Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using ...

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using ...

9 Pages · 2015 · 2.77 MB · English

Patients with Glioblastomas Using Diffusion Tensor Imaging .. We acknowledge Tianyu Yin for assistance in data analysis; Dr. Ruyun Jin, Medical 

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using ... free download

ORIGINAL RESEARCH ADULT BRAIN Differentiating Tumor Progression from Pseudoprogression inPatients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI S Wang, M MartinezLage, Y Sakai, S Chawla, SG Kim, M AlonsoBasanta, RA Lustig, S Brem, S Mohan, RL Wolf, A Desai, and H Poptani ABSTRACT BACKGROUND AND PURPOSE:Early assessment of treatment response is critical in patients with glioblastomas A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression MATERIALS AND METHODS: Fortyone patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied All patients underwent surgery after MR imaging and were histologically classified as having true progression (75% tumor), mixed response (25%–75% tumor), or pseudoprogression ( 25% tumor) Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression RESULTS: Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression ( P  05) There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups The best model to distinguish true progression from non–true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0905 This model also differentiated true progression from mixed response with an area under the curve of 0901 A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0807 CONCLUSIONS: DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas ABBREVIATIONS: AUC area under the curve; CL linear anisotropy coefficient; CP planar anisotropy coefficient; CS spheric anisotropy coefficient; FA  fractional anisotropy; LRM logistic regression model; max maximum; MD mean diffusivity; PsP pseudoprogression; rCBV relative cerebral blood volume; TP true progression T he current standard of care for newly diagnosed glioblastomas is surgical resection and concurrent temozolomide radiation therapy, followed by at least 6 months of adjuvant temozolomide Treatment outcome is generally monitored by using standard clinical MR imaging based on accepted guidelines such as the updated Response Assessment in NeuroOncology criteria 1,2 However, the appearance of enhancing lesions on MR imaging within the first 6 months after completion of chemoradiation therapy poses a challenge because it can reflect true progression (TP) or treatmentrelated changes known as pseudoprogression (PsP) PsP occurs in approximately a third of all patients with glioblas toma, 3in which lesions often decrease in size or stabilize without further treatment, resulting in a longer survival Accurate identifica Received March 10, 2015; accepted after revision June 2 From the Departments of Radiology (SW, YS, SM, RLW, HP), Division of Neu roradiology, Pathology and Laboratory Medicine (MML), Radiation Oncology (MAB, RAL,), Neurosurgery (SB), and HematologyOncology (AD), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Ra diology (SC, SGK), Center for Biomedical Imaging, New York University School of Medicine, New York, New York Current affiliation for HP: Department of Cellular and Molecular Physiology, Uni versity of Liverpool, UK This work was supported by National Institutes of Health grant 1R21CA170284 Please address correspondence to Harish Poptani, PhD, Department of Cellular and Molecular Physiology, University of Liverpool, 2/012 Nuffield Wing, Sherrington Building, Crown St, Liverpool L69 3BX, UK; email: [email protected] Indicates open access to nonsubscribers at wwwajnrorg Indicates article with supplemental online photo http://dxdoiorg/103174/ajnrA4474 AJNR Am J Neuroradiol ●:●●2016 wwwajnrorg 1 Published October 8, 2015 as 103174/ajnrA4474 Copyright 2015 by American Society of Neuroradiology tion of PsP and TP is

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