Reproducibility of CT-Based Hepatocellular Carcinoma Radiomic Features across Different Contrast Imaging Phases: A Proof of Concept on SORAMIC Trial Data.
Abdalla IbrahimYousif WidaatallaTurkey A RefaeeSergey PrimakovRazvan L MicleaOsman ÖcalMatthias Philipp FabritiusMichael IngrischJens RickeRoland HustinxFelix M MottaghyHenry C WoodruffMax SeidenstickerPhilippe LambinPublished in: Cancers (2021)
Handcrafted radiomic features (HRFs) are quantitative imaging features extracted from regions of interest on medical images which can be correlated with clinical outcomes and biologic characteristics. While HRFs have been used to train predictive and prognostic models, their reproducibility has been reported to be affected by variations in scan acquisition and reconstruction parameters, even within the same imaging vendor. In this work, we evaluated the reproducibility of HRFs across the arterial and portal venous phases of contrast-enhanced computed tomography images depicting hepatocellular carcinomas, as well as the potential of ComBat harmonization to correct for this difference. ComBat harmonization is a method based on Bayesian estimates that was developed for gene expression arrays, and has been investigated as a potential method for harmonizing HRFs. Our results show that the majority of HRFs are not reproducible between the arterial and portal venous imaging phases, yet a number of HRFs could be used interchangeably between those phases. Furthermore, ComBat harmonization increased the number of reproducible HRFs across both phases by 1%. Our results guide the pooling of arterial and venous phases from different patients in an effort to increase cohort size, as well as joint analysis of the phases.
Keyphrases
- computed tomography
- contrast enhanced
- high resolution
- gene expression
- magnetic resonance imaging
- magnetic resonance
- dual energy
- diffusion weighted
- end stage renal disease
- healthcare
- deep learning
- newly diagnosed
- chronic kidney disease
- randomized controlled trial
- ejection fraction
- dna methylation
- machine learning
- climate change
- fluorescence imaging
- mass spectrometry
- photodynamic therapy
- optical coherence tomography
- image quality
- open label
- peritoneal dialysis
- patient reported
- big data
- high speed
- phase iii