[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 184.73.122.162. Please contact the publisher to request reinstatement.
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Download PDF
Conventional turbo spin-echo T2-weighted images (A) and the corresponding probability map of gray matter (B), white matter (C), and cerebrospinal fluid (D).

Conventional turbo spin-echo T2-weighted images (A) and the corresponding probability map of gray matter (B), white matter (C), and cerebrospinal fluid (D).

Table 1 
Normalized WM and GM Volumes and NBVs in Elderly Individuals With and Without Nonspecific WM Signal Hyperintensities
Normalized WM and GM Volumes and NBVs in Elderly Individuals With and Without Nonspecific WM Signal Hyperintensities
Table 2 
GM and WM MTR Histogram-Derived Metrics in Elderly Individuals With and Without White-Matter Hyperintensities
GM and WM MTR Histogram-Derived Metrics in Elderly Individuals With and Without White-Matter Hyperintensities
1.
de Leeuw  FEde Groot  JCAchten  E  et al Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study: the Rotterdam Scan Study. J Neurol Neurosurg Psychiatry.2001;70:9-14.
PubMed
2.
Longstreth Jr  WTManolio  TAArnold  A  et al Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: the Cardiovascular Health Study. Stroke.1996;27:1274-1282.
PubMed
3.
Liao  DCooper  LCai  J  et al Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control: the ARIC Study (Atherosclerosis Risk in Communities Study). Stroke.1996;27:2262-2270.
PubMed
4.
Pantoni  LGarcia  JH The significance of cerebral white matter abnormalities 100 years after Binswanger's report: a review. Stroke.1995;26:1293-1301.
PubMed
5.
Pantoni  LGarcia  JH Pathogenesis of leukoaraiosis: a review. Stroke.1997;28:652-659.
PubMed
6.
Tortorella  CViti  BBozzali  M  et al A magnetization transfer histogram study of normal-appearing brain tissue in MS. Neurology.2000;54:186-193.
PubMed
7.
Rovaris  MViti  BCiboddo  G  et al Brain involvement in systemic immune mediated diseases: magnetic resonance and magnetization transfer imaging study. J Neurol Neurosurg Psychiatry.2000;68:170-177.
PubMed
8.
Dousset  VArmand  JPHuot  PViaud  BCaille  JM Magnetization transfer imaging in AIDS-related brain diseases. Neuroimaging Clin North Am.1997;7:447-460.
PubMed
9.
Iannucci  GDichgans  MRovaris  M  et al Correlations between clinical findings and magnetization transfer imaging metrics of tissue damage in individuals with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Stroke.2001;32:643-648.
PubMed
10.
Ge  YGrossman  RIUdupa  JKBabb  JSKolson  DLMcGowan  JC Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol.2001;22:470-475.
PubMed
11.
Cercignani  MBozzali  MIannucci  GComi  GFilippi  M Magnetization transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry.2001;70:311-317.
PubMed
12.
Filippi  MTortorella  CBozzali  M Normal-appearing white matter changes in multiple sclerosis: the contribution of magnetic resonance techniques. Mult Scler.1999;5:273-282.
PubMed
13.
van Buchem  MAGrossman  RIArmstrong  C  et al Correlation of volumetric magnetization transfer imaging with clinical data in MS. Neurology.1998;50:1609-1617.
PubMed
14.
Fazekas  FKleinert  ROffenbacher  H  et al Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology.1993;43:1683-1689.
PubMed
15.
Scheltens  PErkinjunti  TLeys  D  et alEuropean Task Force on Age-Related White Matter Changes White matter changes on CT and MRI: an overview of visual rating scales. Eur Neurol.1998;39:80-89.
PubMed
16.
Grimaud  JLai  MThorpe  J  et al Quantification of MRI lesion load in multiple sclerosis: a comparison of three computer-assisted techniques. Magn Reson Imaging.1996;14:495-505.
PubMed
17.
Ashburner  JFriston  K Multimodal image coregistration and partitioning—a unified framework. Neuroimage.1997;6:209-217.
PubMed
18.
De Stefano  NIannucci  GSormani  MP  et al MR correlates of cerebral atrophy in patients with multiple sclerosis. J Neurol.2002;249:1072-1077.
PubMed
19.
Inzitari  D Age-related white matter changes and cognitive impairment. Ann Neurol.2000;47:141-143.
PubMed
20.
Brooks  WMWesley  MHKodituwakku  PWGarry  PJRosenberg  GA 1H-MRS differentiates white matter hyperintensities in subcortical arteriosclerotic encephalopathy from those in normal elderly. Stroke.1997;28:1940-1943.
PubMed
21.
Moody  DMBell  MAChalla  VR Features of the cerebral vascular pattern that predict vulnerability to perfusion or oxygenation deficiency: an anatomic study. AJNR Am J Neuroradiol.1990;11:431-439.
PubMed
22.
Bladin  CFChambers  BR Clinical features, pathogenesis, and computed tomographic characteristics of internal watershed infarction. Stroke.1993;24:1925-1932.
PubMed
23.
van Swieten  JCvan den Hout  JHvan Ketel  BAHijdra  AWokke  JHvan 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;114:761-774.
PubMed
24.
Imaoka  KKobayashi  SFujihara  SShimode  KNagasaki  M Leukoencephalopathy with cerebral amyloid angiopathy: a semiquantitative and morphometric study. J Neurol.1999;246:661-666.
PubMed
25.
Suter  OCSunthorn  TKraftsik  R  et al Cerebral hypoperfusion generates cortical watershed microinfarcts in Alzheimer disease. Stroke.2002;33:1986-1992.
PubMed
Original Contribution
August 2003

Evidence of Subtle Gray-Matter Pathologic Changes in Healthy Elderly Individuals With Nonspecific White-Matter Hyperintensities

Author Affiliations

From the Neuroimaging Research Unit, Department of Neurology (Drs Mezzapesa, Rocca, Pagani, and Filippi), and Department of Neurology (Dr Comi), Scientific Institute and University Ospedale San Raffaele, Milan, Italy.

Arch Neurol. 2003;60(8):1109-1112. doi:10.1001/archneur.60.8.1109
Abstract

Objective  To investigate whether additional "occult" tissue changes can be detected in the normal-appearing white matter and gray matter of otherwise normal elderly individuals with nonspecific white-matter hyperintensities on conventional magnetic resonance images of the brain.

Methods  Conventional and magnetization transfer magnetic resonance images were obtained from 12 otherwise normal elderly subjects with white-matter hyperintensities and 11 age- and sex-matched normal individuals. After automatic tissue segmentation, image coregistration, and masking of T2-visible lesions, we obtained magnetization transfer ratio histograms of the normal-appearing white matter and gray matter. For each histogram, the average magnetization transfer ratio, the peak height, and the peak position were measured. We also calculated the percentages of gray-matter and white-matter volumes normalized over the total volume of the intracranial content and the total normalized brain volumes.

Results  Average magnetization transfer ratio (P = .03) and mean peak position (P = .01) of the gray-matter histograms from elderly individuals with white-matter hyperintensities were significantly lower than the corresponding quantities from those without white-matter hyperintensities. The normalized percentages of gray and white matter and normalized brain volume did not differ between the 2 groups. The average gray-matter magnetization transfer ratio was correlated with the average lesion magnetization transfer ratio (r = 0.68; P<.01).

Conclusions  This study shows that brain abnormalities in otherwise normal elderly subjects with nonspecific white-matter hyperintensities extend beyond the macroscopic white-matter lesions visualized on conventional magnetic resonance images.

NONSPECIFIC white-matter hyperintensities (WMHs) are frequently seen on conventional magnetic resonance (MR) images of the brain from elderly individuals.13 Although the nature and clinical significance of WMHs in the elderly are still unclear, the most plausible pathological substrate for such changes is thought to be ischemic damage.4,5

In many neurologic diseases associated with focal white-matter (WM) lesions, the use of magnetization transfer (MT) MR imaging has shown that the overall tissue damage extends well beyond that seen on conventional MR images and involves the normal-appearing WM69 and the gray matter (GM).10,11 In these conditions, MT MR imaging has also provided valuable information about the underlying composition of tissue with increased specificity over conventional MR imaging.12

Since definitive histopathological correlations are unlikely to be obtained in patients with nonspecific WMHs, we investigated, by means of MT MR imaging and histogram analysis,13 whether additional "occult" pathologic changes can be detected in the normal-appearing WM and GM of the whole brain of these patients. The aim of the study was not only to provide a more accurate picture of the pathologic changes associated with WMHs in the elderly, but also to gain additional insight into the nature of this condition.

METHODS

Conventional and MT MR images of the brain were obtained from 23 elderly individuals aged 65 years or more with no previous history of neurologic dysfunction and normal results of neurologic examination, who volunteered to take part in this study. They were selected on the basis of the criteria mentioned from a larger group of elderly individuals who served as controls for previous studies conducted at our institution. The study was approved by the local ethical committee, and written informed consent was obtained from all individuals before study entry.

On a single occasion, the following MR sequences of the brain were obtained by means of a 1.5-T machine (Vision; Siemens, Erlangen, Germany) from all individuals: (1) dual-echo turbo spin echo (repetition time, 3300 milliseconds; time to first echo, 16 milliseconds; time to second echo, 98 milliseconds; echo-train length, 5); (2) T1-weighted conventional spin echo (repetition time, 768 milliseconds; echo time, 14 milliseconds); and (3) 2-dimensional gradient echo (repetition time, 640 milliseconds; echo time, 12 milliseconds; flip angle, 20°), with and without an off-resonance radiofrequency saturation pulse (offset frequency, 1.5 kHz; gaussian envelope duration, 16.4 milliseconds; flip angle, 500°). For each pulse sequence, 24 axial, contiguous, 5-mm-thick slices with a 256 × 256 matrix and a 250 × 250-mm2 field of view were obtained.

Dual-echo images from all subjects were reviewed in a random order by consensus by 2 experienced observers (D.M.M. and M.A.R.), unaware of subjects' identity, to identify the presence of WMHs. According to the presence or absence of WMHs, the subjects were divided into 2 groups: the study group (12 individuals; mean age, 69 years; range, 65-73 years; 6 women, 6 men) and the control group (11 individuals; mean age, 68 years; range, 65-74 years; 6 women, 5 men). In the former group, WMHs were scored according to the scale of Fazekas et al.14 This scale provides 2 different scores rated on a 3-point scale according to the following criteria: periventricular score: 0 (absence), 1 (caps or pencil-thin lining), 2 (smooth halo), or 3 (irregular periventricular hyperintensities extending into the deep WM); and WM score: 0 (absence), 1 (punctate foci), 2 (beginning confluence of foci), or 3 (large confluent areas). This scale was chosen because it has been validated histopathologically and is characterized by an acceptable reliability.15

The volume of WMHs was measured by a semiautomated technique based on local thresholding.16 With the use of statistical parametric mapping 99 and maximum image inhomogeneity correction,17 brain GM, WM, and cerebrospinal fluid were automatically segmented from T2- and proton-density–weighted images. Each pixel was classified as either GM, WM, or cerebrospinal fluid, depending on which mask had the greatest probability (maximum likelihood) at that location. This generated mutually exclusive masks for each tissue. Figure 1 shows a typical example of this procedure, indicating how well the segmentation technique worked. At this stage, the percentages of GM and WM volumes normalized over the total volume of the intracranial content were calculated. Maps of the MT ratio (MTR) were obtained as previously described.6 After WMHs were automatically superimposed onto the coregistered MTR map, average MTR of the WMHs was calculated, as extensively described elsewhere.6 Then, the MTR maps (from which the WMHs had been automatically removed) were superimposed onto the GM and WM masks, and MTR histograms (with bins 1% in width) of normal-appearing WM and GM were obtained. To correct for the between-patient differences in brain volumes, each histogram was normalized by dividing it by the total number of pixels included. For each histogram, the average MTR, the peak height (ie, the proportion of pixels at the most common MTR value), and the peak position (ie, the most common MTR value) were measured.

On T1-weighted images, normalized volumes of the whole of the brain were obtained by means of the cross-sectional version of the SIENA (Structural Imaging Evaluation of Normalized Atrophy) software.18 This is a fully automated and accurate method that performs segmentation of brain from nonbrain tissue in the head, estimates the outer skull surface, and uses these results to drive the spatial transformation to a standard template. This software is extensively described elsewhere.18

A Mann-Whitney test was used to compare MTR-derived metrics, normalized brain volume, normalized percentage of GM, and normalized percentage of WM from the 2 groups of subjects. Univariate correlations were assessed by means of the Spearman rank correlation coefficient. Bonferroni correction for multiple comparisons was not used in the present study because of its exploratory nature.

RESULTS

In the 12 subjects with WMHs, the mean lesion load volume was 6.0 mL (SD, 7.1 mL). In all of these subjects, WMHs were scored as grade 1 or grade 2 for both the periventricular (mean, 1.4) and the WM (mean, 1.2) scores, according to the scale of Fazekas et al.14 The average lesion MTR was 39.3% (SD, 1.1%). No macroscopic GM abnormalities were seen on the brain MR images of any of the individuals. The normalized percentage of WM, the percentage of GM, and the normalized brain volume did not differ between the 2 groups (Table 1).

Average MTR (P = .03) and mean peak position (P = .01) of the GM histograms from elderly individuals with WMHs were significantly lower than the corresponding quantities from those without (Table 2). The MTR histogram metrics of the normal-appearing WM were not significantly different between the 2 groups (Table 2).

The average MTR of the GM histogram was correlated with the average lesion MTR (r = 0.68; P<.01). No significant correlation was found between MTR metrics of the GM histograms and the volume of WMHs.

COMMENT

This preliminary study shows that brain pathologic changes in otherwise normal elderly subjects with nonspecific WMHs extend beyond the macroscopic abnormalities visualized on conventional MR images. Using MTR histogram analysis, we detected a subtle involvement of the brain GM of these individuals. This finding not only provides a more complete picture of brain changes in elderly individuals with nonspecific WMHs but also, and more important, may improve our understanding of the pathophysiology of this condition, which is unlikely to be obtained from histopathological studies. Since we are aware that cortical and brain atrophy can cause a GM MTR decrease due to partial volume effects associated with the inclusion of voxels contaminated by cerebrospinal fluid, we measured normalized brain volume and normalized percentage of GM in the 2 groups of elderly individuals (ie, those with and those without WMHs). Since there was no difference of either of these 2 quantities between the 2 groups, we can reasonably exclude that GM MTR decrease in individuals with WMHs is attributable to cortical and brain atrophy. It remains to be established whether these subtle GM changes in otherwise normal individuals might evolve into cortical atrophy and be the basis of the mild cognitive deficits that have been reported in some individuals with WMHs.19

With this in mind, the major issue to be addressed is to elucidate the origin of such GM changes. Since these individuals had WMHs, the most readily apparent explanation for the MTR decrease found in their brain GM is to interpret this finding as the result of a passive upstream effect secondary to the damage of fibers transversing WM lesions. Although we cannot exclude a contribution of this mechanism to the observed GM changes, we believe that retrograde neuronal degeneration is unlikely to play an important role because of the scarcity of the macroscopic WM lesions seen in these patients and the lack of occult damage in the normal-appearing WM. This interpretation fits with the lack of a correlation between the volume of WMHs and MTR histogram-derived metrics, as well as with previous MR spectroscopy data,20 which did not show a decrease in N-acetylaspartate in WMHs of otherwise healthy elderly individuals.

An alternative, although not mutually exclusive, explanation of the GM occult changes seen in these individuals is the presence of small GM lesions that go undetected when conventional MR imaging is used. There are several possible reasons that can explain why these lesions are not seen on conventional MR images; these include the fact that GM lesions may be small, have relaxation characteristics that result in poor contrast with normal GM, and, in the case of cortical lesions, because of partial volume effects with the surrounding cerebrospinal fluid.

The nature of WMHs in elderly individuals is still unclear. However, one of the most plausible explanations for these abnormalities is supposed to be an ischemic injury occurring during episodes of cerebral hypoperfusion.5 The susceptibility of deep WM to systemic or focal decreases of cerebral blood flow is most likely a consequence of the unique pattern of its blood supply through long penetrating end-arterial vessels.21 Since it is known that damage secondary to cerebral hypoperfusion can also cause small cortical infarcts to vascular watershed zones,22 it is tempting to suggest a similar mechanism as the pathologic basis of both WMHs and GM MTR decrease in otherwise normal elderly individuals. Arteriolosclerosis or cerebral amyloid angiopathy might well be additional factors that can concur with the anatomic susceptibility in the genesis of both WMHs and cortical watershed microinfarcts.2325

This interpretation of the results of the present study fits with the absence of diffuse occult WM changes of the brain, and it is supported by the correlation found between average lesion MTR and average GM MTR, which suggests that the severity of WMHs and GM abnormalities are not independent of each other. In this context, it is also worth noting that, with the use of MTR, occult GM involvement has also been reported in patients with WM vascular abnormalities, such as those with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy.9

In conclusion, the preliminary evidence presented herein suggests that brain pathologic changes in these individuals extend beyond the classic deep WM areas, suggesting a diffuse whole-brain disorder. Larger studies are now warranted to confirm the present findings.

Back to top
Article Information

Corresponding author and reprints: Massimo Filippi, MD, Neuroimaging Research Unit, Department of Neurology, Scientific Institute and University Ospedale San Raffaele, Via Olgettina, 60, 20132 Milan, Italy (e-mail: m.filippi@hsr.it).

Accepted for publication January 21, 2003.

Author contributions: Study concept and design (Drs Comi and Filippi); acquisition of data (Drs Mezzapesa and Rocca); analysis and interpretation of data (Drs Mezzapesa, Rocca, and Pagani); drafting of the manuscript (Drs Mezzapesa and Filippi); critical revision of the manuscript for important intellectual content (Drs Mezzapesa, Rocca, Pagani, Comi, and Filippi); statistical expertise (Dr Mezzapesa); obtained funding (Dr Filippi); administrative, technical, and material support (Drs Rocca, Pagani, Comi, and Filippi); study supervision (Dr Filippi).

References
1.
de Leeuw  FEde Groot  JCAchten  E  et al Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study: the Rotterdam Scan Study. J Neurol Neurosurg Psychiatry.2001;70:9-14.
PubMed
2.
Longstreth Jr  WTManolio  TAArnold  A  et al Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: the Cardiovascular Health Study. Stroke.1996;27:1274-1282.
PubMed
3.
Liao  DCooper  LCai  J  et al Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control: the ARIC Study (Atherosclerosis Risk in Communities Study). Stroke.1996;27:2262-2270.
PubMed
4.
Pantoni  LGarcia  JH The significance of cerebral white matter abnormalities 100 years after Binswanger's report: a review. Stroke.1995;26:1293-1301.
PubMed
5.
Pantoni  LGarcia  JH Pathogenesis of leukoaraiosis: a review. Stroke.1997;28:652-659.
PubMed
6.
Tortorella  CViti  BBozzali  M  et al A magnetization transfer histogram study of normal-appearing brain tissue in MS. Neurology.2000;54:186-193.
PubMed
7.
Rovaris  MViti  BCiboddo  G  et al Brain involvement in systemic immune mediated diseases: magnetic resonance and magnetization transfer imaging study. J Neurol Neurosurg Psychiatry.2000;68:170-177.
PubMed
8.
Dousset  VArmand  JPHuot  PViaud  BCaille  JM Magnetization transfer imaging in AIDS-related brain diseases. Neuroimaging Clin North Am.1997;7:447-460.
PubMed
9.
Iannucci  GDichgans  MRovaris  M  et al Correlations between clinical findings and magnetization transfer imaging metrics of tissue damage in individuals with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Stroke.2001;32:643-648.
PubMed
10.
Ge  YGrossman  RIUdupa  JKBabb  JSKolson  DLMcGowan  JC Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol.2001;22:470-475.
PubMed
11.
Cercignani  MBozzali  MIannucci  GComi  GFilippi  M Magnetization transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry.2001;70:311-317.
PubMed
12.
Filippi  MTortorella  CBozzali  M Normal-appearing white matter changes in multiple sclerosis: the contribution of magnetic resonance techniques. Mult Scler.1999;5:273-282.
PubMed
13.
van Buchem  MAGrossman  RIArmstrong  C  et al Correlation of volumetric magnetization transfer imaging with clinical data in MS. Neurology.1998;50:1609-1617.
PubMed
14.
Fazekas  FKleinert  ROffenbacher  H  et al Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology.1993;43:1683-1689.
PubMed
15.
Scheltens  PErkinjunti  TLeys  D  et alEuropean Task Force on Age-Related White Matter Changes White matter changes on CT and MRI: an overview of visual rating scales. Eur Neurol.1998;39:80-89.
PubMed
16.
Grimaud  JLai  MThorpe  J  et al Quantification of MRI lesion load in multiple sclerosis: a comparison of three computer-assisted techniques. Magn Reson Imaging.1996;14:495-505.
PubMed
17.
Ashburner  JFriston  K Multimodal image coregistration and partitioning—a unified framework. Neuroimage.1997;6:209-217.
PubMed
18.
De Stefano  NIannucci  GSormani  MP  et al MR correlates of cerebral atrophy in patients with multiple sclerosis. J Neurol.2002;249:1072-1077.
PubMed
19.
Inzitari  D Age-related white matter changes and cognitive impairment. Ann Neurol.2000;47:141-143.
PubMed
20.
Brooks  WMWesley  MHKodituwakku  PWGarry  PJRosenberg  GA 1H-MRS differentiates white matter hyperintensities in subcortical arteriosclerotic encephalopathy from those in normal elderly. Stroke.1997;28:1940-1943.
PubMed
21.
Moody  DMBell  MAChalla  VR Features of the cerebral vascular pattern that predict vulnerability to perfusion or oxygenation deficiency: an anatomic study. AJNR Am J Neuroradiol.1990;11:431-439.
PubMed
22.
Bladin  CFChambers  BR Clinical features, pathogenesis, and computed tomographic characteristics of internal watershed infarction. Stroke.1993;24:1925-1932.
PubMed
23.
van Swieten  JCvan den Hout  JHvan Ketel  BAHijdra  AWokke  JHvan 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;114:761-774.
PubMed
24.
Imaoka  KKobayashi  SFujihara  SShimode  KNagasaki  M Leukoencephalopathy with cerebral amyloid angiopathy: a semiquantitative and morphometric study. J Neurol.1999;246:661-666.
PubMed
25.
Suter  OCSunthorn  TKraftsik  R  et al Cerebral hypoperfusion generates cortical watershed microinfarcts in Alzheimer disease. Stroke.2002;33:1986-1992.
PubMed
×