Results 11 to 20 of about 4,374,982 (417)

Radiotherapy planning using MRI

Physics in Medicine and Biology, 2015
The use of magnetic resonance imaging (MRI) in radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of challenges are also considered: the requirements that MR images are acquired in the RT treatment position, that they ...
Maria A. Schmidt, Geoffrey S. Payne
openaire   +4 more sources

Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning [PDF]

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018
Multi-task neural network architectures provide a mechanism that jointly integrates information from distinct sources. It is ideal in the context of MR-only radiotherapy planning as it can jointly regress a synthetic CT (synCT) scan and segment organs-at-risk (OAR) from MRI.
Felix J. S. Bragman, Ryutaro Tanno, Z. Eaton-Rosen, Wenqi Li, D. Hawkes, S. Ourselin, D. Alexander, J. McClelland, M. Jorge Cardoso   +8 more
arxiv   +2 more sources

Elevated Coronary Artery Calcium Quantified by a Validated Deep Learning Model From Lung Cancer Radiotherapy Planning Scans Predicts Mortality

JCO Clinical Cancer Informatics, 2022
PURPOSE Coronary artery calcium (CAC) quantified on computed tomography (CT) scans is a robust predictor of atherosclerotic coronary disease; however, the feasibility and relevance of quantitating CAC from lung cancer radiotherapy planning CT scans is ...
K. Atkins, J. Weiss, R. Zeleznik, D. Bitterman, T. Chaunzwa, E. Huynh, C. Guthier, D. Kozono, J. Lewis, B. Tamarappoo, A. Nohria, U. Hoffmann, H. Aerts, R. Mak   +13 more
semanticscholar   +1 more source

Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients - a report of the PET/RANO group.

Neuro-Oncology, 2021
The management of patients with glioma usually requires multimodality treatment including surgery, radiotherapy, and systemic therapy. Accurate neuroimaging plays a central role for radiotherapy planning and follow-up after radiotherapy completion.
N. Galldiks, M. Niyazi, A. Grosu, M. Kocher, K. Langen, I. Law, G. Minniti, Michelle M. Kim, C. Tsien, F. Dhermain, R. Soffietti, M. Mehta, M. Weller, J. Tonn   +13 more
semanticscholar   +1 more source

Identification of Risk of Cardiovascular Disease by Automatic Quantification of Coronary Artery Calcifications on Radiotherapy Planning CT Scans in Patients With Breast Cancer.

JAMA Oncology, 2021
Importance Cardiovascular disease (CVD) is common in patients treated for breast cancer, especially in patients treated with systemic treatment and radiotherapy and in those with preexisting CVD risk factors.
R. Gal, Sanne G M van Velzen, M. Hooning, M. Emaus, F. van der Leij, M. Gregorowitsch, E. Blezer, S. Gernaat, N. Lessmann, M. Sattler, T. Leiner, P. D. de Jong, A. Teske, J. Verloop, J. Penninkhof, I. Vaartjes, H. Meijer, J. J. van Tol-Geerdink, J. Pignol, D. H. van den Bongard, I. Išgum, H. Verkooijen   +21 more
semanticscholar   +1 more source

Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers

Radiation Oncology, 2021
We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes (CTV).
J. Wong, V. Huang, D. Wells, J. Giambattista, Jonathan Giambattista, C. Kolbeck, K. Otto, E. Saibishkumar, A. Alexander   +8 more
semanticscholar   +1 more source

Training and Validation of Deep Learning-Based Auto-Segmentation Models for Lung Stereotactic Ablative Radiotherapy Using Retrospective Radiotherapy Planning Contours

Frontiers in Oncology, 2021
Purpose Deep learning-based auto-segmented contour (DC) models require high quality data for their development, and previous studies have typically used prospectively produced contours, which can be resource intensive and time consuming to obtain.
J. Wong, V. Huang, J. Giambattista, T. Teke, C. Kolbeck, Jonathan Giambattista, S. Atrchian   +6 more
semanticscholar   +1 more source

Assessment of Treatment Plan Quality between Flattening Filter and Flattening Filter Free Photon Beam for Carcinoma of the Esophagus with IMRT Technique [PDF]

Journal of Biomedical Physics and Engineering, 2023
Background: As compared to the flattened photon beam, removing the flattening filter (FF) from the head of a gantry decreases the average energy of the photon beam and increases the dose rate, leading to an impact on the quality of treatment plans ...
Dinesh Kumar Saroj, Suresh Yadav, Neetu Paliwal, Subhas Haldar, Amol Jagtap, Arvind Kumar   +5 more
doaj   +1 more source

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

Cancers, 2021
Simple Summary Conventional magnetic resonance imaging (MRI) sequences have known limitations in target delineation for radiation treatment (RT) planning of cerebral gliomas.
A. Castellano, M. Bailo, F. Cicone, Luciano Carideo, N. Quartuccio, P. Mortini, A. Falini, G. Cascini, G. Minniti   +8 more
semanticscholar   +1 more source

The Impact of Dose Calculation Algorithm for SBRT Lung Cancer Radiotherapy Treatment [PDF]

Iranian Journal of Medical Physics, 2022
Introduction: The study aimed to provide the dose accuracy effects between the Anisotropic Analytical Algorithm (AAA) and the deterministic solver Acuros XB (AXB) that are available on Eclipse TPS (Varian Medical Systems, Palo Alto, CA) treatment ...
Ahmed Mostafa, Abdel Azim Hussein, Mohammed Galal, Khaled El Shahat   +3 more
doaj   +1 more source