Fig. 1

Scatter plots with the results of the regression analysis. A) Scatter plot of the perfusion fraction f_tumor vs. BF_tumor. Linear regression model: \( {BF}_{tumor}\left[\frac{ml}{100 ml\ast \mathit{\min}}\right]=3.772\frac{ml}{100 ml\ast \mathit{\min}\ast \%}\ast {f}_{tumor}\left[\%\right]-1.471\frac{ml}{100 ml\ast \mathit{\min}} \). Goodness of fit: R² = 0.774. B) Scatter plot of the perfusion fraction f_tumor vs. BV_tumor. Linear regression model: \( {BV}_{tumor}\left[\frac{ml}{100 ml}\right]=0.388\frac{ml}{100 ml\ast \%}\ast {f}_{tumor}\left[\%\right]-1.327\frac{ml}{100 ml} \). Goodness of fit: R² = 0.608. C) Scatter plot of the perfusion fraction f_tumor vs. MVD_tumor. Linear regression model: \( {MVD}_{tumor}\left[\frac{1}{mm^2}\right]=3.721\frac{1}{mm^2\ast \%}\ast {f}_{tumor}\left[\%\right]-1.144\frac{1}{mm^2} \). Goodness of fit: R² = 0.476. D) Scatter plot of the perfusion fraction f_tumor vs. MVA_tumor. Linear regression model: \( {MVA}_{tumor}=0.00181\frac{1}{\%}\ast {f}_{tumor}\left[\%\right]-0.00306 \). Goodness of fit: R² = 0.548. E) Scatter plot of BF_tumor vs. MVD_tumor. Linear regression model: \( {MVD}_{tumor}\left[\frac{1}{mm^2}\right]=0.745\frac{100 ml\ast \mathit{\min}}{mm^2\ast ml}\ast {BF}_{tumor}\left[\frac{ml}{100 ml\ast \mathit{\min}}\right]+10.125\frac{1}{mm^2} \). Goodness of fit: R² = 0.490. F) Scatter plot of BF_tumor vs. MVA_tumor. Linear regression model: \( {MVA}_{tumor}=0.00037\frac{100 ml\ast \mathit{\min}}{ml}\ast {BF}_{tumor}\left[\frac{ml}{100 ml\ast \mathit{\min}}\right]+0.00209 \). Goodness of fit: R² = 0.578. G) Scatter plot of BV_tumor vs. MVD_tumor. Linear regression model: \( {MVD}_{tumor}\left[\frac{1}{mm^2}\right]=4.489\frac{100 ml}{mm^2\ast ml}\ast {BV}_{tumor}\left[\frac{ml}{100 ml}\right]+28.346\frac{1}{mm^2} \). Goodness of fit: R² = 0.281. H) Scatter plot of BV_tumor vs. MVA_tumor.. Linear regression model: \( {MVA}_{tumor}=0.00235\frac{100 ml}{ml}\ast {BV}_{tumor}\left[\frac{ml}{100 ml}\right]+0.0106 \). Goodness of fit: R² = 0.372