We evaluated a volume-weighted voxel-based multiparametric (MP) clustering method as an imaging biomarker for differentiating recurrent glioblastoma from delayed radiation necrosis, comparing to the single imaging parameters of DWI, DSC and DCE perfusion MR. In an area under the receiver operating characteristic curve analysis, volume-weighted voxel-based MP clustering demonstrated better diagnostic accuracy for discriminating these two conditions than single imaging parameters. When performed with use of an optimal cutoff, volume-weighted voxel-based MP clustering improved the overall sensitivity. Therefore, quantitative analysis using volume-weighted voxel-based MP clustering is superior to single imaging parameter measurements for differentiating recurrent glioblastoma from delayed radiation necrosis.
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