Background Effective radiotherapy requires balancing target coverage with sparing of organs at risk. We developed a fully automated, Python-based pipeline to integrate white matter tracts (WMTs) into stereotactic brain radiotherapy (SBRT) planning. Methods The pipeline uses a probabilistic atlas of 52 WMTs and includes image pre-processing, affine and non-linear registration to a standardized space, and dose mapping into the atlas framework. Various interpolation techniques were assessed to optimize dose-mapping accuracy. Robustness was assessed through sensitivity analyses of four interpolation methods for affine and non-linear transformations, resulting in 16 combinations, and local perturbations of registration fields. Prospective validation was performed in nine patients with pre-treatment diffusion MRI (GE 3T, 64 directions, b = 1000, 2 mm isotropic, 4′30 acquisition), where atlas-based WMTs were compared with individual tractography using TractSeg and DeepWMA. Results Applied to 108 patients, the pipeline achieved precise spatial registration, with B-spline interpolation providing the most consistent dose mapping. Sensitivity analyses showed negligible effects of interpolation or perturbations on the mean and minimum doses to WMTs, while the maximum dose in tracts located adjacent to the planning target volume was more sensitive, with rare deviations up to ∼1 Gy. In prospective validation, median Dice coefficients across all evaluated WMTs were 0.49 (range 0.00–0.66) for TractSeg versus DeepWMA, 0.45 (0.02–0.68) for TractSeg versus the atlas, and 0.31 (0.00–0.55) for DeepWMA versus the atlas. Despite modest Dice values, as consistently reported in tractography benchmarks, the atlas-based pipeline performed within the same range of variability as that observed between two widely used tractography methods, supporting its validity for clinical application. Conclusions This pipeline enables robust and reproducible integration of WMTs into SBRT planning, validated against tractography and applicable when diffusion MRI is unavailable. It provides a foundation for establishing tract-specific dose constraints, advancing neurocognitive-sparing SBRT.
Integration of white matter tracts in stereotactic brain radiotherapy treatment planning with a fully automated atlas-based pipeline
Satragno, Camilla;
2025
Abstract
Background Effective radiotherapy requires balancing target coverage with sparing of organs at risk. We developed a fully automated, Python-based pipeline to integrate white matter tracts (WMTs) into stereotactic brain radiotherapy (SBRT) planning. Methods The pipeline uses a probabilistic atlas of 52 WMTs and includes image pre-processing, affine and non-linear registration to a standardized space, and dose mapping into the atlas framework. Various interpolation techniques were assessed to optimize dose-mapping accuracy. Robustness was assessed through sensitivity analyses of four interpolation methods for affine and non-linear transformations, resulting in 16 combinations, and local perturbations of registration fields. Prospective validation was performed in nine patients with pre-treatment diffusion MRI (GE 3T, 64 directions, b = 1000, 2 mm isotropic, 4′30 acquisition), where atlas-based WMTs were compared with individual tractography using TractSeg and DeepWMA. Results Applied to 108 patients, the pipeline achieved precise spatial registration, with B-spline interpolation providing the most consistent dose mapping. Sensitivity analyses showed negligible effects of interpolation or perturbations on the mean and minimum doses to WMTs, while the maximum dose in tracts located adjacent to the planning target volume was more sensitive, with rare deviations up to ∼1 Gy. In prospective validation, median Dice coefficients across all evaluated WMTs were 0.49 (range 0.00–0.66) for TractSeg versus DeepWMA, 0.45 (0.02–0.68) for TractSeg versus the atlas, and 0.31 (0.00–0.55) for DeepWMA versus the atlas. Despite modest Dice values, as consistently reported in tractography benchmarks, the atlas-based pipeline performed within the same range of variability as that observed between two widely used tractography methods, supporting its validity for clinical application. Conclusions This pipeline enables robust and reproducible integration of WMTs into SBRT planning, validated against tractography and applicable when diffusion MRI is unavailable. It provides a foundation for establishing tract-specific dose constraints, advancing neurocognitive-sparing SBRT.
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