Comparison of errors associated with single‐ and multi‐bolus injection protocols in low‐temporal‐resolution dynamic contrast‐enhanced tracer kinetic analysis

For clinical dynamic contrast-enhanced (DCE) MRI studies, it is often not possible to obtain reliable arterial input function (AIF) in each measurement. Thus, it is important to find a representative AIF for pharmacokinetic modeling of DCE-MRI data when individual AIF (Ind-AIF) measurements are not available. A total of 16 patients with osteosarcomas in the lower extremity (knee region) underwent multislice DCE-MRI. Reliable Ind-AIFs were obtained in five patients with a contrast injection rate of 2 cc/s and another five patients with a 1 cc/s injection rate. Average AIF (Avg-AIF) for each injection rate was constructed from the corresponding five Ind-AIFs. For each injection rate there are no statistically significant differences between pharmacokinetic parameters of the five patients derived with Ind-AIFs and Avg-AIF. There are no statistically significant changes in pharmacokinetic parameters of the 16 patients when the two AvgAIFs were applied in kinetic modeling. The results suggest that it is feasible, as well as practical, to use a limited-population- There has been increasing interest in the T 1 -weighted dynamic contrast-enhanced (DCE) MRI method for the study of many different tumor types, using the Gd (III) chelate contrast agents (1). There are generally three approaches for analyzing DCE-MRI signal time courses: 1) qualitative subjective assessment of curve shape, such as wash-out, plateau, and persistent; 2) empirical quantitation, such as maximum slope and percent signal intensity change; and 3) analytical pharmacokinetic modeling. The latter is more sophisticated, and also the more desirable. Unlike the first two approaches, analytical modeling of DCE-MRI data extracts pharmacokinetic parameters that should be independent of data acquisition details, contrast agent dose and injection rate, magnetic field strength, and vendor platform, etc. This improves DCE-MRI study reproducibility and enables meaningful comparison of results from different imaging sites where different DCE-MRI protocols are employed. The extracted pharmacokinetic parameters are usually variants of: K trans , a rate constant for contrast agent plasma/interstitium transfer, and v e , the interstitial space volume fraction (the putative contrast agent distribution volume). These parameters have been used for cancer diagnosis (2-4) and monitoring effects of antiangiogenic therapies (5,6).A characteristic aspect of pharmacokinetic modeling of DCE-MRI signal time course is the requirement for an arterial input function (AIF). The absolute accuracy of the pharmacokinetic parameters, K trans and v e , depends on the AIF accuracy (7,8). Ideally, individually measured AIF should be used for kinetic modeling of the corresponding tissue DCE-MRI data in each experiment (3,7,9). However, for patient studies that are conducted in clinical settings, it is often not possible to obtain reliable AIF measurement in each DCE-MRI examination, due to either data acquisition constraints, such as excitation volume coverage and image slice angulation, o...

Section: Discussionmentioning

confidence: 99%

Feasibility of using limited‐population‐based arterial input function for pharmacokinetic modeling of osteosarcoma dynamic contrast‐enhanced MRI data

Huang

Panicek

et al. 2008

“…2 and 3) (42). The initial part of the tissue uptake curves may also have been affected as the increase in signal is sufficiently rapid that it is possible some features of the curve may have been missed at this sampling rate.…”

Section: Study Limitationsmentioning

confidence: 99%

Tracer kinetic analysis of dynamic contrast‐enhanced MRI and CT bladder cancer data: A preliminary comparison to assess the magnitude of water exchange effects

Bains

McGrath

Naish

et al. 2010

Self Cite

The purpose of this study was to determine the impact of water exchange on tracer kinetic parameter estimates derived from T 1 -weighted dynamic contrast-enhanced (DCE)-MRI data using a direct quantitative comparison with DCE-CT. Data were acquired from 12 patients with bladder cancer who underwent DCE-CT followed by DCE-MRI within a week. A two-compartment tracer kinetic model was fitted to the CT data, and two versions of the same model with modifications to account for the fast exchange and no exchange limits of water exchange were fitted to the MR data. The two-compartment tracer kinetic model provided estimates of the fractional plasma volume (v p ), the extravascular extracellular space fraction (v e ), plasma perfusion (F p ), and the microvascular permeability surface area product. Our findings suggest that DCE-CT is an appropriate reference for DCE-MRI in bladder cancers as the only significant difference found between CT and MR parameter estimates were the no exchange limit estimates of v p (P 5 0.002). These results suggest that although water exchange between the intracellular and extravascularextracellular space has a negligible effect on DCE-MRI, vascular-extravascular-extracellular space water exchange may be more important. Magn Reson Med 64:595-603,

“…From these data sets, for which the true K trans values were known, K trans values were predicted for the simulated variations in contrast agent injection. The other kinetic parameters were kept constant at v e ϭ 0.3 and v p ϭ 0.08 within their physiologic range (22,28). The duration of the acquisition was kept constant at 15 min for all simulations.…”

Section: Simulationsmentioning

confidence: 99%

System identification theory in pharmacokinetic modeling of dynamic contrast‐enhanced MRI: Influence of contrast injection

Aerts

Riel²,

Backes

2008

Optimization of experimental settings of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), like the contrast administration protocol, is of great importance for reliable quantification of the microcirculatory properties, such as the volume transfer-constant K trans . Using system identification theory and computer simulations, the confounding effects of volume, rate and multiplicity of a contrast injection on the reliability of K trans estimation was assessed. A new tracer-distribution model (TDM), based on in vivo data from rectal cancer patients, served to describe the relationship between the contrast agent injection and the blood time-course. A pharmacokinetic model (PKM) was used to describe the relation between the blood and tumor tissue time-courses. By means of TDM and PKM in series, the tissue-transfer function of the PKM was analyzed. As both the TDM and PKM represented low-frequency-pass filters, the energy-density at low frequencies of the blood and tissue time-courses was larger than at high frequencies. The simulations, based on measurements in humans, predict that the K trans is most reliable with a high injection volume The development of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has led to the noninvasive characterization of tumor tissue (1,2). The volume transfer constant K trans , which describes the leakage rate of contrast agents into the tumor tissue, is a pharmacokinetic parameter that provides information on the physiological properties of the tumor, including the microvascular permeability and surface area, the relative blood volume, and the relative volume of the interstitial space (3-8). DCE-MRI has been recognized as a valuable tool for the evaluation of novel antiangiogenesis therapies (9 -12). Clinically, it is of importance to have a reliable and accurate quantitatively assessment of the progression or regression of tumor angiogenesis, as it may affect continuation of or changes to the treatment plan (13-15). The quality of the assessment is reflected in the accuracy of the determined pharmacokinetic parameters quantifying the wash-in and wash-out of the contrast agent. This accuracy is to a large extent determined by the experimental conditions (16). Unfortunately, where efforts have been directed to the standardization of the pharmacokinetic modeling (17), little is known on the most optimal experimental conditions. Previous investigations have focused on influences of sampling time, signal-to-noise ratio (SNR), and experiment duration (18 -22). In the present study it is hypothesized that the accuracy of the estimated pharmacokinetic parameters strongly depends on the dynamic shape of the arterial input function (AIF), which can be controlled by the contrast administration protocol.System identification theory is used to relate the reliability of the estimated K trans to the dynamics of the contrast agent injection and to find the optimal protocol for contrast agent administration. This theory states that the number of parameters involved in a ...