CT-Based Radiomics Analysis Before Thermal Ablation to Predict Local Tumor Progression for Colorectal Liver Metastases.
Marjaneh TaghaviFemke StaalFernando Gomez MunozFarshad ImaniDavid B MeekRita SimõesLisa G KlompenhouwerUulke A van der HeideRegina G H Beets-TanMonique MaasPublished in: Cardiovascular and interventional radiology (2021)
A machine learning-based radiomics analysis of routine clinical CT imaging pre-ablation could act as a valuable biomarker model to predict local tumor progression with curative intent for colorectal liver metastases patients.
Keyphrases
- liver metastases
- contrast enhanced
- machine learning
- end stage renal disease
- computed tomography
- poor prognosis
- prognostic factors
- image quality
- ejection fraction
- newly diagnosed
- lymph node metastasis
- dual energy
- chronic kidney disease
- magnetic resonance imaging
- high resolution
- peritoneal dialysis
- radiofrequency ablation
- squamous cell carcinoma
- magnetic resonance
- clinical practice
- patient reported outcomes
- deep learning
- big data
- long non coding rna
- mass spectrometry
- pet ct