Results 11 to 20 of about 4,548,445 (364)

Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss. [PDF]

Nat Commun, 2023
Brain tumor growth is unique to each glioma patient and extends beyond what is visible in imaging scans, infiltrating surrounding brain tissue. Understanding these hidden patient-specific progressions is essential for effective therapies.
Balcerak M, Weidner J, Karnakov P, Ezhov I, Litvinov S, Koumoutsakos P, Amiranashvili T, Zhang RZ, Lowengrub JS, Yakushev I, Wiestler B, Menze B.   +11 more
europepmc   +2 more sources

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

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

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

Effectiveness of Multi-Criteria Optimization-based Trade-Off exploration in combination with RapidPlan for head & neck radiotherapy planning [PDF]

Radiation Oncology, 2018
A new strategy is introduced combining the use of Multi-Criteria Optimization-based Trade-Off Exploration (TO) and RapidPlan™ (RP) for the selection of optimisation parameters that improve the trade-off between sparing of organs at risk (OAR) and target ...
Eliane Miguel-Chumacero, Garry Currie, Abigail Johnston, Suzanne Currie   +3 more
openalex   +2 more sources

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

MRI-Only Radiotherapy Planning for Nasopharyngeal Carcinoma Using Deep Learning

Frontiers in Oncology, 2021
Background Radical radiotherapy is the main treatment modality for early and locally advanced nasopharyngeal carcinoma (NPC). Magnetic resonance imaging (MRI) has the advantages of no ionizing radiation and high soft-tissue resolution compared to ...
Xiangyu Ma, Xinyuan Chen, Jingwen Li, Yu Wang, K. Men, J. Dai   +5 more
semanticscholar   +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

Comparison of Volumetric Quantitative PET Parameters Before and After a CT-Based Elastic Deformation on Dual-Time 18FDG-PET/CT Images: A Feasibility Study in a Perspective of Radiotherapy Planning in Head and Neck Cancer

Frontiers in Medicine, 2022
BackgroundThe use of 18FDG-PET/CT for delineating a gross tumor volume (GTV, also called MTV metabolic tumor volume) in radiotherapy (RT) planning of head neck squamous cell carcinomas (HNSCC) is not included in current recommendations, although its ...
Meriem Maajem, Jean-Christophe Leclère, David Bourhis, David Bourhis, Valentin Tissot, Nicolas Icard, Laëtitia Arnaud, Romain Le Pennec, Romain Le Pennec, Gurvan Dissaux, Dorothy M. Gujral, Dorothy M. Gujral, Pierre-Yves Salaün, Pierre-Yves Salaün, Ulrike Schick, Ronan Abgral, Ronan Abgral   +16 more
doaj   +1 more source