Ultrasound, CT, and MRI for Orbital and Ocular Lesions: A Comparative Study in Nepal

Ultrasound, CT, and MRI for Orbital and Ocular Lesions: A Comparative Study in Nepal | 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 Ultrasound, CT, and MRI for Orbital and Ocular Lesions: A Comparative Study in Nepal Umesh Sharma, Manmohan Bir Shrestha, Rajesh Rimal, Birendra Kumar Yadav, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8597456/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Orbital and ocular lesions pose significant diagnostic challenges in resource-limited settings like Nepal, where accurate imaging is crucial for timely management. This study aims to evaluate and compare the performance of US, CT, and MRI in the detection and characterization of orbital and ocular lesions in a Nepalese hospital-based cohort. Methods This prospective study, conducted at B&C Teaching Hospital in Birtamode-5, Nepal, enrolled 130 patients with suspected orbital lesions or trauma, presenting with symptoms such as proptosis, vision loss, or pain. All patients underwent USG with a high-frequency linear probe; 85 received CT (Brivo 365, GE), and 45 underwent 1.5T MRI (Philips A series). Diagnostic accuracy was assessed against final diagnoses based on clinical findings, laboratory results, surgery, and histopathology. Metrics included sensitivity, specificity and accuracy across lesion types (tumors, trauma, infections, inflammation) and orbital compartments. Results The cohort (58.4% male, mean age 20–40 years) showed orbital tumors (33.0%), inflammation (20.7%), trauma (17.6%), and infections (13.8%) as primary conditions. MRI excelled in tumor characterization (100% intraocular, 98% intraconal) and inflammation (100% for optic neuritis/perineuritis). CT was superior for trauma (100% foreign body detection) and bony lesions. USG demonstrated 100% sensitivity for retinal detachment and vitreous hemorrhage but lower for deep tumors (50–55% characterization). All modalities achieved high accuracy for infections (90–100%). Conclusion US, CT, and MRI play complementary roles in orbital imaging, with USG ideal for initial screening, CT for emergencies, and MRI for complex soft tissue evaluation. A stepwise approach optimizes resource use in Nepal, enhancing diagnostic accuracy and patient outcomes. Orbital lesions Ocular lesions Ultrasound Computed tomography Magnetic resonance imaging Nepal Prospective study Diagnostic accuracy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Background Orbital and ocular lesions encompass a wide spectrum of conditions, including benign and malignant tumors, inflammatory disorders, infections, congenital anomalies, and traumatic injuries. These lesions may arise from the globe, optic nerve, extraocular muscles, lacrimal gland, bony orbit, or surrounding soft tissues, often presenting with overlapping clinical features such as proptosis, pain, visual impairment, and leukocoria. Orbital and ocular lesions are an important public health issue in Nepal. A multicenter study conducted between 2008 and 2012 found that 30% of 100 cases were malignant, with the eyelid being the most commonly affected site (57%) and the highest prevalence among 31–40 year age group [ 1 ]. Similarly, a study from South India involving 6328 patients reported that inflammatory disorders (34.1%) and thyroid eye disease (31.0%) were the most frequent orbital conditions, showing similar patterns to Nepal. These results emphasize the significant burden of orbital disease in the region and the need for accurate diagnosis. Diagnosing orbital and ocular lesions is complex due to their diverse etiologies and overlapping clinical presentations. Timely and accurate diagnosis is crucial for malignant conditions, such as retinoblastoma and basal cell carcinoma, which are relatively common in Nepal [ 3 ]. Imaging plays a vital role for the evaluation of orbital and ocular lesions. Ultrasound (US) is a non-invasive, cost-effective modality useful for assessing vascular lesions and intraocular pathology, making it well-suited for resource-limited settings [ 4 ]. Computed tomography (CT) is preferred in emergencies, detecting bony changes, calcifications and intraorbital foreign bodies [ 4 ]. Magnetic resonance imaging (MRI) offers superior soft tissue contrast, ideal for complex lesions and visual pathway evaluation [ 4 ]. Advanced imaging techniques such as diffusion-weighted imaging (DWI) and positron emission tomography (PET) can further improve diagnostic accuracy by distinguishing benign from malignant lesions Despite the widespread use of imaging, few studies have directly compared the diagnostic performance of US, CT, and MRI in low-resource settings such as Nepal. Low health literacy in Nepal, where awareness of cataract is moderate (49.6%) and knowledge of trachoma is low (6.1%) further delays diagnosis [ 5 ]. Additionally, ocular trauma often from agricultural work contributes a lot to the lesion burden [ 6 , 7 ]. This study evaluates and compares the diagnostic efficacy of US, CT, and MRI with orbital trauma or suspected lesions (e.g., proptosis, vision loss, pain). It aims to guide imaging choices in resource-limited environments by highlighting the strengths and limitations of each modality. Methods Study Design and Setting This hospital-based prospective study was conducted in the Department of Radiodiagnosis at B&C Teaching Hospital, Birtamod, Nepal. B & C Medical College Teaching Hospital and Research Center is a 300-beded tertiary care teaching hospital located in Birtamode Municipality, Jhapa District, Koshi Province, Nepal. Established to provide both advanced clinical services, B&C functions as a major referral center for eastern Nepal. Participants A total of 130 patients were enrolled in the study. Participants with orbital trauma or clinical suspicion of orbital lesions, presenting with symptoms such as proptosis, suspected orbital mass, complete or partial vision loss, leukocoria, pain, redness, or discharge were included in the study. Data Collection and Diagnosis Data were collected for all enrolled patients using a predefined and standardized proforma. Demographic variables included age and sex, while clinical data comprised presenting symptoms such as proptosis, visual impairment or loss, leukocoria, pain, redness, discharge, soft-tissue swelling and history of trauma. All 130 patients underwent orbital ultrasonography (USG) using a high-frequency linear transducer. Computed tomography (CT) was performed in 85 patients using a multidetector CT scanner (Brivo 365, GE Healthcare), primarily for suspected trauma, bony involvement, calcification or emergency indications. Magnetic resonance imaging (MRI) was performed in 45 patients using a 1.5-Tesla system (Philips A-series), particularly for suspected soft-tissue lesions, inflammatory conditions and optic nerve or intracranial extension. For each imaging modality, findings were recorded separately and included lesion location (intraocular, intraconal, or extraconal), size, margins, internal characteristics (echogenicity or signal intensity), presence of calcification, hemorrhage, edema, bone involvement, intraorbital foreign bodies, vascularity (on Doppler imaging where applicable) and associated complications. MRI protocols included T1-weighted, T2-weighted, fat-suppressed, contrast-enhanced sequences and diffusion-weighted imaging when clinically indicated. Image interpretation was performed by experienced radiologists and documented at the time of examination. When more than one imaging modality was used in the same patient, interpretations were made independently for each modality. The final diagnosis was used as the reference standard and was established using a composite of clinical evaluation, laboratory findings, surgical findings, histopathological examination (where available) and follow-up imaging. This composite reference standard was used to evaluate the diagnostic performance of each imaging modality. Data Analysis Data were entered into Microsoft Excel and analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize demographic and clinical characteristics. The diagnostic performance of each imaging modality (USG, CT, and MRI) was evaluated by comparing imaging findings against the final composite reference standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall diagnostic accuracy were calculated for each modality across different lesion types, including orbital tumors, trauma, infections, inflammatory conditions, retinal detachment, vitreous hemorrhage, congenital anomalies, and vascular lesions. Lesion location (intraocular, intraconal, and extraconal) and other relevant imaging characteristics were also analyzed to determine modality-specific performance. Comparative analyses between modalities were performed descriptively, with cross-tabulations used to highlight differences in detection and characterization rates. Ethical Declaration The study was conducted in accordance with internationally accepted ethical standards for research involving human participants, specifically the principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Committee at B&C Medical College Teaching Hospital and Research Center. Informed consent was secured from all participants prior to their inclusion in the study. Results Patient’s characteristics The study cohort comprised 130 patients, with a male predominance of 58.4% (n = 76). The most represented age group was 20–40 years (42.3%). The most frequent clinical presentations were visual disturbances (53.8%), proptosis (43.0%), soft tissue swelling (32.3%), and ocular or periocular pain (23.0%). Based on final composite diagnoses, the primary conditions included orbital tumors in 33.0% of patients (n = 43), inflammatory orbital pathology in 20.7% (n = 27), orbital trauma in 17.6% (n = 23), and orbital infections in 13.8% (n = 20). Diagnostic Performance of Imaging Modalities The performance of USG, CT, and MRI varied depending on the type and location of the lesion. Below are tables that summarize the diagnostic performance for key conditions, addressing the need for clarity and comprehensiveness. Table 1 presents the diagnostic accuracy three imaging modalities of orbital tumors by compartment where, orbital tumors (n = 43) were categorized into intraocular (30.2%, n = 13), intraconal (27.9%, n = 12), and extraconal (41.8%, n = 18) compartments. MRI showed the highest characterization accuracy, particularly for intraocular (100%) and intraconal (98%) lesions such as choroidal melanoma in Fig. 3 . CT was highly effective for detection (100%) across all compartments and had strong characterization accuracy (90–95%) (Fig. 2 , 4 ). USG had lower characterization accuracy, especially for intraconal (55%) and extraconal (50%) lesions, making it less suitable for deep orbital tumors or lesions (Fig. 1 ). Table 1 Diagnostic Accuracy for Orbital Tumors by Compartment Compartment Cases (n) USG Detection / Characterization (%) CT Detection / Characterization (%) MRI Detection / Characterization (%) Intraocular 13 100 / 90 100 / 94 100 / 100 Intraconal 12 90 / 55 100 / 90 100 / 98 Extraconal 18 85 / 50 100 / 95 100 / 95 Table 2 summarizes detection rate including foreign bodies, hematomas, and vitreous haemorrhage. Total cases for each finding were derived from the maximum number detected by any modality. CT was particularly effective for detecting foreign bodies (9/10), orbital hematoma and post traumatic inflammation/edema in trauma cases (Fig. 6). USG was reliable for soft tissue findings like hematomas and vitreous haemorrhage including foreign bodies (Fig. 5). MRI’s limited use (n = 2) restricted its evaluation, detecting only 1 case each of vitreous haemorrhage and optic neuritis. Total cases for each finding were derived from the maximum number detected by any modality. Table 2 Detection of Key Findings in Orbital Trauma Finding Total Cases (n) USG Detected CT Detected MRI Detected Foreign Body 10 8 9 - Orbital Hematoma 5 4 4 1 Vitreous Hemorrhage 5 5 3 1 Lens Dislocation 3 3 3 - Post-Trauma Inflammation / Edema 6 4 6 - Post-traumatic Retinal Detachment 1 1 1 - Choroidal Detachment 1 1 0 - Optic Neuritis 1 0 0 1 Table 3 summarizes detection rates of USG, CT and MRI in orbital infections including cellulitis, abscesses and fungal sinusitis with orbital extension. USG and CT was equally good to detect panophthalmitis and orbital cysticercosis (Fig. 8 , 12 ). USG detected 18/20 cases (90% sensitivity), missing two cases of fungal sinusitis with orbital extension. CT and MRI achieved 100% detection in their respective cases (13/13) and (7/7) (Fig. 8 ). MRI was uniquely effective for detecting fungal sinusitis with orbital extension in 2 patients and for abscess showing diffusion restriction (Fig. 7 ). Table 3 Detection of Orbital Infections Condition Total Cases (n) USG Detected CT Detected MRI Detected Cellulitis 4 4 2 2 Cellulitis with Abscess 5 5 4 1 Abscess Only 5 5 3 2 Panophthalmitis 2 2 2 - Orbital Cysticercosis 2 2 2 - Fungal Sinusitis (Extension) 2 0 - 2 Total Detection 20 18/20 (90%) 13/13 (100%) 7/7 (100%) Table 4 summarizes the detection rates of USG, CT and MRI in inflammatory conditions such as thyroid orbitopathy, inflammatory pseudotumor, optic neuritis, and optic peri neuritis. CT and MRI detected all cases in their respective subsets (100% sensitivity). USG had lower sensitivity (44.4%), detecting only 12/27 cases, particularly struggling with optic neuritis and perineuritis (Fig. 10 ). MRI was superior for optic neuritis and perineuritis, detecting all cases where used. Table 4 Detection of Inflammatory Orbital Pathology Condition Total Cases (n) USG Detected (%) CT Detected (%) MRI Detected (%) Thyroid Orbitopathy 7 5 7 - Inflammatory Pseudotumor 10 6 6 4 Optic Neuritis 8 1 2 6 Optic Perineuritis 2 0 - 2 Total Detection 27 12/27 (44.4%) 15/15 (100%) 12/12 (100%) Table 5 summarizes the performance of USG, CT and MRI for specific conditions. USG was highly sensitive for retinal detachment (100%) and vitreous hemorrhage (80%). CT and MRI achieved 100% sensitivity for orbital infections in their respective cases. MRI was the most sensitive for optic neuritis and perineuritis (100%). Sensitivity for optic neuritis/perineuritis was calculated based on 2 cases each, with USG detecting 1/4 and CT 2/4. For congenital lesions (Fig. 9) and carotid cavernous fistula (Fig. 10 ), USG and CT showed 100% sensitivity. The congenital lesions included intra-orbital encephalocele, persistent hypertrophic primary vitreous (PHPV), sphenoid dysplasia. Table 5 Sensitivity for Specific Conditions Condition Total Cases (n) USG Sensitivity (%) CT Sensitivity (%) MRI Sensitivity (%) Retinal Detachment 9 100 33.3 50 Orbital Infections 20 90 100 100 Optic Neuritis / Perineuritis 10 10 100 100 Vitreous Hemorrhage 5 80 80 20 Congenital Lesions 6 100 100 - Carotid Cavernous Fistula 2 100 100 - Discussion The study found that MRI achieved the highest accuracy for detecting and characterizing orbital tumors, particularly for intraocular (100% detection, 100% characterization) and intraconal (100% detection, 98% characterization) lesions (Fig. 1 , 3 ). CT also performed robustly, with 100% detection across all compartments and 90–95% characterization accuracy, while USG was less effective, particularly for characterization (50–90%) (Fig. 2 ,5). These results align with established literature, which positions MRI as the gold standard for soft tissue evaluation due to its superior contrast resolution and ability to delineate complex orbital pathologies [ 1 , 2 ]. For instance, Goh et al. (2008) emphasize MRI’s role in assessing soft tissue tumors like retinoblastoma and cavernous hemangioma, which were prevalent in our study [ 1 ]. CT’s strength in detecting calcifications and bony abnormalities, as noted in studies by Mafee et al. (1999), was also evident in our findings, particularly for extraconal lesions [ 3 ]. The prevalence of orbital tumors (33.0%, n = 43) in our study, with hemangioma (13.6%) as the most common, mirrors regional data from Nepal, where a multicenter study reported 30% of orbital lesions as malignant, with a similar age distribution (20–40 years in our study vs. 31–40 years) [ 4 ]. This suggests a consistent regional pattern of orbital tumor prevalence, with both benign and malignant etiologies being significant. For orbital trauma (17.6%, n = 23), CT was superior in detecting foreign bodies and bony involvement, aligning with its established role in emergency settings [ 5 , 6 ] (Fig. 6). USG was effective for soft tissue findings like hematomas and vitreous hemorrhage, detecting 80–100% of cases (Fig. 5). This supports literature indicating CT’s preference for trauma due to its rapid acquisition and ability to visualize bony structures and calcifications [ 7 ]. Boyette et al. (2015) highlight CT’s utility in managing orbital fractures, which was evident in our study’s high detection rates for trauma-related findings [ 6 ]. US’s role as a non-invasive, cost-effective tool for initial assessment, as noted by Bryden et al. (1990), was also confirmed, particularly for vitreous hemorrhage [ 8 ]. All three modalities demonstrated high sensitivity for orbital infections (n = 20), with CT and MRI achieving 100% detection in their respective cases, while USG detected 90% of cases, missing two instances of fungal sinusitis with orbital extension .This is consistent with Sepahdari et al. (2009), who advocate MRI for detecting invasive infections due to its soft tissue detail, particularly for conditions like fungal sinusitis [ 9 ]. CT’s role in rapid diagnosis of infections like cellulitis and abscesses, as noted in the Radiology Assistant (2008), was also evident [ 10 ]. US’s high sensitivity for superficial infections like cellulitis supports its use as an initial screening tool in resource-limited settings [ 11 ]. MRI was the most sensitive modality for inflammatory conditions (n = 27), achieving 100% detection for optic neuritis and perineuritis, while CT detected 100% of cases in its subset, and USG had lower sensitivity (44.4%) (Fig. 11 ). These findings align with literature emphasizing MRI’s superiority for inflammatory conditions due to its ability to detect subtle soft tissue changes and optic nerve involvement [ 9 , 12 ]. The high prevalence of inflammatory pathologies (20.7%) in our study, including thyroid orbitopathy and inflammatory pseudotumor, is comparable to a South Indian study reporting 34.1% inflammatory orbital diseases, suggesting regional similarities [ 13 ]. USG demonstrated 100% sensitivity for retinal detachment (n = 9) and 80% for vitreous hemorrhage (n = 5), outperforming CT (33.3% for retinal detachment) and MRI (50% for retinal detachment) (Fig. 5). This supports EyeWiki’s recommendation of USG as the first-line modality for suspected intraocular masses and conditions like retinal detachment due to its accessibility and effectiveness [ 11 ]. Kaufman et al. (1998) also highlight US’s utility for intraocular pathologies, particularly in settings where advanced imaging is limited [ 14 ]. For uncommon conditions such as orbital encephalocele, PHPV, sphenoid dysplasia and CCF, including orbital cysts ultrasound proved to be a useful tool for lesion detection. USG diagnosed PHPV with 100% accuracy. However, CT had the advantage in lesion characterization, particularly in demonstrating intracranial communication and associated bony abnormalities. The study’s findings have significant implications for clinical practice in Nepal, where resource constraints and limited access to advanced imaging are common challenges. US’s cost-effectiveness, non-invasive nature, and high sensitivity for conditions like retinal detachment and vitreous hemorrhage make it an ideal initial diagnostic tool, particularly in rural or resource-limited settings. CT, while more expensive, is widely available and essential for trauma and bony pathologies, offering rapid diagnosis in emergency settings. MRI, despite its superior accuracy for soft tissue lesions and inflammatory conditions, is less accessible due to high costs and limited availability in many parts of Nepal. The study’s findings also emphasize the need for increased awareness and training in the use of USG for initial assessments, as its operator-dependent nature requires skilled radiologists to maximize its diagnostic potential. Strengthening radiology infrastructure and training programs in Nepal could enhance the effective use of these modalities, improving patient outcomes. Several limitations should be noted. First, not all patients underwent all three imaging modalities (US: 130, CT: 85, MRI: 45), which may introduce selection bias, as the choice of CT or MRI was likely based on clinical judgment, potentially favoring more complex cases for advanced imaging. Second, the sample size for certain conditions, such as optic neuritis (n = 8) and perineuritis (n = 2), was small, limiting the generalizability of findings for these pathologies. Third, the study did not assess the economic impact or patient outcomes associated with different imaging strategies, which are critical in resource-limited settings. Finally, the lack of explicit criteria for selecting patients for CT or MRI may have influenced the results, as the decision-making process was not standardized. Future research should focus on larger, multicenter studies to validate these findings across diverse populations in Nepal and other low-resource settings. Investigating the cost-effectiveness of different imaging protocols could guide resource allocation and improve access to diagnostic tools. Additionally, exploring the integration of advanced imaging techniques, such as diffusion-weighted MRI or PET-CT, could enhance the characterization of orbital lesions, particularly for distinguishing benign from malignant tumors [ 1 ]. Studies evaluating the role of telemedicine or teleradiology could address the shortage of expert radiologists in remote areas, improving access to accurate interpretations. Longitudinal studies tracking patient outcomes based on imaging-guided management could further refine clinical decision-making and assess the impact on visual prognosis. Conclusion This study confirms the complementary roles of US, CT, and MRI in diagnosing ocular and orbital lesions, with MRI excelling for soft tissue and inflammatory conditions, CT for trauma and bony abnormalities, and USG for superficial and intraocular pathologies. These findings are particularly relevant in Nepal, where a stepwise imaging strategy starting with US, followed by CT or MRI as needed can optimize diagnostic accuracy while addressing resource constraints. By providing evidence-based guidance for clinicians, this study contributes to improving the management of orbital and ocular lesions in resource-limited settings, ultimately reducing the burden of vision loss. Declarations Ethics approval and consent to participate Ethical approval was obtained from the Institutional Review Committee of B&C Medical College Teaching Hospital. Written informed consent was obtained from all participants or their guardians. Consent for publication Written informed consent for publication of clinical data and images was obtained from all participants or their legal guardians. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding No external funding was received for this study. Authors’ contributions UKS conceived the study. MBS, RR, BKY, UR, DT, SS, and AP contributed to data acquisition and analysis. UKS drafted the manuscript. All authors critically revised the manuscript and approved the final version. Acknowledgements The authors acknowledge the staff of the Departments of Radiology, Ophthalmology, and Pathology at B&C Medical College Teaching Hospital for their support. References Clinico-Histopathological A. Study of Orbital and Ocular Lesions; a Multicenter Study. J Chitwan Med Coll. 2013;3(2):40–4. 10.3126/jcmc.v3i2.8442 . Spectrum of orbital disease. in South India: an Aravind study of 6328 consecutive patients. Ophthal Plast Reconstr Surg. 2010;26(4):315–22. PMID: 20592641. Pattern of ocular tumors. in the eastern region of Nepal. Nepal J Ophthalmol. 2009;1(2):141–3. PMID: 21141015. 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Clinicopathologic and MR imaging features. Radiol Clin North Am. 1999;37(1):219–39. 10.1016/S0033-8389(05)70088-8 . Shrestha SP, Maharjan IM, Shrestha JK, et al. A Clinico-Histopathological Study of Orbital and Ocular Lesions; a Multicenter Study. J Chitwan Med Coll. 2013;3(2):40–4. 10.3126/jcmc.v3i2.8442 . Oesterle CS, Hopper KD, Udovich C, et al. Helical CT of the orbits in children: optimization of technique. AJR Am J Roentgenol. 1997;169(4):1093–6. 10.2214/ajr.169.4.9308472 . Boyette JR, Pemberton JD, Bonilla-Velez J. Management of orbital fractures: challenges and solutions. Clin Ophthalmol. 2015;9:2127–37. 10.2147/OPTH.S80463 . Polito E, Manganelli A, Pichierri P, et al. Orbital cavernous hemangioma: differential diagnosis CT and MR imaging. Radiol Med. 2006;111(2):219–28. 10.1007/s11547-006-0020-7 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 Feb, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers invited by journal 11 Feb, 2026 Editor invited by journal 20 Jan, 2026 Editor assigned by journal 20 Jan, 2026 Submission checks completed at journal 20 Jan, 2026 First submitted to journal 13 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8597456","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590595709,"identity":"c5b63475-2b33-4af3-8dce-0b0317815b55","order_by":0,"name":"Umesh Sharma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDCCAwzMDIwNIBb/gwMfgBQbO/FaeBgfzgBpYSZBC7MxD4gmpIXv9hljw5877PJ1288ek7b5tU2eD2jEh485uLVInssxTuY9k2y57UxemnRu323DNmYGZsmZ23BrMTjDY3yYsY3ZwOxAgpl0bs9tIBvoHV4CWg7+bKs3MDv/wEzasue2PVFaEnjbDhuY3cgxNmb4cTuRoBbJM2zFxrxtx4FaniU+7G24ndzGzNiM1y98Z5g3S/5sqwY6LPnAgR9/btvOb28++OEjHi2ogLENTDYQqx4E/pCieBSMglEwCkYKAADv2FLqQqcP2QAAAABJRU5ErkJggg==","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":true,"prefix":"","firstName":"Umesh","middleName":"","lastName":"Sharma","suffix":""},{"id":590595710,"identity":"1b66db58-c680-4dd7-b74f-1fdd65017f00","order_by":1,"name":"Manmohan Bir Shrestha","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Manmohan","middleName":"Bir","lastName":"Shrestha","suffix":""},{"id":590595711,"identity":"db4026c0-26c0-49c5-b9b8-0c1c682b958f","order_by":2,"name":"Rajesh Rimal","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"Rimal","suffix":""},{"id":590595712,"identity":"6450cf77-befe-44ce-a9e6-c1a0b9b30fea","order_by":3,"name":"Birendra Kumar Yadav","email":"","orcid":"","institution":"Purbanchal Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Birendra","middleName":"Kumar","lastName":"Yadav","suffix":""},{"id":590595713,"identity":"b2748b90-136d-4501-bb15-9536c35bb3a6","order_by":4,"name":"Ujwal Rai","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Ujwal","middleName":"","lastName":"Rai","suffix":""},{"id":590595714,"identity":"82e06eb4-1e34-41ad-a195-f1ede6d97848","order_by":5,"name":"Dinesh Kumar Thapa","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Dinesh","middleName":"Kumar","lastName":"Thapa","suffix":""},{"id":590595715,"identity":"8a3caac8-6530-4e42-b212-c2744289d396","order_by":6,"name":"Sudesh Subedi","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Sudesh","middleName":"","lastName":"Subedi","suffix":""},{"id":590595716,"identity":"dcc4aaf6-0911-4e2b-a54a-e4de05c37dd1","order_by":7,"name":"Akash Pradhan","email":"","orcid":"","institution":"B\u0026C Medical College Teaching Hospital and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Akash","middleName":"","lastName":"Pradhan","suffix":""}],"badges":[],"createdAt":"2026-01-14 04:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8597456/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8597456/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102963492,"identity":"fd4e9350-9cc8-4aa7-a47a-c454ccf1e5ad","added_by":"auto","created_at":"2026-02-19 04:18:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":237713,"visible":true,"origin":"","legend":"\u003cp\u003eAB. 33 Y Male with diminished vision and proptosis of right eye. 1A) Ultrasound of the right orbit shows poorly defined hypoechoic retroorbital mass. 1B) Coronal T2 WI MRI of the orbit shows the mass arising from the right nasal cavity \u0026amp; maxilla extending to the orbit.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/a9950d1bc950085e48795372.png"},{"id":102839305,"identity":"24cab67a-4d33-4834-8777-d1e11c480572","added_by":"auto","created_at":"2026-02-17 11:44:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":925504,"visible":true,"origin":"","legend":"\u003cp\u003eAB: Orbital Cavernous hemangioma-A22 Y male with progressive proptosis. 2A)Ultrasound and color Doppler shows well defined hypoechoic extraconal mass with internal increased vascularity.2B) Corresponding contrast enhanced CT shows enhancing orbital mass\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/c5ad0ae343f89d20ea8c918d.png"},{"id":102963228,"identity":"080f911a-c49e-4b06-a71e-aca0a45a4991","added_by":"auto","created_at":"2026-02-19 04:14:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":550015,"visible":true,"origin":"","legend":"\u003cp\u003e42 years male with choroidal melanoma. T2W coronal image shows hypointense intraocular mass compatible with the melanotic tumor. Corresponding ultrasound shows intraocular mixed echogenic lobulated mass\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/1853cd053ff9ea52dee0bceb.png"},{"id":102962787,"identity":"77aebaad-8ddf-48dc-8528-e787e60e0933","added_by":"auto","created_at":"2026-02-19 04:11:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":453298,"visible":true,"origin":"","legend":"\u003cp\u003e4 year old child with B/L retinoblastoma. Ultrasound and CT scan axial images show calcified intraocular mass.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/fe9861923dfc24600654831b.png"},{"id":102839307,"identity":"a62f9695-f4d8-4caa-874c-fb4d0e6932a6","added_by":"auto","created_at":"2026-02-17 11:44:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":368606,"visible":true,"origin":"","legend":"\u003cp\u003e60 year male with loss of vision in right eye. NCCT scan of orbit show hyperdensity in the posterior aspect of the right globe indicating hemorrhage. Corresponding ultrasound shows retinal detachment with subretinal collection.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/2cc44d93416bc742ed0442b2.png"},{"id":102839315,"identity":"850f81ba-3662-4611-aa94-7af73196e2ec","added_by":"auto","created_at":"2026-02-17 11:44:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":696476,"visible":true,"origin":"","legend":"\u003cp\u003ePatients with orbital trauma. 6 A, B) 38 y female with penetrating orbital injury and shows tiny metallic \u0026nbsp;extraocular foreign body.Ultrasound shows vitreous hemorrhage with a subtle retroocular hyperechoic foreign body. CT confirms the tiny hyperattenuating foreign body, however vitreous hemorrhage is better evaluated by ultrasound. 6 C) 27 Y male \u0026nbsp;with the radiolucent extraocular foreign body, which was not seen in CT scan. 6 D) 55Year female and \u0026nbsp;Ultrasound shows lens dislocation.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/a9fd5e8e5ce66d4bd21f9dc2.png"},{"id":102839309,"identity":"21526fd1-6857-4483-a3e6-e59713884f12","added_by":"auto","created_at":"2026-02-17 11:44:39","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":355183,"visible":true,"origin":"","legend":"\u003cp\u003e3 year old child with orbital abscess. Ultrasound of orbit demonstrates hypoechoic retroorbital lesion. MRI T2 W axial image show retroorbital collection with hypointense wall. DWI shows diffusion restriction in the collection.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/c2e2d5f87c80a2760a2d56db.png"},{"id":102963921,"identity":"21d255d3-5bd2-4f50-b69e-e78881bdaafd","added_by":"auto","created_at":"2026-02-19 04:20:52","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":326531,"visible":true,"origin":"","legend":"\u003cp\u003e52 year female with panophthalmitis and perforation of globe. Ultrasound of the orbit shows perforation of the globe with periocular and intraocular collections. CT scan of the orbit also demonstrates similar findings.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/3462fe2e4058ee39f15d49d6.png"},{"id":102839311,"identity":"12a40cb9-ba56-4d7f-b883-307c1b429613","added_by":"auto","created_at":"2026-02-17 11:44:39","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":375974,"visible":true,"origin":"","legend":"\u003cp\u003e5 months male child with B/L leukokorea with diagnosis of PHPV. \u0026nbsp;Color Doppler ultrasound show intraorbital mass with persistent hyaloid artery. CT scan shows microphthalmia of right globe and hyperdense vitreous on either side.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/b2d9840d3e0f9c0a43bfcacd.png"},{"id":102839314,"identity":"34aebfcf-6597-4422-be48-b61657ee7beb","added_by":"auto","created_at":"2026-02-17 11:44:39","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":411385,"visible":true,"origin":"","legend":"\u003cp\u003eCarotid cavernous fistula. Ultrasound and CT scan shows dilated, tortuous superior orbital vein in right orbit.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/381008b6f857302499a1cd26.png"},{"id":102839313,"identity":"89565271-7109-4c44-a3cf-dd92821c8de4","added_by":"auto","created_at":"2026-02-17 11:44:39","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":379253,"visible":true,"origin":"","legend":"\u003cp\u003ePatient with loss of vision in left eye. Ultrasound could show mild thickening of left optic nerve, whereas contrast enhanced coronal T1 MRI demonstrates features of perineuritis.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/8c63da23ba394227229cc97f.png"},{"id":102963203,"identity":"033f49dd-f322-4f96-b78b-fd7ab1b8b3f7","added_by":"auto","created_at":"2026-02-19 04:14:29","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":795386,"visible":true,"origin":"","legend":"\u003cp\u003e30 year male with history of pain and proptosis of right orbit. Ultrasound and CT scan shows characteristic features of orbital cysticercosis.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/733b33b4d75add0a578e9a30.png"},{"id":102965310,"identity":"18b452eb-74ab-42c1-bdd4-f502da772ce3","added_by":"auto","created_at":"2026-02-19 04:31:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10884688,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8597456/v1/450221e9-b651-486b-8170-b636719e27eb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ultrasound, CT, and MRI for Orbital and Ocular Lesions: A Comparative Study in Nepal","fulltext":[{"header":"Background","content":"\u003cp\u003eOrbital and ocular lesions encompass a wide spectrum of conditions, including benign and malignant tumors, inflammatory disorders, infections, congenital anomalies, and traumatic injuries. These lesions may arise from the globe, optic nerve, extraocular muscles, lacrimal gland, bony orbit, or surrounding soft tissues, often presenting with overlapping clinical features such as proptosis, pain, visual impairment, and leukocoria.\u003c/p\u003e \u003cp\u003eOrbital and ocular lesions are an important public health issue in Nepal. A multicenter study conducted between 2008 and 2012 found that 30% of 100 cases were malignant, with the eyelid being the most commonly affected site (57%) and the highest prevalence among 31\u0026ndash;40 year age group [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Similarly, a study from South India involving 6328 patients reported that inflammatory disorders (34.1%) and thyroid eye disease (31.0%) were the most frequent orbital conditions, showing similar patterns to Nepal. These results emphasize the significant burden of orbital disease in the region and the need for accurate diagnosis.\u003c/p\u003e \u003cp\u003eDiagnosing orbital and ocular lesions is complex due to their diverse etiologies and overlapping clinical presentations. Timely and accurate diagnosis is crucial for malignant conditions, such as retinoblastoma and basal cell carcinoma, which are relatively common in Nepal [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Imaging plays a vital role for the evaluation of orbital and ocular lesions. Ultrasound (US) is a non-invasive, cost-effective modality useful for assessing vascular lesions and intraocular pathology, making it well-suited for resource-limited settings [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Computed tomography (CT) is preferred in emergencies, detecting bony changes, calcifications and intraorbital foreign bodies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Magnetic resonance imaging (MRI) offers superior soft tissue contrast, ideal for complex lesions and visual pathway evaluation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Advanced imaging techniques such as diffusion-weighted imaging (DWI) and positron emission tomography (PET) can further improve diagnostic accuracy by distinguishing benign from malignant lesions\u003c/p\u003e \u003cp\u003eDespite the widespread use of imaging, few studies have directly compared the diagnostic performance of US, CT, and MRI in low-resource settings such as Nepal. Low health literacy in Nepal, where awareness of cataract is moderate (49.6%) and knowledge of trachoma is low (6.1%) further delays diagnosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, ocular trauma often from agricultural work contributes a lot to the lesion burden [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study evaluates and compares the diagnostic efficacy of US, CT, and MRI with orbital trauma or suspected lesions (e.g., proptosis, vision loss, pain). It aims to guide imaging choices in resource-limited environments by highlighting the strengths and limitations of each modality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis hospital-based prospective study was conducted in the Department of Radiodiagnosis at B\u0026amp;C Teaching Hospital, Birtamod, Nepal. B \u0026amp; C Medical College Teaching Hospital and Research Center is a 300-beded tertiary care teaching hospital located in Birtamode Municipality, Jhapa District, Koshi Province, Nepal. Established to provide both advanced clinical services, B\u0026amp;C functions as a major referral center for eastern Nepal.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eA total of 130 patients were enrolled in the study. Participants with orbital trauma or clinical suspicion of orbital lesions, presenting with symptoms such as proptosis, suspected orbital mass, complete or partial vision loss, leukocoria, pain, redness, or discharge were included in the study.\u003c/p\u003e\n\u003ch3\u003eData Collection and Diagnosis\u003c/h3\u003e\n\u003cp\u003eData were collected for all enrolled patients using a predefined and standardized proforma. Demographic variables included age and sex, while clinical data comprised presenting symptoms such as proptosis, visual impairment or loss, leukocoria, pain, redness, discharge, soft-tissue swelling and history of trauma.\u003c/p\u003e \u003cp\u003eAll 130 patients underwent orbital ultrasonography (USG) using a high-frequency linear transducer. Computed tomography (CT) was performed in 85 patients using a multidetector CT scanner (Brivo 365, GE Healthcare), primarily for suspected trauma, bony involvement, calcification or emergency indications. Magnetic resonance imaging (MRI) was performed in 45 patients using a 1.5-Tesla system (Philips A-series), particularly for suspected soft-tissue lesions, inflammatory conditions and optic nerve or intracranial extension.\u003c/p\u003e \u003cp\u003eFor each imaging modality, findings were recorded separately and included lesion location (intraocular, intraconal, or extraconal), size, margins, internal characteristics (echogenicity or signal intensity), presence of calcification, hemorrhage, edema, bone involvement, intraorbital foreign bodies, vascularity (on Doppler imaging where applicable) and associated complications. MRI protocols included T1-weighted, T2-weighted, fat-suppressed, contrast-enhanced sequences and diffusion-weighted imaging when clinically indicated.\u003c/p\u003e \u003cp\u003eImage interpretation was performed by experienced radiologists and documented at the time of examination. When more than one imaging modality was used in the same patient, interpretations were made independently for each modality.\u003c/p\u003e \u003cp\u003eThe final diagnosis was used as the reference standard and was established using a composite of clinical evaluation, laboratory findings, surgical findings, histopathological examination (where available) and follow-up imaging. This composite reference standard was used to evaluate the diagnostic performance of each imaging modality.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were entered into Microsoft Excel and analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize demographic and clinical characteristics. The diagnostic performance of each imaging modality (USG, CT, and MRI) was evaluated by comparing imaging findings against the final composite reference standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall diagnostic accuracy were calculated for each modality across different lesion types, including orbital tumors, trauma, infections, inflammatory conditions, retinal detachment, vitreous hemorrhage, congenital anomalies, and vascular lesions. Lesion location (intraocular, intraconal, and extraconal) and other relevant imaging characteristics were also analyzed to determine modality-specific performance. Comparative analyses between modalities were performed descriptively, with cross-tabulations used to highlight differences in detection and characterization rates.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Declaration\u003c/h3\u003e\n\u003cp\u003e The study was conducted in accordance with internationally accepted ethical standards for research involving human participants, specifically the principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Committee at B\u0026amp;C Medical College Teaching Hospital and Research Center. Informed consent was secured from all participants prior to their inclusion in the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient\u0026rsquo;s characteristics\u003c/h2\u003e \u003cp\u003eThe study cohort comprised 130 patients, with a male predominance of 58.4% (n\u0026thinsp;=\u0026thinsp;76). The most represented age group was 20\u0026ndash;40 years (42.3%). The most frequent clinical presentations were visual disturbances (53.8%), proptosis (43.0%), soft tissue swelling (32.3%), and ocular or periocular pain (23.0%). Based on final composite diagnoses, the primary conditions included orbital tumors in 33.0% of patients (n\u0026thinsp;=\u0026thinsp;43), inflammatory orbital pathology in 20.7% (n\u0026thinsp;=\u0026thinsp;27), orbital trauma in 17.6% (n\u0026thinsp;=\u0026thinsp;23), and orbital infections in 13.8% (n\u0026thinsp;=\u0026thinsp;20).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDiagnostic Performance of Imaging Modalities\u003c/h3\u003e\n\u003cp\u003eThe performance of USG, CT, and MRI varied depending on the type and location of the lesion. Below are tables that summarize the diagnostic performance for key conditions, addressing the need for clarity and comprehensiveness.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the diagnostic accuracy three imaging modalities of orbital tumors by compartment where, orbital tumors (n\u0026thinsp;=\u0026thinsp;43) were categorized into intraocular (30.2%, n\u0026thinsp;=\u0026thinsp;13), intraconal (27.9%, n\u0026thinsp;=\u0026thinsp;12), and extraconal (41.8%, n\u0026thinsp;=\u0026thinsp;18) compartments. MRI showed the highest characterization accuracy, particularly for intraocular (100%) and intraconal (98%) lesions such as choroidal melanoma in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. CT was highly effective for detection (100%) across all compartments and had strong characterization accuracy (90\u0026ndash;95%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e,\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). USG had lower characterization accuracy, especially for intraconal (55%) and extraconal (50%) lesions, making it less suitable for deep orbital tumors or lesions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic Accuracy for Orbital Tumors by Compartment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompartment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSG Detection / Characterization (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT Detection / Characterization (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMRI Detection / Characterization (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraocular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 / 90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 / 94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100 / 100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraconal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 / 55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 / 90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100 / 98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtraconal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 / 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 / 95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100 / 95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes detection rate including foreign bodies, hematomas, and vitreous haemorrhage. Total cases for each finding were derived from the maximum number detected by any modality. CT was particularly effective for detecting foreign bodies (9/10), orbital hematoma and post traumatic inflammation/edema in trauma cases (Fig.\u0026nbsp;6). USG was reliable for soft tissue findings like hematomas and vitreous haemorrhage including foreign bodies (Fig.\u0026nbsp;5). MRI\u0026rsquo;s limited use (n\u0026thinsp;=\u0026thinsp;2) restricted its evaluation, detecting only 1 case each of vitreous haemorrhage and optic neuritis. Total cases for each finding were derived from the maximum number detected by any modality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetection of Key Findings in Orbital Trauma\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Cases (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSG Detected\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT Detected\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMRI Detected\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForeign Body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrbital Hematoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitreous Hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLens Dislocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-Trauma Inflammation / Edema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-traumatic Retinal Detachment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChoroidal Detachment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptic Neuritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes detection rates of USG, CT and MRI in orbital infections including cellulitis, abscesses and fungal sinusitis with orbital extension. USG and CT was equally good to detect panophthalmitis and orbital cysticercosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e8\u003c/span\u003e,\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e12\u003c/span\u003e). USG detected 18/20 cases (90% sensitivity), missing two cases of fungal sinusitis with orbital extension. CT and MRI achieved 100% detection in their respective cases (13/13) and (7/7) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e8\u003c/span\u003e). MRI was uniquely effective for detecting fungal sinusitis with orbital extension in 2 patients and for abscess showing diffusion restriction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetection of Orbital Infections\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Cases (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSG Detected\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT Detected\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMRI Detected\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCellulitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCellulitis with Abscess\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbscess Only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePanophthalmitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrbital Cysticercosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFungal Sinusitis (Extension)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Detection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18/20 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13/13 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7/7 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the detection rates of USG, CT and MRI in inflammatory conditions such as thyroid orbitopathy, inflammatory pseudotumor, optic neuritis, and optic peri neuritis. CT and MRI detected all cases in their respective subsets (100% sensitivity). USG had lower sensitivity (44.4%), detecting only 12/27 cases, particularly struggling with optic neuritis and perineuritis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e10\u003c/span\u003e). MRI was superior for optic neuritis and perineuritis, detecting all cases where used.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetection of Inflammatory Orbital Pathology\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Cases (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSG Detected (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT Detected (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMRI Detected (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid Orbitopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflammatory Pseudotumor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptic Neuritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptic Perineuritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Detection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12/27 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15/15 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12/12 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the performance of USG, CT and MRI for specific conditions. USG was highly sensitive for retinal detachment (100%) and vitreous hemorrhage (80%). CT and MRI achieved 100% sensitivity for orbital infections in their respective cases. MRI was the most sensitive for optic neuritis and perineuritis (100%). Sensitivity for optic neuritis/perineuritis was calculated based on 2 cases each, with USG detecting 1/4 and CT 2/4. For congenital lesions (Fig.\u0026nbsp;9) and carotid cavernous fistula (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e10\u003c/span\u003e), USG and CT showed 100% sensitivity. The congenital lesions included intra-orbital encephalocele, persistent hypertrophic primary vitreous (PHPV), sphenoid dysplasia.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity for Specific Conditions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Cases (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSG Sensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT Sensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMRI Sensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetinal Detachment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrbital Infections\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptic Neuritis / Perineuritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitreous Hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital Lesions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarotid Cavernous Fistula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study found that MRI achieved the highest accuracy for detecting and characterizing orbital tumors, particularly for intraocular (100% detection, 100% characterization) and intraconal (100% detection, 98% characterization) lesions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). CT also performed robustly, with 100% detection across all compartments and 90\u0026ndash;95% characterization accuracy, while USG was less effective, particularly for characterization (50\u0026ndash;90%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e,5). These results align with established literature, which positions MRI as the gold standard for soft tissue evaluation due to its superior contrast resolution and ability to delineate complex orbital pathologies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. For instance, Goh et al. (2008) emphasize MRI\u0026rsquo;s role in assessing soft tissue tumors like retinoblastoma and cavernous hemangioma, which were prevalent in our study [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. CT\u0026rsquo;s strength in detecting calcifications and bony abnormalities, as noted in studies by Mafee et al. (1999), was also evident in our findings, particularly for extraconal lesions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The prevalence of orbital tumors (33.0%, n\u0026thinsp;=\u0026thinsp;43) in our study, with hemangioma (13.6%) as the most common, mirrors regional data from Nepal, where a multicenter study reported 30% of orbital lesions as malignant, with a similar age distribution (20\u0026ndash;40 years in our study vs. 31\u0026ndash;40 years) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This suggests a consistent regional pattern of orbital tumor prevalence, with both benign and malignant etiologies being significant.\u003c/p\u003e \u003cp\u003eFor orbital trauma (17.6%, n\u0026thinsp;=\u0026thinsp;23), CT was superior in detecting foreign bodies and bony involvement, aligning with its established role in emergency settings [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] (Fig.\u0026nbsp;6). USG was effective for soft tissue findings like hematomas and vitreous hemorrhage, detecting 80\u0026ndash;100% of cases (Fig.\u0026nbsp;5). This supports literature indicating CT\u0026rsquo;s preference for trauma due to its rapid acquisition and ability to visualize bony structures and calcifications [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Boyette et al. (2015) highlight CT\u0026rsquo;s utility in managing orbital fractures, which was evident in our study\u0026rsquo;s high detection rates for trauma-related findings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. US\u0026rsquo;s role as a non-invasive, cost-effective tool for initial assessment, as noted by Bryden et al. (1990), was also confirmed, particularly for vitreous hemorrhage [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll three modalities demonstrated high sensitivity for orbital infections (n\u0026thinsp;=\u0026thinsp;20), with CT and MRI achieving 100% detection in their respective cases, while USG detected 90% of cases, missing two instances of fungal sinusitis with orbital extension .This is consistent with Sepahdari et al. (2009), who advocate MRI for detecting invasive infections due to its soft tissue detail, particularly for conditions like fungal sinusitis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. CT\u0026rsquo;s role in rapid diagnosis of infections like cellulitis and abscesses, as noted in the Radiology Assistant (2008), was also evident [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. US\u0026rsquo;s high sensitivity for superficial infections like cellulitis supports its use as an initial screening tool in resource-limited settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMRI was the most sensitive modality for inflammatory conditions (n\u0026thinsp;=\u0026thinsp;27), achieving 100% detection for optic neuritis and perineuritis, while CT detected 100% of cases in its subset, and USG had lower sensitivity (44.4%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e11\u003c/span\u003e). These findings align with literature emphasizing MRI\u0026rsquo;s superiority for inflammatory conditions due to its ability to detect subtle soft tissue changes and optic nerve involvement [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The high prevalence of inflammatory pathologies (20.7%) in our study, including thyroid orbitopathy and inflammatory pseudotumor, is comparable to a South Indian study reporting 34.1% inflammatory orbital diseases, suggesting regional similarities [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUSG demonstrated 100% sensitivity for retinal detachment (n\u0026thinsp;=\u0026thinsp;9) and 80% for vitreous hemorrhage (n\u0026thinsp;=\u0026thinsp;5), outperforming CT (33.3% for retinal detachment) and MRI (50% for retinal detachment) (Fig.\u0026nbsp;5). This supports EyeWiki\u0026rsquo;s recommendation of USG as the first-line modality for suspected intraocular masses and conditions like retinal detachment due to its accessibility and effectiveness [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Kaufman et al. (1998) also highlight US\u0026rsquo;s utility for intraocular pathologies, particularly in settings where advanced imaging is limited [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor uncommon conditions such as orbital encephalocele, PHPV, sphenoid dysplasia and CCF, including orbital cysts ultrasound proved to be a useful tool for lesion detection. USG diagnosed PHPV with 100% accuracy. However, CT had the advantage in lesion characterization, particularly in demonstrating intracranial communication and associated bony abnormalities.\u003c/p\u003e \u003cp\u003eThe study\u0026rsquo;s findings have significant implications for clinical practice in Nepal, where resource constraints and limited access to advanced imaging are common challenges. US\u0026rsquo;s cost-effectiveness, non-invasive nature, and high sensitivity for conditions like retinal detachment and vitreous hemorrhage make it an ideal initial diagnostic tool, particularly in rural or resource-limited settings. CT, while more expensive, is widely available and essential for trauma and bony pathologies, offering rapid diagnosis in emergency settings. MRI, despite its superior accuracy for soft tissue lesions and inflammatory conditions, is less accessible due to high costs and limited availability in many parts of Nepal.\u003c/p\u003e \u003cp\u003eThe study\u0026rsquo;s findings also emphasize the need for increased awareness and training in the use of USG for initial assessments, as its operator-dependent nature requires skilled radiologists to maximize its diagnostic potential. Strengthening radiology infrastructure and training programs in Nepal could enhance the effective use of these modalities, improving patient outcomes.\u003c/p\u003e \u003cp\u003eSeveral limitations should be noted. First, not all patients underwent all three imaging modalities (US: 130, CT: 85, MRI: 45), which may introduce selection bias, as the choice of CT or MRI was likely based on clinical judgment, potentially favoring more complex cases for advanced imaging. Second, the sample size for certain conditions, such as optic neuritis (n\u0026thinsp;=\u0026thinsp;8) and perineuritis (n\u0026thinsp;=\u0026thinsp;2), was small, limiting the generalizability of findings for these pathologies. Third, the study did not assess the economic impact or patient outcomes associated with different imaging strategies, which are critical in resource-limited settings. Finally, the lack of explicit criteria for selecting patients for CT or MRI may have influenced the results, as the decision-making process was not standardized.\u003c/p\u003e \u003cp\u003eFuture research should focus on larger, multicenter studies to validate these findings across diverse populations in Nepal and other low-resource settings. Investigating the cost-effectiveness of different imaging protocols could guide resource allocation and improve access to diagnostic tools. Additionally, exploring the integration of advanced imaging techniques, such as diffusion-weighted MRI or PET-CT, could enhance the characterization of orbital lesions, particularly for distinguishing benign from malignant tumors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Studies evaluating the role of telemedicine or teleradiology could address the shortage of expert radiologists in remote areas, improving access to accurate interpretations. Longitudinal studies tracking patient outcomes based on imaging-guided management could further refine clinical decision-making and assess the impact on visual prognosis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study confirms the complementary roles of US, CT, and MRI in diagnosing ocular and orbital lesions, with MRI excelling for soft tissue and inflammatory conditions, CT for trauma and bony abnormalities, and USG for superficial and intraocular pathologies. These findings are particularly relevant in Nepal, where a stepwise imaging strategy starting with US, followed by CT or MRI as needed can optimize diagnostic accuracy while addressing resource constraints. By providing evidence-based guidance for clinicians, this study contributes to improving the management of orbital and ocular lesions in resource-limited settings, ultimately reducing the burden of vision loss.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Institutional Review Committee of B\u0026amp;C Medical College Teaching Hospital. Written informed consent was obtained from all participants or their guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication of clinical data and images was obtained from all participants or their legal guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUKS conceived the study. MBS, RR, BKY, UR, DT, SS, and AP contributed to data acquisition and analysis. UKS drafted the manuscript. All authors critically revised the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the staff of the Departments of Radiology, Ophthalmology, and Pathology at B\u0026amp;C Medical College Teaching Hospital for their support.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eClinico-Histopathological A. Study of Orbital and Ocular Lesions; a Multicenter Study. 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Radiol Clin North Am. 1999;37(1):219\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0033-8389(05)70088-8\u003c/span\u003e\u003cspan address=\"10.1016/S0033-8389(05)70088-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShrestha SP, Maharjan IM, Shrestha JK, et al. A Clinico-Histopathological Study of Orbital and Ocular Lesions; a Multicenter Study. J Chitwan Med Coll. 2013;3(2):40\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3126/jcmc.v3i2.8442\u003c/span\u003e\u003cspan address=\"10.3126/jcmc.v3i2.8442\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOesterle CS, Hopper KD, Udovich C, et al. Helical CT of the orbits in children: optimization of technique. AJR Am J Roentgenol. 1997;169(4):1093\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2214/ajr.169.4.9308472\u003c/span\u003e\u003cspan address=\"10.2214/ajr.169.4.9308472\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyette JR, Pemberton JD, Bonilla-Velez J. Management of orbital fractures: challenges and solutions. Clin Ophthalmol. 2015;9:2127\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/OPTH.S80463\u003c/span\u003e\u003cspan address=\"10.2147/OPTH.S80463\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolito E, Manganelli A, Pichierri P, et al. Orbital cavernous hemangioma: differential diagnosis CT and MR imaging. Radiol Med. 2006;111(2):219\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11547-006-0020-7\u003c/span\u003e\u003cspan address=\"10.1007/s11547-006-0020-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Orbital lesions, Ocular lesions, Ultrasound, Computed tomography, Magnetic resonance imaging, Nepal, Prospective study, Diagnostic accuracy","lastPublishedDoi":"10.21203/rs.3.rs-8597456/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8597456/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOrbital and ocular lesions pose significant diagnostic challenges in resource-limited settings like Nepal, where accurate imaging is crucial for timely management. This study aims to evaluate and compare the performance of US, CT, and MRI in the detection and characterization of orbital and ocular lesions in a Nepalese hospital-based cohort.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis prospective study, conducted at B\u0026amp;C Teaching Hospital in Birtamode-5, Nepal, enrolled 130 patients with suspected orbital lesions or trauma, presenting with symptoms such as proptosis, vision loss, or pain. All patients underwent USG with a high-frequency linear probe; 85 received CT (Brivo 365, GE), and 45 underwent 1.5T MRI (Philips A series). Diagnostic accuracy was assessed against final diagnoses based on clinical findings, laboratory results, surgery, and histopathology. Metrics included sensitivity, specificity and accuracy across lesion types (tumors, trauma, infections, inflammation) and orbital compartments.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort (58.4% male, mean age 20\u0026ndash;40 years) showed orbital tumors (33.0%), inflammation (20.7%), trauma (17.6%), and infections (13.8%) as primary conditions. MRI excelled in tumor characterization (100% intraocular, 98% intraconal) and inflammation (100% for optic neuritis/perineuritis). CT was superior for trauma (100% foreign body detection) and bony lesions. USG demonstrated 100% sensitivity for retinal detachment and vitreous hemorrhage but lower for deep tumors (50\u0026ndash;55% characterization). All modalities achieved high accuracy for infections (90\u0026ndash;100%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eUS, CT, and MRI play complementary roles in orbital imaging, with USG ideal for initial screening, CT for emergencies, and MRI for complex soft tissue evaluation. A stepwise approach optimizes resource use in Nepal, enhancing diagnostic accuracy and patient outcomes.\u003c/p\u003e","manuscriptTitle":"Ultrasound, CT, and MRI for Orbital and Ocular Lesions: A Comparative Study in Nepal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-17 11:44:33","doi":"10.21203/rs.3.rs-8597456/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-18T13:46:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81895939463578814742676881428601831475","date":"2026-02-18T13:00:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-11T14:52:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-20T08:01:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-20T07:30:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-20T07:24:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ophthalmology","date":"2026-01-14T04:38:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84c9547f-1e4e-40ec-b3b3-80d60bbaa686","owner":[],"postedDate":"February 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-17T11:44:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-17 11:44:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8597456","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8597456","identity":"rs-8597456","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}