Evaluation of gray-matter and white-matter microstructural abnormalities in children with growth hormone deficiency: a comprehensive assessment with synthetic magnetic resonance imaging

Introduction

Short stature is a common developmental disease among children. Growth hormone deficiency (GHD), the most common type of pathological short stature, is characterized by decreased secretion of growth hormone (GH) from the anterior pituitary (1); however, the pathophysiology of pediatric GHD remains elusive. Nevertheless, an increasing number of studies have suggested impairment in the perinatal hypothalamic-pituitary axis may be involved (2,3). GH and insulin-like growth factor-1 (IGF-1) are vital components in the hypothalamic-pituitary axis (4), which is critically involved in linear growth, cognitive function, and even in the brain structure and its maintenance of (5).

The prominent role of the GH-IGF-1 axis in brain morphology and function underlying pediatric GHD had been investigated widely in recent years (6,7). A structural neuroimaging study reported there to be no difference in global gray-matter volume and regional cortical volume between children with GHD (n=11) and typically developing (TD) children (8). However, another study indicated that children with GHD (n=24) had significantly decreased whole-brain gray matter volume, cortical surface area, and thickness of the bilateral hemispheres as compared to those in children with idiopathic short stature (9), which was correlated with the GH level; moreover, cortical regions with significant differences in the mean gray-matter volume and surface area were mainly distributed around the bilateral central sulci and the lateral and basal parts of the temporal lobes (9). In other research, children with GHD (n=15) exhibited reduced volume in the splenium of the corpus callosum, right pallidum, right hippocampus, and left thalamus, indicating that deep gray-matter nuclei may be more susceptible to the variations of GH-IGF-1 axis (10).

Diffusion tensor imaging-derived parameters have been applied to assess axonal and myelin integrity in developmental diseases. Regarding white-matter integrity, lower fractional anisotropy in the corpus callosum and bilateral corticospinal tracts have been found in children with GHD (10). Furthermore, Zhou et al. suggested that mean diffusivity is significantly increased in bilateral corticospinal tracts in children with GHD (8). However, diffusion tensor imaging-derived parameters are not sufficiently specific for the evaluation of myelin (11). Myelin is the critical element in child brain development (12) and is distributed in white matter and in cortical gray matter (13,14). Furthermore, myelin has been reported to be influenced by the GH-IGF-1 axis (5,15). Therefore, pediatric GHD might exert an impact on the structure of white matter and gray matter at the microscopic level. However, due to the considerable heterogeneity of GHD and controls in previous studies and the relatively small sample sizes, the abnormalities in the microscopic biophysical processes of white matter and gray matter in pediatric GHD remain poorly understood.

Synthetic magnetic resonance imaging (MRI)-based methods with the two-dimensional multidynamic multiecho sequence have made possible the simultaneous quantification of T1, T2, and proton density (16); moreover, myelin volume fraction (MVF) can be estimated based on a four-compartment model (17). Consequently, the comprehensive quantification of microstructure alterations of the brain via synthetic MRI-based methods has been widely applied in the investigation of neurological (18) and developmental disorders (19). The aims of this study were as follows: (I) to analyze whole-brain tissue volume alteration in children with GHD using a synthetic MRI-based method; (II) to characterize the regional brain microstructure alterations using MVF, T1, and T2 relaxometry values; and (III) to assess the relationship between significantly altered MRI microstructure metrics and clinical variables. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1404/rc).

Methods

Participants

This prospective study was approved by the institutional review board of The First Affiliated Hospital of Sun Yat-sen University (No. 2021082) and was registered in the Chinese Clinical Trial Registry (https://www.chictr.org.cn/searchproj.html; identifier: ChiCTR2100048109; date: July 2021). The guardians of all participants provided written consent prior to enrollment. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Children with GHD were recruited between August 2021 and January 2023. The inclusion criteria were as follows: (I) short stature, defined as less than the third percentile or below two standard deviations of the mean age-matched population height (20); (II) less than 10 µg/L of peak serum GH level with at least two provocative stimulations; (III) no other clinically significant neurological or psychiatric diseases; (IV) no adrenocorticotropic hormone deficiency, hypoglycemia, thyroid-related diseases, or familial genetic and metabolic diseases; and (V) right-handedness. Meanwhile, TD children were selected from the community using the following inclusion criteria: (I) body height within the normal ranges of the age-matched population; (II) no contraindications to MRI; and (III) right-handedness.

Any participants were excluded if they met any of the following exclusion criteria: (I) a history of GH replacement therapy; (II) a history of any brain lessons detected by MRI or other psychiatric, neurological diseases; and (III) contraindications to MRI.

Clinical data

For children with GHD, age, gender, height, weight, body mass index, serum IGF-1, adrenocorticotropic hormone, cortisol, and thyroid stimulating hormone were obtained from the medical records. Furthermore, children with GHD underwent two provocation tests. Blood samples were collected at time 0, 30, 60, 90, and 120 minutes after intravenous bolus injection of pyridostigmine and levodopa. The GH peak was recorded after the provocation tests. The Achenbach Child Behavior Checklist was also employed. For the TD children, age, gender, height, weight, and body mass index were also recorded.

Imaging acquisition

Whole-brain MRI was performed with a 3-T scanner (SIGNA Pioneer, GE HealthCare, Chicago, IL, USA) using a 32-channel head coil. After any cranial organic lesion was ruled with a T2-weighted sequence, all participants subsequently underwent sagittal three-dimensional T1-weighted fast spoiled gradient echo-based (T1w-FSPGR) and a synthetic MRI sequence. For T1w-FSPGR, the imaging parameters were as follows: repetition time, 8.5 ms; echo time, 3.3 ms; flip angle, 12°; thickness, 1 mm/no gap; pixel size, 1.0 mm × 1.0 mm; number of excitations, 1.00; and scanning time, 5.5 minutes. Regarding synthetic MRI, a two-dimensional multidynamic multiecho pulse sequence, using four automatically calculated saturation delay times and two echo times, was used to acquire the axial sections under the following parameters: repetition time, 10,205.0 ms; echo time, 11.3 and 90.3 ms; flip angle, 20°; thickness, 2 mm/no gap; pixel size, 2.0 mm × 2.0 mm; number of excitations, 1.00; echo train length, 16; and scanning time, 5.5 minutes.

Imaging processing and analysis

Whole-brain evaluation

For each individual, the brain tissue volume was segmented using SyMRI version 11.22 postprocessing software (SyntheticMRAB, Linköping, Sweden). The maps of white-matter, gray-matter, cerebrospinal fluid, non-gray-matter/white-matter/cerebrospinal fluid (NoN), and myelin volume were automatically obtained based according to the instructions in the software. The brain parenchyma volume was the sum of the volume of white matter, gray matter, and NoN. The intracranial volume was the sum of the brain parenchyma volume and cerebrospinal fluid volume. The whole-brain MVF was measured as the ratio of myelin volume to brain parenchyma volume.

Atlas-based evaluation of gray matter

For each individual, the quantitative maps of T1 and T2 were also obtained from the synthetic MRI data using SyMRI version 11.22. First, the T1w-FSPGR image was coregistered to the T1 map for each individual in order to acquire brain regional T1 and T2 values. Second, the coregistered T1 images were normalized to the Montreal Neurologic Institute space via FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/). Third, all T1 and T2 images were subsequently transformed to Montreal Neurologic Institute space. Finally, the values of all 116 regions including cerebrum and cerebellum were extracted for each participant after the Automated Anatomical Labeling (AAL) atlas was applied to all the normalized images.

Atlas-based evaluation of white matter

The details of regional white-matter evaluation are described in our previous paper (19). In brief, postprocessing of the multidynamic multiecho sequence was performed to obtain MVF maps using SyMRI version 11.22. Taking into account B1 inhomogeneity, we then generated T1, T2, and proton density maps from the synthetic magnetic resonance (MR) images (16). The MVF in each voxel was estimated on the basis of a four-compartment model (myelin, excess parenchymal water, cellular water, and free-water volume fractions), which assumes that the T1, T2, and proton density values of each volume fraction in a voxel would contribute to the effective T1, T2, and proton density values of the voxel as a whole (16). The postprocessing time for the generation of MVF map was less than a minute. To normalize the individual myelin map to the Montreal Neurologic Institute space, the proton density map was used as the intermediate modality for bridging two modalities, as it shared the same image space with the myelin map and similar tissue-specific contrasts with the T1-weighted image.

Statistical analysis

SPSS 25 (IBM Corp., Armonk, NY, USA) was used for statistical analyses. The Shapiro-Wilk test was applied to assess the normality of the data. The independent-sample t-test was used to compare the between-group differences in age and clinical data, while the Chi-square test was applied to compare the between-group differences in gender. A P value <0.05 was considered statistically significant.

Analysis of covariance with age, gender, and intracranial volume as nuisance covariates was used to compare between-group differences in total brain structural volume parameters (including gray-matter volume, white-matter volume, brain parenchyma volume, cerebrospinal fluid volume, myelin volume, and NoN volume). Between-group differences in the regional quantitative values (including T1, T2, and MVF maps), global MVF, and intracranial volume were evaluated using analysis of covariance controlled for age and gender. The relationship between the significant quantitative MR parameters and clinical variables (including Achenbach Child Behavior Checklist, IGF-1, and GH peak level) was determined using partial correlations after age and gender were controlled for. The Benjamini and Hochberg false discovery rate (FDR) correction method was applied for multiple comparisons, with P_FDR <0.001 being considered statistically significant.

Results

Participant characteristics

This study initially enrolled 58 children with GHD children and 53 TD children; ultimately, 50 patients with GHD (35 males and 15 females; median age 9 years; interquartile range, 6–11 years) and 50 TD children (35 males and 15 females; median age 9 years; interquartile range, 7–10 years) were included in the study. The other participants were excluded for the following reasons: (I) failure of automatic brain segmentation (3 children with GHD and 2 TD children); (II) head movements (3 children with GHD and 1 TD child); and (III) poor image quality (2 children with GHD). As presented in Table 1, there were no significant differences in the distribution of age (P=0.939) or gender (P=1.000) between the GHD and TD groups. For GHD children, the detailed clinical characteristics are shown in Table 1. The values of adrenocorticotropic hormone, cortisol, and thyroid-stimulating hormone in the children with GHD were within the normal range standardized for age and gender.

Quantification of whole-brain volumetry

The comparison of whole-brain tissue volume between the two groups is presented in Table 2. The whole-brain gray-matter volume was significantly lower in the children with GHD than in TD children (665.904±94.545 vs. 743.188±73.683 mL, P_FDR<0.001). Compared to TD children, the children with GHD had a higher volume of NoN (178.846±96.373 vs. 125.766±42.688 mL, P_FDR<0.001). However, there were no significant between-group differences in the whole-brain white-matter volume, cerebrospinal fluid volume, myelin volume, MVF, brain parenchyma volume, or intracranial volume (all P_FDR values >0.05).

Quantification of regional gray matter and white matter

Atlas-based comparison of T1 and T2 relaxometry values in gray matter

As presented in Table 3 and Figure 1, compared to TD children, the children with GHD showed shorter T1 relaxation values in the bilateral supramarginal gyrus (P_FDR<0.001). However, compared to children with TD, the children with GHD had higher regional T2 relaxation values distributed in widespread gray-matter regions such as the prefrontal, paralimbic, frontal, temporal, limbic, subcortical, occipital, and cerebellar regions. Specifically, these cortical and subcortical regions included the following: (I) the central executive network regions including the bilateral dorsolateral superior frontal gyrus and left middle frontal gyrus; (II) the default mode network including the left medial superior frontal gyrus and left gyrus rectus; (III) the sensorimotor network including the left supplementary motor area; (IV) the limbic regions including the left anterior cingulate and paracingulate gyri, left amygdala, and left olfactory cortex; (V) the striatum including the right pallidum and right putamen; (VI) the visual network including the left cuneus; and (VII) the cerebellum including the vermis.

Figure 1 Compared to the TD group, the GHD group exhibited (A; red) increased T2 relaxometry values and (B; blue) decreased T1 relaxometry values in gray-matter regions. The detailed information can be found in Table 3. TD, typically developing; GHD, growth hormone deficiency.

Atlas-based comparison of MVF and T1 and T2 relaxometry values in white matter

The findings obtained from the atlas-based regional MVF are reported in Table 4 and Figure 2. Briefly, a widespread pattern of increased MVF was observed in the GHD group as compared to the TD group, specifically, in the genu of corpus callosum, right corticospinal tracts, left anterior limb of internal capsule, left posterior limb of internal capsule, left anterior corona radiata, left superior corona radiata, bilateral external capsule, left cingulum, bilateral superior longitudinal fasciculus, and left superior fronto-occipital fasciculus (all P_FDR values <0.001).

Figure 2 Compared to the TD group, the GHD group exhibited (red) increased MVF in the white-matter regions. The detailed information can be found in Table 4. TD, typically developing; GHD, growth hormone deficiency; MVF, myelin volume fraction.

The GHD group had lower T1 relaxometry values in the right superior cerebellar peduncle, right superior longitudinal fasciculus, and tapetum as compared to the TD group (all P_FDR values <0.001). No significant between-group differences were found in the other regions.

As compared to the TD group, GHD group demonstrated significant increases in T2 relaxometry values mainly in the left anterior limb of internal capsule, right anterior corona radiata, right external capsule, and left superior fronto-occipital fasciculus (all P_FDR values <0.001) and significant decreases in T2 relaxometry values in the right superior cerebellar peduncle (all P_FDR values <0.001).

Correlations between quantitative parameters and clinical variables

The total scores of Achenbach Child Behavior Checklist, IGF-1, and GH peak level of the GHD group are summarized in Table 1. Of the 50 children with GHD, 43 completed the Achenbach Child Behavior Checklist. Among the significant magnetic resonance parameters, the T1 relaxation values in the bilateral supramarginal gyrus (left: r=0.382, P=0.014; right: r=0.332, P=0.034) had a significant positive correlation with the total scores of the Achenbach Child Behavior Checklist. Additionally, the T2 relaxation values in the left cuneus (r=0.400; P=0.005) and MVF in the right corticospinal tracts (r=0.313; P=0.032) had a positive relationship with IGF-1 (Figure 3). No significant correlations were noted between significant quantitative parameters and peak GH level.

Figure 3 Correlations between quantitative parameters and clinical variables in pediatric GHD. The T1 relaxation values in the (A) left SMG and (B) right SMG had a significant positive correlation with total scores of the Achenbach Child Behavior Checklist. Moreover, the T2 relaxation values in the (C) left cuneus and (D) MVF in the right corticospinal tract had a positive correlation with IGF-1. SMG, supramarginal gyrus; CBCL, Child Behavior Checklist; IGF-1, insulin-like growth factor-1; GHD, growth hormone deficiency; MVF, myelin volume fraction.

Discussion

Principal findings

The principal findings were as follows: (I) decreased gray matter and increased NoN volume were found in the GHD group at the whole-brain level. (II) Widespread microstructure structure alterations in gray-matter regions spanning the central executive, default mode, sensorimotor, visual, and cerebellar networks were associated with pediatric GHD. (III) Widespread increased regional MVF and altered T1 and T2 relaxometry values were observed mainly in the corpus callosum, corticospinal tracts, internal capsule, corona radiata, external capsule, and cingulum. (IV) The T1 relaxation values in the bilateral supramarginal gyrus had a significant positive correlation with total scores of the Achenbach Child Behavior Checklist. Moreover, the T2 relaxation values in the left cuneus and MVF in the right corticospinal tracts were positively correlated with IGF-1.

Whole-brain volume alteration

We quantitatively evaluated the brain structure alterations between the GHD and TD group using synthetic MRI. The potential of synthetic MRI-based brain segmentation method has been demonstrated in numerous studies, yielding more accurate segmentation as compared to voxel-based morphometry and statistical parametric mapping 12 (21). Furthermore, synthetic MRI is able to produce MVF and myelin volume which T1-based segmentation methods are unable to. MVF based on synthetic MRI sequence has been reported to be correlated with data from other myelin evaluation methods and with histological measures in the postmortem human brain (22,23).

Children with GHD had a significantly decreased whole-brain gray-matter volume, which is consistent with Zhang et al.’s study (9) but inconsistent with other previous studies (8,10). This discrepancy may be attributable to the small sample of children with GHD in previous studies (Zhang et al.’s study: n=24; Zhou et al.’s study: n=15; Webb et al.’s study: n=11). Moreover, the effects of the GH-IGF-1 axis may influence the gray-matter structure (24). NoN is the intracranial content that is not identified as gray matter, white matter, or cerebrospinal fluid, and it is calculated from voxels outside the predetermined tissue clusters in the R1-R2 proton density space, including the vessel and perivessel space, pia mater, T2-weighted hyperintense white matter, and a portion of the choroid plexus (25). The function of GH receptors in choroid plexus has been demonstrated to be involved in the transport of GH across the blood-brain barrier (20). We speculated that the increase of NoN volume in GHD children may involve GH receptor abnormality at the choroid plexus; however, this speculation needs to be confirmed in further research.

Alteration in regional gray-matter microstructure

Gray-matter regions can be classified as specific functional networks (26). Children with GHD have been reported to be affected by abnormalities in the cerebral cortex, especially in the supplementary motor and motor cortex (27). More specifically, Hu et al. observed reductions in whole-brain functional connectivity density in the left post-central gyrus, right precentral gyrus, and left cerebellar lobules 7b and 6, indicating that GHD affects the somatosensory, somatic motor, and cerebellar networks (27). Decreased regional homogeneity has also been observed in the right precentral gyrus, reflecting a dysfunction of the sensorimotor network (28). More recently, it has been indicated that children with GHD exhibit significant dynamic abnormalities in several networks including the default mode, sensorimotor, attention, visual, and execution control networks (29). Thus, consistent with these studies, we also found altered quantitative metrics of gray-matter regions involving the default mode, sensorimotor, attention, visual, execution control, and cerebellar networks in children with GHD. Furthermore, T2 relaxometry values are mainly affected by myelin; however, T1 values are affected by both myelin and iron (14,30). Hence, the widespread microstructure alteration in gray-matter regions was observed in this study using T1 and T2 values, especially T2 mapping.

Regional white-matter microstructure alteration

Recent studies have found decreased fractional anisotropy in the bilateral corticospinal tracts and corpus callosum in children with GHD using tract-based spatial statistics methods (10); however, Zhou et al. reported increased mean diffusivity rather than fractional anisotropy alteration in bilateral corticospinal tracts in children with GHD. The lack of conclusiveness in the related research may be due to the small sample size and the heterogeneity of the control groups. Overall, increased mean diffusivity or decreased fractional anisotropy is typically associated with axonal damage, demyelination, or loss of white-matter integrity (31). White-matter structure is influenced by the GH-IGF-1 axis, while GH is known to exert several effects in nervous system, including prosurvival effects, axonal growth, neuroprotection, synaptogenesis, neurogenesis, and neuroregeneration (7). Additionally, IGF-1 has been reported to promote axon growth, synaptogenesis, and myelination in white matter (15). Thus, as expected, the myelin alterations found in children with GHD in various white-matter regions via quantitative metrics might involve the GH-IGF-1 axis.

Correlations between quantitative metrics and clinical data

Recently, a growing number of neuropsychological studies have noted impairment in cognitive and behavior functioning in children with GHD (27,32), which improves after GH replacement therapy. Furthermore, children with higher Achenbach Child Behavior Checklist scored may be more likely to have behavioral problems (33). Both gray matter (specifically cortico-striatal-limbic loops) and white matter (specifically myelin) are susceptible to GH-IGF-1 axis variations due to the high expression of GH-IGF-1 receptor (20). In line with a previous study (29), we found that children with GHD showed significant dynamic abnormalities in the default mode network. Hence, we speculated the behavioral issues in children GHD may be related to the structural alterations of bilateral supramarginal gyrus affecting the cortico-striatal-limbic loop; however, this needs to be further examined. It was reported that IGF-1 gene delivery can promote the survival of corticospinal neurons in mice with central nervous system injury (34), and in our study, increased MVF in the right corticospinal tracts was positively correlated with IGF-1; this suggests that corticospinal tract development is influenced by the GH-IGF-1 axis.

Our findings further indicate that whole-brain gray-matter volume in children with GHD may be associated with a delay in gray-matter development especially in the cortico-striatal-limbic loop. Quantitative T2 relaxation values reflect the complex factors in the brain, including intra- and extracellular water, as well as myelin (35). Therefore, children with GHD demonstrated decreased T1 values in the gray matter and prolonged T2 values in the gray and white matter likely due to delayed neuronal structural growth and myelination and an enlarged intercellular space. Additionally, the increased vascular interstitial space resulting from a retardation in development may lead to signal alterations (26). We hypothesize that the widespread increase in MVF in children with GHD might be due to the elimination of synapses or presence of compensatory fiber connections in the white matter caused by impairments in the cortical and subcortical connectivity in gray-matter regions.

Limitations

This study involved certain limitations which should be addressed. First, we did not examine the difference in the partial and complete deficiency in children with GHD; however, the number of children with partial and complete GHD was evenly distributed in our study. This, we only focused on the alterations in behavior, leaving the cognitive, executive, and social functions to be evaluated in future research. Second, we employed a cross-sectional design, and a longitudinal study would be needed to observe the brain microstructure alterations after GH replacement therapy.

Conclusions

Overall, reduction of whole-brain gray-matter volume and widespread increase in regional quantitative metrics (MVF, T1, and T2 values) of gray and white matter were found in children in GHD. These findings highlight the changes in brain tissue microstructure of the central executive, default mode, sensorimotor, visual, limbic, striatum, and cerebellar networks underlying GHD and support the involvement of the GH-IGF-1 axis in GHD. Furthermore, the alterations we found in the brain microstructure, especially in the cortico-striatal-limbic loops, might be influenced by the GH-IGF-1 axis and play a key role in the behavioral abnormalities observed in children with GHD.

Acknowledgments

Funding: This study was supported by the Guangdong Basic and Applied Basic Research Foundation, China (No. 2024A1515012561), the Guangzhou Science and Technology Program, China (No. 2023B03J1339), and the Guangdong Medical Development Foundation (No. H2022044).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1404/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1404/coif). G.L.C. is a current employee of Spin Imaging Technology Co., Ltd., Nanjing, China. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The institutional review board of The First Affiliated Hospital of Sun Yat-sen University approved this prospective study (No. 2021082). The guardians of all participants provided written consent prior to enrollment. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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