Icahn School of Medicine at Mount Sinai

Treatment planning for pancreatic SBRT remains challenging due to proximity and overlap of the target with the critical organs-at-risk (OARs). This study uses RapidPlan-predicted dose volume histograms (DVHs) to guide treatment planning in Monaco.

Treatment planning for malignant pleural mesothelioma (MPM) is challenging due to target geometry and organ-at-risk sparing requirements. This study uses RapidPlan-predicted dose volume histograms (DVHs) to guide Monaco planning for TrueBeam and Versa deliver...

Micro-ultrasound (microUS) provides high-resolution visualization of the prostate for interventional procedures; however, the scarcity of annotated datasets limits the development of robust automated segmentation methods. This study leverages a foundation-mod...

A persistent challenge in medical physics education is the lack of centralized, interactive, and easily accessible training tools that integrate into daily clinical workflows. Many existing resources are static, fragmented, and difficult to use consistently a...

To systematically assess whether commonly proposed architectural enhancements provide measurable benefits for deep learning-based radiotherapy dose prediction, using controlled comparisons of 3D U-Net variants to support evidence-based model selection and est...

Treatment planning system (TPS) beam modelling is identified as the largest cause of independent dosimetry audit failure. This study aims to develop and validate a universal beam model (UBM) specific to single-iso multi-target (SIMT) stereotactic radiosurgery...

To test the hypothesis that geometric metrics measured by the enhanced-couch Machine Performance Check (MPC) can serve as a surrogate to predict off-axis isocentricity failure.

While 30% of lung cancer patients cannot tolerate breath-hold, free-breathing(FB) proton pencil-beam-scanning(PBS) deliveries compromise target coverage from the interplay effects of large motion. This study presents a novel FB-gated spirometer-based respirat...

Objective assessment of radiotherapy plans is challenging because expert assessment relies on complex, multidimensional tradeoffs that are not fully captured by predefined dose-volume constraints. This study aims to quantitatively interpret expert treatment p...

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.

Proton LATTICE radiotherapy (LRT), a spatially fractionated radiotherapy (SFRT), delivers high dose to intratumoral vertices while maintaining low valley dose. Single-field optimization (SFO) is robust in preserving peak-to-valley patterns but may increase en...

Commercial treatment planning systems (TPS), such as Varian Eclipse, cannot perform dose calculations on CBCTs acquired with 6DoF couch corrections. This limitation prevents direct dosimetric re-evaluation of verification scans. This study presents an offline...

Ultra-high-dose-rate (UHDR) proton irradiation may spare normal tissue (FLASH effect), but PBS proton dose rate is limited by machine constraints (minimum MU/spot and dwell time). Intra-field interruptions can leave sub-threshold MU for remaining delivery, de...

Accurate prediction of radiation-induced toxicity is crucial for optimizing radiotherapy outcomes, yet most existing models rely on supervised learning with clinician-graded toxicity scores that are susceptible to patient self-reporting errors and intra-obser...

Radiation pneumonitis (RP) remains a clinically significant dose-limiting toxicity in thoracic radiotherapy. Accurate RP prediction is challenging due to its multifactorial etiology and complex interactions among contributing factors. Although multimodal data...

This work aims to develop a physics-aware deep learning framework for radiotherapy dose prediction that improves accuracy and clinical efficiency. The proposed Physics-Aware Multimodal UNet (PhysMM-UNet) integrates CT images, fluence maps, organ masks, and mu...

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...

Intensity-modulated proton therapy (IMPT) plan optimization is time-intensive due to its high dimensionality and the inherent non-convexity of clinical dosimetric constraints. Conventional algorithms like projected gradient descent (PGD) often require extensi...

Consistently automating clinically acceptable plans without human intervention remains a challenge in radiotherapy. While knowledge-based planning (KBP) predicts optimal achievable dose-volume metrics, it often fails to achieve these metrics without manual ad...

Diagnostic and Interventional Radiology Physics

Knowledge-based planning (KBP) improves plan quality and efficiency. However, training institution-specific models requires substantial clinical data and expertise, and publicly available models may not align with local clinical objectives. This study evaluat...

To quantify the dosimetric consequences of physiology-composed abdominal motion on pancreatic cancer SBRT.

To evaluate whether a Large Language Model (LLM)–driven autonomous planning system can self-learn planning strategies from human planner logs and apply this knowledge to generate clinically compatible radiotherapy plans without manual refinements.

To assess the repeatability of brain white matter sodium concentration (TSC) measurements using 3T sodium MRI with the Fermat Looped Orthogonally Encoded Trajectories (FLORET) 3D spiral.

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...

Therapy Physics

In-vivo dosimetry requires compact dosimeters suitable for patient placement, with multiple detectors often deployed simultaneously for spatial sampling. The 2023 nanoDot OSLD recall left many clinics without accessible, low-cost alternatives. Our purpose is...

Monitoring real-time pancreatic target motion during radiotherapy is challenging. The diaphragm can be tracked by ultrasound; however, published findings on its correlation with abdominal motion are inconsistent. We aimed to develop a robust algorithm to asse...

For single-isocenter multi-target (SIMT) stereotactic radiosurgery (SRS), benchmarking, auditing and inter-institutional standardization of dose delivery remains challenging as it requires specialized equipment and expertise. Electronic portal imaging devices...

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.