- Email: [email protected]
Effects of gender and age on anterior commissure volume
Neuroscience Letters 500 (2011) 92–94
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Effects of gender and age on anterior commissure volume Mi-Hyun Choi a , Ji-Hye Kim a , Hong-Won Yeon a , Jin-Seung Choi a , Jang-Yeon Park a , Jae-Hoon Jun a , Beob-Yi Lee b , Hyun-Jun Kim c , Gye-Rae Tack a , Soon-Cheol Chung a,∗ a Department of Biomedical Engineering, Research Institute of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, 322 Danwall-dong, Chungju, Chungbuk 380-701, South Korea b Department of Anatomy, School of Medicine, Konkuk University, Seoul, South Korea c Department of Obstetrics & Gynecology, Konkuk University, Chungju, South Korea
a r t i c l e
i n f o
Article history: Received 12 April 2011 Received in revised form 1 June 2011 Accepted 5 June 2011 Keywords: Anterior commissure volume Age Gender Volumetry
a b s t r a c t The purpose of this study was to measure the average anterior commissure (AC) volume of normal subjects in their 20s or 40s and to determine the effects of gender and age on AC volume. Magnetic resonance brain images were obtained for 93 people in their 20s (46 men, 47 women) and 87 in their 40s (36 men, 51 women). To investigate the effect of gender and age on AC volume, two-way analysis of variance, which used gender (two levels) and age (two levels) as independent variables, was employed. For subjects in their 20s, there was no difference in AC volume between genders, but for those in their 40s, the AC volume of males was less than that of females. There was no difference in AC volume between females in their 20s or 40s; however, the AC volume of men in their 40s was less than that for those in their 20s. There were gender-influenced differences in AC volume changes related to aging. © 2011 Elsevier Ireland Ltd. All rights reserved.
The human cerebrum consists of two hemispheres, and sensory information such as visual, auditory, and olfactory sensation is exchanged by bundles called the anterior commissure (AC) and posterior commissure (PC), which participate in interhemispheric transfer [9,23,28]. Identification of the AC is critical because it is an important brain structure because its location is crucial for performing stereotactic and functional neurosurgery, localization analysis in human brain mapping, medical image analysis, structure segmentation, and labeling in neuroradiology as well as in registration to reduce the number of degrees of freedom [15,21,22]. The Talairach transformation based on the AC also is widely used in human brain mapping for comparing brain structure and function across subjects [16]. Studies concerning the structural properties of the AC are typically conducted in patients, and the area and size of the AC are commonly measured using cross-sectional images. The area of the AC was shown to decrease in response to trauma, traumatic brain injury, or hypoxic stress [12,25,29]. Moon et al. [20] measured AC area and thickness of both normal subjects and patients with neurodegenerative condition, they reported that AC area and thickness of patients with Alzheimer disease and frontotemporal dementia was smaller than those of normal subjects [20].There have been few reports describing the AC area and volume in healthy subjects,
∗ Corresponding author. Tel.: +82 43 840 3759; fax: +82 43 851 0620. E-mail address: [email protected] (S.-C. Chung). 0304-3940/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2011.06.010
thus it is difficult to draw reliable conclusions on the influence of gender [1,8,12]. Further, few studies address AC volume changes in response to aging. Volume information of various brain structures can be used for clinical purposes by comparing unhealthy volumes to standard volumes determined from healthy subjects. Thus, it is of clinical significance to obtain information related to the average AC volumes of healthy subjects. Therefore, this study characterizes the average AC volume by measuring the AC volume of healthy Korean subjects in their 20s and 40s, and it also analyzed AC volume differences associated with gender and aging. A total of 180 healthy Korean subjects (in their 20s or 40s), who had no previous brain damage or head injuries and did not have any medical problems, as confirmed by neurospecialists, were selected for this study. The number of subjects in their 20s was 93 (average age = 23.0 ± 2.6 years), and the group consisted of 46 males (average age = 24.0 ± 2.8 years) and 47 females (average age = 21.9 ± 2.1 years). The number of subjects in their 40s was 87 (average age = 47.5 ± 3.7 years), and the group consisted of 36 males (average age = 48.9 ± 3.9 years) and 51 females (average age = 46.7 ± 3.4 years). MRI measurements were conducted using a 3.0-T FORTE machine (ISOL Technology, Korea) equipped with whole-body gradients and a quadrature head coil. T1-weighted brain images were obtained with a three-dimensional, magnetization-prepared, rapid-gradient echo sequence (TR/TE/TI = 10/4/100 ms; slice thickness = 1.5 mm; field of view = 220 mm × 192 mm × 192 mm;
M.-H. Choi et al. / Neuroscience Letters 500 (2011) 92–94
93
Fig. 1. (a) Segmentation of the anterior commissure in a cross-sectional image. (b) Three-dimensional reconstruction of the anterior commissure.
number of slices = 128; slice gap = 0; matrix size = 256 × 224 × 128; and number of excitations (NEX) = 2). The anterior commissure (AC) region was manually segmented, and its volume was measured by a neuroanatomist using Brain Voyager 2000 (Brain Innovation BV, Germany) software. After MR image acquisition, the image was reconstructed for use in image post-processing using Brain Voyager 2000. Any irregularity in image brightness along each slice, can potentially introduce errors when using segmentation procedures based on image brightness. To compensate for this problem, inhomogeneity correction based on the brightness of white matter was conducted for all axial, sagittal, and coronal planes. A Gaussian smoothing filter was used to increase the signal to noise ratio (SNR) and a sigma filter to improve the image contrast. The manual segmentation was performed by one of the authors, who has sufficient neuroanatomical knowledge for processing boundary and detailed regions properly. After designating the regions of interest (ROI), the AC volume in each slice was determined by multiplying the area of the ROI by slice thickness, and the entire volume of the AC was calculated by summing its volume in each slice [4,5,17]. Fig. 1(a) shows the segmented image of the two-dimensional AC region in a cross-sectional image and Fig. 1(b) shows the three-dimensional, reconstructed image based on the segmented AC region. Covariance analysis, a normalization method, was used to normalize the AC volume based on intracranial volume (ICV) [17,24]. ICV was calculated using cerebral size, i.e., cerebral width, height, and length (Eq. (1)) [6,11,27]: ICV (cc) =
4 length width height ∗∗ ∗ ∗ 3 2 2 2
(1)
It was well-known that there was a relationship between education period and brain structure volume [7,26]. Therefore to investigate the effect of gender and age on the normalized AC volume, two-way analysis of variance (ANOVA), which used a period of education as a covariance variable, gender (two levels) and age (two levels) as independent variables, and AC volume as a dependent variable, was completed using SPSS software (v. 18.0). When an interactive effect among variables was observed, major variables
Fig. 2. Interactive effect between age and gender on anterior commissure volume.
influencing AC volume were determined with simple main effect analysis. Table 1 shows the average AC volume based on gender and ages (subjects in their 20s or 40s). Two-way ANOVA showed that there was no difference between genders, but there was a significant difference between the age groups. The AC volume of subjects in their 40s (0.65 ± 0.15 cm3 ) was significantly smaller than that of those in their 20s (0.74 ± 0.18 cm3 ) (p = .005). Since there was an interactive effect between gender and age (p = .004), there was a difference in AC volume related to gender as the age increased. As age increased, the AC volume of females did not change significantly, but that of the male decreased (Fig. 2). To analyze this interactive effect, simple main effect analysis was performed. Independent t-test of the gender groups (both 20s and 40s) showed that there was no significant difference between the AC volume of males and female in their 20s, but the AC volume of males was significantly smaller than that of females in their 40s (p = .005). Independent t-test of age (both male and female) showed that the AC volume of subjects in their 40s was significantly smaller than that of male subjects in their 20s
Table 1 The mean, minimum, and maximum anterior commissure volumes (cm3 ) by gender and age. Age
Male
Female
Male + female
Mean ± S.D.
Min.
Max.
Mean ± S.D.
Min.
Max.
Mean ± S.D.
Min.
Max.
20s 40s
0.76 ± 0.21 0.60 ± 0.14
0.36 0.30
1.19 0.90
0.70 ± 0.14 0.69 ± 0.16
0.45 0.33
1.02 1.25
0.74 ± 0.18 0.65 ± 0.15
0.36 0.30
1.19 1.25
Total
0.71 ± 0.20
0.30
1.19
0.70 ± 0.15
0.33
1.25
0.70 ± 0.18
0.30
1.25
94
M.-H. Choi et al. / Neuroscience Letters 500 (2011) 92–94
(p < .001), but there was no significant difference between the AC volume of those in their 20s and those of their 40s in females. This study measured AC volume of healthy Korean subjects in their 20s and 40s, and it analyzed the differences in AC volume due to gender and aging. Elisabeth et al. [10] reported that the AC volume of healthy 12 year-old children was 0.04 cm3 . After measuring the AC area in the mid-sagittal plane of postmortem brains in normal subjects (n = 30), Allen and Gorski [1,2] reported that the AC area of males was less than that of females. Highley et al. [12] measured the AC area of normal subjects (male and female) in their 70s, but there was no significant difference between genders. As discussed previously, there have been few reports characterizing the AC area and volume of healthy subjects, but the reports are insufficient, and thus, it is difficult to draw reliable conclusions due to the effect of gender. Until now, there have been no reports related to the change in AC volume due to aging. It is well known that cerebral white matter volume generally decreases with age [14,18,19,28]. There was a significant loss in small diameter myelinated fibers in the older group in addition to atrophy of white matter volume. Therefore, the volume of the white matter and the volume of the myelinated fibers in the aging group were lower than those in the younger group [28]. There have been reports that the corpus callosum volume, a region of white matter, was larger in males than in females; however, until subjects reach their 70s, there was no atrophy due to aging [3,13,17,27]. The results showed that there was no difference in the AC volume between male and female subjects in their 20s. There was no age-related difference in AC volume for females, but there was a significant atrophy in the AC volume of males. Thus, for males in their forties, the AC volume was significantly smaller than that of females, which suggests a gender-based difference in AC volume patterns due to age. Therefore, it is expected that white matter volume change due to the aging be different by the region as well as by the gender. The reason for these gender-influenced differences due to aging is unclear, but they may be attributed to internal (such as sex hormones) and external factors (family circumstances and habits, such as smoking and drinking) [30]. To further investigate the effect of aging on AC volume change according to gender, it is necessary to analyze the AC volume of various age groups and to perform additional physiological and biological analyses concurrently. Manual ROI measurement method can induce operator dependent errors. However in this study, manual ROI measurement was carried out by neuro-anatomical expert to do exact segmentation of the boundary of AC region, and AC volume was measured for 180 subjects. Thus it is believed that operator dependent error be not quite large. Although in this study participants were males and females in their 20s and 40s, this study provides valuable information on the effects of gender and age on AC volume. It is expected that the results of this study will be used as basic research material for the understanding and diagnosis of brain and mental diseases like trauma and schizophrenia, which are closely related to AC atrophy. Acknowledgement This work was supported by Konkuk University in 2011. References [1] L.S. Allen, R.A. Gorski, Sexual dimorphism of the anterior commissure and massa intermedia of the human brain, J. Comp. Neurol. 312 (1991) 97–104. [2] L.S. Allen, R.A. Gorski, Sexual orientation and the size of the anterior commissure in the human brain, Neurobiology 89 (1992) 7199–7202.
[3] J.S. Allen, H. Damasio, T.J. Grabowski, J. Bruss, W. Zhang, Sexual dimorphism and asymmetries in the gray–white composition of the human cerebrum, NeuroImage 18 (2003) 880–894. [4] S.C. Chung, B.Y. Lee, G.R. Tack, S.Y. Lee, J.S. Eom, J.H. Sohn, Effects of age, gender, and weight on the cerebellar volume of Korean people, Brain Res. 1042 (2005) 233–235. [5] S.C. Chung, G.R. Tack, J.H. Yi, B. Lee, M.H. Choi, B.Y. Lee, S.Y. Lee, Effects of gender, age, and body parameters on the ventricular volume of Korean people, Neurosci. Lett. 395 (2006) 155–158. [6] S.C. Chung, M.H. Choi, B. Lee, G.R. Tack, J.H. Jun, J.R. Park, B.C. Min, B.G. Park, A study on the cerebral sizes of Koreans in their 20s and 40s, Int. J. Neurosci. 118 (2008) 1711–1724. [7] C.E. Coffey, J.A. Saxton, G. Ratcliff, R.N. Bryan, J.F. Lucke, Relation of education to brain size in normal aging: implications for the reserve hypothesis, Neurology 53 (1) (1999) 189–196. [8] S. Demeter, J.L. Ringo, R.W. Doty, Morphometric analysis of the human corpus callosum and anterior commissure, Hum. Neurobiol. 6 (4) (1988) 219–226. [9] S. Demeter, D.L. Rosene, G.W. Goesen, Fields of origin and pathways of the interhemispheric commissures in the temporal lobe of macaques, J. Comp. Neurol. 302 (1990) 29–53. [10] A.W. Elisabeth, D.B. Erin, M.H. Janelle, C. Zili, S.L. Harvey, L. Xiaoqi, V.H. Jill, Vulnerability of the anterior commissure in moderate to severe pediatric traumatic brain injury, J. Child. Neurol. 21 (2006) 769–776. [11] S.L. Free, P.S. Bergin, D.R. Fish, M.J. Cook, S.D. Shorvon, J.M. Stevens, Methods for normalization of hippocampal volumes measured with MR, Am. Soc. Neuroradiol. 16 (1995) 637–643. [12] J.R. Highley, M.M. Esiri, B. McDonald, H.C. Roberts, M.A. Walker, T.J. Crow, The size and fiber composition of the anterior commissure with respect to gender and schizophrenia, Soc. Biol. Psychiatry 45 (1999) 1120–1127. [13] S.C. Johnson, T. Farnworth, J.B. Pinkston, E.D. Bigler, D.D. Blatter, Corpus callosum surface area across the human adult life span: effect of age and gender, Brain Res. Bull. 35 (1994) 373–377. [14] B.W. Kristine, M.F. Anders, R. Ivar, L. Arvid, M.D. Anders, E.E. Dag, T.Q. Brian, S. David, M. Nikos, F. Bruce, Effects of age on volumes of cortex, white matter and subcortical structures, Neurobiol. Aging 26 (2005) 1261–1270. [15] A.L.T. Lacerda, A.Y. Hardan, O. Yorbik, M.S. Keshavan, Measurement of the orbitofrontal cortex: a validation study of a new method, NeuroImage 19 (2003) 665–673. [16] J.L. Lancaster, P.T. Fox, Talairach Space as a Tool for Intersubject Standardization in the Brain, Academic Press, San Diego, 2000, pp. 555–567. [17] B.Y. Lee, J.H. Sohn, M.H. Choi, S.J. Lee, H.S. Kim, J.W. Yang, J.S. Choi, H.S. Kim, J.H. Yi, G.R. Tack, S.C. Chung, A volumetric study of the corpus callosum in 20s and 40s Korean people, Brain Struct. Funct. 213 (2009) 463–467. [18] A.K.H. Miller, R.L. Alston, J.A.N. Corsellis, Variation with age in the volume of gray and white matter in the cerebral hemispheres of man: measurements with an image analyser, Neuropathol. Appl. Neurol. 6 (1980) 119–132. [19] T.R. Mirsen, D.H. Lee, C.J. Wong, J.F. Diaz, A.J. Fox, V.C. Hachinski, H. Merskey, Clinical correlates of white matter changes on magnetic resonance imaging scans of the brain, Arch. Neurol. 48 (1991) 1015–1021. [20] W.J. Moon, H.J. Kim, H.G. Roh, S.H. Han, Atrophy measurement of the anterior commissure and substantia innominata with 3 T high-resolution MR imaging: does the measurement differ for patients with frontotemporal and Alzheimer disease and for healthy subjects? Am. J. Neuroradiol. 29 (2008) 1308–1313. [21] W.L. Nowinski, Computerized brain atlases for surgery of movement disorders, Semin. Neurosurg. 12 (2) (2001) 183–194. [22] W.L. Nowinski, A. Thirunavuukarasuu, A locus-driven mechanism for rapid and automated atlas assisted analysis of functional images by using the brain atlas for functional imaging, Neurosurg. Focus 15 (1) (2003) (Article 3). [23] K.N. Prakash, W.L. Nowinski, Morphologic relationship among the corpus callosum, fornix, anterior commissure, and posterior commissure: MRI-based variability study, Acad. Radiol. 13 (2006) 21–35. [24] L.B. Randy, H. Denise, P. Jamie, F.F. Anthony, M. Daniel, C.M. John, Z.S. Abraham, A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume, NeuroImage 23 (2004) 724–738. [25] R.R. Sturrock, Changes in the total number of neuroglia, mitotic cells and necrotic cells in the anterior limb of the mouse anterior commissure following hypoxic stress, J. Anat. 122 (1976) 447–453. [26] R.K. Shelli, F.A. Heather, M.B. Christine, D.B. Erin, Premorbid intellectual functioning, education, and brain size in traumatic brain injury: an investigation of the cognitive reserve hypothesis, Appl. Neuropsych. 10 (3) (2003) 153–162. [27] E.V. Sullivan, M.J. Rosenbloom, J.E. Desmond, A. Pfefferbaum, Sex differences in corpus callosum size: relationship to age and intracranial size, Neurobiol. Aging 22 (2001) 603–611. [28] Y. Tang, J.R. Nyengaard, B. Pakkenberg, H.J.G. Gundersen, Age-induced white matter changes in the human brain: a stereological investigation, Neurobiol. Aging 18 (6) (1997) 609–615. [29] E.A. Wilde, E.D. Bigler, J.M. Haider, Z. Chu, H.S. Levin, X. Li, J.V. Hunter, Vulnerability of the anterior commissure in moderate to severe pediatric traumatic brain injury, J. Child Neurol. 21 (2006) 769–776. [30] J. Xu, S. Kobayashi, S. Yamabuchi, K. Iijima, K. Okada, K. Yamashita, Gender effects on age-related changes in brain structure, Am. J. Neuroradiol. 21 (2000) 112–118.
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Effects of gender and age on anterior commissure volume Mi-Hyun Choi a , Ji-Hye Kim a , Hong-Won Yeon a , Jin-Seung Choi a , Jang-Yeon Park a , Jae-Hoon Jun a , Beob-Yi Lee b , Hyun-Jun Kim c , Gye-Rae Tack a , Soon-Cheol Chung a,∗ a Department of Biomedical Engineering, Research Institute of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, 322 Danwall-dong, Chungju, Chungbuk 380-701, South Korea b Department of Anatomy, School of Medicine, Konkuk University, Seoul, South Korea c Department of Obstetrics & Gynecology, Konkuk University, Chungju, South Korea
a r t i c l e
i n f o
Article history: Received 12 April 2011 Received in revised form 1 June 2011 Accepted 5 June 2011 Keywords: Anterior commissure volume Age Gender Volumetry
a b s t r a c t The purpose of this study was to measure the average anterior commissure (AC) volume of normal subjects in their 20s or 40s and to determine the effects of gender and age on AC volume. Magnetic resonance brain images were obtained for 93 people in their 20s (46 men, 47 women) and 87 in their 40s (36 men, 51 women). To investigate the effect of gender and age on AC volume, two-way analysis of variance, which used gender (two levels) and age (two levels) as independent variables, was employed. For subjects in their 20s, there was no difference in AC volume between genders, but for those in their 40s, the AC volume of males was less than that of females. There was no difference in AC volume between females in their 20s or 40s; however, the AC volume of men in their 40s was less than that for those in their 20s. There were gender-influenced differences in AC volume changes related to aging. © 2011 Elsevier Ireland Ltd. All rights reserved.
The human cerebrum consists of two hemispheres, and sensory information such as visual, auditory, and olfactory sensation is exchanged by bundles called the anterior commissure (AC) and posterior commissure (PC), which participate in interhemispheric transfer [9,23,28]. Identification of the AC is critical because it is an important brain structure because its location is crucial for performing stereotactic and functional neurosurgery, localization analysis in human brain mapping, medical image analysis, structure segmentation, and labeling in neuroradiology as well as in registration to reduce the number of degrees of freedom [15,21,22]. The Talairach transformation based on the AC also is widely used in human brain mapping for comparing brain structure and function across subjects [16]. Studies concerning the structural properties of the AC are typically conducted in patients, and the area and size of the AC are commonly measured using cross-sectional images. The area of the AC was shown to decrease in response to trauma, traumatic brain injury, or hypoxic stress [12,25,29]. Moon et al. [20] measured AC area and thickness of both normal subjects and patients with neurodegenerative condition, they reported that AC area and thickness of patients with Alzheimer disease and frontotemporal dementia was smaller than those of normal subjects [20].There have been few reports describing the AC area and volume in healthy subjects,
∗ Corresponding author. Tel.: +82 43 840 3759; fax: +82 43 851 0620. E-mail address: [email protected] (S.-C. Chung). 0304-3940/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2011.06.010
thus it is difficult to draw reliable conclusions on the influence of gender [1,8,12]. Further, few studies address AC volume changes in response to aging. Volume information of various brain structures can be used for clinical purposes by comparing unhealthy volumes to standard volumes determined from healthy subjects. Thus, it is of clinical significance to obtain information related to the average AC volumes of healthy subjects. Therefore, this study characterizes the average AC volume by measuring the AC volume of healthy Korean subjects in their 20s and 40s, and it also analyzed AC volume differences associated with gender and aging. A total of 180 healthy Korean subjects (in their 20s or 40s), who had no previous brain damage or head injuries and did not have any medical problems, as confirmed by neurospecialists, were selected for this study. The number of subjects in their 20s was 93 (average age = 23.0 ± 2.6 years), and the group consisted of 46 males (average age = 24.0 ± 2.8 years) and 47 females (average age = 21.9 ± 2.1 years). The number of subjects in their 40s was 87 (average age = 47.5 ± 3.7 years), and the group consisted of 36 males (average age = 48.9 ± 3.9 years) and 51 females (average age = 46.7 ± 3.4 years). MRI measurements were conducted using a 3.0-T FORTE machine (ISOL Technology, Korea) equipped with whole-body gradients and a quadrature head coil. T1-weighted brain images were obtained with a three-dimensional, magnetization-prepared, rapid-gradient echo sequence (TR/TE/TI = 10/4/100 ms; slice thickness = 1.5 mm; field of view = 220 mm × 192 mm × 192 mm;
M.-H. Choi et al. / Neuroscience Letters 500 (2011) 92–94
93
Fig. 1. (a) Segmentation of the anterior commissure in a cross-sectional image. (b) Three-dimensional reconstruction of the anterior commissure.
number of slices = 128; slice gap = 0; matrix size = 256 × 224 × 128; and number of excitations (NEX) = 2). The anterior commissure (AC) region was manually segmented, and its volume was measured by a neuroanatomist using Brain Voyager 2000 (Brain Innovation BV, Germany) software. After MR image acquisition, the image was reconstructed for use in image post-processing using Brain Voyager 2000. Any irregularity in image brightness along each slice, can potentially introduce errors when using segmentation procedures based on image brightness. To compensate for this problem, inhomogeneity correction based on the brightness of white matter was conducted for all axial, sagittal, and coronal planes. A Gaussian smoothing filter was used to increase the signal to noise ratio (SNR) and a sigma filter to improve the image contrast. The manual segmentation was performed by one of the authors, who has sufficient neuroanatomical knowledge for processing boundary and detailed regions properly. After designating the regions of interest (ROI), the AC volume in each slice was determined by multiplying the area of the ROI by slice thickness, and the entire volume of the AC was calculated by summing its volume in each slice [4,5,17]. Fig. 1(a) shows the segmented image of the two-dimensional AC region in a cross-sectional image and Fig. 1(b) shows the three-dimensional, reconstructed image based on the segmented AC region. Covariance analysis, a normalization method, was used to normalize the AC volume based on intracranial volume (ICV) [17,24]. ICV was calculated using cerebral size, i.e., cerebral width, height, and length (Eq. (1)) [6,11,27]: ICV (cc) =
4 length width height ∗∗ ∗ ∗ 3 2 2 2
(1)
It was well-known that there was a relationship between education period and brain structure volume [7,26]. Therefore to investigate the effect of gender and age on the normalized AC volume, two-way analysis of variance (ANOVA), which used a period of education as a covariance variable, gender (two levels) and age (two levels) as independent variables, and AC volume as a dependent variable, was completed using SPSS software (v. 18.0). When an interactive effect among variables was observed, major variables
Fig. 2. Interactive effect between age and gender on anterior commissure volume.
influencing AC volume were determined with simple main effect analysis. Table 1 shows the average AC volume based on gender and ages (subjects in their 20s or 40s). Two-way ANOVA showed that there was no difference between genders, but there was a significant difference between the age groups. The AC volume of subjects in their 40s (0.65 ± 0.15 cm3 ) was significantly smaller than that of those in their 20s (0.74 ± 0.18 cm3 ) (p = .005). Since there was an interactive effect between gender and age (p = .004), there was a difference in AC volume related to gender as the age increased. As age increased, the AC volume of females did not change significantly, but that of the male decreased (Fig. 2). To analyze this interactive effect, simple main effect analysis was performed. Independent t-test of the gender groups (both 20s and 40s) showed that there was no significant difference between the AC volume of males and female in their 20s, but the AC volume of males was significantly smaller than that of females in their 40s (p = .005). Independent t-test of age (both male and female) showed that the AC volume of subjects in their 40s was significantly smaller than that of male subjects in their 20s
Table 1 The mean, minimum, and maximum anterior commissure volumes (cm3 ) by gender and age. Age
Male
Female
Male + female
Mean ± S.D.
Min.
Max.
Mean ± S.D.
Min.
Max.
Mean ± S.D.
Min.
Max.
20s 40s
0.76 ± 0.21 0.60 ± 0.14
0.36 0.30
1.19 0.90
0.70 ± 0.14 0.69 ± 0.16
0.45 0.33
1.02 1.25
0.74 ± 0.18 0.65 ± 0.15
0.36 0.30
1.19 1.25
Total
0.71 ± 0.20
0.30
1.19
0.70 ± 0.15
0.33
1.25
0.70 ± 0.18
0.30
1.25
94
M.-H. Choi et al. / Neuroscience Letters 500 (2011) 92–94
(p < .001), but there was no significant difference between the AC volume of those in their 20s and those of their 40s in females. This study measured AC volume of healthy Korean subjects in their 20s and 40s, and it analyzed the differences in AC volume due to gender and aging. Elisabeth et al. [10] reported that the AC volume of healthy 12 year-old children was 0.04 cm3 . After measuring the AC area in the mid-sagittal plane of postmortem brains in normal subjects (n = 30), Allen and Gorski [1,2] reported that the AC area of males was less than that of females. Highley et al. [12] measured the AC area of normal subjects (male and female) in their 70s, but there was no significant difference between genders. As discussed previously, there have been few reports characterizing the AC area and volume of healthy subjects, but the reports are insufficient, and thus, it is difficult to draw reliable conclusions due to the effect of gender. Until now, there have been no reports related to the change in AC volume due to aging. It is well known that cerebral white matter volume generally decreases with age [14,18,19,28]. There was a significant loss in small diameter myelinated fibers in the older group in addition to atrophy of white matter volume. Therefore, the volume of the white matter and the volume of the myelinated fibers in the aging group were lower than those in the younger group [28]. There have been reports that the corpus callosum volume, a region of white matter, was larger in males than in females; however, until subjects reach their 70s, there was no atrophy due to aging [3,13,17,27]. The results showed that there was no difference in the AC volume between male and female subjects in their 20s. There was no age-related difference in AC volume for females, but there was a significant atrophy in the AC volume of males. Thus, for males in their forties, the AC volume was significantly smaller than that of females, which suggests a gender-based difference in AC volume patterns due to age. Therefore, it is expected that white matter volume change due to the aging be different by the region as well as by the gender. The reason for these gender-influenced differences due to aging is unclear, but they may be attributed to internal (such as sex hormones) and external factors (family circumstances and habits, such as smoking and drinking) [30]. To further investigate the effect of aging on AC volume change according to gender, it is necessary to analyze the AC volume of various age groups and to perform additional physiological and biological analyses concurrently. Manual ROI measurement method can induce operator dependent errors. However in this study, manual ROI measurement was carried out by neuro-anatomical expert to do exact segmentation of the boundary of AC region, and AC volume was measured for 180 subjects. Thus it is believed that operator dependent error be not quite large. Although in this study participants were males and females in their 20s and 40s, this study provides valuable information on the effects of gender and age on AC volume. It is expected that the results of this study will be used as basic research material for the understanding and diagnosis of brain and mental diseases like trauma and schizophrenia, which are closely related to AC atrophy. Acknowledgement This work was supported by Konkuk University in 2011. References [1] L.S. Allen, R.A. Gorski, Sexual dimorphism of the anterior commissure and massa intermedia of the human brain, J. Comp. Neurol. 312 (1991) 97–104. [2] L.S. Allen, R.A. Gorski, Sexual orientation and the size of the anterior commissure in the human brain, Neurobiology 89 (1992) 7199–7202.
[3] J.S. Allen, H. Damasio, T.J. Grabowski, J. Bruss, W. Zhang, Sexual dimorphism and asymmetries in the gray–white composition of the human cerebrum, NeuroImage 18 (2003) 880–894. [4] S.C. Chung, B.Y. Lee, G.R. Tack, S.Y. Lee, J.S. Eom, J.H. Sohn, Effects of age, gender, and weight on the cerebellar volume of Korean people, Brain Res. 1042 (2005) 233–235. [5] S.C. Chung, G.R. Tack, J.H. Yi, B. Lee, M.H. Choi, B.Y. Lee, S.Y. Lee, Effects of gender, age, and body parameters on the ventricular volume of Korean people, Neurosci. Lett. 395 (2006) 155–158. [6] S.C. Chung, M.H. Choi, B. Lee, G.R. Tack, J.H. Jun, J.R. Park, B.C. Min, B.G. Park, A study on the cerebral sizes of Koreans in their 20s and 40s, Int. J. Neurosci. 118 (2008) 1711–1724. [7] C.E. Coffey, J.A. Saxton, G. Ratcliff, R.N. Bryan, J.F. Lucke, Relation of education to brain size in normal aging: implications for the reserve hypothesis, Neurology 53 (1) (1999) 189–196. [8] S. Demeter, J.L. Ringo, R.W. Doty, Morphometric analysis of the human corpus callosum and anterior commissure, Hum. Neurobiol. 6 (4) (1988) 219–226. [9] S. Demeter, D.L. Rosene, G.W. Goesen, Fields of origin and pathways of the interhemispheric commissures in the temporal lobe of macaques, J. Comp. Neurol. 302 (1990) 29–53. [10] A.W. Elisabeth, D.B. Erin, M.H. Janelle, C. Zili, S.L. Harvey, L. Xiaoqi, V.H. Jill, Vulnerability of the anterior commissure in moderate to severe pediatric traumatic brain injury, J. Child. Neurol. 21 (2006) 769–776. [11] S.L. Free, P.S. Bergin, D.R. Fish, M.J. Cook, S.D. Shorvon, J.M. Stevens, Methods for normalization of hippocampal volumes measured with MR, Am. Soc. Neuroradiol. 16 (1995) 637–643. [12] J.R. Highley, M.M. Esiri, B. McDonald, H.C. Roberts, M.A. Walker, T.J. Crow, The size and fiber composition of the anterior commissure with respect to gender and schizophrenia, Soc. Biol. Psychiatry 45 (1999) 1120–1127. [13] S.C. Johnson, T. Farnworth, J.B. Pinkston, E.D. Bigler, D.D. Blatter, Corpus callosum surface area across the human adult life span: effect of age and gender, Brain Res. Bull. 35 (1994) 373–377. [14] B.W. Kristine, M.F. Anders, R. Ivar, L. Arvid, M.D. Anders, E.E. Dag, T.Q. Brian, S. David, M. Nikos, F. Bruce, Effects of age on volumes of cortex, white matter and subcortical structures, Neurobiol. Aging 26 (2005) 1261–1270. [15] A.L.T. Lacerda, A.Y. Hardan, O. Yorbik, M.S. Keshavan, Measurement of the orbitofrontal cortex: a validation study of a new method, NeuroImage 19 (2003) 665–673. [16] J.L. Lancaster, P.T. Fox, Talairach Space as a Tool for Intersubject Standardization in the Brain, Academic Press, San Diego, 2000, pp. 555–567. [17] B.Y. Lee, J.H. Sohn, M.H. Choi, S.J. Lee, H.S. Kim, J.W. Yang, J.S. Choi, H.S. Kim, J.H. Yi, G.R. Tack, S.C. Chung, A volumetric study of the corpus callosum in 20s and 40s Korean people, Brain Struct. Funct. 213 (2009) 463–467. [18] A.K.H. Miller, R.L. Alston, J.A.N. Corsellis, Variation with age in the volume of gray and white matter in the cerebral hemispheres of man: measurements with an image analyser, Neuropathol. Appl. Neurol. 6 (1980) 119–132. [19] T.R. Mirsen, D.H. Lee, C.J. Wong, J.F. Diaz, A.J. Fox, V.C. Hachinski, H. Merskey, Clinical correlates of white matter changes on magnetic resonance imaging scans of the brain, Arch. Neurol. 48 (1991) 1015–1021. [20] W.J. Moon, H.J. Kim, H.G. Roh, S.H. Han, Atrophy measurement of the anterior commissure and substantia innominata with 3 T high-resolution MR imaging: does the measurement differ for patients with frontotemporal and Alzheimer disease and for healthy subjects? Am. J. Neuroradiol. 29 (2008) 1308–1313. [21] W.L. Nowinski, Computerized brain atlases for surgery of movement disorders, Semin. Neurosurg. 12 (2) (2001) 183–194. [22] W.L. Nowinski, A. Thirunavuukarasuu, A locus-driven mechanism for rapid and automated atlas assisted analysis of functional images by using the brain atlas for functional imaging, Neurosurg. Focus 15 (1) (2003) (Article 3). [23] K.N. Prakash, W.L. Nowinski, Morphologic relationship among the corpus callosum, fornix, anterior commissure, and posterior commissure: MRI-based variability study, Acad. Radiol. 13 (2006) 21–35. [24] L.B. Randy, H. Denise, P. Jamie, F.F. Anthony, M. Daniel, C.M. John, Z.S. Abraham, A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume, NeuroImage 23 (2004) 724–738. [25] R.R. Sturrock, Changes in the total number of neuroglia, mitotic cells and necrotic cells in the anterior limb of the mouse anterior commissure following hypoxic stress, J. Anat. 122 (1976) 447–453. [26] R.K. Shelli, F.A. Heather, M.B. Christine, D.B. Erin, Premorbid intellectual functioning, education, and brain size in traumatic brain injury: an investigation of the cognitive reserve hypothesis, Appl. Neuropsych. 10 (3) (2003) 153–162. [27] E.V. Sullivan, M.J. Rosenbloom, J.E. Desmond, A. Pfefferbaum, Sex differences in corpus callosum size: relationship to age and intracranial size, Neurobiol. Aging 22 (2001) 603–611. [28] Y. Tang, J.R. Nyengaard, B. Pakkenberg, H.J.G. Gundersen, Age-induced white matter changes in the human brain: a stereological investigation, Neurobiol. Aging 18 (6) (1997) 609–615. [29] E.A. Wilde, E.D. Bigler, J.M. Haider, Z. Chu, H.S. Levin, X. Li, J.V. Hunter, Vulnerability of the anterior commissure in moderate to severe pediatric traumatic brain injury, J. Child Neurol. 21 (2006) 769–776. [30] J. Xu, S. Kobayashi, S. Yamabuchi, K. Iijima, K. Okada, K. Yamashita, Gender effects on age-related changes in brain structure, Am. J. Neuroradiol. 21 (2000) 112–118.