Risk factors for preoperative seizures in intracranial meningiomas

Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study

OBJECTIVE

To develop a nomogram based on tumor and peritumoral edema (PE) radiomics features extracted from preoperative multiparameter MRI for predicting brain invasion (BI) in atypical meningioma (AM).

METHODS

In this retrospective study, according to the 2021 WHO classification criteria, a total of 469 patients with pathologically confirmed AM from three medical centres were enrolled and divided into training (n = 273), internal validation (n = 117) and external validation (n = 79) cohorts. BI was diagnosed based on the histopathological examination. Preoperative contrast-enhanced T1-weighted MR images (T1C) and T2-weighted MR images (T2) for extracting meningioma features and T2-fluid attenuated inversion recovery (FLAIR) sequences for extracting meningioma and PE features were obtained. The multiple logistic regression was applied to develop separate multiparameter radiomics models for comparison. A nomogram was developed by combining radiomics features and clinical risk factors, and the clinical usefulness of the nomogram was verified using decision curve analysis.

RESULTS

Among the clinical factors, PE volume and PE/tumor volume ratio are the risk of BI in AM. The combined nomogram based on multiparameter MRI radiomics features of meningioma and PE and clinical indicators achieved the best performance in predicting BI in AM, with area under the curve values of 0.862 (95% CI, 0.819-0.905) in the training cohort, 0.834 (95% CI, 0.780-0.908) in the internal validation cohort and 0.867 (95% CI, 0.785-0.950) in the external validation cohort, respectively.

CONCLUSIONS

The nomogram based on tumor and PE radiomics features extracted from preoperative multiparameter MRI and clinical factors can predict the risk of BI in patients with AM.

The applicability of established clinical and histopathological risk factors for tumor recurrence during long-term postoperative care in meningioma patients

Risk factors to predict late-onset tumor recurrence in meningioma patients are urgently needed to schedule control intervals during long-term follow-up. We therefore analyzed the value of established risk factors for postoperative meningioma recurrence for the prediction of long-term prognosis. Correlations of clinical and histopathological variables with tumor relapse after 3, 5, and 10 years following microsurgery were analyzed in uni- and multivariate analyses, and compared to findings in the entire cohort. In the entire cohort (N = 1218), skull base location (HR: 1.51, 95%CI 1.05–2.16; p = .026), Simpson ≥ IV resections (HR: 2.41, 95%CI 1.52–3.84; p < .001), high-grade histology (HR: 3.70, 95%CI 2.50–5.47; p < .001), and male gender (HR: 1.46, 95%CI 1.01–2.11; p = .042) were independent risk factors for recurrence. Skull base location (HR: 1.92, 95%CI 1.17–3.17; p = .010 and HR: 2.02, 95%CI 1.04–3.95; p = .038) and high-grade histology (HR: 1.87, 95%CI 1.04–3.38; p = .038 and HR: 2.29, 95%CI 1.07–4.01; p = .034) but not subtotal resection (HR: 1.53, 95%CI .68–3.45; p = .303 and HR: 1.75, 95%CI .52–5.96; p = .369) remained correlated with recurrence after a recurrence-free follow-up of ≥ 3 and ≥ 5 years, respectively. Postoperative tumor volume was related with recurrence in general (p < .001) but not beyond a follow-up of ≥ 3 years (p > .05). In 147 patients with a follow-up of ≥ 10 years, ten recurrences occurred and were not correlated with any of the analyzed variables. Skull base tumor location and high-grade histology but not the extent of resection should be considered when scheduling the long-term follow-up after meningioma surgery. Recurrences ≥ 10 years after surgery are rare, and predictors are lacking.