Regional susceptibility to dose-dependent white matter damage after brain radiotherapy
Michael Connor, Roshan Karunamuni, Carrie McDonald, Tyler Seibert, Nathan White, Vitali Moiseenko, Hauke Bartsch, Nikdokht Farid, Joshua Kuperman, Anitha Krishnan, Anders Dale, Jona A Hattangadi-Gluth, Michael Connor, Roshan Karunamuni, Carrie McDonald, Tyler Seibert, Nathan White, Vitali Moiseenko, Hauke Bartsch, Nikdokht Farid, Joshua Kuperman, Anitha Krishnan, Anders Dale, Jona A Hattangadi-Gluth
Abstract
Background and purpose: Regional differences in sensitivity to white matter damage after brain radiotherapy (RT) are not well-described. We characterized the spatial heterogeneity of dose-response across white matter tracts using diffusion tensor imaging (DTI).
Materials and methods: Forty-nine patients with primary brain tumors underwent MRI with DTI before and 9-12months after partial-brain RT. Maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were generated. Atlas-based white matter tracts were identified. A secondary analysis using skeletonized tracts was also performed. Linear mixed-model analysis of the relationship between mean and max dose and percent change in DTI metrics was performed.
Results: Tracts with the strongest correlation of FA change with mean dose were the fornix (-0.46 percent/Gy), cingulum bundle (-0.44 percent/Gy), and body of corpus callosum (-0.23 percent/Gy), p<.001. These tracts also showed dose-sensitive changes in MD and RD. In the skeletonized analysis, the fornix and cingulum bundle remained highly dose-sensitive. Maximum and mean dose were similarly predictive of DTI change.
Conclusions: The corpus callosum, cingulum bundle, and fornix show the most prominent dose-dependent changes following RT. Future studies examining correlation with cognitive functioning and potential avoidance of critical white matter regions are warranted.
Keywords: Diffusion tensor imaging; Dose-dependent; Radiation; Radiotherapy; White matter.
Conflict of interest statement
Conflict of Interest Statement:
Dr. Hattangadi-Gluth has a research grant from Varian Medical Systems, unrelated to the current study. Dr. Dale receives funding through research agreements with General Electric Healthcare, and Medtronic, unrelated to the current study. Dr. Moiseenko reports prior honorarium and travel fees from Varian Medical Systems for a talk outside the submitted work.
Copyright © 2017 Elsevier B.V. All rights reserved.
Figures
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Linear mixed model coefficients; skeletonized…
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Linear mixed model coefficients; skeletonized tract analysis. Vertical ticks represent percent change per…
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Regional sensitivity to radiation. Tracts…
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Regional sensitivity to radiation. Tracts are filled with their corresponding coefficient for percent…
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- Adult
- Brain Neoplasms / diagnostic imaging
- Brain Neoplasms / radiotherapy*
- Diffusion Tensor Imaging
- Dose-Response Relationship, Radiation
- Female
- Humans
- Magnetic Resonance Imaging
- Male
- Middle Aged
- White Matter / pathology
- White Matter / radiation effects*
- Full Text Sources
- Other Literature Sources
- Medical
- Miscellaneous
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Regional sensitivity to radiation. Tracts…
Fig 4
Regional sensitivity to radiation. Tracts are filled with their corresponding coefficient for percent…
![Fig 4](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5518466/bin/nihms867550f4.jpg)
Source: PubMed