About this Research Topic
Meningiomas are the most common predominantly non-malignant intracranial neoplasms, comprising 40.8% of all such tumors and 56.2% of all non-malignant variants. Despite their prevalence, meningiomas have not been studied as extensively as some other intracranial tumors, such as gliomas. This could partly be attributed to the lower malignancy rates and comparatively favorable prognosis associated with meningiomas. Nevertheless, a subset of meningiomas, particularly those classified as WHO Grade II and III, are characterized by more aggressive or malignant behaviors, leading to a higher rate of tumor recurrence. Moreover, even low-grade meningiomas can carry a risk of morbidity and mortality, often due to factors such as their large size and location in surgically high-risk areas. Additionally, meningiomas can also occur in children and adolescents, with incidence rates ranging from 0.4 to 4.6% of all primary brain tumors, and this subset of patients is considered more aggressive than their adult counterparts. Therefore, advancing our understanding of meningiomas is crucial for developing effective treatment strategies and enhancing patient outcomes.
Recent studies have provided meaningful insights into this area. A notable development is the identification of genetic biomarkers that may predict tumor behavior. These encompass chromosomal instability, epigenetic modifications, NF2 and non-NF2 mutations, familial syndromes, among others. Neuroimaging is another rapidly evolving field. Advanced MRI techniques, PET, radiomics, and artificial intelligence are increasingly enabling non-invasive yet detailed and personalized descriptions of the molecular and metabolic characteristics of meningiomas, especially in preoperative contexts. Such advancements are promising for improving differential diagnosis, enhancing subtyping and grading, assessing growth patterns, and predicting patient outcomes.
This Research Topic endeavors to expand our understanding of the diagnosis and treatment of meningiomas across a wide variety of types. For instance, our studies may include cases from adult patients and those with pediatric onset, as well as idiopathic and radiation-induced meningiomas, among others. We are particularly interested in contributions that explore innovative approaches in these areas. Please note, that manuscripts centered exclusively on bioinformatics or computational analyses of publicly available genomic or transcriptomic databases, lacking significant and relevant validation, are not within the scope of this topic. We welcome submissions of Original Research, Review articles, and Mini-reviews focusing on, but not limited to, the following sub-topics:
— Advances in Imaging Techniques: Exploring the latest advancements in MRI, CT, PET, and other modalities.
— Radiomics and Model Building: Exploring how radiomics-extracted imaging features aid in developing models for improved clinical decision-making and patient management.
— Utilization of Artificial Intelligence (AI) in Perioperative Management: Exploring the role of AI in optimizing perioperative strategies.
— Emerging Diagnostic and Prognostic Markers for Meningiomas: Focusing on novel markers with the potential to enhance the accuracy of meningioma diagnosis and prognosis.
— Advances in Histopathological, Genetic, and Molecular Characteristics of Meningiomas: Exploring the latest developments in histopathology, genetics, and molecular attributes of meningiomas, along with their clinical implications.
— Implications and Complications of Current Treatment Approaches: Evaluating the effects and adverse outcomes associated with surgical resection, radiotherapy, chemotherapy, radiosurgery, and other treatment approaches.
— Assessment of Comprehensive Treatment Effects: Evaluating the impact of combined treatments, such as surgical resection followed by radiotherapy or radiosurgery.
— Novel Treatment Strategies and Techniques: Exploring new and emerging approaches and treatment algorithms for the management of meningiomas.
Recent studies have provided meaningful insights into this area. A notable development is the identification of genetic biomarkers that may predict tumor behavior. These encompass chromosomal instability, epigenetic modifications, NF2 and non-NF2 mutations, familial syndromes, among others. Neuroimaging is another rapidly evolving field. Advanced MRI techniques, PET, radiomics, and artificial intelligence are increasingly enabling non-invasive yet detailed and personalized descriptions of the molecular and metabolic characteristics of meningiomas, especially in preoperative contexts. Such advancements are promising for improving differential diagnosis, enhancing subtyping and grading, assessing growth patterns, and predicting patient outcomes.
This Research Topic endeavors to expand our understanding of the diagnosis and treatment of meningiomas across a wide variety of types. For instance, our studies may include cases from adult patients and those with pediatric onset, as well as idiopathic and radiation-induced meningiomas, among others. We are particularly interested in contributions that explore innovative approaches in these areas. Please note, that manuscripts centered exclusively on bioinformatics or computational analyses of publicly available genomic or transcriptomic databases, lacking significant and relevant validation, are not within the scope of this topic. We welcome submissions of Original Research, Review articles, and Mini-reviews focusing on, but not limited to, the following sub-topics:
— Advances in Imaging Techniques: Exploring the latest advancements in MRI, CT, PET, and other modalities.
— Radiomics and Model Building: Exploring how radiomics-extracted imaging features aid in developing models for improved clinical decision-making and patient management.
— Utilization of Artificial Intelligence (AI) in Perioperative Management: Exploring the role of AI in optimizing perioperative strategies.
— Emerging Diagnostic and Prognostic Markers for Meningiomas: Focusing on novel markers with the potential to enhance the accuracy of meningioma diagnosis and prognosis.
— Advances in Histopathological, Genetic, and Molecular Characteristics of Meningiomas: Exploring the latest developments in histopathology, genetics, and molecular attributes of meningiomas, along with their clinical implications.
— Implications and Complications of Current Treatment Approaches: Evaluating the effects and adverse outcomes associated with surgical resection, radiotherapy, chemotherapy, radiosurgery, and other treatment approaches.
— Assessment of Comprehensive Treatment Effects: Evaluating the impact of combined treatments, such as surgical resection followed by radiotherapy or radiosurgery.
— Novel Treatment Strategies and Techniques: Exploring new and emerging approaches and treatment algorithms for the management of meningiomas.
Keywords: radiosurgery, skull base surgery, meningioma, brain tumor, intracranial tumor, neuroimaging, artificial intelligence, radiomics, model building, genetic biomarker, comprehensive treatment, novel treatment strategy
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
