Sample size and statistical analysis
REGRESSION
Sample size calculation, with a 0.05 level of significance (α) and power (β) 80%, assuming a mean difference of 0.5 points in SEQ with an SD of 1.25, resulted in a sample size of 98 in each group.Data analysis was performed with Statistical Package for the Social Sciences version 28.0 (IBM) and R version 4.2.0 (The R Foundation).Differences between experimental and control groups in patient demographics and scan characteristics were assessed by independent samples t-test, and sex by chi-squared test.Comparisons of OEQ and SEQ were performed with the Wilcoxon rank sum test for unpaired data between the control group and each of the VMIs in the experimental group, and Wilcoxon signed rank test for paired data within the experimental group between VMI at 40 and 50 keV.Cohen’s D was used as effect size on the log-transformed OEQ data since attenuation, CNR and SNR showed normal distribution and noise was gamma distributed on the log scale. For SEQ the rank-biserial coefficient was reported as effect size. The influence of anatomical level, age, sex, and RCT groups on OEQ and SEQ were investigated by multivariable generalized mixed models. Patient ID was included as a random effect allowing for different latent mean values per patient. The log-transformed VA, CNR, and SNR were modelled by Gaussian likelihoods, while the log-transformed noise was modelled by a gamma likelihood, and an ordinal likelihood was used to model the resolved median subjective rating. Reported effect sizes and standard errors are those of the regression coefficients, which are in units of the (log-transformed) response variable per the units of the covariate.