ArticleFrontiers in oncology2021
A Clinical Semantic and Radiomics Nomogram for Predicting Brain Invasion in WHO Grade II Meningioma Based on Tumor and Tumor-to-Brain Interface Features.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed, 51 citations in OpenAlex.
- MRI-based preoperative WHO grade prediction in meningioma: development and comparison of deep learning, radiomics, clinical, and combined models in multicenter data.Journal of neuro-oncology · 2026Article
- Can brain-to-tumour outer interface radiomics improve the efficiency of MRI in predicting the brain invasion of meningiomas?Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Preoperative Prediction of Non-functional Pituitary Neuroendocrine Tumors and Posterior Pituitary Tumors Based on MRI Radiomic Features.Journal of imaging informatics in medicine · 2026Article
- Preoperative prediction of brain invasion in meningiomas: a comparison of diffusion kurtosis imaging and diffusion tensor imaging.BMC neurology · 2025Article
- A systematic review of multiparametric magnetic resonance imaging radiomics in the prediction of brain invasion in meningioma.Translational cancer research · 2025Review
- Advancements in the application of MRI radiomics in meningioma.Radiation oncology (London, England) · 2025Review
- Trends in Malignant and Benign Brain Tumor Incidence and Mobile Phone Use in the U.S. (2000-2021): A SEER-Based Study.International journal of environmental research and public health · 2025Article
- Radiomics based on brain-to-tumor interface enables prediction of metastatic tumor type of brain metastasis: a proof-of-concept study.La Radiologia medica · 2025Article
- MRI-based multiregional radiomics for preoperative prediction of Ki-67 expression in meningiomas: a two-center study.Frontiers in neurology · 2025Article
- FLAIR-based radiomics signature from brain-tumor interface for early prediction of response to EGFR-TKI therapy in NSCLC patients with brain metastasis.Frontiers in cell and developmental biology · 2025Article
- New imaging findings of tumor invasion into brain tissue: "Peritumoral Hyperintense Enhancement Sign".Frontiers in human neuroscience · 2025Article
- Peritumoral vessel characteristics on magnetic resonance venography reflect the sinus invasion status of para-sinus meningioma.Quantitative imaging in medicine and surgery · 2024Article
- Risk stratification of thymic epithelial tumors based on peritumor CT radiomics and semantic features.Insights into imaging · 2024Article
- Preoperative prediction of CNS WHO grade and tumour aggressiveness in intracranial meningioma based on radiomics and structured semantics.Scientific reports · 2024Article
- Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study.BMC medical imaging · 2024Article
- Development and external validation of a novel score for predicting postoperative 30‑day mortality in tumor craniotomy patients: A cross‑sectional diagnostic study.Oncology letters · 2024Article
- The development of a combined clinico-radiomics model for predicting post-operative recurrence in atypical meningiomas: a multicenter study.Journal of neuro-oncology · 2024Article
- Applications and Integration of Radiomics for Skull Base Oncology.Advances in experimental medicine and biology · 2024Review
- A Full View of Papillary Craniopharyngioma Based on Expanded Endonasal Approach: A Comprehensive Clinical Characterization of 101 Cases.Journal of clinical medicine · 2023Article
- A magnetic resonance imaging based radiomics model to predict mitosis cycles in intracranial meningioma.Scientific reports · 2023Article
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16 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBrain invasion in meningioma has independent associations with increased risks of tumor progression, lesion recurrence, and poor prognosis. Therefore, this study aimed to construct a model for predicting brain invasion in WHO grade II meningioma by using preoperative MRI.
methodsOne hundred seventy-three patients with brain invasion and 111 patients without brain invasion were included. Three mainstream features, namely, traditional semantic features and radiomics features from tumor and tumor-to-brain interface regions, were acquired. Predictive models correspondingly constructed on each feature set or joint feature set were constructed.
resultsTraditional semantic findings, e.g., peritumoral edema and other four features, had comparable performance in predicting brain invasion with each radiomics feature set. By taking advantage of semantic features and radiomics features from tumoral and tumor-to-brain interface regions, an integrated nomogram that quantifies the risk factor of each selected feature was constructed and had the best performance in predicting brain invasion (area under the curve values were 0.905 in the training set and 0.895 in the test set).
conclusionsThis study provided a clinically available and promising approach to predict brain invasion in WHO grade II meningiomas by using preoperative MRI.
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