MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features.
Abdalla IbrahimBruno BarufaldiTurkey A RefaeeTelmo M Silva FilhoRaymond J AcciavattiZohaib SalahuddinRoland HustinxFelix Manuel MottaghyAndrew D A MaidmentPhilippe LambinPublished in: Cancers (2022)
The reproducibility of handcrafted radiomic features (HRFs) has been reported to be affected by variations in imaging parameters, which significantly affect the generalizability of developed signatures and translation to clinical practice. However, the collective effect of the variations in imaging parameters on the reproducibility of HRFs remains unclear, with no objective measure to assess it in the absence of reproducibility analysis. We assessed these effects of variations in a large number of scenarios and developed the first quantitative score to assess the reproducibility of CT-based HRFs without the need for phantom or reproducibility studies. We further assessed the potential of image resampling and ComBat harmonization for removing these effects. Our findings suggest a need for radiomics-specific harmonization methods. Our developed score should be considered as a first attempt to introduce comprehensive metrics to quantify the reproducibility of CT-based handcrafted radiomic features. More research is warranted to demonstrate its validity in clinical contexts and to further improve it, possibly by the incorporation of more realistic situations, which better reflect real patients' situations.
Keyphrases
- high resolution
- image quality
- contrast enhanced
- computed tomography
- dual energy
- clinical practice
- end stage renal disease
- magnetic resonance imaging
- chronic kidney disease
- climate change
- magnetic resonance
- positron emission tomography
- squamous cell carcinoma
- ejection fraction
- gene expression
- dna methylation
- peritoneal dialysis
- machine learning
- human health