Altered voxel-wise degree centrality of brain networks in patients with chronic rhinosinusitis: a resting-state functional magnetic resonance imaging study
Original Article

Altered voxel-wise degree centrality of brain networks in patients with chronic rhinosinusitis: a resting-state functional magnetic resonance imaging study

Simin Lin1, Miaomiao Nie2, Bingshan Wang2, Qianwen Huang2, Hao Zheng3, Zhishang Chen1, Shaoyin Duan2, Hengyu Zhao1, Yi Han3

1Department of Radiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; 2Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; 3Department of Ophthalmology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China

Contributions: (I) Conception and design: S Lin, Y Han; (II) Administrative support: Y Han, M Nie; (III) Provision of study materials or patients: M Nie, B Wang; (IV) Collection and assembly of data: M Nie, B Wang; (V) Data analysis and interpretation: Q Huang, S Duan, H Zheng, Z Chen; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Yi Han, PhD, MD. Department of Ophthalmology, The First Affiliated Hospital, No. 69, Chuanshan Road, Shigu District, Hengyang 421001, China. Email: hanyixmu@foxmail.com; hanyi@usc.edu.cn; Hengyu Zhao, MD. Department of Radiology, Xiamen Cardiovascular Hospital of Xiamen University, No. 2999, Jinshan Road, Huli District, Xiamen 361006, China. Email: xzzx_paper@163.com.

Background: Chronic rhinosinusitis (CRS) is a chronic inflammatory disorder of the paranasal sinus and nasal cavity. Previous studies have demonstrated that patients with CRS have an increased risk of emotional and cognitive disorders. Although neuroimaging studies have identified brain alterations in CRS, the specific etiology of these neurological changes remains unclear. This study thus examined the abnormal brain networks in patients with CRS through use of a voxel-wise degree centrality (DC) approach.

Methods: In this cross-sectional study, 26 patients with CRS and 38 healthy controls (HCs) were enrolled for resting-state functional magnetic resonance imaging (rs-fMRI) scans. The DC value was calculated and correlated with clinical symptoms and with anxiety and depression scores in the CRS group. Moreover, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic utility of DC in distinguishing patients from HCs.

Results: Compared with HCs, patients with CRS had decreased DC values in the right precuneus and increased DC values in the left inferior temporal gyrus (ITG) (P<0.05, false-discovery rate corrected). In addition, a positive correlation was identified between the DC values in the left ITG and disease duration (R=0.5317; P=0.0052). ROC curves analysis indicated that the DC values in the right precuneus [area under the curve (AUC) =0.7945] and left ITG (AUC =0.7915) had significant diagnostic accuracy, indicating their potential utility as imaging biomarkers for CRS.

Conclusions: Altered DC in the right precuneus and the left ITG may play important roles in the pathological changes underlying CRS-related brain dysfunction.

Keywords: Chronic rhinosinusitis (CRS); resting-state functional magnetic resonance imaging (rs-fMRI); degree centrality (DC); precuneus; inferior temporal gyrus (ITG)

Submitted Aug 13, 2024. Accepted for publication May 07, 2025. Published online Aug 19, 2025.

doi: 10.21037/qims-24-1680

Introduction

Chronic rhinosinusitis (CRS) is a common chronic inflammatory disease with a prevalence of more than 10% worldwide and is characterized by symptoms lasting more than 12 weeks (1). Aside from the apparent symptoms associated with CRS, including nasal obstruction, nasal discharge, and hyposmia, patients with CRS also have an increased susceptibility to anxiety disorder and depression (2-4). In addition, on cognitive function assessments, patients with CRS have poorer scores in attention, processing speed, and reaction time (5,6). Notably, these physical, emotional, and cognitive alterations may significantly influence patients' quality of life, compromise clinical interventions, and place a considerable burden on society and healthcare systems. Given the involvement of CRS in emotional and cognitive functions, there has been a recent research emphasis on CRS-related brain dysfunction. Significant progress has been made in clarifying the cognitive impact of CRS, and while the neural mechanism of CRS-related brain impairment remains unclear (5,7,8), neuroimaging appears to be an effective means to elucidating the brain abnormalities in CRS (8).

Structural investigations have indicated a reduction of gray-matter volume in certain brain regions in patients with CRS (9,10). Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technology used to detect neural activity according to blood oxygen level-dependent signals, and it has already been implemented to characterize the brain function changes associated with CRS (11,12). Using independent component analysis, Jafari et al. investigated the functional connectivity (FC) of brain networks in CRS and discovered FC abnormalities in the brain regions associated with cognitive function (8). Another recent investigation examined brain activity and FC using amplitude of low-frequency fluctuation and seed-based FC and found increased neural activity in the orbital superior frontal cortex and hypoconnectivity in the precuneus (11).

Degree centrality (DC), a network analysis technique based on graph theory, measures the centrality of voxels by counting the temporal correlations between one voxel and the other voxels at the whole-brain level (13). DC analysis can help to assess the importance of nodes in the brain network and the connectivity strength of each voxel (14,15). It has been widely applied in the pathophysiology research of numerous neurological or psychiatric diseases, such as schizophrenia (16), Parkinson disease (17), depression (18), and anxiety (19). DC analysis has also been used to examine chronic conditions, including diabetes (20), chronic shoulder pain (21), irritable bowel syndrome (22), and end-stage renal disease (23). However, little is known about the DC in patients with CRS. Therefore, we conducted to this study to investigate the characteristics of brain networks in patients with CRS using the voxel-wise DC method. We posited two hypotheses: (I) there is a significant difference in DC values between patients with CRS and healthy individuals. (II) The DC values in patients with CRS are correlated with a spectrum of clinical indicators and with scores for anxiety and depression. The primary aim of this study was to clarify the relationship between sinonasal inflammation and the brain network alterations that may underlie the cognitive and mood changes associated with CRS. The secondary aim was to assess whether DC values in altered brain regions could serve as novel biomarkers for CRS. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1680/rc).

Methods

Participants

From February to August 2022, patients with CRS were enrolled from Zhongshan Hospital of Xiamen University, and sex- and age-matched healthy controls (HCs) were recruited from the community. To assess CRS severity, we conducted subjective and objective assessments using the visual analog scale (VAS) score and Lund-Markay score (LMS), respectively (24,25). In addition, Hospital Anxiety Depression Scale (HADS) scores were collected for all participants to assess the severity of anxiety and depression (26). LMSs were calculated via T2-weighted structural imaging by two experienced radiologists. An excellent correlation between computed tomography (CT) and MRI-based LMS has already been demonstrated in earlier investigations (27,28). The diagnostic criteria for CRS were based on the European Position Paper on Rhinosinusitis and Nasal Polyps (EP3OS) (25). To be included in our CRS study, participants were required to have (I) an LMS of 8 or higher and (II) an age between 20 and 50 years. Patients and controls were excluded if they met one of the following criteria: (I) HADS-anxiety (HADS-A) or HADS-depression (HADS-D) score ≥14; (II) previous history of brain trauma, tumor, and/or neurological or psychiatric disorders; (III) drug or alcohol abuse; (IV) MR contraindications; and (V) left-handedness. We excluded left-handed participants to minimize variability in brain lateralization and FC patterns, as handedness is strongly linked to hemispheric specialization (e.g., language networks) (29). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and was approved by the Ethics Committee of Zhongshan Hospital of Xiamen University (No. 2022-253). Informed consent was obtained from all participants prior to participation.

Data acquisition

All data were obtained with the Ingenia 3.0 T CX MR system (Philips Healthcare, Best, The Netherlands). Rs-fMRI data were collected with a gradient-echo-planar imaging sequence (EPI). Structural images were obtained under a T1-weighted sequence with three-dimensional (3D) magnetization-prepared rapid gradient-echo (MP-RAGE) and a T2-weighted sequence with 3D BrainView. The detailed scanning parameters are shown in Table 1. During scanning, all participants were instructed to keep their eyes closed and to remain awake. Foam pads were employed to diminish head motion artifacts, and earplugs were applied to lessen the effect of acoustic noise.

Table 1

Scanning parameter data

Data acquisition rs-fMRI T1W with 3D MP-RAGE T2W with 3D BrainView
TE/TR (ms) 25/2,000 3.0/6.6 280/3,000
Flip angle 65° 8° 90°
FOV (mm) 219×219 240×240 240×240
Thickness/gap (mm) 2.5/0 1/0 1/-0.5
Matrix 88×88 240×240 240×240
Voxel size (mm) 2.5×2.5×2.5 1.0×1.0×1.0 1.0×1.0×1.0
Number of slices 57 180 320

FOV, field of view; MP-RAGE, magnetization-prepared rapid gradient-echo; rs-fMRI, resting-state functional magnetic resonance imaging; T1W, T1-weighted; T2W, T2-weighted; TE, echo time; TR, repetition time.

Preprocessing of functional imaging data

Data from rs-fMRI were preprocessed and analyzed using Data Processing & Analysis for Brain Imaging (DPABI; http://rfmri.org/dpabi), which is based on Statistical Parametric Mapping 12 (SPM12; Wellcome Centre for Human Neuroimaging, University College London, London, UK; http://www.fil.ion.ucl.ac.uk/spm) (30). First, the initial 10 volumes were discarded to achieve signal equilibrium. The remaining volumes were time corrected to remove any difference in image acquisition, and they were then realigned to correct 3D head movement. Six patients and two controls were eliminated according to a threshold of 2.5 mm or 2.5° in any direction. Subsequently, the remaining data were spatially normalized and resampled to 3-mm isotropic voxels to the standard template. Next, nuisance variables were removed, including linear drift, white matter, cerebrospinal fluid, and head motion parameters. Finally, temporal band-pass filtering was conducted to decrease the influences of low-frequency drift.

Voxel-wise DC

Based on preprocessing, the blood oxygen level-dependent time course for each voxel was extracted, and the Pearson correlation coefficients (defined as a correlation coefficient of r >0.25) with each other voxel in the brain were then calculated to determine the DC (17). We estimated the whole-brain network’s binary DC values. To improve normality, the Fisher r to z transformation was used on the voxel-wise DC values to create a z-score map. Subsequently, each individual DC was spatially smoothed with a 4 mm × 4 mm × 4 mm full-width half maximum Gaussian filter.

Statistical analysis

Intergroup comparisons of demographic data, clinical characteristics, and psychological tests were conducted with SPSS version 26.0 software (IBM Corp., Armonk, NY, USA). The independent two-sample t-test and chi-squared test were used to normally distribute continuous variables and sex, respectively. A P value <0.05 indicated statistical significance.

The independent two-sample t-test was applied to assess the differences in DC values between the patients with CRS and the HCs, with age, sex, and education levels being the covariates. The statistical significance between the two groups was set to the cluster-level false-discovery rate-corrected cluster-wise threshold of P<0.05.

Pearson correlation analysis was applied to investigate the relationship between DC values and normally distributed parameters, including LMS, HADS, and HADS-D. Spearman correlation was used to analyze nonnormally distributed parameters, including disease duration, HADS-A, and VAS.

The receiver operating characteristic (ROC) curve was applied to analyze the diagnostic potential of DC values in altered brain regions to differentiate patients with CRS from the HCs. The area under the curve (AUC) was used to quantify the diagnostic accuracy, enabling a comprehensive assessment of the model’s ability to discriminate between the two groups.

Results

Demographics and clinical characteristics

The demographic and clinical parameters for all participants are summarized in Table 2. In total, 26 patients with CRS and 38 sex- and age-matched HCs were enrolled in the study. Intergroup comparisons indicated no statistical differences in sex, age, or HADS (both HADS-A and HADS-D) scores, but there were significant differences in education level.

Table 2

Demographic and clinical parameters

Variable HCs (n=38) Patients with CRS (n=26) t/χ2 value P value
Demographic data
   Age (years) 34.45±7.69 36.88±7.63 t=−1.250 0.216
   Sex (M/F) 22/16 19/7 χ2=1.546 0.214
   Education (years) 16.16±2.20 14.00±3.15 t=3.231 0.002
Clinical parameter
   Disease duration (years) – 8.08±7.63 – –
   Nasal polyps – 11 (42.3%) – –
   Sinonasal surgery – 7 (21.9%) – –
   LMS 8.16±4.90 11.38±2.53 t=−0.966 0.626
   VAS – 5.63±1.81 t=−1.112 0.270
   HADS 4.26±2.63 9.46±5.85 t=−0.489 0.338
   HADS-A 3.97±2.90 5.12±3.50 t=−1.112 –
   HADS-D 4.35±3.12 4.35±3.12 – –

Continuous variables are expressed as the mean ± SD, while categorical variables are expressed as counts. P<0.05 indicates statistical significance. This table was adapted from Lin et al. (11) under the terms of Creative Commons Attribution License (CC BY 4.0) license. CRS, chronic rhinosinusitis; F, female; HADS, Hospital Anxiety and Depression Scale; HADS-A, Hospital Anxiety and Depression Scale-Anxiety; HADS-D, Hospital Anxiety and Depression Scale-Depression; HC, healthy control; LMS, Lund-Mackay score; M, male; SD, standard deviation; VAS, visual analog scale.

DC analysis and correlation analysis

Compared with HCs, patients with CRS had lower DC values in the right precuneus and higher values in the left inferior temporal gyrus (ITG) in (P<0.05, FDR corrected) (Table 3 and Figure 1A,1B). Spearman correlation analysis indicated a positive correlation between the DC values of the left ITG and the duration of the disease (R=0.5317; P=0.0052) (Figure 2). However, no significant correlation was observed between the DC values in the altered brain regions and HADS scores (including HADS-A and HADS-D scores), VAS, and LMS.

Table 3

Differences in DC values between HCs and patients with CRS

Result Brain region Peak MNI coordinates Voxel number t value
x y z
HCs > CRS Right precuneus cortex 6 −60 24 39 4.347
HCs < CRS Left inferior temporal gyrus −63 −15 −63 38 −4.481

x, y, and z are the locations of the peak voxels in standard MNI coordinates. CRS, chronic rhinosinusitis; DC, degree centrality; HC, healthy control; MNI, Montreal Neurological Institute.

Figure 1 DC differences between HCs and patients with CRS (P<0.05, FDR corrected). (A) The significantly altered DC map in the CRS group (P<0.05, FDR corrected). The color bar denotes the t value. (B) Histogram of the comparison of DC values between the two groups. CRS, chronic rhinosinusitis; DC, degree centrality; FDR, false discovery rate; HC, healthy control; ITG, inferior temporal gyrus; L, left; R, right.
Figure 2 Spearman correlation between the DC values in the left ITG and disease duration. DC, degree centrality; ITG, inferior temporal gyrus.

ROC curves

The ROC curves for DC values in the right precuneus and the left ITG were analyzed to identify the imaging biomarkers capable of diagnosing CRS. The AUC of the DC values of the right precuneus and the left ITG were 0.7945 [95% confidence interval (CI): 0.6855–0.9036] (Figure 3A) and 0.7915 (95% CI: 0.6651–0.9179) (Figure 3B), respectively, indicating good accuracy in diagnosing CRS.

Figure 3 ROC curve analysis for DC values in brain regions. (A) The AUC of the DC values of the right precuneus was 0.7945 (95% CI: 0.6855– 0.9036; P<0.001). (B) The AUC of the DC values of left ITG was 0.7915 (95% CI: 0.6651–0.9179; P<0.001). AUC, area under the curve; CI, confidence interval; DC, degree centrality; ITG, inferior temporal gyrus; ROC, receiver operating characteristic.

Discussion

The DC approach can reveal the topological properties of nodes or brain regions in the whole-brain network (22) and is a valuable and noninvasive fMRI method that can be used to examine the pathogenesis of diseases (20). To the best of our knowledge, this study is the first to use voxel-wise DC to investigate abnormal brain networks in patients with CRS. The principal findings were as follows: (I) patients with CRS exhibited abnormal DC values in the right precuneus and the left ITG as compared to the control group, and (II) a positive correlation was observed between DC values in the ITG and disease duration in patients with CRS.

The precuneus is located on the medial side of the parietal lobe. As a critical part of the default mode network (DMN), the precuneus is involved in higher-order cognitive functional processing, including situational memory, emotional processing, and visuospatial processing (31-33). DC abnormalities in the precuneus have been found in many chronic disorders, such as Parkinson disease (17), diabetes (20), and lifelong premature ejaculation (34). Neuroimaging suggests that the precuneus is a crucial brain region in nasal and sinonasal inflammation. Gao et al. found that patients with allergic rhinitis had lower spontaneous brain activity in the precuneus, which indicates that the precuneus is associated with neurodegeneration-related functions (35). Using independent component analysis, Jafari et al. demonstrated that patients with sinusitis have abnormalities in the DMN, a brain network that regulates cognitive functions, with the precuneus being a core brain region of the DMN (8). In our previous study, we found reduced FC in the right precuneus in patients with CRS (11). In the present study, we applied the voxel-wise DC approach and discovered lower DC values in the right precuneus in patients with CRS as compared to HCs. Based on the above functional imaging studies, we speculate that the precuneus cortex, as a core brain region involved in higher-order neural processing, is central to the neuropathological mechanisms underlying CRS.

The ITG has been implicated in numerous high-order cognitive functions (36). The ITG is mainly involved in emotional regulation and visual and linguistic understanding (37,38). DC abnormalities in the ITG are present in several diseases, including such as bipolar disorder (39), migraines (40), and pediatric attention deficit disorder (41). Abnormal DC in the ITG in patients with bipolar disorder may be involved in aberrant emotional regulation, such as emotional dysregulation and emotional over-reactivity (39,42). Jin et al. reported decreased DC values in the ITG in patients with Parkinson disease with freezing of gait, indicating reduced information integration ability (43). In our study, we found higher DC values in the left ITG in patients with CRS as compared to HCs. Moreover, the DC values in the left ITG were positively correlated with the disease duration. We speculate that the increased DC in the ITG may be a compensation for mild brain impairment, as it improves signal synchronization. The longer the disease duration, the higher were DC values in the ITG, indicating a more pronounced compensatory mechanism.

A previous study demonstrated that the prevalence of anxiety and depression is higher in patients with CRS than in healthy individuals (3). Both the precuneus and ITG are involved in emotional regulation, and they may be linked to anxiety and depression in patients with CRS. However, there was no statistically significant difference in scores for anxiety or depression between the two groups in our study. Given the brain’s capacity for adaptation and compensation, especially among relatively young patients, patients with CRS without severe anxiety or depression may develop intrinsic brain abnormalities prior to the development of anxiety or depressive symptoms.

The precuneus and the ITG are closely associated with higher-order cognitive functions and emotional regulation. The observed alterations in DC values of the precuneus and ITG not only provide neurobiological insights into cognitive and emotional deficits in CRS but also hold translational potential. Clinically, these biomarkers could be integrated into multimodal diagnostic frameworks to identify patients at higher risk of progressive cognitive decline, particularly those with more severe inflammatory conditions. For instance, longitudinal tracking of DC values may aid in monitoring treatment response or predicting relapse, enabling timely adjustments to therapeutic regimens. Future studies should prioritize validating these biomarkers in larger, prospectively designed cohorts and establishing standardized neuroimaging protocols for clinical deployment. Additionally, combining DC metrics with behavioral assessments, such as standardized cognitive assessment or olfactory testing, could further refine their utility in personalized patient management.

Several limitations to our study should be acknowledged. First, only young and middle-aged individuals were included, potentially narrowing the applicability of the findings to a wider demographic spectrum. Second, the study’s limited sample size and single-center design might have introduced selection bias. Third, the lack of cognitive professional scales in our data collection might have precluded a more comprehensive interpretation of the results. Fourth, the exclusion of patients with elevated anxiety or depression scores (HADS ≥14), while methodologically necessary to isolate CRS-specific neural correlates, may limit the generalizability of our findings to CRS populations with comorbid mood disorders. Additionally, the surgical history of sinusitis, medicine, and hyposmia may impact brain function (44-46). Finally, given the cross-sectional nature of this study, temporal relationships could not be established. To address these limitations, we propose several future directions: (I) expansion to multicenter studies with larger participant cohorts to enhance generalizability; (II) collaboration with neurologists to implement standardized cognitive assessments; (III) completion of multimodal imaging-cognitive correlation analyses to clarify the nature of ITG network changes (compensatory vs, pathological); and (IV) prioritization of prospective longitudinal studies tracking treatment regimens (medication dose and surgical history) to better characterize the temporal relationship between DC values and CRS progression and to differentiate disease-specific neural alterations from treatment-related effects.

Conclusions

Patients with CRS showed intrinsic abnormal DC values in the right precuneus and the left ITG, both of which are implicated in cognitive processing and emotional regulation. Additionally, a significant positive correlation was observed between the DC values in the left ITG and disease duration. These findings offer novel insights into the underlying neuropathological mechanisms associated with CRS, potentially contributing to a deeper understanding of the condition’s impact on brain function and behavior.

Acknowledgments

We thank all participants in this study.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1680/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1680/dss

Funding: This work was supported by grants from the China Postdoctoral Science Foundation (No. 2023M741608, Y.H.), the Natural Science Foundation of Hunan Province (No. 2024JJ6402, Y.H.), and the Fujian Provincial Clinical Key Specialty Construction Project (No. zdxk002, H.Z.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1680/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, and was approved by the Ethics Committee of Zhongshan Hospital of Xiamen University (No. 2022-253). Informed consent was obtained from all participants 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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Cite this article as: Lin S, Nie M, Wang B, Huang Q, Zheng H, Chen Z, Duan S, Zhao H, Han Y. Altered voxel-wise degree centrality of brain networks in patients with chronic rhinosinusitis: a resting-state functional magnetic resonance imaging study. Quant Imaging Med Surg 2025;15(9):8505-8514. doi: 10.21037/qims-24-1680

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