Glymphatic system dysfunction in pediatric growth hormone deficiency evidenced by multiple MRI metrics

Introduction

Growth hormone (GH), a peptide hormone secreted by the anterior pituitary gland, regulates the production of insulin-like growth factor-1 (IGF-1) and promotes linear bone growth through the GH/IGF-1 signaling axis (1). Growth hormone deficiency (GHD), primarily caused by hypothalamic–pituitary dysfunction and resulting in insufficient GH secretion, affects approximately 1 in 4,000 children (2). Clinically, GHD is characterized by delayed growth and disproportionate short stature. Beyond its established role in somatic growth, accumulating evidence suggests that GH also exerts neurotrophic effects, including the promotion of neuronal survival, synaptic plasticity, and regulation of cerebral metabolism (3). Moreover, disruptions in the GH/IGF-1 axis may compromise synaptic pruning and impede cerebral metabolic waste clearance mechanisms (4). However, the nature and extent of cerebral waste clearance impairment in children with GHD remain largely unknown.

The glymphatic circulation plays an important role in the clearance of brain metabolic waste. In recent years, an increasing number of neuroimaging studies have focused on its role in neurodevelopmental diseases. For instance, children with autism spectrum disorder (ASD) have been reported to exhibit enlarged subarachnoid space and impaired cerebrospinal fluid (CSF) clearance, suggesting dysfunction within the glymphatic system (5). Similarly, alterations in glymphatic function have been observed in individuals with attention-deficit hyperactivity disorder (ADHD) (6). Given the frequent comorbidity between ADHD and Tourette syndrome—a condition potentially associated with abnormal neurotransmitter activity—these findings hold particular significance. In Tourette syndrome, glymphatic markers have been found to correlate with the severity of motor symptoms, implicating the glymphatic system in the disease’s pathophysiology (7). Despite these insights, the involvement of the glymphatic system in pediatric GHD remains poorly understood.

Although the glymphatic system plays a vital role in metabolic waste clearance, direct in vivo assessment of its structural and functional changes remains challenging. To overcome this, a variety of non-invasive magnetic resonance imaging (MRI)-based methodologies have been developed to evaluate different aspects of glymphatic function. Choroid plexus volume (CPV), measurable via high-resolution MRI, reflects CSF production abnormalities and has emerged as a useful biomarker in related studies (8). In 2017, the diffusion tensor imaging-based analysis along the perivascular space (DTI-ALPS) method was proposed as a novel approach for evaluating the function of the glymphatic system, specifically its efflux pathway (9). However, recent studies have underscored several intrinsic limitations of the DTI-ALPS method. These include its limited specificity in distinguishing glymphatic activity from vascular-related changes (10), reduced applicability in pediatric populations (11), and potential confounding from non-glymphatic factors such as white matter integrity (12,13). Consequently, DTI-ALPS is now regarded more as a composite imaging marker rather than a direct functional readout of glymphatic activity, although it may still partially reflect glymphatic clearance. As morphological and spatial abnormalities in the perivascular space (PVS) offer valuable insights into glymphatic dysfunction and its underlying pathophysiology, the incorporation of PVS imaging analysis has been gaining growing attention in recent research.

Given these methodological considerations, a comprehensive evaluation of the glymphatic function necessitates a multiparametric MRI approach. In this study, we employed three complementary MRI markers to assess glymphatic function in children with GHD: CPV (reflecting CSF production), PVS burden (indicating glymphatic influx), and DTI-ALPS index (capturing glymphatic efflux). Furthermore, correlations between glymphatic imaging metrics and clinical characteristics were evaluated within the GHD cohort. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1108/rc).

Methods

Ethical approval

The Institutional Review Board of The First Affiliated Hospital of Sun Yat-sen University (No. [2021]082) approved this prospective investigation. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and has been registered at https://www.chictr.org.cn/searchproj.html (identifier: ChiCTR2100048109; date: July 2021). Informed written consent was provided by the legal guardians of all participants prior to study enrollment.

Participants

Children with GHD were recruited according to the following inclusion criteria: (I) stature significantly below average, defined as a height falling below the 3rd percentile or more than two standard deviations beneath the mean for age- and sex-matched normative data; (II) less than 10 µg/L peak serum GH level with at least two provocative stimulations; (III) no other clinically significant neurological or psychiatric diseases; (IV) no adrenocorticotropic hormone (ACTH) deficiency, thyroid-related diseases, hypoglycemia, or familial genetic as well as metabolic diseases; and (V) right-handedness.

Simultaneously, a control group of typically developing (TD) children, matched for age and sex, was enrolled based on the following eligibility criteria: (I) the body height was within the normal ranges of the age-matched population; (II) right-handedness; and (III) without MRI contraindication.

No sedation or anesthesia was administered to any participant during MRI acquisition. Additionally, participants were excluded if they met any of the following criteria: (I) prior administration of GH replacement therapy; (II) a history of brain lesions identified on MRI, or any diagnosed psychiatric or neurological disorders; and (III) contraindications to MRI.

From August 2021 to January 2023, 45 pediatric GHD and 43 TDs were recruited. Finally, 40 pediatric GHD and 40 TDs were enrolled, and 5 pediatric GHD and 3 TDs were excluded due to image artifacts or significant registration errors (Figure 1).

Figure 1 The flow diagram of study selection. DTI-ALPS, diffusion tensor imaging-based analysis along the perivascular space; GHD, growth hormone deficiency; PVS, perivascular space; TD, typically developing.

Clinical data

Age, sex, height, weight, and body mass index (BMI) were recorded in GHD and TD children. Besides, IGF-1, ACTH, cortisol, and thyroid-stimulating hormone (TSH) levels were retrieved from electronic medical records in the GHD group. In addition, the GHD group underwent two standardized GH stimulation tests. Blood samples were collected at baseline (0 minutes) and subsequently at 30, 60, 90, and 120 minutes following an intravenous bolus administration of pyridostigmine in combination with levodopa. The peak GH level was determined based on these stimulation protocols. Furthermore, we assessed behavioral alteration in the GHD group using the Achenbach Child Behavior Checklist (CBCL).

MRI acquisition

Whole-brain MRI scans were performed on a 3.0-Tesla scanner (SIGNA Pioneer MR, GE HealthCare, Chicago, IL, USA) equipped with a 32-channel head coil. Following the exclusion of intracranial structural abnormalities using conventional T2-weighted imaging, all participants subsequently underwent sagittal three-dimensional (3D) T1-weighted fast spoiled gradient-recalled echo (T1w-FSPGR), additional T2-weighted sequences, and DTI acquisitions.

The specific MRI protocol including the following sequences: (I) T1w-FSPGR: repetition time (TR) =8.5 ms; echo time (TE) =3.3 ms; flip angle =12°; slice thickness =1 mm with no interslice gap; in-plane resolution =1.0×1.0 mm²; field of view (FOV) =25.6 cm; matrix size =256×256; number of excitations (NEX) =1.0; parallel imaging acceleration factor =2, acquisition time =5 minutes 28 seconds; (II) the fast spin-echo T2-weighted images: TR =7,365 ms, TE =133.2 ms, slice thickness =6 mm/no gap, pixel size =0.5 mm × 0.5 mm, FOV =256 mm, and matrix size =512×512_, acquisition time =1 minutes 6 seconds; (III) DTI: TR =10,000 ms, TE =88.6 ms, FOV =256 mm, matrix size =128×128, voxel size =2 mm isotropic, NEX =1.00, number of directions =32, and b value =1,000 s/mm²_, and one non-diffusion-weighted T2 image (b0), parallel imaging acceleration factor =2, acquisition time =5 minutes 50 seconds.

MRI data processing

Structural data analysis

For each participant, whole-brain tissue volume was segmented using FreeSurfer version 6.0.0 (http://surfer.nmr.mgh.harvard.edu/fswiki) with the recon-all pipeline. Gray matter volume (GMV), CSF volume, and intracranial volume (ICV) were quantitatively extracted from 3D T1-weighted images using the automated processing pipeline implemented in FreeSurfer. Then, the white matter volume (WMV) was measured as the addition of “cerebral WM”, “cerebellar WM”, “brainstem”, and “corpus callosum”. The gross CPV was defined as the sum of the left and right CPV (Figure 2A).

Figure 2 Visualization of CPV segmentation (A) and ALPS-ROI placement (B). (A) T1-weighted images from a child with GHD showing choroid plexus segmentation (yellow overlay, FreeSurfer 6.0.0). (B) Schematic demonstration of DTI-ALPS ROI placement on an axial DTI slice: projection (yellow), association (green), and perivascular (red) ROIs for calculating the ALPS index. CPV, choroid plexus volume; DTI-ALPS, diffusion tensor imaging-based analysis along the perivascular space; GHD, growth hormone deficiency; ROI, region of interest.

PVS burden analysis

For each participant, the T2-weighted images were assessed for technical quality prior to PVS segmentation (14-16), following the protocol established in previous studies. Subsequently, PVS segmentation within the whole-brain white matter was performed using the uAI Research Portal (Shanghai United Imaging Intelligence Co. Ltd., Shanghai, China). The segmentation outputs were subsequently re-imported into ITK-SNAP software (https://www.itk.org) and superimposed onto the corresponding original T2-weighted images for visual verification. Manual corrections were independently performed by two experienced neuroradiologists, each with five years of professional experience, who were blinded to all clinical and demographic information. Before correction, the two neuroradiologists underwent standardized training to ensure consistent criteria for identifying and correcting PVS. Following the initial correction, they reviewed the images collaboratively, resolving discrepancies and reaching a consensus to ensure objectivity and consistency. They excluded structures outside the cerebrum and ensured that only PVS were accurately segmented. Finally, the PVS count and volume within the whole-brain white matter were collected.

Diffusivity and DTI-ALPS index analysis

For each participant, DTI data underwent preprocessing to correct for off-resonance effects and eddy current-induced distortions. Slice-to-volume misalignment, head motion artifacts, and signal outliers were further addressed using the Eddy correction tool (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Eddy), executed within the MATLAB R2019b (MathWorks, Natick, MA, USA) environment (17). The DTI-ALPS index was calculated following protocols established in previous studies (18,19). Diffusivity maps were calculated for three directions: x-axis (Dx), y-axis (Dy), and z-axis (Dz), corresponding to the right-left, anterior-posterior, and inferior-superior axes, respectively. All diffusivity maps were co-registered to the JHU-ICBM-FA-1 mm standard fractional anisotropy (FA) map template. Two experienced neuroradiologists (each with 5 years of experience) who were blinded to clinical and demographic information processed the data. For each participant, a 5-mm region of interest (ROI) was manually drawn on three consecutive axial slices located superior to the bilateral lateral ventricles within the left cerebral hemisphere, considering the right-handedness of all participants. Diffusivity values were extracted from each ROI, and their mean values were computed (Figure 2B). Measurements obtained independently by the two neuroradiologists were then averaged to generate the final diffusivity metrics for each participant. The DTI-ALPS index was calculated using the following formula: ALPS-index = mean (Dxproj, Dxassoc) / mean (Dyproj, Dzassoc).

Statistical analysis

All statistical analyses were performed using SPSS software (version 29.0; IBM Corp., Armonk, NY, USA). The Shapiro-Wilk test was applied to evaluate the normality of continuous variables. Group differences in age and sex were assessed using independent-samples t-tests and chi-squared tests, respectively. A two-tailed P value of <0.05 was considered indicative of statistical significance.

Inter-rater reliability for the DTI-ALPS index was examined using intraclass correlation coefficient analysis. Differences in PVS metrics and brain volumetric measures (excluding ICV) were evaluated using a general linear model (GLM), with adjustments for age, sex, and ICV. For the remaining imaging metrics, GLMs were conducted with age and sex as covariates. Multiple comparisons were corrected using the Benjamini-Hochberg false discovery rate (FDR) procedure. Statistical significance was defined as P_FDR<0.05.

Partial correlation analyses controlling for age and gender were conducted to assess the associations between clinical data and significant MRI metrics. A P value less than 0.05 was considered statistically significant.

Results

Clinical data of participants

Initially, 45 GHD and 43 TD children were recruited for this study. Ultimately, 40 children with GHD {25 males, 15 females; median age 8.93 years [interquartile range (IQR), 7–11 years]} and 40 TD children [25 males, 15 females; median age 8.68 years (IQR, 7–11 years)] were included in the final analysis. The remaining participants were excluded based on the following criteria (Figure 1): (I) failure of automatic brain segmentation (3 GHD and 2 TD); (II) head movements (2 GHD); and (III) poor image quality (1 TD).

There were no significant differences in age (P = 0.749) or gender distribution (P=1.000) between the GHD and TD groups, as shown in Table 1. More clinical characteristics, including ACTH, cortisol, and TSH, are presented in Table 1. Detailed behavioral subscale scores from the Achenbach’s CBCL are presented in Table S1.

Between-group differences in brain volume

The comparison of whole-brain tissue volume between the two groups is displayed in Table 2. Compared to TD children, GHD children had decreased CPV (0.77±0.15 vs. 0.83±0.19 mL, P_FDR=0.002). Nevertheless, no significant difference was found in WMV, GMV, CSF volume, and ICV between GHD and TD children.

Between-group differences in glymphatic function

Pediatric GHD demonstrated significant disruption of the glymphatic system compared to TD children, as detailed in Table 3. Specifically, regarding the glymphatic influx pathway, children with GHD exhibited a significantly reduced PVS volume (P_FDR=0.01, Figure 3), as well as decreased PVS count (P_FDR=0.007), PVS-to-WMV ratio (PVS/WMV; P_FDR=0.003), and PVS-to-ICV ratio (PVS/ICV; P_FDR=0.001), compared to TD controls.

Figure 3 Examples of PVS segmentation results in a child with GHD (A) and TD (B) and the comparison of PVS volume (C). (A) Representative T2-weighted images from a child with GHD, showing automated segmentation of PVS (green overlay). (B) Representative T2-weighted images from TD child with segmented PVS. (C) Group comparison of PVS volume between GHD and TD children. GHD children exhibited significantly lower PVS burden than TD controls (4.51±1.74 vs. 6.30±3.34 mL; P_FDR=0.01). *, P_FDR<0.01. FDR, false discovery rate; GHD, growth hormone deficiency; PVS, perivascular space; TD, typically developing.

The inter-rater reliability for the DTI-ALPS index between the two neuroradiologists was considered good, with an intraclass correlation coefficient of 0.80 [95% confidence interval (CI): 0.65–0.90]. Regarding the glymphatic efflux pathway, which is associated with metabolic waste clearance, children with GHD demonstrated significantly lower DTI-ALPS indices compared to TD children (P_FDR≤0.001). Furthermore, group comparisons of additional diffusion metrics are summarized in Table 3.

Analysis of correlations

No statistically significant correlations were observed between glymphatic metrics and the total scores of the Achenbach’s CBCL or other general clinical data. However, in children with GHD, social competence scores were positively correlated with PVS volume (r=0.358, P=0.032), PVS/WMV (r=0.420, P=0.010), and PVS/ICV (r=0.410, P=0.010). In addition, activity level was negatively correlated with CPV (r=−0.377, P=0.023) (Figure 4).

Figure 4 Social competence was positively correlated with PVS volume (A), PVS/WMV (B), and PVS/ICV (C), whereas activity displayed a negative correlation with CPV (D). CPV, choroid plexus volume; ICV, intracranial volume; PVS, perivascular space; WMV, white matter volume.

Discussion

Main findings

In this study, we investigated the in vivo function of the glymphatic system in children with GHD using a multi-modal, non-invasive MRI approach, incorporating CPV, PVS burden, and DTI-ALPS index. First, GHD children exhibited significantly reduced CPV, suggesting altered CSF production. Second, both PVS burden and DTI-ALPS index were decreased, indicating impaired glymphatic influx and efflux, respectively. Finally, for the pediatric GHD cases, Social Competence scores were positively correlated with PVS volume, PVS/WMV, and PVS/ICV, whereas Activity was negatively correlated with CPV. Collectively, these results offer robust evidence of glymphatic dysfunction in pediatric GHD and underscore the potential role of the GH/IGF-1 axis in regulating cerebral metabolic waste clearance.

Specific effects of choroid plexus structure in GHD

This study found that children with GHD exhibited significantly reduced CPV compared to TDs, whereas no significant group differences were observed in WMV, GMV, or ICV. This suggests that GH deficiency may affect the choroid plexus both structurally, as reflected by reduced volume, and functionally, given its critical role in CSF secretion. Mechanistically, previous studies have demonstrated that GH regulates the proliferation and differentiation of choroid plexus epithelial cells via IGF-1 signaling pathways (20), and GH receptor deficiency can lead to disruption of choroid plexus microvilli and reduced CSF production (21). Notably, similar neuroimaging approaches have successfully captured microstructural alterations associated with glymphatic dysfunction, highlighting the value of advanced MRI biomarkers in detecting choroid plexus abnormalities in endocrine-related conditions (22). Moreover, emerging evidence indicates that GH replacement therapy can improve CSF dynamics in adults with GHD (23), further supporting the direct regulatory role of the GH-IGF-1 axis in choroid plexus function and CSF homeostasis.

Glymphatic dysfunction in GHD

Assessment of glymphatic system function revealed significant bimodal abnormalities in children with GHD, encompassing both impaired influx and clearance pathways. In terms of glymphatic influx, children with GHD exhibited a marked reduction in PVS volume, PVS/WMV, and PVS/ICV. As a primary route for glymphatic fluid entry, the structural integrity and perfusion of PVS are highly dependent on CSF dynamics, which are largely driven by choroid plexus secretion (24). The observed reduction in CPV may therefore directly contribute to diminished PVS perfusion. This finding contrasts with the PVS enlargement frequently reported in other neurodevelopmental disorders such as ASD and tic disorders (5,7), suggesting that glymphatic disruption in GHD may arise through distinct biological mechanisms, particularly deficits in IGF-1 signaling rather than neuroinflammation processes.

In addition, impaired glymphatic clearance was reflected by significantly reduced DTI-ALPS indices in GHD children, indicating disrupted directional water diffusion along perivascular pathways. The ALPS index has been previously linked to β-amyloid clearance efficiency (25), and its reduction may point to misalignment or disorganization of astrocytic aquaporin-4 (AQP4) channels at astrocytic endfeet (26). Importantly, the polarization and distribution of AQP4 are known to be regulated by IGF-1 signaling (27). Deficient glymphatic clearance in this context could result in the accumulation of neurotoxic metabolic byproducts, including phosphorylated tau protein, which may indirectly contribute to neurobehavioral deficits via synaptic degeneration or axonal injury. However, in the study, no significant correlation was observed between DTI-ALPS indices and total scores from the Achenbach’s CBCL, potentially due to the limited sample size.

Methodological considerations for DTI-ALPS

Although widely employed as a surrogate marker for glymphatic function, the DTI-ALPS index requires cautious interpretation. Its sensitivity to image acquisition parameters complicates cross-study comparisons, as noted by Agarwal et al. (12). Moreover, Georgiopoulos et al. questioned the validity of efflux efficiency measurements derived from invasive glymphatic tracers in animal models (11), citing poor correlation among methods. Drenthen and van der Thiel further emphasized that reduced ALPS values may reflect underlying axonal injury rather than glymphatic dysfunction alone, given their observed relationship between ALPS and white matter microstructure (28). Additionally, Wright et al. reported significant inter-case variability, raising concerns about the index’s reliability across individuals (13). Importantly, conventional diffusion parameters such as FA and mean diffusivity (MD) are well-established markers of microstructural integrity and may contribute to variability in ALPS measurements (29). Thus, reduced ALPS indices may not exclusively represent impaired glymphatic function but could also reflect concurrent changes in white matter organization, particularly in pediatric populations undergoing rapid neurodevelopment. Future studies should integrate ALPS with FA/MD and complementary imaging modalities (e.g., dynamic contrast-enhanced MRI or intrathecal tracer-based approaches) to improve interpretability.

Potential mechanisms of glymphatic dysfunction in GHD

Based on our findings, we hypothesize that GH deficiency disrupts glymphatic function through IGF-1-mediated dysregulation of AQP-4 channels (30), ultimately contributing to metabolic waste accumulation and neurobehavioral impairments. GHD leads to a reduction in IGF-1 synthesis systemically. This deficiency may downregulate astrocytic AQP4 expression and disrupt its polarized distribution at perivascular endfeet, thereby impairing the directional flow of glymphatic fluid through PVSs and compromising metabolic waste clearance efficiency (31). Impaired clearance may, in turn, promote the accumulation of neurotoxic substances such as reactive oxygen species, which can trigger microglial activation and foster a neuroinflammatory environment (32). Additionally, proinflammatory cytokines (e.g., interleukin-6) may further inhibit GH receptor signaling, potentially creating a self-reinforcing pathological cycle.

Our behavioral correlation findings further support this mechanistic model. Specifically, Social Competence scores were positively correlated with PVS volume. These associations suggest that increased PVS volume, as a structural marker of glymphatic influx pathways, may enhance CSF perfusion and promote the clearance of neuroinflammatory mediators. This, in turn, may help to preserve the functional integrity of prefrontal-limbic networks implicated in social cognition (33). However, the observed negative association between Activity Level and CPV implies that disproportionate or inefficient CSF production or inefficient glymphatic activity may hinder glymphatic circulation, leading to suboptimal clearance capacity. Moreover, reduced IGF-1 levels may impair synaptic plasticity and circuit stability, thereby exacerbating behavioral impulsivity due to its neurotrophic effects on central nervous system development and maintenance (34).

Collectively, these results suggest a hypothetical regulatory cascade within the GH/IGF-1 axis, wherein hormone deficiency leads to glymphatic dysfunction—manifested as reduced PVS volume or AQP4 dysregulation—resulting in impaired metabolic waste clearance, progressive neuroinflammatory stress, and ultimately, deficits in social and behavioral functioning. This proposed pathway offers a theoretical foundation for considering GH/IGF-1 replacement therapy as a strategy to improve neurobehavioral outcomes in GHD. Moreover, PVS volume may serve as a potential imaging biomarker for monitoring therapeutic response. We recommend that future studies integrate longitudinal behavioral assessments with functional neuroimaging to validate the prognostic value of glymphatic metrics and further elucidate the endocrine–glymphatic–neurobehavioral axis as a target for intervention. Another important consideration for future research is the harmonization of MRI acquisition protocols. Variability in spatial resolution, voxel size, and sequence parameters across scanners and centers can markedly influence the quantification of small structures such as PVSs and the accuracy of diffusion-derived indices, including ALPS. Standardizing acquisition protocols with comparable spatial resolution will be essential to enhance reproducibility, enable reliable cross-study comparisons, and facilitate multicenter collaborations.

Limitations

Several limitations of the present study should be acknowledged. First, the relatively small sample size, an inherent constraint in neuroimaging studies on GHD, may limit the generalizability of the findings. Second, the cross-sectional design precludes the establishment of temporal or causal relationships between GHD and glymphatic system abnormalities; future longitudinal studies are warranted to address this gap. Third, the study did not include a direct assessment of AQP4 polarization status, which limits the ability to elucidate underlying molecular mechanisms. Moreover, the spatial resolution achievable with 3.0T MRI and conventional T2-weighted contrast may be insufficient to reliably depict small-diameter PVS; higher-field or optimized sequences may improve delineation.

Conclusions

This study revealed both morphological and physiological abnormalities within the glymphatic network of pediatric GHD using a multiparametric MRI approach. In particular, reductions in CPV, PVS burden, and the DTI-ALPS index suggest impairments in both glymphatic influx and efflux pathways. Dysfunction of the GH-IGF-1 axis may underlie these changes by disrupting AQP4 channel expression and polarization, potentially leading to impaired metabolic waste clearance and neuroinflammation. These findings suggest that glymphatic dysfunction may contribute to the pathogenesis of GHD. However, due to the methodological limitations associated with the DTI-ALPS technique (11,12), our results should be interpreted as indirect evidence of impaired waste clearance. To validate these findings, future research integrating mechanistic and multi-modal imaging is required.

Acknowledgments

We would like to thank the participants and their families and the staff at the MRI at our center for all their help and support.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1108/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1108/dss

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

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1108/coif). The 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of The First Affiliated Hospital of Sun Yat-sen University (No. [2021]082). Written informed consent was obtained from the legal guardians of all the subjects.

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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