Meningioma: not always a benign tumor. A review of advances in the treatment of meningiomas

Maggio, Ilaria; Franceschi, Enrico; Tosoni, Alicia; Nunno, Vincenzo Di; Gatto, Lidia; Lodi, Raffaele; Brandes, Alba A.

doi:10.2217/cns-2021-0003

Cited by 78 publications

(60 citation statements)

References 134 publications

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“…Meningioma [ 1 ] is the most common type of primary intracranial tumor of the central nervous system, accounting for about one-third of all tumors of the central nervous system. It is a brain tumor originating from the meninges and arachnoid capillary cells, mostly with benign development [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Super-selective Embolization for Parasagittal Meningiomas and Its Effect on the Level of Inflammatory Factors

Zheng

Jia

Zhang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Objective. To evaluate the effectiveness of super-selective embolization for parasagittal meningiomas and its effect on the level of inflammatory factors. Methods. A total of 48 patients with parasagittal meningiomas diagnosed and treated in our hospital from September 2018 to March 2020 were randomly included and assigned to receive meningioma resection (control group) or meningioma resection plus super-selective embolization (study group), with 24 patients in each group. Outcome measures included clinical indices, tumor resection outcome, inflammatory factor levels, and follow-up results. Results. Patients in the study group had shorter operative time and less intraoperative bleeding volume than those in the control group ( P < 0.05 ). The study group had more patients with Simpson I resection (87.50%) than the control group (62.50%) ( P < 0.05 ). There was no statistically significant difference in the levels of inflammatory factors between the two groups of patients before treatment ( P > 0.05 ). After treatment, the levels of interleukin (IL)-6, tumor necrosis factor (TNF)-α, and hypersensitive C-reactive protein (hs-CRP) in patients in the study group were significantly lower than those of the control group. The results of the three-month follow-up showed that one patient in the study group was reoperated for tumor recurrence and there was no death record, while three patients in the control group were reoperated for tumor recurrence and one patient died. The difference in the recurrence and mortality between the two groups did not come up to the statistical standard ( P > 0.05 ). Conclusion. Super-selective embolization for parasagittal meningiomas contributes to reducing intraoperative bleeding, effectively improving tumor resection and surgical safety, and lowering inflammatory factor levels. Further trials are, however, required before clinical promotion.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of Super-selective Embolization for Parasagittal Meningiomas and Its Effect on the Level of Inflammatory Factors

Zheng

Jia

Zhang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“…Meningioma is one of the most common intracranial tumors, accounting for more than one-third of all primary central nervous system tumors [ 1 ]. Meningiomas could be usually diagnosed by accident and be generally considered less malignant than other intracranial tumors [ 2 ]. Meningiomas originate from arachnoid cells located on the inner surface of the dura mater, usually from meningeal precursor cells derived from the mesoderm and neural crest.…”

Section: Introductionmentioning

confidence: 99%

“…Meningiomas originate from arachnoid cells located on the inner surface of the dura mater, usually from meningeal precursor cells derived from the mesoderm and neural crest. Among meningiomas, most meningiomas belong to WHO grade I benign tumors, and the recurrence rate is very low, while nearly 5% are WHO grade II/III tumors, showing a higher nature of invasion and recurrence [ 2 , 3 ]. The diagnosis of meningioma largely depends on radiology.…”

Section: Introductionmentioning

confidence: 99%

“…It is estimated that the 10-year overall survival rate of nonmalignant meningiomas is 81.4%, while that of grade II meningiomas is 53%, and that of grade III meningiomas is 0% [ 1 ]. The 5-year recurrence rate after total resection of grade I meningioma is 7-23%, grade II meningioma is 50-55%, and grade III meningioma is 72-78%[ 1 , 2 ], which is a huge difference. At present, it is difficult to accurately judge the pathological grade of meningiomas before surgery, but it is very important for patients to choose treatment methods, formulate follow-up plans, and guide prognosis.…”

Section: Introductionmentioning

confidence: 99%

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A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas

Wang

Sun

et al. 2022

BioMed Research International

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Purpose. We aim to develop and validate a machine learning model by enhanced MRI to determine the pathological grading of meningiomas with unsupervised clustering image analysis method, which are multihabitat to reflect the inherent heterogeneity of tumors. Materials and Methods. A total of 120 patients with meningiomas confirmed by postoperative pathology were included in the study, including 60 patients with low-grade meningiomas (WHO grade I) and 60 patients with high-grade meningiomas (WHO grade II and WHO grade III). All patients underwent complete head enhanced magnetic resonance scans before surgery or any anti-tumor treatment. Enrolled patients in the group received surgical resection and obtained postoperative pathological data. The patients in the training group (84 people) and the test group (36 people) were randomly divided into two groups according to the ratio of 7 to 3. Multi-habitat features were extracted from MRI images based on enhanced T1. Machine learning method was used to model, which was used to distinguish high-grade meningioma from low-grade meningioma. At the same time, the obtained machine learning model was calibrated and evaluated. Results. In patients with low-grade meningioma and high-grade meningioma, we found significant differences in Silhouette coefficient (P<0.05). In the machine learning model, the area under the curve was 0.838 in the training group (sensitivity, 67.65%; specificity, 88.82%) and 0.73 in the test group (sensitivity, 69.05%; specificity, 71.43%). After the analysis of calibration curve and decision curve analysis, the model had shown the potential of great application value. Conclusions. Multi-habitat analysis based on enhanced MRI (T1) could accurately predict the pathological grading of meningiomas. This unsupervised image-based method could reflect the direct heterogeneity between high-grade meningiomas and low-grade meningiomas, which is of great significance for patients’ treatment and prevention of recurrence.

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“…With an incidence of 7.86 cases per 100,000 people per year [1], meningiomas represent the most frequent CNS tumor, accounting for about 36% of all cases and 53% of benign lesions [1]. They are often benign and mostly diagnosed incidentally [2].…”

Section: Introductionmentioning

confidence: 99%

Discovering the Molecular Landscape of Meningioma: The Struggle to Find New Therapeutic Targets

et al. 2021

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Meningiomas are the most common primary CNS tumors. They are usually benign but can present aggressive behavior in about 20% of cases. The genetic landscape of meningioma is characterized by the presence (in about 60% of cases) or absence of NF2 mutation. Low-grade meningiomas can also present other genetic alterations, particularly affecting SMO, TRAF7, KLF4 AKT1 and PI3KCA. In higher grade meningiomas, mutations of TERT promoter and deletion of CDKN2A/B seem to have a prognostic value. Furthermore, other genetic alterations have been identified, such as BAP1, DMD and PBRM1. Different subgroups of DNA methylation appear to be correlated with prognosis. In this review, we explored the genetic landscape of meningiomas and the possible therapeutic implications.

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Meningioma: not always a benign tumor. A review of advances in the treatment of meningiomas

Cited by 78 publications

References 134 publications

Effectiveness of Super-selective Embolization for Parasagittal Meningiomas and Its Effect on the Level of Inflammatory Factors

Effectiveness of Super-selective Embolization for Parasagittal Meningiomas and Its Effect on the Level of Inflammatory Factors

A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas

Discovering the Molecular Landscape of Meningioma: The Struggle to Find New Therapeutic Targets

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