## Abstract

### Background

The standard uptake value (SUV) approach in oncological positron emission tomography has known shortcomings, all of which affect the reliability of the SUV as a surrogate of the targeted quantity, the metabolic rate of [^{18}F]fluorodeoxyglucose (FDG), *K*
_{
m
}. Among the shortcomings are time dependence, susceptibility to errors in scanner and dose calibration, insufficient correlation between systemic distribution volume and body weight, and, consequentially, residual inter-study variability of the arterial input function (AIF) despite SUV normalization. Especially the latter turns out to be a crucial factor adversely affecting the correlation between SUV and *K*
_{
m
} and causing inter-study variations of tumor SUVs that do not reflect actual changes of the metabolic uptake rate. In this work, we propose to replace tumor SUV by the tumor-to-blood standard uptake ratio (SUR) in order to distinctly improve the linear correlation with *K*
_{
m
}.

### Methods

Assuming irreversible FDG kinetics, SUR can be expected to exhibit a much better linear correlation to *K*
_{
m
} than SUV. The theoretical derivation for this prediction is given and evaluated in a group of nine patients with liver metastases of colorectal cancer for which 15 fully dynamic investigations were available and *K*
_{
m
} could thus be derived from conventional Patlak analysis.

### Results

For any fixed time point *T* at sufficiently late times post injection, the Patlak equation predicts a linear correlation between SUR and *K*
_{
m
} under the following assumptions: (1) approximate shape invariance (but arbitrary scale) of the AIF across scans/patients and (2) low variability of the apparent distribution volume *V*
_{
r
} (the intercept of the Patlak Plot). This prediction - and validity of the underlying assumptions - has been verified in the investigated patient group. Replacing tumor SUVs by SURs does improve the linear correlation of the respective parameter with *K*
_{
m
} from *r* = 0.61 to *r* = 0.98.

### Conclusions

SUR is an easily measurable parameter that is highly correlated to *K*
_{
m
}. In this respect, it is clearly superior to SUV. Therefore, SUR should be seriously considered as a drop-in replacement for SUV-based approaches.