Abstract

Glioblastoma (GBM) is the most common aggressive primary brain tumor in adults, with a short survival time even after aggressive therapy. Non-invasive surrogate biomarkers of therapy response may be relevant for improving patient survival. Previous work produced such biomarkers in preclinical GBM using semi-supervised source extraction and single-slice Magnetic Resonance Spectroscopic Imaging (MRSI). Nevertheless, GBMs are heterogeneous and single-slice studies could prevent obtaining relevant information. The purpose of this work was to evaluate whether a multi-slice MRSI approach, acquiring consecutive grids across the tumor, is feasible for preclinical models and may produce additional insight into therapy response. Nosological images were analyzed pixel-by-pixel and a relative responding volume, the Tumor Responding Index (TRI), was defined to quantify response. Heterogeneous response levels were observed and treated animals were ascribed to three arbitrary predefined groups: high response (HR, n = 2), TRI = 68.2 ± 2.8%, intermediate response (IR, n = 6), TRI = 41.1 ± 4.2% and low response (LR, n = 2), TRI = 13.4 ± 14.3%, producing therapy response categorization which had not been fully registered in single-slice studies. Results agreed with the multi-slice approach being feasible and producing an inverse correlation between TRI and Ki67 immunostaining. Additionally, ca. 7-day oscillations of TRI were observed, suggesting that host immune system activation in response to treatment could contribute to the responding patterns detected.

Highlights

  • Glioblastoma (GBM) is the most common and aggressive glial primary tumor with a survival average of 14–15 months, even after application of standard treatment [1]

  • No high response (HR) cases were found in this first part of the experiment

  • Histopathology analysis was conducted for all acquired grids in chosen animals in order to confirm the results previously described in [13], in which an inverse and significant correlation between the responding pattern and the proliferation marker Ki67 was found, with green, responding zones presenting a significantly lower Ki67% value

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Summary

Introduction

Glioblastoma (GBM) is the most common and aggressive glial primary tumor with a survival average of 14–15 months, even after application of standard treatment [1]. Metabolites 2017, 7, 20 plus radiotherapy is the regular therapeutic choice for such treatment [2] and produces the best survival rates. Magnetic resonance techniques are the most suitable approaches to perform diagnosis and therapy response follow-up in brain tumors as GBM. These techniques could provide anatomical information (MRI, magnetic resonance imaging) or information of the metabolomic profile (MRS, magnetic resonance spectroscopy). Magnetic resonance spectroscopic imaging could provide both, metabolomic information superimposed to anatomical information. The difference between MRS and MRSI is that MRS consists in acquiring single spectrum from a certain volume, whereas in MRSI multiple signals from a grid of voxels are acquired, allowing to gather metabolomic information from different regions of the studied tissue [3]

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