Abstract
Purpose
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.
Procedures
F98 GB growth was seen on MRI 8–23 days post-inoculation (n = 15). RN lesions developed 6–8 months 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.
Results
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 581 s. 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).
Conclusions
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.
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Acknowledgements
This work was supported by Stichting Luka Hemelaere (O.L. Vrouwstraat 40, 8500 Kortrijk, Belgium) and Soroptimist International (S.I.B vzw, Middaglijnstraat 10, 1210 Brussel, Belgium).
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The study was approved by the Ghent University ethics committee for animal experiments (ECD 12/28).
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Bolcaen, J., Descamps, B., Acou, M. et al. In Vivo DCE-MRI for the Discrimination Between Glioblastoma and Radiation Necrosis in Rats. Mol Imaging Biol 19, 857–866 (2017). https://doi.org/10.1007/s11307-017-1071-0
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DOI: https://doi.org/10.1007/s11307-017-1071-0