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BackgroundThe role of kidney hypoxia is considered pivotal in the progression of chronic kidney disease. A widely used method to assess kidney oxygenation is blood oxygen level dependent (BOLD)–magnetic resonance imaging (MRI), but its interpretation remains problematic. The BOLD‐MRI signal is the result of kidney oxygen consumption (a proxy of glomerular filtration) and supply (ie, glomerular perfusion). Therefore, we hypothesized that with pharmacological modulation of kidney blood flow, renal oxygenation, as assessed by BOLD‐MRI, correlates to filtration fraction (ie, glomerular filtration rate/effective renal plasma flow) in healthy humans.Methods and ResultsEight healthy volunteers were subjected to continuous angiotensin‐II infusion at 0.3, 0.9, and 3.0 ng/kg per minute. At each dose, renal oxygenation and blood flow were assessed using BOLD and phase‐contrast MRI. Subsequently, “gold standard” glomerular filtration rate/effective renal plasma flow measurements were performed under the same conditions. Renal plasma flow decreased dose dependently from 660±146 to 467±103 mL/min per 1.73 m2 (F[3, 21]=33.3, P<0.001). Glomerular filtration rate decreased from 121±23 to 110±18 mL/min per 1.73 m2 (F[1.8, 2.4]=6.4, P=0.013). Cortical transverse relaxation rate (R2*; increases in R2* represent decreases in oxygenation) increased by 7.2±3.8% (F[3, 21]=7.37, P=0.001); medullar R2* did not change. Cortical R2* related to filtration fraction (R 2 0.46, P<0.001).ConclusionsBy direct comparison between “gold standard” kidney function measurements and BOLD MRI, we showed that cortical oxygenation measured by BOLD MRI relates poorly to glomerular filtration rate but is associated with filtration fraction. For future studies, there may be a need to include renal plasma flow measurements when employing renal BOLD‐MRI.

Background and purpose: Automatic approaches are widely implemented to automate dose optimization in radiotherapy treatment planning. This study systematically investigates how to configure automatic planning in order to create the best possible plans. Materials and methods: Automatic plans were generated using protocol based automatic iterative optimization. Starting from a simple automation protocol which consisted of the constraints for targets and organs at risk (OAR), the performance of the automatic approach was evaluated in terms of target coverage, OAR sparing, conformity, beam complexity, and plan quality. More complex protocols were systematically explored to improve the quality of the automatic plans. The protocols could be improved by adding a dose goal on the outer 2 mm of the PTV, by setting goals on strategically chosen subparts of OARs, by adding goals for conformity, and by limiting the leaf motion. For prostate plans, development of an automated post-optimization procedure was required to achieve precise control over the dose distribution. Automatic and manually optimized plans were compared for 20 head and neck (H&N), 20 prostate, and 20 rectum cancer patients. Results: Based on simple automation protocols, the automatic optimizer was not always able to generate adequate treatment plans. For the improved final configurations for the three sites, the dose was lower in automatic plans compared to the manual plans in 12 out of 13 considered OARs. In blind tests, the automatic plans were preferred in 80% of cases. Conclusions: With adequate, advanced, protocols the automatic planning approach is able to create high-quality treatment plans.