All conference submissions

Accurate prediction of beam delivery time (BDT) is essential for operational efficiency, 4D dose calculations, and advanced proton therapy techniques such as proton arc therapy. Despite its importance, no machine-specific BDT mod...

Radiation segmentectomy using yttrium-90 (Y‑90) transarterial radioembolization (TARE) is an established treatment for hepatocellular carcinoma (HCC), with the goal of achieving complete tumor necrosis through delivery of high do...

Although immune checkpoint blockade (ICB) benefits only a subset of patients, combining ICB with stereotactic body radiation therapy (SBRT) may enhance therapeutic response. Building on a validated CT-based radiomics score (RS) t...

To determine whether a supervised machine learning (SML) approach to low-dose biodosimetry, trained on radiation-induced chromosomal translocations of astronauts and individual radiation response covariates, could be an alternati...

Daily QA tolerances are often implemented as fixed pass/fail thresholds, yet MR-Linac performance can be facility-specific and may evolve over time. This study used statistical process control (SPC) to establish global, machine-s...

Weekly or triggered online adaptive radiotherapy has not been widely adopted in clinical practice because of the time and resource demands. Although the Ethos platform enables CBCT-based online adaptive radiotherapy, daily adapta...

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-re...

CBCT is routinely acquired prior to proton therapy for patient setup. However, the limited image quality of CBCT compromises the dose calculation accuracy and limits its use for treatment plan adjustments. This study aims to deve...

To develop a clinically adaptable 3D deep learning framework for synthesizing quantitative PET images from routine CT volumes, enabling reliable metabolic assessment for lung cancer while reducing reliance on additional PET scans.

In proton therapy, conventional DVH comparisons may be insensitive to planning changes intended to reduce LET‑associated biological risk in normal tissues, despite clinically observed reductions in toxicity. Dose–LET volume histo...

The delineation of uveal melanoma for proton beam therapy can be guided by 2D fundus photography registered to a patient-specific 3D eye model. However, the mapping suffers from camera-specific distortions and is further impacted...

Deep silicon photon counting CT can produce quantitative CT images with every scan, leveraging 8 energy bins to quantify material densities. This study evaluates the material decomposition (MD) and virtual monoenergetic image (VM...

This study aims to develop a mathematical model to understand the dynamics of immunotherapy and radiotherapy interactions for non-small cell lung cancer (NSCLC), focusing on how tumor and immune cells interact under the effects o...

Accurate delineation of the high-risk clinical target volume (HR-CTV) and organs at risk (OARs) is critical for cervical cancer brachytherapy. However, treatment planning is time-consuming, and prolonged waiting can lead to organ...

This study aimed to quantitatively investigate the robustness of virtual bolus (VB)–generated skin flash under respiratory motion in breast volumetric modulated arc therapy (VMAT) using measurement-based dosimetry.

Radiopharmaceutical therapies (RPTs) effectively treat metastatic castration-resistant prostate cancer, yet injected radioactivities remain empirically prescribed. Although physiologically-based pharmacokinetic (PBPK) and pharmac...

Radiotherapy (RT) for head and neck (HN) cancer frequently induces xerostomia due to radiation‑mediated parotid gland damage. Mechanistic modeling of parotid response may improve understanding of toxicity development and enable m...

To expedite the diagnosis-to-treatment workflow in radiation oncology, this work evaluates a machine learning approach for generating synthetic radiation therapy (RT) planning images directly from diagnostic computed tomography (...

Medical physics is essential to the safe and effective use of ionizing radiation in radiotherapy, diagnostic imaging, and nuclear medicine, with clinically qualified medical physicists (QMPs) playing a critical role in quality as...

Metallic implants within the clinical target volume (CTV) introduce substantial uncertainties in intensity-modulated proton therapy (IMPT) for head and neck cancer (HNC). This work introduces megavoltage CT (MVCT)-assisted uncert...

Accurate, frequent bladder volume monitoring is essential in pelvic radiotherapy because inter-fraction filling variability affects target coverage and organ-at-risk sparing. Yet current options are suboptimal: CBCT offers 3D ana...

To develop and validate a Physics-Informed Neural Network (PINN) framework for simulating blood flow in hepatic arteries, serving as a proof-of-concept for modeling Y-90 microsphere distribution for liver cancer radioembolization...

Radiotherapy is central in lung cancer treatment, but many tumors are intrinsically radioresistant. A mechanism of radioresistance in lung cancer is mutations in the KEAP1 gene, which is present in a significant number (15-20%) o...

In boron neutron capture therapy (BNCT), heterogeneous subcellular distributions of 10B critically affect neutron energy deposition and cell-killing effectiveness. However, biophysical models explicitly incorporating subcellular...