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Estimating volumes of the pituitary gland from T1-weighted magnetic-resonance images: Effects of age, puberty, testosterone, and estradiol
NeuroImage 94 (2014) 216–221
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Estimating volumes of the pituitary gland from T1-weighted magnetic-resonance images: Effects of age, puberty, testosterone, and estradiol Angelita Pui-Yee Wong a,b, Jon Pipitone c, Min Tae M. Park c, Erin W. Dickie b, Gabriel Leonard d, Michel Perron e,f, Bruce G. Pike g, Louis Richer f, Suzanne Veillette e,f, M. Mallar Chakravarty b,c,h,i, Zdenka Pausova j, Tomáš Paus a,b,h,⁎ a
Department of Psychology, University of Toronto, Toronto, Canada Rotman Research Institute, Baycrest, Toronto, Canada c Kimel Family Translational Imaging Genetics Research Laboratory, Research Imaging Centre, The Centre for Addiction and Mental Health, Toronto, Canada d Montreal Neurological Institute, McGill University, Montréal, Canada e ECOBES, Cégep de Jonquière, Jonquière, Canada f University of Quebec in Chicoutimi, Chicoutimi, Canada g Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada h Department of Psychiatry, University of Toronto, Toronto, Canada i Institute of Biomaterials and Biomedical Engineering at the University of Toronto, Toronto, Canada j The Hospital for Sick Children, University of Toronto, Toronto, Canada b
a r t i c l e
i n f o
Article history: Accepted 21 February 2014 Available online 12 March 2014
a b s t r a c t The pituitary gland is a key structure in the hypothalamic–pituitary–gonadal (HPG) axis — it plays an important role in sexual maturation during puberty. Despite its small size, its volume can be quantified using magnetic resonance imaging (MRI). Here, we study a cohort of 962 typically developing adolescents from the Saguenay Youth Study and estimate pituitary volumes using a newly developed multi-atlas segmentation method known as the MAGeT Brain algorithm. We found that age and puberty stage (controlled for age) each predicts adjusted pituitary volumes (controlled for total brain volume) in both males and females. Controlling for the effects of age and puberty stage, total testosterone and estradiol levels also predict adjusted pituitary volumes in males and pre-menarche females, respectively. These findings demonstrate that the pituitary gland grows during adolescence, and its volume relates to circulating plasma-levels of sex steroids in both males and females. © 2014 Elsevier Inc. All rights reserved.
Introduction The pituitary gland is a key structure in the hypothalamic–pituitary– gonadal (HPG) axis; it plays an important role in sexual maturation during puberty. The activation of the HPG axis during this developmental period involves: 1) the release of the gonadotropinreleasing hormone (GnRH) from the hypothalamus; 2) the release of gonadotropins, luteinizing hormone (LH) and follicle stimulating hormone (FSH) from the pituitary gland; and 3) the release of sex steroids from maturing gonads. Even though the pituitary gland is a small structure, its volume can be quantified using magnetic resonance imaging (MRI). Previous
⁎ Corresponding author at: Rotman Research Institute, 3560 Bathurst St., Toronto, Ontario M6A 2E1, Canada. E-mail address: [email protected] (T. Paus).
http://dx.doi.org/10.1016/j.neuroimage.2014.02.030 1053-8119/© 2014 Elsevier Inc. All rights reserved.
neuroimaging studies have noted that pituitary size increases with age in children and adolescents (e.g., Fink et al., 2005; MacMaster et al., 2007; Takano et al., 1999), undergoes a growth spurt during puberty (MacMaster et al., 2007; Takano et al., 1999), and varies with plasma levels of FSH and estradiol during early (10 to 15 years) puberty in females (Peper et al., 2010). In the latter study, pituitary volumes were not related to LH and testosterone in females, nor to any sex hormones in males in this age range. As maximal sex hormone production in males and females is found at a more advanced pubertal stage (Butler et al., 1989; Sehested et al., 2000), it is important to examine the relationship between sex hormones and the pituitary gland in more advanced stages of puberty. Here, we examined the relationship between pituitary volume and development-related variables, namely age, puberty stages, and sex steroids, in a large sample of typically developing adolescents. We hypothesized that – after controlling for total brain volume – volumes of the pituitary gland will correlate with increased age, advanced
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puberty stage, and higher levels of sex steroids in both male and female adolescents. To quantify the pituitary volumes, we performed automatic segmentations of the pituitary gland using a novel label-fusion based methodology known as the MAGeT Brain algorithm (Chakravarty et al., 2013). The MAGeT Brain algorithm has been validated previously for the segmentation of subcortical structures (such as striatum, globus pallidus, and thalamus; Chakravarty et al., 2013) and, more recently, the hippocampus and cerebellar lobules (Park et al., 2014). In this study, we also validated the use of the MAGeT Brain algorithm for the segmentation of the pituitary gland. Methods Participants Data were collected from 1019 adolescents (12 to 18 years of age) recruited in the Saguenay Lac St. Jean (SLSJ) region in Quebec, Canada, as part of the Saguenay Youth Study (Pausova et al., 2007). Participants were recruited through high schools in the SLSJ region. Interested families were contacted by a research nurse for a telephone interview to determine their eligibility for the study. The main exclusion criteria are: (1) positive history of alcohol abuse during pregnancy; (2) positive medical history for meningitis, malignancy, and heart disease requiring heart surgery; (3) severe mental illness (e.g., autism, schizophrenia) or mental retardation (IQ b 70); and (4) MRI contraindications. Data collection for the Saguenay Youth Study (SYS) occurred over several visits. First, a research nurse visited homes of the participating families; during the visit, parents and adolescents signed consent and assent forms, respectively, and filled out a number of questionnaires. This was followed by a hospital visit for magnetic resonance imaging, cardiovascular and metabolic phenotyping. Cognitive testing (6 h) took place in a different day and, in most participants, it was carried out in a dedicated room at their respective school. Finally, the research nurse visited the participant's school to obtain a morning blood sample and to administer additional questionnaires. Details of recruitment and testing procedures are provided in Pausova et al. (2007). In the current report, we excluded 41 participants after quality control of MR images and MAGeT segmentations. Of the excluded participants, 36 participants had poor MR images; 3 participants had poor pituitary segmentations; and 2 participants had abnormal pituitaries. We also excluded 16 participants after quality control of behavioral and sex steroids data. Of the excluded participants, 12 participants did not have measures of sex steroids, 2 male participants had testosterone levels N3 standard deviations away from the mean, and 2 pre-menarche female participants had estradiol levels N3 standard deviations away from the mean. After the exclusions, 962 participants remained for analyses (467 males and 495 females; M = 180.4 months of age; SD = 22 months of age; range = 137– 230 months of age). MRI acquisition Structural MRI data were collected on a Phillips 1.0-T superconducting magnet. T1-weighted images were acquired using the following parameters: 3D RF-spoiled gradient-echo scan with 140–160 slices, 1-mm isotropic resolution, TR = 25 ms, TE = 5 ms, and flip angle = 30°. MRI analysis Pituitary volumes were derived using a novel segmentation method that generates a library of multiple automatically generated templates of different MR images within a dataset (MAGeT Brain algorithm; Chakravarty et al., 2013). Using the MAGeT Brain algorithm, pituitary volumes were estimated in the following three-step process. First, manually labeled pituitary
Fig. 1. Sagittal (top), coronal (middle), and axial (bottom) view of the pituitary gland from a T1-weighted MR image. The pituitary is manually labeled in red on the right.
glands (Fig. 1) of 12 participants were transferred – via non-linear registration – to label MR images of 15 other participants chosen at random from the full dataset. This resulted in a total of 180 segmentations (12 manually labeled pituitary glands × 15 participants) making up the template library. Second, each segmentation in the template library was used to label MRIs of all 962 participants via non-linear transformation. This resulted in 180 segmentations per participant. Third, based on the voxel-wise majority vote, the label occurring most frequently at a voxel was retained (Collins and Pruessner, 2010). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium (Loken et al., 2010). The final labels were visually inspected for quality along with their respective native MR image for all participants (by AW). Using a subset of the participants (n = 33), we validated the accuracy of the MAGeT Brain algorithm for the pituitary gland by comparing the automatic segmentations produced with their respective manual segmentations (generated by AW blind to any identifying participant information). The segmentations were generated using Display, which is part of the minc suite of software tools (http://www.bic.mni.mcgill. ca/ServicesSoftware/HomePage). Sagittal, coronal, and axial views of the MR image were used to locate the pituitary gland. The boundaries of the pituitary gland are detailed in Peper et al. (2010). There was
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high spatial overlap between the 33 manual segmentations and their respective automatically generated labels (mean Dice Kappa = 0.915, SD = 0.019, range = 0.877–0.946). Using the minc suite of software tools, total brain volumes (including ventricles) were estimated by conducting non-linear transformation of the brain mask volume from the average brain (SYS808) to the native space of each participant. Puberty Development Scale The Puberty Development Scale (PDS; Peterson et al., 1988) is a self-report measure of pubertal development based on the Tanner stages. The adolescent is asked to report on changes in the following characteristics: growth spurt in height, pubic hair, and skin change for both males and females; facial hair growth and voice change for males only; and breast development and menarche in females only. Each item is rated on a 4-point scale ranging from 1 to 4. PDS classifies the adolescent into the following five categories of pubertal status: (1) prepubertal; (2) beginning pubertal; (3) midpubertal; (4) advanced pubertal; and (5) postpubertal. Carskadon and Acebo (1993) found a significant positive correlation between self-rated PDS and physician ratings (r = 0.841, p b .001) of pubertal development, demonstrating that the self-rated PDS is a valid measure. Serum testosterone and estradiol Fasting blood samples were drawn between 8:00 a.m. and 9:00 a.m. and analyzed to measure serum levels of total testosterone (nanomoles per liter) and levels of estradiol (picomoles per liter). To measure levels of total testosterone, the first batch of blood samples was analyzed via radioimmunoassay (Testosterone RIA DSL-4000; Diagnostic Systems Laboratory Inc., TX); and the second batch of blood samples was analyzed via enzyme-linked immunosorbent assays (Testosterone EIA-1559; DRG International, NJ). Levels of total testosterone were standardized by calculating z-scores of the testosterone values within each batch to allow for further statistical analyses. To measure levels of estradiol, the first batch of blood samples was analyzed via an automated chemiluminescence immunoassay on ADVIA Centaur Immunoanalyzer (Siemens Healthcare Diagnostics Ltd.), and the second batch of blood samples was analyzed via enzyme-linked immunosorbent assays (Estradiol EIA-2693; DRG International; NJ). Levels of estradiol were standardized in pre-menarche females by calculating z-scores of the estradiol values within each batch to allow for further statistical analyses. Statistical analysis Using linear regression, first we examined how age (in months), puberty stage, total testosterone levels (in males only), and estradiol levels (in pre-menarche females only) predict (each independently) pituitary volumes in males and females. Then, we examined the contributions of the individual variables over and above the other variables by conducting several multiple regression analyses: age only (Model 1); age and puberty stage (Model 2); age and sex steroid (Model 3); and age, puberty stage, and sex steroid (Model 4). For males, the sex steroid in Models 3 and 4 was total testosterone, and for pre-menarche females, the sex steroid in Models 3 and 4 was estradiol. Finally, we calculated F-tests to determine whether these models were significantly different from each other. Results Male and female adolescents did not differ in their age, t(960) = 1.63, p = 0.10. As expected, females were in a more advanced stage of puberty (M = 4.11, SD = 0.71) compared with males (M = 3.38, SD = 0.86), t(960) = 14.38, p b 0.001. Females had larger (absolute) pituitary volumes (M = 0.632 cm3, SD = 0.110 cm3) compared with
males (M = 0.564 cm3, SD = 0.108 cm3), t(960) = 9.66, p b .001, despite males having larger total brain volumes (M = 1373 cm3, SD = 93 cm3 ) compared with females (M = 1241 cm 3 , SD = 87 cm3), t(960) = 22.66, p b .001. Absolute pituitary volumes correlated with total brain volume for males, r = .19, p b .001, and for females, r = .21 p b .001. There was no significant relationship between age and total brain volume in males R2 = .001, F(1, 465) = 0.50, p = .48, and females R2 = .00006, F(1, 493) = 0.03, p = .86. The mean and standard deviations for age, puberty stage, and sex steroid levels for males and females are presented in Table 1. To control for global differences in brain size, we adjusted pituitary volumes by the total brain volume using a linear regression: the residuals from this regression were added to the mean pituitary volume for each sex to calculate the adjusted pituitary volume (dependent variable). From now on, we will use the term ‘pituitary volume’ to refer to these adjusted volumes. Age and puberty stage Using linear regression analyses, we examined how age (in months) and puberty stage, each considered separately, predict pituitary volumes in males and females. Age accounted for a significant amount of the pituitary volumes in males, R2 = .21, F(1, 465) = 126.8, p b .001 and in females R2 = .085, F(1, 493) = 46.05, p b .001 (Fig. 2). Puberty stage accounted for a significant amount of the pituitary volumes in males, R2 = .26, F(1, 465) = 164.9, p b .001 and in females R2 = .15, F(1, 493) = 87.66, p b .001 (Fig. 2). The correlations and linear R2 of these variables are also presented in Table 2. Next, a multiple regression analysis was conducted to evaluate whether puberty stage predicted pituitary volumes over and above age. Puberty stage accounted for a significant proportion of the pituitary volume variance after controlling for age in males, R2 change = .078, F(1, 464) = 51.28, p b .001, and in females, R2 change = .067, F(1, 492) = 38.90, p b .001 (Model 1 versus Model 2 in Table 3). Total testosterone levels Using linear regression analyses, we examined how serum total testosterone levels predict pituitary volumes in males. Testosterone accounted for a significant amount of the pituitary volumes in males, r2 = .24, F(1, 465) = 147.9, p b .001 (Fig. 3 and Table 2). A multiple regression analysis was conducted to evaluate whether total testosterone levels predicted pituitary volumes over and above age. Testosterone accounted for a significant proportion of the pituitary volume variance after controlling for age in males, R2 change = .074, F(1, 464) = 47.98, p b .001 (Model 1 versus Model 3 in Table 3). Next, a multiple regression analysis was conducted with age, puberty stage, and total testosterone levels in males as predictors. The linear combination of the three variables was significantly related to pituitary volumes, R2 = .33, F(3, 463) = 75.72, p b .001 (shown as Model 4 in Table 3). Puberty stage predicted significantly over and above age and testosterone, R2 change = .041, F(1, 463) = 28.45, p b .001 (Model 3 versus Model 4 in Table 3). Testosterone predicted significantly over and above age and puberty stage, R2 change = .037, F(1, 463) = 25.3, p b .001 (Model 2 versus Model 4 in Table 3). Based on these results, Table 1 Sample characteristics for males and females. Variable
Age (months) Puberty Testosterone (nmol/L) Estradiola (pmol/L) a
Males
Females
n
Mean
SD
n
Mean
SD
467 467 467 –
179.2 3.38 15.98 –
21.43 0.86 8.21 –
495 495 – 72
181.5 4.11 – 139.03
22.53 0.71 – 100.62
Estradiol values are presented only for pre-menarche females.
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Fig. 2. The linear relationships (solid black lines) between pituitary volumes with age and puberty stage in males (left panel — blue) and females (right panel — red).
both puberty stage and testosterone levels appear to offer unique additional predictive power beyond age.
Estradiol levels Since serum levels of sex hormones fluctuate in females during their menstrual cycle, we restricted analyses of estradiol to pre-menarche females only (n = 72). This analysis allows us to examine the relationship between estradiol levels and pituitary gland volumes without the possible confounding effects of hormone fluctuations in the cycling females (Peper et al., 2010). Using linear regression analyses, we examined whether estradiol levels predict pituitary volumes in pre-menarche females. Estradiol accounted for a significant amount of the pituitary volumes in premenarche females, R2 = .13, F(1, 70) = 10.62, p = .0017 (Fig. 4 and Table 2). We also examined how age (in months) and puberty stage separately predict pituitary volumes in pre-menarche females. Age and puberty stage did not account for a significant amount of the pituitary volumes in pre-menarche females, R2 = .022, F(1, 70) = 1.56, p = .216 and R2 = .024, F(1, 70) = 1.75, p = .19, respectively. It is likely that the restriction of range of age (M = 155.4 months; SD = 11.20 months; range = 144–201 months) and puberty stage (M = 2.85; SD = 0.46; range = 1–3) in pre-menarche females have limited the ability to detect a significant relationship with pituitary volumes. A multiple regression analysis was conducted to evaluate whether estradiol levels predicted pituitary volumes over and above age. Estradiol accounted for a significant proportion of the pituitary volume variance after controlling for age in pre-menarche females, R2 change = .11, F(1, 69) = 8.85, p = .004 (shown as Model 2 in Table 4). Next, a multiple regression analysis was conducted with age, puberty stage, and estradiol levels in pre-menarche females as predictors. The Table 2 Correlations and linear R-square between pituitary volume and development-related variables (each assessed independently of each other) in males and females. Variable
Age Puberty Testosterone (nmol/L) Estradiola (pmol/L) a
Males
Females
r
R2
p-Value
r
R2
p-Value
.46 .51 .49 –
.214 .262 .241 –
b.001 b.001 b.001 –
.29 .39 – .36
.085 .15 – .132
b.001 b.001 – .0017
Estradiol values are presented only for pre-menarche females.
linear combination of the three variables was significantly related to pituitary volumes, R2 = .14, F(3, 68) = 3.76, p = .015 (shown as Model 4 in Table 4). Estradiol predicted significantly over and above age and puberty stage, R2 change = .10, F(1, 68) = 7.93, p = .006 (Model 2 versus Model 4 in Table 4). Puberty stage did not predict significantly over and above age and estradiol, R 2 change = .009, F(1, 68) = 0.74, p = .39 (Model 3 versus Model 4 in Table 4). Discussion Using the MAGeT Brain algorithm to estimate pituitary volumes in 962 adolescents, this is the largest study to-date examining how pituitary volume changes with age, puberty stage, and sex steroids (testosterone and estradiol) during puberty. We found a positive relationship between age and pituitary volumes in both males and females. This finding is consistent with past research that has examined pituitary volume changes during development (e.g., Peper et al., 2010; Takano et al., 1999; Whittle et al., 2012). Although there are early-to-advanced pubertal adolescents in our study, the majority of the females in our study are in their mid-to-late puberty stages. As a result, even though we were able to find that Table 3 Summary of multiple regression analyses for variables predicting pituitary volumes in males (n = 467) and females (n = 495). R2 Males Model 1 Age Model 2 Age Puberty Model 3 Age Testosterone (nmol/L) Model 4 Age Puberty Testosterone (nmol/L) Females Model 1 Age Model 2 Age Puberty
SE B
β
2.30
0.20
0.46
1.13 45.29
0.25 6.32
0.23 0.36
1.32 36.79
0.24 5.31
0.27 0.35
0.68 34.73 27.42
0.26 6.51 5.45
0.14 0.28 0.26
1.40
0.21
0.29
0.25 53.85
0.27 8.63
0.05 0.35
B
.21 .29
.29
.33
.085 .15
p-Value b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 .01 b.001 b.001 b.001 b.001 b.001 .36 b.001
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A.P.-Y. Wong et al. / NeuroImage 94 (2014) 216–221 Table 4 Summary of multiple regression analyses for variables predicting pituitary volumes in pre-menarche females (n = 72).
Fig. 3. The linear relationship (solid black line) between pituitary volumes with total testosterone levels in males.
pituitary volumes increase with age, the relationship might be even more pronounced in girls during early puberty as demonstrated in Takano et al. (1999). As the sample in our current study includes a range of early-toadvanced pubertal adolescents, we were able to demonstrate a significant positive relationship between puberty stage (as measured by PDS; Peterson et al., 1988) and pituitary volumes in both males and females. That is, a more advanced puberty stage was associated with larger pituitary volumes. This relationship remained after controlling for age, suggesting that puberty stage offers predictive power beyond age. Takano et al. (1999) have speculated that the pronounced pituitary growth during adolescence reflects hypersecretion of pituitary hormones (i.e., gonadotropins — LH and FSH) at this time (Elster et al., 1990; Lee et al., 1976; Martha and Reiter, 1991). Indeed, Peper et al. (2010) have found a positive relationship between pituitary volumes and gonadotropins (LH and FSH) in early pubertal females. Although we did not measure gonadotropins in our study, we examined the relationship between pituitary volumes and sex steroids (i.e., testosterone and estradiol), which are sex hormones regulated by gonadotropins. We found that there was a significant positive relationship between pituitary volumes and total testosterone levels in males. That is, higher testosterone levels were significantly related to larger pituitary volumes. This relationship remained significant after controlling for age and puberty stage, demonstrating that despite the large percentage of variance explained by age and puberty stage, total testosterone levels can explain additional variance of the pituitary volumes beyond age and puberty stage. Although Peper et al. (2010) have examined the relationship between testosterone levels and pituitary volume, they were not able to find a significant relationship in males. The authors' explanation for their null findings in males was that the males studied in their sample were in a less advanced pubertal stage: since males do not produce peak testosterone levels until a later pubertal stage, Tanner stage 4 (Butler et al., 1989), it might be more difficult to examine a clear
Fig. 4. The linear relationship (solid black line) between pituitary volumes with estradiol levels in pre-menarche females. Estradiol remains a significant predictor of pituitary volumes when the two data points N2 SD were also removed, R2 = .077, F(1, 68) = 5.68, p = .02.
Pre-menarche females
R2
Model 1 Age Model 2 Age Puberty Model 3 Age Estradiol (pmol/L) Model 4 Age Puberty Estradiol (pmol/L)
.022
B
SE B
β
1.31
1.05
0.15
1.19 30.65
1.05 25.26
0.13 0.14
0.33 50.69
1.05 17.04
0.04 0.51
0.287 20.95 48.58
1.049 24.32 17.25
0.03 0.10 0.49
.042
.13
.14
p-Value .22 .22 .23 .26 .23 .007 .76 .004 .015 .79 .39 .006
relationship between pituitary volumes and sex hormone production during early puberty. Since the sample in our current study includes early-to-advanced pubertal adolescents and a larger number of participants (and thus more power to detect a significant difference), unlike Peper et al. (2010) we were able to demonstrate that pituitary volumes are positively related to total testosterone levels. To exclude the possible confounding effects of hormonal fluctuations in menstrual-cycling females, we examined the relationship between pituitary volume and estradiol levels in pre-menarche females only. In pre-menarche females, higher estradiol levels were related to larger pituitary volumes. This relationship remained significant after controlling for age and puberty stage, demonstrating that despite the large percentage of variance explained by age and puberty stage, estradiol levels can explain additional variance of the pituitary volumes beyond age and puberty stage. The positive relationship between estradiol and pituitary volume in females is consistent with Peper et al. (2010). In pre-menarche females, estrogen may have been released by primordial follicles, which have undergone varying degrees of maturation to the stage of the early Graafian follicle (Widholm et al., 1974). Besides the ovarian origin, it is important to note that some of the estrogen is of adrenal origin. Since GnRH from the hypothalamus and the gonadotropins from the pituitary gland either indirectly or directly trigger the release of sex steroids, including testosterone and estradiol, it seems reasonable to suggest that larger pituitary glands (presumably due to GnRH effects) result in increased production of sex steroids. One should be cautious, however, when drawing conclusions about the directionality of the relationship between pituitary volume and sex hormones, because the latter also regulate GnRH and gonadotropin production and release via negative feedback loops. Although age, puberty stage, testosterone levels, and estradiol levels were able to explain significant amount of variance in pituitary volumes, it is important to note that pituitary segmentation used here did not distinguish between the anterior lobe and the posterior lobe of the pituitary gland. The anterior lobe of the pituitary gland produces and releases HPG axis-related hormones (i.e., gonadotropin hormones), as well as adrenocorticotropic hormone (ACTH), growth hormone (GH), thyroid-stimulating hormone (TSH), and prolactin. The posterior pituitary is involved in the secretion of oxytocin and vasopressin (Tran et al., 2004). As a result, it is likely that other hormones (i.e., other than HPG axis-related hormones) released by the anterior and posterior pituitary gland influence the total pituitary volume. For example, mental disorders that are characterized by elevated ACTH and cortisol levels through hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis were associated with enlarged pituitary glands. Specifically, larger pituitary volumes were observed in patients with depression (Krishnan et al., 1991; MacMaster and Kusumakar, 2004; MacMaster et al., 2008), firstepisode psychosis (Pariante et al., 2004), and post-traumatic stress disorder (Thomas and De Bellis, 2004). In addition, it has been suggested
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that enlarged pituitary volumes observed in pregnant and postpartum women may be related to the increased prolactin production and secretion during pregnancy (Dinc et al., 1998). In conclusion, we found that the pituitary gland undergoes robust growth with age and puberty stage during adolescence. In addition, we found a significant relationship between pituitary volumes and total testosterone levels in males and a significant relationship between pituitary volumes and estradiol levels in pre-menarche females. Finally, this work demonstrates that the MAGeT Brain segmentation algorithm can estimate the volume of the pituitary gland with high accuracy. Acknowledgments We thank the following individuals for their contributions in acquiring data: Manon Bernard (database architect, The Hospital for Sick Children), Jacynthe Tremblay and her team of research nurses (Saguenay Hospital), Helene Simard and her team of research assistants (Cégep de Jonquière) and Dr. Rosanne Aleong (program manager, Rotman Research Institute). TP is the Tanenbaum Chair in Population Neuroscience at the Rotman Research Institute, University of Toronto. Funding support: The Saguenay Youth Study project is funded by the Canadian Institutes of Health Research (TP, ZP) (MOP178790), Heart and Stroke Foundation of Canada (Quebec) (ZP) (MOP178790), and the Canadian Foundation for Innovation (ZP) (MOP178790). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium. SciNet is funded by: the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund — Research Excellence; and the University of Toronto. References Butler, G.E., Walker, R.F., Walker, R.V., Teague, P., Riad-Fahmy, D., Ratcliffe, S.G., 1989. Salivary testosterone levels and the progress of puberty in the normal boy. Clin. Endocrinol. 30, 587–596. Carskadon, M.A., Acebo, C., 1993. A self-administered rating scale for pubertal development. Journal of Adolescent Health. 14, 190–195. Chakravarty, M.M., Steadman, P., van Eede, M.C., Calcott, R.D., Gu, V., Shaw, P., Raznahan, A., Collins, D.L., Lerch, J.P., 2013. Performing label-fusion-based segmentation using multiple automatically generated templates. Hum. Brain Mapp. http://dx.doi.org/10. 1002/hbm.22092. Collins, D.L., Pruessner, J.C., 2010. Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion. Neuroimage 52, 1355–1366. Dinc, H., Esen, F., Demirci, A., Sari, A., Resit, Gümele H., 1998. Pituitary dimensions and volume measurements in pregnancy and post partum. Acta Radiol. 39, 64–69. Elster, A.D., Chen, M.Y., Williams III, D.W., Key, L.L., 1990. Pituitary gland: MR imaging of physiologic hypertrophy in adolescence. Radiology 174, 681–685. Fink, A.M., Vidmar, S., Kumbla, S., Pedreira, C.C., Kanumakala, S., Williams, C., Carlin, J.B., Cameron, F.J., 2005. Age-related pituitary volumes in prepubertal children with
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normal endocrine function: volumetric magnetic resonance data. J. Clin. Endocrinol. Metab. 90 (6), 3274–3278. Krishnan, K.R.R., Doraiswamy, P.M., Lurie, S.N., Figiel, G.S., Husain, M.M., Boyko, O.B., Ellinwood Jr., E.H., Nemeroff, C.B., 1991. Pituitary size in depression. J. Clin. Endocrinol. Metab. 72 (2), 256–259. Lee, P.A., Xenakis, T., Winer, J., Matsenbaugh, S., 1976. Puberty in girls: correlation of serum levels of gonadotropins, prolactin, androgens, estrogens, and progestin's with physical changes. J. Clin. Endocrinol. 43, 775–784. Loken, C., et al., 2010. SciNet: lessons learned from building a power-efficient top-20 system and data centre. J. Phys. Conf. Ser. 256, 012026. MacMaster, F.P., Kusumakar, V., 2004. MRI study of the pituitary gland in adolescent depression. J. Psychiatr. Res. 38, 231–236. MacMaster, F.P., Keshavan, M., Mirza, Y., Carrey, N., Upadhyaya, A.R., El-Sheikh, R., Buhagia, C.J., Taormina, S.P., Boyd, C., Lynch, M., Rose, M., Ivey, J., Moore, G.J., Rosenberg, D.R., 2007. Development and sexual dimorphism of the pituitary gland. Life Sci. 80, 940–944. MacMaster, F.P., Leslie, R., Rosenberg, D.R., Kusumakar, V., 2008. Pituitary gland volume in adolescent and young adult bipolar and unipolar depression. Bipolar Disord. 10, 101–104. Martha, P.M., Reiter, E.O., 1991. Pubertal growth and growth hormone secretion. Endocrinol. Metab. Clin. N. Am. 20 (1), 165–182. Pariante, C.M., Vassilopoulou, K., Velakoulis, D., Philips, L., Soulsby, B., Wood, S.J., et al., 2004. Pituitary vol. psychosis 185, 5–10. Park, M.T.M., Pipitone, J., Baer, L., Winterburn, J.L., Shah, Y., Chavez, S., Schira, M.M., Lobaugh, N.J., Lerch, J.P., Voineskos, A.N., Chakravarty, M.M., 2014. Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates. NeuroImage 95, 217–231. Pausova, Z., Paus, T., Abrahamowicz, M., Almerigi, J., Arbour, N., Bernard, M., Gaudet, D., et al., 2007. Genes, maternal smoking, and the offspring brain and body during adolescence: design of the Saguenay Youth Study. Hum. Brain Mapp. 28, 502–518. Peper, J., Brouwer, R.M., van Leeuwen, M., Schnack, H.G., Boomsma, D.I., Kahn, R.S., Hulshoff Pol, H.E., 2010. HPG-axis hormones during puberty: a study on the association with hypothalamic and pituitary volumes. Psychoneuroendocrinology 35, 133–140. Peterson, A.C., Crockett, L., Richards, M., Boxer, A., 1988. A self-report measure of pubertal status: reliability, validity, and initial norms. J. Youth Adolesc. 17, 117–133. Sehested, A., Juul, A., Andersson, A.M., Petersen, J.H., Jensen, T.K., Muller, J., Skakkebaek, N. E., 2000. Serum inhibin A and inhibin B in healthy prepubertal, pubertal, and adolescent girls and adult women: relation to age, stage of puberty, menstrual cycle, follicle-stimulating hormone, luteinizing hormone, and estradiol levels. J. Clin. Endocrinol. Metab. 85 (4), 1634–1640. Takano, K., Utsunomiya, H., Ono, H., Ohfu, M., Okazaki, M., 1999. Normal development of the pituitary gland: assessment with three-dimensional MR volumetry. Am. J. Neuroradiol. 20, 312–315. Thomas, L.A., De Bellis, M.D., 2004. Pituitary volumes in pediatric maltreatment-related posttraumatic stress disorder. Biol. Psychiatry 55 (7), 752–758. Tran, P.V., Savage, J.J., Ingraham, H.A., Rhodes, S.J., 2004. Molecular genetics of hypothalamic–pituitary axis development. In: Pescovitaz, O.H., Eugster, E.A. (Eds.), Pediatric Endocrinology, Mechanisms, Manifestations and Management. Lippincott Williams & Wilkins, Philadelphia, pp. 63–79. Whittle, S., Yucel, M., Lorenzetti, V., Byrne, M.L., Simmons, J.G., Wood, S.J., Pantelis, C., Allen, N.B., 2012. Pituitary volume mediates the relationship between pubertal timing and depressive symptoms during adolescence. Psychoneuroendocrinology 37, 881–891. Widholm, O., Kantero, R.-L., Axelson, E., Johansson, E.D.B., Wide, L., 1974. Endocrine changes before and after the menarche: I. Urinary excretion of estrogen, FSH and LH, and serum levels of progesterone, FSH and LH. Acta Obstet. Gynecol. Scand. 53 (3), 197–208.
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NeuroImage journal homepage: www.elsevier.com/locate/ynimg
Estimating volumes of the pituitary gland from T1-weighted magnetic-resonance images: Effects of age, puberty, testosterone, and estradiol Angelita Pui-Yee Wong a,b, Jon Pipitone c, Min Tae M. Park c, Erin W. Dickie b, Gabriel Leonard d, Michel Perron e,f, Bruce G. Pike g, Louis Richer f, Suzanne Veillette e,f, M. Mallar Chakravarty b,c,h,i, Zdenka Pausova j, Tomáš Paus a,b,h,⁎ a
Department of Psychology, University of Toronto, Toronto, Canada Rotman Research Institute, Baycrest, Toronto, Canada c Kimel Family Translational Imaging Genetics Research Laboratory, Research Imaging Centre, The Centre for Addiction and Mental Health, Toronto, Canada d Montreal Neurological Institute, McGill University, Montréal, Canada e ECOBES, Cégep de Jonquière, Jonquière, Canada f University of Quebec in Chicoutimi, Chicoutimi, Canada g Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada h Department of Psychiatry, University of Toronto, Toronto, Canada i Institute of Biomaterials and Biomedical Engineering at the University of Toronto, Toronto, Canada j The Hospital for Sick Children, University of Toronto, Toronto, Canada b
a r t i c l e
i n f o
Article history: Accepted 21 February 2014 Available online 12 March 2014
a b s t r a c t The pituitary gland is a key structure in the hypothalamic–pituitary–gonadal (HPG) axis — it plays an important role in sexual maturation during puberty. Despite its small size, its volume can be quantified using magnetic resonance imaging (MRI). Here, we study a cohort of 962 typically developing adolescents from the Saguenay Youth Study and estimate pituitary volumes using a newly developed multi-atlas segmentation method known as the MAGeT Brain algorithm. We found that age and puberty stage (controlled for age) each predicts adjusted pituitary volumes (controlled for total brain volume) in both males and females. Controlling for the effects of age and puberty stage, total testosterone and estradiol levels also predict adjusted pituitary volumes in males and pre-menarche females, respectively. These findings demonstrate that the pituitary gland grows during adolescence, and its volume relates to circulating plasma-levels of sex steroids in both males and females. © 2014 Elsevier Inc. All rights reserved.
Introduction The pituitary gland is a key structure in the hypothalamic–pituitary– gonadal (HPG) axis; it plays an important role in sexual maturation during puberty. The activation of the HPG axis during this developmental period involves: 1) the release of the gonadotropinreleasing hormone (GnRH) from the hypothalamus; 2) the release of gonadotropins, luteinizing hormone (LH) and follicle stimulating hormone (FSH) from the pituitary gland; and 3) the release of sex steroids from maturing gonads. Even though the pituitary gland is a small structure, its volume can be quantified using magnetic resonance imaging (MRI). Previous
⁎ Corresponding author at: Rotman Research Institute, 3560 Bathurst St., Toronto, Ontario M6A 2E1, Canada. E-mail address: [email protected] (T. Paus).
http://dx.doi.org/10.1016/j.neuroimage.2014.02.030 1053-8119/© 2014 Elsevier Inc. All rights reserved.
neuroimaging studies have noted that pituitary size increases with age in children and adolescents (e.g., Fink et al., 2005; MacMaster et al., 2007; Takano et al., 1999), undergoes a growth spurt during puberty (MacMaster et al., 2007; Takano et al., 1999), and varies with plasma levels of FSH and estradiol during early (10 to 15 years) puberty in females (Peper et al., 2010). In the latter study, pituitary volumes were not related to LH and testosterone in females, nor to any sex hormones in males in this age range. As maximal sex hormone production in males and females is found at a more advanced pubertal stage (Butler et al., 1989; Sehested et al., 2000), it is important to examine the relationship between sex hormones and the pituitary gland in more advanced stages of puberty. Here, we examined the relationship between pituitary volume and development-related variables, namely age, puberty stages, and sex steroids, in a large sample of typically developing adolescents. We hypothesized that – after controlling for total brain volume – volumes of the pituitary gland will correlate with increased age, advanced
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puberty stage, and higher levels of sex steroids in both male and female adolescents. To quantify the pituitary volumes, we performed automatic segmentations of the pituitary gland using a novel label-fusion based methodology known as the MAGeT Brain algorithm (Chakravarty et al., 2013). The MAGeT Brain algorithm has been validated previously for the segmentation of subcortical structures (such as striatum, globus pallidus, and thalamus; Chakravarty et al., 2013) and, more recently, the hippocampus and cerebellar lobules (Park et al., 2014). In this study, we also validated the use of the MAGeT Brain algorithm for the segmentation of the pituitary gland. Methods Participants Data were collected from 1019 adolescents (12 to 18 years of age) recruited in the Saguenay Lac St. Jean (SLSJ) region in Quebec, Canada, as part of the Saguenay Youth Study (Pausova et al., 2007). Participants were recruited through high schools in the SLSJ region. Interested families were contacted by a research nurse for a telephone interview to determine their eligibility for the study. The main exclusion criteria are: (1) positive history of alcohol abuse during pregnancy; (2) positive medical history for meningitis, malignancy, and heart disease requiring heart surgery; (3) severe mental illness (e.g., autism, schizophrenia) or mental retardation (IQ b 70); and (4) MRI contraindications. Data collection for the Saguenay Youth Study (SYS) occurred over several visits. First, a research nurse visited homes of the participating families; during the visit, parents and adolescents signed consent and assent forms, respectively, and filled out a number of questionnaires. This was followed by a hospital visit for magnetic resonance imaging, cardiovascular and metabolic phenotyping. Cognitive testing (6 h) took place in a different day and, in most participants, it was carried out in a dedicated room at their respective school. Finally, the research nurse visited the participant's school to obtain a morning blood sample and to administer additional questionnaires. Details of recruitment and testing procedures are provided in Pausova et al. (2007). In the current report, we excluded 41 participants after quality control of MR images and MAGeT segmentations. Of the excluded participants, 36 participants had poor MR images; 3 participants had poor pituitary segmentations; and 2 participants had abnormal pituitaries. We also excluded 16 participants after quality control of behavioral and sex steroids data. Of the excluded participants, 12 participants did not have measures of sex steroids, 2 male participants had testosterone levels N3 standard deviations away from the mean, and 2 pre-menarche female participants had estradiol levels N3 standard deviations away from the mean. After the exclusions, 962 participants remained for analyses (467 males and 495 females; M = 180.4 months of age; SD = 22 months of age; range = 137– 230 months of age). MRI acquisition Structural MRI data were collected on a Phillips 1.0-T superconducting magnet. T1-weighted images were acquired using the following parameters: 3D RF-spoiled gradient-echo scan with 140–160 slices, 1-mm isotropic resolution, TR = 25 ms, TE = 5 ms, and flip angle = 30°. MRI analysis Pituitary volumes were derived using a novel segmentation method that generates a library of multiple automatically generated templates of different MR images within a dataset (MAGeT Brain algorithm; Chakravarty et al., 2013). Using the MAGeT Brain algorithm, pituitary volumes were estimated in the following three-step process. First, manually labeled pituitary
Fig. 1. Sagittal (top), coronal (middle), and axial (bottom) view of the pituitary gland from a T1-weighted MR image. The pituitary is manually labeled in red on the right.
glands (Fig. 1) of 12 participants were transferred – via non-linear registration – to label MR images of 15 other participants chosen at random from the full dataset. This resulted in a total of 180 segmentations (12 manually labeled pituitary glands × 15 participants) making up the template library. Second, each segmentation in the template library was used to label MRIs of all 962 participants via non-linear transformation. This resulted in 180 segmentations per participant. Third, based on the voxel-wise majority vote, the label occurring most frequently at a voxel was retained (Collins and Pruessner, 2010). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium (Loken et al., 2010). The final labels were visually inspected for quality along with their respective native MR image for all participants (by AW). Using a subset of the participants (n = 33), we validated the accuracy of the MAGeT Brain algorithm for the pituitary gland by comparing the automatic segmentations produced with their respective manual segmentations (generated by AW blind to any identifying participant information). The segmentations were generated using Display, which is part of the minc suite of software tools (http://www.bic.mni.mcgill. ca/ServicesSoftware/HomePage). Sagittal, coronal, and axial views of the MR image were used to locate the pituitary gland. The boundaries of the pituitary gland are detailed in Peper et al. (2010). There was
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high spatial overlap between the 33 manual segmentations and their respective automatically generated labels (mean Dice Kappa = 0.915, SD = 0.019, range = 0.877–0.946). Using the minc suite of software tools, total brain volumes (including ventricles) were estimated by conducting non-linear transformation of the brain mask volume from the average brain (SYS808) to the native space of each participant. Puberty Development Scale The Puberty Development Scale (PDS; Peterson et al., 1988) is a self-report measure of pubertal development based on the Tanner stages. The adolescent is asked to report on changes in the following characteristics: growth spurt in height, pubic hair, and skin change for both males and females; facial hair growth and voice change for males only; and breast development and menarche in females only. Each item is rated on a 4-point scale ranging from 1 to 4. PDS classifies the adolescent into the following five categories of pubertal status: (1) prepubertal; (2) beginning pubertal; (3) midpubertal; (4) advanced pubertal; and (5) postpubertal. Carskadon and Acebo (1993) found a significant positive correlation between self-rated PDS and physician ratings (r = 0.841, p b .001) of pubertal development, demonstrating that the self-rated PDS is a valid measure. Serum testosterone and estradiol Fasting blood samples were drawn between 8:00 a.m. and 9:00 a.m. and analyzed to measure serum levels of total testosterone (nanomoles per liter) and levels of estradiol (picomoles per liter). To measure levels of total testosterone, the first batch of blood samples was analyzed via radioimmunoassay (Testosterone RIA DSL-4000; Diagnostic Systems Laboratory Inc., TX); and the second batch of blood samples was analyzed via enzyme-linked immunosorbent assays (Testosterone EIA-1559; DRG International, NJ). Levels of total testosterone were standardized by calculating z-scores of the testosterone values within each batch to allow for further statistical analyses. To measure levels of estradiol, the first batch of blood samples was analyzed via an automated chemiluminescence immunoassay on ADVIA Centaur Immunoanalyzer (Siemens Healthcare Diagnostics Ltd.), and the second batch of blood samples was analyzed via enzyme-linked immunosorbent assays (Estradiol EIA-2693; DRG International; NJ). Levels of estradiol were standardized in pre-menarche females by calculating z-scores of the estradiol values within each batch to allow for further statistical analyses. Statistical analysis Using linear regression, first we examined how age (in months), puberty stage, total testosterone levels (in males only), and estradiol levels (in pre-menarche females only) predict (each independently) pituitary volumes in males and females. Then, we examined the contributions of the individual variables over and above the other variables by conducting several multiple regression analyses: age only (Model 1); age and puberty stage (Model 2); age and sex steroid (Model 3); and age, puberty stage, and sex steroid (Model 4). For males, the sex steroid in Models 3 and 4 was total testosterone, and for pre-menarche females, the sex steroid in Models 3 and 4 was estradiol. Finally, we calculated F-tests to determine whether these models were significantly different from each other. Results Male and female adolescents did not differ in their age, t(960) = 1.63, p = 0.10. As expected, females were in a more advanced stage of puberty (M = 4.11, SD = 0.71) compared with males (M = 3.38, SD = 0.86), t(960) = 14.38, p b 0.001. Females had larger (absolute) pituitary volumes (M = 0.632 cm3, SD = 0.110 cm3) compared with
males (M = 0.564 cm3, SD = 0.108 cm3), t(960) = 9.66, p b .001, despite males having larger total brain volumes (M = 1373 cm3, SD = 93 cm3 ) compared with females (M = 1241 cm 3 , SD = 87 cm3), t(960) = 22.66, p b .001. Absolute pituitary volumes correlated with total brain volume for males, r = .19, p b .001, and for females, r = .21 p b .001. There was no significant relationship between age and total brain volume in males R2 = .001, F(1, 465) = 0.50, p = .48, and females R2 = .00006, F(1, 493) = 0.03, p = .86. The mean and standard deviations for age, puberty stage, and sex steroid levels for males and females are presented in Table 1. To control for global differences in brain size, we adjusted pituitary volumes by the total brain volume using a linear regression: the residuals from this regression were added to the mean pituitary volume for each sex to calculate the adjusted pituitary volume (dependent variable). From now on, we will use the term ‘pituitary volume’ to refer to these adjusted volumes. Age and puberty stage Using linear regression analyses, we examined how age (in months) and puberty stage, each considered separately, predict pituitary volumes in males and females. Age accounted for a significant amount of the pituitary volumes in males, R2 = .21, F(1, 465) = 126.8, p b .001 and in females R2 = .085, F(1, 493) = 46.05, p b .001 (Fig. 2). Puberty stage accounted for a significant amount of the pituitary volumes in males, R2 = .26, F(1, 465) = 164.9, p b .001 and in females R2 = .15, F(1, 493) = 87.66, p b .001 (Fig. 2). The correlations and linear R2 of these variables are also presented in Table 2. Next, a multiple regression analysis was conducted to evaluate whether puberty stage predicted pituitary volumes over and above age. Puberty stage accounted for a significant proportion of the pituitary volume variance after controlling for age in males, R2 change = .078, F(1, 464) = 51.28, p b .001, and in females, R2 change = .067, F(1, 492) = 38.90, p b .001 (Model 1 versus Model 2 in Table 3). Total testosterone levels Using linear regression analyses, we examined how serum total testosterone levels predict pituitary volumes in males. Testosterone accounted for a significant amount of the pituitary volumes in males, r2 = .24, F(1, 465) = 147.9, p b .001 (Fig. 3 and Table 2). A multiple regression analysis was conducted to evaluate whether total testosterone levels predicted pituitary volumes over and above age. Testosterone accounted for a significant proportion of the pituitary volume variance after controlling for age in males, R2 change = .074, F(1, 464) = 47.98, p b .001 (Model 1 versus Model 3 in Table 3). Next, a multiple regression analysis was conducted with age, puberty stage, and total testosterone levels in males as predictors. The linear combination of the three variables was significantly related to pituitary volumes, R2 = .33, F(3, 463) = 75.72, p b .001 (shown as Model 4 in Table 3). Puberty stage predicted significantly over and above age and testosterone, R2 change = .041, F(1, 463) = 28.45, p b .001 (Model 3 versus Model 4 in Table 3). Testosterone predicted significantly over and above age and puberty stage, R2 change = .037, F(1, 463) = 25.3, p b .001 (Model 2 versus Model 4 in Table 3). Based on these results, Table 1 Sample characteristics for males and females. Variable
Age (months) Puberty Testosterone (nmol/L) Estradiola (pmol/L) a
Males
Females
n
Mean
SD
n
Mean
SD
467 467 467 –
179.2 3.38 15.98 –
21.43 0.86 8.21 –
495 495 – 72
181.5 4.11 – 139.03
22.53 0.71 – 100.62
Estradiol values are presented only for pre-menarche females.
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Fig. 2. The linear relationships (solid black lines) between pituitary volumes with age and puberty stage in males (left panel — blue) and females (right panel — red).
both puberty stage and testosterone levels appear to offer unique additional predictive power beyond age.
Estradiol levels Since serum levels of sex hormones fluctuate in females during their menstrual cycle, we restricted analyses of estradiol to pre-menarche females only (n = 72). This analysis allows us to examine the relationship between estradiol levels and pituitary gland volumes without the possible confounding effects of hormone fluctuations in the cycling females (Peper et al., 2010). Using linear regression analyses, we examined whether estradiol levels predict pituitary volumes in pre-menarche females. Estradiol accounted for a significant amount of the pituitary volumes in premenarche females, R2 = .13, F(1, 70) = 10.62, p = .0017 (Fig. 4 and Table 2). We also examined how age (in months) and puberty stage separately predict pituitary volumes in pre-menarche females. Age and puberty stage did not account for a significant amount of the pituitary volumes in pre-menarche females, R2 = .022, F(1, 70) = 1.56, p = .216 and R2 = .024, F(1, 70) = 1.75, p = .19, respectively. It is likely that the restriction of range of age (M = 155.4 months; SD = 11.20 months; range = 144–201 months) and puberty stage (M = 2.85; SD = 0.46; range = 1–3) in pre-menarche females have limited the ability to detect a significant relationship with pituitary volumes. A multiple regression analysis was conducted to evaluate whether estradiol levels predicted pituitary volumes over and above age. Estradiol accounted for a significant proportion of the pituitary volume variance after controlling for age in pre-menarche females, R2 change = .11, F(1, 69) = 8.85, p = .004 (shown as Model 2 in Table 4). Next, a multiple regression analysis was conducted with age, puberty stage, and estradiol levels in pre-menarche females as predictors. The Table 2 Correlations and linear R-square between pituitary volume and development-related variables (each assessed independently of each other) in males and females. Variable
Age Puberty Testosterone (nmol/L) Estradiola (pmol/L) a
Males
Females
r
R2
p-Value
r
R2
p-Value
.46 .51 .49 –
.214 .262 .241 –
b.001 b.001 b.001 –
.29 .39 – .36
.085 .15 – .132
b.001 b.001 – .0017
Estradiol values are presented only for pre-menarche females.
linear combination of the three variables was significantly related to pituitary volumes, R2 = .14, F(3, 68) = 3.76, p = .015 (shown as Model 4 in Table 4). Estradiol predicted significantly over and above age and puberty stage, R2 change = .10, F(1, 68) = 7.93, p = .006 (Model 2 versus Model 4 in Table 4). Puberty stage did not predict significantly over and above age and estradiol, R 2 change = .009, F(1, 68) = 0.74, p = .39 (Model 3 versus Model 4 in Table 4). Discussion Using the MAGeT Brain algorithm to estimate pituitary volumes in 962 adolescents, this is the largest study to-date examining how pituitary volume changes with age, puberty stage, and sex steroids (testosterone and estradiol) during puberty. We found a positive relationship between age and pituitary volumes in both males and females. This finding is consistent with past research that has examined pituitary volume changes during development (e.g., Peper et al., 2010; Takano et al., 1999; Whittle et al., 2012). Although there are early-to-advanced pubertal adolescents in our study, the majority of the females in our study are in their mid-to-late puberty stages. As a result, even though we were able to find that Table 3 Summary of multiple regression analyses for variables predicting pituitary volumes in males (n = 467) and females (n = 495). R2 Males Model 1 Age Model 2 Age Puberty Model 3 Age Testosterone (nmol/L) Model 4 Age Puberty Testosterone (nmol/L) Females Model 1 Age Model 2 Age Puberty
SE B
β
2.30
0.20
0.46
1.13 45.29
0.25 6.32
0.23 0.36
1.32 36.79
0.24 5.31
0.27 0.35
0.68 34.73 27.42
0.26 6.51 5.45
0.14 0.28 0.26
1.40
0.21
0.29
0.25 53.85
0.27 8.63
0.05 0.35
B
.21 .29
.29
.33
.085 .15
p-Value b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001 .01 b.001 b.001 b.001 b.001 b.001 .36 b.001
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A.P.-Y. Wong et al. / NeuroImage 94 (2014) 216–221 Table 4 Summary of multiple regression analyses for variables predicting pituitary volumes in pre-menarche females (n = 72).
Fig. 3. The linear relationship (solid black line) between pituitary volumes with total testosterone levels in males.
pituitary volumes increase with age, the relationship might be even more pronounced in girls during early puberty as demonstrated in Takano et al. (1999). As the sample in our current study includes a range of early-toadvanced pubertal adolescents, we were able to demonstrate a significant positive relationship between puberty stage (as measured by PDS; Peterson et al., 1988) and pituitary volumes in both males and females. That is, a more advanced puberty stage was associated with larger pituitary volumes. This relationship remained after controlling for age, suggesting that puberty stage offers predictive power beyond age. Takano et al. (1999) have speculated that the pronounced pituitary growth during adolescence reflects hypersecretion of pituitary hormones (i.e., gonadotropins — LH and FSH) at this time (Elster et al., 1990; Lee et al., 1976; Martha and Reiter, 1991). Indeed, Peper et al. (2010) have found a positive relationship between pituitary volumes and gonadotropins (LH and FSH) in early pubertal females. Although we did not measure gonadotropins in our study, we examined the relationship between pituitary volumes and sex steroids (i.e., testosterone and estradiol), which are sex hormones regulated by gonadotropins. We found that there was a significant positive relationship between pituitary volumes and total testosterone levels in males. That is, higher testosterone levels were significantly related to larger pituitary volumes. This relationship remained significant after controlling for age and puberty stage, demonstrating that despite the large percentage of variance explained by age and puberty stage, total testosterone levels can explain additional variance of the pituitary volumes beyond age and puberty stage. Although Peper et al. (2010) have examined the relationship between testosterone levels and pituitary volume, they were not able to find a significant relationship in males. The authors' explanation for their null findings in males was that the males studied in their sample were in a less advanced pubertal stage: since males do not produce peak testosterone levels until a later pubertal stage, Tanner stage 4 (Butler et al., 1989), it might be more difficult to examine a clear
Fig. 4. The linear relationship (solid black line) between pituitary volumes with estradiol levels in pre-menarche females. Estradiol remains a significant predictor of pituitary volumes when the two data points N2 SD were also removed, R2 = .077, F(1, 68) = 5.68, p = .02.
Pre-menarche females
R2
Model 1 Age Model 2 Age Puberty Model 3 Age Estradiol (pmol/L) Model 4 Age Puberty Estradiol (pmol/L)
.022
B
SE B
β
1.31
1.05
0.15
1.19 30.65
1.05 25.26
0.13 0.14
0.33 50.69
1.05 17.04
0.04 0.51
0.287 20.95 48.58
1.049 24.32 17.25
0.03 0.10 0.49
.042
.13
.14
p-Value .22 .22 .23 .26 .23 .007 .76 .004 .015 .79 .39 .006
relationship between pituitary volumes and sex hormone production during early puberty. Since the sample in our current study includes early-to-advanced pubertal adolescents and a larger number of participants (and thus more power to detect a significant difference), unlike Peper et al. (2010) we were able to demonstrate that pituitary volumes are positively related to total testosterone levels. To exclude the possible confounding effects of hormonal fluctuations in menstrual-cycling females, we examined the relationship between pituitary volume and estradiol levels in pre-menarche females only. In pre-menarche females, higher estradiol levels were related to larger pituitary volumes. This relationship remained significant after controlling for age and puberty stage, demonstrating that despite the large percentage of variance explained by age and puberty stage, estradiol levels can explain additional variance of the pituitary volumes beyond age and puberty stage. The positive relationship between estradiol and pituitary volume in females is consistent with Peper et al. (2010). In pre-menarche females, estrogen may have been released by primordial follicles, which have undergone varying degrees of maturation to the stage of the early Graafian follicle (Widholm et al., 1974). Besides the ovarian origin, it is important to note that some of the estrogen is of adrenal origin. Since GnRH from the hypothalamus and the gonadotropins from the pituitary gland either indirectly or directly trigger the release of sex steroids, including testosterone and estradiol, it seems reasonable to suggest that larger pituitary glands (presumably due to GnRH effects) result in increased production of sex steroids. One should be cautious, however, when drawing conclusions about the directionality of the relationship between pituitary volume and sex hormones, because the latter also regulate GnRH and gonadotropin production and release via negative feedback loops. Although age, puberty stage, testosterone levels, and estradiol levels were able to explain significant amount of variance in pituitary volumes, it is important to note that pituitary segmentation used here did not distinguish between the anterior lobe and the posterior lobe of the pituitary gland. The anterior lobe of the pituitary gland produces and releases HPG axis-related hormones (i.e., gonadotropin hormones), as well as adrenocorticotropic hormone (ACTH), growth hormone (GH), thyroid-stimulating hormone (TSH), and prolactin. The posterior pituitary is involved in the secretion of oxytocin and vasopressin (Tran et al., 2004). As a result, it is likely that other hormones (i.e., other than HPG axis-related hormones) released by the anterior and posterior pituitary gland influence the total pituitary volume. For example, mental disorders that are characterized by elevated ACTH and cortisol levels through hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis were associated with enlarged pituitary glands. Specifically, larger pituitary volumes were observed in patients with depression (Krishnan et al., 1991; MacMaster and Kusumakar, 2004; MacMaster et al., 2008), firstepisode psychosis (Pariante et al., 2004), and post-traumatic stress disorder (Thomas and De Bellis, 2004). In addition, it has been suggested
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that enlarged pituitary volumes observed in pregnant and postpartum women may be related to the increased prolactin production and secretion during pregnancy (Dinc et al., 1998). In conclusion, we found that the pituitary gland undergoes robust growth with age and puberty stage during adolescence. In addition, we found a significant relationship between pituitary volumes and total testosterone levels in males and a significant relationship between pituitary volumes and estradiol levels in pre-menarche females. Finally, this work demonstrates that the MAGeT Brain segmentation algorithm can estimate the volume of the pituitary gland with high accuracy. Acknowledgments We thank the following individuals for their contributions in acquiring data: Manon Bernard (database architect, The Hospital for Sick Children), Jacynthe Tremblay and her team of research nurses (Saguenay Hospital), Helene Simard and her team of research assistants (Cégep de Jonquière) and Dr. Rosanne Aleong (program manager, Rotman Research Institute). TP is the Tanenbaum Chair in Population Neuroscience at the Rotman Research Institute, University of Toronto. Funding support: The Saguenay Youth Study project is funded by the Canadian Institutes of Health Research (TP, ZP) (MOP178790), Heart and Stroke Foundation of Canada (Quebec) (ZP) (MOP178790), and the Canadian Foundation for Innovation (ZP) (MOP178790). Computations were performed on the GPC supercomputer at the SciNet HPC Consortium. SciNet is funded by: the Canada Foundation for Innovation under the auspices of Compute Canada; the Government of Ontario; Ontario Research Fund — Research Excellence; and the University of Toronto. References Butler, G.E., Walker, R.F., Walker, R.V., Teague, P., Riad-Fahmy, D., Ratcliffe, S.G., 1989. Salivary testosterone levels and the progress of puberty in the normal boy. Clin. Endocrinol. 30, 587–596. Carskadon, M.A., Acebo, C., 1993. A self-administered rating scale for pubertal development. Journal of Adolescent Health. 14, 190–195. Chakravarty, M.M., Steadman, P., van Eede, M.C., Calcott, R.D., Gu, V., Shaw, P., Raznahan, A., Collins, D.L., Lerch, J.P., 2013. Performing label-fusion-based segmentation using multiple automatically generated templates. Hum. Brain Mapp. http://dx.doi.org/10. 1002/hbm.22092. Collins, D.L., Pruessner, J.C., 2010. Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion. Neuroimage 52, 1355–1366. Dinc, H., Esen, F., Demirci, A., Sari, A., Resit, Gümele H., 1998. Pituitary dimensions and volume measurements in pregnancy and post partum. Acta Radiol. 39, 64–69. Elster, A.D., Chen, M.Y., Williams III, D.W., Key, L.L., 1990. Pituitary gland: MR imaging of physiologic hypertrophy in adolescence. Radiology 174, 681–685. Fink, A.M., Vidmar, S., Kumbla, S., Pedreira, C.C., Kanumakala, S., Williams, C., Carlin, J.B., Cameron, F.J., 2005. Age-related pituitary volumes in prepubertal children with
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