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Patient-Specific CBCT Synthesis for Real-time Tumor Tracking in Surface-guided Radiotherapy

Pan S, Su V, Peng J, Li J, Gao Y, Chang CW, Wang T, Tian Z et al.

ArXiv, 2024

22 participants

Abstract

In this work, we present a new imaging system to support real-time tumor tracking for surface-guided radiotherapy (SGRT). SGRT uses optical surface imaging (OSI) to acquire real-time surface topography images of the patient on the treatment couch. This serves as a surrogate for intra-fractional tumor motion tracking to guide radiation delivery. However, OSI cannot visualize internal anatomy, leading to motion tracking uncertainties for internal tumors, as body surface motion often does not have a good correlation with the internal tumor motion, particularly for lung cancer. This study proposes an Advanced Surface Imaging (A-SI) framework to address this issue. In the proposed A-SI framework, a high-speed surface imaging camera consistently captures surface images during radiation delivery, and a CBCT imager captures single-angle X-ray projections at low frequency. The A-SI then utilizes a generative model to generate real-time volumetric images with full anatomy, referred to as Optical Surface-Derived cone beam computed tomography (OSD-CBCT), based on the real-time high-frequent surface images and the low-frequency collected single-angle X-ray projections. The generated OSD-CBCT can provide accurate tumor motion for precise radiation delivery. The A-SI framework uses a patient-specific generative model: physics-integrated consistency-refinement denoising diffusion probabilistic model (PC-DDPM). This model leverages patient-specific anatomical structures and respiratory…

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