Blood oxygen level-dependent (BOLD) MRI data of kidney, while indicative of tissue oxygenation level (Po2), is in fact influenced by multiple confounding factors, such as R2, perfusion, oxygen permeability, and hematocrit. We aim to explore the feasibility of extracting tissue Po2 from renal BOLD data. A method of two steps was proposed: first, a Monte Carlo simulation to estimate blood oxygen saturation (SHb) from BOLD signals, and second, an oxygen transit model to convert SHb to tissue Po2. The proposed method was calibrated and validated with 20 pigs (12 before and after furosemide injection) in which BOLD-derived tissue Po2 was compared with microprobe-measured values. The method was then applied to nine healthy human subjects (age: 25.7 ± 3.0 yr) in whom BOLD was performed before and after furosemide. For the 12 pigs before furosemide injection, the proposed model estimated renal tissue Po2 with errors of 2.3 ± 5.2 mmHg (5.8 ± 13.4%) in cortex and -0.1 ± 4.5 mmHg (1.7 ± 18.1%) in medulla, compared with microprobe measurements. After injection of furosemide, the estimation errors were 6.9 ± 3.9 mmHg (14.2 ± 8.4%) for cortex and 2.6 ± 4.0 mmHg (7.7 ± 11.5%) for medulla. In the human subjects, BOLD-derived medullary Po2 increased from 16.0 ± 4.9 mmHg (SHb: 31 ± 11%) at baseline to 26.2 ± 3.1 mmHg (SHb: 53 ± 6%) at 5 min after furosemide injection, while cortical Po2 did not change significantly at ∼58 mmHg (SHb: 92 ± 1%). Our proposed method, validated with a porcine model, appears promising for estimating tissue Po2 from renal BOLD MRI data in human subjects.
Keywords: blood oxygen level-dependent MRI; kidney; magnetic resonance imaging; oxygen transit modeling; tissue oxygenation level.