ArticleThe British journal of radiology2022
A radiomics nomogram for predicting the meningioma grade based on enhanced
Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- MRI radiomics in diagnosing high and low grade meningiomas through systematic review and meta analysis.Scientific reports · 2025Pooled it
- Performance of Radiomics-based machine learning and deep learning-based methods in the prediction of tumor grade in meningioma: a systematic review and meta-analysis.Neurosurgical review · 2025Pooled it
- Late surgical site hemorrhage is a possible radiologic indicator of early tumor recurrence in grossly totally resected high-grade meningioma: A case report.Radiology case reports · 2026Article
- A predictive nomogram model for overall survival in obstructive colorectal cancer based on clinical and laboratory indicators.Journal of gastrointestinal oncology · 2026Article
- Advancements in the application of MRI radiomics in meningioma.Radiation oncology (London, England) · 2025Review
- An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.Scientific reports · 2025Article
- An MRI-Based Deep Transfer Learning Radiomics Nomogram to Predict Ki-67 Proliferation Index of Meningioma.Journal of imaging informatics in medicine · 2024Article
- The value of an apparent diffusion coefficient histogram model in predicting meningioma recurrence.Journal of cancer research and clinical oncology · 2023Article
- Article
- MRI-based machine learning models predict the malignant biological behavior of meningioma.BMC medical imaging · 2023Article
- Meningioma grading based on positron emission tomography: A systematic review and meta-analysis.World neurosurgery: X · 2023Article
- Nomograms for Predicting the Risk and Prognosis of Liver Metastases in Pancreatic Cancer: A Population-Based Analysis.Journal of personalized medicine · 2023Article
- Performance comparison of 2D and 3D MRI radiomics features in meningioma grade prediction: A preliminary study.Frontiers in oncology · 2023Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe objective of this study was to develop a radiomics nomogram for predicting the meningioma grade based on enhanced
methods188 patients with meningioma were analyzed retrospectively. There were 94 high-grade meningioma to form high-grade group and 94 low-grade meningioma were selected randomly to form low-grade group. Clinical data and MRI features were analyzed and compared. The clinical model was built by using the significant variables. The least absolute shrinkage and selection operator regression was used to select the most valuable radiomics feature. The radiomics signature was built and the Rad-score was calculated. The radiomics nomogram was developed by the significant variables of the clinical factors and Rad-score. The calibration curve and the Hosmer-Lemeshow test were used to evaluate the radiomics nomogram. Different models were compared by Delong test and decision curve analysis curve.
resultsThe sex, size and surrounding invasion were used to build clinical model. The area under the receiver operator characteristic curve (AUC) of clinical model was 0.870 (95% CI: 0.782-0.959). Nine features were used to construct the radiomics signature. The AUC of the radiomics signature was 0.885 (95% CI: 0.802-0.968). The AUC of radiomics nomogram was 0.952 (95% CI: 0.904-1). The AUC of radiomics nomogram was higher than that of clinical model and radiomics signature with a significant difference (
conclusionThe radiomics nomogram based on enhanced ADVANCES IN KNOWLEDGE: 1. We first constructed a radiomic nomogram to predict the meningioma grade.2. We compared the results of the clinical model, radiomics signature and radiomics nomogram.
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