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We have applied a novel pharmacokinetic model of the distribution of contrast media to dynamic contrast-enhanced MRI data from patients with hepatic neoplasms. The model uses data collected during the passage of a bolus of contrast medium and allows breath-hold image acquisition. The aims of the study were to investigate the feasibility of permeability mapping using the first pass technique and breath-hold acquisitions, and to examine the reproducibility of the technique and the effect of the liver's dual vascular supply on the assumptions of the model. Imaging was performed in 14 patients with hepatic neoplasms. Dynamic data clearly demonstrated differences in the timing and shape of the contrast medium concentration-time course curve in the systemic arterial and portal venous systems. Mapping of the arrival time (T 0 ) of contrast medium allowed identification of tissue supplied by the hepatic arteries and portal vein. Hepatic tumours all showed typical hepatic arterial enhancement. Repeated measurements of endothelial permeability surface area product (k fp ) and relative blood volume (rBV), performed in five patients, showed excellent reproducibility with variance ratios (V r ) of 0.134 and 0.113, respectively. Measurement of enhancing tumour volume was also highly reproducible (V r = 0.096) and this was further improved by the use of T 0 maps to identify pixels supplied by the hepatic artery (V r = 0.026). Estimates of k fp and rBV in normal hepatic tissue supplied by the portal vein were highly inaccurate and these pixels were identified by use of the T 0 parameter and excluded from the analysis. In conclusion, dynamic MRI contrast enhancement combined with a pharmacokinetic model of the distribution of contrast media in the first pass allows us to produce highly reproducible parametric maps of k fp and rBV from hepatic tumours that are supplied by the hepatic arterial system using breath-hold acquisitions.

The purpose of this study was to examine the benefits of routine generation of a parametric image of scaled curve fitting errors in the analysis of dynamic susceptibility contrast enhanced MR perfusion imaging. We describe the scaled fitting error (SFE), which reflects the magnitude of potential errors in the estimation of perfusion parameters from dynamic susceptibility contrast enhanced studies. The SFE is the root-mean-square error between the observed values in the time course of change of effective transverse relaxation rate (delta R2* (t)) in tissue and the theoretical values derived by gamma variate curve fitting, scaled with a simple function related to the area under the fitted gamma variate curve. The SFE was tested using Monte Carlo simulation and by observations in normal volunteers and patients. This demonstrated that the SFE was linearly related to uncertainties in calculation of the values of relative cerebral blood volume (rCBV) and relative mean transit time (rMTT). High spatial resolution SFE maps were obtained in all volunteers and patients. In normal brain, SFE was consistently higher in white matter than in grey matter. In 54/85 patients with neurodegenerative or vascular brain disease, SFE maps showed focal areas with high values owing to poor signal to noise ratio in delta R2*(t). Increased SFE was also found in 11/54 brain tumours owing to loss of conformance of delta R2*(t) to the gamma variate function. SFE mapping is simple to implement and the computational overhead is negligible. It is concluded that parametric maps of SFE allow visual and quantitative comparison of fitting errors with the theoretical gamma variate model between anatomical regions and provide a quality control device to rapidly assess the reliability of the associated rCBV and rMTT estimations.

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