Individual Arterial Input Function Research Articles

Measuring perfusion and permeability in renal cell carcinoma with dynamic contrast‐enhanced MRI: A pilot study

To retrospectively assess an improved quantitative methodology with separate assessment of perfusion and permeability for characterization of primary renal cell carcinoma (RCC) and monitoring antiangiogenic treatment. Fifteen RCC patients before surgery, 6 RCC patients before and after neoadjuvant antiangiogenic therapy, and 15 patients without renal disease underwent dynamic contrast-enhanced (DCE)-MRI of the kidney with integrated retrospective respiratory triggering and an individual arterial input function. Tracer kinetic analysis was performed with a two-compartment-filtration-model for the kidney data and a two-compartment-exchange-model for the tumor data, providing four independent parameters: the perfusion-parameters plasma flow (F(P)) and plasma volume (V(P)), and the permeability-parameters extraction flow (F(E)) and extravascular-extracellular volume (V(E)). In tumors F(P) and F(E) were significantly lower than in normal kidneys. Tracer kinetic analysis displayed hemodynamic alteration caused by vessel infiltration or necrosis. Papillary RCC could be differentiated from clear-cell variants by a distinct perfusion pattern. In antiangiogenically treated RCC V(E) was not significantly decreased, while the perfusion parameters V(P) and F(P) were significantly diminished. DCE-MRI with integrated motion compensation enables evaluation of primary RCC and detects distinct perfusion patterns. Quantification with a two-compartment-exchange-model produces a separate perfusion- and permeability characterization and may become a diagnostic tool to monitor antiangiogenic treatment.

Comparison between Population Average and Experimentally Measured Arterial Input Function in Predicting Biopsy Results in Prostate Cancer

To test whether individually measured arterial input function (AIF) provides more accurate prostate cancer diagnosis then population average AIF when dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data are acquired with limited temporal resolution. Twenty-six patients with a high clinical suspicion for prostate cancer and no prior treatment underwent DCE MRI examination at 3.0 T before biopsy. DCE MRI data were fitted to a pharmacokinetic model using three forms of AIF: an individually measured, a local population average, and a literature double exponential population average. Receiver operating characteristic (ROC) analysis was used to correlate MRI with the biopsy results. Goodness of fit (chi(2)) for the three AIFs was compared using nonparametric Mann-Whitney test. Average volume transfer constant (K(trans)) values were significantly higher in tumor than in normal peripheral zone for all three AIFs. The individually measured and the local population average AIFs had the highest sensitivity (76%), whereas the double exponential AIF had the highest specificity (82%). The areas under the ROC curves were not significantly different between any of the AIFs (0.81, 0.76, and 0.81 for the individually measured, local population average, and double exponential AIFs, respectively). chi(2) was not significantly different for the three AIFs; however, it was significantly higher in enhancing than in nonenhancing regions for all three AIFs. These results suggest that, when DCE MRI data are acquired with limited temporal resolution, experimentally measured individual AIF is not significantly better than population average AIF in predicting the biopsy results in prostate cancer.

Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced–MRI analysis

Bone metastases of 16 prostate cancer patients were scanned twice 1 week apart by dynamic contrast enhanced (DCE)-MRI at 2-s resolution using a two-dimensional gradient-echo pulse sequence. With a multiple reference tissue method (MRTM), the local tissue arterial input function (AIF) was estimated using the contrast agent enhancement data from tumor subregions and muscle. The 32 individual AIFs estimated by the MRTM, which had considerable intra-patient and inter-patient variability, were similar to directly measured AIFs in the literature and using the MRTM AIFs in a pharmacokinetic model to derive estimated individual cardiac outputs provided physiologically reasonable results. The MRTM individual AIFs gave better fits with smaller sum of squared errors and equally reproducible estimate of kinetic parameters compared with a previous reported population AIF measured from remote arteries. The individual MRTM AIFs were also used to obtain a mean local tissue AIF for the unique population of this study, which further improved the reproducibility of the estimated kinetic parameters. The MRTM can be applied to DCE-MRI studies of bone metastases from prostate cancers to provide an AIF from which reproducible quantitative DCE-MRI parameters can be derived, thus help standardize DCE-MRI studies in cancer patients.

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

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 Avg-AIFs were applied in kinetic modeling. The results suggest that it is feasible, as well as practical, to use a limited-population-based Avg-AIF for pharmacokinetic modeling of osteosarcoma DCE-MRI data. Further validation with a larger population and multiple regions is desirable.

Simplified quantification of small animal [18F]FDG PET studies using a standard arterial input function

Arterial input function (AIF) measurement for quantification of small animal PET studies is technically challenging and limited by the small blood volume of small laboratory animals. The present study investigated the use of a standard arterial input function (SAIF) to simplify the experimental procedure. Twelve [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET studies accompanied by serial arterial blood sampling were acquired in seven male Sprague-Dawley rats under isoflurane anaesthesia without (every rat) and with additional (five rats) vibrissae stimulation. A leave-one-out procedure was employed to validate the use of a SAIF with individual scaling by one (1S) or two (2S) arterial blood samples. Automatic slow bolus infusion of [(18)F]FDG resulted in highly similar AIF in all rats. The average differences of the area under the curve of the measured AIF and the individually scaled SAIF were 0.11+/-4.26% and 0.04+/-2.61% for the 1S (6-min sample) and the 2S (4-min/43-min samples) approach, respectively. The average differences between the cerebral metabolic rates of glucose (CMR(glc)) calculated using the measured AIF and the scaled SAIF were 1.31+/-5.45% and 1.30+/-3.84% for the 1S and the 2S approach, respectively. The use of a SAIF scaled by one or (preferably) two arterial blood samples can serve as a valid substitute for individual AIF measurements to quantify [(18)F]FDG PET studies in rats. The SAIF approach minimises the loss of blood and should be ideally suited for longitudinal quantitative small animal [(18)F]FDG PET studies.

Deuterium NMR tissue perfusion measurements using the tracer uptake approach: I. Optimization of methods.

This paper considers potential problems encountered when using the Kety approach to measure perfusion in small laboratory animals with nuclear magnetic resonance (NMR) tracer uptake methods: a) the need to measure the arterial input function (AIF) in each animal; b) sensitivity to perfusion heterogeneity; c) sensitivity to low signal-to-noise ratio (SNR); and d) influence of changes in the AIF. A method to estimate the AIF in rats is presented that derives an AIF from the time course of a tracer passing through a carotid chamber. The results of computer simulations indicate that a common AIF obtained in one set of animals can be used for perfusion estimations in another set of animals if the tracer is delivered as a dose and that optimal data analysis (fitting data vs. integration approach) is dictated by SNR and perfusion heterogeneity. Experimental strategies are suggested to minimize the effects of changes in the individual AIF that could distort perfusion estimates.