All conference submissions

To investigate the combined effects of gold nanoparticles (GNPs) and ultrahigh dose rate (UHDR) electron beams on reactive oxygen species (ROS) generation under FLASH radiotherapy conditions using Monte Carlo (MC) simulations.

Diffusing Alpha-emitter Radiation Therapy (‘Alpha DaRT’) is a novel modality for treating solid tumours with alpha particles from the decay of 224Ra. This study aims to model well chamber response to derive activity calibration c...

To simulate, using Geant4-DNA, proton radiation induced plasmid DNA fragmentation in the plateau as well as Bragg peak regions in a cell-free, aqueous environment of different free radical scavenger concentrations. Atomic Force M...

To analyze the morphological and dosimetric variations in bladder patients during radiotherapy, and establish a dose-anatomy adaptive radiotherapy(ART) triggering model, providing a basis for individualized ART in clinical practi...

Respiratory motion and delivery dynamics can affect delivered dose in scanned proton therapy, particularly for thoracic treatments. Many existing motion-evaluation approaches rely on simplified delivery assumptions or research-on...

Proton therapy plans are optimized by relating the delivered dose to an equivalent photon dose using the Relative Biological Effectiveness (RBE). Clinically, a constant RBE of 1.1 is assumed, despite evidence that RBE varies alon...

To develop and validate an MRI–based fusion model (Rad–SRad–SwinT) integrating conventional radiomics (Rad), subregional radiomics (SRad), and Transformer–derived deep learning features (Swin Transformer, SwinT) to predict post–r...

To develop an MRI-compatible, tissue-equivalent lung phantom with two embedded lesions capable of reproducing realistic breathing motion, including lesion displacement and tissue compression during the breathing cycle. This phant...

To develop and evaluate a time-efficient pulse sequence – MR-MED (multi-readout reduced field-of-view (rFOV) multi-spin-echo EPI diffusion-weighted imaging (MR-MED) sequence for prostate luminal water imaging (LWI). This sequence...

To compare MR-simulation motion emulation with measured respiratory gating performance for ultra-central lung treatments on 1.5T MR-linac and to identify the dominant factors affecting gating efficiency. The study focuses on the...

To develop and validate a robust CT-radiomics framework using feature-level multicenter distribution adaptation (MDA) to differentiate pulmonary tuberculosis (TB) from fungal pneumonia (FP), explicitly addressing the challenge of...

Lattice radiotherapy (LRT) intentionally creates heterogeneous “peak-and-valley” dose distributions to improve therapeutic ratio in bulky tumors. Conventional plan-quality metrics fail to capture the multi-dimensional nature of L...

To characterize the reproducibility and dosimetric stability of a 5-day fractionated preclinical irradiation protocol delivered on a clinical Varian TrueBeam linac operated under FLASH and conventional (CONV) settings.

Monte Carlo (MC) simulation is the gold standard for dose calculation in radiation therapy, as it can accurately reproduce the interaction processes between photons and human tissues in intensity-modulated radiation therapy (IMRT...

Multi‑target Winston–Lutz (Multi‑WL) testing supports stereotactic QA for single‑isocenter, multi‑lesion SRS/SBRT. Targeting accuracy was benchmarked across 10 clinical linacs (Varian and Elekta) used by multiple institutions to...

To develop and validate consensus electron density (ED) look-up tables (LUTs) for MR-only radiotherapy planning through multi-institutional collaboration.

Although the number of proton centers continues to rise worldwide, rapid methods for commissioning and dose verification are still lacking. To evaluate the performance of a GPU-accelerated Monte Carlo (MC) dose computational fram...

The Varian Halcyon linear accelerator, featuring a ring-gantry design and dual-layer multileaf collimator (MLC), has gained increasing clinical adoption due to its streamlined workflow and operational efficiency. Unlike conventio...

Dose distribution maps are critical for high-quality radiotherapy treatment planning, yet plan optimization remains largely manual and trial-and-error, leading to substantial time costs and limited efficiency. While knowledge-bas...

To mitigate the loss of spatial information inherent to DVH-based and coarse categorical descriptors used for breast cancer–related lymphedema prediction, we present a multi-modal cross-attention predictive model with self-attent...

This work assesses a multimodal Large Language Model (MedGemma) for generating planning objectives in standard fractionation (60Gy/30fx) lung cancer radiotherapy. Unlike static vendors' templates, the proposed system dynamically...

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 fac...

Manual verification of AI-based auto-contouring is labor-intensive and prone to fatigue-related errors. This study evaluated the feasibility of automated visual quality assessment using a multimodal large language model (LLM), Ge...

To develop a multi-omics data integration method based on ensemble learning to construct a prognostic decision model for MRI-guided radiotherapy in gliomas, providing reliable reference for clinical decision-making.