In Vivo DCE-MRI for the Discrimination Between Glioblastoma and Radiation Necrosis in Rats

Abstract

In this study, the potential of semiquantitative and quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) was investigated to differentiate glioblastoma (GB) from radiation necrosis (RN) in rats. F98 GB growth was seen on MRI 8-23days post-inoculation (n=15). RN lesions developed 6-8months post-irradiation (n=10). DCE-MRI was acquired using a fast low-angle shot (FLASH) sequence. Regions of interest (ROIs) encompassed peripheral contrast enhancement in GB (n=15) and RN (n=10) as well as central necrosis within these lesions (GB (n=4), RN (n=3)). Dynamic contrast-enhanced time series, obtained from the DCE-MRI data, were fitted to determine four function variables (amplitude A, offset from zero C, wash-in rate k, and wash-out rate D) as well as maximal intensity (ImaxF) and time to peak (TTPF). Secondly, maps of semiquantitative and quantitative parameters (extended Tofts model) were created using Olea Sphere (O). Semiquantitative DCE-MRI parameters included wash-inO, wash-outO, area under the curve (AUCO), maximal intensity (ImaxO), and time to peak (TTPO). Quantitative parameters included the rate constant plasma to extravascular-extracellular space (EES) (K trans), the rate constant EES to plasma (K ep), plasma volume (V p), and EES volume (V e). All (semi)quantitative parameters were compared between GB and RN using the Mann-Whitney U test. ROC analysis was performed. Wash-in rate (k) and wash-out rate (D) were significantly higher in GB compared to RN using curve fitting (p=0.016 and p=0.014). TTPF and TTPO were significantly lower in GB compared to RN (p=0.001 and p=0.005, respectively). The highest sensitivity (87%) and specificity (80%) were obtained for TTPF by applying a threshold of 581s. K trans, K ep, and V e were not significantly different between GB and RN. A trend towards higher V p values was found in GB compared to RN, indicating angiogenesis in GB (p=0.075). Based on our results, in a rat model of GB and RN, wash-in rate, wash-out rate, and the time to peak extracted from DCE-MRI time series data may be useful to discriminate GB from RN.