Quantitative measurement to evaluate morphological changes of the corpus callosum in patients with subcortical ischemic vascular dementia

Abstract

Background

Subcortical ischemic vascular dementia (SIVD) is a subtype of dementia associated with abnormalities in the subcortical white matter regions. Recent imaging techniques can be used to detect such abnormalities in vivo.

Purpose

To examine morphological changes of the corpus callosum in patients with SIVD by using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI).

Material and Methods

MRI was performed to explore changes of cerebral white matter, especially corpus callosum. Brain matter diffusivity was examined with DTI by measuring the fractional anisotropy (FA). Results of 30 patients diagnosed with SIVD and 30 healthy subjects were analyzed and compared.

Results

The thicknesses of the genu, the anterior third, middle, and posterior third of the body, and the splenium of the corpus callosum were smaller in SIVD patients compared to healthy controls (0.54 ± 0.08 vs. 0.68 ± 0.09 cm, P = 0.0011; 0.27 ± 0.06 vs. 0.38 ± 0.07 cm, P = 0.002; 0.28 ± 0.05 vs. 0.38 ± 0.08 cm, P = 0.009; 0.18 ± 0.04 vs. 0.26 ± 0.06 cm, P = 0.013; 0.54 ± 0.07 vs. 0.72 ± 0.09 cm, P = 0.003, respectively). The FA values of the genu and splenium of the corpus callosum in patients with SIVD were decreased compared to healthy controls (0.664 ± 0.042 vs. 0.778 ± 0.041, P < 0.001; 0.691 ± 0.038 vs. 0.786 ± 0.039, P = 0.001, respectively).

Conclusion

Patients with SIVD exhibit corpus callosum atrophy and morphological changes, and these characteristics may be useful for diagnosis.

Keywords

Subcortical ischemic vascular dementia (SIVD)corpus callosum diffusion tensor imaging (DTI)

Introduction

As the second most common type of dementia, vascular dementia (VD) encompasses a heterogeneous group of cognitive impairments caused by various cerebrovascular lesions. Subcortical ischemic vascular dementia (SIVD) is a subtype of dementia that accounts for 36–67% of all cases of VD (1). SIVD originates from ischemic microvascular diseases in the brain (2 –5). Clinical features of SIVD include: (i) acute sensory-movement disorder caused by lacunar infarction; and (ii) cognitive impairment, personality change, emotional changes, gait disturbance, and movement disorder in the sub-acute stage. Cognitive disorders of SIVD mainly present as executive dysfunctions caused by frontal lobe dysfunctions, rather than severe dementia syndrome. Other cortical functions, such as language and calculation, are preserved. The ischemic changes manifest as high signal intensities in white matter on T2-weighted (T2W) magnetic resonance imaging (MRI). The clinical impact of white matter ischemia in patients with SIVD has been well studied (6 –9).

Although a definitive diagnosis of dementia requires autopsy (10), recent advances in neuroimaging have enabled the earlier diagnosis of various types of dementia. SIVD is associated with abnormalities in the subcortical white matter regions, which can be detected by MRI (11). Recent MRI technologies have enabled the assessment of the white matter integrity in vivo. For example, diffusion tensor imaging (DTI) is a functional MRI approach that can be used to examine the microstructural integrity of the white matter (12,13). The fractional anisotropy (FA) parameter quantitatively reflects the directional averaged diffusion. Patients with dementia reportedly show microscopic changes in their white matter by DTI (14,15).

The corpus callosum is an important myelinated axonal relay that connects the cortical-cortical and cortical-subcortical areas between two cerebral hemispheres. The aim of this study was to identify morphological changes of different regions of the corpus callosum in patients with SIVD by using combined DTI with conventional MRI sequences.

Material and Methods

This study was approved by the ethics committee of the university hospital. All of the recruited subjects provided their written informed consent. From March 2006 to June 2009, 30 patients who were diagnosed with SIVD were prospectively enrolled in this study (mean age, 65.3 ± 5.9 years; 17 men). SIVD was diagnosed according to the criteria of the National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer Disease and Related Disorders Association (NINCDS-ADRDA) (11) by two senior psychiatrists. The inclusion criteria for SIVD were: (i) 30-point Mini Mental State Examination (MMSE) score <24; (ii) Hachinski Ischemic Score (HIS) >7. Patients with other types of dementia, psychiatric disease, or who consumed alcohol were excluded from the study.

Thirty healthy adult subjects were recruited as healthy controls (mean age, 63.9 ± 5.3 years; 16 men). The healthy subjects all had MMSE ≥ 24 and reported no complaints of decreased memory, history of cognitive impairment, neurological, or psychological diseases.

MRI acquisition

The MR images were acquired with a 1.5-Tesla GE Excite MRI system (GE Healthcare, Milwaukee, WI, USA). For each subject, routine whole-brain MRI scans were performed, including axial T2W imaging (TR/TE, 5600/90; slice thickness, 5 mm), axial fluid-attenuated inversion recovery (FLAIR) (TR/TI/TE, 9000/2250/85; slice thickness, 5 mm), and coronal 3D T1-weighted (T1W) imaging with an inversion-prepared spoiled gradient echo (IR-SPGR) sequence (TR/TE/flip angle, 10.5/2.2/15°; slice thickness, 1.5 mm).

For DTI acquisition, single-shot spin-echo (SE) EPI acquisition was used with 25 uniformly distributed gradient directions (TR/TE, 6000/90 ms; b-value, 1000 s/mm²; NEX, 2). Twenty-four contiguous axial slices were acquired with a slice thickness of 5 mm, 128 × 128 matrix, and field of view of 24 × 24 cm. The slices were positioned to run parallel to the anterior and posterior commissural planes. The total acquisition time was 5 min 40 s.

Measurement of corpus callosum size

The thicknesses of regions of the corpus callosum, including the genu, the anterior third, middle, posterior third of the body, and the splenium, were measured by sagittal SE T1W imaging (Fig. 1 a–c).

Fig. 1.

Maximum sagittal diameter (a). Area of the brain and the corpus callosum (b) and thickness of the genu (CX), the anterior third (GH), middle (EZ), and posterior third (MN) of the body, and the splenium (DY) of the corpus callosum (c) by sagittal imaging.

DTI measurement and analysis

The postprocessing of the DTI data was performed on a GE workstation (FuncTool, Advantage Workstation 4.2, GE Healthcare, Milwaukee, WI, USA). The EPI distortion was automatically corrected by scaling, shearing, and translating each image to align it with the reference image (b = 0). The goal of this process was to minimize the mismatch between the diffusion and reference images.

The FA images were computed and displayed together with the reference image. The FA was measured at different locations of the corpus callosum through a region of interest (ROI)-based analysis. The rater placed ROIs (size, 28–32 mm²) at the genu and splenium of the corpus callosum (Fig. 2). The ROIs were selected from images acquired without diffusion gradients (b = 0 s/mm²). Each subject’s ROIs were transferred onto the FA images to avoid selection bias from different DTI parameters.

Fig. 2.

Measurement of the fractional anisotropy (FA) of the genu and splenium of the corpus callosum.

To eliminate the effects of the cerebrospinal fluid (CSF) and gray matter on the image, partial volume averaging from the CSF space or gray matter structure was reduced by placing an ovoid sphere in the center of the target white matter. The ROI size was gradually adjusted (8–12 pixels), to avoid reaching the CSF space or gray matter. In the case of the corpus callosum atrophy, the long axis of the ovoid sphere was aligned along with the direction of the fiber tract. A small, slender ROI (e.g. 2 × 4 pixels) was created to avoid partial volume effects. This method takes advantage of ovoid spherical ROIs of variable sizes.

Quality control

All of the measurements were performed by two senior radiologists who had received intensive initial training. Every structure was measured three times, and the mean value was used for analysis. The Kappa value of inter-rater variability was >0.79. To eliminate subjective errors, the neuroradiologist who performed all analyses was blinded to the clinical diagnosis of the subjects.

Statistical methods

To validate the thickness and area in different patients, the following equations were used: validated thickness = (measured thickness/maximal brain sagittal diameter) × 10; validated area = (measured area / maximal brain sagittal area) × 10. The thickness and FA values were presented as the mean ± SD. SPSS13.0 software (SPSS Inc., Chicago, IL, USA) was used for data analysis. The mean values of the two groups were compared with ANOVA. The mean measurements of each part of the corpus callosum were compared using the independent sample t-test. Differences with P < 0.05 were regarded as statistically significant.

Results

As shown in Table 1, the thicknesses of different regions of the corpus callosum, including the genu, the anterior third, middle, and posterior third of the body, and the splenium, were smaller in patients with SIVD than in healthy controls. The mean validated area of the corpus callosum in patients with SIVD (4.67 ± 0.39 cm²) was smaller than that in healthy controls (5.93 ± 0.48 cm²; P < 0.05). Independent t-tests revealed that the thickness differences in different regions of the corpus callosum between the two groups were significant (all P < 0.05). The areas of the corpus callosum also showed significant differences between the two groups (all P < 0.05).

Table 1.

Thickness (cm) of different regions of the corpus callosum in healthy control and patients with SIVD.

Group/Parameter	Region of the corpus callosum
Group/Parameter	Genu	Anterior third of body	Middle of the body	Posterior third of the body	Splenium
Control	0.68 ± 0.09	0.38 ± 0.07	0.38 ± 0.08	0.26 ± 0.06	0.72 ± 0.09
SIVD	0.54 ± 0.08	0.27 ± 0.06	0.28 ± 0.05	0.18 ± 0.04	0.54 ± 0.07
F value	12.514	9.323	8.612	6.737	11.923
P value	0.011	0.002	0.009	0.013	0.007

Table 2 reports the FA values of the genu and splenium of the corpus callosum in patients with SIVD and healthy controls. Patients with SIVD showed significantly lower FA values in the genu and splenium of the corpus callosum compared with healthy controls.

Table 2.

FA of the genu and splenium of the corpus callosum in healthy control and patients with SIVD.

Control	SIVD	t value	P value
Genu	0.778 ± 0.041	0.664 ± 0.042	–2.381	0.000
Splenium	0.786 ± 0.039	0.691 ± 0.038	–3.437	0.001

Discussion

The results of the current study indicate that SIVD patients have significantly reduced corpus callosum size compared with healthy controls. This corpus callosum atrophy can be detected by MRI.

Callosal changes due to the brain atrophy have been characterized in Alzheimer’s disease (AD) (16,17), multiple sclerosis (17), and Huntington disease (18). The corpus callosum is vulnerable to diffuse axonal injury and atrophy after brain traumas (19). Atrophy of the corpus callosum is also associated with AD (12), VD (20), and cognitive and motor deficits in the elderly (21). Thus, we hypothesized that the thickness of the corpus callosum in different sections measured by MRI may reflect the changes of the corpus callosum in SIVD. To the best of our knowledge, this is the first study to explore the role of callosal tissue loss in patients with SIVD. Our findings showed that the size of the corpus callosum, based on the thickness of its different regions, is reduced in patients with SIVD.

Regarding differences in the corpus callosum size between SIVD patients and healthy controls, special attention should be paid to the quantitative morphological analysis of the mid-sagittal corpus callosum. The size and shape of this region show considerable interindividual variability. Gender may also influence the size of the corpus callosum (22). These confounders should be considered when interpreting the quantitative analyses of the corpus callosum.

The present study showed that the reduced thickness of the corpus callosum in patients with SIVD compared to healthy controls and the degree of atrophy were different in different sections, which indicates that the different regions of the corpus callosum are reduced unevenly and the morphology is changed in SIVD. Findings about the area in the corpus callosum of patients with VD have been controversial (23 –25). Lyoo et al. reported different patterns of regional corpus callosum area loss in subjects with AD and multi-infarct dementia (25). Pantel et al. investigated atrophic alterations in different regions of the corpus callosum in AD and VD with respect to clinical changes, and found that the total callosal size was significantly reduced in AD but not in VD. Furthermore, the most rostral regions of the corpus callosum were significantly smaller in AD when compared to controls. Again, these changes were not found in patients with VD (23).

Another finding of the present study was that the FA values in the genu and splenium of the corpus callosum of SIVD patients are reduced significantly compared with healthy controls. Thus, the DTI sequence may aid in the detection of SIVD. The reduced FA value on DTI indicates that corpus callosum atrophy in AD may be caused by an interhemispheric disconnection, namely Wallerian degeneration of interhemispheric commissural nerve fibers originating from pyramidal neurons in the cerebral cortex, which has been verified by neuroimaging studies. Tomimoto et al. found that the corpus callosum atrophy is correlated with the brain atrophy in AD, which is relevant to the mechanism of interhemispheric disconnection, while focal ischemic injuries cannot be ruled out (20).

Our study has some limitations. A relatively small number of patients were included in the study. Aging and gender may affect the morphological change of the corpus callosum, but their possible effects were not addressed because of the small sample size. We used a cross-sectional approach to compare the size and FA values between patients with SIVD and healthy controls; however, this method does not take into account the effect of age and its relationship with imaging under different grading conditions. To explore the role of the corpus callosum in SIVD, additional prospective studies enrolling more subjects should be performed.

In conclusion, this study demonstrated the atrophy and morphological changes of the corpus callosum in SIVD. These findings suggest that neuroimaging may be helpful for detecting SIVD.

Footnotes

Acknowledgements

This project was supported by the Shannxi Science and Technology Department (2008K11-020).

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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