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Stroke. 2000;31:2182-2188

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(Stroke. 2000;31:2182.)
© 2000 American Heart Association, Inc.

Original Contributions

Impact of White Matter Changes on Clinical Manifestation of Alzheimer’s Disease

A Quantitative Study

Nobutsugu Hirono, MD; Hajime Kitagaki, MD; Hiroaki Kazui, MD; Mamoru Hashimoto, MD Etsuro Mori, MD

From the Divisions of Clinical Neurosciences (N.H., H. Kazui, M.H., E.M.) and Neuroimaging Research (H. Kitagaki), Hyogo Institute for Aging Brain and Cognitive Disorders, Himeji, Japan.

Correspondence to Dr Nobutsugu Hirono, Division of Clinical Neuroscience, Hyogo Institute for Aging Brain and Cognitive Disorders, 520 Saisho-ko, Himeji 670-0981, Japan. E-mail hirono{at}hiabcd.go.jp


*    Abstract
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 *Abstract
down arrowIntroduction
 down arrowSubjects and Methods
 down arrowResults
 down arrowDiscussion
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Background and Purpose—There have been conflicting results involving the clinical significance of white matter changes in patients with Alzheimer’s disease (AD). We studied the association between the volume of white matter hyperintensities (WMHs) on T2-weighted images and cognitive, neurological, and neuropsychiatric symptoms.

Methods—The subjects were 76 AD patients who had WMHs but no obvious cerebrovascular diseases. We quantified the volume of WMHs by using fast-fluid–attenuated inversion recovery images and whole brain atrophy by using 3D spoiled gradient-echo images. Effects of WMHs and brain atrophy on dementia severity, cognitive function, neuropsychiatric disturbances, and neurological findings were examined.

Results—Whole brain atrophy was significantly associated with dementia severity and cognitive disturbances, as well as with grasp reflex and some kinds of neuropsychiatric disturbances. After we controlled for the effects of brain atrophy, duration of symptoms, and demographic factors, we found that WMH volume was not associated with global cognitive disturbances or dementia severity but was significantly associated with urinary incontinence, grasp reflex, and aberrant motor behaviors. Brain atrophy and WMH volume were not significantly correlated either before or after controlling for age, sex, education, and duration of symptoms. WMH volume was associated with hypertension, but brain atrophy was not positively correlated with any vascular risk factors.

Conclusions—Our results support the hypothesis that WMHs in AD patients are superimposed phenomena of vascular origin. WMHs contribute to specific neurological and neuropsychiatric manifestations but not to global cognitive impairment, which is more closely associated with brain atrophy.


Key Words: Alzheimer disease • atrophy • neurological deficits • risk factors • white matter


*    Introduction
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 up arrowAbstract
 *Introduction
down arrowSubjects and Methods
 down arrowResults
 down arrowDiscussion
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White matter (WM) changes are often found in patients with vascular dementia, especially of small vessel/subcortical subtypes, including Binswanger’s disease, and are generally considered to be a consequence of chronic ischemia associated with microangiopathy.1 2 However, it is also true that the presence of WM changes is not exclusively linked to vascular dementia, because WM changes on neuroimagings are also common in patients with Alzheimer’s disease (AD).3 4 5 6 7 8 9 10 Presently, there is a lack of agreement on the effect of WM changes on the development of dementia.

Some studies have shown a significant relationship between WM changes and certain cognitive functions and/or dementia severity,11 12 13 14 15 16 17 whereas others4 10 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 have failed to find any such relationships in patients with AD. Different study populations and the heterogeneity of WM changes may explain the inconsistency among these studies. Selection of AD patients without vascular risk factors and/or neurological signs may result in excluding severe WM changes and ignoring the clinical significance of WM changes. Small subcortical infarcts frequently accompanied by WM changes,1 2 which do not necessarily exclude the diagnosis of AD by the clinical diagnostic criteria, obscure the independent effects of WM changes by affecting the strategic sites causing dementia.24 In some studies, periventricular changes in the form of caps or smooth halos were included, with irregular confluent changes in the deep and periventricular WM. The former changes are apparently of nonischemic origin, whereas the latter changes represent ischemic tissue damage.33 34

In addition, the neuroimaging technique used is an important factor. MRI is more sensitive to WM changes than is CT.35 36 37 38 Although WM changes have been semiquantified with a visual rating scale in most studies, none of these scales have been validated, and the concordance of different scales is insufficient.39 Although MRI quantification of WM changes is desirable, a manual outlining of WM changes12 25 is essentially dependent on visual inspection that may be affected by an arbitrary gray scale used for display and filming. Computer-based thresholding methods for voxel intensities40 41 are preferable. Finally, the effect of brain atrophy has rarely been considered,16 29 although some studies4 13 22 have analyzed the cerebrospinal fluid space. Because diffuse brain atrophy, which is a main gross pathological feature of AD, is an index of neuronal and synaptic loss, brain atrophy should also be taken into consideration in analyzing the impact of WM changes on cognitive function.

In the present study, we examined a purely selected cohort of patients with AD who had WM changes but no obvious cerebrovascular diseases so as to determine the effect of WM changes on cognitive, neurological, and neuropsychiatric symptoms. We quantified the volume of WM hyperintensities (WMHs) and brain atrophy on MRI by means of computer-based techniques. We also tested the hypothesis that WM changes are associated with vascular risk factors but not with brain atrophy.


*    Subjects and Methods
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 up arrowIntroduction
 *Subjects and Methods
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The present study was conducted at the Hyogo Institute for Aging Brain and Cognitive Disorders (HI-ABCD), a research-oriented hospital for dementia

Subjects
All procedures of the present study strictly followed the 1993 Clinical Study Guidelines of the Ethics Committee of HI-ABCD and were approved by the Internal Review Board. After a complete description of all procedures of the present study, written informed consent was obtained from patients or their relatives.

On the basis of the following inclusion/exclusion criteria, 76 AD patients were selected from a consecutive series of 391 patients with dementia who were given a short-term admission for examination to the HI-ABCD infirmary between April 1997 and March 1999. All patients were examined by both neurologists and psychiatrists with standardized medical history inquiries, neurological examinations, routine laboratory tests, electroencephalography, magnetic resonance (MR) images of the brain, and MR angiography of the head and neck. The inclusion criteria were those identified by (1) the Diagnostic and Statistical Manual of Mental Disorders, Third Edition, revised for dementia42 ; (2) the presence of WM changes, which were defined as irregular periventricular, early confluent deep, or confluent deep WMHs on T2-weighted MRI according to Fazekas and colleagues34 43 and our previous report44 ; and (3) the National Institute of Neurological and Communicative Disorders and Stroke, Alzheimer’s Disease and Related Disorders Association, for AD45 when disregarding WM changes.

Although 234 patients fulfilled the inclusion criteria, 158 patients were excluded from the present study in accordance with the exclusion criteria. Excluded were patients (1) with medical illnesses possibly causing cognitive impairment or WM lesions, including demyelinating diseases, thyroid diseases, vitamin deficiencies, and malignant diseases with or without antineoplastic agents (n=23); (2) with focal brain lesions, including lacunar infarcts and hematoma (n=84); (3) with complication of developmental abnormalities, mental diseases, substance abuse, or significant neurological antecedents, such as brain trauma, brain tumor, epilepsy, and inflammatory disease (n=21); (4) with evidence of severe intracranial or cervical arterial occlusive lesions on MR angiography (n=1); and (5) whose informed consent was not obtained (n=29).

The subjects consisted of 64 women and 12 men; the mean±SD age at examination was 75.6±7.1 years, and the mean educational attainment was 8.8±2.0 years. The mean duration of symptoms, determined through an interview with the primary caregiver and defined as the time between the first appearance of symptoms of sufficient severity to interfere with social or occupational functioning and the admission,46 was 30.8±19.4 months. The functional severity was very mild in 7 patients, mild in 41 patients, moderate in 22 patients, and severe in 6 patients, as determined by the Clinical Dementia Rating Scale (CDR).47 No patient had a history of stroke.

Assessment of Vascular Risk Factors and Neurological Disturbances
Hypertension, diabetes mellitus, lipid disorder, smoking habit, drinking habit, and cardiac diseases were evaluated as vascular risk factors. Hypertension was judged as present when either a systolic pressure of >160 mm Hg or a diastolic pressure of >95 mm Hg was demonstrated on repeated examinations or when a history of treatment for hypertension was present. Diagnosis of diabetes mellitus was made when the fasting blood glucose level was >7.770 mmol/L (140 mg/dL) or when a history of treatment for diabetes mellitus was present. Lipid disorder was judged as present when laboratory examination of the serum at presentation showed a total cholesterol level of >5.698 mmol/L (220 mg/dL), a triglyceride level of >1.695 mmol/L (150 mg/dL), or an HDL cholesterol level of <1.036 mmol/L (40 mg/dL) or when a history of treatment was present. Smoking habit was defined as >=1 cigarette/d for >=1 year, and drinking habit was defined as >=30 mL ethanol equivalent per day for >=1 year sometime in life. Cardiac diseases were assumed to be present whenever there was a known history or clinical demonstration of any kind of heart disease, including myocardial infarction, angina pectoris, and arrhythmia.

A careful neurological examination was given to document the presence or absence of hemiparesis, sensory loss, visual field defects, postural instability (gait disturbance and/or pulsion), pyramidal signs (hyperreflexia, spasticity, and/or extensor plantar responses), extrapyramidal signs (resting tremor, bradykinesia, and/or rigidity), pseudobulbar palsy, ataxia, grasp reflexes, and urinary incontinence. No attempt was made to grade the severity of these risk factors or neurological abnormalities.

Assessment of Cognitive Function and Neuropsychiatric Status
We assessed the cognitive function of the patients with the Mini-Mental State Examination,48 Wechsler Adult Intelligence Scale–Revised,49 and Alzheimer’s Disease Assessment Scale–Cognitive Part.50 The 10-word list recall subtest of the Alzheimer’s Disease Assessment Scale was also analyzed separately. The patients’ behavioral changes were assessed semiquantitatively during an interview with the caregiver by using the Neuropsychiatric Inventory (NPI).51 In the NPI, the following 10 behavioral changes in dementia were rated on the basis of the condition of the patients in the previous month before the interview: delusions, hallucinations, depression (dysphoria), anxiety, agitation and aggression, disinhibition, euphoria, irritability and lability, apathy, and aberrant motor activity. According to the criterion-based rating scheme, the severity of each manifestation was classified into 4 grades (from 0 to 3), and the frequency of each manifestation was classified into 5 grades (from 0 to 4). The NPI score (severityxfrequency) was calculated for each manifestation (range of possible scores 0 to 12). All clinical measures were taken with the investigators blinded to the inclusion of subjects in the present study.

MR Acquisition
MR was performed on a 1.5-T superconducting magnet (Signa Advantage, General Electric Medical Systems). Axial double-echo fast-spin echo T2-weighted images (3000/105/2 [repetition time/effective echo time/excitations]), spin-echo T1-weighted images (550/15/2), and fast-fluid–attenuated inversion recovery (FLAIR) images (9002/147/2200/1 [repetition time/effective echo time/inversion time/excitations]) were obtained for 14 locations parallel to the anteroposterior commissure plane with a section thickness of 5 mm and intersection gap of 2.5 mm covering the area from the base of the cerebellum to the vertex. In all acquisitions, the field of view was 200x200 mm, and the matrix size was 256x256. All scans were reviewed by one neuroradiologist without knowledge of the patients’ clinical data. Lacunar infarcts were specified as lesions with diameters of <=15 mm with (1) hyperintensity on T2-weighted images, (2) distinct hypointensity on T1-weighted images, and (3) hyperintensity with central hypointensity on FLAIR images. By use of these criteria, lacunar infarcts can be distinguished from the état cribré or punctuate hyperintensity form of WMHs.52 For measurements of whole brain volume (WBV) and total intracranial volume (TIV), we also obtained coronal, 3D, spoiled gradient-echo images (11.1/2/2 [repetition time/effective echo time/excitations]). The field of view was 220x220 mm, the matrix size was 256x256, contiguous sections were 124x1.5 mm, and the flip angle was 20°. The images were generated perpendicular to the anteroposterior commissural plane, which covers the whole calvarium.

Measurement of Volume of WMHs
We used FLAIR images for quantification of WMH volume. FLAIR is a heavily T2-weighted inversion-recovery technique that nulls fluid, such as cerebroventricular fluid. By use of this technique, subtle periventricular WM lesions can be easily recognized, and their extents can be assessed on a background of cerebrospinal fluid and normal WM. This technique has been reported to be useful for examining WM diseases, such as multiple sclerosis, cerebral infarction, and leukoaraiosis.53 54 The MR data sets of all images were directly transmitted to a personal computer (Power Macintosh 8100/80, Apple) from the MR unit and analyzed by means of the public-domain National Institutes of Health Image version 1.61 program (written by Wayne Rasband and available from the Internet by anonymous ftp from zippy.nimh.nih.gov or on floppy disk from NTIS, 5285 Port Royal Rd, Springfield, VA 22161, part No. PB93-504868) with residential macro programs developed in our institution. To fit a limitation of the software (8-bit voxel value), 12 bits of MR voxel data were converted to 8 bits at a scale factor of 0.5 by the minimum (voxel value 0) and maximum (voxel value 510) levels. Basically, we used a semiautomatic segmentation technique through intensity thresholding, thereby avoiding the observer’s bias. The segmentation thresholding for WMHs was a priori determined to be 3.5 SDs in voxel intensity levels of the normal WM. The outline of WMHs with the surrounding normal WM, gray matter, and cerebroventricular fluid was first traced with a manually driven mouse cursor (FigureDown). The volume of WMHs was obtained by automatically counting the number of voxels that showed signal intensities higher than the threshold within this outline and then by multiplying the number by the voxel size [(200/256)2x7.5= 4.58 mm3]. Because some normal gray matter demonstrated signal intensities higher than the threshold, we carefully excluded these high–signal-intensity gray matter structures as far as possible. Measurements were performed by another investigator blinded to the clinical information. The test-retest reliability for this method was examined with 20 patients, and a high intraclass correlation coefficient was obtained (r=0.969).



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  		Figure 1. Measurement of volume of WMH areas. Original images (top) and processed images (bottom). The volume of WMH areas was obtained by automatic count of the number of voxels of values higher than the threshold (shown in blue) within the regions of interest determined by a manually driven mouse cursor (white line).

Measurement of WBV and TIV
The detailed MRI procedure for obtaining WBV and TIV is described elsewhere.55 In brief, the data sets of all spoiled gradient-echo images were directly transmitted to a graphic workstation (INDIGO II HighImpact, Silicon Graphics) from the MRI unit and were analyzed with 3D MRI-analyzing software developed by Yamato et al.56 The software makes use of a combination of a gray-scale algorithm (a 3D expansion of the region-growing method), an edge-detection algorithm (a 3D expansion of Sobel filtering), and some a priori knowledge. With this software, the whole brain was segmented by detecting the boundary between the cerebrospinal fluid and gray matter, and the calvarium was extracted by detecting the outer surface of the dura mater. WBV and TIV were calculated by multiplying the number of voxels in the extracted regions by the voxel size. The caudal end of the whole brain and calvarium was manually set at the plane intersecting the occipitoatloid junction, which is the only supervised operation required. The appropriateness of the extraction of the whole brain and calvarium was assessed by 2 reviewers who were blinded to the clinical data and who examined on-site 3D reconstruction displays of elective view points and 2D slice images of selected sections. The reliability and validity of this method have been established and are described elsewhere.55 57 The measurements were performed by the same neuroradiologist who reviewed the MR images. To adjust for premorbid brain volume variability, WBV was normalized by dividing it by TIV. A smaller normalized WBV (nWBV) indicates a greater brain atrophy.

Statistical Analysis
We used nonparametric statistics because many variables were not normally distributed. Computation was performed with the SAS program package, release 6.12 (Statistical Analysis Systems). The relationship between vascular risk factors and WMH volume was examined by using partial Spearman rank correlation coefficients, where the effects of age, sex, education, duration of symptoms, and brain atrophy (nWBV) were controlled. Similarly, the relationship between vascular risk factors and brain atrophy (nWBV) were examined while controlling the effects of the confounding variables and WMH volume. The effects of WMH volume and nWBV on neurological signs, cognitive functions, CDR, and the NPI scores were also tested by using partial Spearman rank correlation coefficients; age, sex, duration of symptoms, and education level were entered into the models. The effect of nWBV or WMH volume was also controlled in each analysis. For all analyses, the statistical {alpha} level was set at 0.05.


*    Results
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 up arrowAbstract
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 up arrowSubjects and Methods
 *Results
down arrowDiscussion
 down arrowReferences
 
The mean±SD WMH volume was 38.4±23.3 cm3. The mean WBV was 1009±96 cm3, TIV was 1394±103 cm3, and nWBV was 0.725±0.048. No significant correlation was noted between the volume of WMHs and nWBV before (r=-0.002, P=0.99) or after (r=0.12, P=0.31) controlling for the effects of age, sex, education, and duration of symptoms. The frequencies of risk factors and neurological disturbances and the mean scores of the cognitive tests and NPI are summarized in Table 1Down. None of the patients showed hemiparesis, sensory loss, ataxia, or visual field defects. Because pseudobulbar palsy was seen in only 1 patient, no further analysis of this sign was undertaken.


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  		Table 1. Risk Factors, Neurological Signs, and Scores of Cognitive Tests and NPI

There was a highly significant negative correlation between age and nWBV even after controlling for the effects of the confounding variables and volume of WMHs (Table 2Down). Although the relationship between volume of WMHs and age was significant in a univariate analysis, it did not remain significant after controlling for the effect of the confounding variables and nWBV. Similarly, the relationship between nWBV and the duration of symptoms was significant only before controlling for the effects of the confounding variables and volume of WMHs. Table 3Down describes partial Spearman rank correlation coefficients between the volume of WMHs and the risk factors and between nWBV and the risk factors. WMH volume was positively correlated with hypertension. nWBV was positively correlated with smoking (nWBV was larger in smokers). Table 4Down summarizes the partial Spearman rank correlation coefficients of volume of WMHs and nWBV with neurological disturbances, CDR, cognitive test scores, and NPI scores after controlling for the effects of the confounding variables. The volume of WMHs was significantly correlated with incontinence and grasp reflex and with the NPI aberrant motor behavior scores but not with cognitive test scores or CDR. On the other hand, nWBV was significantly correlated with all cognitive test scores and CDR, with grasp reflex, and with NPI disinhibition and aberrant motor behavior scores.


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  		Table 2. Association of Volume of WMHs and nWBV With Demographic Factors


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  		Table 3. Association of Volume of WMHs and nWBV With Risk Factors


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  		Table 4. Association of volume of WMHs and nWBV With Neurological, Cognitive, and Neurobehavioral Symptoms


*    Discussion
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 up arrowAbstract
 up arrowIntroduction
 up arrowSubjects and Methods
 up arrowResults
 *Discussion
down arrowReferences
 
WM changes, when defined as irregular periventricular hyperintensities, early confluent deep WMHs, and confluent deep WMHs, had a significant relationship with hypertension, as expected. An association between WM changes and high blood pressure or hypertension and/or the other vascular risk factors has been demonstrated in a number of clinical studies,7 13 18 44 and the relationship between these WM changes and ischemic vascular changes has been documented in pathological studies.33 34 On the other hand, we found no significant correlation between brain atrophy and vascular risk factors. Furthermore, brain atrophy was not correlated with WMH volume either with or without controlling for age, sex, education, and the duration of symptoms. Using quantitative MRI, DeCarli et al29 also demonstrated no significant differences either in brain or cerebrospinal fluid volumes between AD patients with and without WMHs. These findings suggest that WM changes and brain atrophy were independent phenomena. Recent studies have demonstrated that AD itself is not involved in forming WMHs.20 58 59 Although WMHs are sometimes reported as being significantly more frequent in AD patients than in control subjects, the increase is attributed to mild periventricular changes of probably nonischemic origin, including caps, halos, and thin lining.5 7 9 10 Moreover, Scheltens et al6 reported that compared with WMH in control subjects, WMH was more intense in patients with senile onset AD but not in patients with presenile onset AD and suggested that additional microvascular factors are involved in elderly patients with senile onset AD. Together with those findings in the recent studies, our results suggests that WM changes in AD patients, when they are defined as irregular periventricular or confluent deep WMHs, are superimposed phenomena of ischemic origin. It is also interesting that our results demonstrated that a smoking habit had a modest but significant protective effect against brain atrophy. Smoking has been reported to prevent AD,60 and our findings might support this hypothesis.

In the present study, WMH volume was not correlated with the severity of dementia, global cognitive impairment, or memory impairment. This finding is compatible with the findings of our previous study,61 in which we demonstrated that WMHs were associated with decreased cerebral blood flow but not with decreased oxygen metabolism in patients with AD. Brain atrophy, but not reduced cerebral blood flow, was significantly associated with cognitive impairments. These findings suggest that the cognitive impairment in our patients is not attributable to WM changes but to brain atrophy, although WM changes are reported to impair some cognitive functions that were not evaluated in the present study.11 WMHs associated with more severe small-vessel diseases might affect cognitive functions in patients with AD. Snowdon et al62 reported that in subjects with pathological evidence of AD, those lacunar infarcts in the basal ganglia, thalamus, or deep white matter had poorer cognitive function and a higher prevalence of dementia than those without infarcts. However, even in patients who were diagnosed as having vascular dementia, the association between WM changes and global cognitive impairment is unconvincing.10 11 22 25 63 64 65 66 Although Binswanger’s disease reportedly causes dementia without a cortical degenerative process, the pathological features of this disorder include not only WM changes but also lacunar infarcts in the basal ganglia and thalamus.1 2 Coexistent lacunar infarcts may affect the strategic sites, causing dementia.67 Inzitari et al68 pointed out that a strong association between WM changes and dementia was an epiphenomenon that could be explained by a history of stroke. In a longitudinal study of patients with lacunar infarcts, Loeb et al69 found that the development of dementia was significantly associated with cerebral atrophy and new focal cerebrovascular episodes but not with WM changes. These findings, together with those in the present study, suggest that cognitive impairment, both in AD and vascular dementia, is not principally attributable to WM changes.

On the other hand, the present study clearly demonstrated that WM changes and brain atrophy were independently associated with certain neurological and neurobehavioral signs. Urinary incontinence, grasp reflexes, and aberrant motor behaviors were significantly correlated with WMH volume even after controlling for brain atrophy, although the latter 2 were also correlated with brain atrophy after controlling for WMH volume. Urinary incontinence is considered to be one of the central clinical features of Binswanger’s disease,1 2 and an involvement of WM changes in its development has been shown in previous studies.23 24 Primitive reflexes have also been reported to be associated with WM changes in elderly people70 71 and in patients with dementia.72 Positive associations between WM changes and psychiatric symptoms have been reported in subjects without dementia.73 74 Although previous studies have failed to find a relationship between WM changes and neurobehavioral signs in patients with dementia,14 21 28 30 the present study clearly demonstrated that WM changes were involved in the development of aberrant motor behaviors. Aberrant motor behaviors, including wandering, pacing, and rummaging, belong to repetitive and excessive behaviors, which are likely to be caused by frontal lobe dysfunction. Our findings indicate that WM changes would at least add frontal lobe–related neurological and neurobehavioral features as manifestations of dementia.

In conclusion, WM changes in AD patients without any obvious cerebrovascular diseases are related to hypertensive microangiopathy and are independent of brain atrophy that would be attributable to a degenerative process. WM changes contribute to the development of some frontal lobe–related neurological and neurobehavioral signs but not to the development of a global cognitive impairment, which is more closely associated with brain atrophy. Further studies are needed to generalize our findings to include AD patients with more severe vascular disease.


*    Acknowledgments
 
We thank Satoshi Tanimukai, MD, Tokiji Hanihara, MD, Toru Imamura, MD (Division of Clinical Neurosciences), Mieko Matsui, MD, Setsu Sakamoto, MD, and Kazunari Ishii, MD (Division of Neuroimaging Research) for their help with various parts of the study.

Received May 5, 2000; revision received June 16, 2000; accepted June 16, 2000.


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 up arrowSubjects and Methods
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 *References
 

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