PURPOSE:

Assessing renal perfusion in-vivo is challenging and quantitative information regarding renal hemodynamics is hardly incorporated in medical decision-making while abnormal renal hemodynamics might play a crucial role in the onset and progression of renal disease. Combining physiological stimuli with rubidium-82 positron emission tomography/computed tomography (82Rb PET/CT) offers opportunities to test the kidney perfusion under various conditions. The aim of this study is (1) to investigate the application of a one-tissue compartment model for measuring renal hemodynamics with dynamic 82Rb PET/CT imaging, and (2) to evaluate whether dynamic PET/CT is sensitive to detect differences in renal hemodynamics in stress conditions compared to resting state.

METHODS:

A one-tissue compartment model for the kidney was applied to cardiac 82Rb PET/CT scans that were obtained for ischemia detection as part of clinical care. Retrospective data, collected from 17 patients undergoing dynamic myocardial 82Rb PET/CT imaging in rest, were used to evaluate various CT-based volumes of interest (VOIs) of the kidney. Subsequently, retrospective data, collected from 10 patients (five impaired kidney functions and five controls) undergoing dynamic myocardial 82Rb PET/CT imaging, were used to evaluate image-derived input functions (IDIFs), PET-based VOIs of the kidney, extraction fractions, and whether dynamic 82Rb PET/CT can measure renal hemodynamics differences using the renal blood flow (RBF) values in rest and after exposure to adenosine pharmacological stress.

RESULTS:

The delivery rate (K1) values showed no significant (p = 0.14) difference between the mean standard deviation (SD) K1 values using one CT-based VOI and the use of two, three, and four CT-based VOIs, respectively 2.01(0.32), 1.90(0.40), 1.93(0.39), and 1.94(0.40) mL/min/mL. The ratio between RBF in rest and RBF in pharmacological stress for the controls were overall significantly lower compared to the impaired kidney function group for both PET-based delineation methods (region growing and iso-contouring), with the smallest median interquartile range (IQR) of 0.40(0.28-0.66) and 0.96(0.62-1.15), respectively (p < 0.05). The K1 of the impaired kidney function group were close to 1.0 mL/min/mL.

CONCLUSIONS:

This study demonstrated that obtaining renal K1 and RBF values using 82Rb PET/CT was feasible using a one-tissue compartment model. Applying iso-contouring as the PET-based VOI of the kidney and using AA as an IDIF is suggested for consideration in further studies. Dynamic 82Rb PET/CT imaging showed significant differences in renal hemodynamics in rest compared to when exposed to adenosine. This indicates that dynamic 82Rb PET/CT has potential to detect differences in renal hemodynamics in stress conditions compared to the resting state, and might be useful as a novel diagnostic tool for assessing renal perfusion.