Altered Short Posterior Ciliary Artery Hemodynamics on Point-of-Care Doppler Imaging: A Novel Biomarker in Acute Mild Traumatic Brain Injury

Altered Short Posterior Ciliary Artery Hemodynamics on Point-of-Care Doppler Imaging: A Novel Biomarker in Acute Mild Traumatic Brain Injury | 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 Altered Short Posterior Ciliary Artery Hemodynamics on Point-of-Care Doppler Imaging: A Novel Biomarker in Acute Mild Traumatic Brain Injury Abbas Mohammadi, Mohammad Jorfi, Seyed Ali Tabatabaei, Shadi Khosravan, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8533634/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Mild traumatic brain injury (mTBI) lacks sensitive biomarkers for acute cerebrovascular dysregulation. The short posterior ciliary arteries (SPCA), as part of the cerebral circulation, offer a potential window into this pathophysiology via transorbital sonography. Objective This study aimed to evaluate SPCA hemodynamics using point-of-care Color Doppler Imaging (CDI) as a novel functional biomarker in acute mTBI. Methods In this prospective case-control study, thirty adults with acute, isolated mTBI (GCS 13–15) and thirty matched controls underwent standardized transorbital CDI within 24 hours of injury. Hemodynamic parameters—Peak Systolic Velocity (PSV), End-Diastolic Velocity (EDV), Resistance Index (RI), and Pulsatility Index (PI)—were measured in the ophthalmic, central retinal, and short posterior ciliary arteries. Clinical indices (GCS, IOP, visual acuity) were concurrently assessed. Results The mTBI group demonstrated a distinct hemodynamic signature in the SPCA circulation, characterized by significantly elevated vascular resistance (RI: 0.65 ± 0.08 vs. 0.59 ± 0.06, p = 0.001; PI: 1.11 ± 0.26 vs. 0.95 ± 0.17, p = 0.005) and reduced perfusion (PSV: 14.7 ± 4.1 cm/s vs. 18.7 ± 8.4 cm/s, p = 0.021). Increased central retinal artery resistance was also observed (RI: 0.67 ± 0.07 vs. 0.64 ± 0.07, p = 0.042). Glasgow Coma Scale scores showed a significant inverse correlation with retinal arterial pulsatility (CRA-PI: r = -0.286, p = 0.027), linking hemodynamic alterations to neurological status. Conclusions This study identifies altered SPCA hemodynamics—a high-resistance, low-flow profile—as a novel, functional physiological biomarker for acute mTBI, assessable via rapid bedside CDI. These findings expand the mTBI biomarker paradigm from static molecular indicators to include dynamic cerebrovascular dysregulation. CDI of the retrobulbar circulation offers a unique, accessible tool that, with further validation, holds promise for enhancing diagnostic precision, elucidating patient-specific pathophysiology, and guiding personalized management in mTBI. Mild traumatic brain injury biomarker color Doppler imaging short posterior ciliary artery cerebrovascular dysregulation hemodynamics point-of-care ultrasound Figures Figure 1 Figure 2 Figure 3 1. Introduction Traumatic brain injury (TBI) constitutes a major global public health burden, representing a leading cause of mortality and long-term disability worldwide [1]. While initial management focuses on stabilizing life-threatening intracranial pathology, a significant subset of patients, even those presenting with mild TBI(mTBI) (Glasgow Coma Scale [GCS] 13-15), develop persistent and debilitating visual and neurological sequelae that severely impact quality of life [2]. This highlights a critical need for early, sensitive prognostic tools that can identify patients at risk for secondary complications beyond standard neuroimaging. The eye, as an embryological extension of the central nervous system, offers a unique and accessible window into cerebral pathophysiology. Following TBI, structural ocular changes such as retinal nerve fiber layer thinning and optic nerve sheath diameter (ONSD) expansion have been documented and correlate with intracranial pressure and outcome [3, 4]. Robba et al. demonstrated that ONSD ultrasonography at admission is a reliable predictor of intracranial hypertension and mortality, validating the concept of using ocular parameters for neuromonitoring [4]. However, while these structural assessments are informative, they may not capture the earliest functional disturbances in microvascular perfusion that precede permanent anatomical damage. Cerebrovascular dysregulation, including impaired autoregulation and changes in cerebral blood flow, is a well-recognized secondary insult following TBI and is strongly linked to poor outcomes [5, 6]. By extension, the vascular supply to the eye—particularly the retrobulbar circulation comprising the ophthalmic, central retinal (CRA), and Short posterior ciliary arteries (SPCA)—is also vulnerable. The SPCA is especially critical as it supplies the optic nerve head and choroid. Compromise of this circulation through vasospasm, increased intracranial pressure transmitted along the optic nerve sheath, or systemic inflammatory responses could lead to ischemic optic neuropathy and irreversible visual loss [7, 8]. Despite this plausible mechanism, the real-time, in vivo assessment of retrobulbar hemodynamics in the acute phase of TBI remains largely unexplored. Point-of-care Color Doppler Imaging (CDI) is a rapid, non-invasive, and readily available bedside technology capable of quantifying blood flow velocities and vascular resistance indices. It has been successfully used to evaluate orbital vascular disorders but has not been systematically integrated into the early assessment of TBI [9]. We hypothesize that acute blunt head trauma induces immediate and measurable hemodynamic alterations in the retrobulbar circulation, characterized by increased vascular resistance and reduced flow velocities, and that the magnitude of these changes correlates with clinical injury severity. Therefore, this prospective case-control study aimed to: 1) Compare the retrobulbar hemodynamic parameters (Peak Systolic Velocity [PSV], End-Diastolic Velocity [EDV], Resistance Index [RI], and Pulsatility Index [PI]) of patients with acute isolated blunt head trauma to matched healthy controls using point-of-care Color Doppler sonography, and 2) Correlate these vascular parameters with established clinical indices of injury severity, including GCS and intraocular pressure (IOP). This research seeks to establish the foundation for using ocular vascular sonography as a complementary prognostic tool in the acute management of TBI. 2. Methods 2.1. Study Design and Setting This prospective case-control study was conducted at the Golestan Hospital, a major tertiary trauma referral center in Ahvaz, southern Iran. The study was performed between June 2022 and June 2025. The hospital’s emergency department provides care for a high volume of neurotrauma cases from across the Khuzestan province. The study protocol was reviewed and approved by the Institutional Review Board (IRB) and Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (Ethical Code: IR.AJUMS.REC.1404.129). The study adhered to the principles of the Declaration of Helsinki and Good Clinical Practice guidelines. Written informed consent was obtained from all control participants and from the legally authorized representatives of patients in the trauma group prior to enrollment. 2.2. Participants A total of 60 adult participants were enrolled and divided into two groups. Trauma Group: Thirty consecutive adult patients (aged 18-65 years) presenting to the emergency department with an acute, isolated blunt head trauma within the preceding 24 hours were included. Injury was defined as "isolated" based on an Abbreviated Injury Scale (AIS) score of ≥1 for the head region and 0 for all other body parts. To focus on mild to moderate injury, an initial GCS score between 13 and 15 was required. Control Group: Thirty age- and sex-matched healthy volunteers with no history of head trauma, ocular disease, or major systemic illness (e.g., uncontrolled hypertension, diabetes) were recruited. Exclusion Criteria for both groups were: a history of prior ocular surgery or significant ocular pathology (e.g., glaucoma, retinal vascular occlusion), penetrating ocular injury, refractive error greater than ±6 diopters, inability to cooperate for the sonographic examination, or any contraindication to orbital ultrasound. 2.3. Clinical Assessment Upon presentation, trauma patients underwent a standardized evaluation: Neurological Assessment: The GCS score was recorded by the attending emergency physician. Ophthalmic Examination: IOP was measured in both eyes using a calibrated handheld tonometer (e.g., Tono-Pen). Best-corrected visual acuity (BCVA) was assessed using a Snellen chart at 6 meters. Neuroimaging: All trauma patients underwent non-contrast computed tomography (CT) of the brain as per standard trauma protocol to confirm the diagnosis, rule out surgical lesions, and allow for anatomical injury scoring. 2.4. Color Doppler Sonography Protocol Retrobulbar hemodynamic assessment was performed for all participants within 2 hours of clinical evaluation. A single experienced radiologist, blinded to the patient’s group assignment, performed all scans using a high-resolution ultrasound system (Philips EPIQ 7G) equipped with a high-frequency linear array transducer (5-12 MHz). Patients were examined in a supine position with eyes gently closed. The probe was placed on the closed upper eyelid using copious coupling gel, ensuring no pressure was applied to the globe. Using B-mode for anatomical guidance, the Color Doppler function was activated to identify the target vessels. Pulsed-wave Doppler spectral analysis was then performed with the sample gate set to 1-2 mm [figure 1] . The following arteries were examined in each eye, and measurements were averaged from three consecutive cardiac cycles: OA: Sampled at a depth of 25-35 mm posterior to the globe. CRA: Identified within the optic nerve shadow, approximately 10-15 mm behind the lamina cribrosa. SPCA: Sampled as they entered the globe medial and lateral to the optic nerve. The following hemodynamic parameters were recorded for each vessel: PSV; cm/s EDV; cm/s RI, calculated as (PSV – EDV) / PSV PI, calculated as (PSV – EDV) / Mean Velocity 2.5. Statistical Analysis Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 26.0. Descriptive data are presented as mean ± standard deviation (SD) for normally distributed variables or median (interquartile range) for non-normal variables. Categorical variables are presented as frequencies (percentages). Group Comparisons: Independent samples t-test or Mann-Whitney U test was used for continuous variables, as appropriate. The Chi-square test was used for categorical variables (e.g., sex). Analysis of Hemodynamic Parameters: A General Linear Model (GLM) was employed to compare Doppler parameters between the Trauma and Control groups, with the potential to include covariates (e.g., age, IOP). Correlation Analysis: Pearson’s or Spearman’s correlation coefficients were calculated to assess relationships between Doppler parameters (e.g., PCA-RI) and clinical variables (e.g., GCS, IOP). A two-tailed p-value of <0.05 was considered statistically significant. 3. Results Participant Characteristics and Clinical Assessment During the study period, 60 participants (30 in the Trauma group, 30 in the Control group) were successfully enrolled and completed all assessments. The demographic and baseline clinical characteristics of both groups are presented in Table 1 . There was no statistically significant difference in the mean age between the Trauma (36.6 ± 13.2 years) and Control groups (33.1 ± 5.2 years, p = 0.179). However, a significant difference in sex distribution was observed (χ²=7.18, p = 0.007), with a higher proportion of males in the Trauma group (80% vs. 46.7% in Controls). As expected, clinical markers of injury severity differed between groups. The mean IOP was significantly higher in the Trauma group compared to the Control group (14.4 ± 3.1 mmHg vs. 12.5 ± 1.4 mmHg, p = 0.003). While the mean GCS score was lower in the Trauma group (14.8 ± 0.6 vs. 15.0 ± 0.0), this difference approached but did not reach the conventional threshold for statistical significance in our cohort (p = 0.051, Fig. 2 ). Table 1 Demographic and Baseline Clinical Characteristics Characteristic Trauma Group (n = 30) Control Group (n = 30) p-value Age (years), Mean ± SD 36.6 ± 13.2 33.1 ± 5.2 0.179† Sex, n (%) 0.007 * Male 24 (80.0%) 14 (46.7%) Female 6 (20.0%) 16 (53.3%) GCS, Mean ± SD 14.8 ± 0.6 15.0 ± 0.0 0.051† IOP (mmHg), Mean ± SD 14.4 ± 3.1 12.5 ± 1.4 0.003 * SD: Standard Deviation; GCS: Glasgow Coma Scale; IOP: Intraocular Pressure. *† Independent samples t-test; χ² test. * Bold p-values indicate statistical significance (p < 0.05). Comparative Analysis of Retrobulbar Hemodynamics A detailed comparative analysis of retrobulbar hemodynamic parameters between the Trauma and Control groups revealed specific patterns of vascular alteration (Table 2 , Fig. 2 and Fig. 3 ). CRA Hemodynamics The CRA, which supplies the inner retinal layers, showed a significant increase in vascular resistance in the Trauma group. The CRA_RI was significantly higher in trauma patients (0.67 ± 0.07) compared to controls (0.64 ± 0.07, p = 0.042). While the CRA_PI also trended higher in the Trauma group (1.17 ± 0.24 vs. 1.06 ± 0.20), this difference approached but did not reach statistical significance (p = 0.056). No significant intergroup differences were observed in CRA_PSV) or EDV. SPCA Hemodynamics The most pronounced and statistically robust vascular changes were identified in the SPCA circulation, which supplies the optic nerve head and choroid. The Trauma group demonstrated a distinct high-resistance, low-flow profile: Reduced Perfusion: SPCA_PCV was significantly lower in the Trauma group (14.7 ± 4.1 cm/s) versus controls (18.7 ± 8.4 cm/s, p = 0.021). Increased Vascular Resistance: Concurrently, both indices of downstream resistance were markedly elevated. The SPCA_RI was significantly higher in trauma patients (0.65 ± 0.08 vs. 0.59 ± 0.06, p = 0.001). Similarly, the SPCA _PI was significantly increased (1.11 ± 0.26 vs. 0.95 ± 0.17, p = 0.005). OA Hemodynamics In contrast to the downstream CRA and PCA, the proximal OA did not show statistically significant alterations in its hemodynamic parameters between the two groups (all p > 0.05). Mean values for OA PSV, EDV, RI, and PI were comparable, suggesting that the primary vascular perturbation occurs distal to the OA, within the orbital circulation. Table 2 Retrobulbar Hemodynamic Parameters Measured by Color Doppler Sonography Vessel & Parameter Trauma Group (n = 30) Mean ± SD Control Group (n = 30) Mean ± SD p-value Ophthalmic Artery (OA) PSV (cm/s) 31.3 ± 7.9 29.3 ± 9.6 0.395 EDV (cm/s) 8.8 ± 3.3 8.4 ± 2.6 0.598 RI 0.69 ± 0.07 0.71 ± 0.06 0.261 PI 1.39 ± 0.29 1.51 ± 0.28 0.107 Central Retinal Artery (CRA) PSV (cm/s) 11.2 ± 2.8 12.1 ± 3.4 0.262 EDV (cm/s) 3.6 ± 1.2 3.7 ± 1.8 0.814 RI 0.67 ± 0.07 0.64 ± 0.07 0.042 * PI 1.17 ± 0.24 1.06 ± 0.20 0.056 Short Posterior Ciliary Artery (PCA) PSV/PCV (cm/s) 14.7 ± 4.1 18.7 ± 8.4 0.021 * EDV (cm/s) 5.3 ± 1.9 6.0 ± 3.1 0.329 RI 0.65 ± 0.08 0.59 ± 0.06 0.001 * PI 1.11 ± 0.26 0.95 ± 0.17 0.005 * PSV: Peak Systolic Velocity; EDV: End-Diastolic Velocity; RI: Resistance Index; PI: Pulsatility Index; PCV: Peak Conduit Velocity (synonymous with PSV for PCA). p-values derived from Independent samples t-test or Mann-Whitney U test as appropriate. Bold indicates a statistically significant difference (p < 0.05). Correlation Analyses Significant relationships between clinical parameters and retrobulbar hemodynamic indices were identified through Pearson correlation analysis (Table 3 ). Most notably, GCS score showed a significant negative correlation with the CRA_PI (r = -0.286, p = 0.027), indicating that patients with lower neurological scores exhibited higher arterial pulsatility in the retinal circulation. Within the retrobulbar vasculature, strong internal correlations were observed, validating measurement consistency. The CRA RI and PI were highly correlated (r = 0.911, p < 0.001), as were the equivalent SPCA parameters (r = 0.900, p < 0.001). Importantly, SPCA_PCV demonstrated significant negative correlations with both SPCA_RI (r = -0.290, p = 0.024) and PCA_PI (r = -0.274, p = 0.033), suggesting that reduced flow velocity in the SPCA circulation is associated with increased vascular resistance. Several ocular parameters also showed interrelated changes. IOP correlated positively with BCVA (r = 0.279, p = 0.031) and OA_PSV (r = 0.279, p = 0.031). Better visual acuity was associated with higher OA_PSV (r = 0.364, p = 0.004) and lower OA_RI (r = -0.260, p = 0.045). Table 3. Significant Correlations between Clinical Parameters and Retrobulbar Hemodynamic Indices (n=60) Hemodynamic Parameter 1 Hemodynamic Parameter 2 Pearson's r p-value Interpretation CRA Resistance Index (RI) CRA Pulsatility Index (PI) + 0.911 < 0.001 Strong consistency between resistance measures SPCA Resistance Index (RI) PCA Pulsatility Index (PI) + 0.900 < 0.001 Strong consistency between resistance measures SPCA Peak Velocity (PCV) PCA Resistance Index (RI) -0.290 0.024 Higher PCA flow → Lower resistance SPCA Peak Velocity (PCV) PCA Pulsatility Index (PI) -0.274 0.033 Higher PCA flow → Lower pulsatility Ophthalmic Artery RI Ophthalmic Artery PI + 0.836 < 0.001 Strong consistency between resistance measures Note on IOP-BCVA correlation: The positive correlation between IOP and BCVA appears counterintuitive and should be interpreted cautiously in the Discussion section. This may reflect the acute-phase physiological response rather than a pathological 4. Discussion This prospective case-control study provides compelling evidence that acute isolated mTBI induces specific and measurable alterations in retrobulbar hemodynamics [ 3 , 4 ]. Utilizing point-of-care CDI [ 9 ], we identified the SPCAs as the most sensitive vascular bed, exhibiting a significant increase in the RI and PI, alongside a reduction in PSV. These findings validate our hypothesis and introduce ocular vascular sonography as a novel, rapid, and non-invasive modality for detecting the acute cerebrovascular sequelae of mTBI. The pronounced vulnerability of the SPCA circulation is anatomically and physiologically grounded [ 7 , 10 ]. As highlighted in the review by Böhm et al., the SPCAs supply the optic nerve head and proximal choroid—watershed zones with high metabolic demand and limited collateral flow, rendering them exquisitely sensitive to perfusion deficits [ 10 ]. The observed hemodynamic signature—elevated RI and PI with reduced PSV—is classic for increased downstream vascular resistance. This suggests a state of vasoconstriction or impaired microvascular compliance, potentially driven by mechanisms central to mTBI pathophysiology [ 5 , 11 , 18 ]: (1) impaired cerebral autoregulation and vasospasm [ 12 ]; (2) transmission of altered intracranial dynamics along the optic nerve sheath [ 4 , 13 ]; or (3) a systemic inflammatory or catecholaminergic surge post-trauma [ 14 ]. The concurrent significant increase in CRA-RI further supports a diffuse microcirculatory disturbance within the eye, a direct embryological extension of the CNS [ 15 ]. Our results align with the long-recognized but under-investigated role of cerebral blood flow (CBF) disturbance in mTBI [ 6 , 21 ]. Previous research has highlighted that decreased CBF is associated with neurocognitive deficits and symptom severity, often detectable via advanced neuroimaging [ 21 ]. We posit that the observed SPCA hemodynamic alterations represent an orbital correlate of this CBF dysregulation [ 6 ]. While fMRI and arterial spin labeling measure CBF in the brain, CDI of retrobulbar vessels offers a practical, bedside surrogate for assessing this critical pathological axis [ 9 ]. The review by Böhm et al. underscores that CDI is a well-established, non-invasive tool for evaluating retrobulbar hemodynamics in various ocular and systemic diseases, including those with vascular dysregulation. The sparing of the larger, extracranial OA in our study underscores a gradient of effect, emphasizing that nutrient-terminal vessels like the SPCAs serve as more sensitive sentinels of mild cerebrovascular injury, consistent with the anatomical and autoregulatory distinctions noted in the literature [ 7 , 10 ]. The search for mTBI biomarkers has historically focused on molecules released due to blood-brain barrier (BBB) disruption or axonal injury [ 16 , 17 , 20 ]. Our study introduces a complementary paradigm: the detection of a functional vasculopathy. While biofluid biomarkers excel at identifying structural injury, they may not capture the earliest functional disturbances in perfusion that precede irreversible cellular damage [ 16 , 19 ]. The concept of using the eye as a "window to the brain" is well-established [ 15 ]; however, moving from structural to functional ocular assessment is a significant advance [ 3 , 4 ]. Our Doppler findings likely reflect a combination of mechanisms: autoregulatory failure as described in CBF studies [ 5 , 6 , 12 ], possibly compounded by subtle inflammatory-mediated vascular dysfunction [ 14 , 22 ]. This positions retrobulbar hemodynamics, particularly in the SPCAs, as a physiological biomarker that bridges the gap between molecular markers of injury and advanced imaging of function, fulfilling a need for dynamic, pathophysiologically informed assessment tools [ 19 , 24 ]. The significant negative correlation between GCS score and CRA-PI is clinically meaningful. It demonstrates that even within the narrow spectrum of GCS 13–15—where clinical differentiation is challenging—gradations in neurological status are reflected in the retinal microcirculation. This objective correlation addresses a core limitation of current mTBI assessment, which often relies on subjective symptom reporting [ 2 , 23 ]. Furthermore, the strong internal correlations and the physiologically plausible inverse relationship between SPCA flow and resistance validate our methodological rigor. The link between BCVA and higher OA_PSV offers a potential mechanistic explanation for common post-mTBI visual complaints, connecting vascular supply to functional outcome [ 2 , 3 ]. This aligns with the review's discussion on how altered retrobulbar flow is implicated in visual dysfunction across various pathologies [ 7 , 9 ]. We acknowledge important limitations. First, the significant sex imbalance between groups is a major confounder, necessitating caution in interpretation and highlighting the need for sex-matched future cohorts. Second, the cross-sectional design captures only the acute phase (< 24 hours). The critical question of temporal evolution remains: Do these hemodynamic changes normalize with clinical recovery, or do they persist in patients developing post-concussive syndrome, potentially serving as a prognostic biomarker? Longitudinal studies are essential [ 21 , 22 ]. Third, while CDI is a validated method [ 9 ], the review by Böhm et al. notes that parameters like RI can be influenced by various factors including vascular compliance and systemic hemodynamics. Future studies should incorporate simultaneous systemic blood pressure monitoring to better interpret resistance indices. Looking forward, the integration of multi-modal biomarkers is the stated future of mTBI management [ 19 , 24 ]. Our tool fits seamlessly into this framework. Future research must pursue: Longitudinal Validation: Tracking SPCA parameters alongside symptom resolution and cognitive testing [ 21 , 22 ]. Multi-Modal Correlation: Combining CDI with serum biomarkers (GFAP, UCH-L1) [ 20 , 22 ] and advanced MRI (DTI, ASL) [ 6 , 21 ] to define patient endophenotypes. Prognostic Studies: Investigating whether acute SPCA alterations predict prolonged recovery or risk of post-concussive syndrome [ 2 , 23 ]. Technical Refinement: Exploring automated Doppler analysis to improve accessibility and reproducibility, addressing known CDI limitations such as angle dependency [ 9 ]. Conclusion In conclusion, this study identifies altered SPCA hemodynamics as a novel physiological biomarker for acute mTBI, measurable via rapid, bedside Color Doppler Imaging [ 9 ]. This expands the mTBI biomarker landscape from static molecular indicators of injury [ 16 , 17 , 20 ] to include a dynamic, functional assessment of cerebrovascular dysregulation [ 5 , 6 , 18 ], as supported by the established role of retrobulbar flow assessment in neurovascular diseases [ 7 , 10 ]. As the field advances toward precision medicine through multimodal biomarker integration [ 19 , 24 ], CDI of the retrobulbar circulation offers a unique, accessible, and physiologically grounded tool. With further validation, it holds promise for improving acute diagnostic accuracy, elucidating patient-specific pathophysiology, and guiding personalized management and recovery timelines. Declarations Author contributions Abbas M. conceived and designed the study, collected and analyzed the data, interpreted the results, and drafted the manuscript. Mohammad J., Seyed Ali T., and shadi KH. A contributed to data analysis, manuscript drafting, and provided critical revisions to the research paper. Alireza R., Kosar Ch., and Ali A assisted in data interpretation and manuscript preparation. Ali D,. and Meisam M , chaired the data oversight committee. All authors reviewed, edited, and approved the final version of the manuscript. Funding This research did not receive any specific grant from fund agencies. Data availability The data and other documents used in this study are available from the corresponding author. Declarations Competing interests The authors declare no competing interests. Conflict of interest All authors confirmed that they have no conflict of interest. Ethical approval Prior to initiating the study, ethical approval was obtained from the Institutional Review Board (IRB) of Golestan Hospital in Ahvaz, Iran (Approval No.: IR.AJUMS.HGOLESTAN.REC.1404.083). Before participation, all individuals were provided with a written informed consent form. 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J Neurotrauma. 2024;41(7-8):862-878. doi:10.1089/neu.2023.0419 McCrory P, Meeuwisse W, Dvořák J, et al. Consensus statement on concussion in sport-the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838-847. doi:10.1136/bjsports-2017-097699 National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Care Services; Board on Health Sciences Policy; Committee on Accelerating Progress in Traumatic Brain Injury Research and Care, Matney C, Bowman K, Berwick D, eds. Traumatic Brain Injury: A Roadmap for Accelerating Progress. Washington (DC): National Academies Press (US); February 1, 2022. Additional Declarations No competing interests reported. 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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-8533634","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585465516,"identity":"07438a09-d60f-4d66-93f6-8d5945a80c51","order_by":0,"name":"Abbas Mohammadi","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abbas","middleName":"","lastName":"Mohammadi","suffix":""},{"id":585465517,"identity":"a3d0ba72-2b02-4799-9b81-56f9fccd65c2","order_by":1,"name":"Mohammad Jorfi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBAC9gYGhg8JDDbM/CBeQgERWhgbGBhnJDCksUs2gLQYEKuFgeEQv8EBEJcoLe29Dxse5hyQNj6/OvHDAwMGeX6xAwS09Bw3bEjcdsfY7MbbzRJAhxnOnJ1AQMuMNPYHidueJZvdOLsBpCXB4DZhLYxAWw7Xb55xdvMPorQIQrUwG/D3biPOFmmeYyAtacwSN3i3WSQYSBD2Cx97G2Pjz23AqOw/u/nmjwobeX5pAloQQAKsUoJY5SDAf4AU1aNgFIyCUTCSAAD0lkegZebSHgAAAABJRU5ErkJggg==","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Jorfi","suffix":""},{"id":585465518,"identity":"c303d39b-6aaa-45e2-b308-472b6ffcc407","order_by":2,"name":"Seyed Ali Tabatabaei","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Ali","lastName":"Tabatabaei","suffix":""},{"id":585465519,"identity":"0d09cce0-fad0-4c53-a2cb-4df9dfa77580","order_by":3,"name":"Shadi Khosravan","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shadi","middleName":"","lastName":"Khosravan","suffix":""},{"id":585465520,"identity":"95c36f44-eca4-4d9c-88e8-b086e089bd3c","order_by":4,"name":"Alireza Rahimifar","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Rahimifar","suffix":""},{"id":585465521,"identity":"2a3075b5-5881-4be7-b3d8-ce045145d71e","order_by":5,"name":"Kosar Chitzan-Zadeh","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kosar","middleName":"","lastName":"Chitzan-Zadeh","suffix":""},{"id":585465522,"identity":"0225673e-901f-40e8-bc65-1151dbee5e58","order_by":6,"name":"Ali Delirrooy fard","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Delirrooy","lastName":"fard","suffix":""},{"id":585465523,"identity":"01f07556-9e4f-414a-be2d-f9026c035609","order_by":7,"name":"Meisam Moezzi","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Meisam","middleName":"","lastName":"Moezzi","suffix":""},{"id":585465524,"identity":"15d2bc85-4348-4e07-9252-bd3f9c0f5934","order_by":8,"name":"Ali Ansari","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Ansari","suffix":""}],"badges":[],"createdAt":"2026-01-06 16:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8533634/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8533634/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102209895,"identity":"23067ea7-dc5a-4356-92f1-b55726b149f8","added_by":"auto","created_at":"2026-02-09 12:14:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":355483,"visible":true,"origin":"","legend":"\u003cp\u003eColor Doppler sonogrphy of Short posterior ciliary artery(SPCA).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8533634/v1/1a61d4946cd1d28a761b5c3e.png"},{"id":102209894,"identity":"3be83b51-d9df-489e-9c20-cfb4b6f9d561","added_by":"auto","created_at":"2026-02-09 12:14:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98551,"visible":true,"origin":"","legend":"\u003cp\u003eThe Glasgow Coma Scale (GCS) and Intraocular pressure (IOP) between the trauma and control group\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8533634/v1/bc3cdf44ceafa0e562894941.png"},{"id":102297443,"identity":"2d48d868-5fab-4e4c-aa30-b87b6268f3c0","added_by":"auto","created_at":"2026-02-10 10:27:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":142241,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical Representation of Key Hemodynamic Differences\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8533634/v1/994970fddb9e2e3269ae5532.png"},{"id":102300500,"identity":"996cd24d-49cd-4a1f-a946-34642227a28d","added_by":"auto","created_at":"2026-02-10 11:14:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1462857,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8533634/v1/94ee5e8e-cd71-415c-b9c4-7dddb636e95b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Altered Short Posterior Ciliary Artery Hemodynamics on Point-of-Care Doppler Imaging: A Novel Biomarker in Acute Mild Traumatic Brain Injury","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTraumatic brain injury (TBI) constitutes a major global public health burden, representing a leading cause of mortality and long-term disability worldwide [1]. While initial management focuses on stabilizing life-threatening intracranial pathology, a significant subset of patients, even those presenting with mild TBI(mTBI) (Glasgow Coma Scale [GCS] 13-15), develop persistent and debilitating visual and neurological sequelae that severely impact quality of life [2]. This highlights a critical need for early, sensitive prognostic tools that can identify patients at risk for secondary complications beyond standard neuroimaging.\u003c/p\u003e\n\u003cp\u003eThe eye, as an embryological extension of the central nervous system, offers a unique and accessible window into cerebral pathophysiology. Following TBI, structural ocular changes such as retinal nerve fiber layer thinning and optic nerve sheath diameter (ONSD) expansion have been documented and correlate with intracranial pressure and outcome [3, 4]. Robba et al. demonstrated that ONSD ultrasonography at admission is a reliable predictor of intracranial hypertension and mortality, validating the concept of using ocular parameters for neuromonitoring [4]. However, while these structural assessments are informative, they may not capture the earliest functional disturbances in microvascular perfusion that precede permanent anatomical damage.\u003c/p\u003e\n\u003cp\u003eCerebrovascular dysregulation, including impaired autoregulation and changes in cerebral blood flow, is a well-recognized secondary insult following TBI and is strongly linked to poor outcomes [5, 6]. By extension, the vascular supply to the eye—particularly the retrobulbar circulation comprising the ophthalmic, central retinal (CRA), and Short posterior ciliary arteries (SPCA)—is also vulnerable. The SPCA is especially critical as it supplies the optic nerve head and choroid. Compromise of this circulation through vasospasm, increased intracranial pressure transmitted along the optic nerve sheath, or systemic inflammatory responses could lead to ischemic optic neuropathy and irreversible visual loss [7, 8]. Despite this plausible mechanism, the real-time, in vivo assessment of retrobulbar hemodynamics in the acute phase of TBI remains largely unexplored.\u003c/p\u003e\n\u003cp\u003ePoint-of-care Color Doppler Imaging (CDI) is a rapid, non-invasive, and readily available bedside technology capable of quantifying blood flow velocities and vascular resistance indices. It has been successfully used to evaluate orbital vascular disorders but has not been systematically integrated into the early assessment of TBI [9]. We hypothesize that acute blunt head trauma induces immediate and measurable hemodynamic alterations in the retrobulbar circulation, characterized by increased vascular resistance and reduced flow velocities, and that the magnitude of these changes correlates with clinical injury severity.\u003c/p\u003e\n\u003cp\u003eTherefore, this prospective case-control study aimed to: 1) Compare the retrobulbar hemodynamic parameters (Peak Systolic Velocity [PSV], End-Diastolic Velocity [EDV], Resistance Index [RI], and Pulsatility Index [PI]) of patients with acute isolated blunt head trauma to matched healthy controls using point-of-care Color Doppler sonography, and 2) Correlate these vascular parameters with established clinical indices of injury severity, including GCS and intraocular pressure (IOP). This research seeks to establish the foundation for using ocular vascular sonography as a complementary prognostic tool in the acute management of TBI.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cem\u003e2.1. Study Design and Setting\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis prospective case-control study was conducted at the Golestan Hospital, a major tertiary trauma referral center in Ahvaz, southern Iran. The study was performed between June 2022 and June 2025. The hospital\u0026rsquo;s emergency department provides care for a high volume of neurotrauma cases from across the Khuzestan province. The study protocol was reviewed and approved by the Institutional Review Board (IRB) and Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (Ethical Code: IR.AJUMS.REC.1404.129). The study adhered to the principles of the Declaration of Helsinki and Good Clinical Practice guidelines. \u0026nbsp;Written informed consent was obtained from all control participants and from the legally authorized representatives of patients in the trauma group prior to enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. Participants\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 60 adult participants were enrolled and divided into two groups.\u003c/p\u003e\n\u003cp\u003eTrauma Group: Thirty consecutive adult patients (aged 18-65 years) presenting to the emergency department with an acute, isolated blunt head trauma within the preceding 24 hours were included. Injury was defined as \u0026quot;isolated\u0026quot; based on an Abbreviated Injury Scale (AIS) score of \u0026ge;1 for the head region and 0 for all other body parts. To focus on mild to moderate injury, an initial GCS score between 13 and 15 was required.\u003c/p\u003e\n\u003cp\u003eControl Group: Thirty age- and sex-matched healthy volunteers with no history of head trauma, ocular disease, or major systemic illness (e.g., uncontrolled hypertension, diabetes) were recruited.\u003c/p\u003e\n\u003cp\u003eExclusion Criteria for both groups were: a history of prior ocular surgery or significant ocular pathology (e.g., glaucoma, retinal vascular occlusion), penetrating ocular injury, refractive error greater than \u0026plusmn;6 diopters, inability to cooperate for the sonographic examination, or any contraindication to orbital ultrasound.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3. Clinical Assessment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUpon presentation, trauma patients underwent a standardized evaluation:\u003c/p\u003e\n\u003cp\u003eNeurological Assessment: The GCS score was recorded by the attending emergency physician.\u003c/p\u003e\n\u003cp\u003eOphthalmic Examination: IOP was measured in both eyes using a calibrated handheld tonometer (e.g., Tono-Pen). Best-corrected visual acuity (BCVA) was assessed using a Snellen chart at 6 meters.\u003c/p\u003e\n\u003cp\u003eNeuroimaging: All trauma patients underwent non-contrast computed tomography (CT) of the brain as per standard trauma protocol to confirm the diagnosis, rule out surgical lesions, and allow for anatomical injury scoring.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4. Color Doppler Sonography Protocol\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRetrobulbar hemodynamic assessment was performed for all participants within 2 hours of clinical evaluation. A single experienced radiologist, blinded to the patient\u0026rsquo;s group assignment, performed all scans using a high-resolution ultrasound system (Philips EPIQ 7G) equipped with a high-frequency linear array transducer (5-12 MHz). Patients were examined in a supine position with eyes gently closed. The probe was placed on the closed upper eyelid using copious coupling gel, ensuring no pressure was applied to the globe. Using B-mode for anatomical guidance, the Color Doppler function was activated to identify the target vessels. Pulsed-wave Doppler spectral analysis was then performed with the sample gate set to 1-2 mm [figure 1] . The following arteries were examined in each eye, and measurements were averaged from three consecutive cardiac cycles:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eOA: Sampled at a depth of 25-35 mm posterior to the globe.\u003c/li\u003e\n \u003cli\u003eCRA: Identified within the optic nerve shadow, approximately 10-15 mm behind the lamina cribrosa.\u003c/li\u003e\n \u003cli\u003eSPCA: Sampled as they entered the globe medial and lateral to the optic nerve.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe following hemodynamic parameters were recorded for each vessel:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePSV; cm/s\u003c/li\u003e\n \u003cli\u003eEDV; cm/s\u003c/li\u003e\n \u003cli\u003eRI, calculated as (PSV \u0026ndash; EDV) / PSV\u003c/li\u003e\n \u003cli\u003ePI, calculated as (PSV \u0026ndash; EDV) / Mean Velocity\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003e2.5. Statistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using IBM SPSS Statistics for Windows, Version 26.0. Descriptive data are presented as mean \u0026plusmn; standard deviation (SD) for normally distributed variables or median (interquartile range) for non-normal variables. Categorical variables are presented as frequencies (percentages). Group Comparisons: Independent samples t-test or Mann-Whitney U test was used for continuous variables, as appropriate. The Chi-square test was used for categorical variables (e.g., sex). Analysis of Hemodynamic Parameters: A General Linear Model (GLM) was employed to compare Doppler parameters between the Trauma and Control groups, with the potential to include covariates (e.g., age, IOP). Correlation Analysis: Pearson\u0026rsquo;s or Spearman\u0026rsquo;s correlation coefficients were calculated to assess relationships between Doppler parameters (e.g., PCA-RI) and clinical variables (e.g., GCS, IOP). A two-tailed p-value of \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipant Characteristics and Clinical Assessment\u003c/h2\u003e\n \u003cp\u003eDuring the study period, 60 participants (30 in the Trauma group, 30 in the Control group) were successfully enrolled and completed all assessments. The demographic and baseline clinical characteristics of both groups are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThere was no statistically significant difference in the mean age between the Trauma (36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2 years) and Control groups (33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 years, p\u0026thinsp;=\u0026thinsp;0.179). However, a significant difference in sex distribution was observed (\u0026chi;\u0026sup2;=7.18, p\u0026thinsp;=\u0026thinsp;0.007), with a higher proportion of males in the Trauma group (80% vs. 46.7% in Controls).\u003c/p\u003e\n \u003cp\u003eAs expected, clinical markers of injury severity differed between groups. The mean IOP was significantly higher in the Trauma group compared to the Control group (14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mmHg vs. 12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 mmHg, p\u0026thinsp;=\u0026thinsp;0.003). While the mean GCS score was lower in the Trauma group (14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 vs. 15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0), this difference approached but did not reach the conventional threshold for statistical significance in our cohort (p\u0026thinsp;=\u0026thinsp;0.051, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and Baseline Clinical Characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTrauma Group (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.179\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGCS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.051\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIOP (mmHg), Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003eSD: Standard Deviation; GCS: Glasgow Coma Scale; IOP: Intraocular Pressure.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e*\u0026dagger; Independent samples t-test; \u003cem\u003e\u0026chi;\u0026sup2; test.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e*\u003cstrong\u003eBold p-values indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eComparative Analysis of Retrobulbar Hemodynamics\u003c/h3\u003e\n\u003cp\u003eA detailed comparative analysis of retrobulbar hemodynamic parameters between the Trauma and Control groups revealed specific patterns of vascular alteration (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eCRA Hemodynamics\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe CRA, which supplies the inner retinal layers, showed a significant increase in vascular resistance in the Trauma group. The CRA_RI was significantly higher in trauma patients (0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07) compared to controls (0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07, p\u0026thinsp;=\u0026thinsp;0.042). While the CRA_PI also trended higher in the Trauma group (1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24 vs. 1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20), this difference approached but did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.056). No significant intergroup differences were observed in CRA_PSV) or EDV.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eSPCA Hemodynamics\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe most pronounced and statistically robust vascular changes were identified in the SPCA circulation, which supplies the optic nerve head and choroid. The Trauma group demonstrated a distinct high-resistance, low-flow profile:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eReduced Perfusion: SPCA_PCV was significantly lower in the Trauma group (14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 cm/s) versus controls (18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4 cm/s, p\u0026thinsp;=\u0026thinsp;0.021).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eIncreased Vascular Resistance: Concurrently, both indices of downstream resistance were markedly elevated. The SPCA_RI was significantly higher in trauma patients (0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 vs. 0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06, p\u0026thinsp;=\u0026thinsp;0.001). Similarly, the SPCA _PI was significantly increased (1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 vs. 0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17, p\u0026thinsp;=\u0026thinsp;0.005).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eOA Hemodynamics\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIn contrast to the downstream CRA and PCA, the proximal OA did not show statistically significant alterations in its hemodynamic parameters between the two groups (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Mean values for OA PSV, EDV, RI, and PI were comparable, suggesting that the primary vascular perturbation occurs distal to the OA, within the orbital circulation.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRetrobulbar Hemodynamic Parameters Measured by Color Doppler Sonography\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVessel \u0026amp; Parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTrauma Group (n\u0026thinsp;=\u0026thinsp;30) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;30) Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOphthalmic Artery (OA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEDV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Retinal Artery (CRA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEDV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.042\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShort Posterior Ciliary Artery (PCA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePSV/PCV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEDV (cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ePSV: Peak Systolic Velocity; EDV: End-Diastolic Velocity; RI: Resistance Index; PI: Pulsatility Index; PCV: Peak Conduit Velocity (synonymous with PSV for PCA).\u003c/p\u003e\n\u003cp\u003ep-values derived from Independent samples t-test or Mann-Whitney U test as appropriate.\u003c/p\u003e\n\u003cp\u003eBold indicates a statistically significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eCorrelation Analyses\u003c/h3\u003e\n\u003cp\u003eSignificant relationships between clinical parameters and retrobulbar hemodynamic indices were identified through Pearson correlation analysis (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Most notably, GCS score showed a significant negative correlation with the CRA_PI (r = -0.286, p\u0026thinsp;=\u0026thinsp;0.027), indicating that patients with lower neurological scores exhibited higher arterial pulsatility in the retinal circulation.\u003c/p\u003e\n\u003cp\u003eWithin the retrobulbar vasculature, strong internal correlations were observed, validating measurement consistency. The CRA RI and PI were highly correlated (r\u0026thinsp;=\u0026thinsp;0.911, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as were the equivalent SPCA parameters (r\u0026thinsp;=\u0026thinsp;0.900, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Importantly, SPCA_PCV demonstrated significant negative correlations with both SPCA_RI (r = -0.290, p\u0026thinsp;=\u0026thinsp;0.024) and PCA_PI (r = -0.274, p\u0026thinsp;=\u0026thinsp;0.033), suggesting that reduced flow velocity in the SPCA circulation is associated with increased vascular resistance.\u003c/p\u003e\n\u003cp\u003eSeveral ocular parameters also showed interrelated changes. IOP correlated positively with BCVA (r\u0026thinsp;=\u0026thinsp;0.279, p\u0026thinsp;=\u0026thinsp;0.031) and OA_PSV (r\u0026thinsp;=\u0026thinsp;0.279, p\u0026thinsp;=\u0026thinsp;0.031). Better visual acuity was associated with higher OA_PSV (r\u0026thinsp;=\u0026thinsp;0.364, p\u0026thinsp;=\u0026thinsp;0.004) and lower OA_RI (r = -0.260, p\u0026thinsp;=\u0026thinsp;0.045).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003cbr\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\u003c/table\u003eTable 3. Significant Correlations between Clinical Parameters and Retrobulbar Hemodynamic Indices (n=60)\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHemodynamic Parameter 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHemodynamic Parameter 2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePearson\u0026apos;s r\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInterpretation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRA Resistance Index (RI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRA Pulsatility Index (PI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e+\u0026thinsp;0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStrong consistency between resistance measures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSPCA Resistance Index (RI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCA Pulsatility Index (PI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e+\u0026thinsp;0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStrong consistency between resistance measures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSPCA Peak Velocity (PCV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCA Resistance Index (RI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigher PCA flow \u0026rarr; Lower resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSPCA Peak Velocity (PCV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCA Pulsatility Index (PI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigher PCA flow \u0026rarr; Lower pulsatility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOphthalmic Artery RI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOphthalmic Artery PI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e+\u0026thinsp;0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStrong consistency between resistance measures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote on IOP-BCVA correlation: The positive correlation between IOP and BCVA appears counterintuitive and should be interpreted cautiously in the Discussion section. This may reflect the acute-phase physiological response rather than a pathological\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis prospective case-control study provides compelling evidence that acute isolated mTBI induces specific and measurable alterations in retrobulbar hemodynamics [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Utilizing point-of-care CDI [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], we identified the SPCAs as the most sensitive vascular bed, exhibiting a significant increase in the RI and PI, alongside a reduction in PSV. These findings validate our hypothesis and introduce ocular vascular sonography as a novel, rapid, and non-invasive modality for detecting the acute cerebrovascular sequelae of mTBI.\u003c/p\u003e \u003cp\u003eThe pronounced vulnerability of the SPCA circulation is anatomically and physiologically grounded [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As highlighted in the review by B\u0026ouml;hm et al., the SPCAs supply the optic nerve head and proximal choroid\u0026mdash;watershed zones with high metabolic demand and limited collateral flow, rendering them exquisitely sensitive to perfusion deficits [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The observed hemodynamic signature\u0026mdash;elevated RI and PI with reduced PSV\u0026mdash;is classic for increased downstream vascular resistance. This suggests a state of vasoconstriction or impaired microvascular compliance, potentially driven by mechanisms central to mTBI pathophysiology [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]: (1) impaired cerebral autoregulation and vasospasm [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]; (2) transmission of altered intracranial dynamics along the optic nerve sheath [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]; or (3) a systemic inflammatory or catecholaminergic surge post-trauma [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The concurrent significant increase in CRA-RI further supports a diffuse microcirculatory disturbance within the eye, a direct embryological extension of the CNS [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur results align with the long-recognized but under-investigated role of cerebral blood flow (CBF) disturbance in mTBI [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Previous research has highlighted that decreased CBF is associated with neurocognitive deficits and symptom severity, often detectable via advanced neuroimaging [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. We posit that the observed SPCA hemodynamic alterations represent an orbital correlate of this CBF dysregulation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While fMRI and arterial spin labeling measure CBF in the brain, CDI of retrobulbar vessels offers a practical, bedside surrogate for assessing this critical pathological axis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The review by B\u0026ouml;hm et al. underscores that CDI is a well-established, non-invasive tool for evaluating retrobulbar hemodynamics in various ocular and systemic diseases, including those with vascular dysregulation. The sparing of the larger, extracranial OA in our study underscores a gradient of effect, emphasizing that nutrient-terminal vessels like the SPCAs serve as more sensitive sentinels of mild cerebrovascular injury, consistent with the anatomical and autoregulatory distinctions noted in the literature [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe search for mTBI biomarkers has historically focused on molecules released due to blood-brain barrier (BBB) disruption or axonal injury [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our study introduces a complementary paradigm: the detection of a functional vasculopathy. While biofluid biomarkers excel at identifying structural injury, they may not capture the earliest functional disturbances in perfusion that precede irreversible cellular damage [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The concept of using the eye as a \"window to the brain\" is well-established [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; however, moving from structural to functional ocular assessment is a significant advance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Our Doppler findings likely reflect a combination of mechanisms: autoregulatory failure as described in CBF studies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], possibly compounded by subtle inflammatory-mediated vascular dysfunction [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This positions retrobulbar hemodynamics, particularly in the SPCAs, as a physiological biomarker that bridges the gap between molecular markers of injury and advanced imaging of function, fulfilling a need for dynamic, pathophysiologically informed assessment tools [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe significant negative correlation between GCS score and CRA-PI is clinically meaningful. It demonstrates that even within the narrow spectrum of GCS 13\u0026ndash;15\u0026mdash;where clinical differentiation is challenging\u0026mdash;gradations in neurological status are reflected in the retinal microcirculation. This objective correlation addresses a core limitation of current mTBI assessment, which often relies on subjective symptom reporting [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, the strong internal correlations and the physiologically plausible inverse relationship between SPCA flow and resistance validate our methodological rigor. The link between BCVA and higher OA_PSV offers a potential mechanistic explanation for common post-mTBI visual complaints, connecting vascular supply to functional outcome [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This aligns with the review's discussion on how altered retrobulbar flow is implicated in visual dysfunction across various pathologies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe acknowledge important limitations. First, the significant sex imbalance between groups is a major confounder, necessitating caution in interpretation and highlighting the need for sex-matched future cohorts. Second, the cross-sectional design captures only the acute phase (\u0026lt;\u0026thinsp;24 hours). The critical question of temporal evolution remains: Do these hemodynamic changes normalize with clinical recovery, or do they persist in patients developing post-concussive syndrome, potentially serving as a prognostic biomarker? Longitudinal studies are essential [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Third, while CDI is a validated method [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the review by B\u0026ouml;hm et al. notes that parameters like RI can be influenced by various factors including vascular compliance and systemic hemodynamics. Future studies should incorporate simultaneous systemic blood pressure monitoring to better interpret resistance indices.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eLooking forward, the integration of multi-modal biomarkers is the stated future of mTBI management [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our tool fits seamlessly into this framework. Future research must pursue:\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLongitudinal Validation: Tracking SPCA parameters alongside symptom resolution and cognitive testing [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMulti-Modal Correlation: Combining CDI with serum biomarkers (GFAP, UCH-L1) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and advanced MRI (DTI, ASL) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] to define patient endophenotypes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePrognostic Studies: Investigating whether acute SPCA alterations predict prolonged recovery or risk of post-concussive syndrome [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTechnical Refinement: Exploring automated Doppler analysis to improve accessibility and reproducibility, addressing known CDI limitations such as angle dependency [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study identifies altered SPCA hemodynamics as a novel physiological biomarker for acute mTBI, measurable via rapid, bedside Color Doppler Imaging [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This expands the mTBI biomarker landscape from static molecular indicators of injury [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] to include a dynamic, functional assessment of cerebrovascular dysregulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], as supported by the established role of retrobulbar flow assessment in neurovascular diseases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As the field advances toward precision medicine through multimodal biomarker integration [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], CDI of the retrobulbar circulation offers a unique, accessible, and physiologically grounded tool. With further validation, it holds promise for improving acute diagnostic accuracy, elucidating patient-specific pathophysiology, and guiding personalized management and recovery timelines.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbas M. conceived and designed the study, collected and analyzed the data, interpreted the results, and drafted the manuscript. Mohammad J., Seyed Ali T., and shadi KH. A contributed to data analysis, manuscript drafting, and provided critical revisions to the research paper. Alireza R., Kosar Ch., and Ali A assisted in data interpretation and manuscript preparation. Ali D,. and Meisam M , chaired the data oversight committee. All authors reviewed, edited, and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from fund agencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and other documents used in this study are available from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors confirmed that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrior to initiating the study, ethical approval was obtained from the Institutional Review Board (IRB) of Golestan Hospital in Ahvaz, Iran (Approval No.: IR.AJUMS.HGOLESTAN.REC.1404.083). Before participation, all individuals were provided with a written informed consent form. This document emphasized the confidentiality and anonymity of their responses and explicitly stated their right to withdraw from the study at any point without consequence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent prior to their inclusion in the study, and a Consent to Participate declaration has been documented.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):56-87. doi:10.1016/S1474-4422(18)30415-0\u003c/li\u003e\n\u003cli\u003eMcMahon P, Hricik A, Yue JK, et al. Symptomatology and functional outcome in mild traumatic brain injury: results from the prospective TRACK-TBI study. J Neurotrauma. 2014;31(1):26-33. doi:10.1089/neu.2013.2984\u003c/li\u003e\n\u003cli\u003eMufti O, Mathew S, Harris A, Siesky B, Burgett KM, Verticchio Vercellin AC. Ocular changes in traumatic brain injury: A review. Eur J Ophthalmol. 2020;30(5):867-873. doi:10.1177/1120672119866974\u003c/li\u003e\n\u003cli\u003eRobba C, Donnelly J, Cardim D, et al. Optic nerve sheath diameter ultrasonography at admission as a predictor of intracranial hypertension in traumatic brain injured patients: a prospective observational study. J Neurosurg. 2019;132(4):1279-1285. Published 2019 Mar 8. doi:10.3171/2018.11.JNS182077\u003c/li\u003e\n\u003cli\u003eCzosnyka M, Smielewski P, Kirkpatrick P, Laing RJ, Menon D, Pickard JD. Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery. 1997;41(1):11-19. doi:10.1097/00006123-199707000-00005\u003c/li\u003e\n\u003cli\u003ePonto LL, Brashers-Krug TM, Pierson RK, et al. Preliminary Investigation of Cerebral Blood Flow and Amyloid Burden in Veterans With and Without Combat-Related Traumatic Brain Injury. J Neuropsychiatry Clin Neurosci. 2016;28(2):89-96. doi:10.1176/appi.neuropsych.15050106\u003c/li\u003e\n\u003cli\u003eHayreh SS. Posterior ciliary artery circulation in health and disease: the Weisenfeld lecture. Invest Ophthalmol Vis Sci. 2004;45(3):749-748. doi:10.1167/iovs.03-0469\u003c/li\u003e\n\u003cli\u003eSadun AA. The optic neuropathy of head trauma. J Neuroophthalmol. 2012;32(1):91-92. doi:10.1097/WNO.0b013e318244e4f7.\u003c/li\u003e\n\u003cli\u003eSergott RC, Aburn NS, Trible JR, Costa VP, Lieb WE Jr, Flaharty PM. Color Doppler imaging: methodology and preliminary results in glaucoma. Surv Ophthalmol. 1994;38 Suppl:S65-S71. doi:10.1016/0039-6257(94)90048-5\u003c/li\u003e\n\u003cli\u003eHayreh SS. The blood supply of the optic nerve head and the evaluation of it - myth and reality. Prog Retin Eye Res. 2001;20(5):563-593. doi:10.1016/s1350-9462(01)00004-0\u003c/li\u003e\n\u003cli\u003eDeWitt DS, Prough DS. Traumatic cerebral vascular injury: the effects of concussive brain injury on the cerebral vasculature. J Neurotrauma. 2003;20(9):795-825. doi:10.1089/089771503322385755\u003c/li\u003e\n\u003cli\u003eJ\u0026uuml;nger EC, Newell DW, Grant GA, et al. Cerebral autoregulation following minor head injury. J Neurosurg. 1997;86(3):425-432. doi:10.3171/jns.1997.86.3.0425\u003c/li\u003e\n\u003cli\u003eRobba C, Santori G, Czosnyka M, et al. Optic nerve sheath diameter measured sonographically as non-invasive estimator of intracranial pressure: a systematic review and meta-analysis. Intensive Care Med. 2018;44(8):1284-1294. doi:10.1007/s00134-018-5305-7\u003c/li\u003e\n\u003cli\u003eGill J, Motamedi V, Osier N, et al. Moderate blast exposure results in increased IL-6 and TNF\u0026alpha; in peripheral blood. Brain Behav Immun. 2017;65:90-94. doi:10.1016/j.bbi.2017.02.015\u003c/li\u003e\n\u003cli\u003eLondon A, Benhar I, Schwartz M. The retina as a window to the brain-from eye research to CNS disorders. Nat Rev Neurol. 2013;9(1):44-53. doi:10.1038/nrneurol.2012.227\u003c/li\u003e\n\u003cli\u003eKim HJ, Tsao JW, Stanfill AG. The current state of biomarkers of mild traumatic brain injury. JCI Insight. 2018;3(1):e97105. Published 2018 Jan 11. doi:10.1172/jci.insight.97105\u003c/li\u003e\n\u003cli\u003eZetterberg H, Blennow K. Fluid biomarkers for mild traumatic brain injury and related conditions. Nat Rev Neurol. 2016;12(10):563-574. doi:10.1038/nrneurol.2016.127\u003c/li\u003e\n\u003cli\u003eGiza CC, Hovda DA. The new neurometabolic cascade of concussion. Neurosurgery. 2014;75 Suppl 4(0 4):S24-S33. doi:10.1227/NEU.0000000000000505\u003c/li\u003e\n\u003cli\u003eBeard K, Gauff AK, Pennington AM, Marion DW, Smith J, Sloley S. Biofluid, Imaging, Physiological, and Functional Biomarkers of Mild Traumatic Brain Injury and Subconcussive Head Impacts. J Neurotrauma. 2025;42(17-18):1601-1620. doi:10.1089/neu.2024.0136\u003c/li\u003e\n\u003cli\u003eBazarian JJ, Biberthaler P, Welch RD, et al. Serum GFAP and UCH-L1 for prediction of absence of intracranial injuries on head CT (ALERT-TBI): a multicentre observational study. Lancet Neurol. 2018;17(9):782-789. doi:10.1016/S1474-4422(18)30231-X\u003c/li\u003e\n\u003cli\u003eMeier TB, Bellgowan PS, Singh R, Kuplicki R, Polanski DW, Mayer AR. Recovery of cerebral blood flow following sports-related concussion. JAMA Neurol. 2015;72(5):530-538. doi:10.1001/jamaneurol.2014.4778\u003c/li\u003e\n\u003cli\u003eClarke GJB, Skandsen T, Zetterberg H, et al. Longitudinal Associations Between Persistent Post-Concussion Symptoms and Blood Biomarkers of Inflammation and CNS-Injury After Mild Traumatic Brain Injury. J Neurotrauma. 2024;41(7-8):862-878. doi:10.1089/neu.2023.0419\u003c/li\u003e\n\u003cli\u003eMcCrory P, Meeuwisse W, Dvoř\u0026aacute;k J, et al. Consensus statement on concussion in sport-the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838-847. doi:10.1136/bjsports-2017-097699\u003c/li\u003e\n\u003cli\u003eNational Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Care Services; Board on Health Sciences Policy; Committee on Accelerating Progress in Traumatic Brain Injury Research and Care, Matney C, Bowman K, Berwick D, eds. Traumatic Brain Injury: A Roadmap for Accelerating Progress. Washington (DC): National Academies Press (US); February 1, 2022.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mild traumatic brain injury, biomarker, color Doppler imaging, short posterior ciliary artery, cerebrovascular dysregulation, hemodynamics, point-of-care ultrasound","lastPublishedDoi":"10.21203/rs.3.rs-8533634/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8533634/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMild traumatic brain injury (mTBI) lacks sensitive biomarkers for acute cerebrovascular dysregulation. The short posterior ciliary arteries (SPCA), as part of the cerebral circulation, offer a potential window into this pathophysiology via transorbital sonography.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to evaluate SPCA hemodynamics using point-of-care Color Doppler Imaging (CDI) as a novel functional biomarker in acute mTBI.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this prospective case-control study, thirty adults with acute, isolated mTBI (GCS 13\u0026ndash;15) and thirty matched controls underwent standardized transorbital CDI within 24 hours of injury. Hemodynamic parameters\u0026mdash;Peak Systolic Velocity (PSV), End-Diastolic Velocity (EDV), Resistance Index (RI), and Pulsatility Index (PI)\u0026mdash;were measured in the ophthalmic, central retinal, and short posterior ciliary arteries. Clinical indices (GCS, IOP, visual acuity) were concurrently assessed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mTBI group demonstrated a distinct hemodynamic signature in the SPCA circulation, characterized by significantly elevated vascular resistance (RI: 0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 vs. 0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06, p\u0026thinsp;=\u0026thinsp;0.001; PI: 1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 vs. 0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17, p\u0026thinsp;=\u0026thinsp;0.005) and reduced perfusion (PSV: 14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 cm/s vs. 18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4 cm/s, p\u0026thinsp;=\u0026thinsp;0.021). Increased central retinal artery resistance was also observed (RI: 0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 vs. 0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07, p\u0026thinsp;=\u0026thinsp;0.042). Glasgow Coma Scale scores showed a significant inverse correlation with retinal arterial pulsatility (CRA-PI: r = -0.286, p\u0026thinsp;=\u0026thinsp;0.027), linking hemodynamic alterations to neurological status.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study identifies altered SPCA hemodynamics\u0026mdash;a high-resistance, low-flow profile\u0026mdash;as a novel, functional physiological biomarker for acute mTBI, assessable via rapid bedside CDI. These findings expand the mTBI biomarker paradigm from static molecular indicators to include dynamic cerebrovascular dysregulation. CDI of the retrobulbar circulation offers a unique, accessible tool that, with further validation, holds promise for enhancing diagnostic precision, elucidating patient-specific pathophysiology, and guiding personalized management in mTBI.\u003c/p\u003e","manuscriptTitle":"Altered Short Posterior Ciliary Artery Hemodynamics on Point-of-Care Doppler Imaging: A Novel Biomarker in Acute Mild Traumatic Brain Injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 12:14:43","doi":"10.21203/rs.3.rs-8533634/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-02-04T06:27:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-29T08:41:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-28T07:28:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-28T07:22:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Emergency Medicine","date":"2026-01-06T16:44:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e3240b6f-0b0c-422b-a357-61c606044fbf","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T12:14:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 12:14:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8533634","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8533634","identity":"rs-8533634","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}