Radiomics features based on T2-weighted fluid-attenuated inversion recovery MRI predict the expression levels of CD44 and CD133 in lower-grade gliomas.
Zhenhua WangXiaoping TangJi WuZhaotao ZhangKeng HeDi WuShiQi ChenXinlan XiaoPublished in: Future oncology (London, England) (2021)
Objective: To verify the association between CD44 and CD133 expression levels and the prognosis of patients with lower-grade gliomas (LGGs) and constructing radiomic models to predict those two genes' expression levels before surgery. Materials & methods: Genomic data of patients with LGG and the corresponding T2-weighted fluid-attenuated inversion recovery images were downloaded from the Cancer Genome Atlas and the Cancer Imaging Archive, which were utilized for prognosis analysis, radiomic feature extraction and model construction, respectively. Results & conclusion: CD44 and CD133 expression levels in LGG can significantly affect the prognosis of patients with LGG. Based on the T2-weighted fluid-attenuated inversion recovery images, the radiomic features can effectively predict the expression levels of CD44 and CD133 before surgery.
Keyphrases
- poor prognosis
- contrast enhanced
- nk cells
- magnetic resonance imaging
- magnetic resonance
- minimally invasive
- binding protein
- machine learning
- papillary thyroid
- genome wide
- high grade
- coronary artery bypass
- computed tomography
- high resolution
- coronary artery disease
- convolutional neural network
- transcription factor
- photodynamic therapy
- optical coherence tomography
- single cell
- squamous cell
- big data
- lymph node metastasis
- network analysis