Author profile
The University of Texas MD Anderson Cancer Center
To evaluate the feasibility and adapt-to-shape (ATS) workflow efficiency of a novel UPFRONT "Brachy-like" Stereotactic Body Radiation Therapy (SBRT) technique delivered via MR-LINAC. This upfront boost aims to deliver a steep-gradient high dose to a "Virtual-...
Common contour evaluation metrics(e.g., DSC or HD) provide global summaries that can miss localized, anisotropic disagreements that drive clinically meaningful edits. Although surface-DSC(SDSC) better reflects boundary discrepancies, it typically uses a subje...
Deep-learning (DL) auto-segmentation is routinely used clinically, yet domain shift and vendor model upgrades can change behavior in non-intuitive ways. We present a regression-testing framework to commission upgraded commercial auto-contouring models and to...
The primary objective of this study was to develop a generalized deep learning-based dose calculation engine capable of accurate, site-independent dose prediction. By utilizing a beamlet-based input strategy, we aimed to establish a computationally consistent...
To develop and validate a contour-regulated automated registration framework for correcting motion artifacts and aligning time-resolved scans in liver CT perfusion (CTp) series.
To develop and validate consensus electron density (ED) look-up tables (LUTs) for MR-only radiotherapy planning through multi-institutional collaboration.
Vacuum cradles/bags (VC) combined with head and leg immobilization are commonly used for prostate stereotactic body radiotherapy (SBRT) treatment setup. Removing the VC may offer practical advantages for efficient patient positioning, comfort, and high-qualit...
Daily re-planning based on warm-start optimization is a common strategy for online adaptive radiotherapy. This method is beneficial in cases when differences between the reference and daily anatomy are within a limited range. We quantify the effects of this s...