Breath‐hold perfusion and permeability mapping of hepatic malignancies using magnetic resonance imaging and a first‐pass leakage profile model

Abstract

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.

An improved coverage and spatial resolution—using dual injection dynamic contrast‐enhanced (ICE‐DICE) MRI: A novel dynamic contrast‐enhanced technique for cerebral tumors

“…It is important to note that the values of DCE-MRIbased parameters seen in cerebral lesions calculated using the modified Tofts model, particularly values of K trans (26)(27)(28)(29), tend to be lower than those reported in tissues of other parts of the body, such as breast and myocardium (30)(31)(32)(33)(34)(35)(36). These low values result in a reduction in covariance errors in the fitting procedure (4,37) and consequently, supports the use of a temporal sampling interval longer than 4-5 s in brain lesions.…”

Molecular Imaging of Antiangiogenic Agents

“…Relative changes in semiquantitative parameters, such as the maximum gradient of the signalintensity-time curve, the maximum increase in signal intensity normalized to baseline signal intensity (enhancement), and the area under the initial part of the curve, can be examined and are indirectly related to changes in the physiologic end points of interest: tissue perfusion, vascular permeability, and vessel surface area [27,30,[35][36][37]. A couple of reproducibility studies of this technique in humans have been performed, in glioma and in liver tumors, which defined the limits of change in these DCE-MRI parameters that might occur spontaneously between two examinations performed 5 days apart [38][39][40]. A number of significant issues were revealed during the course of that work, and these issues are reviewed here.…”

“…The reproducibility of these studies in the abdomen is lower than those of studies in the brain. When liver metastases were studied over an 8-hour period using a first-pass method to measure K trans , the coefficient of variation was 11% and the percentage change required to prove drug activity in that setting was 15% [40]. Currently, techniques are under development to measure vascular parameters through DCE-MRI in the thorax, the major hurdle of which is the movement associated with breathing and the heart beat.…”

Inter-Operator Variability in Perfusion Assessment of Tumors in MRI Using Automated AIF Detection

“…The change over time in signal intensity in a voxel or region of interest in this time series can then be related to tracer concentration. By making use of a two-compartment model, with one compartment representing blood plasma and the other extra-vascular extra-cellular space (EES), the observed enhancement curves in tissue and plasma can be used to estimate various physiological parameters [3,4,5,6].…”