BACKGROUND AND OBJECTIVES: Hematologic toxicity (HT) is a common and serious side effect for advanced cervical cancer patients undergoing chemoradiotherapy. Accurately predicting HT can significantly improve patient management and treatment outcomes....
. Gamma analysis serves as a critical safety assurance tool in radiotherapy, yet its broader clinical implementation remains constrained by insufficient error cause determination. To address this limitation, this study proposes a gamma passing rate (...
BACKGROUND: To evaluate the precision of automated segmentation facilitated by deep learning (DL) and dose calculation in adaptive radiotherapy (ART) for nasopharyngeal cancer (NPC), leveraging synthetic CT (sCT) images derived from cone-beam CT (CBC...
BACKGROUND: Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained mode...
BACKGROUND: Proton therapy is commonly used for treating hepatocellular carcinoma (HCC); however, its feasibility can be challenging to assess in large tumors or those adjacent to critical organs at risk (OARs), which are typically assessed only afte...
PURPOSE: In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating...
We propose a new variance reduction technique called last vertex splitting (LVS) designed to reduce computation time in Monte Carlo (MC) simulations for particles traversing high-attenuating media, such as the collimator and other beam-limiting devic...
. Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in frontier artificial intelligence (AI) m...
.: In radiation oncology, precision and timeliness of both planning and treatment are paramount values of patient care. Machine learning has increasingly been applied to various aspects of photon radiotherapy to reduce manual error and improve the ef...
Radiotherapy (RT) has become increasingly sophisticated, necessitating advanced tools for analyzing extensive treatment data in hospital databases. Such analyses can enhance future treatments, particularly through Knowledge-Based Planning, and aid in...
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