Literature DB >> 20219546

Adaptive radiotherapy of head and neck cancer.

Pierre Castadot1, John A Lee, Xavier Geets, Vincent Grégoire.   

Abstract

Intensity-modulated radiation therapy (IMRT) in head and neck (H&N) cancer has the capability to generate steep dose gradients, leading to an improved therapeutic index. IMRT plans are typically based on a pretreatment computed tomography scan that provides a snapshot of the patient's anatomy. Nevertheless, interfractional patient variations may occur because of setup error and anatomical modifications. Therefore, the accuracy of IMRT delivery for H&N cancer may be compromised during the treatment course, potentially affecting the therapeutic index. In this framework, adaptive radiotherapy is a potential solution, which consists of "the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy." Adaptive radiotherapy has brought an additional dimension to the management of patients with H&N cancer and has the potential to counteract the effects of positioning errors and anatomical changes. This article reviews the causes and discusses potential solutions to circumvent the discrepancies between the planned dose and the actual dose received by patients treated for H&N malignancies. Copyright 2010 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20219546     DOI: 10.1016/j.semradonc.2009.11.002

Source DB:  PubMed          Journal:  Semin Radiat Oncol        ISSN: 1053-4296            Impact factor:   5.934


  51 in total

1.  Influence of the type of imaging on the delineation process during the treatment planning.

Authors:  Weronika Jackowiak; Bartosz Bąk; Anna Kowalik; Adam Ryczkowski; Małgorzata Skórska; Małgorzata Paszek-Widzińska
Journal:  Rep Pract Oncol Radiother       Date:  2015-06-18

2.  Automatic large quantity landmark pairs detection in 4DCT lung images.

Authors:  Yabo Fu; Xue Wu; Allan M Thomas; Harold H Li; Deshan Yang
Journal:  Med Phys       Date:  2019-08-07       Impact factor: 4.071

Review 3.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

4.  Strategies to optimize radiotherapy based on biological responses of tumor and normal tissue.

Authors:  Weidong Wang; Jinyi Lang
Journal:  Exp Ther Med       Date:  2012-05-30       Impact factor: 2.447

5.  Volumetric change of human papillomavirus-related neck lymph nodes before, during, and shortly after intensity-modulated radiation therapy.

Authors:  Giuseppe Sanguineti; Francesco Ricchetti; Binbin Wu; Nishant Agrawal; Christine Gourin; Harold Agbahiwe; Shanthi Marur; Stefania Clemente; Todd McNutt; Arlene Forastiere
Journal:  Head Neck       Date:  2012-01-20       Impact factor: 3.147

6.  Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

Authors:  J Neylon; Y Min; P Kupelian; D A Low; A Santhanam
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-08-25       Impact factor: 2.924

Review 7.  Head and Neck Cancer Adaptive Radiation Therapy (ART): Conceptual Considerations for the Informed Clinician.

Authors:  Jolien Heukelom; Clifton David Fuller
Journal:  Semin Radiat Oncol       Date:  2019-07       Impact factor: 5.934

8.  Clinical outcomes of adaptive radiotherapy in head and neck cancers.

Authors:  Tejinder Kataria; Deepak Gupta; Shikha Goyal; Shyam S Bisht; Trinanjan Basu; Ashu Abhishek; Kushal Narang; Susovan Banerjee; Shahida Nasreen; Sasikumar Sambasivam; Aruj Dhyani
Journal:  Br J Radiol       Date:  2016-03-17       Impact factor: 3.039

Review 9.  The physical basis and future of radiation therapy.

Authors:  T Bortfeld; R Jeraj
Journal:  Br J Radiol       Date:  2011-06       Impact factor: 3.039

10.  The tumor shape changes of nasopharyngeal cancer during chemoradiotherapy: the estimated margin to cover the geometrical variation.

Authors:  Wenyong Tan; Jianzeng Ye; Ruilian Xu; Xianming Li; Wan He; Xiaohong Wang; Yanping Li; Desheng Hu
Journal:  Quant Imaging Med Surg       Date:  2016-04
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