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(Stroke. 2001;32:1318.)
© 2001 American Heart Association, Inc.
Original Contributions |
A New Rating Scale for Age-Related White Matter Changes Applicable to MRI and CT
From the Department of Clinical Neuroscience, NEUROTEC (L.O.W.), and Department of Radiology (L.B.), Karolinska Institutet at Huddinge University Hospital, Huddinge, Sweden; Departments of Radiology (F.B., P.S.) and Neurology (P.S.), Research Institute Neurosciences, Academisch Ziekenhuis Vrije Universitet, Amsterdam, the Netherlands; Department of Neurology and MR Center, Karl-Franzens University (F.F. M.A.), Graz, Austria; Institute of Clinical Neuroscience, Section of Psychiatry, Göteborg University (M.S., A.W.), Mölndal, Sweden; Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine, Vrije Universitet (H.A.), Amsterdam, the Netherlands; Service de Neurologie Vasculaire, Hopital Roger Salengro (D.L., F.P.), Lille, France; Department of Neurological and Psychiatric Sciences, University of Florence (L.P.), Florence, Italy; and Memory Research Unit, Department of Clinical Neuroscience, Helsinki University Central Hospital (T.E.), Helsinki, Finland.
Correspondence to L.O. Wahlund, MD, PhD, Department of Clinical Neuroscience, NEUROTEC, B 56, Huddinge University Hospital, S-141 86 Huddinge, Sweden. E-mail lars-olof.wahlund{at}neurotec.ki.se
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Abstract |
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 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
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Background and Purpose—MRI is more sensitive than CT for detection of age-related white matter changes (ARWMC). Most rating scales estimate the degree and distribution of ARWMC either on CT or on MRI, and they differ in many aspects. This makes it difficult to compare CT and MRI studies. To be able to study the evolution and possible effect of drug treatment on ARWMC in large patient samples, it is necessary to have a rating scale constructed for both MRI and CT. We have developed and evaluated a new scale and studied ARWMC in a large number of patients examined with both MRI and CT.
Methods—Seventy-seven
patients with ARWMC on either CT or MRI were recruited and a
complementary examination (MRI or CT) performed. The patients came from
4 centers in Europe, and the scans were rated by 4 raters on 1 occasion
with the new ARWMC rating scale. The interrater reliability was
evaluated by using 
statistics. The degree and distribution of ARWMC
in CT and MRI scans were compared in different brain
areas.
Results—Interrater
reliability was good for MRI (=0.67) and moderate for CT (=0.48).
MRI was superior in detection of small ARWMC, whereas larger lesions
were detected equally well with both CT and MRI. In the
parieto-occipital and infratentorial areas, MRI detected significantly
more ARWMC than did CT. In the frontal area and basal ganglia, no
differences between modalities were found. When a fluid-attenuated
inversion recovery sequence was used, MRI detected significantly more
lesions than CT in frontal and parieto-occipital areas. No differences
were found in basal ganglia and infratentorial
areas.
Conclusions—We present a new ARWMC scale applicable to both CT and MRI that has almost equal sensitivity, except for certain regions. The interrater reliability was slightly better for MRI, as was the detectability of small lesions.
Key Words: dementia • magnetic resonance imaging • rating scales • tomography, x-ray computed • white matter
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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White matter changes (WMC) are defined as areas with high signal intensities on T2-weighted MRI and as areas with low attenuation on CT. The mechanisms for development of WMC are not fully understood, but several histopathologic correlates have been reported. These include enlarged perivascular (Virchow-Robin) spaces, as well as degeneration of myelin and axons with increased intracellular and extracellular water content, gliosis, and even infarction.1 2 3 4 5 6 7 8 9 10
The clinical significance of WMC has not been fully elucidated. There is a relationship between several cerebrovascular risk factors and the presence of WMC. One of the strongest risk factors, apart from hypertension, is that of age.11 12 13 Henceforth, we will designate WMC as "age-related white matter changes" (ARWMC).
There is also evidence for a relationship between ARWMC and cognitive impairment in demented patients14 15 16 as well as in healthy elderly individuals.13 17 18 19 However, the extent of this association is still controversial. Little is known about the natural history of ARWMC, starting from their development to possibly subsequent progression. It is also unclear whether it is possible to affect the evolution of ARWMC with pharmacological treatment and whether this would have any impact on cognitive performance or other tasks that require more complex cerebral processing, such as coordinated movement. The advent of MRI has focused attention on ARWMC due to the conspicuousness of such lesions on proton density (PD) and T2-weighted images, including fluid-attenuated inversion recovery (FLAIR). Also, the high sensitivity of this technique has increasingly brought into question the utility of CT for delineating ARWMC.
Given the possible effect of ARWMC on cognitive function in modern pharmacological antidementia treatment, there is a need for the evaluation of ARWMC. The degree and distribution of ARWMC are important in vascular dementia as well as in other dementia disorders, such as Alzheimer’s disease. CT is less costly and more easily performed than MRI, and in many regions the number of MRI scanners is still limited. Several rating scales exist for visual rating of ARWMC on MRI scans.20 Many of them are validated and widely used. Similarly, there are a number of rating scales for CT.20 At present, there is only a single study in which the authors have attempted to design a scale applicable to both CT and MRI scans.5 However, this scale, as designed by van Swieten, uses different criteria for CT and MRI scans, thus leading to different sensitivities for the respective modalities. It is therefore impossible to compare the results of different studies on ARWMC within and, even more so, between the 2 imaging modalities. By generating a combined CT-MRI ARWMC rating scale, we wanted to provide a tool for such between-modality comparison as well as to have an instrument for comparing the sensitivity for ARWMC and the reliability of their rating between CT and MRI.
Such a scale was developed under the auspices of the European Task Force on Age-Related White Matter Changes. In this study, we compared the regional sensitivity of MRI and CT for ARWMC within the same patient. The interobserver reliability of the new scale in both imaging techniques was also studied.
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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In the ARWMC scale, the degree of white matter changes is rated on a 4-point scale. Ratings were done on CT images by using standard hard copies and on MRI images on computer screen with either PD and T2-weighted images or T2 and FLAIR images. Examples of the different rating scores are shown in Figure 1
.
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White matter changes on MRI were defined as ill-defined
hyperintensities 
5 mm on both T2 and PD/FLAIR images, and on CT
as ill-defined and moderately hypodense areas of 5 mm. Lacunes
were defined as well-defined areas of >2 mm with attenuation (on
CT) or signal characteristics (on MRI) the same as cerebrospinal
fluid. If lesions with these characteristics were 
2 mm,
they were considered perivascular spaces, except around the anterior
commissure, where perivascular spaces can be large.
Changes in the basal ganglia were rated in the same way and
considered white matter lesions even if located in the gray matter
nuclei, which contains a small amount of white matter. The definitions
of rating scores (0–3) are shown in
Table 1.
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Five different regions were rated in the right and left hemispheres separately: (1) the frontal area, which was the frontal lobe anterior to the central sulcus; (2) the parieto-occipital area, which consisted of the parietal and occipital lobes together; (3) the temporal area, which was the temporal lobe (the border between the parieto-occipital and temporal lobes was approximated as a line drawn from the posterior part of the Sylvian fissure to the trigone areas of the lateral ventricles); (4) the infratentorial area, which included the brain stem and cerebellum; and (5) the basal ganglia, which included the striatum, globus pallidus, thalamus, internal and external capsules, and insula.
All ratings were performed on one occasion at Huddinge Hospital. After a training session in which all 4 raters (F.B., L.B., M.A., and M.S.) together rated 10 cases, the raters were divided into pairs. Each pair of raters then evaluated MRI and CT scans from half of the cases. Within each pair, the 2 raters reached consensus. Interrater reliability values were calculated from a further series of rating both MRI and CT images from 20 patients, in which all 4 raters rated individually.
Previously acquired cerebral scans from 77 patients were used in this study. The patients had been examined at either Huddinge (n=20), Amsterdam (n=5), Lille (n=14), or Graz (n=38). They were included if ARWMC was noticed on a routine examination (on either MRI or CT) and when both MRI and CT had been performed no more than 3 months apart. We assume that no major alterations in the degree of white matter changes occurred during this time period. Patients with other gross pathological findings such as tumors, large bleedings, and recent territorial infarctions were excluded. We did not consider the final diagnosis or underlying risk factors in these patients; our only purpose was to compare ARWMC on MRI and CT scans. To simulate routine clinical conditions, we also did not advise a common scanning protocol and we allowed the use of different machinery.
Different CT scanners were used. Slice thicknesses varied from 2.5 to 10 mm. The MRI equipment used operated at 1.0 T or 1.5 T, and T2/PD sequences were used as well as FLAIR. Slice thickness was 5 mm at all centers. All images were transferred to 1 center (Huddinge Hospital) on either digital media or as hard copies. These were then presented to the raters on either computer screen or viewing boxes.
The subsample (n=38) of the study population that was imaged with the FLAIR technique was evaluated separately as well as together with the whole material (n=77).
Statistics
No descriptive data were available to perform power
calculations. Therefore, type II errors could not be excluded for some
comparisons.
The nonparametric sign test was used to compare
visual ratings between MRI and CT. Weighted values were calculated
as a measure of reproducibility: values <0.4 indicated poor
agreement, values from 0.41 through 0.6 indicated moderate agreement,
values from 0.61 through 0.8 indicated good agreement, and values
>0.81 indicated excellent
agreement.21
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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The means and standard deviations of the MRI and CT ratings in each separate area are shown in Table 2
(medians are not shown due to lack of
variability). As expected, most lesions were found in the frontal and
parieto-occipital regions. The distribution of the rating scores
(sum of the right side and left side) according to brain region is
presented in
Figure 2. There was a size-dependent difference
in the distribution of rating scores between MRI and CT. MRI detected
more of the small ARWMC whereas CT was equal or superior in detecting
larger lesions.
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To address the relative detection capacity of each imaging
modality, we compared in a pairwise fashion the MRI and CT and
described them as either (1) MRI and CT scoring equal, (2) MRI scoring
higher than CT, or (3) CT scoring higher than MRI. Few lesions were
detected in the temporal areas, and therefore no comparison was made
between MRI and CT in this region. The data are shown as a percentage
of all rated subjects. As evident from
Table 3, MRI and CT were equal in >50% of all
ratings. However, in the parieto-occipital and infratentorial areas,
MRI rated significantly more ARWMC than did CT. When the MRI ratings
were based on the FLAIR sequence (38 subjects), significantly more
ARWMC were rated in all areas except for the basal ganglia and
infratentorial area. Also in these cases, >50% of all ratings from CT
were equal to MRI (see
Table 4).
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The results of the interrater reliability are
presented in
Table 5. This showed moderate-excellent agreement for
MRI and CT. The highest values were found for the rating of
frontal, parieto-occipital, and basal ganglia areas, whereas the
score was lower for the temporal area as well as for the number of
infarcts. As expected, the infratentorial area was significantly more
reliably rated with MRI than with CT. When ARWMC in all areas were
considered together, good agreement was found for MRI (0.67) and
moderate agreement for CT (0.48). From
Table 5 it is evident that the value was larger for MRI
than CT in all but 1 region. The lack of statistical significance might
be due to type II error.
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|
Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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To be able to assess the degree of ARWMC from both MRI and CT examinations obtained on a clinical, day-to-day basis, we developed a scale that can be applied to MRI and CT alike. This ARWMC scale could also be used in clinical trials with large patient samples, in which drugs affecting brain degenerative processes are tested and both MRI and CT are used for evaluation.
The scale was evaluated by 4 raters and showed good
reliability for both CT and MRI in most regions. As expected, the
reliability was higher for MRI rating than for CT rating. This was
especially true in the frontal and parieto-occipital regions, where
very high values were detected. Furthermore, MRI was significantly
more reliably rated in the parietal/occipital area than CT. This might
be explained by the fact that CT scans were obtained from a variety of
scanners with different slice thickness and image quality.
We found that when using standard T2/PD images, MRI was more sensitive in detecting ARWMC in the parieto-occipital and infratentorial regions of the brain. The latter region is easier to study with MRI than with CT because no bone artifacts are present. Moreover, the differences were mainly due to the ability of MRI to detect small ARWMCs. CT was as good as MRI in detecting larger lesions. This might explain why many studies have shown that ARWMC found on CT correlate better with symptoms than do the changes detected with MRI. When the FLAIR sequence was used for MRI rating, ARWMC were found significantly more often than with CT. This suggests that FLAIR may be preferable for the study of ARWMC. However, this issue will have to be addressed more extensively in a further study.
To summarize, this study shows that differences of MRI and CT in detecting ARWMC are primarily related to lesion size. MRI was superior due to its better detection of small ARWMC, whereas medium and large lesions were detected equally well by both modalities. Regional differences played a subordinate role, which is not unexpected from the predominant location of ARWMC in areas that can usually be imaged with high quality by both MRI and CT. Therefore, CT studies in combination with MRI might be used in evaluation of ARWMC in multicenter studies when attempting to address primarily more marked white matter damage. (This could also be the type of white matter damage that shows closer relation to clinical-cognitive deficits, at least in cross-sectional studies). In this context, the new ARWMC rating scale may be a useful tool that demonstrates good interrater reliability. However, for minor ARWMC, MRI appears mandatory, and it is probably also the technique needed for monitoring ARWMC progression.
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Acknowledgments |
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This study was financially supported by Alzheimerfonden, Lund. We acknowledge Dr Richard Cowburn, research nurse Ulla Swahn, and Dr Leif Svensson for excellent typographic and technical support.
Received October 23, 2000; revision received January 18, 2001; accepted January 19, 2001.
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L. A. van de Pol, W. M. van der Flier, E.S.C. Korf, N. C. Fox, F. Barkhof, and P. Scheltens Baseline predictors of rates of hippocampal atrophy in mild cognitive impairment Neurology, October 9, 2007; 69(15): 1491 - 1497. [Abstract] [Full Text] [PDF]
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C. Cordonnier, R. Al-Shahi Salman, and J. Wardlaw Spontaneous brain microbleeds: systematic review, subgroup analyses and standards for study design and reporting Brain, August 1, 2007; 130(8): 1988 - 2003. [Abstract] [Full Text] [PDF]
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L. A. van de Pol, E. S. C. Korf, W. M. van der Flier, H. R. Brashear, N. C. Fox, F. Barkhof, and P. Scheltens Magnetic Resonance Imaging Predictors of Cognition in Mild Cognitive Impairment Arch Neurol, July 1, 2007; 64(7): 1023 - 1028. [Abstract] [Full Text] [PDF]
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G. B. Frisoni, M. Pievani, C. Testa, F. Sabattoli, L. Bresciani, M. Bonetti, A. Beltramello, K. M. Hayashi, A. W. Toga, and P. M. Thompson The topography of grey matter involvement in early and late onset Alzheimer's disease Brain, March 1, 2007; 130(3): 720 - 730. [Abstract] [Full Text] [PDF]
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P. Behl, C. Bocti, R. H. Swartz, F. Gao, D. J. Sahlas, K. L. Lanctot, D. L. Streiner, and S. E. Black Strategic Subcortical Hyperintensities in Cholinergic Pathways and Executive Function Decline in Treated Alzheimer Patients Arch Neurol, February 1, 2007; 64(2): 266 - 272. [Abstract] [Full Text] [PDF]
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C.R.V. Blain, G. J. Barker, J. M. Jarosz, N. A. Coyle, S. Landau, R. G. Brown, K. R. Chaudhuri, A. Simmons, D. K. Jones, S. C.R. Williams, et al. Measuring brain stem and cerebellar damage in parkinsonian syndromes using diffusion tensor MRI Neurology, December 26, 2006; 67(12): 2199 - 2205. [Abstract] [Full Text] [PDF]
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L. Cabrejo, L. Guyant-Marechal, A. Laquerriere, M. Vercelletto, F. De La Fourniere, C. Thomas-Anterion, C. Verny, F. Letournel, F. Pasquier, A. Vital, et al. Phenotype associated with APP duplication in five families Brain, November 1, 2006; 129(11): 2966 - 2976. [Abstract] [Full Text] [PDF]
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S E Rose, K L McMahon, A L Janke, B O'Dowd, G de Zubicaray, M W Strudwick, and J B Chalk Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment J. Neurol. Neurosurg. Psychiatry, October 1, 2006; 77(10): 1122 - 1128. [Abstract] [Full Text] [PDF]
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V. Stenset, L. Johnsen, D. Kocot, A. Negaard, A. Skinningsrud, P. Gulbrandsen, A. Wallin, and T. Fladby Associations between white matter lesions, cerebrovascular risk factors, and low CSF Abeta42. Neurology, September 12, 2006; 67(5): 830 - 833. [Abstract] [Full Text] [PDF]
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A. J. Saykin, H. A. Wishart, L. A. Rabin, R. B. Santulli, L. A. Flashman, J. D. West, T. L. McHugh, and A. C. Mamourian Older adults with cognitive complaints show brain atrophy similar to that of amnestic MCI. Neurology, September 12, 2006; 67(5): 834 - 842. [Abstract] [Full Text] [PDF]
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V. Hachinski, C. Iadecola, R. C. Petersen, M. M. Breteler, D. L. Nyenhuis, S. E. Black, W. J. Powers, C. DeCarli, J. G. Merino, R. N. Kalaria, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards Stroke, September 1, 2006; 37(9): 2220 - 2241. [Abstract] [Full Text] [PDF]
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V. Novak, D. Last, D. C. Alsop, A. M. Abduljalil, K. Hu, L. Lepicovsky, J. Cavallerano, and L. A. Lipsitz Cerebral Blood Flow Velocity and Periventricular White Matter Hyperintensities in Type 2 Diabetes Diabetes Care, July 1, 2006; 29(7): 1529 - 1534. [Abstract] [Full Text] [PDF]
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M. Silvestrini, P. Pasqualetti, R. Baruffaldi, M. Bartolini, Y. Handouk, M. Matteis, F. Moffa, L. Provinciali, and F. Vernieri Cerebrovascular Reactivity and Cognitive Decline in Patients With Alzheimer Disease Stroke, April 1, 2006; 37(4): 1010 - 1015. [Abstract] [Full Text] [PDF]
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R. Bergamaschi, C. Livieri, C. Uggetti, E. Candeloro, M. G. Egitto, A. Pichiecchio, V. Cosi, and S. Bastianello Brain white matter impairment in congenital adrenal hyperplasia. Arch Neurol, March 1, 2006; 63(3): 413 - 416. [Abstract] [Full Text] [PDF]
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E. C.W. van Straaten, F. Fazekas, E. Rostrup, P. Scheltens, R. Schmidt, L. Pantoni, D. Inzitari, G. Waldemar, T. Erkinjuntti, R. Mantyla, et al. Impact of White Matter Hyperintensities Scoring Method on Correlations With Clinical Data: The LADIS Study Stroke, March 1, 2006; 37(3): 836 - 840. [Abstract] [Full Text] [PDF]
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N.F. Fanning, T.D. Walters, A.J. Fox, and S.P. Symons Association between Calcification of the Cervical Carotid Artery Bifurcation and White Matter Ischemia. AJNR Am. J. Neuroradiol., February 1, 2006; 27(2): 378 - 383. [Abstract] [Full Text] [PDF]
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A. J. Bastos Leite, W. M. van der Flier, E. C. W. van Straaten, P. Scheltens, and F. Barkhof Infratentorial Abnormalities in Vascular Dementia Stroke, January 1, 2006; 37(1): 105 - 110. [Abstract] [Full Text] [PDF]
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D. J. Werring, L. J. Coward, N. A. Losseff, H. R. Jager, and M. M. Brown Cerebral microbleeds are common in ischemic stroke but rare in TIA Neurology, December 27, 2005; 65(12): 1914 - 1918. [Abstract] [Full Text] [PDF]
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M. Cosottini, M. C. Michelassi, M. Puglioli, G. Lazzarotti, G. Orlandi, F. Marconi, G. Parenti, and C. Bartolozzi Silent Cerebral Ischemia Detected With Diffusion-Weighted Imaging in Patients Treated With Protected and Unprotected Carotid Artery Stenting Stroke, November 1, 2005; 36(11): 2389 - 2393. [Abstract] [Full Text] [PDF]
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M. Pawlak and J. Krejza A New Visual Scale to Assess White Matter Hyperintensities Within Cholinergic Pathways Stroke, October 1, 2005; 36(10): 2064 - 2065. [Full Text] [PDF]
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C. Bocti, R. H. Swartz, F.-Q. Gao, D. J. Sahlas, P. Behl, and S. E. Black A New Visual Rating Scale to Assess Strategic White Matter Hyperintensities Within Cholinergic Pathways in Dementia Stroke, October 1, 2005; 36(10): 2126 - 2131. [Abstract] [Full Text] [PDF]
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F-E de Leeuw, F Barkhof, and P Scheltens Progression of cerebral white matter lesions in Alzheimer's disease: a new window for therapy? J. Neurol. Neurosurg. Psychiatry, September 1, 2005; 76(9): 1286 - 1288. [Abstract] [Full Text] [PDF]
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A. Fellgiebel, M. J. Muller, M. Mazanek, K. Baron, M. Beck, and P. Stoeter White matter lesion severity in male and female patients with Fabry disease Neurology, August 23, 2005; 65(4): 600 - 602. [Abstract] [Full Text] [PDF]
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J H Fu, C Z Lu, Z Hong, Q Dong, Y Luo, and K S Wong Extent of white matter lesions is related to acute subcortical infarcts and predicts further stroke risk in patients with first ever ischaemic stroke J. Neurol. Neurosurg. Psychiatry, June 1, 2005; 76(6): 793 - 796. [Abstract] [Full Text] [PDF]
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A M J MacLullich, J M Wardlaw, K J Ferguson, J M Starr, J R Seckl, and I J Deary Enlarged perivascular spaces are associated with cognitive function in healthy elderly men J. Neurol. Neurosurg. Psychiatry, November 1, 2004; 75(11): 1519 - 1523. [Abstract] [Full Text] [PDF]
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D. J. Werring, D. W. Frazer, L. J. Coward, N. A. Losseff, H. Watt, L. Cipolotti, M. M. Brown, and H. R. Jager Cognitive dysfunction in patients with cerebral microbleeds on T2*-weighted gradient-echo MRI Brain, October 1, 2004; 127(10): 2265 - 2275. [Abstract] [Full Text] [PDF]
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H. M. Wen, V. C.T. Mok, Y. H. Fan, W. W.M. Lam, W. K. Tang, A. Wong, R. X. Huang, and K. S. Wong Effect of White Matter Changes on Cognitive Impairment in Patients With Lacunar Infarcts Stroke, August 1, 2004; 35(8): 1826 - 1830. [Abstract] [Full Text] [PDF]
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E. S.C. Korf, L.-O. Wahlund, P. J. Visser, and P. Scheltens Medial temporal lobe atrophy on MRI predicts dementia in patients with mild cognitive impairment Neurology, July 13, 2004; 63(1): 94 - 100. [Abstract] [Full Text] [PDF]
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R. Schmidt, Ph. Scheltens, T. Erkinjuntti, L. Pantoni, H. S. Markus, A. Wallin, F. Barkhof, and F. Fazekas White matter lesion progression: A surrogate endpoint for trials in cerebral small-vessel disease Neurology, July 13, 2004; 63(1): 139 - 144. [Abstract] [Full Text] [PDF]
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V C T Mok, A Wong, W W M Lam, Y H Fan, W K Tang, T Kwok, A C F Hui, and K S Wong Cognitive impairment and functional outcome after stroke associated with small vessel disease J. Neurol. Neurosurg. Psychiatry, April 1, 2004; 75(4): 560 - 566. [Abstract] [Full Text] [PDF]
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F.-E. de Leeuw, F. Barkhof, and P. Scheltens White matter lesions and hippocampal atrophy in Alzheimer's disease Neurology, January 27, 2004; 62(2): 310 - 312. [Abstract] [Full Text] [PDF]
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G B Frisoni, P h Scheltens, S Galluzzi, F M Nobili, N C Fox, P H Robert, H Soininen, L-O Wahlund, G Waldemar, and E Salmon Neuroimaging tools to rate regional atrophy, subcortical cerebrovascular disease, and regional cerebral blood flow and metabolism: consensus paper of the EADC J. Neurol. Neurosurg. Psychiatry, October 1, 2003; 74(10): 1371 - 1381. [Abstract] [Full Text] [PDF]
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E. C.W. van Straaten, P. Scheltens, D. L. Knol, M. A. van Buchem, E. J. van Dijk, P. A.M. Hofman, G. Karas, O. Kjartansson, F.-E. de Leeuw, N. D. Prins, et al. Operational Definitions for the NINDS-AIREN Criteria for Vascular Dementia: An Interobserver Study Stroke, August 1, 2003; 34(8): 1907 - 1912. [Abstract] [Full Text] [PDF]
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P. Kapeller, R. Barber, R.J. Vermeulen, H. Ader, P. Scheltens, W. Freidl, O. Almkvist, M. Moretti, T. del Ser, P. Vaghfeldt, et al. Visual Rating of Age-Related White Matter Changes on Magnetic Resonance Imaging: Scale Comparison, Interrater Agreement, and Correlations With Quantitative Measurements Stroke, February 1, 2003; 34(2): 441 - 445. [Abstract] [Full Text] [PDF]
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L. Pantoni, M. Simoni, G. Pracucci, R. Schmidt, F. Barkhof, and D. Inzitari Visual Rating Scales for Age-Related White Matter Changes (Leukoaraiosis): Can the Heterogeneity Be Reduced? Stroke, December 1, 2002; 33(12): 2827 - 2833. [Abstract] [Full Text] [PDF]
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