Impact of muscular uptake and statistical noise on tumor quantification based on simulated FDG-PET studies

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PurposeThe aim of this work is to study the effect of physiological muscular uptake variations and statistical noise on tumor quantification in FDG-PET studies. MethodsWe designed a realistic framework based on simulated FDG-PET acquisitions from an anthropomorphic phantom that included different muscular uptake levels and three spherical lung lesions with diameters of 31, 21 and 9mm. A distribution of muscular uptake levels was obtained from 136 patients remitted to our center for whole-body FDG-PET. Simulated FDG-PET acquisitions were obtained by using the Simulation System for Emission Tomography package (SimSET) Monte Carlo package. Simulated data was reconstructed by using an iterative Ordered Subset Expectation Maximization (OSEM) algorithm implemented in the Software for Tomographic Image Reconstruction (STIR) library. Tumor quantification was carried out by using estimations of SUVmax, SUV50 and SUVmean from different noise realizations, lung lesions and multiple muscular uptakes. ResultsOur analysis provided quantification variability values of 17–22% (SUVmax), 11–19% (SUV50) and 8–10% (SUVmean) when muscular uptake variations and statistical noise were included. Meanwhile, quantification variability due only to statistical noise was 7–8% (SUVmax), 3–7% (SUV50) and 1–2% (SUVmean) for large tumors (>20mm) and 13% (SUVmax), 16% (SUV50) and 8% (SUVmean) for small tumors (<10mm), thus showing that the variability in tumor quantification is mainly affected by muscular uptake variations when large enough tumors are considered. In addition, our results showed that quantification variability is strongly dominated by statistical noise when the injected dose decreases below 222MBq. ConclusionsOur study revealed that muscular uptake variations between patients who are totally relaxed should be considered as an uncertainty source of tumor quantification values.