Brain Morphometric Alterations Along the Visual Pathway in Nonarteritic Anterior Ischemic Optic Neuropathy: A Voxel-Based Morphometry Study

Brain Morphometric Alterations Along the Visual Pathway in Nonarteritic Anterior Ischemic Optic Neuropathy: A Voxel-Based Morphometry Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Brain Morphometric Alterations Along the Visual Pathway in Nonarteritic Anterior Ischemic Optic Neuropathy: A Voxel-Based Morphometry Study Selda Celik Dulger, Mehtap Oktay, Nihal Gurlek Celik This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9311057/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To investigate brain morphometric changes in patients with non-arteritic anterior ischemic optic neuropathy (NAION) using voxel-based morphometry (VBM) and to explore their associations with structural and functional ophthalmic parameters. Methods: This retrospective, cross-sectional study included 15 patients with NAION and 15 healthy controls. All participants underwent high-resolution 3.0-Tesla brain magnetic resonance imaging. Whole-brain VBM was performed using the Computational Anatomy Toolbox (CAT12) implemented in Statistical Parametric Mapping (SPM12) to assess gray and white matter volume differences between groups. Ophthalmic evaluation included best-corrected visual acuity, visual field mean deviation, retinal nerve fiber layer thickness, and ganglion cell–inner plexiform layer thickness measured by optical coherence tomography. Correlation analyses were performed to evaluate the relationships between brain morphometric measures and ophthalmic parameters. Results: Compared with controls, patients with NAION showed significantly reduced gray matter volumes in the limbic lobe, cuneus, occipital lobe, temporal lobe, middle temporal gyrus, parietal lobe, and frontal lobe (all p < 0.001). Increased gray matter volumes were observed in the bilateral cerebellum, while increased white matter volumes were found in the right cerebellum and posterior cerebellar lobe (p 0.05). Conclusions: Patients with NAION exhibit brain morphometric differences involving visual pathway–related cortical regions and the cerebellum. These findings suggest that central nervous system involvement in NAION may extend beyond isolated optic nerve pathology. Nonarteritic anterior ischemic optic neuropathy voxel-based morphometry magnetic resonance imaging optical coherence tomography visual pathway Figures Figure 1 Highlights • Whole-brain voxel-based morphometry revealed cortical changes in NAION. • Gray matter reductions were observed in visual pathway–related regions. • Increased gray and white matter volumes were detected in the cerebellum. • No significant correlations were found between OCT and brain morphometry. • Findings suggest central nervous system involvement in NAION. Introduction Non-arteritic anterior ischemic optic neuropathy (NAION) is the most prevalent cause of acute optic neuropathy in middle-aged and elderly individuals. It is characterized by sudden, painless, unilateral visual loss in patients over 50 years of age, with a reported annual incidence of approximately 10 per 100,000 individuals. In NAION, perfusion failure of the short posterior ciliary arteries leads to acute ischemic infarction of the optic nerve, followed by ongoing inflammation, resulting in apoptosis of retinal ganglion cells and degeneration of axons. The underlying pathophysiological mechanisms remain incompletely understood [ 1 ]. The literature includes a limited number of conventional magnetic resonance imaging (MRI) studies evaluating the brains of patients with NAION. These studies have reported an increased burden of white matter hyperintensities (WMHs). 2 WMHs are believed to represent areas of atrophic perivascular demyelination, and their prevalence increases with advancing age. In a study using magnetization transfer imaging (MTI), which is more sensitive than conventional MRI for detecting subtle white matter changes, a higher number of WMHs was identified in patients with NAION, potentially reflecting microangiopathic changes suggested in prior imaging studies [ 2 ]. A functional MRI study evaluating neuroplasticity in patients with NAION demonstrated decreased activity in occipital visual regions following an acute NAION episode, with these changes persisting for up to six months. In addition, increased dynamic activity was observed in extra-visual cortical regions during the same period. Fellow-eye stimulation–induced activation in the visual cortex (Brodmann areas 17 and 18) was detected during the acute phase, suggesting that the visual system undergoes dynamic reorganization in response to afferent visual pathway damage [ 3 ]. The development of automated and reliable quantitative MRI-based brain imaging techniques has substantially advanced the investigation of neurological disorders. MRI-based brain volumetry is increasingly used to characterize neurodegenerative diseases such as multiple sclerosis, epilepsy, and Alzheimer’s disease. Historically, manual segmentation was the primary method for analyzing specific brain structures on MRI; however, this approach is labor-intensive and time-consuming, limiting its clinical applicability. Consequently, automated and objective segmentation algorithms have been developed to address the growing volume of neuroimaging data [ 4 ]. Voxel-based morphometry (VBM), an extension of statistical parametric mapping (SPM), enables voxel-wise quantitative assessment of gray and white matter morphology [ 4 ]. VBM detects differences in local brain tissue composition while minimizing the influence of large-scale anatomical variability through spatial normalization, tissue segmentation, and subsequent statistical analysis [ 5 ]. Several studies have investigated the relationship between retinal nerve fiber loss and gray and white matter volumes, as well as regional brain volumes, in patients with optic neuritis and multiple sclerosis [ 6 ]. Although NAION is associated with ganglion cell apoptosis and optic nerve axonal degeneration, its effects on the cerebral cortex and visual processing centers remain unclear. MRI-based brain morphometry has been widely applied in neurological diseases involving the optic nerve, such as optic neuritis; however, to the best of our knowledge, this methodology has not yet been systematically applied to patients with NAION. In this study, we employed VBM analysis to evaluate whether patients with NAION exhibit structural brain changes and to examine the relationship between brain morphometric findings and optical coherence tomography (OCT) parameters. Materials and Methods Study Design This nonrandomized, retrospective, cross-sectional study included patients with NAION and healthy controls. Demographic and clinical data were obtained retrospectively from the Picture Archiving and Communication Systems database. All data were de-identified prior to analysis. The study was approved by the local ethics committee as a retrospective review with a waiver of informed consent and was conducted in accordance with the Declaration of Helsinki. Data Collection The study included 15 patients diagnosed with NAION and 15 healthy controls evaluated at the Neuro-Ophthalmology Unit of a tertiary hospital between 2022 and 2025. Data collected for patients with NAION included demographic characteristics and ophthalmological findings, such as best-corrected visual acuity, intraocular pressure, color vision assessed using Ishihara plates, and fundus examination performed with a + 90 diopter Volk lens (Volk Optical Inc., Mentor, OH, USA). Visual field testing of the central 30° was conducted using the 30 − 2 program on a Humphrey Field Analyzer (Allergan-Humphrey, San Leandro, CA, USA). Visual field mean deviation, retinal nerve fiber layer (RNFL) thickness, and ganglion cell–inner plexiform layer (GC-IPL) thickness were measured using OCT. MRI data from all participants were archived for subsequent analysis. Patients in the NAION group met established diagnostic criteria, including optic disc edema, sudden painless vision loss, color vision impairment, optic disc hemorrhage, disc-at-risk in the fellow eye, and altitudinal visual field defects, with normal erythrocyte sedimentation rate and C-reactive protein levels. Patients with inflammatory, hereditary, traumatic, or toxic optic neuropathies were excluded. Control participants were individuals who underwent MRI at the Radiology Unit of a tertiary hospital and had no documented neurologic, psychiatric, or ophthalmologic disorders or history of neurosurgery. OCT Acquisition and Analysis RNFL and GC-IPL measurements were obtained using a spectral-domain OCT system (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA, USA). Peripapillary RNFL thickness was measured using the Optic Disc Cube 200 × 200 protocol, which acquires data from a 6 × 6 mm region centered on the optic disc. GC-IPL thickness was measured using the Macular Cube 512 × 128 scan, providing quantitative assessment of the ganglion cell and inner plexiform layers. MRI Protocol All participants underwent 3.0-Tesla MRI (Philips Ingenia Elition, Philips Healthcare, Best, The Netherlands) using a standard head coil. High-resolution sagittal T1-weighted three-dimensional turbo field echo images were acquired with the following parameters: repetition time, 6.8 ms; echo time, 3.2 ms; field of view, 256 × 256 mm²; matrix size, 256 × 256; slice thickness, 1 mm. A total of 195 slices were obtained in approximately 2 minutes and 35 seconds. Voxel-Based Morphometry Analysis VBM analysis was performed using the Computational Anatomy Toolbox (CAT12), an extension of Statistical Parametric Mapping (SPM12), implemented in MATLAB (R2010a). Preprocessing followed the CAT12 user manual guidelines, including tissue segmentation and spatial normalization. Segmented images were smoothed using an 8-mm full-width at half-maximum Gaussian kernel. Group differences in gray and white matter volumes were assessed using two-sample t tests with age, and total intracranial volume included as covariates. Statistical analyses were performed using an uncorrected voxel-level threshold of p < 0.001 with a minimum cluster size of 50 voxels. Accordingly, no formal correction for multiple comparisons was applied. Results were visualized using xjView. Given the limited sample size, whole-brain voxel-based morphometry findings should be considered exploratory and hypothesis-generating. Total gray matter, white matter, and intracranial volumes were obtained using CAT12 segmentation pipelines. Volumes of specific gray matter regions, including the thalamus, occipital lobe, and cuneus, were extracted using the Neuromorphometrics atlas and validated using the Hammers atlas. Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics version 23 and IBM AMOS version 24. Normality was assessed using the Shapiro–Wilk test. Continuous variables were compared using independent-samples t tests or Mann–Whitney U tests, as appropriate. Associations between categorical variables were analyzed using Fisher’s exact test. Pearson or Spearman correlation analyses were used to assess relationships between quantitative variables based on data distribution. Path analysis was conducted using the maximum likelihood method. Statistical significance was defined as p < 0.05. Results Fifteen patients with NAION and 15 healthy controls were included. Demographic and clinical characteristics are presented in Table 1 . Table 1 Demographic and clinical characteristics of the study groups. Variable NAION (n = 15) Controls (n = 15) p value Age (years) 62.27 ± 4.65 61.47 ± 5.82 0.681 x Sex (male), n (%) 12 (80) 12 (80) 1.000 y Disease duration (months) 16.6 ± 6.9 – – Systemic disease, n (%) 14 (93.3) 0 – x Independent-samples t test, y Fisher exact test. There were no significant differences between groups with respect to age ( p = 0.68) or sex distribution ( p = 1.00). In both groups, 12 participants were male. Except for two patients, all individuals in the NAION group had systemic comorbidities such as hypertension or diabetes mellitus. No documented systemic vascular disease was present in the control group based on available medical records. The mean follow-up duration for patients with NAION was 16.6 ± 6.6 months (range, 7–27 months). Among 30 examined eyes, 20 (66.7%) were affected by NAION. The most common visual field defect was inferior altitudinal loss (33.3%). Six patients received oral corticosteroid therapy during the acute phase. Significant differences were observed between affected and unaffected eyes in BCVA, visual field mean deviation, average RNFL thickness, average GC-IPL thickness, and sectoral RNFL measurements ( p < 0.001; Table 2 ). Table 2 Ophthalmic parameters in involved and noninvolved eyes of patients with NAION. Parameter Involved eye Noninvolved eye p value RNFL temporal (µm) 54.5 (41–75) 71 (62–110) < 0.001 x RNFL nasal (µm) 59 (48–87) 82.5 (63–101) < 0.001 x RNFL superior (µm) 71.45 ± 12.36 126.2 ± 15.38 < 0.001 y RNFL inferior (µm) 75 (54–150) 140.5 (124–157) < 0.001 x RNFL average (µm) 69.6 ± 8.71 104.3 ± 10.44 < 0.001 y MD (dB) 17.05 ± 9.73 0.73 ± 0.46 < 0.001 y BCVA (logMAR) 0.55 (0.1–1.5) 0 (0–0.2) < 0.001 x GC-IPL average (µm) 60.85 ± 10.27 85.1 ± 5.72 < 0.001 y Values are presented as mean ± standard deviation or median (min–max). x Mann–Whitney U test; y Independent-samples t test. NAION, non-arteritic anterior ischemic optic neuropathy; BCVA, best corrected visual acuity; MD, mean deviation of visual field test; RNFL, retinal nerve fiber layer; GC-IPL, ganglion cell- inner plexiform layer. Correlation analyses revealed a strong positive association between average RNFL and GC-IPL thickness ( r = 0.718, p < 0.001). BCVA was strongly correlated with visual field mean deviation ( r = 0.79, p < 0.001). No significant associations were observed between ophthalmic parameters, disease duration, and MRI-derived volumetric measures (Table 3 ). Table 3 Correlations between ophthalmic parameters and brain morphometric measures in patients with nonarteritic anterior ischemic optic neuropathy. Brain volume parameter RNFL r (p) GC-IPL r (p) MD r (p) Disease duration r (p) BCVA r (p) White matter volume 0.068 (0.722) −0.044 (0.817) 0.064 (0.736) −0.095 (0.617) −0.045 (0.815) Gray matter volume 0.017 (0.929) −0.113 (0.553) 0.033 (0.861) 0.173 (0.362) −0.064 (0.737) Intracranial volume 0.154 (0.415) 0.042 (0.828) −0.017 (0.929) 0.101 (0.597) −0.052 (0.786) Thalamus total volume 0.149 (0.431) 0.063 (0.741) 0.044 (0.820) 0.153 (0.420) −0.094 (0.621) Occipital total volume −0.027 (0.887) −0.004 (0.983) −0.032 (0.866) 0.182 (0.337) 0.062 (0.744) Cuneus total volume 0.157 (0.407) 0.102 (0.598) −0.144 (0.449) 0.200 (0.291) 0.026 (0.893) GC-IPL average 0.718 (< 0.001) – – – – Abbreviations : Correlation coefficients were calculated using Spearman’s rho or Pearson correlation analysis as appropriate. RNFL: retinal nerve fiber layer; GC-IPL: ganglion cell-inner plexiform layer; MD: mean deviation of visual field; BCVA: best corrected visual acuity. VBM analysis identified reduced gray matter volumes in the limbic lobe, cuneus, occipital lobe, temporal lobe, middle temporal gyrus, parietal lobe, and frontal lobe in patients with NAION compared with healthy controls (Table 4 ). Table 4 Brain regions showing reduced gray matter volume in patients with nonarteritic anterior ischemic optic neuropathy compared with healthy controls (NAION < control). Anatomical region Cluster size (voxels) T value Peak-level Z score p value (uncorrected) MNI coordinates (x, y, z) Cluster 1 Limbic lobe / Anterior cingulate (BA 32, 24) 980 5.83 4.62 < 0.001 −1.5, 39, 12 Cluster 2 Occipital lobe / Cuneus 128 5.24 4.29 < 0.001 22.5, − 88.5, 19.5 Cluster 3 Rolandic operculum / Parietal lobe 462 5.14 4.23 < 0.001 −45, − 13.5, 13.5 Cluster 4 Temporal lobe / Middle temporal gyrus 672 5.07 4.19 < 0.001 −57, 6, − 21 Cluster 5 Frontal lobe / Middle frontal gyrus 125 4.50 3.83 < 0.001 28.5, 49.5, 1.5 Cluster 6 Occipital lobe 150 4.45 3.80 < 0.001 40.5, − 57, −9 Cluster 7 Superior medial frontal gyrus 98 4.01 3.50 < 0.001 10.5, 40.5, 57 Abbreviations : MNI: Montreal Neurological Institute. x,y,z: Coordinates according to the Talairach Atlas. aal: Anatomical Automatic Labeling. R: Right, L: Left; Mid: Middle; Sup: Superior; Oper: Operculum. Voxel-based morphometry analysis was performed using a two-sample t test with age and total intracranial volume as covariates. Results are reported at an uncorrected voxel-level threshold of p < 0.001 with a minimum cluster size of 50 voxels. GM: gray matter. Increased gray matter volumes were observed in the bilateral cerebellum. Additionally, white matter volumes in the right cerebellum and posterior cerebellar lobe were greater in the NAION group than in controls (Table 5 ). Table 5 Brain regions showing increased gray and white matter volumes in patients with nonarteritic anterior ischemic optic neuropathy compared with healthy controls (NAION > control). White matter Anatomical region Cluster size (voxels) T value Peak-level Z score p value (uncorrected) MNI coordinates (x, y, z) Right cerebellum / posterior cerebellar lobe 98 4.34 3.73 < 0.001 12, − 61.5, − 45 Gray matter All clusters survived the predefined voxel-level threshold (p < 0.001, uncorrected) with a minimum cluster extent of 50 voxels. Group differences in gray matter volume are illustrated in Fig. 1 . Discussion In this voxel-based morphometry study, we demonstrated that patients with nonarteritic anterior ischemic optic neuropathy (NAION) exhibit significant gray matter volume reductions in multiple regions along the visual pathway, including the occipital lobe, cuneus, and associated cortical areas, accompanied by increased gray and white matter volumes in the cerebellum. These findings suggest that NAION is associated with structural brain alterations extending beyond the optic nerve and involves widespread neuroanatomical reorganization. The observed gray matter reductions in the occipital cortex and related visual areas are consistent with previous studies reporting structural alterations following optic nerve injury. Damage to the optic nerve disrupts afferent visual input to the cortex, leading to trans-synaptic degeneration along the visual pathway [ 7 – 9 ]. This process may result in progressive atrophy of the visual cortex due to reduced neuronal stimulation and axonal degeneration. Similar reductions in gray and white matter volumes have been reported in conditions such as optic neuritis, glaucoma, and macular degeneration, supporting the concept that decreased visual input leads to cortical structural changes [ 8 – 10 ]. In line with these findings, Urhan et al. demonstrated reduced volumes in the occipital lobe, calcarine cortex, and lingual gyrus in patients with NAION using a region-based volumetric approach, emphasizing the vulnerability of visual cortical regions to optic nerve damage [ 11 ]. Beyond the primary visual cortex, we also identified volumetric reductions in frontal, parietal, temporal, and limbic regions. These findings may reflect the involvement of interconnected corticocortical and subcortical pathways. The visual system is anatomically and functionally linked with multiple higher-order brain regions through extensive white matter connections, and disruption of these networks may contribute to widespread structural alterations [ 10 ]. In particular, degeneration within white matter tracts may lead to secondary cortical atrophy in connected regions, supporting the concept that NAION-related damage is not restricted to the visual cortex but affects broader brain networks. Interestingly, our study demonstrated increased gray and white matter volumes in the cerebellum. This finding is consistent with previous studies reporting cerebellar involvement in visual system disorders and may reflect compensatory neuroplastic mechanisms [ 8 , 12 ]. The cerebellum plays a critical role not only in motor coordination but also in cognitive and sensory integration processes. Increased cerebellar volume has been interpreted as a marker of adaptive reorganization in response to reduced visual input, potentially reflecting enhanced reliance on non-visual sensory modalities and motor planning systems. Similar cerebellar volumetric increases have been reported in patients with monocular vision loss and optic neuritis, further supporting this compensatory hypothesis [ 12 ]. In contrast to structural brain changes, we did not observe significant correlations between brain morphometric measures and ophthalmic parameters, including retinal nerve fiber layer (RNFL) and ganglion cell–inner plexiform layer (GC-IPL) thickness. Although previous studies in optic neuritis and multiple sclerosis have demonstrated associations between OCT parameters and brain volumes [ 13 ], the absence of correlation in our study suggests that the relationship between retinal structural damage and cortical changes in NAION may be more complex. Potential explanations include variability in disease duration, differences in individual neuroplastic responses, and the temporal dissociation between retinal degeneration and cortical remodeling. Our findings support the growing body of evidence that NAION should not be considered solely an isolated optic nerve disorder but rather a neuro-ophthalmologic condition involving widespread structural brain alterations. The combination of cortical atrophy along the visual pathway and compensatory cerebellar changes highlights the complex interplay between neurodegeneration and neuroplasticity in response to visual system injury. This study has several limitations. First, the relatively small sample size limits the generalizability of our findings and may reduce statistical power. Second, the cross-sectional design precludes conclusions regarding the temporal evolution of brain changes. Third, systemic vascular risk factors commonly associated with NAION were not directly analyzed in relation to brain morphometry. Future longitudinal studies with larger cohorts are needed to better elucidate the relationship between optic nerve damage, cortical degeneration, and neuroplastic adaptation. In conclusion, voxel-based morphometry revealed that NAION is associated with widespread structural brain alterations, particularly affecting the visual cortex and related networks, along with compensatory changes in the cerebellum. These findings reinforce the concept that NAION involves both degenerative and adaptive processes within the central nervous system. Abbreviations NAION Nonarteritic anterior ischemic optic neuropathy VBM Voxel–based morphometry MRI Magnetic resonance imaging RNFL Retinal nerve fiber layer GC IPL–Ganglion cell–inner plexiform layer BCVA Best corrected visual acuity Declarations Acknowledgments None. Funding This research received no external funding. Conflicts of Interest The authors declare no conflict of interest. Institutional Review Board Statement This study was approved by the Ethics Committee of Ankara Etlik City Hospital (AEŞH-BADEK1-2025-649). The study was conducted in accordance with the principles of the Declaration of Helsinki. Informed Consent Statement Written informed consent was waived by the ethics committee due to the retrospective nature of the study. Data Availability Statement The data supporting the findings of this study are not publicly available due to patient privacy and ethical restrictions but are available from the corresponding author upon reasonable request and with appropriate ethical approval. Author Contributions Conceptualization, S.C.D.; methodology, S.C.D.; data curation, S.C.D., N.G.C., and M.O.; formal analysis, S.C.D., M.O., and N.G.C.; writing—original draft preparation, S.C.D.; writing—review and editing, S.C.D., N.G.C., and M.O.; supervision, S.C.D., M.O., and N.G.C. All authors have read and agreed to the published version of the manuscript. References Mathews MK (2005) Nonarteritic anterior ischemic optic neuropathy. Curr Opin Ophthalmol 16:341–345 Argyropoulou MI, Zikou AK, Tzovara I et al (2007) Non-arteritic anterior ischaemic optic neuropathy: evaluation of the brain and optic pathway by conventional MRI and magnetisation transfer imaging. Eur Radiol 17:1669–1674 Aguirregomozcorta M, Mancini L, Jenkins TM et al (2011) A longitudinal functional MRI study of non-arteritic anterior ischaemic optic neuropathy patients. J Neurol Neurosurg Psychiatry 82:905–913 Manjón JV, Coupé P (2016) VolBrain: an online MRI brain volumetry system. Front Neuroinform 10:30 Mechelli A, Price CJ, Friston KJ, Ashburner J (2005) Voxel-based morphometry of the human brain: methods and applications. Curr Med Imaging Rev 1:1–9 Cagol A, Fuertes NC, Stoessel M et al (2023) Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis. J Neurol 270:2139–2148 Ptito M, Schneider FC, Paulson OB, Kupers R (2008) Alterations of the visual pathways in congenital blindness. Exp Brain Res 187:41–49 Frezzotti P, Giorgio A, Motolese I et al (2014) Structural and functional brain changes beyond the visual system in patients with advanced glaucoma. PLoS ONE. ;9 Sayin Sakul A, Pence KB, Ormeci T, Gunal M (2023) Can volumetric analysis of the brain help diagnose isolated optic neuritis? Clin Anat 36:1109–1115 Hanson RL, Gale RP, Gouws AD et al (2019) Following the status of visual cortex over time in patients with macular degeneration reveals atrophy of visually deprived brain regions. Invest Ophthalmol Vis Sci 60:5045–5051 Urhan AT, Sapmaz HI, Konuk ŞG et al (2025) Volumetric examination of the cerebellum and cortical visual centres in individuals with nonarteritic anterior ischemic optic neuropathy using automatic segmentation. J Med Top Updates 4:1–8 Özen Ö, Aslan F (2021) Morphometric evaluation of cerebellar structures in late monocular blindness. Int Ophthalmol 41:769–776 Stellmann JP, Cetin H, Young KL et al (2017) Pattern of gray matter volumes related to retinal thickness and its association with cognitive function in relapsing remitting multiple sclerosis. Brain Behav. ;7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9311057","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617709441,"identity":"c5e72223-ec5d-43d0-b918-add854f0bcd4","order_by":0,"name":"Selda Celik Dulger","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYDCCAwyMB3gYLAz4QZyEAuK0MAC1SBhINoC0GJCixeAAiEeMFr7bxx8ceFMjYWx8fnXihwcGDPL8Ygfwa5E8l2NwcM4xCTOzG283SwAdZjhzdgJ+LQZneBgO8zZI2JjdOLsBpCXB4DZBLewPwFqMZ5zd/INILQwGIC1mBvy924izRfIMD9gvxhI3eLdZJBhIEPYL3xn2hw/e1NgY9vef3XzzR4WNPL80AS0IIAFWKUGschDgP0CK6lEwCkbBKBhJAAB8c0cBlYr/JgAAAABJRU5ErkJggg==","orcid":"","institution":"Ministry of Health Ankara Etlik City Hospital","correspondingAuthor":true,"prefix":"","firstName":"Selda","middleName":"Celik","lastName":"Dulger","suffix":""},{"id":617709442,"identity":"6a8af8a7-44b7-494e-9b17-5f05a86e4feb","order_by":1,"name":"Mehtap Oktay","email":"","orcid":"","institution":"Ministry of Health Ankara Etlik City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mehtap","middleName":"","lastName":"Oktay","suffix":""},{"id":617709443,"identity":"834e32a3-39ce-4876-8256-5427ecaf39cb","order_by":2,"name":"Nihal Gurlek Celik","email":"","orcid":"","institution":"Faculty of Medicine, Amasya University","correspondingAuthor":false,"prefix":"","firstName":"Nihal","middleName":"Gurlek","lastName":"Celik","suffix":""}],"badges":[],"createdAt":"2026-04-03 09:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9311057/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9311057/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106214826,"identity":"8572837d-441d-470a-8368-184a67186a5e","added_by":"auto","created_at":"2026-04-06 08:17:10","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":443610,"visible":true,"origin":"","legend":"\u003cp\u003eVoxel-based morphometry results comparing patients with NAION and healthy controls using SPM12.\u003cbr\u003e\n(A) Whole-brain statistical parametric map showing gray matter differences (blue: NAION \u0026lt; controls; red: NAION \u0026gt; controls).\u003cbr\u003e\n(B) Slice view of gray matter differences displayed with xjView.\u003cbr\u003e\n(C) Three-dimensional rendered brain view demonstrating regions with significant gray matter differences.\u003c/p\u003e","description":"","filename":"figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9311057/v1/ddcb2da597daa87c6ed126b3.jpg"},{"id":106404200,"identity":"d92afda2-b031-43e5-ae06-907ad22eee9c","added_by":"auto","created_at":"2026-04-08 09:15:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1288427,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9311057/v1/bc374835-7cba-46f2-a028-5d466a4182bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Brain Morphometric Alterations Along the Visual Pathway in Nonarteritic Anterior Ischemic Optic Neuropathy: A Voxel-Based Morphometry Study","fulltext":[{"header":"Highlights","content":"\u003cp\u003e• Whole-brain voxel-based morphometry revealed cortical changes in NAION.\u003c/p\u003e\n\u003cp\u003e• Gray matter reductions were observed in visual pathway–related regions.\u003c/p\u003e\n\u003cp\u003e• Increased gray and white matter volumes were detected in the cerebellum.\u003c/p\u003e\n\u003cp\u003e• No significant correlations were found between OCT and brain morphometry.\u003c/p\u003e\n\u003cp\u003e• Findings suggest central nervous system involvement in NAION.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eNon-arteritic anterior ischemic optic neuropathy (NAION) is the most prevalent cause of acute optic neuropathy in middle-aged and elderly individuals. It is characterized by sudden, painless, unilateral visual loss in patients over 50 years of age, with a reported annual incidence of approximately 10 per 100,000 individuals. In NAION, perfusion failure of the short posterior ciliary arteries leads to acute ischemic infarction of the optic nerve, followed by ongoing inflammation, resulting in apoptosis of retinal ganglion cells and degeneration of axons. The underlying pathophysiological mechanisms remain incompletely understood [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe literature includes a limited number of conventional magnetic resonance imaging (MRI) studies evaluating the brains of patients with NAION. These studies have reported an increased burden of white matter hyperintensities (WMHs).\u003csup\u003e2\u003c/sup\u003e WMHs are believed to represent areas of atrophic perivascular demyelination, and their prevalence increases with advancing age. In a study using magnetization transfer imaging (MTI), which is more sensitive than conventional MRI for detecting subtle white matter changes, a higher number of WMHs was identified in patients with NAION, potentially reflecting microangiopathic changes suggested in prior imaging studies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA functional MRI study evaluating neuroplasticity in patients with NAION demonstrated decreased activity in occipital visual regions following an acute NAION episode, with these changes persisting for up to six months. In addition, increased dynamic activity was observed in extra-visual cortical regions during the same period. Fellow-eye stimulation\u0026ndash;induced activation in the visual cortex (Brodmann areas 17 and 18) was detected during the acute phase, suggesting that the visual system undergoes dynamic reorganization in response to afferent visual pathway damage [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe development of automated and reliable quantitative MRI-based brain imaging techniques has substantially advanced the investigation of neurological disorders. MRI-based brain volumetry is increasingly used to characterize neurodegenerative diseases such as multiple sclerosis, epilepsy, and Alzheimer\u0026rsquo;s disease. Historically, manual segmentation was the primary method for analyzing specific brain structures on MRI; however, this approach is labor-intensive and time-consuming, limiting its clinical applicability. Consequently, automated and objective segmentation algorithms have been developed to address the growing volume of neuroimaging data [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Voxel-based morphometry (VBM), an extension of statistical parametric mapping (SPM), enables voxel-wise quantitative assessment of gray and white matter morphology [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. VBM detects differences in local brain tissue composition while minimizing the influence of large-scale anatomical variability through spatial normalization, tissue segmentation, and subsequent statistical analysis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have investigated the relationship between retinal nerve fiber loss and gray and white matter volumes, as well as regional brain volumes, in patients with optic neuritis and multiple sclerosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although NAION is associated with ganglion cell apoptosis and optic nerve axonal degeneration, its effects on the cerebral cortex and visual processing centers remain unclear. MRI-based brain morphometry has been widely applied in neurological diseases involving the optic nerve, such as optic neuritis; however, to the best of our knowledge, this methodology has not yet been systematically applied to patients with NAION. In this study, we employed VBM analysis to evaluate whether patients with NAION exhibit structural brain changes and to examine the relationship between brain morphometric findings and optical coherence tomography (OCT) parameters.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis nonrandomized, retrospective, cross-sectional study included patients with NAION and healthy controls. Demographic and clinical data were obtained retrospectively from the Picture Archiving and Communication Systems database. All data were de-identified prior to analysis. The study was approved by the local ethics committee as a retrospective review with a waiver of informed consent and was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eThe study included 15 patients diagnosed with NAION and 15 healthy controls evaluated at the Neuro-Ophthalmology Unit of a tertiary hospital between 2022 and 2025. Data collected for patients with NAION included demographic characteristics and ophthalmological findings, such as best-corrected visual acuity, intraocular pressure, color vision assessed using Ishihara plates, and fundus examination performed with a\u0026thinsp;+\u0026thinsp;90 diopter Volk lens (Volk Optical Inc., Mentor, OH, USA). Visual field testing of the central 30\u0026deg; was conducted using the 30\u0026thinsp;\u0026minus;\u0026thinsp;2 program on a Humphrey Field Analyzer (Allergan-Humphrey, San Leandro, CA, USA). Visual field mean deviation, retinal nerve fiber layer (RNFL) thickness, and ganglion cell\u0026ndash;inner plexiform layer (GC-IPL) thickness were measured using OCT. MRI data from all participants were archived for subsequent analysis.\u003c/p\u003e \u003cp\u003ePatients in the NAION group met established diagnostic criteria, including optic disc edema, sudden painless vision loss, color vision impairment, optic disc hemorrhage, disc-at-risk in the fellow eye, and altitudinal visual field defects, with normal erythrocyte sedimentation rate and C-reactive protein levels. Patients with inflammatory, hereditary, traumatic, or toxic optic neuropathies were excluded.\u003c/p\u003e \u003cp\u003eControl participants were individuals who underwent MRI at the Radiology Unit of a tertiary hospital and had no documented neurologic, psychiatric, or ophthalmologic disorders or history of neurosurgery.\u003c/p\u003e\n\u003ch3\u003eOCT Acquisition and Analysis\u003c/h3\u003e\n\u003cp\u003eRNFL and GC-IPL measurements were obtained using a spectral-domain OCT system (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA, USA). Peripapillary RNFL thickness was measured using the Optic Disc Cube 200 \u0026times; 200 protocol, which acquires data from a 6 \u0026times; 6 mm region centered on the optic disc. GC-IPL thickness was measured using the Macular Cube 512 \u0026times; 128 scan, providing quantitative assessment of the ganglion cell and inner plexiform layers.\u003c/p\u003e\n\u003ch3\u003eMRI Protocol\u003c/h3\u003e\n\u003cp\u003eAll participants underwent 3.0-Tesla MRI (Philips Ingenia Elition, Philips Healthcare, Best, The Netherlands) using a standard head coil. High-resolution sagittal T1-weighted three-dimensional turbo field echo images were acquired with the following parameters: repetition time, 6.8 ms; echo time, 3.2 ms; field of view, 256 \u0026times; 256 mm\u0026sup2;; matrix size, 256 \u0026times; 256; slice thickness, 1 mm. A total of 195 slices were obtained in approximately 2 minutes and 35 seconds.\u003c/p\u003e\n\u003ch3\u003eVoxel-Based Morphometry Analysis\u003c/h3\u003e\n\u003cp\u003eVBM analysis was performed using the Computational Anatomy Toolbox (CAT12), an extension of Statistical Parametric Mapping (SPM12), implemented in MATLAB (R2010a). Preprocessing followed the CAT12 user manual guidelines, including tissue segmentation and spatial normalization. Segmented images were smoothed using an 8-mm full-width at half-maximum Gaussian kernel. Group differences in gray and white matter volumes were assessed using two-sample \u003cem\u003et\u003c/em\u003e tests with age, and total intracranial volume included as covariates. Statistical analyses were performed using an uncorrected voxel-level threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 with a minimum cluster size of 50 voxels. Accordingly, no formal correction for multiple comparisons was applied. Results were visualized using xjView. Given the limited sample size, whole-brain voxel-based morphometry findings should be considered exploratory and hypothesis-generating.\u003c/p\u003e \u003cp\u003eTotal gray matter, white matter, and intracranial volumes were obtained using CAT12 segmentation pipelines. Volumes of specific gray matter regions, including the thalamus, occipital lobe, and cuneus, were extracted using the Neuromorphometrics atlas and validated using the Hammers atlas.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics version 23 and IBM AMOS version 24. Normality was assessed using the Shapiro\u0026ndash;Wilk test. Continuous variables were compared using independent-samples \u003cem\u003et\u003c/em\u003e tests or Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e tests, as appropriate. Associations between categorical variables were analyzed using Fisher\u0026rsquo;s exact test. Pearson or Spearman correlation analyses were used to assess relationships between quantitative variables based on data distribution. Path analysis was conducted using the maximum likelihood method. Statistical significance was defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFifteen patients with NAION and 15 healthy controls were included. Demographic and clinical characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of the study groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNAION (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.27\u0026thinsp;\u0026plusmn;\u0026thinsp;4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.47\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystemic disease, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ex\u003c/sup\u003e Independent-samples t test, \u003csup\u003ey\u003c/sup\u003eFisher exact test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere were no significant differences between groups with respect to age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.68) or sex distribution (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00). In both groups, 12 participants were male. Except for two patients, all individuals in the NAION group had systemic comorbidities such as hypertension or diabetes mellitus. No documented systemic vascular disease was present in the control group based on available medical records.\u003c/p\u003e \u003cp\u003eThe mean follow-up duration for patients with NAION was 16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6 months (range, 7\u0026ndash;27 months). Among 30 examined eyes, 20 (66.7%) were affected by NAION. The most common visual field defect was inferior altitudinal loss (33.3%). Six patients received oral corticosteroid therapy during the acute phase. Significant differences were observed between affected and unaffected eyes in BCVA, visual field mean deviation, average RNFL thickness, average GC-IPL thickness, and sectoral RNFL measurements (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOphthalmic parameters in involved and noninvolved eyes of patients with NAION.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvolved eye\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoninvolved eye\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFL temporal (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.5 (41\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (62\u0026ndash;110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFL nasal (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (48\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.5 (63\u0026ndash;101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFL superior (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.45\u0026thinsp;\u0026plusmn;\u0026thinsp;12.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFL inferior (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (54\u0026ndash;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.5 (124\u0026ndash;157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFL average (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD (dB)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.05\u0026thinsp;\u0026plusmn;\u0026thinsp;9.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCVA (logMAR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55 (0.1\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0\u0026ndash;0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC-IPL average (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.85\u0026thinsp;\u0026plusmn;\u0026thinsp;10.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (min\u0026ndash;max).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ex\u003c/sup\u003e Mann\u0026ndash;Whitney U test; \u003csup\u003ey\u003c/sup\u003e Independent-samples t test. NAION, non-arteritic anterior ischemic optic neuropathy; BCVA, best corrected visual acuity; MD, mean deviation of visual field test; RNFL, retinal nerve fiber layer; GC-IPL, ganglion cell- inner plexiform layer.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCorrelation analyses revealed a strong positive association between average RNFL and GC-IPL thickness (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.718, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). BCVA was strongly correlated with visual field mean deviation (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.79, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant associations were observed between ophthalmic parameters, disease duration, and MRI-derived volumetric measures (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eCorrelations between ophthalmic parameters and brain morphometric measures in patients with nonarteritic anterior ischemic optic neuropathy.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain volume parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRNFL r (p)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGC-IPL r (p)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMD r (p)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDisease duration r (p)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBCVA r (p)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite matter volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.068 (0.722)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.044 (0.817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.064 (0.736)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;0.095 (0.617)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;0.045 (0.815)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGray matter volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.017 (0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.113 (0.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.033 (0.861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.173 (0.362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;0.064 (0.737)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntracranial volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.154 (0.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.042 (0.828)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.017 (0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.101 (0.597)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;0.052 (0.786)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThalamus total volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.149 (0.431)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063 (0.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044 (0.820)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.153 (0.420)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;0.094 (0.621)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccipital total volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.027 (0.887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.004 (0.983)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.032 (0.866)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.182 (0.337)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.062 (0.744)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCuneus total volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.157 (0.407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102 (0.598)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.144 (0.449)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.200 (0.291)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.026 (0.893)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC-IPL average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.718 \u003cb\u003e(\u0026lt;\u0026thinsp;0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCorrelation coefficients were calculated using Spearman\u0026rsquo;s rho or Pearson correlation analysis as appropriate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRNFL: retinal nerve fiber layer; GC-IPL: ganglion cell-inner plexiform layer; MD: mean deviation of visual field; BCVA: best corrected visual acuity.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eVBM analysis identified reduced gray matter volumes in the limbic lobe, cuneus, occipital lobe, temporal lobe, middle temporal gyrus, parietal lobe, and frontal lobe in patients with NAION compared with healthy controls (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBrain regions showing reduced gray matter volume in patients with nonarteritic anterior ischemic optic neuropathy compared with healthy controls (NAION\u0026thinsp;\u0026lt;\u0026thinsp;control).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnatomical region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster size (voxels)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePeak-level Z score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep value (uncorrected)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMNI coordinates (x, y, z)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLimbic lobe / Anterior cingulate (BA 32, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;1.5, 39, 12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccipital lobe / Cuneus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.5, \u0026minus;\u0026thinsp;88.5, 19.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRolandic operculum / Parietal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;45, \u0026minus;\u0026thinsp;13.5, 13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemporal lobe / Middle temporal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;57, 6, \u0026minus;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrontal lobe / Middle frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.5, 49.5, 1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccipital lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.5, \u0026minus;\u0026thinsp;57, \u0026minus;9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCluster 7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuperior medial frontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5, 40.5, 57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eAbbreviations\u003c/b\u003e:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMNI: Montreal Neurological Institute. x,y,z: Coordinates according to the Talairach Atlas. aal: Anatomical Automatic Labeling. R: Right, L: Left; Mid: Middle; Sup: Superior; Oper: Operculum. Voxel-based morphometry analysis was performed using a two-sample \u003cem\u003et\u003c/em\u003e test with age and total intracranial volume as covariates. Results are reported at an uncorrected voxel-level threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 with a minimum cluster size of 50 voxels. GM: gray matter.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIncreased gray matter volumes were observed in the bilateral cerebellum. Additionally, white matter volumes in the right cerebellum and posterior cerebellar lobe were greater in the NAION group than in controls (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBrain regions showing increased gray and white matter volumes in patients with nonarteritic anterior ischemic optic neuropathy compared with healthy controls (NAION\u0026thinsp;\u0026gt;\u0026thinsp;control). White matter\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnatomical region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster size (voxels)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePeak-level Z score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep value (uncorrected)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMNI coordinates (x, y, z)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight cerebellum / posterior cerebellar lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12, \u0026minus;\u0026thinsp;61.5, \u0026minus;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eGray matter\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll clusters survived the predefined voxel-level threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, uncorrected) with a minimum cluster extent of 50 voxels. Group differences in gray matter volume are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this voxel-based morphometry study, we demonstrated that patients with nonarteritic anterior ischemic optic neuropathy (NAION) exhibit significant gray matter volume reductions in multiple regions along the visual pathway, including the occipital lobe, cuneus, and associated cortical areas, accompanied by increased gray and white matter volumes in the cerebellum. These findings suggest that NAION is associated with structural brain alterations extending beyond the optic nerve and involves widespread neuroanatomical reorganization.\u003c/p\u003e \u003cp\u003eThe observed gray matter reductions in the occipital cortex and related visual areas are consistent with previous studies reporting structural alterations following optic nerve injury. Damage to the optic nerve disrupts afferent visual input to the cortex, leading to trans-synaptic degeneration along the visual pathway [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This process may result in progressive atrophy of the visual cortex due to reduced neuronal stimulation and axonal degeneration. Similar reductions in gray and white matter volumes have been reported in conditions such as optic neuritis, glaucoma, and macular degeneration, supporting the concept that decreased visual input leads to cortical structural changes [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In line with these findings, Urhan et al. demonstrated reduced volumes in the occipital lobe, calcarine cortex, and lingual gyrus in patients with NAION using a region-based volumetric approach, emphasizing the vulnerability of visual cortical regions to optic nerve damage [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond the primary visual cortex, we also identified volumetric reductions in frontal, parietal, temporal, and limbic regions. These findings may reflect the involvement of interconnected corticocortical and subcortical pathways. The visual system is anatomically and functionally linked with multiple higher-order brain regions through extensive white matter connections, and disruption of these networks may contribute to widespread structural alterations [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In particular, degeneration within white matter tracts may lead to secondary cortical atrophy in connected regions, supporting the concept that NAION-related damage is not restricted to the visual cortex but affects broader brain networks.\u003c/p\u003e \u003cp\u003eInterestingly, our study demonstrated increased gray and white matter volumes in the cerebellum. This finding is consistent with previous studies reporting cerebellar involvement in visual system disorders and may reflect compensatory neuroplastic mechanisms [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The cerebellum plays a critical role not only in motor coordination but also in cognitive and sensory integration processes. Increased cerebellar volume has been interpreted as a marker of adaptive reorganization in response to reduced visual input, potentially reflecting enhanced reliance on non-visual sensory modalities and motor planning systems. Similar cerebellar volumetric increases have been reported in patients with monocular vision loss and optic neuritis, further supporting this compensatory hypothesis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast to structural brain changes, we did not observe significant correlations between brain morphometric measures and ophthalmic parameters, including retinal nerve fiber layer (RNFL) and ganglion cell\u0026ndash;inner plexiform layer (GC-IPL) thickness. Although previous studies in optic neuritis and multiple sclerosis have demonstrated associations between OCT parameters and brain volumes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the absence of correlation in our study suggests that the relationship between retinal structural damage and cortical changes in NAION may be more complex. Potential explanations include variability in disease duration, differences in individual neuroplastic responses, and the temporal dissociation between retinal degeneration and cortical remodeling.\u003c/p\u003e \u003cp\u003eOur findings support the growing body of evidence that NAION should not be considered solely an isolated optic nerve disorder but rather a neuro-ophthalmologic condition involving widespread structural brain alterations. The combination of cortical atrophy along the visual pathway and compensatory cerebellar changes highlights the complex interplay between neurodegeneration and neuroplasticity in response to visual system injury.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the relatively small sample size limits the generalizability of our findings and may reduce statistical power. Second, the cross-sectional design precludes conclusions regarding the temporal evolution of brain changes. Third, systemic vascular risk factors commonly associated with NAION were not directly analyzed in relation to brain morphometry. Future longitudinal studies with larger cohorts are needed to better elucidate the relationship between optic nerve damage, cortical degeneration, and neuroplastic adaptation.\u003c/p\u003e \u003cp\u003eIn conclusion, voxel-based morphometry revealed that NAION is associated with widespread structural brain alterations, particularly affecting the visual cortex and related networks, along with compensatory changes in the cerebellum. These findings reinforce the concept that NAION involves both degenerative and adaptive processes within the central nervous system.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAION\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNonarteritic anterior ischemic optic neuropathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVoxel\u0026ndash;based morphometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRNFL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRetinal nerve fiber layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIPL\u0026ndash;Ganglion cell\u0026ndash;inner plexiform layer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBCVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBest corrected visual acuity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003ch3\u003eConflicts of Interest\u003c/h3\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003ch3\u003eInstitutional Review Board Statement\u003c/h3\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Ankara Etlik City Hospital (AEŞH-BADEK1-2025-649). The study was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eInformed Consent Statement\u003c/h3\u003e\n\u003cp\u003eWritten informed consent was waived by the ethics committee due to the retrospective nature of the study.\u003c/p\u003e\n\u003ch3\u003eData Availability Statement\u003c/h3\u003e\n\u003cp\u003eThe data supporting the findings of this study are not publicly available due to patient privacy and ethical restrictions but are available from the corresponding author upon reasonable request and with appropriate ethical approval.\u003c/p\u003e\n\u003ch3\u003eAuthor Contributions\u003c/h3\u003e\n\u003cp\u003eConceptualization, S.C.D.; methodology, S.C.D.; data curation, S.C.D., N.G.C., and M.O.; formal analysis, S.C.D., M.O., and N.G.C.; writing—original draft preparation, S.C.D.; writing—review and editing, S.C.D., N.G.C., and M.O.; supervision, S.C.D., M.O., and N.G.C.\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMathews MK (2005) Nonarteritic anterior ischemic optic neuropathy. Curr Opin Ophthalmol 16:341\u0026ndash;345\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArgyropoulou MI, Zikou AK, Tzovara I et al (2007) Non-arteritic anterior ischaemic optic neuropathy: evaluation of the brain and optic pathway by conventional MRI and magnetisation transfer imaging. Eur Radiol 17:1669\u0026ndash;1674\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAguirregomozcorta M, Mancini L, Jenkins TM et al (2011) A longitudinal functional MRI study of non-arteritic anterior ischaemic optic neuropathy patients. J Neurol Neurosurg Psychiatry 82:905\u0026ndash;913\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManj\u0026oacute;n JV, Coup\u0026eacute; P (2016) VolBrain: an online MRI brain volumetry system. Front Neuroinform 10:30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMechelli A, Price CJ, Friston KJ, Ashburner J (2005) Voxel-based morphometry of the human brain: methods and applications. Curr Med Imaging Rev 1:1\u0026ndash;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCagol A, Fuertes NC, Stoessel M et al (2023) Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis. J Neurol 270:2139\u0026ndash;2148\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePtito M, Schneider FC, Paulson OB, Kupers R (2008) Alterations of the visual pathways in congenital blindness. Exp Brain Res 187:41\u0026ndash;49\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrezzotti P, Giorgio A, Motolese I et al (2014) Structural and functional brain changes beyond the visual system in patients with advanced glaucoma. PLoS ONE. ;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSayin Sakul A, Pence KB, Ormeci T, Gunal M (2023) Can volumetric analysis of the brain help diagnose isolated optic neuritis? Clin Anat 36:1109\u0026ndash;1115\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanson RL, Gale RP, Gouws AD et al (2019) Following the status of visual cortex over time in patients with macular degeneration reveals atrophy of visually deprived brain regions. Invest Ophthalmol Vis Sci 60:5045\u0026ndash;5051\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUrhan AT, Sapmaz HI, Konuk ŞG et al (2025) Volumetric examination of the cerebellum and cortical visual centres in individuals with nonarteritic anterior ischemic optic neuropathy using automatic segmentation. J Med Top Updates 4:1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zen \u0026Ouml;, Aslan F (2021) Morphometric evaluation of cerebellar structures in late monocular blindness. Int Ophthalmol 41:769\u0026ndash;776\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStellmann JP, Cetin H, Young KL et al (2017) Pattern of gray matter volumes related to retinal thickness and its association with cognitive function in relapsing remitting multiple sclerosis. Brain Behav. ;7\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Nonarteritic anterior ischemic optic neuropathy, voxel-based morphometry, magnetic resonance imaging, optical coherence tomography, visual pathway","lastPublishedDoi":"10.21203/rs.3.rs-9311057/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9311057/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e \u003cp\u003eTo investigate brain morphometric changes in patients with non-arteritic anterior ischemic optic neuropathy (NAION) using voxel-based morphometry (VBM) and to explore their associations with structural and functional ophthalmic parameters.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis retrospective, cross-sectional study included 15 patients with NAION and 15 healthy controls. All participants underwent high-resolution 3.0-Tesla brain magnetic resonance imaging. Whole-brain VBM was performed using the Computational Anatomy Toolbox (CAT12) implemented in Statistical Parametric Mapping (SPM12) to assess gray and white matter volume differences between groups. Ophthalmic evaluation included best-corrected visual acuity, visual field mean deviation, retinal nerve fiber layer thickness, and ganglion cell\u0026ndash;inner plexiform layer thickness measured by optical coherence tomography. Correlation analyses were performed to evaluate the relationships between brain morphometric measures and ophthalmic parameters.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eCompared with controls, patients with NAION showed significantly reduced gray matter volumes in the limbic lobe, cuneus, occipital lobe, temporal lobe, middle temporal gyrus, parietal lobe, and frontal lobe (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Increased gray matter volumes were observed in the bilateral cerebellum, while increased white matter volumes were found in the right cerebellum and posterior cerebellar lobe (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant correlations were identified between brain morphometric measures and ophthalmic parameters, disease duration, or visual function (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003ePatients with NAION exhibit brain morphometric differences involving visual pathway\u0026ndash;related cortical regions and the cerebellum. These findings suggest that central nervous system involvement in NAION may extend beyond isolated optic nerve pathology.\u003c/p\u003e","manuscriptTitle":"Brain Morphometric Alterations Along the Visual Pathway in Nonarteritic Anterior Ischemic Optic Neuropathy: A Voxel-Based Morphometry Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-06 08:17:05","doi":"10.21203/rs.3.rs-9311057/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c86fc721-eccb-45ee-8b38-4ef18d97f88c","owner":[],"postedDate":"April 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T06:09:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-06 08:17:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9311057","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9311057","identity":"rs-9311057","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}