Continuous variables were summarized as median (range) and categorical variables as number (percent). For the primary analysis, univariable associations were assessed between kinetic parameters and MVD dichotomized as low (≤ median value) vs. high (> median value). Associations were summarized using odds ratios (ORs) from univariable logistic regression models and the area under the receiver operating characteristic curve (AUC). Differences between lower and higher MVD were tested using the Wilcoxon rank-sum test. Due to testing four kinetic parameters, we used a Bonferroni-corrected significance threshold of α = 0.0125 to determine statistical significance. As a sensitivity analysis, we also performed an analogous analysis where we used Spearman’s rank correlation coefficient to evaluate associations of kinetic parameters with MVD as a continuous variable.

As a secondary, hypothesis-generating analysis, we used similar methods to evaluate associations of radiomic texture features with MVD, both as a dichotomous variable and a continuous variable. We used a significance threshold α = 0.01 to reduce the risk of false positive findings, though did not perform a full adjustment for multiple comparisons to avoid a substantial loss of statistical power. Two-sided confidence intervals (CIs) were calculated for all ORs, AUC values, and Spearman’s rank correlation coefficients. A confidence level of 95% was used for all CIs. All statistical tests performed were two-sided. Statistical calculations were conducted with the statistical computing language R (version 3.1.1; R Foundation for Statistical Computing, Vienna, Austria).

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