BACKGROUND: Noninvasively differentiating therapy-induced pseudoprogression from recurrent disease in patients with glioblastoma is prospectively difficult due to the current lack of a biologically specific imaging metric. Ferumoxytol iron oxide nanoparticle MRI contrast characterizes innate immunity mediated neuroinflammation; therefore, we hypothesized that combined ferumoxytol and gadolinium enhanced MRI could serve as a biomarker of glioblastoma pseudoprogression. METHODS: In this institutional review board-approved, retrospective study, we analyzed ferumoxytol and gadolinium contrast enhanced T1-weighted 3T MRI in 45 patients with glioblastoma over multiple clinical timepoints. Isocitrate dehydrogenase 1 (IDH-1) mutational status was characterized by exome sequencing. Sum of products diameter measurements were calculated according to Response Assessment in Neuro-Oncology criteria from both gadolinium and ferumoxytol enhanced sequences. Enhancement mismatch was calculated as the natural log of the ferumoxytol to gadolinium sum of products diameter ratio. Analysis of variance and Student's t-test assessed differences in mismatch ratios. P-value <0.05 indicated statistical significance. RESULTS: With the development of pseudoprogression we observed a significantly elevated mismatch ratio compared with disease recurrence (P < 0.01) within IDH-1 wild type patients. Patients with IDH-1 mutation demonstrated significantly reduced mismatch ratio with the development of pseudoprogression compared with disease recurrence (P < 0.01). Receiver operator curve analysis demonstrated 100% sensitivity and specificity for the use of mismatch ratios as a diagnostic biomarker of pseudoprogression. CONCLUSION: Our study suggests that ferumoxytol to gadolinium contrast mismatch ratios are an MRI biomarker for the diagnosis of pseudoprogression in patients with glioblastoma. This may be due to the unique characterization of therapy-induced neuroinflammation. Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2018.
BACKGROUND: Noninvasively differentiating therapy-induced pseudoprogression from recurrent disease in patients with glioblastoma is prospectively difficult due to the current lack of a biologically specific imaging metric. Ferumoxytoliron oxide nanoparticle MRI contrast characterizes innate immunity mediated neuroinflammation; therefore, we hypothesized that combined ferumoxytol and gadolinium enhanced MRI could serve as a biomarker of glioblastoma pseudoprogression. METHODS: In this institutional review board-approved, retrospective study, we analyzed ferumoxytol and gadolinium contrast enhanced T1-weighted 3T MRI in 45 patients with glioblastoma over multiple clinical timepoints. Isocitrate dehydrogenase 1 (IDH-1) mutational status was characterized by exome sequencing. Sum of products diameter measurements were calculated according to Response Assessment in Neuro-Oncology criteria from both gadolinium and ferumoxytol enhanced sequences. Enhancement mismatch was calculated as the natural log of the ferumoxytol to gadolinium sum of products diameter ratio. Analysis of variance and Student's t-test assessed differences in mismatch ratios. P-value <0.05 indicated statistical significance. RESULTS: With the development of pseudoprogression we observed a significantly elevated mismatch ratio compared with disease recurrence (P < 0.01) within IDH-1 wild type patients. Patients with IDH-1 mutation demonstrated significantly reduced mismatch ratio with the development of pseudoprogression compared with disease recurrence (P < 0.01). Receiver operator curve analysis demonstrated 100% sensitivity and specificity for the use of mismatch ratios as a diagnostic biomarker of pseudoprogression. CONCLUSION: Our study suggests that ferumoxytol to gadolinium contrast mismatch ratios are an MRI biomarker for the diagnosis of pseudoprogression in patients with glioblastoma. This may be due to the unique characterization of therapy-induced neuroinflammation. Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2018.
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