Physiological system analysis of the kidney by high-temporal-resolution monitoring of an oxygenation step response

Examine the feasibility of characterizing the regulation of renal oxygenation using high-temporal-resolution monitoring of the $$ response to a step-like oxygenation stimulus.

For $$ mapping, multi-echo gradient-echo imaging was used (temporal resolution = 9 seconds). A step-like renal oxygenation challenge was applied involving sequential exposure to hyperoxia (100% O₂ ), hypoxia (10% O₂ + 90% N₂ ), and hyperoxia (100% O₂ ). In vivo experiments were performed in healthy rats (N = 10) and in rats with bilateral ischemia-reperfusion injury (N = 4). To assess the step response of renal oxygenation, a second-order exponential model was used (model parameters: amplitude [A], time delay [Δt], damping constant [D], and period of the oscillation [T]) for renal cortex, outer stripe of the outer medulla, inner stripe of the outer medulla, and inner medulla.

The second-order exponential model permitted us to model the exponential $$ recovery and the superimposed $$ oscillation following renal oxygenation stimulus. The in vivo experiments revealed a difference in D_{outer medulla} between healthy controls (D < 1, indicating oscillatory recovery) and ischemia-reperfusion injury (D > 1, reflecting aperiodic recovery). The increase in D_{outer medulla} by a factor of 3.7 (outer stripe of the outer medulla) and 10.0 (inner stripe of the outer medulla) suggests that this parameter might be rather sensitive to (patho)physiological oxygenation changes.

This study demonstrates the feasibility of monitoring the dynamic oxygenation response of renal tissues to a step-like oxygenation challenge using high-temporal-resolution $$ mapping. Our results suggest that the implemented system analysis approach may help to unlock questions regarding regulation of renal oxygenation, with the ultimate goal of providing imaging means for diagnostics and therapy of renal diseases.