Dynamic contrast-enhanced imaging allows assessing functional information in addition to morphology using various modalities. Several applications have been established in clinical practice; however, there is no standard with respect to injection protocols or postprocessing algorithms. The purpose of this study was to develop a phantom for generating reproducible contrast-enhancement curves and providing a standard for comparison of different protocols and modalities in dynamic imaging.
Our experimental setup consists of a peristaltic pump to generate a water flow through the phantom and a contrast injection pump. The phantom holds a sequence of layers allowing for assessment of perfusion, signal-to-noise ratio, and spatiotemporal resolution; the latter is the spatial resolution of structures with temporally changing contrast. Reproducibility was evaluated by the functional parameters time to peak, mean transit time, and peak enhancement by 24 scans over 4 weeks on a clinical computed tomography scanner. In addition, the area under the curve was evaluated for different injection durations at constant injection volume. Spatiotemporal resolution was assessed by spatial profiles on perfused bore patterns and compared for standard reconstructions, smooth reconstructions, and highly constrained backprojection for local reconstruction (HYPR LR).
The phantom showed good reproducibility in repeated measurements, with maximal deviations of 4% for time to peak, 9% for mean transit time, and 8% for peak enhancement. Area under the curve was constant within 3.5% for different injection protocols. For the static case, HYPR LR maintained spatial resolution. For dynamic objects, however, HYPR LR reduced spatial resolution dependent on temporal dynamics by up to 19% for highest dynamics, which was still superior to smooth reconstructions (27%).
The proposed phantom showed good reproducibility and therefore allows for comparing injection protocols or modalities in dynamic imaging. Assessment of spatiotemporal resolution under measurement conditions provides means for assessing postprocessing methods and reconstruction techniques in dynamic imaging.
From the Institute of Medical Physics, University of Erlangen-Nuremberg, Erlangen, Germany.
Received November 8, 2011; and accepted for publication, after revision February 15, 2012.
Conflicts of interest and sources of funding: This work was supported by the German Science Foundation “Research unit 661: Multimodal Imaging in Preclinical Investigation” (DFG: KA 1254/11-1).
The authors report no conflicts of interest.
Reprints: Robert Brauweiler, Institute of Medical Physics (IMP), University of Erlangen-Nürnberg, Henkestraße 91, 91052 Erlangen, Germany. E-mail: Robert.Brauweiler@imp.uni-erlangen.de.