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CBCT Reconstruction Using Single X-Ray Projection With Cycle-Domain Geometry-Integrated Denoising Diffusion

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    This study introduces a new AI model, the Patient-specific Cycle-domain Geometric-integrated Denoising Diffusion Probabilistic Model (CG-DDPM), for ultra-fast 3D Cone Beam Computed Tomography (CBCT) reconstruction. The CG-DDPM enables high-quality imaging from single X-ray views, improving radiotherapy motion monitoring.

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    Area of Science:

    • Medical Imaging
    • Radiotherapy
    • Artificial Intelligence

    Background:

    • Traditional Cone Beam Computed Tomography (CBCT) requires extensive X-ray projections, limiting its use for real-time motion monitoring during radiotherapy.
    • Current acquisition times of approximately one minute impede intra-fractional motion assessment.

    Purpose of the Study:

    • To develop a novel method for ultra-fast 3D CBCT reconstruction from single X-ray projections.
    • To enable precise intra-fractional motion monitoring during radiotherapy delivery.

    Main Methods:

    • Introduction of the Patient-specific Cycle-domain Geometric-integrated Denoising Diffusion Probabilistic Model (CG-DDPM).
    • Utilizes patient-specific CT/4DCT priors for reconstruction.
    • Employs a dual DDPM structure (Projection-DDPM and CBCT-DDPM) integrated with a Cycle-Domain Geometry-Integrated (CDGI) method and Geometric Transformation Module (GTM).

    Main Results:

    • Successfully reconstructed 3D CBCT from single-view projections in 37 lung cancer patients.
    • CG-DDPM significantly outperformed existing methods (V-nets, GANs, DDPMs) in reconstruction fidelity and artifact reduction.
    • Demonstrated high-quality reconstruction from both simulated and real-world data.

    Conclusions:

    • The CG-DDPM enables high-quality, ultra-fast volumetric imaging from single CBCT projections at any angle.
    • This advancement is crucial for radiotherapy of motion-associated cancers and image-guided interventions.
    • Paves the way for real-time, intra-fractional motion monitoring in radiotherapy.