–1068.
34. Bohnen NI, Kaufer DI, Ivanco LS, Lopresti B, Koeppe RA, Davis JG, Mathis CA, Moore RY, DeKosky ST. Cortical cholinergic function is more severely affected in Parkinsonian dementia than in Alzheimer disease: an in vivo positron emission tomographic study. Arch Neurol. 2003; 60: 1745–1748.
35. Bohnen NI, Kaufer DI, Hendrickson R, Ivanco LS, Lopresti BJ, Constantine GM, Mathis Ch A, Davis JG, Moore RY, Dekosky ST. Cognitive correlates of cortical cholinergic denervation in Parkinson’s disease and Parkinsonian dementia. J Neurol. 2006; 253: 242–247.[CrossRef][Medline] [Order article via Infotrieve]
36. Karussis D, Leker RR, Abramsky O. Cognitive dysfunction following thalamic stroke: a study of 16 cases and review of the literature. J Neurol Sci. 2000; 172: 25–29.[CrossRef][Medline] [Order article via Infotrieve]
37. Molko N, Pappata S, Mangin JF, Poupon C, Vahedi K, Jobert A, LeBihan D, Bousser MG, Chabriat H. Diffusion tensor imaging study of subcortical gray matter in cadasil. Stroke. 2001; 32: 2049–2054.
38. O'Sullivan M, Singhal S, Charlton R, Markus HS. Diffusion tensor imaging of thalamus correlates with cognition in CADASIL without dementia. Neurology. 2004; 62: 702–707.
39. Kilander L, Nyman H, Boberg M, Hansson L, Lithell H. Hypertension is related to cognitive impairment: a 20-year follow-up of 999 men. Hypertension. 1998; 31: 780–786.
40. Knopman D, Boland LL, Mosley T, Howard G, Liao D, Szklo M, McGovern P, Folsom AR. Cardiovascular risk factors and cognitive decline in middle-aged adults. Neurology. 2001; 56: 42–48.
41. Forette F, Seux ML, Staessen JA, Thijs L, Birkenhager WH, Babarskiene MR, Babeanu S, Bossini A, Gil-Extremera B, Girerd X, Laks T, Lilov E, Moisseyev V, Tuomilehto J, Vanhanen H, Webster J, Yodfat Y, Fagard R. Prevention of dementia in randomised double-blind placebo-controlled Systolic Hypertension in Europe (Syst-Eur) trial. Lancet. 1998; 352: 1347–1351.[CrossRef][Medline] [Order article via Infotrieve]
42. Forette F, Seux ML, Staessen JA, Thijs L, Babarskiene MR, Babeanu S, Bossini A, Fagard R, Gil-Extremera B, Laks T, Kobalava Z, Sarti C, Tuomilehto J, Vanhanen H, Webster J, Yodfat Y, Birkenhager WH. The prevention of dementia with antihypertensive treatment: new evidence from the Systolic Hypertension in Europe (Syst-Eur) study. Arch Intern Med. 2002; 162: 2046–2052.
43. Lee SH, Park JM, Kwon SJ, Kim H, Kim YH, Roh JK, Yoon BW. Left ventricular hypertrophy is associated with cerebral microbleeds in hypertensive patients. Neurology. 2004; 63: 16–21.
44. O'Sullivan M, Morris RG, Markus HS. Brief cognitive assessment for patients with cerebral small vessel disease. J Neurol Neurosurg Psychiatry. 2005; 76: 1140–1145.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||