Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
Objectives: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), apparent diffusion coefficient (ADC), and fractional...
| Publicado en: | European Radiology Vol. 29; no. 8; pp. 4068 - 4077 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2019
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| Acceso en línea: | Ver este registro en EBSCOhost |