Purpose To determine whether early assessment of cerebral white matter degradation can predict late delayed cognitive decline after radiation therapy (RT). Methods and Materials Ten patients undergoing conformal fractionated brain RT participated in a prospective diffusion tensor magnetic resonance imaging (MRI) study. MRI was acquired prior to RT, 3 weeks and 6 weeks during RT, and 10, 30, and 78 weeks after starting RT. Diffusivity variables in the parahippocampal cingulum bundle and temporal lobe white matter were computed. Quality of life (QOL) survey and neurocognitive function tests were administered pre-RT and at post-RT MRI follow-ups. Results In both structures, longitudinal diffusivity (λ||) decreased and perpendicular diffusivity (λ⊥) increased following RT, with early changes correlating to later changes (p < 0.05). Radiation dose correlated with increase in cingulum λ⊥ at 3 weeks, and patients with >50% of cingula volume receiving >12 Gy had a higher increase in λ⊥ at 3 weeks and 6 weeks (p < 0.05). Post-RT changes in verbal recall scores were linearly correlated with late changes in cingulum λ|| (30 weeks, p < 0.02). By receiver operating characteristic curves, early cingulum λ|| changes predicted post-RT changes in verbal recall scores (3 weeks and 6 weeks, p < 0.05). Neurocognitive test scores were significantly correlated with QOL survey results. Conclusions The correlation between early diffusivity changes in the parahippocampal cingulum and the late decline in verbal recall suggests that diffusion tensor imaging may be useful as a biomarker for predicting late delayed cognitive decline.

Many tomographic interpretations of crosshole seismic traveltimes have approximated the raypaths with straight lines connecting the source and receiver. This approximation is valid where the velocity does not vary greatly, but in many regions of interest velocity variations of 10–20 percent or more are observed, causing significant ray curvature. Other work has taken this nonlinear effect into account, but there do not appear to be many cases of demonstrated success in its application to the crosshole seismic problem. We present here an iterative inversion scheme based on two‐dimensional ray tracing and its successful application to field data. The interpretation method iteratively ray traces and then updates the velocity model. Within each iteration, the differences between the data and the current model traveltimes obtained by ray tracing are related to the unknown velocity perturbations through a system of linear equations. A damped least‐squares method solves for the velocity perturbations which update the model. The iterations continue until the synthetic traveltimes fit the data to within the data error or until no improvement in the fit of the traveltimes is observed. The method is demonstrated on a small synthetic data set, where convergence to the correct solution is achieved in a few iterations. The method is then applied to field data from a crosshole experiment in crystalline rock. The frequency range of the seismograms is 1 to 6.6 kHz, allowing resolution of velocity structure on a scale of several meters. The resulting velocity image shows good agreement with other geologic and geophysical data. Synthetic Maslov seismograms calculated for the derived velocity model agree well with the waveform data, providing an independent test of the validity of the inversion method.

Purpose/Objectives Radiation injury to parahippocampal cingulum white matter is associated with cognitive decline. Diffusion tensor imaging (DTI) detects micropathologic changes in white matter. Increased radial diffusion (RD) and decreased axial diffusion (AD) correspond to demyelination and axonal degeneration/gliosis respectively. We aimed to develop a predictive model for radiation-induced cognitive changes based upon DTI changes. Materials/Methods Twenty-seven adults with benign or low-grade tumors received partial brain radiation therapy (RT) to a median dose of 54 Gy. Patients underwent DTI before RT, during RT, and at the end of RT. Cognitive testing was performed before RT, and 6 and 18 months after RT. Parahippocampal cingulum white matter was contoured to obtain mean values of AD and RD. Results By univariate analysis, decreasing AD and increasing RD during RT predicted declines in verbal memory and verbal fluency. By multivariate analysis, baseline neurocognitive score was the only clinical variable predicting verbal memory change; no clinical variables predicted verbal fluency change. In a multivariate model, increased RD at the end of RT significantly predicted decline in verbal fluency 18 months after RT. Conclusions Imaging biomarkers of white matter injury contributed to predictive models of cognitive function change after RT.

PurposeThere is little known about how brain white matter structures differ in their response to radiation, which may have implications for radiation-induced neurocognitive impairment. We used diffusion tensor imaging (DTI) to examine regional variation in white matter changes following chemoradiotherapy.MethodsFourteen patients receiving two or three weeks of whole-brain radiation therapy (RT) ± chemotherapy underwent DTI pre-RT, at end-RT, and one month post-RT. Three diffusion indices were measured: fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). We determined significant individual voxel changes of diffusion indices using tract-based spatial statistics, and mean changes of the indices within fourteen white matter structures of interest.ResultsVoxels of significant FA decreases and RD increases were seen in all structures (p<0.05), with the largest changes (20–50%) in the fornix, cingula, and corpus callosum. There were highly significant between-structure differences in pre-RT to end-RT mean FA changes (p<0.001). The inferior cingula had a mean FA decrease from pre-RT to end-RT significantly greater than 11 of the 13 other structures (p<0.00385).ConclusionsBrain white matter structures varied greatly in their response to chemoradiotherapy as measured by DTI changes. Changes in FA and RD related to white matter demyelination were prominent in the cingula and fornix, structures relevant to radiation-induced neurocognitive impairment. Future research should evaluate DTI as a predictive biomarker of brain chemoradiotherapy adverse effects.