Vascular-Based Compartmental Resection of Anterior Clinoidal Meningiomas: An Inter-Perforator Microdebulking Strategy

Vascular-Based Compartmental Resection of Anterior Clinoidal Meningiomas: An Inter-Perforator Microdebulking Strategy | 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 Vascular-Based Compartmental Resection of Anterior Clinoidal Meningiomas: An Inter-Perforator Microdebulking Strategy Kentaro Watanabe, Kohei Ishikawa, Ande Fachniadin, Saivikram Madireddy, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9399548/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Anterior clinoidal meningiomas (ACMs) frequently encase critical perforating arteries, making safe resection technically challenging and placing patients at risk for ischemic complications. This study aimed to evaluate the feasibility and surgical outcomes of a perforator-oriented inter-perforator microdebulking approach designed to preserve perforating arteries during ACM resection. Methods We retrospectively reviewed 11 patients with ACMs who underwent surgical resection using an inter-perforator microdebulking technique between 2019 and 2024. The surgical strategy consisted of systematic tumor compartmentalization along major arterial trunks followed by further subdivision at the perforator level, enabling controlled microdebulking within inter-perforator spaces. Surgical outcomes, ischemic complications, visual outcomes, cranial nerve deficits, and tumor recurrence were analyzed. Results Simpson Grade II resection was achieved in 10 of 11 patients (91%), and one patient underwent Simpson Grade III resection to avoid vascular injury. No patient developed a symptomatic ischemic stroke. Asymptomatic infarctions were observed in 5 patients (45%), predominantly involving the basal ganglia, all of whom had large tumors (≥45 mm). Visual improvement occurred in 2 of 4 symptomatic patients (50%), and no visual deterioration was observed. Transient oculomotor nerve palsy occurred in 2 patients, with complete resolution during follow-up; no permanent cranial nerve deficits were noted. No tumor recurrence was observed during a median follow-up of 19 months. Conclusions Perforator-oriented inter-perforator microdebulking provides an anatomically rational framework for ACM surgery, enabling systematic tumor removal while preserving critical perforating arteries. This approach may facilitate safer resection of anatomically high-risk ACMs in selected patients. Anterior clinoidal meningioma Skull base surgery Perforating arteries Compartmental resection Microdebulking Figures Figure 1 Figure 2 Introduction Anterior clinoidal meningiomas (ACMs) are among the most technically challenging skull base tumors because of their intimate relationship with critical neurovascular structures, including the internal carotid artery (ICA) and optic nerve [2, 3, 15]. Despite advances in microsurgical techniques, safe resection remains difficult, with reported gross total resection rates of 50–80% and neurological morbidity of 10–30% [4, 8, 11]. While previous studies have primarily focused on visual outcomes, ischemic complications—particularly those related to perforating artery injury—have received comparatively less attention [7, 9, 12, 16]. Preservation of perforating arteries is a critical determinant of surgical outcome in ACMs. These vessels, arising from the ICA, anterior cerebral artery (ACA), and middle cerebral artery (MCA), supply eloquent regions such as the internal capsule and basal ganglia, and their injury may result in devastating neurological deficits [5, 6, 11, 18]. However, detailed surgical strategies specifically addressing perforator preservation remain insufficiently described. We hypothesized that tumor regions located between adjacent perforating arteries (inter-perforator spaces) represent key anatomical constraints that limit safe resection. Based on this concept, we developed a perforator-oriented surgical strategy in which preserved perforators serve as anatomical landmarks to guide systematic tumor dissection. In this study, we retrospectively evaluated the feasibility and surgical outcomes of an inter-perforator microdebulking approach in a consecutive series of patients with ACMs. Methods Patients We retrospectively analyzed patients with anterior clinoidal meningiomas who underwent surgical resection using the inter-perforator microdebulking technique at our institution between 2019 and 2024. All patients provided informed consent for surgery and data publication. This retrospective study was approved by the institutional review board. Tumor extension was classified according to the Al-Mefty classification and the Xu classification based on preoperative imaging and intraoperative findings [2, 20].The defining criteria of these classifications are summarized in Table 1. Surgical Technique All cases were treated using an inter-perforator microdebulking technique. The procedure consisted of the following key steps: (1) extradural anterior clinoidectomy; (2) center-first dural opening; (3) detachment of the tumor from its dural attachment at the (ACP) and surrounding sphenoid ridge dura; (4) initial tumor subdivision along major arterial trunks, including the ICA and ACA, to create primary compartments; (5) subsequent perforator-level tumor subdivision creating multiple micro-compartments; (6) inter-perforator space management using a center-corridor microdebulking approach with a strict no-touch principle for preserved perforators; and (7) compartment-by-compartment dissection and removal of tumor, with careful attention to the specific neurovascular and arachnoidal relationships unique to each compartment. A schematic overview of these steps is shown in Figure 1. Careful attention was also paid to venous anatomy throughout the procedure. Sylvian veins and other cortical draining veins were preserved whenever possible, and dissection planes were developed along the arachnoid to avoid venous injury. Venous structures were incorporated into the compartmental dissection strategy to maintain adequate venous drainage during tumor removal. Outcome Measures Primary outcomes included extent of resection (Simpson grading), ischemic complications (new postoperative infarcts on MRI), visual outcome (change in visual acuity and fields at 3-6 months), cranial nerve injuries, and other complications. The extent of resection was determined based on intraoperative assessment and postoperative MRI findings and evaluated according to the Simpson grading system. Simpson Grade I–II was defined as gross total resection, and Grade III as near-total resection. Postoperative MRI studies were independently reviewed by a neurosurgeon who was not involved in the surgical procedures and was blinded to intraoperative findings. Tumor recurrence was assessed during the follow-up period. An exploratory analysis was performed to assess the association between tumor size (≥45 mm vs <45 mm) and postoperative ischemic infarction using Fisher’s exact test. Results Patient Characteristics A total of 11 patients were included in this study. Baseline patient characteristics, surgical outcomes, and follow-up data are summarized in Table 1. The median age was 57 years (range, 26-75 years), with 2 male and 9 female patients. The median maximum tumor diameter was 47 mm (range 20-60 mm). Regarding tumor extension, according to the Al-Mefty classification, 2 cases were classified as Group I, 9 as Group II, and 0 as Group III. Using the Xu classification, 2 cases were classified as Type I, 4 as Type IIa, 1 as Type IIb, 0 as Type III, and 4 as Type IV. Table 1. Summary of anterior clinoidal meningiomas treated with an inter-perforator microdebulking strategy. Tumor extension was classified according to the Al-Mefty and Xu classifications. The Al-Mefty classification categorizes tumors based on the presence or absence of an arachnoid plane between the tumor and the internal carotid artery. The Xu classification categorizes tumors according to their site of origin around the anterior clinoid process and the associated meningeal architecture. Postoperative ischemia was assessed on diffusion-weighted MRI. Abbreviations: MRI, magnetic resonance imaging; FU, follow-up Surgical Outcomes Resection rate: Simpson Grade II resection (gross total resection with residual dural attachment or small cavernous sinus remnant) was achieved in 10/11 cases (91%). One case (Case 3 with complete ICA-MCA occlusion) achieved Simpson Grade III (near-total resection with residual tumor at vascular interface) to minimize vascular injury risk. No patient underwent Simpson Grade I resection (complete with dural excision) due to intentional cavernous sinus preservation. Histopathological examination demonstrated World Health Organization (WHO) grade I meningioma in all cases. Ischemic complications: No patient developed a major ischemic stroke, however asymptomatic infarctions were observed in 5 of 11 patients (45%). These lesions were predominantly located in the basal ganglia, and no infarctions attributable to the anterior choroidal artery or lenticulostriate arteries were identified. All five patients with infarction had large meningiomas with a maximum diameter ≥45 mm; thus, infarction occurred in 5 of 7 patients (71%) with ACMs measuring ≥45 mm, whereas no infarctions were observed in tumors <45 mm (0/4). This association did not reach statistical significance (Fisher's exact test, p = 0.06). Visual outcomes: Four patients presented with preoperative visual symptoms. Among them, visual improvement occurred in 2 patients (50%), while the remaining 2 patients maintained stable visual function without deterioration. The other 7 patients had no preoperative visual deficits and maintained normal visual function postoperatively. Cranial nerve complications: Transient oculomotor nerve palsy developed in 2/11 patients (18%, Case 7, 8), manifesting as ptosis and medial rectus weakness; complete resolution occurred at 6 weeks postoperatively without intervention. No other cranial nerve deficits were observed. Other Complications: No cerebrospinal fluid leak, hemorrhage, infection, or mortality occurred. No patient required reoperation. No venous infarction occurred despite venous drainage impairment in Case 1, attributed to strict venous preservation strategy. Intraoperative observation: The bilateral floating vessel phenomenon was frequently observed intraoperatively following sufficient central tumor debulking within inter-perforator spaces. This phenomenon refers to the spontaneous separation and mobilization of perforating arteries away from the tumor as the central tumor mass is progressively reduced. Follow-Up and Tumor Control No tumor recurrence was observed during the follow-up period, and no patient required adjuvant treatment such as radiotherapy. The median follow-up duration was 19 months (range, 1–48 months). The single patient who underwent Simpson grade III resection (Case 3) was referred to another institution for follow-up at 6 months postoperatively. Illustrative Case (Case 5: Figure 2, Supplementary Video 1) A 54-year-old woman presented with progressive visual loss. Her symptoms had gradually worsened over the preceding year, and at presentation she had complete visual loss in the left eye and mild visual disturbance in the right eye. Preoperative magnetic resonance imaging demonstrated a giant ACM with a maximum diameter of 60 mm, showing multidirectional extension into the cavernous sinus, diaphragm sellae, and suprasellar region. Surgical resection was performed via an orbitozygomatic approach. Using the inter-perforator microdebulking strategy described above, the tumor was systematically subdivided into multi compartments, and sequential piecemeal debulking and dissection were performed within each compartment. In compartments involving these perforators, meticulous microdebulking was carried out with strict preservation of the perforating vessels. The tumor was resected to Simpson grade II. A narrated operative video demonstrating the overall surgical workflow, including key aspects of the inter-perforator microdebulking technique, is provided as Supplementary Video 1. Postoperatively, an asymptomatic ischemic lesion was observed. Transient venous edema was noted but gradually resolved. Visual function did not improve; however, the patient was discharged with neurological function unchanged from the preoperative status. At 36 months of follow-up, no tumor recurrence was observed. Discussion Surgical Rationale and Anatomical Considerations This study presents a perforator-oriented refinement of tumor compartmentalization in ACM surgery, with clinical validation in a consecutive series including high-risk cases. ACMs remain among the most technically challenging skull base tumors because of their close relationship with critical neurovascular structures such as the ICA and optic nerve [3, 15]. While previous surgical strategies have primarily focused on visual preservation, ischemic complications—particularly those related to perforator injury—have received comparatively less attention [5, 7, 9, 12, 16]. In ACM surgery, perforating arteries are particularly vulnerable not only to direct injury but also to traction or stretching during tumor dissection. Even when anatomically preserved, these vessels may be functionally compromised, resulting in ischemic complications. Therefore, preservation of perforators represents a critical determinant of surgical outcome. Although several surgical strategies for ACM resection have been reported, including techniques focusing on vascular exposure and compartmentalization, our approach builds upon these established principles by extending them to the level of individual perforating arteries [1, 2, 18, 19]. Based on this concept, we focused on tumor regions located between adjacent perforating arteries, defined as inter-perforator spaces, which represent key anatomical constraints limiting safe resection. We hypothesized that further subdivision of tumors into micro-compartments defined by individual perforators could facilitate safer dissection. In our approach, central tumor debulking is performed within these inter-perforator spaces while minimizing direct manipulation of adjacent vessels. We observed that progressive debulking within these confined corridors often resulted in spontaneous separation of perforating arteries from the tumor (the “floating vessel phenomenon”), thereby facilitating dissection without direct traction on the vessels. Although this observation was not quantitatively measured, it may represent a mechanical advantage of the inter-perforator microdebulking strategy by reducing direct manipulation of perforating arteries. Further studies are required to determine whether this phenomenon correlates with improved perforator preservation or reduced ischemic complications. Thus, the inter-perforator microdebulking technique may complement established surgical strategies by introducing a perforator-oriented perspective that prioritizes preservation of critical microvascular structures while maintaining effective tumor resection. Comparison with Established Strategies and Surgical Outcomes Compartmentalization techniques for skull base meningiomas have evolved substantially since Yasargil’s foundational work and Al-Mefty’s systematic classification of clinoidal tumors [2, 21].Contemporary approaches typically employ vascular landmarks—such as the ICA, MCA, and ACA—to subdivide tumors into manageable segments, a strategy that has improved outcomes compared with historical en bloc resection techniques. Our technique represents an extension rather than a replacement of these principles: whereas conventional compartmentalization creates 3–5 large segments bounded by major vessels, perforator-level subdivision results in 10–15 micro-compartments defined by individual perforating arteries. Notably, Couldwell et al. discussed perforator preservation strategies in petroclival meningiomas; although this work focused on a different anatomical region, it provides an important conceptual foundation for our approach [10]. With respect to perforator territory ischemia, asymptomatic infarctions predominantly involving the basal ganglia were observed in 5 of 11 patients (45%) in our series; however, no patient developed hemiparesis or other symptomatic ischemic deficits. Although no patient developed symptomatic ischemic deficits, the relatively high incidence of asymptomatic infarctions in this series indicates that subclinical ischemic injury remains a relevant concern, particularly in large tumors. All cases with infarction involved large ACMs with a maximum diameter ≥45 mm, and 4 of the 5 cases were classified as Xu Type IV, underscoring the inherent difficulty of achieving complete resection without any ischemic injury in such advanced tumors. Exploratory statistical analysis suggested a higher incidence of infarction in larger tumors, although this association did not reach statistical significance, likely due to the small sample size. Few prior studies have specifically addressed asymptomatic postoperative infarction following ACM surgery. Nevertheless, our surgical outcomes—100% gross total or near-total resection and 0% symptomatic infarction—compare favorably with published series reporting gross total resection rates of 50–80% and ischemic complication rates of 5–15%, although the small sample size (n=11) precludes statistical comparison and warrants cautious interpretation [4, 8, 11]. With respect to visual outcomes, most patients in this series did not present with significant preoperative visual deficits, and visual function remained stable postoperatively in those without preoperative impairment. These findings suggest that meticulous inter-perforator microdebulking may contribute to improved resection by facilitating favorable tumor–brain dissection planes while avoiding clinically significant ischemic complications. When examining large series comprising more than 100 patients, a potential trade-off between extent of resection and ischemic morbidity becomes apparent. Liu et al. reported a gross total resection rate of 81.8% in a series of 127 ACMs, with postoperative motor deficits occurring in 10% of patients [13]. In contrast, Bassiouni et al. achieved a lower gross total resection rate of 58.5% in 106 cases, with a motor deficit rate of 2.8%, while Nakamura et al. reported a gross total resection rate of 42.6% and motor deficits in 3.7% of 108 patients [6, 14]. These large series suggest that higher resection rates may be associated with an increased risk of ischemic motor deficits, likely reflecting perforator-related injury. In this context, the inter-perforator microdebulking strategy employed in the present study may offer a means of mitigating this trade-off by facilitating favorable tumor–brain dissection planes while prioritizing perforator preservation. Whether this approach can consistently achieve both high rates of tumor resection and avoidance of motor deficits requires further validation in larger cohorts. Regarding extent of resection, the EANS consensus statement on ACMs acknowledges that gross total resection may be unachievable when no arachnoidal plane exists between the tumor and the arterial adventitia, particularly in Al-Mefty Group I tumors, and recommends acceptance of subtotal resection to minimize morbidity [17]. Our series included two Al-Mefty Group I cases (Cases 1 and 3) with extensive vascular involvement; one achieved gross total resection (Simpson Grade II) and the other near-total resection (Simpson Grade III), both without permanent neurological deficit, suggesting that systematic inter-perforator microdebulking may enable safer aggressive resection even in unfavorable anatomical conditions. In Case 3, however, a small residual tumor at the ICA–adventitial interface was intentionally left to avoid vascular injury, consistent with consensus recommendations prioritizing neurological preservation over radical resection. Although no recurrence was observed in this case during the initial 6-month follow-up, subsequent follow-up was transferred to another institution for social reasons. Further evaluation in a larger cohort with longer follow-up is required to clarify the long-term tumor control achievable with this technique. Limitations and Future Directions Several limitations must be acknowledged when interpreting the results of this study. First, the small sample size of 11 patients precludes statistically robust conclusions. As noted above, few prior studies have specifically addressed asymptomatic postoperative infarction following ACM surgery; therefore, the observation of diffusion-weighted imaging hyperintensity in five cases in our series warrants further investigation. Although no patient developed symptomatic ischemic infarction, a larger cohort is required to enable meaningful comparison with historical reports. Second, this series reflects the experience of a single surgeon at a specialized skull base center who had treated more than 15 ACMs, limiting the generalizability of the results to community practice or to surgeons with less experience. Outcomes from the early learning curve, during which different surgical strategies were employed, were not included in this analysis. The learning curve associated with perforator-level subdivision and inter-perforator microdebulking may be substantial, and the reproducibility of this technique in less experienced hands remains uncertain. Third, the follow-up duration in this series was relatively short and variable, with a median of 19 months (range, 1–48 months). In particular, one patient had only 1 month of follow-up, which provides limited information regarding long-term tumor control. Therefore, conclusions regarding recurrence should be interpreted cautiously, and longer follow-up is necessary to evaluate the durability of tumor control. In addition to the general limitations described above, several technique-specific considerations should also be acknowledged. First, the process of creating multiple micro-compartments may increase operative complexity and prolong surgical time, potentially leading to cumulative traction on perforating arteries during repeated manipulation. Although our strategy aims to minimize direct vessel handling through central debulking, the balance between sufficient tumor reduction and excessive manipulation remains delicate and may vary depending on tumor consistency and vascular anatomy. Second, this technique relies on clear identification of perforating arteries to define micro-compartments. In cases with very small, densely clustered, or poorly visualized perforators, accurate subdivision may be challenging or impractical, limiting the applicability of the approach. In such situations, conventional compartmentalization strategies based on major vessels may be more appropriate. Third, although we hypothesize that the spontaneous mobilization of perforating arteries observed during inter-perforator microdebulking may contribute to perforator preservation, the precise timing and mechanism of perforator-related ischemia remain unclear. Ischemic injury may occur not only during dissection within individual perforator-defined micro-compartments but also during earlier stages of tumor manipulation or major vessel exposure, where vessel stretching may induce ischemia. Further investigation is required to clarify these mechanisms and to optimize surgical strategies accordingly.Although this study focused on ACMs, the inter-perforator microdebulking approach may theoretically be applicable to meningiomas in other locations involving critical perforating branches, such as petroclival and tuberculum sellae meningiomas. Further validation in larger series and with longer follow-up is required. Conclusions We evaluated a perforator-oriented inter-perforator microdebulking approach for ACMs, including anatomically high-risk cases. The technique enabled systematic tumor removal while preserving critical perforating arteries, with favorable extent of resection, low rates of symptomatic ischemic morbidity, and stable neurological outcomes. Although limited by small sample size and short follow-up, these findings suggest that targeting inter-perforator spaces using preserved perforators as anatomical landmarks may provide a feasible and anatomically rational strategy for ACMs. Further validation in larger studies is warranted. Abbreviations ACM, Anterior clinoidal meningioma; ACP, anterior clinoid process; ICA, internal carotid artery; GTR, gross total resection; MCA, middle cerebral artery; ACA, anterior cerebral artery; MRI, magnetic resonance imaging Declarations Ethics approval and consent to participate All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Jikei University Certified Review Board (Approval No. 29-353 (8969)). Informed consent was obtained from the all patients. Availability of data and material The data that support the findings of this study are available from the corresponding author upon reasonable request. Restrictions apply due to patient privacy and institutional regulations. Competing interests The authors have no relevant financial or non-financial interests to disclose. Funding The authors did not receive support from any organization for the submitted work. Authors' contributions K.W. performed project administration, data curation, investigation, and wrote the original draft. K.I. contributed to data curation, investigation, methodology, and writing of the original draft, as well as review and editing. A.F. contributed to conceptualization and methodology. S.M. contributed to data curation, video editing, and writing of the original draft. N.W. contributed to conceptualization, validation, and review and editing of the manuscript. K.T. and Y.I. contributed to conceptualization. Y.M. supervised the study and contributed to review and editing of the manuscript. All authors reviewed the manuscript. Acknowledgements Not applicable References Aldea S, Le Guérinel C (2024) Microsurgical removal of an anterior clinoid meningioma with extensive vascular encasement: 2-dimensional operative video. Oper Neurosurg 27:394-395 Al-Mefty O (1990) Clinoidal meningiomas. J Neurosurg 73:840-849 Arab A, Hawsawi A, Bafaquh M, Orz Y, AlYamany M, Alobaid A (2021) Medial extension of medial sphenoid wing1 meningioma from the anterior clinoid line: does it truly affect the surgical outcome? J Neurol Surg B Skull Base 82:624-630 Arnautovic KI, Lasica N (2025) Update on anterior clinoid process removal in anterior clinoid meningioma surgery: literature review, and a new didactical concept. Acta Neurochir 167:335 Attia M, Umansky F, Paldor I, Dotan S, Shoshan Y, Spektor S (2012) Giant anterior clinoidal meningiomas: surgical technique and outcomes. J Neurosurg 117:654-665 Bassiouni H, Asgari S, Sandalcioglu IE, Seifert V, Stolke D, Marquardt G (2009) Anterior clinoidal meningiomas: functional outcome after microsurgical resection in a consecutive series of 106 patients. J Neurosurg 111:1078-1090 Baucher G, Troude L, Roux A, Loundou A, Boucekine M, Meling T, Roche PH (2022) Predictors of visual function after resection of skull base meningiomas with extradural anterior clinoidectomy. Neurosurg Rev 45:2133-2149 Chen LH, Xia Y, Wei F, Sun K, Huang HZ, Xu RX (2023) The factors influencing postoperative efficacy of anterior clinoidal meningioma treatment and an analysis of best-suited surgical strategies. Front Neurol 14:1097686 Cohen-Cohen S, Graffeo CS, Botello-Hernandez E, Carlstrom LP, Perry A, Tooley AA, Link MJ (2024) Anterior clinoid meningiomas: surgical results and proposed scoring system to predict visual outcomes. J Neurosurg 140:1295-1304 Couldwell WT, Fukushima T, Giannotta SL, Weiss MH (1996) Petroclival meningiomas: surgical experience in 109 cases. J Neurosurg 84:20-28 Giammattei L, Starnoni D, Levivier M, Messerer M, Daniel RT (2019) Surgery for clinoidal meningiomas: case series and meta-analysis of outcomes and complications. World Neurosurg 129:e700-e717 Leclerc A, Gaberel T, Laville MA, Derrey S, Quintyn JC, Emery E (2022) Factors associated with favorable visual outcome after surgery of clinoidal meningiomas. Clin Neurol Neurosurg 223:107508 Liu DY, Yuan XR, Liu Q, Jiang XJ, Jiang WX, Peng ZF, Ding XP, Luo DW, Yuan J (2012) Large medial sphenoid wing meningiomas: long-term outcome and correlation with tumor size after microsurgical treatment in 127 consecutive cases. Turk Neurosurg 22:547-557 Nakamura M, Roser F, Jacobs C, Vorkapic P, Samii M (2006) Medial sphenoid wing meningiomas: clinical outcome and recurrence rate. Neurosurgery 58:626-639 Pamir MN, Belirgen M, Ozduman K, Kilic T, Ozek M (2008) Anterior clinoidal meningiomas: analysis of 43 consecutive surgically treated cases. Acta Neurochir 150:625-635 Salgado Lopez L, Munoz Hernandez F, Asencio Cortes C, Tresserras Ribo P, Alvarez Holzapfel MJ, Molet Teixido (2018) Extradural anterior clinoidectomy in the management of parasellar meningiomas: analysis of 13 years of experience and literature review. Neurocirugia (Astur) 29:225-232 Tarnoni D, Tuleasca C, Giammattei L et al (2021) Surgical management of anterior clinoidal meningiomas: consensus statement on behalf of the EANS skull base section. Acta Neurochir 163:3387-3400 Tomasello F, de Divitiis O, Angileri FF, Salpietro FM, d'Avella D (2003) Large sphenocavernous meningiomas: is there still a role for the intradural approach via the pterional-transsylvian route? Acta Neurochir 145:273-282 Wong AK, Eddelman DB, Kramer DE, Munich SA, Byrne RW (2021) Surgical resection of clinoidal meningiomas without routine use of clinoidectomy. World Neurosurg 146:e467-e472 Xu T, Yan Y, Evins AI, Gong Z, Jiang L, Sun H, Cai L, Wang H, Li W, Zhang M, Chen J (2020) Anterior clinoidal meningiomas: meningeal anatomical considerations and surgical implications. Front Oncol 10:634 Yasargil MG, Mortara RW, Curcic M (1980) Meningiomas of basal posterior fossa. In: Krayenbuhl U (ed) Advances and technical standards in neurosurgery, vol 7. Springer, Berlin Additional Declarations No competing interests reported. Supplementary Files supplementvideo1.mp4 Video Legends Supplementary Video 1. Narrated operative video of Case 5 demonstrating the stepwise surgical procedure based on compartmental principles, including the inter-perforator microdebulking technique. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 16 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Submission checks completed at journal 13 Apr, 2026 First submitted to journal 13 Apr, 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-9399548","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628320618,"identity":"86c55276-8a74-4dc0-9ab6-9c23a26c95e7","order_by":0,"name":"Kentaro Watanabe","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kentaro","middleName":"","lastName":"Watanabe","suffix":""},{"id":628320619,"identity":"3984527e-ebb4-4555-a2c6-6d17ebd12fad","order_by":1,"name":"Kohei Ishikawa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie2RvWrDMBCAzxic5cCrhUv6Cpex0DavoiLw5ILHjgZDMnZt3yKT6VaBoVkEXT06BDxlSPGSoZCeSwNZongMVB9IHAef7kcADscFEoGX+0CSQ1+T1IB/6UFKIIcq/DxAryAB6AGNidwvuixLrmlptlljbq9gVDVw83ZaicGbxS+UThbmcUGyThAwIRDmtDJmxUd68krdK9uKZ0m5+MyqFB0r0/Jz07CyRwg3doUby2Ok9KGsU15crRGiM1VEwbMgJeq9bomkURhELWnbLNFyvu7wW929Pqt2svu4n4ahWq2FZWP9pxwI6PfmU4ncohzbzSHyvgYqDofD8S/4AQT1TeraF/bqAAAAAElFTkSuQmCC","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Kohei","middleName":"","lastName":"Ishikawa","suffix":""},{"id":628320620,"identity":"2ee1adfd-fe27-490a-8078-73c1750a4b9e","order_by":2,"name":"Ande Fachniadin","email":"","orcid":"","institution":"Universitas Indonesia, Dr. Cipto Mangunkusumo Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ande","middleName":"","lastName":"Fachniadin","suffix":""},{"id":628320621,"identity":"bc0d246d-856d-42fe-abba-400c34eb8604","order_by":3,"name":"Saivikram Madireddy","email":"","orcid":"","institution":"University of Tokyo Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Saivikram","middleName":"","lastName":"Madireddy","suffix":""},{"id":628320622,"identity":"c7a5d54c-2a1b-4901-b3a6-fd6286f83f93","order_by":4,"name":"Nobuyuki Watanabe","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nobuyuki","middleName":"","lastName":"Watanabe","suffix":""},{"id":628320623,"identity":"a1fd0323-b322-41a3-993b-f22beaccb630","order_by":5,"name":"Kyoichi Tomoto","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kyoichi","middleName":"","lastName":"Tomoto","suffix":""},{"id":628320624,"identity":"67e18149-dc89-45be-806e-cbf93cb90ac2","order_by":6,"name":"Yudo Ishii","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yudo","middleName":"","lastName":"Ishii","suffix":""},{"id":628320625,"identity":"fc145146-d15b-4fe6-b4d1-fd4d501de1af","order_by":7,"name":"Yuichi Murayama","email":"","orcid":"","institution":"The Jikei University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Murayama","suffix":""}],"badges":[],"createdAt":"2026-04-13 06:26:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9399548/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9399548/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108009356,"identity":"1a8ec332-a4a5-4c33-b1c7-78447f446dba","added_by":"auto","created_at":"2026-04-28 13:10:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":149939,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic illustration of the surgical workflow and inter-perforator microdebulking strategy for anterior clinoidal meningioma based on compartmental principles.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Detachment of the tumor from its dural attachment, allowing identification of the deeply situated internal carotid artery.\u003c/p\u003e\n\u003cp\u003e(B) Exposure of the middle cerebral artery, internal carotid artery, and anterior cerebral artery, enabling subdivision of the tumor into major compartments.\u003c/p\u003e\n\u003cp\u003e(C) Further subdivision of the tumor into micro-compartments defined by individual perforating arteries.\u003c/p\u003e\n\u003cp\u003e(D) Systematic debulking within each inter-perforator micro-compartment to minimize traction and mechanical stress on adjacent perforating arteries during dissection.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ICA, internal carotid artery; ACA, anterior cerebral artery; MCA, middle cerebral artery; Pcom, posterior communicating artery; Ant cho A, anterior choroidal artery; LSA; lenticulostriate artery.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9399548/v1/5a1e62339a09bb02f0fcf5da.jpg"},{"id":108009605,"identity":"e00df8c9-2262-4b5c-bd62-8eb4ba1c2104","added_by":"auto","created_at":"2026-04-28 13:10:31","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIllustrative case (Case 5).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Preoperative contrast-enhanced MRI demonstrating a giant anterior clinoidal meningioma.\u003c/p\u003e\n\u003cp\u003e(B) Preoperative surgical simulation based on contrast-enhanced CT angiography with tumor fusion. The image is oriented to reflect the operative view after frontotemporal craniotomy and anterior clinoidectomy. The tumor is shown in green.\u003c/p\u003e\n\u003cp\u003e(C) \u0026nbsp;The tumor is divided into three major compartments (#1–3, outlined in yellow) based on the internal carotid artery, anterior cerebral artery, and middle cerebral artery. Each major compartment is further subdivided into micro-compartments (outlined in purple) according to perforating arteries: compartment #1 by the anterior choroidal artery and posterior communicating artery; compartment #2 by the superior hypophyseal artery; and compartment #3 by the lenticulostriate arteries (LSAs) and A1 perforators.\u003c/p\u003e\n\u003cp\u003e(D) Intraoperative view showing compartmentalization at the perforator level. In this case, LSAs are shown delineating the compartment boundaries.\u003c/p\u003e\n\u003cp\u003e(E) Intraoperative view demonstrating the bilateral floating vessel phenomenon, in which perforating arteries surrounding the tumor spontaneously elevate following microdebulking.\u003c/p\u003e\n\u003cp\u003e(F) Postoperative contrast-enhanced MRI confirming gross total resection without ischemic complications.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9399548/v1/b3bec7e0f0f3d6e797403180.jpg"},{"id":108010836,"identity":"07f97a92-80cb-4895-a1b9-b5c413648df0","added_by":"auto","created_at":"2026-04-28 13:14:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":656050,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9399548/v1/85fcec52-cbd2-40a5-81e9-742278b59328.pdf"},{"id":108009332,"identity":"5f7843e2-fb4d-46ac-a93a-89d85b3dacfe","added_by":"auto","created_at":"2026-04-28 13:10:03","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":282056839,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVideo Legends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Video 1. Narrated operative video of Case 5 demonstrating the stepwise surgical procedure based on compartmental principles, including the inter-perforator microdebulking technique.\u003c/p\u003e","description":"","filename":"supplementvideo1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-9399548/v1/72842c086c1a2841f01f3ce1.mp4"}],"financialInterests":"No competing interests reported.","formattedTitle":"Vascular-Based Compartmental Resection of Anterior Clinoidal Meningiomas: An Inter-Perforator Microdebulking Strategy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnterior clinoidal meningiomas (ACMs) are among the most technically challenging skull base tumors because of their intimate relationship with critical neurovascular structures, including the internal carotid artery (ICA) and optic nerve [2, 3, 15]. Despite advances in microsurgical techniques, safe resection remains difficult, with reported gross total resection rates of 50\u0026ndash;80% and neurological morbidity of 10\u0026ndash;30% [4, 8, 11]. While previous studies have primarily focused on visual outcomes, ischemic complications\u0026mdash;particularly those related to perforating artery injury\u0026mdash;have received comparatively less attention [7, 9, 12, 16].\u003c/p\u003e\n\u003cp\u003ePreservation of perforating arteries is a critical determinant of surgical outcome in ACMs. These vessels, arising from the ICA, anterior cerebral artery (ACA), and middle cerebral artery (MCA), supply eloquent regions such as the internal capsule and basal ganglia, and their injury may result in devastating neurological deficits [5, 6, 11, 18]. However, detailed surgical strategies specifically addressing perforator preservation remain insufficiently described.\u003c/p\u003e\n\u003cp\u003eWe hypothesized that tumor regions located between adjacent perforating arteries (inter-perforator spaces) represent key anatomical constraints that limit safe resection. Based on this concept, we developed a perforator-oriented surgical strategy in which preserved perforators serve as anatomical landmarks to guide systematic tumor dissection.\u003c/p\u003e\n\u003cp\u003eIn this study, we retrospectively evaluated the feasibility and surgical outcomes of an inter-perforator microdebulking approach in a consecutive series of patients with ACMs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePatients\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe retrospectively analyzed patients with anterior clinoidal meningiomas who underwent surgical resection using the inter-perforator microdebulking technique at our institution between 2019 and 2024. All patients provided informed consent for surgery and data publication. This retrospective study was approved by the institutional review board. Tumor extension was classified according to the Al-Mefty classification and the Xu classification based on preoperative imaging and intraoperative findings [2, 20].The defining criteria of these classifications are summarized in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurgical Technique\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll cases were treated using an inter-perforator microdebulking technique. The procedure consisted of the following key steps: (1) extradural anterior clinoidectomy; (2) center-first dural opening; (3) detachment of the tumor from its dural attachment at the (ACP) and surrounding sphenoid ridge dura; (4) initial tumor subdivision along major arterial trunks, including the ICA and ACA, to create primary compartments; (5) subsequent perforator-level tumor subdivision creating multiple micro-compartments; (6) inter-perforator space management using a center-corridor microdebulking approach with a strict no-touch principle for preserved perforators; and (7) compartment-by-compartment dissection and removal of tumor, with careful attention to the specific neurovascular and arachnoidal relationships unique to each compartment. A schematic overview of these steps is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003eCareful attention was also paid to venous anatomy throughout the procedure. Sylvian veins and other cortical draining veins were preserved whenever possible, and dissection planes were developed along the arachnoid to avoid venous injury. Venous structures were incorporated into the compartmental dissection strategy to maintain adequate venous drainage during tumor removal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome Measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary outcomes included extent of resection (Simpson grading), ischemic complications (new postoperative infarcts on MRI), visual outcome (change in visual acuity and fields at 3-6 months), cranial nerve injuries, and other complications. The extent of resection was determined based on intraoperative assessment and postoperative MRI findings and evaluated according to the Simpson grading system. Simpson Grade I\u0026ndash;II was defined as gross total resection, and Grade III as near-total resection. Postoperative MRI studies were independently reviewed by a neurosurgeon who was not involved in the surgical procedures and was blinded to intraoperative findings. Tumor recurrence was assessed during the follow-up period. An exploratory analysis was performed to assess the association between tumor size (\u0026ge;45 mm vs \u0026lt;45 mm) and postoperative ischemic infarction using Fisher\u0026rsquo;s exact test.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePatient Characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 11 patients were included in this study. Baseline patient characteristics, surgical outcomes, and follow-up data are summarized in Table 1. The median age was 57 years (range, 26-75 years), with 2 male and 9 female patients. The median maximum tumor diameter was 47 mm (range 20-60 mm). Regarding tumor extension, according to the Al-Mefty classification, 2 cases were classified as Group I, 9 as Group II, and 0 as Group III. Using the Xu classification, 2 cases were classified as Type I, 4 as Type IIa, 1 as Type IIb, 0 as Type III, and 4 as Type IV.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1. Summary of anterior clinoidal meningiomas treated with an inter-perforator microdebulking strategy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTumor extension was classified according to the Al-Mefty and Xu classifications. The Al-Mefty classification categorizes tumors based on the presence or absence of an arachnoid plane between the tumor and the internal carotid artery. The Xu classification categorizes tumors according to their site of origin around the anterior clinoid process and the associated meningeal architecture. Postoperative ischemia was assessed on diffusion-weighted MRI.\u003c/p\u003e\n\u003cp\u003eAbbreviations: MRI, magnetic resonance imaging; FU, follow-up\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"724\" height=\"464\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurgical Outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResection rate: Simpson Grade II resection (gross total resection with residual dural attachment or small cavernous sinus remnant) was achieved in 10/11 cases (91%). One case (Case 3 with complete ICA-MCA occlusion) achieved Simpson Grade III (near-total resection with residual tumor at vascular interface) to minimize vascular injury risk. No patient underwent Simpson Grade I resection (complete with dural excision) due to intentional cavernous sinus preservation. Histopathological examination demonstrated World Health Organization (WHO) grade I meningioma in all cases.\u003c/p\u003e\n\u003cp\u003eIschemic complications: No patient developed a major ischemic stroke, however asymptomatic infarctions were observed in 5 of 11 patients (45%). These lesions were predominantly located in the basal ganglia, and no infarctions attributable to the anterior choroidal artery or lenticulostriate arteries were identified. All five patients with infarction had large meningiomas with a maximum diameter \u0026ge;45 mm; thus, infarction occurred in 5 of 7 patients (71%) with ACMs measuring \u0026ge;45 mm, whereas no infarctions were observed in tumors \u0026lt;45 mm (0/4). This association did not reach statistical significance (Fisher\u0026apos;s exact test, p = 0.06).\u003c/p\u003e\n\u003cp\u003eVisual outcomes: Four patients presented with preoperative visual symptoms. Among them, visual improvement occurred in 2 patients (50%), while the remaining 2 patients maintained stable visual function without deterioration. The other 7 patients had no preoperative visual deficits and maintained normal visual function postoperatively.\u003c/p\u003e\n\u003cp\u003eCranial nerve complications: Transient oculomotor nerve palsy developed in 2/11 patients (18%, Case 7, 8), manifesting as ptosis and medial rectus weakness; complete resolution occurred at 6 weeks postoperatively without intervention. No other cranial nerve deficits were observed.\u003c/p\u003e\n\u003cp\u003eOther Complications: No cerebrospinal fluid leak, hemorrhage, infection, or mortality occurred. No patient required reoperation. No venous infarction occurred despite venous drainage impairment in Case 1, attributed to strict venous preservation strategy.\u003c/p\u003e\n\u003cp\u003eIntraoperative observation: The bilateral floating vessel phenomenon was frequently observed intraoperatively following sufficient central tumor debulking within inter-perforator spaces. This phenomenon refers to the spontaneous separation and mobilization of perforating arteries away from the tumor as the central tumor mass is progressively reduced.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFollow-Up and Tumor Control\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo tumor recurrence was observed\u0026nbsp;during the follow-up period, and no patient required adjuvant treatment such as radiotherapy. The median follow-up duration was 19 months (range, 1\u0026ndash;48 months). The single patient who underwent Simpson grade III resection (Case 3) was referred to another institution for follow-up at 6 months postoperatively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIllustrative Case (Case 5: Figure 2, Supplementary Video 1)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 54-year-old woman presented with progressive visual loss. Her symptoms had gradually worsened over the preceding year, and at presentation she had complete visual loss in the left eye and mild visual disturbance in the right eye. Preoperative magnetic resonance imaging demonstrated a giant ACM with a maximum diameter of 60 mm, showing multidirectional extension into the cavernous sinus, diaphragm sellae, and suprasellar region.\u003c/p\u003e\n\u003cp\u003eSurgical resection was performed via an orbitozygomatic approach. Using the inter-perforator microdebulking strategy described above, the tumor was systematically subdivided into multi compartments, and sequential piecemeal debulking and dissection were performed within each compartment. In compartments involving these perforators, meticulous microdebulking was carried out with strict preservation of the perforating vessels. The tumor was resected to Simpson grade II. A narrated operative video demonstrating the overall surgical workflow, including key aspects of the inter-perforator microdebulking technique, is provided as Supplementary Video 1.\u003c/p\u003e\n\u003cp\u003ePostoperatively, an asymptomatic ischemic lesion was observed. Transient venous edema was noted but gradually resolved. Visual function did not improve; however, the patient was discharged with neurological function unchanged from the preoperative status. At 36 months of follow-up, no tumor recurrence was observed.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurgical Rationale and Anatomical Considerations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study presents a perforator-oriented refinement of tumor compartmentalization in ACM surgery, with clinical validation in a consecutive series including high-risk cases. ACMs remain among the most technically challenging skull base tumors because of their close relationship with critical neurovascular structures such as the ICA and optic nerve [3, 15]. While previous surgical strategies have primarily focused on visual preservation, ischemic complications—particularly those related to perforator injury—have received comparatively less attention [5, 7, 9, 12, 16].\u003c/p\u003e\n\u003cp\u003eIn ACM surgery, perforating arteries are particularly vulnerable not only to direct injury but also to traction or stretching during tumor dissection. Even when anatomically preserved, these vessels may be functionally compromised, resulting in ischemic complications. Therefore, preservation of perforators represents a critical determinant of surgical outcome.\u003c/p\u003e\n\u003cp\u003eAlthough several surgical strategies for ACM resection have been reported, including techniques focusing on vascular exposure and compartmentalization, our approach builds upon these established principles by extending them to the level of individual perforating arteries [1, 2, 18, 19]. Based on this concept, we focused on tumor regions located between adjacent perforating arteries, defined as inter-perforator spaces, which represent key anatomical constraints limiting safe resection. We hypothesized that further subdivision of tumors into micro-compartments defined by individual perforators could facilitate safer dissection.\u003c/p\u003e\n\u003cp\u003eIn our approach, central tumor debulking is performed within these inter-perforator spaces while minimizing direct manipulation of adjacent vessels. We observed that progressive debulking within these confined corridors often resulted in spontaneous separation of perforating arteries from the tumor (the “floating vessel phenomenon”), thereby facilitating dissection without direct traction on the vessels. Although this observation was not quantitatively measured, it may represent a mechanical advantage of the inter-perforator microdebulking strategy by reducing direct manipulation of perforating arteries. Further studies are required to determine whether this phenomenon correlates with improved perforator preservation or reduced ischemic complications.\u003c/p\u003e\n\u003cp\u003eThus, the inter-perforator microdebulking technique may complement established surgical strategies by introducing a perforator-oriented perspective that prioritizes preservation of critical microvascular structures while maintaining effective tumor resection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eComparison with Established Strategies and Surgical Outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompartmentalization techniques for skull base meningiomas have evolved substantially since Yasargil’s foundational work and Al-Mefty’s systematic classification of clinoidal tumors [2, 21].Contemporary approaches typically employ vascular landmarks—such as the ICA, MCA, and ACA—to subdivide tumors into manageable segments, a strategy that has improved outcomes compared with historical en bloc resection techniques. Our technique represents an extension rather than a replacement of these principles: whereas conventional compartmentalization creates 3–5 large segments bounded by major vessels, perforator-level subdivision results in 10–15 micro-compartments defined by individual perforating arteries. Notably, Couldwell et al. discussed perforator preservation strategies in petroclival meningiomas; although this work focused on a different anatomical region, it provides an important conceptual foundation for our approach [10].\u003c/p\u003e\n\u003cp\u003eWith respect to perforator territory ischemia, asymptomatic infarctions predominantly involving the basal ganglia were observed in 5 of 11 patients (45%) in our series; however, no patient developed hemiparesis or other symptomatic ischemic deficits. Although no patient developed symptomatic ischemic deficits, the relatively high incidence of asymptomatic infarctions in this series indicates that subclinical ischemic injury remains a relevant concern, particularly in large tumors. All cases with infarction involved large ACMs with a maximum diameter ≥45 mm, and 4 of the 5 cases were classified as Xu Type IV, underscoring the inherent difficulty of achieving complete resection without any ischemic injury in such advanced tumors. Exploratory statistical analysis suggested a higher incidence of infarction in larger tumors, although this association did not reach statistical significance, likely due to the small sample size. Few prior studies have specifically addressed asymptomatic postoperative infarction following ACM surgery. Nevertheless, our surgical outcomes—100% gross total or near-total resection and 0% symptomatic infarction—compare favorably with published series reporting gross total resection rates of 50–80% and ischemic complication rates of 5–15%, although the small sample size (n=11) precludes statistical comparison and warrants cautious interpretation [4, 8, 11]. With respect to visual outcomes, most patients in this series did not present with significant preoperative visual deficits, and visual function remained stable postoperatively in those without preoperative impairment. These findings suggest that meticulous inter-perforator microdebulking may contribute to improved resection by facilitating favorable tumor–brain dissection planes while avoiding clinically significant ischemic complications. When examining large series comprising more than 100 patients, a potential trade-off between extent of resection and ischemic morbidity becomes apparent. Liu et al. reported a gross total resection rate of 81.8% in a series of 127 ACMs, with postoperative motor deficits occurring in 10% of patients [13]. In contrast, Bassiouni et al. achieved a lower gross total resection rate of 58.5% in 106 cases, with a motor deficit rate of 2.8%, while Nakamura et al. reported a gross total resection rate of 42.6% and motor deficits in 3.7% of 108 patients [6, 14]. These large series suggest that higher resection rates may be associated with an increased risk of ischemic motor deficits, likely reflecting perforator-related injury. In this context, the inter-perforator microdebulking strategy employed in the present study may offer a means of mitigating this trade-off by facilitating favorable tumor–brain dissection planes while prioritizing perforator preservation. Whether this approach can consistently achieve both high rates of tumor resection and avoidance of motor deficits requires further validation in larger cohorts.\u003c/p\u003e\n\u003cp\u003eRegarding extent of resection, the EANS consensus statement on ACMs acknowledges that gross total resection may be unachievable when no arachnoidal plane exists between the tumor and the arterial adventitia, particularly in Al-Mefty Group I tumors, and recommends acceptance of subtotal resection to minimize morbidity [17]. Our series included two Al-Mefty Group I cases (Cases 1 and 3) with extensive vascular involvement; one achieved gross total resection (Simpson Grade II) and the other near-total resection (Simpson Grade III), both without permanent neurological deficit, suggesting that systematic inter-perforator microdebulking may enable safer aggressive resection even in unfavorable anatomical conditions. In Case 3, however, a small residual tumor at the ICA–adventitial interface was intentionally left to avoid vascular injury, consistent with consensus recommendations prioritizing neurological preservation over radical resection. Although no recurrence was observed in this case during the initial 6-month follow-up, subsequent follow-up was transferred to another institution for social reasons. Further evaluation in a larger cohort with longer follow-up is required to clarify the long-term tumor control achievable with this technique.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLimitations and Future Directions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations must be acknowledged when interpreting the results of this study. First, the small sample size of 11 patients precludes statistically robust conclusions. As noted above, few prior studies have specifically addressed asymptomatic postoperative infarction following ACM surgery; therefore, the observation of diffusion-weighted imaging hyperintensity in five cases in our series warrants further investigation. Although no patient developed symptomatic ischemic infarction, a larger cohort is required to enable meaningful comparison with historical reports. Second, this series reflects the experience of a single surgeon at a specialized skull base center who had treated more than 15 ACMs, limiting the generalizability of the results to community practice or to surgeons with less experience. Outcomes from the early learning curve, during which different surgical strategies were employed, were not included in this analysis. The learning curve associated with perforator-level subdivision and inter-perforator microdebulking may be substantial, and the reproducibility of this technique in less experienced hands remains uncertain. Third, the follow-up duration in this series was relatively short and variable, with a median of 19 months (range, 1–48 months). In particular, one patient had only 1 month of follow-up, which provides limited information regarding long-term tumor control. Therefore, conclusions regarding recurrence should be interpreted cautiously, and longer follow-up is necessary to evaluate the durability of tumor control.\u003c/p\u003e\n\u003cp\u003eIn addition to the general limitations described above, several technique-specific considerations should also be acknowledged. First, the process of creating multiple micro-compartments may increase operative complexity and prolong surgical time, potentially leading to cumulative traction on perforating arteries during repeated manipulation. Although our strategy aims to minimize direct vessel handling through central debulking, the balance between sufficient tumor reduction and excessive manipulation remains delicate and may vary depending on tumor consistency and vascular anatomy. Second, this technique relies on clear identification of perforating arteries to define micro-compartments. In cases with very small, densely clustered, or poorly visualized perforators, accurate subdivision may be challenging or impractical, limiting the applicability of the approach. In such situations, conventional compartmentalization strategies based on major vessels may be more appropriate. Third, although we hypothesize that the spontaneous mobilization of perforating arteries observed during inter-perforator microdebulking may contribute to perforator preservation, the precise timing and mechanism of perforator-related ischemia remain unclear. Ischemic injury may occur not only during dissection within individual perforator-defined micro-compartments but also during earlier stages of tumor manipulation or major vessel exposure, where vessel stretching may induce ischemia. Further investigation is required to clarify these mechanisms and to optimize surgical strategies accordingly.Although this study focused on ACMs, the inter-perforator microdebulking approach may theoretically be applicable to meningiomas in other locations involving critical perforating branches, such as petroclival and tuberculum sellae meningiomas. Further validation in larger series and with longer follow-up is required.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe evaluated a perforator-oriented inter-perforator microdebulking approach for ACMs, including anatomically high-risk cases. The technique enabled systematic tumor removal while preserving critical perforating arteries, with favorable extent of resection, low rates of symptomatic ischemic morbidity, and stable neurological outcomes. Although limited by small sample size and short follow-up, these findings suggest that targeting inter-perforator spaces using preserved perforators as anatomical landmarks may provide a feasible and anatomically rational strategy for ACMs. Further validation in larger studies is warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACM, Anterior clinoidal meningioma; ACP, anterior clinoid process; ICA, internal carotid artery; GTR, gross total resection; MCA, middle cerebral artery; ACA, anterior cerebral artery; MRI, magnetic resonance imaging\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Jikei University Certified Review Board (Approval No. 29-353 (8969)). Informed consent was obtained from the all patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. Restrictions apply due to patient privacy and institutional regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK.W. performed project administration, data curation, investigation, and wrote the original draft. K.I. contributed to data curation, investigation, methodology, and writing of the original draft, as well as review and editing. A.F. contributed to conceptualization and methodology. S.M. contributed to data curation, video editing, and writing of the original draft. N.W. contributed to conceptualization, validation, and review and editing of the manuscript. K.T. and Y.I. contributed to conceptualization. Y.M. supervised the study and contributed to review and editing of the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAldea S, Le Gu\u0026eacute;rinel C (2024) Microsurgical removal of an anterior clinoid meningioma with extensive vascular encasement: 2-dimensional operative video. Oper Neurosurg 27:394-395\u003c/li\u003e\n \u003cli\u003eAl-Mefty O (1990) Clinoidal meningiomas. J Neurosurg 73:840-849\u003c/li\u003e\n \u003cli\u003eArab A, Hawsawi A, Bafaquh M, Orz Y, AlYamany M, Alobaid A (2021) Medial extension of medial sphenoid wing1 meningioma from the anterior clinoid line: does it truly affect the surgical outcome? J Neurol Surg B Skull Base 82:624-630\u003c/li\u003e\n \u003cli\u003eArnautovic KI, Lasica N (2025) Update on anterior clinoid process removal in anterior clinoid meningioma surgery: literature review, and a new didactical concept. Acta Neurochir 167:335\u003c/li\u003e\n \u003cli\u003eAttia M, Umansky F, Paldor I, Dotan S, Shoshan Y, Spektor S (2012) Giant anterior clinoidal meningiomas: surgical technique and outcomes. J Neurosurg 117:654-665\u003c/li\u003e\n \u003cli\u003eBassiouni H, Asgari S, Sandalcioglu IE, Seifert V, Stolke D, Marquardt G (2009) Anterior clinoidal meningiomas: functional outcome after microsurgical resection in a consecutive series of 106 patients. J Neurosurg 111:1078-1090\u003c/li\u003e\n \u003cli\u003eBaucher G, Troude L, Roux A, Loundou A, Boucekine M, Meling T, Roche PH (2022) Predictors of visual function after resection of skull base meningiomas with extradural anterior clinoidectomy. Neurosurg Rev 45:2133-2149\u003c/li\u003e\n \u003cli\u003eChen LH, Xia Y, Wei F, Sun K, Huang HZ, Xu RX (2023) The factors influencing postoperative efficacy of anterior clinoidal meningioma treatment and an analysis of best-suited surgical strategies. Front Neurol 14:1097686\u003c/li\u003e\n \u003cli\u003eCohen-Cohen S, Graffeo CS, Botello-Hernandez E, Carlstrom LP, Perry A, Tooley AA, Link MJ (2024) Anterior clinoid meningiomas: surgical results and proposed scoring system to predict visual outcomes. J Neurosurg 140:1295-1304\u003c/li\u003e\n \u003cli\u003eCouldwell WT, Fukushima T, Giannotta SL, Weiss MH (1996) Petroclival meningiomas: surgical experience in 109 cases. J Neurosurg 84:20-28\u003c/li\u003e\n \u003cli\u003eGiammattei L, Starnoni D, Levivier M, Messerer M, Daniel RT (2019) Surgery for clinoidal meningiomas: case series and meta-analysis of outcomes and complications. World Neurosurg 129:e700-e717\u003c/li\u003e\n \u003cli\u003eLeclerc A, Gaberel T, Laville MA, Derrey S, Quintyn JC, Emery E (2022) Factors associated with favorable visual outcome after surgery of clinoidal meningiomas. Clin Neurol Neurosurg 223:107508\u003c/li\u003e\n \u003cli\u003eLiu DY, Yuan XR, Liu Q, Jiang XJ, Jiang WX, Peng ZF, Ding XP, Luo DW, Yuan J (2012) Large medial sphenoid wing meningiomas: long-term outcome and correlation with tumor size after microsurgical treatment in 127 consecutive cases. Turk Neurosurg 22:547-557\u003c/li\u003e\n \u003cli\u003eNakamura M, Roser F, Jacobs C, Vorkapic P, Samii M (2006) Medial sphenoid wing meningiomas: clinical outcome and recurrence rate. Neurosurgery 58:626-639\u003c/li\u003e\n \u003cli\u003ePamir MN, Belirgen M, Ozduman K, Kilic T, Ozek M (2008) Anterior clinoidal meningiomas: analysis of 43 consecutive surgically treated cases. Acta Neurochir 150:625-635\u003c/li\u003e\n \u003cli\u003eSalgado Lopez L, Munoz Hernandez F, Asencio Cortes C, Tresserras Ribo P, Alvarez Holzapfel MJ, Molet Teixido (2018) Extradural anterior clinoidectomy in the management of parasellar meningiomas: analysis of 13 years of experience and literature review. Neurocirugia (Astur) 29:225-232\u003c/li\u003e\n \u003cli\u003eTarnoni D, Tuleasca C, Giammattei L et al (2021) Surgical management of anterior clinoidal meningiomas: consensus statement on behalf of the EANS skull base section. Acta Neurochir 163:3387-3400\u003c/li\u003e\n \u003cli\u003eTomasello F, de Divitiis O, Angileri FF, Salpietro FM, d\u0026apos;Avella D (2003) Large sphenocavernous meningiomas: is there still a role for the intradural approach via the pterional-transsylvian route? Acta Neurochir 145:273-282\u003c/li\u003e\n \u003cli\u003eWong AK, Eddelman DB, Kramer DE, Munich SA, Byrne RW (2021) Surgical resection of clinoidal meningiomas without routine use of clinoidectomy. World Neurosurg 146:e467-e472\u003c/li\u003e\n \u003cli\u003eXu T, Yan Y, Evins AI, Gong Z, Jiang L, Sun H, Cai L, Wang H, Li W, Zhang M, Chen J (2020) Anterior clinoidal meningiomas: meningeal anatomical considerations and surgical implications. Front Oncol 10:634\u003c/li\u003e\n \u003cli\u003eYasargil MG, Mortara RW, Curcic M (1980) Meningiomas of basal posterior fossa. In: Krayenbuhl U (ed) Advances and technical standards in neurosurgery, vol 7. Springer, Berlin\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-neurochirurgica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anch","sideBox":"Learn more about [Acta Neurochirurgica](http://link.springer.com/journal/701)","snPcode":"701","submissionUrl":"https://submission.springernature.com/new-submission/701/3","title":"Acta Neurochirurgica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Anterior clinoidal meningioma, Skull base surgery, Perforating arteries, Compartmental resection, Microdebulking","lastPublishedDoi":"10.21203/rs.3.rs-9399548/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9399548/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003cbr\u003e\n \u003c/strong\u003eAnterior clinoidal meningiomas (ACMs) frequently encase critical perforating arteries, making safe resection technically challenging and placing patients at risk for ischemic complications. This study aimed to evaluate the feasibility and surgical outcomes of a perforator-oriented inter-perforator microdebulking approach designed to preserve perforating arteries during ACM resection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003cbr\u003e\n \u003c/strong\u003eWe retrospectively reviewed 11 patients with ACMs who underwent surgical resection using an inter-perforator microdebulking technique between 2019 and 2024. The surgical strategy consisted of systematic tumor compartmentalization along major arterial trunks followed by further subdivision at the perforator level, enabling controlled microdebulking within inter-perforator spaces. Surgical outcomes, ischemic complications, visual outcomes, cranial nerve deficits, and tumor recurrence were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003cbr\u003e\n \u003c/strong\u003eSimpson Grade II resection was achieved in 10 of 11 patients (91%), and one patient underwent Simpson Grade III resection to avoid vascular injury. No patient developed a symptomatic ischemic stroke. Asymptomatic infarctions were observed in 5 patients (45%), predominantly involving the basal ganglia, all of whom had large tumors (≥45 mm). Visual improvement occurred in 2 of 4 symptomatic patients (50%), and no visual deterioration was observed. Transient oculomotor nerve palsy occurred in 2 patients, with complete resolution during follow-up; no permanent cranial nerve deficits were noted. No tumor recurrence was observed during a median follow-up of 19 months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003cbr\u003e\n \u003c/strong\u003ePerforator-oriented inter-perforator microdebulking provides an anatomically rational framework for ACM surgery, enabling systematic tumor removal while preserving critical perforating arteries. This approach may facilitate safer resection of anatomically high-risk ACMs in selected patients.\u003c/p\u003e","manuscriptTitle":"Vascular-Based Compartmental Resection of Anterior Clinoidal Meningiomas: An Inter-Perforator Microdebulking Strategy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 12:55:35","doi":"10.21203/rs.3.rs-9399548/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-16T05:43:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"148561813010925115927221225048998248685","date":"2026-04-29T12:39:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T10:37:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308653255503731244531576283076719186551","date":"2026-04-23T07:20:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283117118148424358136121007752919458471","date":"2026-04-20T17:03:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106198940294538628993765279391552315036","date":"2026-04-19T17:44:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-19T17:27:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-14T12:30:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T00:33:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Neurochirurgica","date":"2026-04-13T06:19:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-neurochirurgica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anch","sideBox":"Learn more about [Acta Neurochirurgica](http://link.springer.com/journal/701)","snPcode":"701","submissionUrl":"https://submission.springernature.com/new-submission/701/3","title":"Acta Neurochirurgica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a91e8508-862b-4798-8f9e-b39e13b55b03","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-16T05:43:24+00:00","index":18,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T12:55:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 12:55:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9399548","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9399548","identity":"rs-9399548","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}