Differentiation of pseudoprogression and real progression in glioblastoma using ADC parametric response maps

Purpose The purpose of this study was to investigate whether a voxel-wise analysis of apparent diffusion coefficient (ADC) values may differentiate between progressive disease (PD) and pseudoprogression (PsP) in patients with high-grade glioma using the parametric response map, a newly introduced po...

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Hauptverfasser: Reimer, Caroline Andrea (VerfasserIn) , Wiestler, Benedikt (VerfasserIn) , Vollmuth, Philipp (VerfasserIn) , Wick, Wolfgang (VerfasserIn) , Bendszus, Martin (VerfasserIn) , Radbruch, Alexander (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 6 April 2017
In: PLOS ONE
Year: 2017, Jahrgang: 12, Heft: 4
ISSN:1932-6203
DOI:10.1371/journal.pone.0174620
Online-Zugang:Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1371/journal.pone.0174620
Verlag, kostenfrei, Volltext: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0174620
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Verfasserangaben:Caroline Reimer, Katerina Deike, Markus Graf, Peter Reimer, Benedikt Wiestler, Ralf Omar Floca, Philipp Kickingereder, Heinz-Peter Schlemmer, Wolfgang Wick, Martin Bendszus, Alexander Radbruch

MARC

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245 1 0 |a Differentiation of pseudoprogression and real progression in glioblastoma using ADC parametric response maps  |c Caroline Reimer, Katerina Deike, Markus Graf, Peter Reimer, Benedikt Wiestler, Ralf Omar Floca, Philipp Kickingereder, Heinz-Peter Schlemmer, Wolfgang Wick, Martin Bendszus, Alexander Radbruch 
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520 |a Purpose The purpose of this study was to investigate whether a voxel-wise analysis of apparent diffusion coefficient (ADC) values may differentiate between progressive disease (PD) and pseudoprogression (PsP) in patients with high-grade glioma using the parametric response map, a newly introduced postprocessing tool. Methods Twenty-eight patients with proven PD and seven patients with PsP were identified in this retrospective feasibility study. For all patients ADC baseline and follow-up maps on four subsequent MRIs were available. ADC maps were coregistered on contrast enhanced T1-weighted follow-up images. Subsequently, enhancement in the follow-up contrast enhanced T1-weighted image was manually delineated and a reference region of interest (ROI) was drawn in the contralateral white matter. Both ROIs were transferred to the ADC images. Relative ADC (rADC) (baseline)/reference ROI values and rADC (follow up)/reference ROI values were calculated for each voxel within the ROI. The corresponding voxels of rADC (follow up) and rADC (baseline) were subtracted and the percentage of all voxels within the ROI that exceeded the threshold of 0.25 was quantified. Results rADC voxels showed a decrease of 59.2% (1st quartile (Q1) 36.7; 3rd quartile (Q3) 78.6) above 0.25 in patients with PD and 18.6% (Q1 3.04; Q3 26.5) in patients with PsP (p = 0.005). Receiver operating characteristic curve analysis showed the optimal decreasing rADC cut-off value for identifying PD of > 27.05% (area under the curve 0.844±0.065, sensitivity 0.86, specificity 0.86, p = 0.014). Conclusion This feasibility study shows that the assessment of rADC using parametric response maps might be a promising approach to contribute to the differentiation between PD and PsP. Further research in larger patient cohorts is necessary to finally determine its clinical utility. 
650 4 |a Cancer treatment 
650 4 |a Central nervous system 
650 4 |a Diffusion weighted imaging 
650 4 |a Glioblastoma multiforme 
650 4 |a Magnetic resonance imaging 
650 4 |a Mass diffusivity 
650 4 |a Progressive diseases 
650 4 |a Radiation therapy 
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