Quantitative transport mapping (QTM) of the kidney with an approximate microvascular network.

ABSTRACT

PURPOSE: Proof-of-concept study of mapping renal blood flow vector field according to the inverse solution to a mass transport model of time resolved tracer-labeled MRI data. THEORY AND METHODS: To determine tissue perfusion according to the underlying physics of spatiotemporal tracer concentration variation, the mass transport equation is integrated over a voxel with an approximate microvascular network for fitting time-resolved tracer imaging data. The inverse solution to the voxelized transport equation provides the blood flow vector field, which is referred to as quantitative transport mapping (QTM). A numerical microvascular network modeling the kidney with computational fluid dynamics reference was used to verify the accuracy of QTM and the current Kety's method that uses a global arterial input function. Multiple post-label delay arterial spin labeling (ASL) of the kidney on seven subjects was used to assess QTM in vivo feasibility. RESULTS: Against the ground truth in the numerical model, the error in flow estimated by QTM (18.6%) was smaller than that in Kety's method (45.7%, 2.5-fold reduction). The in vivo kidney perfusion quantification by QTM (cortex 443 ± 58 mL/100 g/min and medulla 190 ± 90 mL/100 g/min) was in the range of that by Kety's method (482 ± 51 mL/100 g/min in the cortex and 242 ± 73 mL/100 g/min in the medulla), and QTM provided better flow homogeneity in the cortex region. CONCLUSIONS: QTM flow velocity mapping is feasible from multi-delay ASL MRI data based on inverting the transport equation. In a numerical simulation, QTM with deconvolution in space and time provided more accurate perfusion quantification than Kety's method with deconvolution in time only.