Assessing regional homogeneity and cognitive function alterations in pediatric brain tumor patients: a resting-state functional magnetic resonance imaging study

Introduction

Central nervous system (CNS) tumors have recently overtaken leukemia as the most common tumor in children aged 0–14 years, with a reported incidence of 5.96 per 100,000 children annually, presenting a significant challenge to pediatric health (1). Despite the high malignancy rate in pediatric CNS tumors, advancements in medical science and technology have significantly improved the 5-year survival rates, which currently range from 18% to as high as 93% (2). This improvement in survival rates underscores the growing need to assess and understand cognitive abilities in these children, an area in which research is still limited (3).

Resting-state functional magnetic resonance imaging (rs-fMRI), a noninvasive and nonionizing technique offering high spatial resolution, is instrumental in detecting activated brain regions in vivo through blood oxygenation level-dependent (BOLD) signals and has become integral in brain disease research (4,5). Among the analytical methods derived from rs-fMRI, regional homogeneity (ReHo) is notable (6). ReHo reflects spontaneous brain functional activity as a measurement of the synchrony of time series between a target voxel and its neighboring voxels via the Kendall coefficient concordance (KCC). It is particularly valuable for characterizing the local attributes of spontaneous brain activity. Variations in ReHo, either as an increase or decrease, can indicate alterations in the synchronization or coordination of local brain activity, which may potentially underpin the cognitive dysfunction in patients (7).

The fourth edition of Wechsler Intelligence Scale for Children (WISC-IV), a cornerstone in the assessment of children’s cognitive function, has been extensively used in clinical practice (8). The development of the fourth edition of this scale in 2003 (9) marked a significant update in its approach to cognitive assessment. The Chinese version of the WISC-IV was introduced to China in 2008, broadening its application in diverse cultural contexts. The WISC-IV is designed for children aged 6–16 years and comprises several indices: the Verbal Comprehension Index (VCI), Perceptual Reasoning Index (PRI), Working Memory Index (WMI), Processing Speed Index (PSI), and the Full-Scale Intelligence Quotient (FSIQ). These indices collectively offer a multidimensional evaluation of a child’s cognitive abilities, covering aspects including language, visual-spatial processing, logic, and speed of information processing.

Given the prevalence of cognitive impairments in children with brain tumors, it is plausible that alterations in ReHo are present in this population and may correlate with cognitive function. Our study leveraged the rs-fMRI and ReHo methodologies to clarify the potential pathophysiological mechanisms behind local brain functional activity changes and cognitive dysfunction in patients with pediatric brain tumor. Our goal is to provide a neuroimaging foundation for the clinical diagnosis and prognostic evaluation of these patients. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-529/rc).

Methods

Participants

A total of 21 patients were recruited from September 2021 to June 2023 at the Tsinghua University Yuquan Hospital (Tsinghua University Integrated Traditional Chinese and Western Medicine Hospital). Age- and sex-matched healthy controls (HCs) were also enrolled.

MRI scans were conducted on all participants using a 3-T MRI scanner (Philips, Amsterdam, the Netherlands) equipped with a 32-channel head coil. Two models, the 3-T Ingenia and the 3-T Achieva (Philips), were used at the respective facilities of Tsinghua University and Tsinghua University Yuquan Hospital in Beijing, China.

This study adhered to the Declaration of Helsinki (as revised in 2013) and received approval from the Ethics Committee of Yuquan Hospital, Tsinghua University (No. 20220711). Informed consent was obtained from all participants’ guardians prior to participation.

Children diagnosed with brain tumors were recruited based on the following inclusion criteria: (I) age range between 6 to 16 years, (II) right-handedness, and (III) confirmed brain tumor diagnosis. The exclusion criteria for these patients were prior chemotherapy and/or radiotherapy, extensive metastasis, MRI contraindications, and inability to cooperate during MRI procedures.

Age- and sex-matched HCs were enrolled according to the following inclusion criteria: (I) age between 6 to 16 years, (II) right-handedness, and (III) absence of CNS-related diseases. Meanwhile, the exclusion criteria for HCs included psychiatric or neurological disorders, MRI contraindications, and recent long-term medication use.

Assessment of cognitive function

Cognitive functioning was evaluated using the WISC-IV. This scale is suitable for children aged 6 to 16 years and encompasses 10 core subtests, such as block building and vocabulary, along with 4 supplementary tests. It measures various cognitive abilities, yielding scores for the VCI, PRI, WMI, PSI, and FSIQ. The WISC-IV assessments were conducted in a controlled environment within the psychiatric ward of Tsinghua Yuquan hospital and were administered by two certified psychologists.

Image acquisition

Brain MRI scans were performed for all participants using 3-T scanners, which included T1-weighted image three-dimensional (T1WI 3D) imaging and rs-fMRI. The T1WI 3D imaging parameters were set as follows: 160 transverse slices, a voxel size of 1×1×1 mm³, a repetition time/echo time (TR/TE) of 8.1/3.7 ms, a matrix size of 256×256, a flip angle of 6°, and a field of view (FOV) of 256×256 mm.

For rs-fMRI, the parameters included a voxel size of 3.0×3.0×3.5 mm³, a flip angle of 90°, 41 transverse slices without interslice gaps, a slice thickness of 3 mm, 240 time points, a TR/TE of 2,620/30 ms, an FOV of 192×192 mm², and a matrix of 64×55. During scanning, participants were instructed to remain still with their eyes closed but to remain awake. Foam padding and soft earplugs were provided to minimize head motion and reduce noise exposure. For younger participants aged below 10 years, a guardian was present to ensure compliance and comfort during scanning.

rs-fMRI data processing

The rs-fMRI image data were preprocessed using the Data Processing and Analysis for Brain Imaging (DPABI; V8.1_240101; http://rfmri.org/dpabi) toolkit (10) which is based on Statistical Parametric Mapping 12 (SPM12; http://www.fil.ion.ucl.ac.uk/spm/). The preprocessing steps included (I) conversion of image data from Digital Imaging and Communications in Medicine (DICOM) format, (II) removal of the initial 10 time points to achieve steady-state magnetization, (III) slice timing correction, (IV) realignment to exclude participants with excessive head motion (more than 2.5 mm translation or 2.5° rotation), (V) spatial normalization of the motion-corrected data to the Montreal Neurological Institute space with resampling of voxels to 3 mm³, and (VI) regression of nuisance covariates (including Friston-24 head movement parameters, linear trends, and signals from cerebral white matter and cerebrospinal fluid), followed by band-pass filtering within the range of 0.01 to 0.08 Hz.

Tumor lesions were delineated using ITK-Snap software, with individual lesion masks subsequently merged into a composite mask, as illustrated in Figure 1. The mask was then applied to exclude tumor-affected areas from the ReHo analysis. The lesion outlining was uniformly performed by a single neurosurgeon (Z.Z.).

Figure 1 Tumor mask overlay. The tumor masks, registered to the MNI space, are overlaid to illustrate the distribution. Colors represent the frequency of tumor occurrence at each location across subjects. MNI, Montreal Neurological Institute.

ReHo analysis

ReHo analysis was performed using the DPABI toolkit (6,10). The steps included were as follows: (I) calculation of the KCC for each voxel, with its time series and that of its 26 nearest neighbors being used (6); (II) normalization of ReHo maps, with the KCC value for each voxel being divided by the mean KCC value across the entire brain to minimize individual variations; and (III) spatial smoothing, with a Gaussian kernel of 4-mm full-width at half maximum (FWHM) used to reduce spatial noise and enhance the signal-to-noise ratio. The KCC formula was as follows.

W=∑(Ri)2−n(R¯)2112K2(n3−n)R¯=(n+1)×K2[1]

Statistical analysis

Clinical data from both patients and HCs were analyzed using SPSS 26 (IBM Corp., Armonk, NY, USA). Age differences were evaluated using a nonparametric test, while chi-square tests were employed for gender distribution. All tests were two-tailed with a significance threshold set at P<0.05.

For ReHo analysis, a two-sample t-test was carried out on a voxel-by-voxel basis within a predefined gray-matter mask via DPABI. Covariates including age, gender, education level, and MRI scanner type were controlled in the analysis. DPABI software was used for thresholding statistical maps. We applied threshold-free cluster enhancement (TFCE) and familywise error correction (FWE) for multiple comparison corrections, with a significance level set at P<0.05. A total of 5,000 permutations were performed for each test.

To assess the clinical significance of our findings, Pearson correlation coefficients were calculated between significant ReHo values and clinical variables from the WISC-IV, including VCI, PRI, WMI, PSI, and FSIQ.

Results

Demographic information

This study included 21 pediatric patients diagnosed with brain tumors (11 females; mean age 9.47±2.82 years; age range, 6–15 years;) and 19 age- and sex-matched HCs (9 females; mean age 10.53±2.82; age range, 6–16 years). Statistical analysis revealed no significant differences in age, gender, or education levels between the two groups (P>0.05). Detailed demographic and clinical characteristics of both the patient and control groups are presented in Table 1.

ReHo analysis

Analysis revealed a significant reduction in ReHo in the left anterior cingulate and right middle frontal gyrus (MFG) in children with brain tumors as compared to HCs (P<0.05, TFCE and FWE corrected and 5,000 permutations). These findings are presented in Table 2 and illustrated in Figure 2.

Figure 2 ReHo alterations in patients with brain tumor. The ReHo values were decreased in the left anterior cingulate and right middle frontal gyrus of patients brain tumor as compared to healthy controls (P<0.05, TFCE and FWE corrected and 5,000 permutations). The yellow regions indicate areas with significant ReHo changes. ReHo, regional homogeneity; TFCE, threshold-free cluster enhancement; FWE, familywise error.

Correlation between ReHo and cognitive behavior

A significant correlation was observed between ReHo values in the right MFG of brain tumor patients and PRI scores (R=0.471; P=0.031) and WMI (R=0.531; P=0.013) of the WISC-IV. However, no significant correlation was found between ReHo in the anterior cingulate and any parameters of the WISC-IV, as shown in Figure 3 and Table 3.

Figure 3 Correlation analysis between ReHo values and WISC-IV. (A) Correlation analysis of right MFG and PRI. (B) Correlation analysis of the right MFG and WMI (P<0.05). ReHo, regional homogeneity; WISC-IV, fourth edition of the Wechsler Intelligence Scale for Children; MFG, middle frontal gyrus; PRI, Perceptual Reasoning Index; WMI, Working Memory Index.

Discussion

Our study represents a pioneering effort in preoperative neuroimaging research, focusing on brain function differences in patients with pediatric brain tumor during rest. The application of rs-fMRI in our study revealed distinct ReHo value differences between patients with pediatric brain tumor and HCs, particularly in the MFG and left anterior cingulate. Correlation analysis between these ReHo values and WISC-IV scores indicated a positive relationship of ReHo values in the right MFG with the PRI and the WMI. The right MFG was the focus of this study because this brain area’s ReHo values were significantly different between patients with tumor and HCs and correlated with the behavioral results.

Tumor-induced alterations, such as increased intracranial pressure, reduced cerebral blood flow, and neurotransmitter availability limitations, may result in axonal and myelin damage or neuronal apoptosis causing cognitive impairment (11-13). The right MFG emerged as a focal point in our study due to significant ReHo differences and its correlation with cognitive performance outcomes. This observation aligns with existing research suggesting the involvement of the ventral frontoparietal network in the right hemisphere, particularly in attention regulation driven by sensory-driven, exogenous stimuli, which consists of the temporoparietal junction (TPJ) and ventral frontal cortex, including the MFG and inferior frontal gyrus (IFG). This regional network is known as the ventral attention network (VAN) (14,15). Each node of this network is thought to be involved in the attentional regulation of the formation of exogenous unexpected stimuli driven by bottom-up, nonautonomous stimuli (16). For example, the TPJ is active in any situation that requires orientation adjustment unrelated to expectation, whereas the right IFG and the right MFG are active only when orientation is adjusted to an unexpected stimulus (17). Meanwhile, the right IFG and the right MFG are active only when orientation is adjusted to an unexpected stimulus (17,18). In sum, this network is involved in the reorientation of relevant targets that appear in unexpected locations or important but less obvious targets (19,20).

One study suggests that the right MFG may play an important role in shifting attention from exogenous to endogenous control (21). In addition, another study demonstrated that the MFG has similar ability as does the Broca’s area in task-fMRI studies; it may thus be used as a predictor of language fluency to indicate hemisphental language dominance and as a supplementary measure for determining language laterality in preoperative planning (22). Subsequently, some researchers have studied the ability of the MFG to determine the dominant language hemisphere in patients with brain tumors based on rs-fMRI (23), indicating that the MFG has a similar function to the Broca’s area. In an rs-fMRI study of frontal lobe gliomas, voxel-mirrored homotopic connectivity (VMHC) in the right MFG was found to be decreased in patients with frontal lobe gliomas and was significantly and positively correlated with cognitive function (24). Our results align with previous rs-fMRI studies indicating the role of the right MFG in cognitive functions, including attentional shifts and language-processing abilities. The positive correlation of ReHo values in the right MFG with PRI and WMI in our study reinforces its potential role in cognitive changes, particularly in attention and working memory.

In Wechsler’s original model, verbal intelligence (VIQ) and performance intelligence (PIQ) combined to form Full-Scale Intelligence Quotient (FSIQ) (25). While VIQ includes VCI and WMI, PIQ includes PRI and PSI, with Block Design and Matrix Reasoning and Visual Puzzles being the core of PRI. These integrate multiple elements related to cognition, including visual perception, simultaneous processing, working memory, and spatial manipulation. Meanwhile, the WMI composite consists of two primary subtests, Digit Span and Arithmetic. It measures attention, concentration, and working memory. Working memory, based on attention and concentration, refers to the ability to temporarily retain information in the mind while the information is processed or engaged in distracting tasks and the subsequent ability to accurately reproduce the updated information or take action correctly. In previous studies, the Wechsler Intelligence Scale was widely used to measure cognitive function (26,27). In our study, ReHo values in the right MFG were found to be positively correlated with PRI and WMI, confirming the correlation between ReHo values in the right MFG and increased attention. The right MFG may be a potential target brain region for cognitive function changes in pediatric brain tumor patients, and the specific physiological mechanism needs to be further explored.

While some research has examined the functional aspects associated with brain tumors (28), our study focused on nontumor brain function changes. Due to the uneven distribution of tumor locations, we employed masking techniques to mitigate tumor influences in our statistical analysis (29,30). Several studies have shown that tumors can disrupt the structural brain networks in a variety of ways, such as physical displacement, invasion and destruction, altered connectivity, and pressure and inflammation (31-34). Our study preoperatively examined patients with brain tumor and cognitive impairment, which may be attributed to numerous factors, likely tumor size and extent, but subsequent studies should clarify the key factors (35).

This study has the following limitations: First, the sample size was relatively small, and we believe that a study with a larger sample size may benefit the generalizability of the findings. Our team will also continue to enroll research participants and conduct larger studies to determine the generalizability of the findings. Second, we did not perform age stratification to ensure adequate sample size because of the wide age range in our study, although we did include age as a covariate in the statistical analysis to eliminate its influence on the results. Third, due to the wide age distribution of participants, we employed an adult brain template, which may introduce some inaccuracies, particularly in younger children. Fourth, we did not group tumors according to specific location and pathology in our study. Considering that pediatric brain tumors often grow along the midline and progress rapidly in pathological studies (36), we will further verify these conclusions in a separate data set when sufficient samples have been collected. Moreover, validating our methodology through simulations or using existing larger datasets would enhance the robustness of our study. Although certain constraints prevented us from including such validations, we have outlined plans to incorporate them in future research. Finally, we used two functional MRI scans in our study because of force majeure, but both were operated by the same company and had the same parameters, and we included this factor as a covariate in our analysis.

Conclusions

We identified significant ReHo alterations in patients with pediatric brain tumor, primarily in brain regions associated with cognitive processing and found there to be a positive correlation between these alterations and specific cognitive functions. These findings contribute to understanding cognitive impairments in the patients with pediatric brain tumor and suggest potential areas for targeted intervention.

Acknowledgments

We would like to thank Rui Hao, Yan Lu, and Ting Gao for their technical support, as well as all participating children for their cooperation.

Funding: This work was supported by the Beijing Natural Science Foundation (No. L222154).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-529/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-529/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 adhered to the Declaration of Helsinki (as revised in 2013) and received approval from the Ethics Committee of Yuquan Hospital, Tsinghua University (No. 20220711). Informed consent was obtained from all participants’ guardians prior to participation.

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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