Predicting intraoperative meningioma consistency using features from standard MRI sequences: a preoperative evaluation.
prospective_cohort · Level II
Where this comes from
- Record sourced from PubMed, PMID 40542946.
- Also identified by DOI 10.1007/s00701-025-06582-9 and PMC identifier 12182493.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Symptomatic meningiomas may require surgical resection to save or improve neurological function. The extent of tumor resection depends on multiple factors, including the tumor's consistency, its location, and the patient's overall condition. This prospective study aims to explore new criteria in combination with previously proposed tumor features on MRI to establish a rapid approach to tumor consistency characterization pre-operatively. Forty-eight patients with meningiomas were prospectively included and underwent a dedicated MRI protocol prior to surgery. Qualitative and quantitative MRI characteristics of the tumor were correlated to a previously proposed surgical tumor consistency grading. Soft tumors were associated with homogeneous contrast enhancement, high T2 signal, absence of peritumoral edema (PTE), the presence of tumor cysts, and a uniformly dark appearance on fractional anisotropy (FA) maps. In contrast, firmer tumors were characterized by heterogeneous contrast enhancement, low T2 signal, the presence of PTE, absence of tumor cysts and a heterogeneous appearance on FA maps, requiring supranormal ultrasonic aspirator settings. Tumor signal quantification on T2 and Apparent Diffusion Coefficient maps (ADC) correlated moderately to tumor consistency. T1 sequences did not contribute in determining tumor consistency. An array of simple qualitative meningioma characteristics on MRI can assist in swift discrimination of soft and hard tumors preoperatively. These have been displayed in a figure that can easily be implemented clinically for optimal surgical planning.
Medical subject headings
- Meningioma
- Meningeal Neoplasms
- Magnetic Resonance Imaging