Recent studies have focused on advanced imaging techniques and biomarkers to enhance the understanding and management of meningiomas. One significant study evaluated the use of 18F-FLT PET imaging as a predictor of tumor progression in asymptomatic meningiomas, revealing a positive correlation between tumor growth rates and 18F-FLT uptake (r < 0.513, P < 0.015), suggesting its potential as a non-invasive biomarker for monitoring tumor behavior (ref: Bashir doi.org/10.1093/brain/). Another study investigated the role of soluble PD-L1 as a systemic inflammation marker in patients with various brain tumors, including meningiomas, highlighting its association with local and systemic inflammation (ref: Mair doi.org/10.1136/esmoopen-2020-000863/). Furthermore, an integrated analysis of transcriptomic and proteomic data provided insights into the molecular landscape of meningiomas, identifying potential biomarkers for aggressive forms of the disease (ref: Dunn doi.org/10.3390/cancers12113270/). Techniques such as superselective pseudocontinuous arterial spin labeling (ss-pCASL) have shown promise in predicting tumor blood supply and embolization feasibility, with high interobserver agreement (κ = 0.817) (ref: Yoo doi.org/10.3171/2020.7.JNS201915/). Additionally, the use of apparent diffusion coefficient maps derived from diffusion-weighted imaging has been proposed as a method to predict the consistency of meningiomas, achieving a positive predictive value of 81% for detecting soft tumors (ref: Miyoshi doi.org/10.3171/2020.6.JNS20740/). Lastly, a radiomics model developed to predict histopathological grading based on MRI has the potential to enhance preoperative decision-making (ref: Han doi.org/10.1016/j.mri.2020.11.009/).