Advanced CT techniques for assessing hepatocellular carcinoma.
Yuko NakamuraToru HigakiYukiko HondaFuminari TatsugamiChihiro TaniWataru FukumotoKeigo NaritaShota KondoMotonori AkagiKazuo AwaiPublished in: La Radiologia medica (2021)
Hepatocellular carcinoma (HCC) is the sixth-most common cancer in the world, and hepatic dynamic CT studies are routinely performed for its evaluation. Ongoing studies are examining advanced imaging techniques that may yield better findings than are obtained with conventional hepatic dynamic CT scanning. Dual-energy CT-, perfusion CT-, and artificial intelligence-based methods can be used for the precise characterization of liver tumors, the quantification of treatment responses, and for predicting the overall survival rate of patients. In this review, the advantages and disadvantages of conventional hepatic dynamic CT imaging are reviewed and the general principles of dual-energy- and perfusion CT, and the clinical applications and limitations of these technologies are discussed with respect to HCC. Finally, we address the utility of artificial intelligence-based methods for diagnosing HCC.
Keyphrases
- dual energy
- computed tomography
- image quality
- artificial intelligence
- contrast enhanced
- machine learning
- magnetic resonance imaging
- big data
- high resolution
- deep learning
- end stage renal disease
- positron emission tomography
- magnetic resonance
- peritoneal dialysis
- chronic kidney disease
- photodynamic therapy
- ejection fraction
- prognostic factors
- patient reported