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The unintended side effects of cancer treatment are increasing recognized. Among these is a syndrome of long-term neurocognitive dysfunction called cancer/chemotherapy related cognitive impairment. To date, all studies examining the cognitive impact of cancer treatment have emphasized chemotherapy. Radiation-induced bystander effects have been described in cell culture and, to a limited extent, in rodent model systems. The purpose of this study was to examine, for the first time, the impact of non-brain directed radiation therapy on the brain in order to elucidate its potential relationship with cancer/chemotherapy related cognitive impairment. To address this objective, female BALB/c mice received either a single 16 gray fraction of ionizing radiation to the right hind limb or three doses of methotrexate, once per week for three consecutive weeks. Mice were sacrificed either 3 or 30 days post-treatment and brain injury was determined via quantification of activated astrocytes and microglia. To characterize the effects of non-brain directed radiation on brain glucose metabolism, mice were evaluated by fluorodeoxygluocose positron emission tomography. A single fraction of 16 gray radiation resulted in global decreases in brain glucose metabolism, a significant increase in the number of activated astrocytes and microglia, and increased TNF-α expression, all of which lasted up to 30 days post-treatment. This inflammatory response following radiation therapy was statistically indistinguishable from the neuroinflammation observed following methotrexate administration. In conclusion, non-brain directed radiation was sufficient to cause significant brain bystander injury as reflected by multifocal hypometabolism and persistent neuroinflammation. These findings suggest that radiation induces significant brain bystander effects distant from the irradiated cells and tissues. These effects may contribute to the development of cognitive dysfunction in treated human cancer patients and warrant further study.

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The aim of this work is to generate synthetic computed tomography (sCT) images from multi-sequence magnetic resonance (MR) images using an adversarial network and to assess the feasibility of sCT-based treatment planning for brain radiotherapy. Datasets for 15 patients with glioblastoma were selected and 580 pairs of CT and MR images were used. T1-weighted, T2-weighted and fluid-attenuated inversion recovery MR sequences were combined to create a three-channel image as input data. A conditional generative adversarial network (cGAN) was trained using image patches. The image quality was evaluated using voxel-wise mean absolute errors (MAEs) of the CT number. For the dosimetric evaluation, 3D conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT) plans were generated using the original CT set and recalculated using the sCT images. The isocenter dose and dose–volume parameters were compared for 3D-CRT and VMAT plans, respectively. The equivalent path length was also compared. The mean MAEs for the whole body, soft tissue and bone region were 108.1 ± 24.0, 38.9 ± 10.7 and 366.2 ± 62.0 hounsfield unit, respectively. The dosimetric evaluation revealed no significant difference in the isocenter dose for 3D-CRT plans. The differences in the dose received by 2% of the volume (D2%), D50% and D98% relative to the prescribed dose were <1.0%. The overall equivalent path length was shorter than that for real CT by 0.6 ± 1.9 mm. A treatment planning study using generated sCT detected only small, clinically negligible differences. These findings demonstrated the feasibility of generating sCT images for MR-only radiotherapy from multi-sequence MR images using cGAN.