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X-ray computed tomography (CT) has been traditionally used for morphologic analysis and in the recent past has been used for physiology imaging. This paper seeks to demonstrate functional CT as an effective tool for monitoring changes in tissue physiology associated with disease processes and cellular and molecular level therapeutic processes. We investigated the effect of noise and sampling time on the uncertainty of tissue physiologic parameters. A whole body compartmental model of mouse was formulated to simulate tissue time density curves and study the deviation of tissue physiologic parameters from their true values. These results were then used to determine the appropriate scanning protocols for the experimental studies. Dynamic contrast enhanced CT (DCE-CT) was performed in mice following the injection of hydrophilic iodinated contrast agent (CA) at three different injection rates, namely 0.5 ml/min, 1 ml/min, and 2.0 ml/min. These experiments probed the Nyquist sampling limit for reproducibility of tissue physiologic parameters. Separate experiments were performed with three mice at four different X-ray tube currents corresponding to different image noise values. A two-compartment model (2CM) model was formulated to describe the contrast kinematics in the kidney cortex. Three different 2CMs were implemented namely the 4-parameter (4P), 5-parameter (5P), and the 6-parameter (6P) model. The tissue kinematics is fitted to the models by using the Levenberg-Marquardt algorithm implemented in IDL (RSI Inc.) programming language to minimize the weighted sum of squares. The relevant tissue physiologic parameters extracted from the models are the renal blood flow (RBF), glomerular filtration rate (GFR), fractional plasma volume, fractional tubular volumes and urine formation rates. The experimental results indicate that the deviation of the tissue physiologic parameters is within the limits required for tracking disease physiology in vivo and thus small animal functi- - onal X-ray CT would be able to determine changes in tissue physiology in vivo.