Accuracy of Non-Contrast Brain CT in Pre-Embolization Evaluation of the Middle Meningeal Artery

Accuracy of Non-Contrast Brain CT in Pre-Embolization Evaluation of the Middle Meningeal Artery | 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 Accuracy of Non-Contrast Brain CT in Pre-Embolization Evaluation of the Middle Meningeal Artery Lubin Klotz, Guillaume Bellanger, Marina Poinsignon, Vincent Grandjean, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8524129/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Chronic subdural hematoma (cSDH) is typically diagnosed on non-contrast brain CT. Embolization of the middle meningeal artery (MMA) has become an effective and increasingly adopted treatment. However, pre-procedural understanding of MMA anatomy remains crucial, as anatomical variations—such as atypical origins or accessory branches—can affect procedural safety and strategy. This study evaluated whether three-dimensional (3D) reconstructions from routine non-contrast CT can accurately depict MMA anatomy compared with digital subtraction angiography (DSA), the current reference standard. Materials and Methods In this retrospective study, 76 patients (91 MMAs) who underwent both non-contrast CT and DSA were analyzed. The anterior, posterior, and middle branches were assessed. Branch dominance was categorized as Type I (anterior), Type II (posterior), or Type III (mixed), and posterior branch origin as proximal (A), intermediate (B), or distal (C). The Extended-Adachi classification was used for overall anatomical patterns. The foramen spinosum (FS) and MMA tortuosity were also evaluated. Concordance rates between CT and DSA were calculated. Results On CT, the anterior, posterior, and middle branches were visible in 100%, 94.5%, and 96.7% of cases, respectively. CT–DSA concordance was high for branch identification (91.1% anterior, 85.7% posterior, 78.0% middle) and moderate for dominance (45.5%) and posterior origin (39.3%). Absence of the FS on CT was strongly associated with anatomical variants (3 of 4 cases). Conclusion 3D reconstructions from non-contrast CT allow visualization of the main MMA branches and the foramen spinosum. FS assessment on CT provides a valuable indirect marker for identifying anatomical variations and should be systematically included in pre-embolization evaluation. Chronic Subdural Hematoma CT scan angiography middle meningeal artery embolization Figures Figure 1 Figure 2 Figure 3 Figure 4 Key Points 3D non-contrast CT reliably identifies major branches of the middle meningeal artery (MMA) and the foramen spinosum, making it a valuable tool for initial anatomical assessment. Absence of the foramen spinosum on CT may serve as an indicator of anatomical variants potentially affecting embolization feasibility. Concordance between CT and angiography is low for MMA dominance, posterior branch origin, and full anatomical pattern classification. Importance of the study: This is the first study to quantitatively assess the concordance between non-contrast CT and angiography in evaluating MMA anatomy prior to embolization in patients with chronic subdural hematoma. As embolization becomes increasingly used, especially in high-risk or elderly populations, identifying reliable, non-invasive preoperative imaging modalities is critical. The study highlights the strengths and limitations of CT imaging in this context, reinforcing its role in early screening while affirming the necessity of angiographic evaluation for procedural planning. INTRODUCTION Chronic subdural hematoma (cSDH) is a frequent neurosurgical condition, particularly in the elderly, with an incidence of up to 58 per 100,000 individuals over the age of 65 [ 1 ]. This rate is expected to rise with population aging and the increased use of anticoagulants and antiplatelet agents [ 2 – 6 ]. Although often triggered by minor trauma, the persistence and recurrence of cSDH are mainly driven by chronic inflammation, angiogenesis within the neomembrane, and recurrent microhemorrhages [ 7 , 8 ]. Surgical evacuation through burr holes remains the standard treatment, but recurrence occurs in 10%–20% of patients, sometimes requiring repeated procedures [ 9 – 12 ]. These limitations have prompted exploration of adjunctive or alternative approaches that address the biological mechanisms underlying recurrence. Embolization of the middle meningeal artery (MMA) has emerged as an effective minimally invasive treatment that targets the vascular supply to the outer hematoma membrane [ 13 , 14 ]. Recent randomized controlled trials, including STEM [ 15 ], EMBOLISE [ 16 ], and MAGIC-MT [ 17 ], have demonstrated reduced recurrence rates when combined with surgery, and marked reductions in recurrence for embolization alone. As the technique gains widespread adoption, accurate understanding of MMA anatomy has become critical for procedural safety and efficacy [ 18 – 20 ]. Digital subtraction angiography (DSA) remains the reference standard for evaluating MMA anatomy but is invasive. Conversely, non-contrast cranial CT, already part of the routine diagnostic workup for cSDH, could offers a simple and non-invasive means of assessing the bony course of the MMA through high-resolution bone-window reconstructions. This study aimed to determine whether three-dimensional reconstructions from routine non-contrast CT can accurately depict MMA anatomy compared with DSA. We hypothesized that non-contrast CT 3D reconstructions can reliably identify key anatomical landmarks relevant to pre-embolization planning. METHODS Study Population This was a retrospective, single-center anatomical study conducted at the University Hospital of Purpan (Toulouse, France). Patients were included if they underwent both cerebral angiography and non-contrast-enhanced cranial CT with bone window acquisition between March 2023 and April 2024. Inclusion/Exclusion Criteria Participants eligible for inclusion were adults aged 18 years or older who underwent high-resolution, non-contrast cranial computed tomography (CT) with an intact cranial vault, along with cerebral angiography sufficient to allow for the assessment of the middle meningeal artery (MMA). Exclusion criteria comprised individuals younger than 18 years, those with skull fractures or discontinuities of the cranial vault, and cases lacking either CT or angiographic imaging in the hospital’s picture archiving and communication system (PACS). Additional exclusions included anatomical distortion due to arteriovenous fistulas (AVFs) or arteriovenous malformations (AVMs), as well as patients with bone flap interference or post-craniectomy alterations impeding reliable MMA evaluation. Ethical Considerations This study was conducted in accordance with the Declaration of Helsinki and was approves by insitutionnal review board (n° IRB00011687 Collège de neurochirurgie IRB #1: 2025/43). Due to its retrospective non interventional design and exclusive use of anonymized data obtained during routine clinical care, informed consent was waived. Prior to imaging procedures, patients had been informed that their imaging data could be used for research purposes. Imaging Acquisition All patients underwent non-contrast-enhanced CT scans with bone window reconstruction at millimetric slice thickness. Three-dimensional volume-rendered reconstructions were generated using Change Healthcare Radiology Solutions software (McKesson, Irving, TX, USA). Each skull was segmented in the sagittal plane to isolate right and left MMA territories. MMA anatomy was assessed based on the osseous grooves and canals visualized. Cerebral digital subtraction angiography (DSA) was performed in all patients and used as the reference modality. Selective injection of the external carotid artery allowed direct visualization of the MMA and its branches. Image Evaluation Each imaging modality was reviewed by a dedicated rater, blinded to the other modality. Side-specific evaluation of the MMA was performed to assess concordance between CT and angiography findings. The anatomical evaluation included assessment of the presence or absence of the anterior, oblique, and posterior branches of the middle meningeal artery (MMA), as well as the dominance pattern based on the Adachi classification [21]. The origin of the posterior branch was classified according to the Shotar system [19]. A combined anatomical pattern was determined using the Extended-Adachi classification (E-AC) [19]. Additional parameters included the tortuosity of the MMA, the presence of a petrosal branch, and the presence or absence of the foramen spinosum. Anatomical Classification MMA dominance was defined according to Adachi’s model (1928) [19,22], which classifies MMA branching based on the origin of the middel (obelic) branch: Type I, in which the middle (obelic) branch arises from the anterior branch; Type II, where it originates from the posterior branch; and Type III, characterized by a dual origin from both the anterior and posterior branches. This model focuses on anatomical distribution rather than vessel caliber. The posterior branch origin was classified per Shotar et al.: Type A, indicating a proximal origin near the foramen spinosum; Type B, representing an intermediate origin; and Type C, defined by a distal origin beyond the orbital apex. Combining both systems, a total of nine MMA patterns were defined (E-AC Classification): IA, IB, IC, IIA, IIB, IIC, IIIA, IIIB, and IIIC. Each MMA was categorized on CT and angiography accordingly (Fig.1). Diagram of the projection of the middle meningeal artery (MMA) on a lateral skull radiograph. Dominance is not determined by the relative calibers of the anterior and posterior branches, but rather by the origin of the obelic terminal branches. The anterior branch is shown in red; the obelic branch in orange; and the posterior branch in purple. Panels (a, d, g) demonstrates anterior dominance (Type I) MMA with anterior branch dominance, giving rise to the obelic branch (in yellow). Panels (b, e, h) illustrate posterior dominance (Type II); and panels (c, f, i) depict codominance of anterior and posterior branches (Type III). The origin of the posterior branch is also subclassified: proximal origin (Type A; a–c), intermediate origin (Type B; d–f), and distal origin (Type C; g–i). MMA: Middle Meningeal Artery Primary and Secondary Endpoints The primary outcome was the concordance in the presence or absence of the anterior, obelic, and posterior branches of the middle meningeal artery (MMA) as well as the presence or absence of the foramen spinosum on CT, used as an indirect indicator of MMA origin variants. Secondary endpoints included the pattern concordance rate (E-AC classification) between CT and angiography as well as the concordance of the posterior branch origin type (A, B, or C). A pattern was considered concordant when both modalities identified the same subclass (Fig.2). Additional endpoints involved evaluating concordance in the classification of the MMA course as tortuous versus straight, with tortuosity defined by the presence of three or more visible curvatures and used as an indicator of challenging MMA catheterization. The detection of petrosal branches, were also recorded. Statistical Analysis Digital subtraction angiography (DSA) was considered the reference standard for all comparisons. For each anatomical parameter, concordance between CT and DSA was recorded in binary fashion (1 = match, 0 = mismatch). Descriptive statistics were used to summarize the degree of agreement. The concordance rate was defined as the proportion of middle meningeal arteries (MMAs) showing identical findings on both CT and DSA. The corresponding failure rate represented the proportion of MMAs with discrepancies between the two modalities. Each discordant case was reviewed to identify systematic trends in misclassification. Comparisons of detection rates, such as the presence or absence of individual branches, were performed using the McNemar test. A p-value below 0.05 was considered statistically significant. Finally, Pearson correlation analyses were conducted between the number of CT slices and the accuracy of MMA dominance, posterior branch origin, and overall anatomical classification to evaluate whether higher imaging resolution improved interpretive performance. RESULTS Population Of 300 patients screened, 77 met inclusion criteria, yielding 91 evaluable MMAs (42 right, 49 left). Mean age was 58.9 years (SD = 20.2, range 19–88); 64 male, 27 female (Fig.3). CT-based anatomical visualization The anterior branch was visible in 100% of cases, posterior in 94.5%, and middle (obelic) in 96.7% (Table 1). A petrosal branch was seen in 25.3%, and a tortuous main trunk in 38.5%. The FS was absent in 4.4% (4/91). The posterior branch originated proximally (Type A) in 20.7%, intermediately (Type B) in 32,2%, and distally (Type C) in 47,1%. Dominance was anterior (Type I) in 48,4%, posterior (Type II) in 14,3%, and mixed (Type III) in 37,4%. Table 1 Proportion of Different Branches According to Imaging Modality Groups CT group Angiography group p – value (McNemar) Concordance rate Presence of anterior B. 91/91 (100%) 82/90 (91,1%%) 0,005 82/90 (91,1%) Presence of posterior B. 86/91 (94,5%) 83/91 (91,2%) 0,405 78/91(85,7%) Presence of middle B. 88/91 (96,7%) 72/91 (79,1%) < 0,001 71/91 (78%) Presence of petrous B. 72/91 (79,1%) 59/88 (67%) < 0,001 33/88 (37,5%) Table 1 : Proportion of Different Branches According to Imaging Modality Groups (B: Branch; CT: Computed Tomography) Angiographic Findings On DSA, the anterior branch was visible in 91.1%, posterior in 91.2%, and obelic in 79.1%. The posterior branch originated proximally (Type A) in 21.6%, intermediately (Type B) in 13.6%, and distally (Type C) in 64.8%. Dominance was anterior (Type I) in 45.5%, posterior (Type II) in 44.3%, and mixed (Type III) in 10.2%. McNemar analysis demonstrated significant discordance between CT and angiography for the anterior, middle (obelic), and petrosal branches, indicating systematic overestimation on CT, whereas no significant difference was observed for the posterior branch, which showed the highest concordance between modalities (Table 2). Foramen Spinosum Variations In the four cases lacking a visible FS on CT, three had major anatomical variants on DSA (absence of a main MMA trunk or ophthalmic origin), highlighting the FS as a reliable indirect marker. Table 2 Proportion of patterns by imaging modality CT group Angiography group Concordance rate Origin 33/84 (39,3%) A 18/87 (20,7%) 19/88 (21,6%) 5/18 (27,8%) B 28/87 (32,2%) 12/88 (13,6%) 2/12 (16,7%) C 41/87 (47,1%) 57/88 (64,8%) 26/54 (48,1%) Dominance 40/88 (45,5%) I 44/91 (48,4%) 40/88 (45,5%) 26/39 (66 7%) II 13/91 (14,3%) 39/88 (44,3%) 9/39 (23,1%) III 34/91 (37,4%) 9/88 (10,2%) 4/9 (44,4%) Pattern 15/84 (17,9%) IA 7/87 (8%) 7/88 (8%) 0% IB 13/87 (14,9%) 5/88 (5,7%) 0% IC 20/87 (23%) 28/88 (31,8%) 8/24 (33,3%) IIA 4/87 (4,6%) 9/88 (10,2%) 1/9 (11,1%) IIB 3/87 (3,4%) 5/88 (5,7%) 0% IIC 6/87 (6,9%) 25/88 (28,4%) 4/25 (16%) IIIA 6/87 (6,9%) 3/88 (3,4%) 1/3 (33,3%) IIIB 12/87 (13,8%) 2/88 (2,3%) 0% IIIC 16/87 (18,4%) 4/88 (4,5%) 1/4 (25%) Table 2: Proportion of patterns by imaging modality (MMA: Middle Meningeal Artery; CT: Computed Tomography) NB: In the CT group, the origin of the MMA could not be determined in four cases due to lack of visibility. These four MMAs were later identified on angiography as one Type A and three Type C, accounting for the loss of one Type A and three Type C cases in the concordance rate calculations. For the same reason, only 24 MMAs classified as pattern IC could be compared between CT and angiography. CT-Angiography concordance Concordance was high for identifying major branches (91.1% anterior, 85.7% posterior, 78.0% middle) but lower for dominance (45.5%) and posterior origin (39.3%). Complete E-AC pattern agreement occurred in 17.9% of MMAs. Type C origins were best recognized (48.1%), while Type B was most frequently misclassified. Dominance Type II was the most error-prone, often labeled Type III. MMA tortuosity concordance was 65.2%, with CT tending to overestimate tortuosity. No significant correlation was found between the number of CT slices and classification accuracy. DISCUSSION This study is, to our knowledge, the first to directly compare MMA anatomy using both non-contrast CT 3-D reconstructions and DSA. We found that while CT reliably delineates the main branches and the foramen spinosum. Branch Identification and Prevalence The detection of anterior and posterior branches (> 90%) aligns with historical anatomical data from Chandler et Derezinski. [23], who reported anterior branch presence in nearly all cases and posterior branch presence in approximately 89%, and supports the reliability of bone-window CT for gross MMA mapping. Foramen Spinosum and Anatomical Variants Absence of the FS was rare (4.4%) but consistently associated with major variants, including ophthalmic origin of the MMA. This finding emphasizes the clinical importance of verifying FS presence on pre-embolization CT to anticipate potential arterial anomalies and avoid non-target embolization (fig .4). Classification of Posterior Branch Origin Posterior origin Type C predominated in both CT and DSA, though CT underestimated its frequency. Misclassification mainly occurred between Types B and C, reflecting the difficulty of tracing distal grooves in 3-D reconstructions without contrast enhancement MMA Dominance Patterns CT overestimated mixed (Type III) dominance, likely due to confusion between the obelic and posterior branches. Similar variability was noted by Shotar et al. [19] (κ = 0.53). This suggests that non-contrast CT alone cannot distinguish dominance patterns requiring dynamic flow information. Anthropological data support low prevalence of mixed dominance, with more balanced proportions between anterior and posterior patterns [24,25]. These findings are congruent with our angiographic results and underscore the limited reliability of CT-based dominance classification in the absence of vascular contrast (Table 3) Table 3 Anthropological series classifying middle meningeal artery dominance Study Number of subjects Type I (%) Type II (%) Type III (%) Toida (1934) [28] 192 48,3 (112) 34,0 (79) 17,7 (41) Adachi (1928) [21] 100 51,0 (51) 40,0 (40) 9,0 (9) Akiba (1925) [29] 219 43,8 (96) 53,4 (117) 2,8 (6) Giuffrida-Ruggeri (1913) [30] 119 59,6 (71) 37,8 (45) 2,5 (3) Rothman (1937) [24] 191 37,7 (72) 60,2 (115) 2,1 (4) Rothman (1937) [24] 212 41,5 (88) 55,7 (118) 2,8 (6) Table 3: Anthropological series classifying middle meningeal artery dominance NB: Rothman et al. (1937) compared two different cohorts, one consisting of Caucasian American subjects (n = 191) and the other of African American subjects (n = 212). Anatomical and Technical Considerations The MMA enters the cranial cavity via the foramen spinosum and courses along the floor of the middle cranial fossa before bifurcating near the pterion. The MMA’s course within osseous canals varies substantially [25-27]. In some cases, bony coverage may obscure surface grooves, explaining partial CT misidentification. We found no evidence that higher spatial resolution improved classification accuracy, underscoring that interpretive limitations, not imaging quality, are the main barrier. Clinical Implications Incorporating CT-based assessment of the FS and major branch course into pre-procedural workflow could enhance safety screening before DSA and embolization. However, full morphological classification still requires angiographic evaluation. Study Limitations This retrospective design limited control of imaging parameters. This study is limited by the absence of interobserver and intraobserver reproducibility analysis, which may influence the interpretation of the reported concordance results. Cohen’s kappa was not reported, as the aim of this study was to assess the ability of non-contrast CT to identify MMA branches relative to angiography as a reference standard, rather than to evaluate interobserver agreement. In addition, the highly unbalanced distribution of several categorical variables could have resulted in misleading kappa estimates. Some angiographic examinations were performed for indications other than detailed MMA assessment, which may have affected the visualization and interpretation of specific anatomical features. Furthermore, bone-based classification may not fully correspond to intraluminal arterial anatomy. CONCLUSION This study, the first to directly compare non-contrast CT 3D reconstructions with angiography for middle meningeal artery (MMA) assessment, shows that routine bone-window CT can reliably identify key anatomical features relevant to embolization. Among all evaluated parameters, the foramen spinosum (FS) proved to be a particularly powerful marker: its absence on CT was strongly associated with major MMA variants, including ophthalmic origin. Because non-contrast CT is already performed in every patient with chronic subdural hematoma, systematic FS evaluation offers a simple, non-invasive, and immediately applicable way to anticipate challenging anatomy before angiography or embolization. These findings introduce a practical imaging marker that has not been previously reported and may enhance procedural planning and patient selection. Future work may refine this approach using higher-resolution CT or automated segmentation. Abbreviations AVF : Arteriovenous fistulas AVM : Arteriovenous malformations CSDH : Chronic subdural hematoma CT : Computed Tomography DSA : Digital Subtraction Angiography FS : Foramen Spinosum MMA : Middle Meningeal Artery SD : Standard Deviation TX : Texas USA : United States of America Declarations Author Contribution Conceptualization : L.K, A.DB and G.B; Methodology: L.K, A.DB and G.B Formal analysis and investigation : L.K, A.DB, G.B, V.G, M.P; Writing - original draft preparation : L.K, A.DB and G.BWriting - review and editing: P.C, J.CS, F-E.R, A.DB, G.BSupervision: P.C, J.CS, F-E.R, A.DB, G.B Acknowledgement We would like to thank the patients. Then, the authors wish to acknowledge all neuroradiologists, neurosurgeons, and all those who participated in this collaborative work. Data Availability All data supporting the findings of this study are available. Anonymized original data from this manuscript will be made available upon reasonable request to the corresponding author. 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Anthropol. 23:341-360, 1925 GiuffridaRuggeri, V. über die enclokranischen Furchen der Arteria meningea media beim Menschen. Zeitschr. f. Morph. u. Anthrop. 15:401-413, 1913 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8524129","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":574660502,"identity":"c240a7ad-cb71-4aac-8e38-54ef5c3fceb1","order_by":0,"name":"Lubin Klotz","email":"","orcid":"","institution":"Université Toulouse III - Paul Sabatier","correspondingAuthor":false,"prefix":"","firstName":"Lubin","middleName":"","lastName":"Klotz","suffix":""},{"id":574660503,"identity":"abe92212-6f51-4c2a-8d6e-21c357ea827d","order_by":1,"name":"Guillaume Bellanger","email":"","orcid":"","institution":"Université Toulouse III - Paul 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08:10:15","extension":"html","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":123668,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/4aa47950623becbfed2a7436.html"},{"id":100546594,"identity":"d0b6ee01-c5b8-4f60-b42d-9907290a1cea","added_by":"auto","created_at":"2026-01-19 08:11:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":270807,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnatomical Variants of Middle Meningeal Artery (MMA) Branching According to the Extended Adachi Classification by Shotar et al. \u003c/strong\u003e[19]\u003c/p\u003e\n\u003cp\u003eDiagram of the projection of the middle meningeal artery (MMA) on a lateral skull radiograph Dominance is not determined by the relative calibers of the anterior and posterior branches, but rather by the origin of the obelic terminal branches. The anterior branch is shown in red; the obelic branch in orange; and the posterior branch in purple.\u003c/p\u003e\n\u003cp\u003ePanels (a, d, g) demonstrates anterior dominance (Type I) MMA with anterior branch dominance, giving rise to the obelic branch (in yellow). Panels (b, e, h) illustrate posterior dominance (Type II); and panels (c, f, i) depict codominance of anterior and posterior branches (Type III). The origin of the posterior branch is also subclassified: proximal origin (Type A; a–c), intermediate origin (Type B; d–f), and distal origin (Type C; g–i).\u003c/p\u003e\n\u003cp\u003eMMA: Middle Meningeal Artery)\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/3d6d80c9e2c5a352754258d8.png"},{"id":100546580,"identity":"4b62159d-2616-4378-816f-6aba5d13554c","added_by":"auto","created_at":"2026-01-19 08:11:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":108402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConcordance Between CT and Angiography\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeft and Center: Internal view of a left cranial vault showing the middle meningeal artery (MMA) reconstructed in 3D using volume rendering from non-contrast CT. Right: Cerebral angiography from the same patient, with contrast injection into the left external carotid artery, demonstrating the patient's MMA.The MMA pattern identified as Type IIC on CT (A) (distal bifurcation with posterior branch dominance) shows concordance with angiographic findings. Additionally, a tortuous anterior branch is visible (B).\u003c/p\u003e\n\u003cp\u003e(MMA: Middle Meningeal Artery; CT: Computed Tomography)\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/8fd43a617a0ab8a15a3f8ad5.png"},{"id":100432226,"identity":"2c5daae8-ed92-4627-9efe-ed57439da375","added_by":"auto","created_at":"2026-01-16 15:03:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":166814,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow Chart\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(MMA: Middle Meningeal Artery; CT: Computed Tomography)\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/20944e7f2154af1342bf7694.png"},{"id":100432229,"identity":"1ca7f0a4-ae03-46f3-bb0d-f5502520556e","added_by":"auto","created_at":"2026-01-16 15:03:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRight chronic subdural hematoma in a patient who underwent digital subtraction angiography with selective injection of the right internal carotid artery\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe angiogram demonstrates a right middle meningeal artery (MMA) originating from the ophthalmic artery. Review of the bone-window CT shows absence of the right foramen spinosum.\u003c/p\u003e","description":"","filename":"Binder14.png","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/ad7d4f2933b39976923f7469.png"},{"id":101673742,"identity":"63a2234f-4452-4693-b384-99524acb557c","added_by":"auto","created_at":"2026-02-02 13:13:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1531641,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8524129/v1/553b6b38-d998-4e27-b251-6a7482dd87d5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Accuracy of Non-Contrast Brain CT in Pre-Embolization Evaluation of the Middle Meningeal Artery","fulltext":[{"header":"Key Points","content":"\u003col\u003e\n \u003cli\u003e3D non-contrast CT reliably identifies major branches of the middle meningeal artery (MMA) and the foramen spinosum, making it a valuable tool for initial anatomical assessment.\u003c/li\u003e\n \u003cli\u003eAbsence of the foramen spinosum on CT may serve as an indicator of anatomical variants potentially affecting embolization feasibility.\u003c/li\u003e\n \u003cli\u003eConcordance between CT and angiography is low for MMA dominance, posterior branch origin, and full anatomical pattern classification.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eImportance of the study:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the first study to quantitatively assess the concordance between non-contrast CT and angiography in evaluating MMA anatomy prior to embolization in patients with chronic subdural hematoma. As embolization becomes increasingly used, especially in high-risk or elderly populations, identifying reliable, non-invasive preoperative imaging modalities is critical. The study highlights the strengths and limitations of CT imaging in this context, reinforcing its role in early screening while affirming the necessity of angiographic evaluation for procedural planning.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eChronic subdural hematoma (cSDH) is a frequent neurosurgical condition, particularly in the elderly, with an incidence of up to 58 per 100,000 individuals over the age of 65 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This rate is expected to rise with population aging and the increased use of anticoagulants and antiplatelet agents [\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although often triggered by minor trauma, the persistence and recurrence of cSDH are mainly driven by chronic inflammation, angiogenesis within the neomembrane, and recurrent microhemorrhages [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSurgical evacuation through burr holes remains the standard treatment, but recurrence occurs in 10%\u0026ndash;20% of patients, sometimes requiring repeated procedures [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These limitations have prompted exploration of adjunctive or alternative approaches that address the biological mechanisms underlying recurrence.\u003c/p\u003e \u003cp\u003eEmbolization of the middle meningeal artery (MMA) has emerged as an effective minimally invasive treatment that targets the vascular supply to the outer hematoma membrane [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recent randomized controlled trials, including STEM [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], EMBOLISE [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and MAGIC-MT [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], have demonstrated reduced recurrence rates when combined with surgery, and marked reductions in recurrence for embolization alone. As the technique gains widespread adoption, accurate understanding of MMA anatomy has become critical for procedural safety and efficacy [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDigital subtraction angiography (DSA) remains the reference standard for evaluating MMA anatomy but is invasive. Conversely, non-contrast cranial CT, already part of the routine diagnostic workup for cSDH, could offers a simple and non-invasive means of assessing the bony course of the MMA through high-resolution bone-window reconstructions.\u003c/p\u003e \u003cp\u003eThis study aimed to determine whether three-dimensional reconstructions from routine non-contrast CT can accurately depict MMA anatomy compared with DSA. We hypothesized that non-contrast CT 3D reconstructions can reliably identify key anatomical landmarks relevant to pre-embolization planning.\u003c/p\u003e"},{"header":"METHODS ","content":"\u003cp\u003e\u003cem\u003eStudy Population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis was a retrospective, single-center anatomical study conducted at the University Hospital of Purpan (Toulouse, France). Patients were included if they underwent both cerebral angiography and non-contrast-enhanced cranial CT with bone window acquisition between March 2023 and April 2024.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInclusion/Exclusion Criteria\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eParticipants eligible for inclusion were adults aged 18 years or older who underwent high-resolution, non-contrast cranial computed tomography (CT) with an intact cranial vault, along with cerebral angiography sufficient to allow for the assessment of the middle meningeal artery (MMA). Exclusion criteria comprised individuals younger than 18 years, those with skull fractures or discontinuities of the cranial vault, and cases lacking either CT or angiographic imaging in the hospital\u0026rsquo;s picture archiving and communication system (PACS). Additional exclusions included anatomical distortion due to arteriovenous fistulas (AVFs) or arteriovenous malformations (AVMs), as well as patients with bone flap interference or post-craniectomy alterations impeding reliable MMA evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthical Considerations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and was approves by insitutionnal review board (n\u0026deg; IRB00011687 Coll\u0026egrave;ge de neurochirurgie IRB #1: 2025/43). Due to its retrospective non interventional design and exclusive use of anonymized data obtained during routine clinical care, informed consent was waived. Prior to imaging procedures, patients had been informed that their imaging data could be used for research purposes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImaging Acquisition\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll patients underwent non-contrast-enhanced CT scans with bone window reconstruction at millimetric slice thickness. Three-dimensional volume-rendered reconstructions were generated using Change Healthcare Radiology Solutions software (McKesson, Irving, TX, USA). Each skull was segmented in the sagittal plane to isolate right and left MMA territories. MMA anatomy was assessed based on the osseous grooves and canals visualized. Cerebral digital subtraction angiography (DSA) was performed in all patients and used as the reference modality. Selective injection of the external carotid artery allowed direct visualization of the MMA and its branches.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImage Evaluation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEach imaging modality was reviewed by a dedicated rater, blinded to the other modality. Side-specific evaluation of the MMA was performed to assess concordance between CT and angiography findings. The anatomical evaluation included assessment of the presence or absence of the anterior, oblique, and posterior branches of the middle meningeal artery (MMA), as well as the dominance pattern based on the Adachi classification [21]. The origin of the posterior branch was classified according to the Shotar system [19]. A combined anatomical pattern was determined using the Extended-Adachi classification (E-AC) [19]. Additional parameters included the tortuosity of the MMA, the presence of a petrosal branch, and the presence or absence of the foramen spinosum.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnatomical Classification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMMA dominance was defined according to Adachi\u0026rsquo;s model (1928) [19,22], which classifies MMA branching based on the origin of the middel (obelic) branch: Type I, in which the middle (obelic) branch arises from the anterior branch; Type II, where it originates from the posterior branch; and Type III, characterized by a dual origin from both the anterior and posterior branches. This model focuses on anatomical distribution rather than vessel caliber. The posterior branch origin was classified per Shotar et al.: Type A, indicating a proximal origin near the foramen spinosum; Type B, representing an intermediate origin; and Type C, defined by a distal origin beyond the orbital apex. Combining both systems, a total of nine MMA patterns were defined (E-AC Classification): IA, IB, IC, IIA, IIB, IIC, IIIA, IIIB, and IIIC. Each MMA was categorized on CT and angiography accordingly (Fig.1).\u003c/p\u003e\n\u003cp\u003eDiagram of the projection of the middle meningeal artery (MMA) on a lateral skull radiograph. Dominance is not determined by the relative calibers of the anterior and posterior branches, but rather by the origin of the obelic terminal branches. The anterior branch is shown in red; the obelic branch in orange; and the posterior branch in purple.\u003c/p\u003e\n\u003cp\u003ePanels (a, d, g) demonstrates anterior dominance (Type I) MMA with anterior branch dominance, giving rise to the obelic branch (in yellow). Panels (b, e, h) illustrate posterior dominance (Type II); and panels (c, f, i) depict codominance of anterior and posterior branches (Type III). The origin of the posterior branch is also subclassified: proximal origin (Type A; a\u0026ndash;c), intermediate origin (Type B; d\u0026ndash;f), and distal origin (Type C; g\u0026ndash;i). MMA: Middle Meningeal Artery\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrimary and Secondary Endpoints\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome was the concordance in the presence or absence of the anterior, obelic, and posterior branches of the middle meningeal artery (MMA) as well as the presence or absence of the foramen spinosum on CT, used as an indirect indicator of MMA origin variants. Secondary endpoints included the pattern concordance rate (E-AC classification) between CT and angiography as well as the concordance of the posterior branch origin type (A, B, or C). A pattern was considered concordant when both modalities identified the same subclass (Fig.2). Additional endpoints involved evaluating concordance in the classification of the MMA course as tortuous versus straight, with tortuosity defined by the presence of three or more visible curvatures and used as an indicator of challenging MMA catheterization. The detection of petrosal branches, were also recorded.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDigital subtraction angiography (DSA) was considered the reference standard for all comparisons. For each anatomical parameter, concordance between CT and DSA was recorded in binary fashion (1 = match, 0 = mismatch). Descriptive statistics were used to summarize the degree of agreement.\u003c/p\u003e\n\u003cp\u003eThe concordance rate was defined as the proportion of middle meningeal arteries (MMAs) showing identical findings on both CT and DSA. The corresponding failure rate represented the proportion of MMAs with discrepancies between the two modalities. Each discordant case was reviewed to identify systematic trends in misclassification.\u003c/p\u003e\n\u003cp\u003eComparisons of detection rates, such as the presence or absence of individual branches, were performed using the McNemar test. A p-value below 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eFinally, Pearson correlation analyses were conducted between the number of CT slices and the accuracy of MMA dominance, posterior branch origin, and overall anatomical classification to evaluate whether higher imaging resolution improved interpretive performance.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cem\u003ePopulation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOf 300 patients screened, 77 met inclusion criteria, yielding 91 evaluable MMAs (42 right, 49 left). Mean age was 58.9 years (SD = 20.2, range 19\u0026ndash;88); 64 male, 27 female (Fig.3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCT-based anatomical visualization\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe anterior branch was visible in 100% of cases, posterior in 94.5%, and middle (obelic) in 96.7% (Table 1). A petrosal branch was seen in 25.3%, and a tortuous main trunk in 38.5%. The FS was absent in 4.4% (4/91). The posterior branch originated proximally (Type A) in 20.7%, intermediately (Type B) in 32,2%, and distally (Type C) in 47,1%. Dominance was anterior (Type I) in 48,4%, posterior (Type II) in 14,3%, and mixed (Type III) in 37,4%.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 379px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cem\u003eProportion of Different Branches According to Imaging Modality Groups\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eCT group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eAngiography group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003ep \u0026ndash; value\u003c/p\u003e\n \u003cp\u003e(McNemar)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eConcordance rate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003ePresence of anterior B.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e91/91 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e82/90 (91,1%%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e82/90 (91,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003ePresence of posterior B.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e86/91 (94,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e83/91 (91,2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0,405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e78/91(85,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003ePresence of middle B.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e88/91 (96,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e72/91 (79,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt; 0,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e71/91 (78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003ePresence of petrous B.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e72/91 (79,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e59/88 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt; 0,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e33/88 (37,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Proportion of Different Branches According to Imaging Modality Groups\u003c/p\u003e\n\u003cp\u003e(B: Branch; CT: Computed Tomography)\u003c/p\u003e\n\u003ch3\u003e\u003cem\u003eAngiographic Findings\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eOn DSA, the anterior branch was visible in 91.1%, posterior in 91.2%, and obelic in 79.1%. The posterior branch originated proximally (Type A) in 21.6%, intermediately (Type B) in 13.6%, and distally (Type C) in 64.8%. Dominance was anterior (Type I) in 45.5%, posterior (Type II) in 44.3%, and mixed (Type III) in 10.2%. McNemar analysis demonstrated significant discordance between CT and angiography for the anterior, middle (obelic), and petrosal branches, indicating systematic overestimation on CT, whereas no significant difference was observed for the posterior branch, which showed the highest concordance between modalities (Table 2).\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eForamen Spinosum Variations\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eIn the four cases lacking a visible FS on CT, three had major anatomical variants on DSA (absence of a main MMA trunk or ophthalmic origin), highlighting the FS as a reliable indirect marker.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"700\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 589px;\"\u003e\n \u003cp\u003e\u003cem\u003eProportion of patterns by imaging modality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eCT group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAngiography group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eConcordance rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eOrigin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e33/84 (39,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e18/87 (20,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e19/88 (21,6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e5/18 (27,8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e28/87 (32,2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e12/88 (13,6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2/12 (16,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e41/87 (47,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e57/88 (64,8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e26/54 (48,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eDominance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e40/88 (45,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e44/91 (48,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e40/88 (45,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e26/39 (66\u0026nbsp;7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e13/91 (14,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e39/88 (44,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e9/39 (23,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e34/91 (37,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e9/88 (10,2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4/9 (44,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e15/84 (17,9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"9\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e7/87 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e7/88 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e13/87 (14,9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e5/88 (5,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e20/87 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e28/88 (31,8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e8/24 (33,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e4/87 (4,6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e9/88 (10,2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1/9 (11,1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e3/87 (3,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e5/88 (5,7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e6/87 (6,9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e25/88 (28,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4/25 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e6/87 (6,9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e3/88 (3,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1/3 (33,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e12/87 (13,8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e2/88 (2,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eIIIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e16/87 (18,4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e4/88 (4,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1/4 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eProportion of patterns by imaging modality\u003c/p\u003e\n\u003cp\u003e(MMA: Middle Meningeal Artery; CT: Computed Tomography)\u003c/p\u003e\n\u003cp\u003eNB: In the CT group, the origin of the MMA could not be determined in four cases due to lack of visibility. These four MMAs were later identified on angiography as one Type A and three Type C, accounting for the loss of one Type A and three Type C cases in the concordance rate calculations. For the same reason, only 24 MMAs classified as pattern IC could be compared between CT and angiography.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCT-Angiography concordance\u0026nbsp;\u003c/em\u003e\u003cbr\u003e\u0026nbsp;Concordance was high for identifying major branches (91.1% anterior, 85.7% posterior, 78.0% middle) but lower for dominance (45.5%) and posterior origin (39.3%). Complete E-AC pattern agreement occurred in 17.9% of MMAs. Type C origins were best recognized (48.1%), while Type B was most frequently misclassified. Dominance Type II was the most error-prone, often labeled Type III. MMA tortuosity concordance was 65.2%, with CT tending to overestimate tortuosity. No significant correlation was found between the number of CT slices and classification accuracy.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e\u003cstrong\u003eThis study is, to our knowledge, the first to directly compare MMA anatomy using both non-contrast CT 3-D reconstructions and DSA. We found that while CT reliably delineates the main branches and the foramen spinosum.\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eBranch Identification and Prevalence\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe detection of anterior and posterior branches (\u0026gt; 90%) aligns with historical anatomical data from Chandler et Derezinski. [23], who reported anterior branch presence in nearly all cases and posterior branch presence in approximately 89%, and supports the reliability of bone-window CT for gross MMA mapping.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eForamen Spinosum and Anatomical Variants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbsence of the FS was rare (4.4%) but consistently associated with major variants, including ophthalmic origin of the MMA. This finding emphasizes the clinical importance of verifying FS presence on pre-embolization CT to anticipate potential arterial anomalies and avoid non-target embolization (fig .4).\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eClassification of Posterior Branch Origin\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003ePosterior origin Type C predominated in both CT and DSA, though CT underestimated its frequency. Misclassification mainly occurred between Types B and C, reflecting the difficulty of tracing distal grooves in 3-D reconstructions without contrast enhancement\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eMMA Dominance Patterns\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eCT overestimated mixed (Type III) dominance, likely due to confusion between the obelic and posterior branches. Similar variability was noted by Shotar et al. [19] (\u0026kappa; = 0.53). This suggests that non-contrast CT alone cannot distinguish dominance patterns requiring dynamic flow information.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnthropological data support low prevalence of mixed dominance, with more balanced proportions between anterior and posterior patterns [24,25]. These findings are congruent with our angiographic results and underscore the limited reliability of CT-based dominance classification in the absence of vascular contrast (Table 3)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cem\u003eAnthropological series classifying middle meningeal artery dominance\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eNumber of subjects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 279px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eType I (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eType II (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eType III (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eToida (1934) [28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e48,3 (112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e34,0 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e17,7 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAdachi (1928) [21]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e51,0 (51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e40,0 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e9,0 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAkiba (1925) [29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e43,8 (96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e53,4 (117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2,8 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eGiuffrida-Ruggeri (1913) [30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e59,6 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e37,8 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2,5 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eRothman (1937) [24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e37,7 (72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e60,2 (115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2,1 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eRothman (1937) [24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e41,5 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e55,7 (118)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e2,8 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eAnthropological series classifying middle meningeal artery dominance\u003c/p\u003e\n\u003cp\u003eNB: Rothman et al. (1937) compared two different cohorts, one consisting of Caucasian American subjects (n = 191) and the other of African American subjects (n = 212).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnatomical and Technical Considerations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe MMA enters the cranial cavity via the foramen spinosum and courses along the floor of the middle cranial fossa before bifurcating near the pterion. The MMA\u0026rsquo;s course within osseous canals varies substantially [25-27]. In some cases, bony coverage may obscure surface grooves, explaining partial CT misidentification. We found no evidence that higher spatial resolution improved classification accuracy, underscoring that interpretive limitations, not imaging quality, are the main barrier.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical Implications\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncorporating CT-based assessment of the FS and major branch course into pre-procedural workflow could enhance safety screening before DSA and embolization. However, full morphological classification still requires angiographic evaluation.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eStudy Limitations\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis retrospective design limited control of imaging parameters. This study is limited by the absence of interobserver and intraobserver reproducibility analysis, which may influence the interpretation of the reported concordance results. Cohen\u0026rsquo;s kappa was not reported, as the aim of this study was to assess the ability of non-contrast CT to identify MMA branches relative to angiography as a reference standard, rather than to evaluate interobserver agreement. In addition, the highly unbalanced distribution of several categorical variables could have resulted in misleading kappa estimates. Some angiographic examinations were performed for indications other than detailed MMA assessment, which may have affected the visualization and interpretation of specific anatomical features. Furthermore, bone-based classification may not fully correspond to intraluminal arterial anatomy.\u003c/p\u003e"},{"header":"CONCLUSION ","content":"\u003cp\u003eThis study, the first to directly compare non-contrast CT 3D reconstructions with angiography for middle meningeal artery (MMA) assessment, shows that routine bone-window CT can reliably identify key anatomical features relevant to embolization. Among all evaluated parameters, the foramen spinosum (FS) proved to be a particularly powerful marker: its absence on CT was strongly associated with major MMA variants, including ophthalmic origin.\u003c/p\u003e\n\u003cp\u003eBecause non-contrast CT is already performed in every patient with chronic subdural hematoma, systematic FS evaluation offers a simple, non-invasive, and immediately applicable way to anticipate challenging anatomy before angiography or embolization. These findings introduce a practical imaging marker that has not been previously reported and may enhance procedural planning and patient selection.\u003c/p\u003e\n\u003cp\u003eFuture work may refine this approach using higher-resolution CT or automated segmentation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAVF\u003c/strong\u003e: Arteriovenous fistulas\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAVM\u003c/strong\u003e: Arteriovenous malformations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCSDH\u003c/strong\u003e: Chronic subdural hematoma\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e: Computed Tomography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDSA\u003c/strong\u003e: Digital Subtraction Angiography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFS\u003c/strong\u003e: Foramen Spinosum\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMMA\u003c/strong\u003e: Middle Meningeal Artery\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e: Standard Deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTX\u003c/strong\u003e: Texas\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUSA\u003c/strong\u003e: United States of America\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization : L.K, A.DB and G.B; Methodology: L.K, A.DB and G.B Formal analysis and investigation : L.K, A.DB, G.B, V.G, M.P; Writing - original draft preparation : L.K, A.DB and G.BWriting - review and editing: P.C, J.CS, F-E.R, A.DB, G.BSupervision: P.C, J.CS, F-E.R, A.DB, G.B\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe would like to thank the patients. Then, the authors wish to acknowledge all neuroradiologists, neurosurgeons, and all those who participated in this collaborative work.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data supporting the findings of this study are available. Anonymized original data from this manuscript will be made available upon reasonable request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFeghali J, Yang W, Huang J. Updates in Chronic Subdural Hematoma: Epidemiology, Etiology, Pathogenesis, Treatment, and Outcome. \u003cem\u003eWorld Neurosurg\u003c/em\u003e. 2020;141:339-345. doi:10.1016/j.wneu.2020.06.140\u003c/li\u003e\n\u003cli\u003eToi H, Kinoshita K, Hirai S, et al. Present epidemiology of chronic subdural hematoma in Japan: analysis of 63,358 cases recorded in a national administrative database. \u003cem\u003eJ Neurosurg\u003c/em\u003e. 2018;128(1):222-228. doi:10.3171/2016.9.JNS16623\u003c/li\u003e\n\u003cli\u003eNeifert SN, Chaman EK, Hardigan T, et al. Increases in Subdural Hematoma with an Aging Population\u0026mdash;the Future of American Cerebrovascular Disease. \u003cem\u003eWorld Neurosurg\u003c/em\u003e. 2020;141:e166-e174. doi:10.1016/j.wneu.2020.05.060\u003c/li\u003e\n\u003cli\u003eSahyouni R, Goshtasbi K, Mahmoodi A, Tran DK, Chen JW. Chronic Subdural Hematoma: A Historical and Clinical Perspective. \u003cem\u003eWorld Neurosurg\u003c/em\u003e. 2017;108:948-953. doi:10.1016/j.wneu.2017.09.064\u003c/li\u003e\n\u003cli\u003eAspegren OP, \u0026Aring;strand R, Lundgren MI, Romner B. Anticoagulation therapy a risk factor for the development of chronic subdural hematoma. \u003cem\u003eClin Neurol Neurosurg\u003c/em\u003e. 2013;115(7):981-984. doi:10.1016/j.clineuro.2012.10.008\u003c/li\u003e\n\u003cli\u003eRust T, Kiemer N, Erasmus A. Chronic subdural haematomas and anticoagulation or anti-thrombotic therapy. \u003cem\u003eJ Clin Neurosci\u003c/em\u003e. 2006;13(8):823-827. doi:10.1016/j.jocn.2004.12.013\u003c/li\u003e\n\u003cli\u003eEdlmann E, Giorgi-Coll S, Whitfield PC, Carpenter KLH, Hutchinson PJ. Pathophysiology of chronic subdural haematoma: inflammation, angiogenesis and implications for pharmacotherapy. \u003cem\u003eJ Neuroinflammation\u003c/em\u003e. 2017;14(1):108. doi:10.1186/s12974-017-0881-y\u003c/li\u003e\n\u003cli\u003eHaines DE, Harkey HL, Al-Mefty O. The \u0026ldquo;subdural\u0026rdquo; space: a new look at an outdated concept. \u003cem\u003eNeurosurgery\u003c/em\u003e. Published online 1993. doi:https://doi.org/10.1227/00006123-199301000-00017\u003c/li\u003e\n\u003cli\u003eMehta V, Harward SC, Sankey EW, Nayar G, Codd PJ. Evidence based diagnosis and management of chronic subdural hematoma: A review of the literature. \u003cem\u003eJ Clin Neurosci\u003c/em\u003e. 2018;50:7-15. doi:10.1016/j.jocn.2018.01.050\u003c/li\u003e\n\u003cli\u003eAlmenawer SA, Farrokhyar F, Hong C, et al. Chronic Subdural Hematoma Management: A Systematic Review and Meta-analysis of 34829 Patients. \u003cem\u003eAnn Surg\u003c/em\u003e. 2014;259(3):449-457. doi:10.1097/SLA.0000000000000255\u003c/li\u003e\n\u003cli\u003eLiu W, Bakker NA, Groen RJM. Chronic subdural hematoma: a systematic review and meta-analysis of surgical procedures: A systematic review. \u003cem\u003eJ Neurosurg\u003c/em\u003e. 2014;121(3):665-673. doi:10.3171/2014.5.JNS132715\u003c/li\u003e\n\u003cli\u003eChon KH, Lee JM, Koh EJ, Choi HY. Independent predictors for recurrence of chronic subdural hematoma. \u003cem\u003eActa Neurochir (Wien)\u003c/em\u003e. 2012;154(9):1541-1548. doi:10.1007/s00701-012-1399-9\u003c/li\u003e\n\u003cli\u003eKan P, Maragkos GA, Srivatsan A, et al. Middle Meningeal Artery Embolization for Chronic Subdural Hematoma: A Multi-Center Experience of 154 Consecutive Embolizations. \u003cem\u003eNeurosurgery\u003c/em\u003e. 2021;88(2):268-277. doi:10.1093/neuros/nyaa379\u003c/li\u003e\n\u003cli\u003eKhorasanizadeh M, Shutran M, Garcia A, et al. Middle meningeal artery embolization for treatment of chronic subdural hematomas: does selection of embolized branches affect outcomes? \u003cem\u003eJ Neurosurg\u003c/em\u003e. Published online November 1, 2022:1-9. doi:10.3171/2022.9.JNS221663\u003c/li\u003e\n\u003cli\u003eFiorella D, Monteith SJ, Hanel R, et al. Embolization of the Middle Meningeal Artery for Chronic Subdural Hematoma. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2025;392(9):855-864. doi:10.1056/NEJMoa2409845\u003c/li\u003e\n\u003cli\u003eDavies JM, Knopman J, Mokin M, et al. Adjunctive Middle Meningeal Artery Embolization for Subdural Hematoma. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2024;391(20):1890-1900. doi:10.1056/NEJMoa2313472\u003c/li\u003e\n\u003cli\u003eLiu J, Ni W, Zuo Q, et al. Middle Meningeal Artery Embolization for Nonacute Subdural Hematoma. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2024;391(20):1901-1912. doi:10.1056/NEJMoa2401201\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez JL, Domingo RA, Sattur M, et al. The Middle Meningeal Artery: Branches, Dangerous Anastomoses, and Implications in Neurosurgery and Neuroendovascular Surgery. \u003cem\u003eOper Neurosurg\u003c/em\u003e. 2022;22(1):1-13. doi:10.1227/ONS.0000000000000010\u003c/li\u003e\n\u003cli\u003eShotar E, Premat K, Lenck S, et al. Angiographic Anatomy of the Middle Meningeal Artery in Relation to Chronic Subdural Hematoma Embolization. \u003cem\u003eClin Neuroradiol\u003c/em\u003e. 2022;32(1):57-67. doi:10.1007/s00062-021-00996-5\u003c/li\u003e\n\u003cli\u003eLevitt MR, Hirsch JA, Chen M. Middle meningeal artery embolization for chronic subdural hematoma: an effective treatment with a bright future. \u003cem\u003eJ NeuroInterventional Surg\u003c/em\u003e. 2024;16(4):329-330. doi:10.1136/jnis-2024-021602\u003c/li\u003e\n\u003cli\u003eAdachi, B. and Hasebe, K. Anatomie der Japaner 2: Das Arteriensystem der Japaner. \u003cem\u003eAnatomie der Japaner 2: Das Arteriensystem der Japaner (Vol. 2).\u003c/em\u003e 1928.\u003c/li\u003e\n\u003cli\u003eBruner E, Mantini S, Ripani M. Landmark‐Based Analysis of the Morphological Relationship Between Endocranial Shape and Traces of the Middle Meningeal Vessels. \u003cem\u003eAnat Rec\u003c/em\u003e. 2009;292(4):518-527. doi:10.1002/ar.20868\u003c/li\u003e\n\u003cli\u003eChandler SB, Derezinski CF. The variations of the middle meningeal artery within the middle cranial fossa. \u003cem\u003eAnat Rec\u003c/em\u003e. 1935;62(3):309-319. doi:10.1002/ar.1090620309\u003c/li\u003e\n\u003cli\u003eRothman D. The endocranial course of the middle meningeal artery in American Whites and American Negroes. \u003cem\u003eAm J Phys Anthropol\u003c/em\u003e. 1937;22(3):425-435. doi:10.1002/ajpa.1330220305\u003c/li\u003e\n\u003cli\u003eBartlett W. A contribution to the surgical anatomy of the middle cranial fossa, with special reference to operations for the removal of the gasserian ganglion. \u003cem\u003eAnn Surg\u003c/em\u003e. 1902;36(5):680-694. doi:10.1097/00000658-190211000-00003\u003c/li\u003e\n\u003cli\u003eBonasia S, Smajda S, Ciccio G, Robert T. Middle Meningeal Artery: Anatomy and Variations. \u003cem\u003eAm J Neuroradiol\u003c/em\u003e. 2020;41(10):1777-1785. doi:10.3174/ajnr.A6739\u003c/li\u003e\n\u003cli\u003eEberlova L, Pisova S, Papezova L, et al. Bony canal and grooves of the middle meningeal artery: mythic structures in anatomy and neurosurgery? \u003cem\u003eFolia Morphol\u003c/em\u003e. 2020;79(3):450-461. doi:10.5603/FM.a2019.0098\u003c/li\u003e\n\u003cli\u003eToida, N. \u0026uuml;ber die endokranischen Furchen der Arteria meningea media bei den Chinesen. J. Oriental. Med. 21:13-15, 1934\u003c/li\u003e\n\u003cli\u003eAkiba, T. \u0026uuml;ber die endokranischen Furchen der Arteria meningea media bei Japanern. Zeitschr. f. Morph. u. Anthropol. 23:341-360, 1925\u003c/li\u003e\n\u003cli\u003eGiuffridaRuggeri, V. \u0026uuml;ber die enclokranischen Furchen der Arteria meningea media beim Menschen. Zeitschr. f. Morph. u. Anthrop. 15:401-413, 1913\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic Subdural Hematoma, CT scan, angiography, middle meningeal artery, embolization","lastPublishedDoi":"10.21203/rs.3.rs-8524129/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8524129/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003ePurpose\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eChronic subdural hematoma (cSDH) is typically diagnosed on non-contrast brain CT. Embolization of the middle meningeal artery (MMA) has become an effective and increasingly adopted treatment. However, pre-procedural understanding of MMA anatomy remains crucial, as anatomical variations—such as atypical origins or accessory branches—can affect procedural safety and strategy. This study evaluated whether three-dimensional (3D) reconstructions from routine non-contrast CT can accurately depict MMA anatomy compared with digital subtraction angiography (DSA), the current reference standard.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMaterials and Methods\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn this retrospective study, 76 patients (91 MMAs) who underwent both non-contrast CT and DSA were analyzed. The anterior, posterior, and middle branches were assessed. Branch dominance was categorized as Type I (anterior), Type II (posterior), or Type III (mixed), and posterior branch origin as proximal (A), intermediate (B), or distal (C). The Extended-Adachi classification was used for overall anatomical patterns. The foramen spinosum (FS) and MMA tortuosity were also evaluated. Concordance rates between CT and DSA were calculated.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOn CT, the anterior, posterior, and middle branches were visible in 100%, 94.5%, and 96.7% of cases, respectively. CT–DSA concordance was high for branch identification (91.1% anterior, 85.7% posterior, 78.0% middle) and moderate for dominance (45.5%) and posterior origin (39.3%). Absence of the FS on CT was strongly associated with anatomical variants (3 of 4 cases).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConclusion\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e3D reconstructions from non-contrast CT allow visualization of the main MMA branches and the foramen spinosum. FS assessment on CT provides a valuable indirect marker for identifying anatomical variations and should be systematically included in pre-embolization evaluation.\u003c/p\u003e","manuscriptTitle":"Accuracy of Non-Contrast Brain CT in Pre-Embolization Evaluation of the Middle Meningeal Artery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 15:02:56","doi":"10.21203/rs.3.rs-8524129/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65ecf8e5-5865-466e-a69d-bd99213fb532","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T13:12:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 15:02:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8524129","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8524129","identity":"rs-8524129","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}