UNASSIGNED: 2009 Background: @entity1 with @entity463 ( @entity463 ) treated with @entity2903 and radiotherapy (RT) may experience early @entity74 ( @entity74 ) or pseudoprogression (PsP) due to radiation effects, both of which appear as contrast-enhancing lesions on MRI. Currently, there is no reliable way to differentiate between @entity74 and PsP, posing a common diagnostic and treatment dilemma since @entity1 with @entity74 have a poor prognosis, while PsP usually resolves without changes in therapy. METHODS: We retrospectively identified 71 @entity463 @entity1 with new or enlarging enhancing lesions on initial MRI following @entity2903 and RT. In twenty @entity1 , dynamic susceptibility (DSC) MR perfusion had been performed, including relative cerebral blood volume (rCBV), relative peak height (rPH) and peak signal recovery (PSR) of the enhancing lesions. Two independent reviewers unaware of results of DSC MR perfusion imaging assigned @entity1 to either @entity74 or PsP based on review of clinical data and follow up or results of biopsy of the enhancing lesions (if available). Two-sided Wilcoxon rank-sum tests were used to evaluate associations between DSC parameters and @entity74 or PsP status. RESULTS: The PsP group had significantly lower median rCBV compared to @entity74 (1.5 vs 2.8, p=0.009) and rPH (1.3 vs 3.0, p<0.001), with higher PSR (1.0 vs 0.8, p=0.039). Receiver operator characteristic analysis revealed an optimal rCBV threshold of <= 1.80 to detect PsP with 100% sensitivity and 75% specificity (AUC=0.938). To maximize specificity, an rCBV threshold of <= 2.40 achieved 69% sensitivity and 100% specificity to detect PsP. CONCLUSIONS: DSC MR perfusion imaging of new or enlarging enhancing lesions immediately after completion of RT and @entity2903 successfully identified @entity1 with PsP versus those with @entity74 , which has important implications for clinical treatment.

Magnetic resonance (MR) perfusion imaging to differentiate early progression from pseudoprogression following chemoradiotherapy for @entity463 ( XXXX ).

@entity1 :: ('9606', 'Species') :: ['Patients', 'patients'] @entity463 :: ('MESH:D005909', 'Disease') :: ['GBM', 'glioblastoma'] @entity74 :: ('MESH:D030342', 'Disease') :: ['PD', 'progressive disease'] @entity2903 :: ('MESH:C047246', 'Chemical') :: ['temozolomide']
@entity463 :: (MESH:D005909,Disease) :: ['GBM']
