Multi-component diffusion characterization of radiation-induced white matter damage
Abstract
PURPOSE: We used multi-b-value diffusion models to characterize microstructural white matter changes after brain radiation into fast and slow components, in order to better understand the pathophysiology of radiation-induced tissue damage.
METHODS: Fourteen patients were included in this retrospective analysis with imaging prior to, and at 1, 4-5, and 9-10 months after radiotherapy (RT). Diffusion signal decay within brain white matter was fit to a biexponential model to separate changes within the slow and fast components. Linear mixed-effects models were used to obtain estimates of the effect of radiation dose and time on the model parameters.
RESULTS: We found an increase of 0.11 × 10-4 and 0.14 × 10-4 mm2 /s in the fast diffusion coefficient per unit dose-time (Gy-month) in the longitudinal and transverse directions, respectively. By contrast, the longitudinal slow diffusion coefficient decreased independently of dose, by 0.18 × 10-4 , 0.16 × 10-4 , and 0.098 × 10-4 mm2 /s at 1, 4, and 9 months post-RT, respectively.
CONCLUSIONS: Radiation-induced white matter changes in the first year following RT are driven by dose-dependent increases in the fast component and dose-independent decreases in the slow component.
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.