A functional form for a representative individual arterial input function measured from a population using high temporal resolution DCE MRI

Abstract

Purpose To measure the arterial input function (AIF), an essential component of tracer kinetic analysis, in a population of patients using an optimized dynamic contrast‐enhanced (DCE) imaging sequence and to estimate inter‐ and intrapatient variability. From these data, a representative AIF that may be used for realistic simulation studies can be extracted. Methods Thirty‐nine female patients were imaged on multiple visits before and during a course of neoadjuvant chemotherapy for breast cancer. A total of 97 T1‐weighted DCE studies were analyzed including bookend estimates of T1 and model‐fitting to each individual AIF. Area under the curve and cardiac output were estimated from each first pass peak, and these data were used to assess inter‐ and intrapatient variability of the AIF. Results Interpatient variability exceeded intrapatient variability of the AIF. There was no change in cardiac output as a function of MR visit (mean value 5.6 ± 1.1 L/min) but baseline blood T1 increased significantly following the start of chemotherapy (which was accompanied by a decrease in hematocrit). Conclusion The AIF in an individual patient can be measured reproducibly but the variability of AIFs between patients suggests that use of a population AIF will decrease the precision of tracer kinetic analysis performed in cross‐patient comparison studies. A representative AIF is presented that is typical of the population but retains the characteristics of an individually measured AIF.

Pharmacokinetic modeling of dynamic contrast‐enhanced MRI using a reference region and input function tail

“…This difference could be due to the literature‐based AIF being measured from the abdomen instead of the brain or due to variations in injection protocol. Although the preliminary results presented here are promising, it should be noted that there are many literature‐based AIFs and their tail concentrations are not exactly equal . Determining the cause for this variation requires further study.…”

“…The inflow effect can lead to a bias of roughly 40% but this can be corrected with additional measurements, or the effect can be minimized by changing the slice orientation or by optimal selection of the AIF voxel . The impact of partial volume effects is difficult to quantify because they have a non‐linear effect on the AIF shape and the severity depends on the acquired spatial resolution. Since RRIFT is viable at slower temporal resolutions, the extra scan time could be used to improve volume coverage, spatial resolution, and noise.…”

“…If a reliable AIF tail measurement is unavailable, then one alternative is to assume a literature‐based AIF tail and this was attempted on in vivo data in the current work. The rationale for assuming a literature‐based tail is that they tend to be similar between patients with most of the variation occurring in the initial passes of the bolus . We found decent agreement between RRIFT using a literature‐based AIF tail versus the ETM using a measured AIF, with some disagreement between the 2 caused by the measured AIF tail being slightly larger on average in the 8 in vivo studies.…”

“…Concentration‐time curves for the tissues of interest and reference region were simulated using the ETM, with the convolution approximated by an iterative formula, for a duration of 10 min including a 60 s baseline. The simulated curves were generated at an initial sampling rate of 0.1 s and then downsampled to temporal resolutions of 5, 10, 15, and 30 s. The AIF was defined using a literature‐based model …”

“…The location of the chosen voxels was either in the straight or sagittal sinus for different patients. The tracer concentration in blood plasma was calculated by assuming a blood hematocrit of 0.4 …”