ArticleScientific data2025
A comprehensive dataset of germinoma on MRI/CT with clinical and radiomic data.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A Non-enhanced CT Dataset for Differential Diagnosis of Pediatric Extracranial Germ Cell Tumors.Scientific data · 2026Article
- Article
- A comprehensive dataset of germinoma on MRI/CT with clinical and radiomic data.Scientific data · 2025Article
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13 authors.
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Abstract
Intracranial germ cell tumors (GCTs) are rare neoplasms with a peak incidence in adolescents. Germinoma is the most common histological subtype of intracranial GCTs. Its symptoms include intracranial hypertension, visual field defects, and hormonal disorders, affecting the physical health of adolescents. Germinoma is sensitive to chemo-radiotherapy, and most patients do not require neurosurgical resection. Therefore, improving the accuracy of germinoma diagnosis helps to avoid unnecessary surgery. At present, the application of artificial intelligence (AI) in medical imaging has improved the accuracy of disease diagnosis. However, few studies focused on the AI model to diagnosis germinoma and there are no publicly available imaging datasets for germinoma. This study aimed to create a comprehensive dataset for germinoma using magnetic resonance imaging/computed tomography findings with clinical and radiomic data to train and validate AI models. Featuring 65 pathologically confirmed germinomas, the dataset included axial T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery, T1-weighted imaging, T1-weighted imaging with contrast enhancement, diffusion-weighted MR imaging, CT images, clinical data, and morphological and radiomic-based features obtained by segmentation.
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