Author profile
Département de Physique, Université de Montréal
Dose accumulation using deformable image registration (DIR) enables a more accurate evaluation of delivered dose in adaptive radiotherapy, allowing evaluation of discrepancies between planned and delivered treatments. However, different DIR algorithms produce...
Deep inspiration breath-hold (DIBH) can reduce cardiac dose in left-sided breast cancer radiotherapy, but its benefit varies substantially between patients. DIBH is also more resource-intensive than free breathing (FB), increasing treatment time and workflow...
Accurate dose measurement in ultra-high dose rate (UHDR) electron beams is essential for clinical quality assurance. Plastic scintillation detectors (PSDs) are promising candidates for UHDR dosimetry but must demonstrate radiation hardness and calibration sta...
Simulation-free (SimF) workflows for MR-guided radiotherapy demonstrate potential to streamline treatment initiation by eliminating dedicated simulation scans. We evaluated the feasibility of implementing an SimF approach for single fraction liver SBRT on the...
Therapy Physics
Adaptive radiotherapy (ART) requires accurate daily volumetric imaging, yet cone-beam CT (CBCT) is fundamentally limited by X-ray scatter, leading to degraded contrast, CT number inaccuracy, and reduced reliability of automated segmentation. These limitations...
FLASH radiotherapy, defined by ultra-high dose rates (UHDR; >40 Gy/s), can reduce normal-tissue toxicity while maintaining tumor control, yet reported FLASH effects show substantial variability across experimental and preclinical studies. Dielectric materials...
Robust and quantitative treatment planning remains a critical barrier to reproducible preclinical FLASH radiotherapy (FLASH-RT) research. We developed and validated a Monte Carlo–based treatment planning interface (TPI) for electron FLASH beams, enabling accu...
To compare different dual-energy cone-beam CT (DE-CBCT) configurations for the Varian HyperSight system via relative electron density (ED) and effective atomic number (EAN) quantification, as well as contrast improvement.
Deep learning dose prediction (DP) models rapidly predict radiotherapy dose distributions, addressing critical time constraints in adaptive radiotherapy (ART). Recent patient-specific (PS) approaches fine-tune models on individual initial plans for highly tai...
Therapy Physics