| Summary: | Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula>- and T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>-weighted images, pre-contrast quantitative T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula> maps (qT<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula>), and contrast-enhanced T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula>-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box–Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from <inline-formula><math display="inline"><semantics><mrow><mn>0.30</mn></mrow></semantics></math></inline-formula> to <inline-formula><math display="inline"><semantics><mrow><mn>0.99</mn></mrow></semantics></math></inline-formula>, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula>- and T<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>-weighted images, and decrease ICCs for qT<inline-formula><math display="inline"><semantics><msub><mrow></mrow><mn>1</mn></msub></semantics></math></inline-formula> maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.
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