BACKGROUND: Previous knowledge-based planning studies have demonstrated the feasibility of predicting three-dimensional photon dose distributions and subsequently generating treatment plans. The steepness of dose fall-off represents a critical metric...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 4, 2025
PURPOSE: To investigate the feasibility of deep-learning-based synthetic 4DCT (4D-sCT) generation from 4DMRI data of abdominal patients undergoing Carbon Ion Radiotherapy (CIRT).
Journal of applied clinical medical physics
Apr 3, 2025
PURPOSE: Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs-at-risk (OARs). Particularly in the case of lung tumors, de...
BACKGROUND: As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 1, 2025
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
Journal of applied clinical medical physics
Mar 31, 2025
INTRODUCTION: Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a...
International journal of radiation oncology, biology, physics
Mar 29, 2025
PURPOSE: Recent advances in artificial intelligence (AI) have showcased the potential of automatic treatment planning for clinical trials involving radiation therapy. This paper offers an overview of the current landscape of AI-based treatment planni...
BACKGROUND: Conventional proton dose calculation methods are either time- and resource-intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade-off between computational efficiency and accu...
Technology in cancer research & treatment
Mar 28, 2025
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segme...
To evaluate the impact of beam mask implementation and data aggregation on artificial intelligence-based dose prediction accuracy in proton therapy, with a focus on scenarios involving limited or highly heterogeneous datasets.In this study, 541 prost...
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