Abstract

PurposeThis study aims to test the ability of quantitative temporal diffusion spectroscopy (qTDS) to assess cellular changes associated with radiation-induced cell death in a rat glioma model. Methods and MaterialsTumor response to a single fraction of 20 Gy of x-ray radiation was investigated in a rat glioma (9L) model. Tumor response was monitored longitudinally at postinoculation days 21, 23, and 25, using a specific implementation of qTDS with acronym IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion), as well as conventional diffusion and high-resolution anatomic imaging. IMPULSED method combines diffusion-weighted signals acquired over a range of diffusion times that are then analyzed and interpreted using a theoretical model of water diffusion in tissues, which generates parametric maps depicting cellular and subcellular structural information on a voxel-wise basis. Results from different metrics were compared statistically. ResultsA single dose of 20 Gy x-ray radiation significantly prolonged survival of 9L-bearing rats. The mean cell sizes of irradiated tumors decreased (P < .005) after radiation treatment, which we associate with cell shrinkage and the formation of small cellular bodies during apoptosis and necrosis. A combination of IMPULSED-derived parameters (mean cell size d and extracellular structural parameter βex) separated 90% of irradiated tumors from the nonirradiated cases at post inoculation day 23, whereas a combination of tumor growth and conventional apparent diffusion coefficient did not differentiate irradiated tumors from nonirradiated tumors. ConclusionsThis proof-of-concept study demonstrates the IMPULSED method to be a new method for deriving quantitative microstructural parameters in a preclinical tumor model. The method provides unique information based on the diffusion time dependency of diffusion magnetic resonance imaging, which cannot be obtained by conventional diffusion weighted imaging methods, and the results have a close correlation with primary biologic markers of treatment efficacy, such as cell death and survival.

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