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Altered Functional Connectivity Strength in the Cuneus and Precuneus in Patients with Persistent Postural-Perceptual Dizziness

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Altered Functional Connectivity Strength in the Cuneus and Precuneus in Patients with Persistent Postural-Perceptual Dizziness Altered functional connectivity strength in the cuneus and precuneus in patients with persistent postural-perceptual dizziness Kangzhi Li Aerospace center hospital Bin Cui Aerospace center hospital Lihong Si Aerospace center hospital Zheyuan Li Aerospace center hospital Xu Yang ( [email protected] ) Peking university aerospace school of clinical medicine https://orcid.org/0000-0002-3615-3063 Research Keywords: persistent-postural perceptual dizziness, resting state functional magnetic resonance imaging, precuneus, cuneus, functional connectivity strength Posted Date: April 14th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-22381/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/9 Abstract Background: Persistent Postural-Perceptual Dizziness (PPPD) is a chronic functional vestibular disorder, but its pathogenesis is still unclear. Results of our previous study revealed altered spontaneous functional activity of cuneus and precuneus in PPPD patients, which may be associated with the development of PPPD. The study aimed to explore the changes in functional integration, especially the changes in functional connectivity strength (FCS) in the cuneus and precuneus in patients with PPPD using FCS and seed-based functional connectivity (FC) analyses. Methods: Twelve PPPD patients and 12 healthy controls were enrolled. Functional MRI (fMRI) was further performed in all subjects. Global FCS, long--range FCS (lFCS) and short-range FCS (sFCS) were calculated to explore the FCS changes in PPPD patients. Moreover, seed-based FC analysis was performed on regions with altered FCS to further investigate the alterations in FC and the possible causes for FCS changes. Correlation analysis between FCS/FC and clinical indicators in PPPD patients were performed. Results: Compared with healthy controls, no signicant change in global FCS and lFCS was found in PPPD patients. PPPD patients exhibited weaker sFCS in the cuneus and precuneus (K=621, P<0.05, FWE corrected). Areas showing weaker sFCS included precuneus, cuneus, extending inward along the parieto- occipital sulcus, covering parahippocampal gyrus and cortices at the splenium of the corpus callosum. Further seed-based FC analysis showed reduced FC with precuneus, cuneus, indicating that weaker sFCS was mainly caused by reduced FC in the precuneus and cuneus. Changes in sFCS and FC were negatively correlated with DHI and DHI-F scores, and the lower the FCS values, the more severe the subjective symptoms of patients. Conclusion: PPPD patients exhibited altered FCS in the bilateral precuneus and cuneus, which may be associated with abnormal integration of visual and vestibular information and abnormal integration between different spatial reference frames. Background Persistent Postural-Perceptual Dizziness (PPPD) is a chronic functional vestibular disorder. This disorder can seriously affect the patient's daily activities and quality of life [1], But the exact pathogenesis of PPPD is still unclear. Exploring the pathophysiological mechanism of PPPD is essential to investigate the nature of this disease, and can provide the basis for exploring new treatments for PPPD. In recent years, the functional magnetic resonance imaging (fMRI) has been the main method for measuring brain function changes and pathophysiological mechanisms of PPPD [2-5]. Previous studies of PPPD mainly focused on two aspects, i.e. brain’s response to task stimuli and changes in brain functional activity during resting state, and revealed brain function changes in patients with PPPD, but there was high heterogeneity among studies, which may be related to the difference in study design and subjects included. The previous studies not only included patients with PPPD, but also included patients with visual induced dizziness (VID) and chronic subjective dizziness (CSD) [2-5]. Although the denition of PPPD was derived from the four precursors, including PPV, SMD, VID, and CSD, but there are differences in the diagnostic criteria of the four precursors and PPPD [1]. The results of previous study need to be further validated in patients who met the diagnostic criteria of PPPD. In our previous study, we included PPPD patients without peripheral vestibular lesions, the results showed that the spontaneous functional activity of cuneus and precuneus in PPPD patients were altered, FC between cuneus and precuneus, as well as between the precuneus and precentral gyrus were decreased, which indicated that cuneus and precuneus may be the responsibility lesions of PPPD [6]. Based on the ndings of previous study, investigating the changes in functional integration in the brain of patients with PPPD, especially the functional connectivity patterns changes in the cuneus and precuneus will help us further explain the pathophysiological mechanism of PPPD. It should be noted that in previous fMRI studies of PPPD, FC analysis was performed using a seed-region based approach seeds or automated anatomical labeling (AAL) template based on prior anatomical knowledge or partitions, but these methods neglect the changes in the entire brain and may be affected by subjective factors and template selection, which may also cause high heterogeneity between studies. Functional connectivity strength (FCS) analysis is a voxel-based data-driven method to examine the functional hubs and connectivity patterns in brain networks [7-9]. Unlike the above mentioned of traditional FC analyses, FCS can measure the number of functional connections per voxel, and voxel with higher FCS values indicate a larger number of functional connections between this voxel with other voxels, sugggesting stronger ability of information transfer. Moreover, FCS can be classied into short-range FCS (sFCS) or long-range FCS (lFCS) according to the anatomical distance of a given voxel. Therefore, the FCS can determine the functional nodes in the cortex and subcortical regions without selecting any seed regions, and avoid heterogeneity observed across different anatomical templates. However, based on FCS analysis, we are unable to determine the possible causes for FCS changes. FCS combined with seed-based FC analysis can help us to explore functional connectivity patterns changes in patients with PPPD. Given the above background, and based on our previous study, we used FCS and seed-based FC analysis in the present study to explore the changes in functional integration, and further elucidate functional abnormalities within brain regions in patients with PPPD. Subjects And Methods All subjects volunteered to participate in this study and signed informed consent. This study was approved by the Ethics Committee of Peking University Aerospace School of Clinical Medicine, China. Subjects A total of 12 patients with PPPD who received treatment in our hospital from January 2018 to December 2018 were included in the study. Detailed medical information of all patents was collected. The symptoms of all patients were evaluated by dizziness handicap inventory score (DHI). The diagnosis of PPPD was based on the diagnostic criteria of Bárány Society (the 2017 edition). 12 age- and gender-matched healthy controls were also included. All healthy controls had no history of headache or dizziness. fMRI was performed in all subjects. Page 2/9 Acquisition parameters for fMRI data and Data processing All MRI scans were performed on 3.0-Tesla MR scanner (MAGNETOM Skyra syngo MR D13; Siemens, Germany) with a 32-channel head and neck coil. fMRI data were acquired according to the method of our previous study [6]. fMRI data were processed with DPABI software on the MATLAB2013 platform [10]. fMRI data preprocessing The acquired images were processed using Statistical Parametric Mapping (SPM12). Data were converted from DICOM format to NIFTI. The rst 10 time points of the functional images were deleted due to the possible instability of the initial MRI signal. Then slice timing and realignment were conduct. To ensure the accuracy of the position information, and the subjects who had more than 1.5 mm head translation in x, y, or z and 1.5° head rotation were removed. Then using DARTEL, fMRI images were registered and spatially normalized to Montreal Neurological Institute space. Furthermore, a linear regression model was used to remove the interference signal in the blood oxygen level dependent (BOLD) signal. At last, data was band-pass ltered in the range 0.01-0.1 Hz to reduce low-frequency drift and physiological high-frequency noise. FCS calculation For each subject, Pearson’s correlation coecients were calculated between the time series of each voxel and the other voxels within a whole brain gray matter mask, and a whole-brain functional connectivity matrix was constructed for each subject. According to previous study, a threshold of 0.2 was chosen to eliminate voxels with weak correlations due to signal noise. To improve normality, the FC matrix was transformed to a z-score matrix using a Fisher’s z transformation [11]. FCS for a given voxel was calculated as the summation of the connectivity strength between this voxel and all the other voxels. In order to further examine the effects of anatomical distance on FCS analyses, FCS was divided into sFCS and lFCS, the sFCS is dened as the sum of the correlations between the given voxel and other voxels with an anatomical distance less than 75 mm, while the lFCS is dened as the sum of the connections with an anatomical distance greater than 75 mm [12]. The long- and short-range matrix was transformed to a z-score matrix using a Fisher’s z transformation. Finally, images were spatially smoothed using Gaussian kernel with full-width at half-maximum of 8 mm. In order to further verify the reproducibility of our result, we also used two additional correlation thresholds (0.15, 0.3) to compute the FCS maps. Seed-based FC analysis To further examine the possible causes for FCS changes in PPPD patients, a seed-based FC analysis was conducted. Seed regions was established as region of interest (ROIs) as 6 mm radius spheres centered on at the peak coordinate of each cluster showing signicant changes in global, long- or short-rang FCS.
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