The Feasibility of Integrating Resting-State fMRI Networks into Radiotherapy Treatment Planning

Abstract

Background: Functional magnetic resonance imaging (fMRI) presents the ability to selectively protect functionally significant regions of the brain when primary brain tumors are treated with radiation therapy. Previous research has focused on task-based fMRI of language and sensory networks; however, there has been limited investigation on the inclusion of resting-state fMRI into the design of radiation treatment plans. Methods and materials: In this pilot study of 9 patients with primary brain tumors, functional data from the default mode network (DMN), a network supporting cognitive functioning, was obtained from resting-state fMRI and retrospectively incorporated into the design of radiation treatment plans. We compared the dosimetry of these fMRI DMN avoidance treatment plans with standard of care treatment plans to demonstrate feasibility. In addition, we used normal tissue complication probability models to estimate the relative benefit of fMRI DMN avoidance treatment plans over standard of care treatment plans in potentially reducing memory loss, a surrogate for cognitive function. Results: On average, we achieved 20% (P = 0.002) and 12% (P = 0.002) reductions in the mean and maximum doses, respectively, to the DMN without compromising the dose coverage to the planning tumor volume or the dose-volume constraints to organs at risk. Normal tissue complication probability models revealed that when the fMRI DMN was considered during radiation treatment planning, the probability of developing memory loss was lowered by more than 20%. Conclusion: In this pilot study, we demonstrated the feasibility of including rs-MRI data into the design of radiation treatment plans to spare cognitively relevant brain regions during radiation therapy. These results lay the groundwork for future clinical trials that incorporate such treatment planning methods to investigate the long-term behavioral impact of this reduction in dose to the cognitive areas and their neural networks that support cognitive performance.