Paper Proffered Program Therapy Physics

Beam Angle Optimization and Dose Quantification for Tumor Tracking Using Kv Scattered X-Ray Imaging

Abstract
Purpose

Photon-counting detectors (PCD) exhibit high sensitivity for scattered photons, enabling kilovoltage (kV) scattered X-ray imaging with potential for real-time tumor tracking for lung cancer radiotherapy. The performance in this application is strongly influenced by imaging geometry and signal statistics. This study investigated the effects of incident beam angle and dose on image quality and tumor tracking accuracy in kV scattered X-ray imaging, with the goal of identifying an optimal configuration for robust tumor tracking.

Methods

Comprehensive Monte Carlo simulations were performed to model scattered X-ray images using a patient-derived 4D-CT containing a spherical-like tumor target. To identify the optimal beam angle, we simulated at 8 beam angles using a fixed X-ray dose at the 40% phase. Image quality was quantified by the contrast-to-noise ratio (CNR) of the tumor region. With the optimal beam angle identified, CNR was evaluated at three dose levels, including the maximum permissible dose, to assess dose-dependent image quality. The optimized beam angle and maximum dose were used to generate scattered images across all respiratory phases. The resulting images were denoised using Gaussian filtering, and tumor tracking was performed via a template-matching approach. Tracking accuracy was quantified by comparing the tumor displacements with ground-truth motions derived directly from the 4D-CT.

Results

For this patient, the optimal beam angle was 315°, and the maximum permissible dose was 166.6 μGy. Using this configuration, tumor tracking was evaluated across 10 respiratory phases. Tumor localization achieved 0.60 ± 0.70 mm accuracy.

Conclusion

Beam angle and X-ray dose were shown to be key factors governing image quality and tumor tracking accuracy in kV scattered X-ray imaging. These findings support the feasibility of kV scattered X-ray imaging as a low-dose, marker-free approach for tumor tracking in lung radiotherapy.

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