Randomized trial demonstrates high accuracy in real-time dose monitoring using monocular imaging in breast cancer patients, suggesting improved adaptive radiotherapy.
BACKGROUND: Interfractional anatomical variations during breast cancer radiotherapy can significantly deviate the delivered dose from the treatment plan. Standard image guidance via Cone-Beam CT (CBCT) is typically sparse due to radiation and workflow constraints, leaving daily geometric changes unmonitored. PURPOSE: To bridge this gap, we propose a physics-informed framework that utilizes monocular surface vision for continuous, non-ionizing 3D dose reconstruction. METHODS: The system utilizes the weekly CBCT scans from the first 2 weeks of treatment (Week 1 and Week 2) for patient-specific calibration. Surface features are extracted via a hybrid HOG-CNN descriptor, while 3D deformation vector fields (DVFs) are compressed into a low-dimensional latent space via Principal Component Analysis (PCA). A linear mapping from surface topography to PCA coefficients is optimized using physics-informed Tikhonov regularization, incorporating an eigenvalue-based penalty matrix to suppress high-order non-physical modes. Post-calibration, the model reconstructs 3D dose distributions for subsequent fractions in real time using only monocular input. RESULTS: Validated on 29 patients (87 fractions), the framework achieved a deformation coefficient correlation of R = 0.796. Reconstructed doses yielded a mean Gamma passing rate (3%/3 mm) of 93.8% ± 3.1% and a dose correlation of 0.940 ± 0.037. Ablation studies demonstrated that removing physics constraints or PCA reduction significantly degraded performance (ΔGPR = -8.5% and -22.1%, respectively; p < 0.001). End-to-end latency was 42 ± 5 ms per fraction, representing a ∼124-fold acceleration over commercial deformable registration solutions. CONCLUSIONS: This framework transforms routine weekly CBCTs into robust "calibration anchors" for continuous visual dose monitoring. It provides clinical-grade accuracy with negligible computational overhead and no additional ionizing dose, offering a practical solution for real-time adaptive radiotherapy.
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Deng et al. (2026) studied this question.
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