Sun Yat-sen University Cancer Center

To develop a quantitative plan quality scoring (PQS) tool for evaluation of left-sided breast radiotherapy plans and to compare performance across four platforms.

To prospectively validate a prior and constraint-informed deep learning auto-segmentation framework for nasopharyngeal carcinoma (NPC) across three clinical centers, addressing accuracy, efficiency, and anatomical plausibility under real-world time constraint...

The combination of FLASH and ion-beam therapy could potentially enhance the therapeutic index of radiation therapy. The goal of this study was to establish a FLASH effect modeling approach for ion beams based on microdosimetry.

To develop and validate a cone-beam breast CT (CBBCT)-based multiregional radiomics model for identification of lymphovascular invasion (LVI) and fuse it into Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram for predicting axillary lymph node (ALN) met...

In the microdosimetric kinetic model (MKM), the quadratic coefficient β is commonly assumed to be independent of linear energy transfer (LET). However, experimental data suggest that β decreases at very high LET, likely because the conventional MKM does not e...

This study proposes an automated quality assurance (QA) method for radiation therapy structure delineation based on the RT contour QA software, addressing issues such as low efficiency in delineating clinical radiation therapy regions of interest (ROIs), sign...

To explore the feasibility of applying large language models (LLMs) for radiotherapy plan(RTP) evaluation to assist radiotherapy plan quality control and clinical decision making.

Volumetric modulated arc therapy (VMAT) planning is complex and time-consuming. This study proposes a direct VMAT plan generation method for cervical cancer, enhanced by a physics-guided 3D dose-domain supervision strategy to ensure dosimetric quality.

To investigate the inter- and intra-fractional morphological and dosimetric variations in precision radiotherapy for bladder cancer using Fan Beam CT (FBCT) and Electronic Portal Imaging Device (EPID), providing evidence for motion management.

Based on measured failure data and adverse event records from five sentinel hospitals, this study compares failure characteristics of medical electron linear accelerators (LA) across brands, regions and service life, clarifies core failure modes, evolutionary...

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 practice.

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.

This study proposed the residual dynamic transformer-nnU-Net (RDT-nnU-Net) for automated delineation of esophageal cancer and adjacent organs at risk (OARs) in radiotherapy, aiming to improve accuracy, coverage, and adaptability across radiotherapy strategies.

To evaluate a deep-learning based real-time automated radiotherapy planning pipeline for nasopharyngeal carcinoma (NPC) in both retrospective multi-center study and prospective clinical deployment.

X-ray-induced acoustic (XA) imaging provides a potential solution for noninvasive, real-time 3D dose verification by characterizing the radiation-induced thermoelastic effect. However, clinical implementation is severely hampered by limited-view sampling and...

Lattice radiation therapy (LRT) is an innovative radiotherapy technique lacking the standardized approach for the spatial distribution of high-dose regions. Manual placement is time-consuming and subjective. Automated regular geometric lattice arrangements ca...