Results 201 to 210 of about 2,965,478 (248)

A review of artificial intelligence in brachytherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen, Richard L. J. Qiu, Tonghe Wang, Shadab Momin, Xiaofeng Yang   +4 more
wiley   +1 more source

Stereotactic radiotherapy for metastatic brain tumors: A comparative analysis of dose distributions among VMAT, Helical TomoTherapy, CyberKnife, Gamma Knife, and ZAP‐X

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract This study evaluates various radiotherapy techniques for treating metastatic brain tumor (BT), focusing on non‐coplanar volumetric modulated arc radiotherapy (NC‐VMAT), coplanar VMAT (C‐VMAT), Helical TomoTherapy (HT), CyberKnife (CK), Gamma Knife (GK), and ZAP‐X.
Toshihiro Suzuki, Masahide Saito, Ryutaro Nomura, Hikaru Nemoto, Naoto Yanagisawa, Ryuma Sawada, Zennosuke Mochizuki, Naoki Sano, Hiroshi Onishi, Hiroshi Takahashi   +9 more
wiley   +1 more source

A comparative analysis of deep learning architectures with data augmentation and multichannel input for locoregional breast cancer radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Studies on deep learning dose prediction increasingly focus on 3D models with multiple input channels and data augmentation, which increases the training time and thus also the environmental burden and hampers the ease of re‐training. Here we compare 2D and 3D U‐Net models with clinical accepted plans to evaluate the appropriateness of
Rosalie Klarenberg, Nienke L. M. Bakx, Coen W. Hurkmans   +2 more
wiley   +1 more source

Practical experience in commissioning ring applicators using ring applicator component type with bravos control software v1.2

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose The Bravos v1.2 control software introduces a ring applicator component type (ACT) with channel length verification to address geometric characteristics and dosimetric discrepancies caused by source positioning inaccuracies. This study aims to commission the ring applicator and investigate the new ring ACT in Bravos 1.2.
Xiuxiu He, Michael A. Trager, Gil'ad N. Cohen, Antonio L. Damato, David Aramburu Núñez   +4 more
wiley   +1 more source

Geometric and dosimetric evaluation of a commercial AI auto‐contouring tool on multiple anatomical sites in CT scans

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan, Alexandra Quinn, Patrick Horsley, Joseph Chan, Maegan Stewart, Regina Bromley, Jeremy Booth   +6 more
wiley   +1 more source

Toward a human‐centric co‐design methodology for AI detection of differences between planned and delivered dose in radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract 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 misalignment between AI systems and their users.
Luca M. Heising, Frank Verhaegen, Stefan G. Scheib, Maria J. G. Jacobs, Carol X. J. Ou, Viola Mottarella, Yin‐Ho Chong, Mariangela Zamburlini, Sebastiaan M. J. J. G. Nijsten, Ans Swinnen, Michel Öllers, Cecile J. A. Wolfs   +11 more
wiley   +1 more source

Quantification and dosimetric impact of intra‐fractional bladder changes during CBCT‐guided online adaptive radiotherapy for pelvic cancer treatments

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study quantitatively evaluates bladder changes and their dosimetric impact during the on‐couch adaptive process on a commercial CBCT‐based online adaptive radiotherapy (CT‐gART) platform. Methods Data from 183 fractions of ten patients receiving online ART for pelvic cancers were analyzed retrospectively.
Ingrid Valencia Lozano, Elizabeth Buss, Catherine S. Spina, David P. Horowitz, Lisa A. Kachnic, Michael Price, Yi‐Fang Wang, Reshma Munbodh   +7 more
wiley   +1 more source

Semi‐automated hippocampal avoidance whole‐brain radiotherapy planning

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Hippocampal avoidance whole‐brain radiotherapy (HA‐WBRT) is designed to spare cognitive function by reducing radiation dose to the hippocampus during the treatment of brain metastases. Current manual planning methods can be time‐consuming and may vary in quality, necessitating the development of automated approaches to streamline ...
Dong Joo Rhee, Subha Perni, Kelly J. Perrin, Kevin E. Casey, Alexandra O. Leone, Callistus M. Nguyen, Laurence E. Court, He Wang, Xin Wang, Eun Young Han   +9 more
wiley   +1 more source

Fast, automated optimization of virtual monoenergetic images with the dual‐energy image synthesizer for cone‐beam CT

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Dual‐energy cone‐beam CT (DE‐CBCT) has become subject of recent interest due to the ability to produce virtual monoenergetic images (VMIs) with improved soft‐tissue contrast and reduced nonuniformity artifacts. However, efficient production and optimization of VMIs remains an under‐explored part of DE‐CBCT's application.
Andrew Keeler, Jason Luce, Mathias Lehmann, John C. Roeske, Hyejoo Kang   +4 more
wiley   +1 more source

Open‐source deep‐learning models for segmentation of normal structures for prostatic and gynecological high‐dose‐rate brachytherapy: Comparison of architectures

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The use of deep learning‐based auto‐contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containing high‐dose‐rate (HDR) brachytherapy treatment scans, leading to poor performance on images ...
Andrew J. Krupien, Yasin Abdulkadir, Dishane C. Luximon, John Charters, Huiming Dong, Jonathan Pham, Dylan O'Connell, Jack Neylon, James M. Lamb   +8 more
wiley   +1 more source