Deformable Dose Mapping and Accumulation Techniques for Stereotactic Body Radiation Therapy (SBRT) of Lung Cancers.

Chetty, Indrin J; Zhong, Hualiang · Int J Radiat Oncol Biol Phys · 2026

review · Level V

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Abstract

Deformable dose mapping and accumulation are essential tools in lung cancer stereotactic body radiation therapy (SBRT). Here, we provide a critical review of deformable image registration (DIR)-based dose mapping and accumulation techniques in SBRT for lung cancers, with emphasis on methodological principles, clinical applications, limitations, and guidance for practice. A broad appraisal of the literature was conducted, emphasizing DIR algorithms and related dose mapping strategies, including direct dose mapping, voxel warping, and energy/mass-congruent mapping. These methods were examined across key clinical scenarios for lung SBRT planning, including motion management, adaptive radiation therapy and reirradiation. Significant errors can occur when anatomic changes are large, such as tumor regression, mass and density variations, etc., as observed in reirradiation scenarios. These errors will propagate to the mapped and composite dose distributions, particularly in steep dose gradients, resulting in inaccuracies. Biomechanical models combined with energy/mass-congruent mapping better preserve physical principles under such conditions. Quality assurance remains challenging due to the absence of standardized benchmarks. Tools for validation of DIR and deformable dose accumulation accuracy in the clinic are severely lacking. The development of quality assurance frameworks is critical to safe implementation. Clinicians should apply DIR-based dose accumulation conservatively, particularly when anatomy changes considerably in reirradiation settings, given the potential for significant uncertainties in the composite doses. Each clinical case should be viewed carefully by assessing the risk/benefit, and clinical application should follow cooperative group guidelines. Standardization of methods for dose accumulation will enhance dose-volume-effect modeling.

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