Radiology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Published online before print October 9, 2001, 10.1148/radiol.2213010295
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
2213010295v1
221/3/810    most recent
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Van Laere, K. J.
Right arrow Articles by Dierckx, R. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Van Laere, K. J.
Right arrow Articles by Dierckx, R. A.
(Radiology. 2001;221:810-817.)
© RSNA, 2001


Nuclear Medicine

Brain Perfusion SPECT: Age- and Sex-related Effects Correlated with Voxel-based Morphometric Findings in Healthy Adults1

Koenraad J. Van Laere, MD, DSc and Rudi A. Dierckx, MD, PhD

1 From the Division of Nuclear Medicine, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium. Received January 9, 2001; revision requested March 5; revision received April 20; accepted May 21. Supported by a special research grant from Ghent University and the Flemish government (BOZF 01104699). Address correspondence to K.J.V.L. (e-mail: koen.vanlaere@rug.ac.be).


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
PURPOSE: To investigate brain perfusion at single photon emission computed tomography (SPECT) as a function of age and sex in healthy adult volunteers and to correlate perfusion with gray matter concentration determined by using voxel-based morphometry (VBM).

MATERIALS AND METHODS: Eighty-one healthy volunteers underwent both technetium 99m ethylene cysteine dimer SPECT and three-dimensional magnetization preparation rapid acquisition gradient-echo magnetic resonance (MR) imaging. Statistical parametric mapping was used to conduct VBM analysis of the morphologic data, which were compared voxel by voxel with the results of a similar analysis of the perfusion data and more specifically in brain areas showing significant perfusion changes.

RESULTS: VBM data, as compared with perfusion changes, indicated a more symmetric age-related gray matter volume decrease along the Sylvian fissure and in subcortical regions (P < .001). The combination of functional and structural changes indicated a relatively lower functional decrease with aging, as compared with the structural atrophy in the visual, parietal, sensorimotor, and right prefrontal cortices. Significant relative morphologic sex-based differences were found in the cerebellar and temporal cortices, but the comparison did not reveal significant differences between the functional and morphometric data.

CONCLUSION: Age-related perfusion changes are paralleled by similar more symmetric changes in gray matter concentration, which are more prominent than the perfusion changes in some regions. No sex-based differences between perfusion and gray matter concentration were found.

Index terms: Brain, atrophy, 10.83 • Brain, MR, 13.12141, 13.121412 • Brain, perfusion • Brain, radionuclide studies, 13.12162, 13.12163 • Brain, SPECT, 13.12162


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Advances in instrumentation and analysis software have enhanced the clinical usefulness of functional brain single photon emission computed tomography (SPECT). Improved sensitivity and resolution due to the use of multihead gamma cameras with fan-beam collimation enable imaging of technetium 99m (99mTc)–labeled radioligands with a resolution of 7–8 mm full width at half maximum. Correction for physical factors that degrade image quality and quantification, such as attenuation and scatter, can now be performed with commercial systems (1,2). Voxel-based analysis involving statistical parametric mapping (SPM) of functional data also is being used with SPECT imaging (37). This technique has the advantage of enabling systematic, objective, and fast analysis of the entire brain volume, in contrast to visual inspection or interactive region-of-interest methods, which are operator biased and labor intensive. Moreover, voxel-based analysis with SPM allows a pictorial representation of the findings, precise anatomic localization of the substantial changes, and thus objective comparisons between studies (8). However, the clinical and/or research use of this approach necessitates quantitative comparisons with carefully selected normal data (9).

99mTc-labeled ethylene cysteine dimer (ECD) and hexamethyl-propyleneamine oxime act as chemical microspheres and are retained in the brain in a fixed distribution that reflects the cerebral perfusion pattern, but these agents have different uptake mechanisms and patterns in healthy (3) and pathologic states (7,10). Because 99mTc ECD has higher in vitro stability and cerebral retention, lower radiation burden, rapid blood clearance of metabolites, and rapid elimination from extracerebral tissue, this radioligand has generated increased interest. However, the data on the properties of this agent in healthy populations are scarce in the literature (11,12).

For optimal clinical and research analysis sensitivity, the detailed characterization of covariate factors such as age and sex, which may affect interindividual physiologic uptakes, is very important. Although the results of many studies indicate that aging alters both regional blood flow and glucose metabolism with a specific frontotemporal pattern (8), to our knowledge, none of these functional topographic studies have included regional structural data in the analysis. This is particularly interesting because the results of numerous computed tomographic (CT) and magnetic resonance (MR) imaging studies have demonstrated an age-related decrease in brain size, an enlargement of cortical sulci, and an increase in cerebrospinal fluid space (CSF) after the age of 30 (1317). Therefore, atrophy is considered a confounding variable in functional studies because it causes a partial volume effect that increases with lower spatial resolution. Since, to our knowledge, no clinically practical voxel-based atrophy correction schemes have been validated (1820) yet, it was our aim to investigate brain perfusion at SPECT as a function of age and sex in healthy adult volunteers for 6 age decades and to correlate these perfusion findings with gray matter concentrations determined by using voxel-based morphometry (VBM).


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
The recruitment, prescreening, and screening procedures, as well as the exclusion criteria, for the healthy volunteers have been described previously (12). In short, all included subjects underwent thorough screening to establish a healthy status; this included a complete medical history, a physical examination, blood and urine testing, a full clinical neurologic examination performed by a board-certified neurologist, a psychiatric examination, and neuropsychologic testing performed by a board-certified psychiatrist (12). The high-spatial-resolution T1-weighted magnetization preparation rapid acquisition gradient-echo (MPRAGE) and T2-weighted transaxial MR imaging findings, as evaluated by a board-certified neuroradiologist, were normal in all subjects.

A total of 81 adult subjects (41 women, 40 men; age range, 20–81 years; average age, 44.2 years; all age decades stratified for sex) in whom good-quality MPRAGE images were available were included in this prospective cross-sectional study. The study was approved by the local ethics committee of Ghent University Hospital. Written informed consent was obtained from all the volunteers prior to the MR imaging and SPECT studies, after the nature of the procedures had been fully explained.

Background (Previous Study) Information
All selected volunteers underwent perfusion SPECT imaging with 925 MBq of 99mTc ECD (Dupont Pharmaceuticals, Brussels, Belgium). Acquisition and reconstruction, with incorporation of nonuniform attenuation and triple-energy window scatter correction, were performed as described previously (12). The previous study also included SPECT data analysis performed with special software used to test hypotheses about neurologic imaging data (SPM99; Wellcome Department of Cognitive Neurology, University College, London). In short, nonlinear warping with use of the corresponding MPRAGE MR images was performed. In that study (12), a highly significant decrease with age in the following tissue volumes was found (P < .001): anterior cingulate gyrus; left prefrontal, left lateral frontal, and left superior temporal and insular cortices; bilateral basal ganglia; and medial thalami. The contrast of relative increased perfusion with age indicated substantial clusters at the left and right cunei in the occipital cortex, in accordance with a relative sparing of these areas (ie, proportional scaling effect). As for sex-related differences, at SPECT, men had higher perfusion in the cerebellum bilaterally and in the left anterior temporal and orbitofrontal cortices, with extension to the anterior cingulate. On the other hand, women had significantly higher perfusion in the right parietal cortex than men (P < .001), with extension to the posterior temporal cortex.

MR Imaging
In the present study, MR images were obtained within 3 months after the first SPECT scans were obtained in all subjects (mean interval between date of MR imaging and date of SPECT, -1 week ± 3.5; range, -11 to 7 weeks) with a 1.5-T unit (Magnetom SP4000; Siemens, Erlangen, Germany). High-spatial-resolution anatomic imaging was performed with a three-dimensional MPRAGE sequence (9.7/4.0 [repetition time msec/echo time msec], 8° flip angle, 178 sections, 0.9-mm section thickness, 230 x 256 matrix, 250-mm field of view, one signal acquired). This sequence yielded T1-weighted sagittal images with a nearly isotropic resolution: The voxel size was 0.98 x 0.98 x 0.90 mm.

VBM Analysis
To investigate underlying age- and sex-related structural changes, a VBM study also was conducted (21,22). With the SPM software, automated segmentation based on a combination of intensity-driven and Bayesian classifications was carried out on normalized MR images, with subdivision of the gray matter, white matter, CSF, and extracerebral structures. Inhomogeneity corrections were incorporated because they have been shown to substantially improve the segmentation process (22). From this segmentation software, the relative CSF, gray matter, and white matter volumes normalized to each individual’s intracranial volume were extracted and evaluated as functions of age and sex by using linear regression analysis (SPSS v9.0; SPSS, Heverlee, Belgium).

For segmentation, nonlinear normalization was performed with the same parameters as those described earlier but with a final voxel size of 1.5 x 1.5 x 1.5 mm. Afterward, the binary segmented gray matter image was converted to a 3 x 3 x 3-mm voxel image. The gray matter image was then smoothed with an anisotropic Gaussian kernel approximating that of the SPECT spatial resolution, as measured with point sources. The in-plane (ie, transaxial) full width at half maximum was 7.9 mm, and the z-axis (ie, transverse) full width at half maximum was 8.9 mm (23). This differential smoothing to the same smoothness allows the assumption of an equal spatial autocovariance structure of both of the two data sets (24). Then, the same isotropic kernel as that used for the perfusion data was applied before analysis with the SPM software. Data were also adjusted by means of proportional scaling to a value of 50 and with a gray matter threshold of 0.10. To test the influence of the nonlinear normalization procedure, the same analysis was conducted with affine transformation (ie, no nonlinear parameters).

Age-related differences were studied on a voxel-wise basis in a correlation design. Linear voxel-wise regression with the subject’s age as a covariate was investigated. Contrasts were defined for age-related regional perfusion decrease and increase.

We also followed an approach used by Büchel et al (25), in which nonlinear regression was used with second-order polynomial expansion by defining the squared values of the subject’s age as a second covariate of interest. To assess the magnitude of the nonlinear effect of age, the squared values were used as covariates of interest in the study design, with the linear evolution of age as a covariate of no interest (26).

Sex-based differences were studied by comparing age-matched studies in a categorical population-comparison design with one scan per subject (voxel-wise t test). Contrasts were defined to examine the areas where perfusion was higher in men than in women and vice versa. The resultant set of statistical values for each contrast constituted a statistical parametric map of the t statistic, which was transformed into the normal distribution of the unit, SPM{Z} (27). This SPM{Z} map was interrogated at the height threshold corresponding to a P value (Phgt) of .001 and at the extent threshold corresponding to a P value (Pext) of less than .05, which were corrected for multiple comparisons unless stated otherwise.

To compare the differential structural adjusted response with the functional adjusted response, a single-subject, two-condition design in which perfusion was one condition, gray matter concentration was the second (24), and age and sex were covariates was explored. The covariate interactions were explicitly modeled and centered around the mean value. The variable-covariate interaction effects (eg, changes as functions of age) were then contrasted in the statistical analysis with the same thresholds as those defined earlier (ie, Phgt = .001; Pext = .05). This approach assumes implicit linearity between gray matter concentration and perfusion. For this analysis, a gray matter threshold of 0.40 was used.

The structural and functional adjusted responses were directly compared by using a 10-mm volume of interest centered at the most prominent voxel in the following three brain areas: the left insula, right insula, and left caudate head. These volume-of-interest data were analyzed by using linear regression with the software package described earlier (SPSS). All results for specific regions were defined probabilistically on the Montreal Neurological Institute template, with visual control of the normalized template images.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Age-related Morphologic Changes
The relative gray matter content after segmentation was inversely correlated with age (linear regression coefficient R = 0.72; P < .001). There was an average relative loss of total brain gray matter volume per decade of 1.1% ± 0.1 (SD) (Fig 1). A quadratic model did not improve the global goodness of fit. However, when the population was divided into subjects younger and older than 60 years, a doubling of the gradient was observed after the age of 60 (-2.1%/decade vs -1.0%/decade for the group younger than 60 years). The total relative CSF space increased with age (+0.9%; R = 0.77; P < .001), whereas there was no significant change in white matter content (P = .35).



View larger version (43K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 1. Graph illustrates relative cerebral volumes of gray matter ({blacksquare}), white matter ({square}), and CSF (*), which are expressed as percentage fractions of intracranial volume and plotted as functions of age. Data were obtained from automated segmentation at T1-weighted MPRAGE MR imaging performed in the healthy volunteers. For each volume group, linear fits with individual 95% regression prediction intervals are given.

 
Figure 2 shows the results of regional voxel-wise negative correlations with age at a Phgt of .001. A strikingly symmetric pattern was observed: The voxels with the most significant differences were around the Sylvian fissure (ie, inferior frontal and superior temporal gyri, supramarginal region, and parietal cortex), bilaterally along the third ventricle in the caudate head and medial thalamus, and to a lesser extent in the hippocampus and anterior cingulate. The cluster coordinates with significant differences are listed in Table 1. At lower intensity thresholds (Phgt = .005), the medial frontal gyrus also showed significant differences, as did some smaller clusters in the cerebellar hemispheres.



View larger version (119K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 2. MR images, with superimposed changes in yellow color scale, depict the results of VBM regression analysis: Findings indicate a decrease in gray matter concentration with age. The images show parametric maps on which the voxels with a significant negative correlation with age are superimposed on a template for the 15 youngest volunteers in the study. This template was created with nonlinear normalization (ie, orientation in radiologic convention). The correlation was tested at significance thresholds of Pext = .001 and Pext = .05, with correction for multiple comparisons.

 

View this table:
[in this window]
[in a new window]

 
TABLE 1. Voxel-based Morphometric Results, with Age as a Covariate

 
There were no changes in cluster number, extent, location, or significance at VBM analysis conducted with affine or nonlinear normalization. These results were also insensitive to the gray matter threshold value for voxels included in the SPM analysis (tested between a threshold of 0.10 and a threshold of 0.50).

Age-related Morphologic Changes Compared with Perfusion
The results of a direct comparison of gray matter concentration versus perfusion changes with age, which were studied in a categorical design with comparisons of age-condition interactions, showed a relatively smaller perfusion decrease with age in the parietal, sensorimotor, and occipital cortices, bilaterally distributed in equal extent and significance (Fig 3). A relatively smaller perfusion decrease with age was seen also in the right prefrontal cortex. The coordinates of the locations with significant differences and the corresponding P values are listed in Table 2.



View larger version (36K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 3. Glass brain maps show a direct voxel-wise comparison of gray matter concentration versus perfusion changes with age after resolution adjustment (comparative regression design). The maps show that the decrease in gray matter concentration with age is greater than the perfusion changes. Phgt is .001, and Pext is .05, with correction for multiple comparisons. L = left, R = right.

 

View this table:
[in this window]
[in a new window]

 
TABLE 2. Voxel-based Comparison of Functional versus Morphometric Data, with Age as a Covariate

 
The graphs in Figure 4 illustrate a direct comparison of perfusion versus gray matter concentration decreases within a volume-of-interest sphere (10-mm radius), scaled to the same adjusted response, for those three regions that were common among the regions with the most significant differences in both analyses: the left and right insula and the left caudate head. These data indicate that there were parallel decreases in perfusion and gray matter concentration. There was a significant correlation between perfusion and VBM data, with Pearson correlation coefficients (r values) ranging from 0.56 to 0.61 for the regions shown (P < .001). With a linear model of age-related decrease in perfusion and gray matter volume, only the right insula had a significant difference in linear regression coefficient (smaller for perfusion; P = .03), whereas no significant differences in adjusted response gradients were found for either the left insula (P = .09) or the left caudate head (P = .53). Use of a quadratic age model did not yield a significant increase in the goodness of fit for any studied region.



View larger version (33K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 4a. Graphs illustrate adjusted response changes in a 10-mm sphere for 99mTc ECD perfusion ({blacktriangleup}) and gray matter concentration at VBM ({circ}) in the (a) left and (b) right insulae and (c) the left caudate head as functions of age, with a Phgt threshold of less than .001. Both data sets were normalized to an average value of 50. The lines represent a linear regression through the data; perfusion is represented by the dashed line; and VBM, by the nondashed line. L = left, R = right.

 


View larger version (32K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 4b. Graphs illustrate adjusted response changes in a 10-mm sphere for 99mTc ECD perfusion ({blacktriangleup}) and gray matter concentration at VBM ({circ}) in the (a) left and (b) right insulae and (c) the left caudate head as functions of age, with a Phgt threshold of less than .001. Both data sets were normalized to an average value of 50. The lines represent a linear regression through the data; perfusion is represented by the dashed line; and VBM, by the nondashed line. L = left, R = right.

 


View larger version (34K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 4c. Graphs illustrate adjusted response changes in a 10-mm sphere for 99mTc ECD perfusion ({blacktriangleup}) and gray matter concentration at VBM ({circ}) in the (a) left and (b) right insulae and (c) the left caudate head as functions of age, with a Phgt threshold of less than .001. Both data sets were normalized to an average value of 50. The lines represent a linear regression through the data; perfusion is represented by the dashed line; and VBM, by the nondashed line. L = left, R = right.

 
Sex-based Differences in Morphologic Features
Women had a 4.3% higher gray matter brain content than did men (52.3 vs 50.0 relative gray matter volume, as adjusted for age; P < .001). As a function of age, the relative amount of gray matter progressed to the same values during the upper 2 age decades. Also, the CSF volume, relative to the total intracranial volume, was lower in women, as adjusted for age (P = .001). Figure 5 shows the results of the categorical comparison of men and women with regard to regional gray matter concentration. Men had a greater concentration in the upper cerebellar hemispheres bilaterally (Phgt = .01, Pext = .05; both corrected for multiple comparisons). Women had a tendency to have a higher perisylvian right temporal gray matter concentration than men (Phgt = .05, Pext = .05; neither corrected for multiple comparisons), but this was not statistically significant at levels corrected for multiple comparisons. The significance values and locations of these clusters are shown in Table 3.



View larger version (28K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 5a. Standardized sagittal (left), transaxial (middle), and coronal (right) glass brain maps on a Talairach grid illustrate categorical statistical parametric analysis of contrasts in gray matter concentration between men and women. (a) Contrast shows areas with a higher gray matter concentration in men than in women, as evaluated at thresholds of Phgt = .01 and Pext = .05, with correction for multiple comparisons. (b) Contrast shows areas with a higher gray matter concentration in women than in men, as evaluated at thresholds of Phgt = .05 and Pext = .05, without correction for multiple comparisons. For the latter contrast (b), no clusters survived the stringent correction for multiple comparisons, but the results are communicated because previously obtained information on the possible right temporal differences between the sexes exists. L = left, R = right.

 


View larger version (29K):
[in this window]
[in a new window]
[Download PPT slide]
 
Figure 5b. Standardized sagittal (left), transaxial (middle), and coronal (right) glass brain maps on a Talairach grid illustrate categorical statistical parametric analysis of contrasts in gray matter concentration between men and women. (a) Contrast shows areas with a higher gray matter concentration in men than in women, as evaluated at thresholds of Phgt = .01 and Pext = .05, with correction for multiple comparisons. (b) Contrast shows areas with a higher gray matter concentration in women than in men, as evaluated at thresholds of Phgt = .05 and Pext = .05, without correction for multiple comparisons. For the latter contrast (b), no clusters survived the stringent correction for multiple comparisons, but the results are communicated because previously obtained information on the possible right temporal differences between the sexes exists. L = left, R = right.

 

View this table:
[in this window]
[in a new window]

 
TABLE 3. Voxel-based Morphometric Results with Sex-based Differences Corrected for Age

 
Sex-based Morphologic Differences Compared with Perfusion
A comparison of the functional and structural data between men and women did not reveal significant mismatches between the structural and perfusion data sets for the sexes at the Phgt .05 and Pext .05 levels either when these values were corrected for multiple comparisons or when they were not.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Age-related Changes
As previously reported, we found perfusion differences with age in the frontotemporal regions—primarily in the left insula, prefrontal and lateral frontal cortices, anterior and superior temporal cortices, anterior cingulate, and both caudate heads. There is general agreement in the literature that aging is associated with regional changes in resting blood flow and/or metabolism. These changes most commonly are a selective reduction of blood flow and metabolism in the frontal and anterior cingulate cortices and are most prominent on the left side (8). The agreement on the topographic distribution of blood flow and metabolism changes is substantial, especially in two smaller published studies (28,29) that involved the use of similar mapping approaches instead of region-of-interest analysis.

On the other hand, the regional loss of gray matter volume with aging in our study was most prominent in the temporal and lateral frontal cortices and in the precentral, postcentral, and parietal cortices. A gray matter concentration decrease was found subcortically in the hippocampus, medial thalamus, and caudate heads. These voxel-based topographic results are in conjunction with those obtained in several region-of-interest–based volumetric MR studies (14,17,3032). The relative gray and white matter and CSF volume changes with age in the adults in the current series correspond to data in a recent volumetric MR study (13) involving 116 volunteers examined from childhood to late adulthood. The results of these studies and of investigations by other authors have also shown an age-related dilatation of CSF ventricular spaces with aging. This dilatation consistently affects the median nuclei of the thalamus and superficial cortical sulci in the frontal, parietal, and parasagittal regions (13,31,33). The age-related reductions in cerebellar volume observed at lower levels of significance in this study, albeit mild compared with the cerebral shrinkage, have also been described in other studies (34,35).

However, there has been ample discussion in the literature as to whether neuronal loss subtending gross structural changes in healthy volunteers fully explains the regional changes measured with functional imaging. Contrary to widely held belief, neuronal concentration remains essentially constant during normal aging, but neuron size decreases—presumably as a result of reduced dendritic arborization and dendritic spine concentration (36)—and the number of glial cells decreases (8). These phenomena occur with substantial variability according to genetic factors, education, profession, lifestyle, intellectual and physical activity, and general physical condition (37,38). From our study data, we hypothesize that the majority of observed age-related regional perfusion changes can be attributed to underlying changes in gray matter volume (ie, increase in atrophy). In one recent positron emission tomography 15O-H2O perfusion study (39) in which region-of-interest–based partial volume corrections were applied on predefined regions in healthy volunteers, a similar conclusion was made.

Moreover, from the direct voxel-wise correlation contrast between 99mTc ECD uptake and gray matter concentration, it was determined that visual and sensorimotor regions show relatively increased sparing of perfusion with advancing age; this was also the case for the right periinsular and prefrontal cortices. The latter effect of functional lateralization toward the right hemisphere with advancing age has been observed in earlier studies (11,12, 40,41) but not in all investigations (29). A relative increase in basic neuronal perfusion delivery in the right, predominantly anterior, hemisphere consistently adheres to the emerging principle of greater left-to-right functional vulnerability with aging and neurodegeneration (42).

Sex-Specific Differences
The influence of sex on regional metabolism and perfusion is somewhat controversial and is probably marginal, but a limited number of studies have addressed this issue with reasonable statistical accuracy (29,41).

In this study, we found discrete but significantly higher perfusion in the left anterior temporal cortex and orbitofrontal cortex in men; to our knowledge, these findings have not been described before. Higher cerebellar perfusion in men has been observed before (41), but it is unclear whether it was related to relative differences in cerebellar volume in other independent volumetric studies (34). On the basis of our study data in the same subjects, it is likely that both gray matter volume and perfusion in the cerebellar hemispheres are greater in men to an equal extent, and thus, functional differences are based on structural properties.

Women had higher perfusion in the right inferior parietal cortex; this finding is in accordance with the results of a study involving the use of 99mTc hexamethyl-propyleneamine oxime in 120 adult subjects aged 50–90 years (43). MR volumetric study findings have shown no sex-related difference in parietal cortex volume in healthy volunteers after correction for global hemispheric differences (44), in accordance with our VBM analysis results. It is known that men relatively excel at visuoconstructional tasks (45); this finding has been connected to the parietal cortex. Further studies may be warranted to investigate a tentative relationship to the observed differential functional perfusion demand during the resting state (43).

The trend toward increased right-side temporal gray matter concentration in women indicated by our VBM analysis results is in line with the results of other recent MR volumetric studies (46,47); however, this finding is not in accordance with the results of a study with 465 healthy volunteers (48). In a histologic study (49), women had greater neuron concentration bilaterally in the planum temporale of the posterior temporal cortex. The physiologic implications of these findings, however, remain indeterminate and require further investigation.

Methodological Aspects and Study Limitations
There are a few issues concerning the use of VBM in this study that need addressing. First, since proportional scaling was used for global normalization of voxel values, a constant relationship between gray matter concentration and perfusion in each brain region was implicitly assumed. This also led to a proportional scaling of the error variance, which is a requirement for studying interaction effects. This assumption is reasonable since under normal circumstances, tracer uptake is proportional to local gray matter volume.

Second, the most important possible confounding factor in the direct comparison between perfusion and gray matter concentration is the risk of spillover effects between gray and white matter (24). Non–gray matter was given a value of zero at VBM, so no account was given to the contribution from spill in from white matter with regard to perfusion. for. It is known that white matter perfusion is approximately one-third to one-fourth of gray matter (8), and a more sophisticated approach would incorporate a linear combination of gray matter, white matter, and possibly CSF segmented image partitions. Whether underestimation of white matter perfusion spill in is an explanation for the apparently preserved 99mTc ECD uptake relative to gray matter volume in some regions may depend on the local tissue characteristics. Cortical spill-in effects should be relatively homogeneous, except in regions where more gray matter is present, such as the periinsular area. If present, however, such confounding effects are not expected to invalidate the observed asymmetric effect in the right anterior regions.

Third, the uptake pattern of 99mTc ECD is known to be nonlinear with respect to true blood flow, especially in high-perfusion areas such as the visual cortex (50), and as a consequence, activation or age-related changes may be less pronounced in these regions. Therefore, the observed finding that 99mTc ECD uptake decreases less than does atrophy in the occipital area may be at least partly confounded by the saturation effect in the relation between 99mTc ECD uptake and perfusion.

Finally, in this study, only indirectly partial volume effects were studied. A more rigid approach to correction for underlying changes would involve voxel-based partial volume correction. However, to our knowledge, such methods have not been established and well validated in static clinical SPECT or PET data (19,20) and therefore were not attempted in the current investigation. Apart from the underlying physiologic implications, the results of this study indicate the absolute necessity to interpret functional SPECT data in light of structural changes to obtain nondistorted analysis data with maximal sensitivity.


    FOOTNOTES
 
Abbreviations: CSF = cerebrospinal fluid space, ECD = ethylene cysteine dimer, MPRAGE = magnetization preparation rapid acquisition gradient-echo, SPM = statistical parametric mapping, VBM = voxel-based morphometry

Author contributions: Guarantors of integrity of entire study, K.J.V.L., R.A.D.; study concepts and design, K.J.V.L.; literature research, K.J.V.L.; clinical and experimental studies, K.J.V.L.; data acquisition and analysis/interpretation, K.J.V.L.; statistical analysis, K.J.V.L.; manuscript preparation, K.J.V.L.; manuscript definition of intellectual content, K.J.V.L., R.A.D.; manuscript editing, K.J.V.L.; manuscript revision/review and final version approval, K.J.V.L.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Bailey DL. Transmission scanning in emission tomography. Eur J Nucl Med 1998; 25:774-787.
  2. Hashimoto J, Kubo A, Ogawa K, et al. Scatter and attenuation correction in technetium-99m brain SPECT. J Nucl Med 1997; 38:157-162.
  3. Patterson JC, Early TS, Martin A, et al. SPECT image analysis using statistical parametric mapping: comparison of technetium-99m-HMPAO and technetium-99m-ECD. J Nucl Med 1997; 38:1721-1725.
  4. Matthew E, Hill TC. Brain mapping with single photon emission CT. Radiology 1998; 206:483-489.
  5. Ebmeier KP, Glabus MF, Prentice N, Ryman A, Goodwin GM. A voxel-based analysis of cerebral perfusion in dementia and depression of old age. Neuroimage 1998; 7:199-208.
  6. Imran MB, Kawashima R, Awata S, et al. Parametric mapping of cerebral blood flow deficits in Alzheimer’s disease: a SPECT study using HMPAO and image standardization technique. J Nucl Med 1999; 40:244-249.
  7. Hyun Y, Lee JS, Rha JH, et al. Different uptake of 99mTc-ECD and 99mTc-HMPAO in the same brains: analysis by statistical parametric mapping. Eur J Nucl Med 2001; 28:191-197.
  8. Baron JC, Godeau C. Human aging. In: Toga A, Mazziotta JC, eds. Brain mapping: the systems. San Diego, Calif: Academic Press, 2000; 591-604.
  9. Otte A. The importance of the control group in functional brain imaging (letter). Eur J Nucl Med 2000; 27:1420.
  10. Asenbaum S, Brücke T, Pirker W, Pietrzyk U, Podreka I. Imaging of cerebral blood flow with technetium-99m-HMPAO and technetium-99m-ECD: a comparison. J Nucl Med 1998; 39:613-618.
  11. Tanaka F, Vines D, Tsuchida T, Freedman M, Ichise M. Normal patterns on Tc-99m-ECD brain SPECT scans in adults. J Nucl Med 2000; 41:1456-1464.
  12. Van Laere K, Koole M, Versijpt J, et al. 99mTc-ECD brain perfusion SPET: variability, asymmetry and effects of age and gender in healthy adults. Eur J Nucl Med 2001; 28:873-887.
  13. Courchesne E, Chisum HJ, Townsend J, et al. Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology 2000; 216:672- 682.
  14. Autti T, Raininko R, Vanhanen SL, Kallio M, Santavuori P. MRI of the normal brain from early childhood to middle age. II. Age dependence of signal intensity changes on T2-weighted images. Neuroradiology 1994; 36:649-651.
  15. Matsumae M, Kikinis R, Morocz IA, et al. Age-related changes in intracranial compartment volumes in normal adults assessed by magnetic resonance imaging. J Neurosurg 1996; 84:982-991.
  16. Blatter DD, Bigler ED, Gale SD, et al. Quantitative volumetric analysis of brain MR: normative database spanning 5 decades of life. AJNR Am J Neuroradiol 1995; 16:241-251.
  17. Salonen O, Autti T, Raininko R, Ylikoski A, Erkinjuntti T. MRI of the brain in neurologically healthy middle-aged and elderly individuals. Neuroradiology 1997; 39:537-545.
  18. Labbé C, Froment JC, Kennedy A, Ashburner J, Cinotti L. Positron emission tomography metabolic data corrected for cortical atrophy using magnetic resonance imaging. Alzheimer Dis Assoc Disord 1996; 10:141-170.
  19. Strul D, Bendriem B. Robustness of anatomically guided pixel-by-pixel algorithms for partial volume effect correction in positron emission tomography. J Cereb Blood Flow Metab 1999; 19:547-559.
  20. Meltzer CC, Kinahan PE, Greer PJ, et al. Comparative evaluation of MR-based partial-volume correction schemes for PET. J Nucl Med 1999; 40:2053-2065.
  21. Wright IC, McGuire PK, Poline JB, et al. A voxel-based method for the statistical analysis of gray and white matter density applied to schizophrenia. Neuroimage 1995; 2:244-252.
  22. Ashburner J, Friston K. Voxel-based morphometry: the methods. Neuroimage 2000; 11:805-821.
  23. Van Laere K, Koole M, Versijpt J, et al. Transfer of normal 99mTc-ECD brain SPET databases between different gamma cameras. Eur J Nucl Med 2001; 28:435-449.
  24. Richardson MP, Friston KJ, Sisodiya SM, et al. Cortical grey matter and benzodiazepine receptors in malformations of cortical development: a voxel-based comparison of structural and functional imaging data. Brain 1997; 120:1961-1973.
  25. Büchel C, Wise RJS, Mummery CJ, Poline JB, Friston KJ. Nonlinear regression in parametric activation studies. Neuroimage 1996; 4:60-66.
  26. Van Bogaert P, Wikler D, Damhaut P, Szliwowski HB, Goldman S. Regional changes in glucose metabolism during brain development from the age of 6 years. Neuroimage 1998; 8:62-68.
  27. Friston KJ, Holmes AP, Worsley KJ, et al. Statistical parametric maps in functional imaging: a general linear approach. Hum Brain Mapp 1995; 2:165-189.
  28. Martin AJ, Friston KJ, Colebatch JG, Frackowiak RS. Decreases in regional cerebral blood flow with normal aging. J Cereb Blood Flow Metab 1991; 11:684-689.
  29. Petit-Taboue MC, Landeau B, Desson JF, Desgranges B, Baron JC. Effects of healthy aging on the regional cerebral metabolic rate of glucose assessed with statistical parametric mapping. Neuroimage 1998; 7:176-184.
  30. Autti T, Raininko R, Vanhanen SL, Kallio M, Santavuori P. MRI of the normal brain from early childhood to middle age. I. Appearances on T2- and proton density–weighted images and occurrence of incidental high-signal foci. Neuroradiology 1994; 36:644-648.
  31. Goldstein S, Reivich M. Cerebral blood flow and metabolism in aging and dementia. Clin Neuropharmacol 1991; 14(suppl 1):S34-S44.
  32. Gunning-Dixon FM, Head D, McQuain J, Acker JD, Raz N. Differential aging of the human striatum: a prospective MR imaging study. AJNR Am J Neuroradiol 1998; 19:1501-1507.
  33. Murphy DG, DeCarli C, McIntosh AR, et al. Sex differences in human brain morphometry and metabolism: an in vivo quantitative magnetic resonance imaging and positron emission tomography study on the effect of aging. Arch Gen Psychiatry 1996; 53:585-594.
  34. Raz N, Dupuis JH, Briggs SD, McGavran C, Acker JD. Differential effects of age and sex on the cerebellar hemispheres and the vermis: a prospective MR study. AJNR Am J Neuroradiol 1998; 19:65-71.
  35. Luft AR, Skalej M, Schulz JB, et al. Patterns of age-related shrinkage in cerebellum and brainstem observed in vivo using three-dimensional MRI volumetry. Cereb Cortex 1999; 9:712-721.
  36. Anderson B, Rutledge V. Age and hemispheric effects on dendritic structure. Brain 1996; 119:1983-1990.
  37. Terry RD, DeTeresa R, Hansen LA. Neocortical cell counts in normal human adult aging. Ann Neurol 1987; 21:530-539.
  38. Peters A, Morrison JH, Rosene DL, Hyman BT. Feature article: are neurons lost from the primate cerebral?. Cereb Cortex 1998; 8:295-300.
  39. Meltzer CC, Cantwell MN, Greer PJ, et al. Does cerebral blood flow decline in healthy aging? A PET study with partial-volume correction. J Nucl Med 2000; 41:1842-1848.
  40. Markus HS, Ring H, Kouris K, Costa DC. Alterations in regional cerebral blood flow, with increased temporal interhemispheric asymmetries, in the normal elderly: an HMPAO SPECT study. Nucl Med Commun 1993; 14:628-633.
  41. Gur RC, Mozley LH, Mozley PD, et al. Sex differences in regional glucose metabolism during the resting state. Science 1995; 267:528-531.
  42. Thompson PM, Moussai J, Zohoori S, et al. Cortical variability and asymmetry in normal aging and Alzheimer’s disease. Cereb Cortex 1998; 8:492-509.
  43. Jones K, Johnson KA, Becker JA, et al. Use of singular value decomposition to characterize age and gender differences in SPECT cerebral perfusion. J Nucl Med 1998; 39:965-973.
  44. Coffey CE, Saxton JA, Ratcliff G, Bryan RN, Lucke JF. Relation of education to brain size in normal aging: implications for the reserve hypothesis. Neurology 1999; 53:189-196.
  45. Snow W, Weinstock J. Sex differences among non–brain-damaged adults on the Wechsler Adult Intelligence Scales: a review of the literature. J Clin Exp Neuropsychol 1990; 11:423-428.
  46. Bryant NL, Buchanan RW, Vladar K, Breier A, Rothman M. Gender differences in temporal lobe structures of patients with schizophrenia: a volumetric MRI study. Am J Psychiatry 1999; 156:603-609.
  47. Verchinski B, Meyer-Lindenberg A, Japee S, et al. Gender differences in gray matter density: a study of structural MRI images using voxel-based morphometry. Neuroimage 2000; 11:S228.
  48. Good C, Johnsrude I, Ashburner J, Friston K, Frackowiak R. Voxel based morphometry of 465 normal adult human brains (abstr). Neuroimage 2000; 11:S607.
  49. Witelson SF, Glezer II, Kigar DL. Women have greater density of neurons in posterior temporal cortex. J Neurosci 1995; 15:3418-3428.
  50. Tsuchida T, Yonekura Y, Nishizawa S, et al. Nonlinearity correction of brain perfusion SPECT based on permeability-surface area product model. J Nucl Med 1996; 37:1237-1241.



This article has been cited by other articles:


Home page
AJGPHome page
S. Paradiso, J. G. Vaidya, L. M. McCormick, A. Jones, and R. G. Robinson
Aging and Alexithymia: Association With Reduced Right Rostral Cingulate Volume
Am J Geriatr Psychiatry, September 1, 2008; 16(9): 760 - 769.
[Abstract] [Full Text] [PDF]


Home page
J. Neurosci.Home page
N. Villain, B. Desgranges, F. Viader, V. de la Sayette, F. Mezenge, B. Landeau, J.-C. Baron, F. Eustache, and G. Chetelat
Relationships between Hippocampal Atrophy, White Matter Disruption, and Gray Matter Hypometabolism in Alzheimer's Disease
J. Neurosci., June 11, 2008; 28(24): 6174 - 6181.
[Abstract] [Full Text] [PDF]


Home page
BrainHome page
G. Chetelat, B. Desgranges, B. Landeau, F. Mezenge, J. B. Poline, V. de la Sayette, F. Viader, F. Eustache, and J.-C. Baron
Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer's disease
Brain, January 1, 2008; 131(1): 60 - 71.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
L. Marti-Bonmati, J. J. Lull, G. Garcia-Marti, E. J. Aguilar, D. Moratal-Perez, C. Poyatos, M. Robles, and J. Sanjuan
Chronic Auditory Hallucinations in Schizophrenic Patients: MR Analysis of the Coincidence between Functional and Morphologic Abnormalities
Radiology, August 1, 2007; 244(2): 549 - 556.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
V. H. ten Dam, D. M. J. van den Heuvel, A. J. M. de Craen, E. L. E. M. Bollen, H. M. Murray, R. G. J. Westendorp, G. J. Blauw, and M. A. van Buchem
Decline in Total Cerebral Blood Flow Is Linked with Increase in Periventricular but Not Deep White Matter Hyperintensities
Radiology, April 1, 2007; 243(1): 198 - 203.
[Abstract] [Full Text] [PDF]


Home page
JSLHRHome page
M. D. Devous Sr., D. Altuna, N. Furl, W. Cooper, G. Gabbert, W. T. Ngai, S. Chiu, J. M. Scott III, T. S. Harris, J. K. Payne, et al.
Maturation of Speech and Language Functional Neuroanatomy in Pediatric Normal Controls.
J Speech Lang Hear Res, August 1, 2006; 49(4): 856 - 866.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Neuroradiol.Home page
A.-S. Pirson, T. Vander Borght, K. Van Laere, K. Takahashi, and S. Yamaguchi
Age and Gender Effects on Normal Regional Cerebral Blood Flow
AJNR Am. J. Neuroradiol., June 1, 2006; 27(6): 1161 - 1163.
[Full Text] [PDF]


Home page
StrokeHome page
V. H. ten Dam, F. M.A Box, A. J.M. de Craen, D. M.J. van den Heuvel, E. L.E.M. Bollen, H. M. Murray, M. A. van Buchem, R. G.J. Westendorp, G. Jan Blauw, and on behalf of the PROSPER Study Group
Lack of Effect of Pravastatin on Cerebral Blood Flow or Parenchymal Volume Loss in Elderly at Risk for Vascular Disease
Stroke, August 1, 2005; 36(8): 1633 - 1636.
[Abstract] [Full Text] [PDF]


Home page
NeurologyHome page
A. F. Fotenos, A. Z. Snyder, L. E. Girton, J. C. Morris, and R. L. Buckner
Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD
Neurology, March 22, 2005; 64(6): 1032 - 1039.
[Abstract] [Full Text] [PDF]


Home page
JNMHome page
H. Matsuda, T. Ohnishi, T. Asada, Z.-j. Li, H. Kanetaka, E. Imabayashi, F. Tanaka, and S. Nakano
Correction for Partial-Volume Effects on Brain Perfusion SPECT in Healthy Men
J. Nucl. Med., August 1, 2003; 44(8): 1243 - 1252.
[Abstract] [Full Text] [PDF]


Home page
J. Neurol. Neurosurg. PsychiatryHome page
G B Frisoni, C Testa, A Zorzan, F Sabattoli, A Beltramello, H Soininen, and M P Laakso
Detection of grey matter loss in mild Alzheimer's disease with voxel based morphometry
J. Neurol. Neurosurg. Psychiatry, December 1, 2002; 73(6): 657 - 664.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
2213010295v1
221/3/810    most recent
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Van Laere, K. J.
Right arrow Articles by Dierckx, R. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Van Laere, K. J.
Right arrow Articles by Dierckx, R. A.


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
RADIOLOGY RADIOGRAPHICS