Renal statistical map for positron emission tomography with [O-15] water

Image statistics are frequently used for functional and molecular imaging research in which images from a patient group with a specific diagnosis are compared with images from a healthy control group who have been matched for demographic variables. The success of image statistics for brain imaging has encouraged us to develop a method for obtaining volumetrically normalized kidney to perform image statistics so that we can locally visualize the statistical significant difference comparing voxel by voxel between certain groups in terms kidney blood flow kinetic parameters. For the development of this evolutionary process, we first volumetrically normalized all subjects, which include healthy control (HC) and chronic renal failure (CRF) patients, ¹⁵O water PET image with respect to one HC subject's MRI image using affine transformation. Then ¹⁵O kinetic parametric images of normalized kidneys were obtained through the basis function method. Finally, the statistical map of these parametric images was produced using the threshold-free cluster enhancement based permutation method. Kinetic parameters of kidney namely, uptake rate constant (K₁), clearance rate constant (k₂) and blood volume (V_a), were found to be notably lower in CRF than those of in HC and k₂ parameter was found to be more stable compared to K₁ and V_a. The statistical map of these parametric images allowed us to visualize local significant differences statistically (P<0.05) between HC and CRF groups. Though PET and MRI techniques have enormous potentiality for functional and molecular imaging of kidney, these are, at best, in experimental level. It is speculated that statistical mapping of kidney could play a significant role in the successful implementation of functional and molecular kidney imaging. However, more research involving a larger sample size and improved normalization technique will be needed for the robustness of the process.