P01.051 Imaging based analysis of changes in grey and white matter in glioblastoma patients treated with tumor treating fields

P01.051 基于影像的肿瘤电场治疗胶质母细胞瘤患者灰质和白质变化分析

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Abstract

BACKGROUND: After a positive randomized clinical trial showing significant survival benefits, Tumor Treating Fields (TTFields) have been implemented in the management of newly diagnosed glioblastoma (GBM). Biophysical modeling of TTField application has demonstrated a heterogeneous electric field distribution within the intracranial space, reaching maximal intensities at tissue borders with different electric conductivity. However, no imaging modality is available to visualize the impact of TTField treatment within the tumor and the bordering normal brain in each individual patient. Our hypothesis is that the distribution and field intensity may be highly heterogeneous between GBM patients depending on tumor size, resection status and perifocal edema. The goal of our study is to develop a voxel based imaging analysis tool, which may allow to detect specific changes induced by TTFields in GBM patients. MATERIAL AND METHODS: Structural MR-Data of 27 patients suffering from newly diagnosed GBM treated according to the Stupp protocol combined with TTFields and 27 control patients (matched for gender, age, IDH1 mutation and MGMT promoter methylation status) treated according to the Stupp protocol without TTFields. Imaging acquisition was conducted at 1.5 T MRI-Scanners at the Department of Neuroradiology of the University Regensburg Medical Center. For both patients groups a high-resolution T1-weigthed image (3D magnetization prepared rapid gradient echo) was acquired during disease control after the concomitant phase and after the first two cycles of adjuvant chemotherapy either with or without TTField treatment. To analyze group and therapy-induced longitudinal differences of grey and white matter density, individual MRI-T1-data sets were preprocessed using the (V)oxel (b)ased (M)orphmetry and D(iffeomorphic) A(natomical) R(egistration) T(hrough) E(xponentiated) L(ie) A(lgebra) toolboxes both implemented in (S)tatistical (P)arametric (M)apping 12 running under MaTLab R2016b. Possible group differences were subsequently assessed by parametric t-test for independent samples as well as within subject’s t-tests for determination of longitudinal therapy-inducing effects. RESULTS: The study has received a positive vote from the Ethical Board of the University Regensburg Medical Center. The first patients are being recruited, the actual results will be evaluated and presented during the meeting.

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