Two nomograms based on radiomics models using triphasic CT for differentiation of adrenal lipid-poor benign lesions and metastases in a cancer population: an exploratory study.
Gongzheng WangBing KangJingjing CuiYan DengYun ZhaoCongshan JiXi-Ming WangPublished in: European radiology (2022)
• All four radiomics models and two nomograms using triphasic CT images exhibited favourable performances in three cohorts to characterise the cancer population's adrenal benign lesions and metastases. • Unenhanced and triphasic radiomics models had similar predictive performances, outperforming arterial and venous models. • Unenhanced and triphasic nomograms also exhibited similar efficacies and good clinical benefits, indicating that contrast-enhanced examinations could be avoided when identifying adrenal benign lesions and metastases.
Keyphrases
- contrast enhanced
- diffusion weighted
- magnetic resonance imaging
- dual energy
- computed tomography
- magnetic resonance
- papillary thyroid
- diffusion weighted imaging
- lymph node metastasis
- squamous cell
- squamous cell carcinoma
- deep learning
- image quality
- convolutional neural network
- fatty acid
- optical coherence tomography
- machine learning
- pet ct