Purpose: To assess the contribution of 1H-magnetic resonance spectroscopy (1H-MRS), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic susceptibility contrast-enhanced (DSCE) imaging metrics in the differentiation of glioblastomas from solitary metastasis, and particularly to clarify the controversial reports regarding the hypothesis that there should be a significant differentiation between the intratumoral and peritumoral areas. Methods: Conventional MR imaging, 1H-MRS, DWI, DTI and DSCE MRI was performed on 49 patients (35 glioblastomas multiforme, 14 metastases) using a 3.0-T MR unit. Metabolite ratios, apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) were measured in the intratumoral and peritumoral regions of the lesions. Receiver-operating characteristic analysis was used to obtain the cut-off values for the parameters presenting a statistical difference between the two tumor groups. Furthermore, we investigated the potential effect of the region of interest (ROI) size on the quantification of diffusion properties in the intratumoral region of the lesions, by applying two different ROI methods. Results: Peritumoral N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, Cho/NAA and rCBV significantly differentiated glioblastomas from intracranial metastases. ADC and FA presented no significant difference between the two tumor groups. Conclusions: 1H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases. The quantification of the diffusion properties in the intratumoral region is independent of the ROI size placed.

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

This study determines the optimal clinical scenarios for gold nanoparticle dose enhancement as a function of irradiation conditions and potential biological targets using megavoltage x-ray beams. Four hundred and eighty clinical beams were studied for different potential cellular or sub-cellular targets. Beam quality was determined based on a 6 MV linac with and without a flattening filter for various delivery conditions. Dose enhancement ratios DER = D GNP /D water were calculated for all cases using the GEANT4 Monte Carlo code and the CEPXS/ONEDANT radiation transport deterministic code. Dose enhancement using GEANT4 agreed with CEPXS/ONEDANT. DER for unflattened beams is ∼2 times larger than for flattened beams. The maximum DER values were calculated for split-IMRT fields (∼6) and for out-of-field areas of an unflattened linac (∼17). In-field DER values, at the surface of gold nanoparticles, ranged from 2.2 to 4.2 (flattened beam) and from 3 to 4.7 (unflattened beams). For a GNP cluster with thicknesses of 10 and 100 nm, the DER ranges from 14% to 287%. DER is the greatest for split-IMRT, larger depths, out-of-field areas and/or unflattened linac. Mapping of a GNP location in tumor and normal tissue is essential for efficient and safe delivery of nanoparticle-enhanced radiotherapy.

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