Retrospective intrafraction motion verification using triggered kilovoltage images during bone metastases stereotactic body radiotherapy

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• Picked for Medical Physics (paper of the day, 25 August 2026): Triggered KV images used for intrafraction motion verification

Abstract

BACKGROUND AND PURPOSE: Triggered kilovoltage images acquired during radiotherapy delivery remain underexploited for quantitative intrafraction motion analysis. This study aimed to develop and evaluate a retrospective workflow for intrafraction motion verification using triggered kilovoltage images during bone metastases stereotactic body radiotherapy. MATERIALS AND METHODS: Triggered kilovoltage images and corresponding treatment-planning data were retrospectively extracted from 49 patients treated in two radiotherapy centers. For each triggered image, a digitally reconstructed radiograph was generated from planning computed tomography dataset. After preprocessing, rigid in-plane registration between triggered images and digitally reconstructed radiographs was performed. The workflow was evaluated using phantom experiments with known physical displacements and patient datasets with simulated shifts, then applied to 8717 triggered images acquired during 183 treatment fractions. RESULTS: Correct registration was obtained for 7105 images (81.5%), while 1612 images (18.5%) were classified as aberrant and excluded from motion analysis. After exclusion, the mean displacement vector magnitude was 1.2 ± 0.8 mm. Overall, 85% of measurements showed displacements ≤2 mm and 98% showed displacements ≤3 mm. Sustained displacement events exceeding 2 mm over three consecutive images were observed in 405 of 7105 images (5.7%) and in 46 of 159 analyzable fractions (28.9%). The mean computation time per image registration was 1699 ± 504 ms. CONCLUSIONS: Triggered kilovoltage images contain quantitative information that can support retrospective intrafraction motion assessment during bone metastases stereotactic body radiotherapy. This workflow may help identify fractions requiring further review and support offline quality assurance, although prospective validation is required before clinical implementation.

Abstract as published, via PubMed.