INTRODUCTION

 

Cerebral small vessel disease (SVD) is a group of clinical, neuroimaging, and pathological processes with various etiologies that affect the small arteries and capillaries of the brain.¹ Hypertension-related cerebral small vessel diseases and cerebral amyloid angiopathy are the most common forms. It has been postulated that cerebral microvascular disease contributes to vascular dementia and vascular cognitive impairment. ¹ Most of the published studies assessed  cerebral small vessel disease associated with vascular dementia, ,on the contrary, few studies assessed the cerebral small vessel disease associated with vascular cognitive impairment.³   It is estimated that older adults with small vessel disease develop vascular dementia between 5 and 25 times more than age-matched individuals.² The pattern of cognitive impairment found in cerebral SVD differs from that found in Alzheimer’s disease where deficits of episodic memory, which is the hallmark of Alzheimer’s disease, are often mild or even  absent in SVD associated cognitive impairment.⁴ Cognitive changes from cerebral small vessel disease (SVD)

generally include impairment of attention and working memory, executive functions, processing speed, and memory performance i.e., primarily encoding and retrieval rather than retention. ^5,6,7,8,9, Most established brief cognitive assessment tools, such as the mini-mental state examination (MMSE), ¹⁰ have been developed in the context of Alzheimer’s disease. These tools are  insensitive  even to the gross impairment of the executive functions.¹¹ The aim of this work is to evaluate the cognitive functions  in patients with SVD and its correlation with the findings of the brain imaging.

 

SUBJECTS AND METHODS

 

Subjects

This case-control study was conducted on forty Egyptian patients (Group I) whose age ranged between 50-70 years (mean ± SD = 61.43±6.25). They were diagnosed to have small vessel disease clinically and by using brain magnetic resonance imaging (MRI) criteria for lacunar syndromes and diffuse white matter abnormality (Fazekas’ scale)¹². Patients were enrolled from Neurology clinic and Neurology department, Kasr El-Aini Hospital, Cairo University, during the period between January 2013 to March 2014. Ten healthy volunteers matching the patient group in age, sex and educational level were also enrolled as a control group (Group II).  We had included patients with neurological symptoms and signs of lacunar infarction clinical syndromes who were able to read and write, and do simple calculations. We had excluded patients whose age were below 50 years, patients with large vessel disease either by neurological signs or MRI evidence of cortical infarction, patients with an evidence of cardioembolic source, patients presenting with dementia or MMSE scores below 24, patients with an evidence of medical systemic disease that can affect the cognitive function (e.g. hepatic encephalopathy, uremic encephalopathy, septicemia, diabetic coma or hypothyroidism), those with history of chronic drug intake or alcohol consumption that may affect the cognitive function, patients with severe dysphasia, severe hearing or visual impairment affecting ability to complete testing, patients presenting with other causes of small vessel disease like CADASIL, vasculitis,...etc., and those with any medical condition that interfere with MRI.

 

METHODS

 

All patients in group (I) and healthy volunteers in control group (group II) were subjected to thorough neurological assessment and neuropsychological tests including global cognitive functioning and specific cognitive functions tests.

 

Neuropsychometric Assessment

A.     Assessment of global cognitive functioning included:

Mini-Mental State Examination (MMSE) ¹⁰ with total score 30 (patients with score below 24 were excluded from the study) to exclude dementia patients. We also used Addenbrooke's cognitive examination (ACE-R) Final Revised Version A (2005) which includes the MMSE in addition to assessment of the executive function and visuospatial skills with a total score 100, scores above 82 exclude dementia. ¹² We used the translated Arabic version, which is valid for assessment of dementia in Arabic speaking people. ¹³

B.     Assessment of specific cognitive functions included:

a.      Assessment of verbal memory: using Paired Associate Learning Test (PALT) which uses the concept of semantic cueing for assessment of verbal memory¹⁴

b.   Assessment of language skills:

i.       Verbal Fluency (animals) Test (VFT): The semantic subtest has also been shown to be quite effective in measuring executive functioning and language ability. This may be because the subtest seems to require a higher level of thought processes since people have to think of meaning rather than just beginning sounds of words.¹⁵ Scores below 17 indicates concern.

ii.      Token test: The short version used in this study contains 36 commands (scored one if correct and 0 if incorrect). The test is divided into six parts. The score is calculated by assigning 1 point for each item answered completely correct, ranging from zero to 36 points. The cut-off score was 29.
The pieces are arranged in a specific order and the subject must answer exactly as the item requests^.16

c.      Assessment of praxis: We used block design subtest, which is one of the performance Wechsler Adult Intelligence Scales (WAIS) for assessment of visuospatial abilities. The cut off score is 21.¹⁷

d.      Assessment of executive functions:

i.       Trail making: to test for visual attention and task switching. The test consists of two parts : part A to make a trail between 25 circles numbered from 1 to 25 as fast as possible, part B to make a trail between 25 circles numbered from 1 to 13 and alphabetic  from (أ  ) to ( س ). Cut off score more than five minutes.

ii.      Digit symbol tests (DST): The subject is showed numbers from 1-9 and different symbols attached to each number. The subject try to remember them and then to recall in the test. the score scaled on Wechsler Adult Intelligence Scales.¹⁷

All neuropsychological tests were performed in a face -to-face interview in a quite examination room with a break for about ten minutes after Addenbrooke's test and five minutes- break after each test.

C.           Beck Inventory for measuring depression:

It includes screening questions for depression by self-report statements. It is especially useful in assessing depression in patients with neurological disease. ¹⁸

 

 

MRI Brain:

Axial T1-, T2-, and proton density-weighted cerebral MR scans on a 1.5-Tesla SIEMENS scanner were used to assess patients and control. The Fazeka's scale was used which rates periventricular hyperintensities (PVHIs) and diffuse white matter hyperintensities (DWMHIs) on T2/PD-weighted images on a 4-grade scale; Fazekas 0: None or a single punctuate WMH lesion, Fazekas 1: Multiple punctuate lesions, Fazekas 2: Beginning confluency of lesions (bridging), Fazekas 3: Large confluent lesions. ¹⁹

 

Routine Laboratory Tests

Both groups were tested for fasting blood sugar, 2 hours postprandial sugar, complete blood count, estimated sedimentation rate, kidney function test urea, creatinine and uric acid, liver function tests (AST and ALT), serum electrolytes, lipid profile (Cholesterol ,Triglycerides, HDL and LDL).

 

ECG and Trans-thoracic Echocardiography

To exclude arrhythmias.

 

Statistical Methods

Analysis of data was done using SPSS (statistical program for social science version 12) as follows: Description of quantitative variables as mean, S.D. and range, description of qualitative variables as numbers and percentage, Chi-square test was used to compare qualitative variables between groups. Fisher exact test was used instead of Chi-square test when one or more expected cells<5. Spearman correlation coefficient test was used to rank different variables versus each other positively or inversely. Unpaired t-test was used for comparison of quantitative variables between two independent groups in parametric data (S.D.< 50%) mean. Mann Whitney Wilcoxon U test was used instead of unpaired t-test in parametric data. P-value: >0.05 insignificant, < 0.05 significant and < 0.01 highly significant.

 

RESULTS

 

1.                Sample characteristics:

Demographics and vascular risk factors for  both groups are shown in Table 1, As indicated in the Table, all of the participants in group I were diabetic and hypertensive, 28% of them had ECG changes suggestive of IHD while 30% were smokers.

2.                Comparisons of the cognitive functions tests:

Table (2) presents the mean scores (±SD) for the cognitive functions tests for the two groups. As can be seen in Table ​2, the performance of the patient group (group I) was lower than group II in  Addenbrooke test, verbal fluency test, trail making B test, DST, PALT and block design test  and these statistical differences were highly significant (P value <0.01), a statistically significant difference  between the 2 groups was also found in trail making A test (P value <0.05), however, no statistical significant difference was found between the performance of the  two groups as regard the token test (P value > 0.05).

3.        Correlation between age and cognitive functions tests:

Table (3) presents correlation between age and cognitive functions tests for the two groups. There were a highly statistical significant negative correlation between age and the performance of the patients and control groups in Addenbrooke test, trail making test, DST, PALT and block design test (P value <0.01), and statistical significant negative correlation between age and the performance of the patients and control groups in verbal fluency test and block design test (P value <0.05). A statistical significant negative correlation was found  between age and the performance of the patients in token test (P value <0.05). 

4.        Correlation between duration of Fazekas’ scale, duration of diabetes mellitus (DM), duration of hypertension, and cognitive functions tests:

Table (4) presents correlation between Fazekas scale, duration of diabetes mellitus (DM), duration of hypertension, and cognitive functions tests for the patient group. As Table (4) indicates. There  were a  highly statistical significant negative correlation between Fazekas scale and performance of patients at Addenbrooke test, trail making B test, DST and block design test (P value <0.01), a statistically significant negative correlation was also found in verbal fluency test, trail making A test, and PALT (P value <0.05). Such statistically significant negative correlation was not found in token test (P value˃0.05). There were a highly statistical significant negative correlation between duration of DM and performance of patients at trail making B test, DST and block design test (P value <0.01), moreover, a statistically significant negative correlation between duration of DM and performance of patients was found in Addenbrooke test, verbal fluency test, trail making A test, PALT and token test (P value <0.05). There were a highly statistical significant negative correlation between duration of hypertension and performance of patients at block design test, trail making A test, trail making B test and DST (P value <0.01), a statistically significant negative correlation between duration of hypertension and performance of patients was also found in Addenbrooke test, verbal fluency test, PALT and token test (P value <0.05).

 

Table 1. Demographics and vascular risk factors for patients and control groups.

 

	Patients group (Group I)	Control group (Group II)	P-value
Demographic data:           Age (Mean±SD)	61.43±6.25	59.55±5.25	0.12
Sex:   Male	23(57.5%)	6(60%)	-
Female	17(42.5%)	4(40%)	-
Vascular risk factors:
Patients with HTN (n)	40	0	-
Duration of HTN (years)	9.08±4.79	0	-
Patients with DM (n)	40	0	-
Duration of DM (years) (Mean±SD)	7.54±4.43	0
FBS ( mg/dl ) (Mean±SD)	127.95 ±51.56	86.10±6.12	.014
Patients with ECG changes	14 (28%)	0	-
Uric acid (mg/dl) (Mean±SD)	5.68 ±0.66	5.45±0.58	0.312
Cholesterol  (mg/dl ) (Mean±SD)	185.10 ±12.16	168.35±21.85	0.024*
Triglycerides ( mg/dl ) (Mean±SD)	99.7±54.4	127.8±47.4	0.034*
LDL( mg/dl) (Mean±SD)	140±15	117±29	0.044
HDL( mg/dl) (Mean±SD)	55±10.3	45±10.3	0.023*
Smokers (n(%))	12(30%)	4(40%)	-

ECG Electrocardiogram, DM Diabetes mellitus, FBS Fasting blood sugar, HDL High density lipoprotein, HTN hypertension,  LDL Low density lipoprotein

*Significant at P<0.05

 

Table 2. Comparison  of  the scores of  the cognitive functions tests between the  patients and control groups.

 

	Patients group (Group I) Mean ± SD	Control  group (Group II) Mean ± SD	t. test	P. value
Addenbrooke test (ACE-R)	92.23±3.60	98.80±0.92	-5.691	<0.01**
Verbal fluency test (0-14)	19.35±3.78	33.00±2.83	-10.664	<0.01**
Block design test (0-20)	10.43±1.32	15.90±1.20	-11.945	<0.01**
Trail making test part A in seconds	12.53±4.32	10.30±2.00	16.465	<0.05*
Trail making test part B in seconds	63.88±7.46	18.50±3.31	18.675	<0.01**
DST (0-20)	6.75±1.28	8.5±0.7	-4.16	<0.01**
PALT (0-36)	12.13±3.00	20.40±0.70	-8.597	<0.01**
Token  test (0-36)	35.95±0.32	36±0	-0.5	> 0.05

DST Digit symbol tests, PALT Paired association learning test.

*Significant at P<0.05 **Significant at P<0.01

Table 3. Correlation between age and cognitive functions tests.

 

		Age
		Patients group (Group I)	Control  group (Group II)
Addenbrooke's test	r	-.094	0.423
	P. value	< 0.01**	< 0.01**
Verbal fluency test	r	-.269	-0.187
	P. value	< 0.05*	< 0.05*
Block design	r	-.237	-0.182
	P. value	< 0.05*	< 0.05*
Trail making test part A	r	0.499	-.144
	P. value	< 0.01**	< 0.05*
Trail making test part B	r	0.463	0.116
	P. value	< 0.01**	< 0.05*
PALT	r	-0.406	0.236
	P. value	< 0.01**	< 0.01**
DST	r	-0.256	0.291
	P. value	< 0.01**	< 0.01**
Token test	r	-0.222	0.244
	P. value	< 0.05*	> 0.05

DST Digit symbol tests, PALT Paired association learning test.

*Significant at P<0.05 **Significant at P<0.01

 

Table 4. Correlation between MRI Fazekas scale, duration of DM, duration of hypertension, and cognitive functions tests.

 

		MRI Fazekas scale	DM (Years)	HTN (Years)
Addenbrooke's test	r	-.885	-0.057	-0.188
	P. value	< 0.01**	<0.05*	< 0.05*
Verbal fluency test	r	-.665	0.129	-0.231
	P. value	< 0.05*	< 0.05*	< 0.05*
Block design test	r	-.659	0.129	-0.224
	P. value	< 0.01**	< 0.01**	< 0.01**
Trail making test part A	r	.725	0.114	0.509
	P. value	< 0.05*	< 0.05*	< 0.01**
Trail making test part B	r	.818	-0.009	0.457
	P. value	< 0.01**	< 0.01**	< 0.01**
PALT	r	-.465	-0.005	-0.293
	P. value	< 0.05*	< 0.05*	< 0.05*
DST	r	-.527	-0.361	-0.270
	P. value	< 0.01**	< 0.01**	< 0.01**
Token test	r	-.196	0.114	-0.201

DST Digit symbol tests, HTN hypertension, PALT Paired association learning test.

*Significant at P<0.05 **Significant at P<0.01

 

 

DISCUSSION

 

Cerebral small vessel disease (SVD) is a major cause of stroke, age-related cognitive decline, and vascular dementia.²⁰ Most of the published studies focused on vascular dementia (Vad) rather than mild cognitive impairment (MCI) associated with cerebral small vessel disease. The cognitive impairment in SVD associated with lacunes may well be due to damage to cortical–subcortical pathways, disrupting the complex and distributed networks that underpin processes such as executive function and information processing.²¹ On cerebral magnetic resonance imaging (MRI), white matter hyperintensities (WMH) and lacunes, both of which are frequently observed in the elderly, are generally viewed as evidence of small vessel disease. ²²

Our study was aiming at detection of the subtle cognitive impairment associated with SVD in non-demented subjects. we assessed multiple domains of cognition: verbal memory, language skills, praxis and executive function.

We faced some obstacles in using Addenbrooke's Cognitive Examination-Revised 2005 (the English version) because some questions, even with highly educated subjects, were not familiar and inappropriate for Arabic cultures (like the name of the USA president who was assassinated in the 1960's), also in language repetition, naming and reading. So we used the version which was translated to Arabic language in King Khaled University Hospital Neurology section in Riyadh KSA which is valid for assessment of dementia in Arabic speaking people.¹³ The total score of Addenbrooke's Cognitive Examination-Revised in patients group was 92.23±3.6 (mean±SD) while control group was 98.80± 0.92 (mean ± SD) with p-value (0.001). The Arabic version of ACE-R appears to be a reliable tool for the assessment of the cognitive impairment associated with small vessel disease.

Results of our study revealed a statistically significant difference between the patients and control groups in the performance of most of the cognitive function tests. The current findings are going with previous studies that have shown that cognitive impairment is common among SVD patients.^23.24 A highly statistical significant difference was found between the scores of the patients and control subjects in trail making test specially part-B, digit symbol test, and  block design  test. A statistical significant difference was found between the scores of the patients and control subjects in Trail making test part A (P-value < 0.05*). These results signify that executive functions can be affected in non-demented individuals with SVD. The current findings are in concordance with previous studies that have shown that cognitive impairment is common in the SVD patients.^{23.24, 25}

A highly significant statistical difference was found between the scores of the patients and control subjects in verbal fluency test, paired associate learning test (PALT) denoting that verbal memory and language skills are affected as well. This can add to the pattern of cognitive impairment associated with SVD across various studies that found mainly impairment of executive function and information processing speed. ^23.24,25

We also found that the duration of the vascular risk factors of the SVD (hypertension and diabetes mellitus) were negatively correlated with the performance of the patient group in all of the cognitive tests i.e. the longer the duration of hypertension and diabetes mellitus the poorer the cognitive performance. These findings have been supported by other studies that have been designed to assess the magnitude of cognitive dysfunction in diabetes mellitus. ^26,27,28

A similar significant correlation was found between the grade of Fazekas scale, which were negatively correlated, with the performance of the patient group in all of the cognitive testing apart from the token test i.e. patients with higher Fazekas grade had poorer cognitive performance. These results are consistent with the findings of many other studies that assessed the correlation between leukoaraiosis and cognitive decline. ^29,30,31

In conclusion, we found that SVD was associated with poor performance in verbal fluency, language skills and executive functions. However, since this was a cross-sectional study, further prospective studies will be needed to elucidate the association between MRI parameters and vascular cognitive impairment.

 

[Disclosure: Authors report no conflict of interest]

 

REFERENCES

 

1.        Sierra C. Cerebral small vessel disease, cognitive impairment and vascular dementia. Panminerva Med. 2012; 54(3): 179-88.

2.        Mosley TH Jr, Knopman DS, Catellier DJ, Bryan N, Hutchinson RG, Grothues CA, et.al. Cerebral MRI findings and cognitive functioning: the Atherosclerosis Risk in Communities study. 2005; Neurology. 64: 2056–62.

3.        Loeb C, Meyer JS. Vascular dementia: still a debatable entity? J Neurol Sci. 1996;143:31–40.

4.        Lafosse JM, Reed BR, Mungas D, Sterling SB, Wahbeh H, Jagust WJ. Fluency and memory differences between ischemic vascular dementia and Alzheimer’s disease. Neuropsychol. 1997;11:514–22.

5.        Grau-Olivares M, Arboix A. Mild cognitive impairment in stroke patients with ischemic cerebral small-vessel disease: a forerunner of vascular dementia? Expert Rev Neurotherap. 2009; 9:1201–17.

6.        Jokinen H, Kalska H, Ylikoski R, Madureira S, Verdelho A, van der Flier WM, et al. Longitudinal cognitive decline in subcortical ischemic vascular disease–the LADIS Study. Cerebrovasc Dis. 2009; 27: 384–91.

7.        Kramer JH, Reed BR, Mungas D, Weiner MW, Chui HC. Executive dysfunction in subcortical ischaemic vascular disease. J Neurol Neurosurg Psychiatry. 2002;72:217–20.

8.        Lesage SR, Mosley TH, Wong TY, Szklo M, Knopman D, Catellier DJ, et al.  Retinal microvascular abnormalities and cognitive decline: the ARIC 14-year follow-up study. Neurology. 2009;73:862–8.

9.        Prins ND, van Dijk EJ, den Heijer T, Vermeer SE, Jolles J, Koudstaal PJ, Hofman A, et al.  Cerebral small-vessel disease and decline in information processing speed, executive function and memory. Brain. 2005;128:2034–41.

10.     Folstein MF, Folstein SE, McHugh PH. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res.1975;12:189–98.

11.     Lezak DM. The problem of assessing executive functions. Int J Psychiatry.1982;17:281–97.

12.      Mioshi E, Dawson K, Mitchell J, Arnold R, Hodges JR. The Addenbrooke’s Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening. Int J Geriatr Psychiatry.2006;21:1078–85

13.     Al Salman AS. The Saudi Arabian Adaptation of Addenbrooke's cognitive examination –Revised (Arabic ACE-R) 2013; 3:57-80. [Cited 2014 July 13]. Available from: http://theses.gla.ac.uk/4706.

14.     Wechsler D, Stone C. Wechsler Memory Scale. New York: Psychological Corporation; 1973.

15.     Poeck K1, Huber W, Willmes K. Outcome of intensive language treatment in aphasia. J Speech Hear Disord. 1989 Aug;54(3):471-9.

16.     de Paula JJ, Schlottfeldt CG, Moreira L, Cotta M, Bicalho MA, Romano-Silva MA, et al. Psychometric properties of a brief neuropsychological protocol for use in geriatric populations. Rev Psiq Clín. 2010; 37(6):246-50.

17.     Wechsler, D. Manual for the Wechsler Adult Intelligence Scale- Revised. New York: Psychological Corporation; 1981.

18.     Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961; 4: 561-71.

19.      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 (2): 351-6.

20.     Roman GC, Erkinjuntti T, Wallin A, Pantoni L, Chui HC. Subcortical  ischaemic vascular dementia. Lancet Neurol. 2002;1:426–436.

21.     Bressler SL, Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci. 2010;14:277–90.

22.     van Swieten JC, van den Hout JH, van Ketel BA, Hijdra A, Wokke JH, van Gijn J. Periventricular lesions in the white matter on magnetic resonance imaging in the elderly. A morphometric correlation with arteriolosclerosis and dilated perivascular spaces. Brain. 1991; 114: 761–74.

23.     O’Sullivan M, Morris RG, Markus HS. Brief cognitive assessment for patients with cerebral small vessel disease. J Neurol Neurosurg Psychiatry. 2005; 76: 1140.

24.     O'Brien JT, Erkinjuntti T, Reisberg B,Roman G,,Sawada T, Pantoni L, et.al. Vascular cognitive impairment. Lancet Neurol. 2003; 2: 89–98.

25.     Charlton RA, Morris RG, Nitkunan A, Markus HS. The cognitive profiles of CADASIL and sporadic small vessel disease. Neurology 2006; 66: 1523.

26.     Ryan CM, Geckle MO, Orchard TJ. Cognitive efficiency declines over time in adults with type 1 diabetes: effects of micro- and macrovascular complications. Diabetologia. 2003; 46:940–8.

27.     Messier C. Impact of impaired glucose tolerance and type 2 diabetes on cognitive aging. Neurobiol Aging. 2005;26 (1):26–30. 

28.     Brands AM, Kessels RP, Hoogma RP, Henselmans JM, van der Beek Boter JW, et al. Cognitive performance, psychological well-being, and brain magnetic resonance imaging in older patients with type 1 diabetes. Diabetes. 2006; 55:1800–6.

29.     Schmidt R, Petrovic K, Ropele S, Enzinger C, Fazekas F. Progression of leukoaraiosis and cognition. Stroke. 2007;38(9):2619-25.

30.     Schmidt R, Scheltens P, Erkinjuntti T, Pantoni L, Markus HS, Wallin A, et al.  White matter lesion progression: a surrogate endpoint for trials in cerebral small-vessel disease. Neurology. 2004 13;63(1):139-44.

31.     Pavlovic AM, Pekmezovic T, Tomic G, Trajkovic JZ, Sternic N. Baseline predictors of cognitive decline in patients with cerebral small vessel disease. J Alzheimers Dis. 2014  1;42(0):S37-43.