Disruptions of morphological brain networks and their associations with multi-symptoms in children with spastic cerebral palsy

Introduction

Cerebral palsy (CP) is a group of non-progressive motor and postural disorders resulting from defects or lesions in the developing brain. It is the most common motor disorder syndrome in children (1). From 1988 to 2020, the pooled prevalence of CP in China was approximately 2.07%, with an increasing trend observed in children and adolescents (2). Beyond its effect on motor function, CP encompasses a spectrum of sensory, cognitive, communicative, and behavioral disorders, as well as epileptic seizures and secondary musculoskeletal complications, and thus imposes a significant burden on families and society (3). Spastic cerebral palsy (SCP), which is the predominant subtype of CP, is characterized by hypertonia, hyperreflexia, dyskinesia, and postural abnormalities (3). These symptoms are frequently linked to periventricular white matter injury (PWMI), a condition affecting more than 4% of preterm infants (4-6). Prematurity is recognized as a major risk factor for CP, largely due to the heightened vulnerability of the developing white matter in preterm infants, which makes them more prone to injury and subsequent neurological deficits (7).

Beyond white matter injury, recent neuroimaging studies have highlighted the vital roles of gray matter morphological alterations in understanding the pathology of SCP (8,9). For example, Lee et al. found significant gray-matter volume reductions mainly in the posterior part of the cerebral cortex, including the sensorimotor cortex, basal ganglia, and thalamus, in patients with diplegic SCP compared to healthy controls (9). Despite these insights, such studies rely on volumetric measures that reflect a composite of thickness, area, and folding, and thus may not reveal specific morphological alterations (10,11). Conversely, surface-based morphometry provides a more nuanced understanding of cortical morphology, allowing for the detailed assessment of features such as cortical thickness (CT) (12).

The structural complexity of the brain extends beyond regional morphology, encompassing a network of interconnected regions (13). Local morphological analyses fail to fully capture the intricacies of brain structural reorganization (14). Morphological brain networks, which explore interregional morphological similarities, have proven instrumental in studying neuropsychiatric conditions (15). Previous group-level morphological brain networks estimate interregional morphological connectivity (MC) by examining specific morphological features across participants (16,17). However, such group-level analyses often fail to capture individual variability (18-20). Conversely, single-subject morphological brain networks provide a more nuanced approach to characterizing inter-individual differences and their cognitive and clinical relevance (21-23).

This study aimed to bridge these gaps by investigating single-subject morphological brain networks in SCP children with PWMI. Leveraging the granularity of individual morphological brain networks, we sought to uncover the topological organization and network alterations specific to this subgroup. We hypothesized that the SCP children would exhibit distinct morphological network properties that might be correlated with clinical manifestations. The identification of such patterns could provide critical biomarkers for early diagnosis and personalized therapeutic strategies, thereby improving patient outcomes and reducing the burden on healthcare systems. Specifically, the identification of disrupted network properties may facilitate the earlier prediction of motor and cognitive deficits, enabling timely interventions to mitigate these challenges and enhance overall quality of life of patients. Through this exploration, we aimed to advance the understanding of the neurobiological basis of SCP in children with PWMI and lay the groundwork for novel diagnostic and therapeutic approaches. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2949/rc).

Methods

Ethics statement

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of the Affiliated Hospital of Zunyi Medical University (No. KLL-2024-078), and informed consent was obtained from the parents or legal guardians of all the participants.

Participants

A total of 104 participants were initially recruited from the Affiliated Hospital of Zunyi Medical University, including 73 children with SCP and 31 age- and sex-matched children with typical development (TD). To be included in the study, the patients had to meet the following inclusion criteria: have a diagnosis of SCP as confirmed by pediatric neurologists; and be aged between 4–14 years. After exclusions based on magnetic resonance imaging (MRI) findings or image quality, 42 SCP and 2 TD children were excluded from the study. Ultimately, a total of 60 children (31 SCP children and 29 TD children) were included in the analyses. For full details on the inclusion criteria, see the Appendix 1.

Clinical measurements

All the participants underwent intelligence assessment using the Wechsler Intelligence Scale (Chinese version, IV edition), which includes the verbal comprehension index (VCI), working memory index (WMI), processing speed index (PSI), and full-scale intelligence quotient (FSIQ). All the assessments were performed by experienced pediatricians. The children with SCP underwent additional examinations based on the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS). Under the GMFCS, MACS, and CFCS, the children were rated from I (good) to V (bad). For further details, see the Appendix 1.

MRI acquisition

The MRI data were acquired on a GE Signa HDx 3.0T scanner. The acquisition protocols for three dimensional-T1 MRI data and preprocessing steps, including head stabilization and sedation procedures, are detailed in the Appendix 1.

Data preprocessing and network construction

All the MRI data were preprocessed using the Computational Anatomy Toolbox (CAT12, http://www.neuro.uni-jena.de/cat) in the Statistical Parametric Mapping software (SPM12, http://www.fil.ion.ucl.ac.uk/spm/software/spm12/) to facilitate the extraction of the CT, fractal dimension (FD), gyrification index (GI), and sulcus depth (SD) from the structural images. The morphological maps were re-sampled to a standard template and smoothed using a Gaussian kernel (12 mm for CT, and 25 mm for each of FD, GI, and SD). The Human Connectome Project atlas was applied to parcellate the cortex into 360 regions of interest, each serving as a node. The MC between regions was quantified by calculating the Jensen-Shannon divergence between the regional probability distributions of CT, FD, GI, and SD, resulting in four network types: cortical thickness-based (CTNs), fractal dimension-based networks (FDNs), gyrification index-based networks (GINs), and sulcus depth-based networks (SDNs). For further details on the data preprocessing and network construction procedures, see the Appendix 1.

Statistical analysis

The demographic characteristics of the participants were compared using the chi-square test for the categorical variables, and the t-test or Mann-Whitney U test for the continuous variables based on their distribution. Group differences in the MRI metrics were analyzed using permutation tests with multiple comparisons corrected by false discovery rate (FDR) and threshold-free network-based statistics (TFNBS). Correlations between significant MRI measures and clinical scores were assessed using Spearman partial correlations, adjusted for demographic covariates, with FDR correction applied to control for multiple comparisons. For further details on the methodological specifics, see the Appendix 1.

Effect of gestational age

There were preterm children in the SCP group, which might have confounded the results reported in this study. Thus, we compared the full-term (n=22) and preterm (n=9) children in the SCP group, and found significant differences between the SCP and TD groups in terms of the MRI-derived features (see the Results section below). A FDR procedure was used to correct for multiple comparisons across features.

Results

Demographic and clinical characteristics

The demographic and clinical characteristics of all the participants are shown in Table 1. The gestational age and birth weight were significantly lower in the SCP group than the TD group (both P<0.001). Further, the VCI, WMI, PSI, and FSIQ scores on the Wechsler Intelligence Scale were significantly lower in the SCP group than the TD group (all P<0.001). No significant differences were observed between the SCP and TD groups in terms of age or sex (both P>0.05).

Alterations in regional morphology in children with SCP

No significant differences were found between the SCP and TD groups in terms of the mean morphological values in any regions regardless of the morphological index (P>0.05, FDR corrected).

Alterations in interregional MC in children with SCP

Compared with the TD group, the SCP group exhibited significant reductions in 161 MCs in the CTNs (P<0.05, TFNBS corrected) (Figure 1A). Notably, 59 (36.7%) of these 161 MCs were linked to the right area 25 (Figure 1B). Moreover, at the subnetwork level, the majority of these 161 MCs were linked to brain regions belonging to the default mode network (DMN) (Figure 1C). This was also the case when the MCs were divided into intra-network (Figure 1D) or inter-network (Figure 1E) connections. No significant between-group differences were found in the MCs of the FDNs, GINs, or SDNs (P>0.05, TFNBS corrected).

Figure 1 Decreased MCs in the CTNs in SCP children. (A) Anatomical projection of the decreased MCs in SCP children. (B) Cortical map showing the number of decreased MCs connected to each region in SCP children. Most of the colored regions connected 1–11 decreased MCs, while the right area 25 connected 59 decreased MCs. (C) Matrix indicating the number of decreased MCs that fall within each network and between each pair of networks. (D) Bar chart of the decreased intra-network MC number. (E) Bar chart of the decreased inter-network MC number. AUD network, auditory network; CO network, cingulo-opercular network; CTNs, cortical thickness-based networks; DAN, dorsal attention network; DMN, default mode network; FPN, frontoparietal network; LAN network, language network; MC, morphological connectivity; OA network, orbito-affective network; PM, posterior multimodal network; SCP, spastic cerebral palsy; SM, somatomotor network; VIS1, primary visual network; VIS2, secondary visual network; VM network, ventral multimodal network.

Alterations in morphological brain network topological properties in children with SCP

Compared with the TD group, the SCP group had a longer characteristic path length (L_p) (t=3.909, P=4.0×10^–4) and normalized L_p (t=3.756, P=2.0×10^–4) for the CTNs (Figure 2). No significant between-group differences were found in any nodal properties of the CTNs or any topological properties of the FDNs, GINs, or SDNs (P>0.05, FDR corrected).

Figure 2 Between-group differences in global properties based on the CTNs. Both the characteristic L_p and normalized L_p were significantly higher in the SCP group than the TD group. The values in the violin plots are the residuals of properties after removing the effects of age, sex, weight, and gestational age via multiple linear regression. CTNs, cortical thickness-based networks; L_p, path length; SCP, spastic cerebral palsy; TD, typical development.

Correlation between altered MRI-based measures and clinical variables in children with SCP

In the children with SCP, the MC between the right area 11l and right medial belt (Mbelt) complex was positively correlated with the CFCS (rho=0.662, P=1.7×10^-4) (Figure 3). The characteristic L_p of the CTNs was negatively correlated with the VCI (rho=–0.435, P=0.023), PSI (rho=–0.452, P=0.018), and FSIQ (rho=–0.471, P=0.013), and positively correlated with the GMFCS (rho=0.399, P=0.039) and MACS (rho=0.459, P=0.016). The normalized L_p of the CTNs was negatively correlated with the VCI (rho=–0.445, P=0.020), PSI (rho=–0.465, P=0.015), and FSIQ (rho=–0.475, P=0.012), and positively correlated with the GMFCS (rho=0.436, P=0.023), MACS (rho=0.529, P=0.005), and CFCS (rho=0.419, P=0.030) (Figure 4).

Figure 3 Correlation between the MCs derived from the CTNs and clinical variables. The values in the scatter plots are the residuals of the MCs and clinical variables after removing the effects of age, sex, weight, and gestational age via multiple linear regressions. CTNs, cortical thickness-based networks; CFCS, communication function classification system; 11L, area 11l; MBelt, medial belt; MC, morphological connectivity.

Figure 4 Correlations between the global properties derived from the CTNs and clinical variables. The values in the scatter plots are the residuals of the global properties and clinical variables after removing the effects of age, sex, weight, and gestational age via multiple linear regressions. *, P<0.05 after false discovery rate correction. CFCS, Communication Function Classification System; CTNs, cortical thickness-based networks; FSIQ, full-scale intelligence quotient; GMFCS, Gross Motor Function Classification System; L_p, path length; MACS, Manual Ability Classification System; PSI, processing speed index; VCI, verbal comprehension index.

Effect of gestational age

No significant differences between the full-term and preterm groups were observed for the 161 MCs, characteristic L_p, or normalized L_p in the CTNs that differed significantly between the SCP and TD groups (P>0.05, FDR corrected).

Discussion

In this study, we investigated alterations in single-subject morphological brain networks and their associations with clinical variables in children with SCP. Compared to the TD group, the SCP group exhibited an increased characteristic L_p and decreased MCs in the CTNs. Notably, at the nodal level, 36.7% of the decreased MCs were linked to the right area 25. At the functional subnetwork level, the majority of these MCs were connected with brain regions in the DMN. More importantly, the increased characteristic L_p showed significant correlations with various clinical manifestations, including intelligence level, gross motor function, manual ability, and communication function in patients. Additionally, one of the decreased MCs was significantly correlated with communication function in patients. These findings provide new evidence of brain network alterations in children with SCP from the perspective of single-subject morphological brain networks. The identified alterations may serve as potential biomarkers for the clinical diagnosis and prognosis of the disease.

Interregional MC alterations in the CTNs of SCP children

In this study, we observed a reduction in 161 MCs in the CTNs of children with SCP, most of which were connected to brain regions in the DMN at the functional subnetwork level. This observation aligns with previous findings from a functional MRI study that reported reduced functional connectivity between the DMN and other networks in children with SCP (24). The DMN plays a significant role in various cognitive domains such as social cognition, episodic memory, and language processing (25). Therefore, the weakened connectivity between the DMN and other networks might impair social participation, learning capabilities, and communication functions in children with SCP (26). Notably, the highest number of decreased MCs was linked to the right area 25 at the nodal level. Area 25 belongs to the anterior cingulate cortex (ACC) and is also functionally assigned to the DMN (27). The ACC is not only involved in higher-order functions such as emotion processing and cognitive control (28,29) but also plays a crucial role in pain processing (30). Pain is a common complication in SCP (31), and may be directly caused by symptoms such as muscle tension and spasms (32). The decreased MCs between the ACC and other brain regions might be the underlying neurophysiological mechanism that contributes to pain experiences in SCP children.

Clinical correlates of MC alterations in the CTNs of children with SCP

We observed that the decreased number of MCs between the right area 11l and the right Mbelt was positively correlated to the CFCS scores, with higher scores indicating poorer communication function in the SCP group. Specifically, we found that as the communication function decreased, MC increased, reducing the deviation from the TD group. The area 11l and Mbelt complex are located in the orbital and polar frontal cortex, and the early auditory cortex, respectively (33), the latter of which are both responsible for cognitive functions (34,35). Notably, the early auditory cortex is closely related to language processing (35). Therefore, the impairment of communication functions in children with SCP may be partly attributable to the disorganized connection of regions accounting for language processing. This speculation is supported by a previous DTI study that found that the language track is smaller in CP patients with poor objective language comprehension skills than in controls (36). These findings suggest that the disorganization of the regions responsible for language processing may be the underlying neural mechanism of communicative impairments in children with SCP. Notably, the observed positive correlation between the decreased number of MCs and the CFCS scores in the SCP group is somewhat counter-intuitive. Thus, further studies need to be conducted to confirm this result and explore the factors modulating this correlation.

Topological alterations in the CTNs of children with SCP

In addition to the decreased number of MCs, children with SCP exhibit an increased characteristic L_p and normalized L_p in the CTNs, which is consistent with previous findings derived from structural brain networks (37-39). For example, Duan et al. (37) investigated whole-brain structural network organization, and found that the normalized L_p was increased in SCP. The increased L_p indicates longer average shortest L_p values between all the nodes in the CTNs (40), suggesting less efficient information transmission (41) in children with SCP. However, unlike some previous studies (38,42), we did not observe any alterations in nodal properties. This inconsistency might stem from differences in the methods used to construct the brain networks. Lee et al. (43) investigated whole-brain structural and functional brain networks for SCP, and found lower global and local efficiency in patients compared to controls for the structural networks but not for the functional networks. Alternately, the different results might reflect the inherent heterogeneity of SCP.

Clinical correlates of topological alterations in the CTNs of children with SCP

First, the increased characteristic L_p was negatively correlated with scores on the Wechsler Intelligence Scale, which includes the VCI, PSI, and FSIQ, in children with SCP. Intelligence is a general indicator of cognitive function, and shorter characteristic L_p values are generally associated with more efficient cognitive processing (44). Therefore, the correlation between increased characteristic L_p values and lower intelligence levels indicate that inefficient information transmission may contribute to cognitive impairment in children with SCP. Additionally, longer characteristic L_p values were associated with more severe gross motor and manual dysfunction in the SCP group. Based on these results, we speculate that inefficient information transmission may also negatively affect motor control and coordination in children with SCP, leading to difficulties, clumsiness, and a lack of coordination in motor tasks. Finally, we observed that the increased characteristic L_p values were associated with communication impairments, which corresponds to the correlation between decreased MCs and communication function. Collectively, these results suggest that the inefficient information transmission of the brain networks, especially the language pathways, may be the underlying mechanism leading to communication impairments in children with SCP.

Interpretation of the lack of significant cortical differences between the SCP and TD groups

In this study, we did not observe any significant differences in the cortical morphology between the SCP and TD groups, which might be due to our relatively small sample size. A limited sample size may reduce the statistical power needed to detect subtle morphological differences. Additionally, upon reviewing previous studies, we found that to date very few studies have specifically focused on cortical morphological changes in children with SCP. While some research has explored cortical changes in CP as a whole, these studies often do not distinguish among specific subtypes, such as SCP (45), or focus solely on adult populations (46). However, CP is a highly heterogeneous condition, and different subtypes may exhibit unique patterns of structural brain changes, making it challenging to generalize findings from CP as a whole to specific types like SCP. Moreover, given the dynamic nature of brain development, the cortical changes observed in adults with SCP may not directly translate to children. Children’s brains undergo significant growth and have significant plasticity, which may lead to differences in how SCP affects cortical morphology across developmental stages.

In summary, our study indicates that SCP children exhibit abnormal morphological brain network topology, which is characterized by increased characteristic L_p values and decreased MCs, especially in the DMN. These imaging markers may serve as objective indicators of underlying neuroanatomical abnormalities, and may enhance diagnostic accuracy in cases with subtle or atypical symptoms.

Limitations and future directions

This study had a number of limitations. First, the sample size of this study was small; thus, studies with larger sample sizes need to be conducted to test the reproducibility of our results in the future. Second, SCP has complex clinical manifestations, and the cerebral alterations may vary among different subtypes of SCP. To better understand this disease, future research needs to explore specific brain alterations associated with each subtype. Third, our cohort spanned a broad developmental window (4–14 years). During this period, morphological networks are still undergoing substantial refinement. Core modular architecture is already detectable in the neonatal period and continues to mature through adolescence (47-49), with network measures such as clustering, global efficiency and small-worldness following inverted-U trajectories that peak in mid-adolescence before stabilizing or declining in adulthood (50). It is important to note that while basic morphological networks are present at age 4, their refined integration and connectivity patterns continue to develop with age. Therefore, the observed differences in MC in our cross-sectional sample likely reflect a complex interplay between underlying neuropathology and ongoing neurodevelopmental processes, and thus may not be direct indicators of maturation status. Such age-related variability can increase within-group heterogeneity and may obscure SCP-specific deviations from TD. To enhance sensitivity to disease-related effects, future studies should either focus on narrower age bands to reduce the confounding effects of differing developmental stages or adopt longitudinal designs that chart individual trajectories against well-characterized normative curves. Finally, there are several different methods for constructing single-subject morphological brain networks (18,22,23). Future studies should seek to determine which method is the most sensitive in detecting alterations in children with SCP to aid in the diagnosis and prognosis of the disease.

Conclusions

SCP is associated with significant alterations in the topological organization of CT-based brain networks, which may contribute to disturbances in motor and cognitive functions. These findings advance our understanding of the morphological organization of SCP, and provide biomarkers for the early diagnosis and potential intervention strategies for SCP.

Acknowledgments

We are grateful to the children with CP and their families for their participation, which made this study possible. We would also like to acknowledge the various programs that provided funding and thus essential resources for this work.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2949/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2949/dss

Funding: This work was supported by the Young Outstanding Scientific and Technological Talent Program of Guizhou Province (grant No. Qiankehepingtairencai[2021]5620), the Key Basic Research Program of Guizhou Province (grant No. Qiankehejichu-ZK[2022]zhongdian 051), the Talent Program for Future Famous Clinical Doctors of Zunyi Medical University (No. rc220211205), the Innovation Talent Team of Science and Technology in Zunyi City (No. Zunshikerencai[2024]5), and the Postgraduate Research Fund Project of Class B in 2023 (grant No. ZYK263).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2949/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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of the Affiliated Hospital of Zunyi Medical University (No. KLL-2024-078), and informed consent was obtained from the parents or legal guardians of all the participants.

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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