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Differentiating medulloblastoma and pilocytic astrocytoma in children based on multimodal MRI radiomics model
Xinyu Wang1, Wenjing Li1, Yichen Guo1
1Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, zhengzhou, China.
Purpose:
Medulloblastoma (MB) and pilocytic astrocytoma (PA) are common in pediatric brain tumors and difficult to distinguish. To establish and evaluate a radiomics model based on multimodal MRI to distinguish medulloblastoma from pilocytic astrocytoma.
Methods:
Retrospective collection of magnetic resonance images from 113 patients with MB and 74 patients with PA. Radiomics analysis was performed on Dynamic Contrast-Enhanced T1 weighted imaging (DCE-T1WI), T2 weighted imaging (T2WI), and Apparent diffusion coefficient (ADC) images, respectively. A multimodal MRI combined radiomics model incorporating DCE-T1WI, T2WI, and ADC sequence features was developed by extraction of valuable features, and the radiomics nomogram was generated to evaluate its diagnostic capability. The DeLong test was used to compare the diagnostic performance of DCE-T1WI, T2WI, ADC single sequence model, and multimodal MRI radiomics model.
Results:
The combined model showed the highest performance among all models, with an area under the curve (AUC) of 0.999 on the primary cohort and maintained an AUC of 0.994 during the validation cohort. For the single-sequence model, the ADC sequence model performs better in the primary cohort, with an AUC of 0.996; the T2WI sequence model slightly outperforms in validation cohort, with an AUC of 0.985. The DCE-T1WI sequence model performed slightly worse than ADC and T2WI in the validation cohort, with an AUC of 0.951. Overall, the combined model performed best in the differential diagnosis of MB and PA.
Conclusion:
Multimodal MRI-based radiomics analysis is effective in differentiating MB from PA and radiomics imaging may have important clinical significance in the preoperative detection of posterior fossa brain tumors in children.
Insights
A new multimodal MRI radiomics model effectively distinguishes medulloblastoma (MB) from pilocytic astrocytoma (PA) in children. This advanced imaging approach shows high accuracy for preoperative diagnosis of pediatric posterior fossa brain tumors.
Area of Science:
- Radiology
- Oncology
- Medical Imaging Analysis
Background:
- Medulloblastoma (MB) and pilocytic astrocytoma (PA) are common pediatric brain tumors.
- Distinguishing between MB and PA using conventional imaging is challenging.
Purpose of the Study:
- To develop and validate a radiomics model using multimodal magnetic resonance imaging (MRI) for differentiating MB from PA.
- To assess the diagnostic performance of single MRI sequences versus a combined multimodal approach.
Main Methods:
- Retrospective analysis of MRI scans from 113 MB and 74 PA patients.
- Radiomics features extracted from Dynamic Contrast-Enhanced T1-weighted imaging (DCE-T1WI), T2-weighted imaging (T2WI), and Apparent Diffusion Coefficient (ADC) sequences.
- Development of a combined multimodal radiomics model and nomogram; comparison with single-sequence models using DeLong test.
Main Results:
- The combined multimodal radiomics model achieved high diagnostic accuracy, with an area under the curve (AUC) of 0.999 in the primary cohort and 0.994 in the validation cohort.
- Single-sequence models showed strong performance (ADC: AUC 0.996, T2WI: AUC 0.985), but the combined model outperformed them.
- The combined model demonstrated superior efficacy in the differential diagnosis of MB and PA.
Conclusions:
- Multimodal MRI-based radiomics analysis is a highly effective method for differentiating MB from PA.
- Radiomics imaging holds significant clinical potential for the preoperative detection of pediatric posterior fossa brain tumors.
