Does Dual-Energy Computed Tomography Material Decomposition Improve Radiomics Capability to Predict Survival in Head and Neck Squamous Cell Carcinoma Patients? A Preliminary Investigation.
Simon BernatzInes BöthJörg AckermannIris BurckScherwin MahmoudiLukas LengaSimon S MartinJan-Erik ScholtzVitali KochLeon D GrünewaldIna KochTimo StöverPeter J WildRia WinkelmannThomas J VoglDaniel Pinto Dos SantosPublished in: Journal of computer assisted tomography (2023)
Radiomics AI applications may be used for SCCHN survival prognostication, but the spectral information of DECT material decomposition did not improve the model's performance in our preliminary investigation.
Keyphrases
- dual energy
- computed tomography
- contrast enhanced
- end stage renal disease
- ejection fraction
- magnetic resonance imaging
- newly diagnosed
- positron emission tomography
- image quality
- chronic kidney disease
- prognostic factors
- squamous cell carcinoma
- machine learning
- patient reported outcomes
- health information
- deep learning