Author profile
Icahn School of Medicine at Mount Sinai
To implement a full abdominal motion model that combines respiration with gastrointestinal (GI) motility and quantify its interplay impact in pencil-beam scanning (PBS) proton therapy.
Accurate prediction of radiation-induced toxicity is crucial for optimizing radiotherapy outcomes. However, most existing predictive models rely on uni-modal data and deterministic models that are vulnerable to label noise and uncertainty. This study aims to...
Accurate real-time tumor tracking is critical for MRI-guided radiotherapy, where geometric uncertainty can significantly increase dose to surrounding critical organs. Continuous cine-MRI enables motion-adaptive treatment. However, accurate tracking under larg...
To quantify the dosimetric consequences of physiology-composed abdominal motion on pancreatic cancer SBRT.
Existing deep learning-based dose prediction methods primarily learn empirical mappings between anatomy and dose, without modeling beam delivery physics. This gap may limit their robustness and accuracy, especially in heterogeneous regions where dose depositi...
To quantify the impact of gastrointestinal (GI) motility on pencil-beam scanning (PBS) proton therapy for abdominal cancers, and assess how fractionation and motion amplitude mitigate motility-induced interplay effects.