MRI Mapping in Meningioma: A Clinical Perspective on Presentation and Management

See also article by Hudelist et al in this issue.

Ramona-Alexandra Todea, MD, is a clinical and academic neuroradiologist at the University Hospital and University of Zürich and is board certified by the Swiss Board in General Radiology and Diagnostic Neuroradiology and the European Board in Neuroradiology and Pediatric Neuroradiology. Her work focuses on MRI-based brain tumor characterization and advanced imaging in neuro-oncology. She is involved in teaching at the University of Zürich and contributes to peer review and academic education. Her research centers on multimodal glioma imaging using advanced MRI techniques for diagnosis, treatment planning, and therapy assessment.

Meningiomas are the most common primary intracranial tumors of the central nervous system, accounting for approximately 40% of all primary brain tumors in adults (1). Tumor location is a critical determinant of patient management, influencing clinical presentation, histomolecular characteristics, therapeutic strategies, malignancy grade, and outcomes (2).

Conventional anatomic classifications, such as skull base, convexity, or falcine/parasagittal meningiomas, remain clinically useful for communication, risk stratification, and treatment planning. However, large or multicompartment tumors are often assigned to a single category, potentially introducing misclassification and obscuring more subtle spatial associations (3,4).

Unbiased MRI-based voxel-based lesion mapping addresses these limitations by normalizing lesions to a common stereotactic template and quantifying spatial density without relying on predefined anatomic labels. This approach reduces classification bias and enables more precise spatial characterization of tumor distribution (4,5). Voxel-based lesion mapping also represents a methodologic advance by enabling continuous spatial analysis of tumor distribution within standardized brain space. However, interpretation remains population dependent and may be influenced by referral and treatment-selection biases, requiring caution when extrapolating voxelwise associations to individual patient decision-making.

Prior meningioma atlas studies have improved understanding of spatial patterns and biologic associations (3,4); however, none have provided a unified voxelwise assessment of clinically relevant variables, including neurologic presentation, treatment strategy, and tumor grade.

The study by Hudelist et al published in this issue of Radiology: Imaging Cancer, investigated the relationship between meningioma location, clinical presentation, management, and outcomes using voxel-based lesion mapping in a large, homogeneous cohort of patients with intracranial meningiomas (6). This single-center retrospective analysis included adults treated between January 2000 and December 2024 with available preoperative MRI. Collected variables included age, sex, and clinical presentation, such as signs of elevated intracranial pressure, focal neurologic deficits (including cranial nerve palsy), seizures, exophthalmos, subcutaneous mass, or incidental detection, as well as tumor characteristics including volume, laterality, brain edema on fluid-attenuated inversion recovery images, and mass effect on the lateral ventricles. Initial management was stratified into watch-and-wait, surgery, or radiation therapy, and histopathologic assessment included World Health Organization (WHO) grade and extent of resection according to the Simpson classification. Tumor location was categorized as skull base or convexity.

Meningioma segmentation was performed manually on preoperative MRI using Brainlab Elements software (version 6.3.0.27, Brainlab AG). Enhancing tumor components, necrotic regions, and calcifications were included to define the total solid tumor volume as the region of interest. Voxelwise group-level analyses assessed associations between tumor location and clinical presentation (focal neurologic deficits, epilepsy, elevated intracranial pressure), treatment strategy, and malignancy grade in surgically treated patients (WHO grade 1 vs grades 2–3). Tumor volume was included as a covariate in all models, and analyses were based on lesion masks rather than intratumoral imaging features.

The final cohort comprised 1333 patients (mean age, 58 years ± 13; 79.8% female) with 1676 intracranial meningiomas and a mean tumor volume of 16.3 cm³ ± 26.0. Tumors were most frequently located at the lateral convexity (29.8%) and lateral skull base (28.1%), followed by midline convexity (21.6%) and midline skull base (18.7%). In contrast, voxel-density mapping demonstrated a dominant cluster in the anterior and middle skull base, forming a bilateral aggregation of 11 732 voxels and highlighting spatial patterns not captured by conventional classification.

Symptomatic tumors clustered in the bilateral motor and premotor cortices, deep frontobasal regions, and anteromedial skull base. Focal neurologic deficits were associated with the left precentral region and anteromedial skull base, epilepsy with bilateral premotor regions, and elevated intracranial pressure with deep frontal and cerebellar regions.

Resection probability was highest in clusters involving the anterior and middle skull base, supplementary motor areas, left precentral gyrus, and deep frontobasal regions. Overall, 55.8% of tumors were managed conservatively and 40.4% underwent surgical resection. Higher-grade tumors (WHO grades 2–3) demonstrated a small right frontal cluster along the superior and middle frontal gyri, indicating only a limited spatial association.

These findings reinforce the relationship between tumor location, symptom profile, and management strategy, particularly in eloquent cortical and skull base regions. However, the observed resection patterns likely reflect a combination of symptom-driven selection and anatomic accessibility rather than intrinsic tumor biology. Similarly, the weak spatial association with higher-grade tumors suggests limited location dependence of tumor grade within this cohort, although interpretation is constrained by the relatively small number of higher-grade cases.

Previous voxel-based meningioma studies (3,4,7) have also linked tumor location to biologic features such as age, sex, WHO grade, immunohistochemical markers, and recurrence patterns, suggesting that spatial distribution may partly reflect underlying tumor biology. In contrast, the current study by Hudelist et al shifts the focus from biologic stratification toward clinically actionable outcomes, demonstrating stronger and more consistent spatial associations with symptoms and management decisions while showing only a limited relationship with WHO grade. This suggests that, unlike prior work emphasizing biologic heterogeneity, the present atlas may be more directly relevant to clinical decision-making, with location primarily acting as a surrogate for clinical presentation and treatment selection rather than tumor biology.

Overall, voxelwise analysis provided substantially greater anatomic resolution than conventional classification. While traditional categorization suggested a balanced distribution between convexity and skull base lesions, voxel-density mapping demonstrated predominance within the anterior and middle skull base, with additional frontal and parasagittal involvement, underscoring the added value of spatially continuous mapping approaches.

Clinically, these results support the concept that meningioma location is functionally relevant rather than purely descriptive. Spatial clustering within eloquent cortical and skull base regions aligns with observed symptom patterns and surgical decision-making, suggesting potential utility for preoperative risk stratification and patient counseling. However, these associations should be interpreted probabilistically, as management decisions are influenced by multiple clinical and nonspatial factors.

The most important conceptual advance of this work lies in reframing meningiomas from compartment-based entities to spatially distributed lesions with graded relationships to functional brain networks. At the same time, caution is warranted, as voxelwise precision may overstate biologic determinism in a retrospective cohort spanning more than 2 decades, during which surgical indications, grading systems, and molecular classification criteria evolved. Accordingly, these findings should be viewed as hypothesis-generating rather than prescriptive for individual clinical decision-making.

Future research should focus on integrating molecular and genetic alterations to clarify whether spatial tumor distribution also reflects underlying biologic behavior. Importantly, longitudinal imaging studies are needed to characterize growth trajectories over time and determine how progression rates influence clinical decision-making, particularly the timing of surgical intervention for incidental or minimally symptomatic tumors. Such approaches would better reflect real-world practice, where treatment decisions are driven not only by static tumor location but also by documented tumor evolution.

In summary, this study reinforces that meningioma location is not merely descriptive but is closely linked to clinically relevant phenotypes and management decisions, underscoring a shift toward spatially informed neuro-oncology.

Disclosures of conflicts of interest

Please see ICMJE form(s) for author conflicts of interest. These have been provided as supplemental materials.