Author profile
UT Southwestern Medical Center
Treating multiple oligometastatic lesions typically requires creating separate SBRT plans, resulting in longer treatment time and an increase in planning complexity. In this work we evaluate biology-guided multi-target treatment (MTT) approach for a PET-linea...
Therapy Physics
To develop a practical and simple method for estimating beam-on delay associated with respiratory-gated radiotherapy and validating the accuracy of the estimated delays
CBCT-based online adaptive radiotherapy (CBCT-oART) enables daily plan adaptation but is sensitive to intra-fraction motion during extended adaptive workflows. This study evaluates breath-hold (BH) motion stability and workflow impact using an in-bore surface...
Timely dose verification is essential for quality assurance (QA) in modern radiotherapy (RT), particularly in online adaptive RT, where measurement-based QA is often impractical. Current approaches are limited by machine/energy-specific designs, hindering sca...
Time-resolved volumetric MRI reconstructed from minimal k-space samples is critical for motion-adaptive radiotherapy to capture real-time deformable motion. We propose a Gaussian representation-based one-shot learning framework that models patient anatomy and...
Therapy Physics
While deep learning autosegmentation models are widely integrated into clinical workflows in radiation oncology, a critical gap has emerged: the "static deployment" trap. Once deployed, model performance can deteriorate due to real-world data evolution, makin...
Existing adaptive radiotherapy (ART) only accounts for inter-fraction variations in anatomy. Adapted plans can become suboptimal immediately due to anatomical changes during online planning and treatment delivery, degrading treatment quality and efficacy. To...
Treatment planning for MR-guided adaptive radiotherapy (MRgART) requires extensive time and effort in both preplanning and online adaptation processes. It is a major bottleneck hindering the efficiency and quality of MRgART. Specifically, extended preplanning...
Real-time liver motion tracking is essential in image-guided radiotherapy to enable precise tumor targeting. We developed a conditional latent point cloud diffusion model (Latent-Liver) for real-time deformable liver motion tracking and tumor localization usi...
AI-based autosegmentation is widely used in radiation oncology to improve efficiency and consistency; however, these models may silently fail when applied to cases that deviate from their training distribution, placing responsibility on clinicians to detect u...