Dose-dependent regional cerebral blood flow changes during remifentanil infusion in humans - A positron emission tomography study

Background: The current study investigated dose-dependent effects of the mu -selective agonist remifentanil on regional cerebral blood now (rCBF) in v olunteers using positron emission tomography (PET). Methods: Ten right-handed male volunteers were included in a O-15-water PET study. Seven underwent three conditions: control (saline), low remifentani l (0.05 mug . kg(-1) . min(-1)), and moderate remifentanil(0.05 mug . kg(-1 ) . min(-1)). The remaining three participated in the low and moderate cond itions. A semi-randomized study protocol was used with control and remifent anil conditions 3 or more months apart. The order of low and moderate condi tions was randomized. Cardiovascular and respiratory parameters were monito red. Categoric comparisons between the control, low, and moderate condition s and a pixelwise correlation analysis across the three conditions were per formed (P < 0.05, corrected for multiple comparisons) using statistical par ametric mapping. Results: Cardiorespiratory parameters were maintained constant over time, A t the low remifentanil dose, significant increases in relative rCBF were no ted in the lateral prefrontal cortices, inferior parietal cortices, and sup plementary motor area. Relative rCBF decreases were observed in the basal m ediofrontal cortex, cerebellum, superior temporal lobe, and midbrain gray m atter. Moderate doses further increased rCBF in mediofrontal and anterior c ingulate cortices, occipital lobe transition, and caudal periventricular gr ey. Significant decreases were detected in the inferior parietal lobes. The se dose-dependent effects of remifentanil on rCBF were confirmed by a corre lation analysis. Conclusion: Remifentanil induced dose-dependent changes in relative rCBF in areas involved in pain processing. At moderate doses, rCBF responses were additionally detected in structures known to participate in modulation of v igilance and alertness. Insight into the mechanisms of opioid analgesia wit hin the pain-processing neural network may lead to a better understanding o f antinociception and opioid treatment.