Literature DB >> 30576843

Standardizing Normal Tissue Contouring for Radiation Therapy Treatment Planning: An ASTRO Consensus Paper.

Jean L Wright1, Sue S Yom2, Musaddiq J Awan3, Samantha Dawes4, Benjamin Fischer-Valuck5, Randi Kudner6, Raymond Mailhot Vega7, George Rodrigues8.   

Abstract

PURPOSE: The comprehensive identification and delineation of organs at risk (OARs) are vital to the quality of radiation therapy treatment planning and the safety of treatment delivery. This guidance aims to improve the consistency of ontouring OARs in external beam radiation therapy treatment planning by providing a single standardized resource for information regarding specific OARs to be contoured for each disease site. The guidance is organized in table format as a quality assurance tool for practices and a training resource for residents and other radiation oncology students (see supplementary materials). METHODS AND MATERIALS: The Task Force formulated recommendations based on clinical practice and consensus. The draft manuscript was peer reviewed by 16 reviewers, the American Society for Radiation Oncology (ASTRO) legal counsel, and ASTRO's Multidisciplinary Quality Assurance Subcommittee and revised accordingly. The recommendations were posted on the ASTRO website for public comment in June 2018 for a 6-week period. The final document was approved by the ASTRO Board of Directors in August 2018.
RESULTS: Standardization improves patient safety, efficiency, and accuracy in radiation oncology treatment. This consensus guidance represents an ASTRO quality initiative to provide recommendations for the standardization of normal tissue contouring that is performed during external beam treatment planning for each anatomic treatment site. Table 1 defines 2 sets of structures for anatomic sites: Those that are recommended in all adult definitive cases and may assist with organ selection for palliative cases, and those that should be considered on a case-by-case basis depending on the specific clinical scenario. Table 2 outlines some of the resources available to define the parameters of general OAR tissue delineation.
CONCLUSIONS: Using this paper in conjunction with resources that define tissue parameters and published dose constraints will enable practices to develop a consistent approach to normal tissue evaluation and dose documentation.
Copyright © 2018 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2018        PMID: 30576843     DOI: 10.1016/j.prro.2018.12.003

Source DB:  PubMed          Journal:  Pract Radiat Oncol        ISSN: 1879-8500


  10 in total

Review 1.  Artificial intelligence in radiation oncology.

Authors:  Elizabeth Huynh; Ahmed Hosny; Christian Guthier; Danielle S Bitterman; Steven F Petit; Daphne A Haas-Kogan; Benjamin Kann; Hugo J W L Aerts; Raymond H Mak
Journal:  Nat Rev Clin Oncol       Date:  2020-08-25       Impact factor: 66.675

2.  General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis.

Authors:  Asma Amjad; Jiaofeng Xu; Dan Thill; Colleen Lawton; William Hall; Musaddiq J Awan; Monica Shukla; Beth A Erickson; X Allen Li
Journal:  Med Phys       Date:  2022-02-07       Impact factor: 4.071

3.  Image-based data mining applies to data collected from children.

Authors:  Lydia J Wilson; Abigail Bryce-Atkinson; Andrew Green; Yimei Li; Thomas E Merchant; Marcel van Herk; Eliana Vasquez Osorio; Austin M Faught; Marianne C Aznar
Journal:  Phys Med       Date:  2022-05-21       Impact factor: 3.119

4.  An Evaluation of Health Numeracy among Radiation Therapists and Dosimetrists.

Authors:  Gabrielle W Peters; Jacqueline R Kelly; Jason M Beckta; Marney White; Lawrence B Marks; Eric Ford; Suzanne B Evans
Journal:  Adv Radiat Oncol       Date:  2020-11-03

5.  A first radiotherapy application of functional bulboclitoris anatomy, a novel female sexual organ-at-risk, and organ-sparing feasibility study.

Authors:  Deborah C Marshall; Zahra Ghiassi-Nejad; Allison Powers; Joy S Reidenberg; Pamela Argiriadi; Meng Ru; Vishruta Dumane; Michael Buckstein; Karyn Goodman; Stephanie V Blank; Julie Schnur; Barry Rosenstein
Journal:  Br J Radiol       Date:  2021-06-30       Impact factor: 3.629

6.  Initial experience with introducing national guidelines for CT- and MRI-based delineation of organs at risk in radiotherapy.

Authors:  Caroline Olsson; Tufve Nyholm; Elinore Wieslander; Eva Onjukka; Adalsteinn Gunnlaugsson; Johan Reizenstein; Stefan Johnsson; Ingrid Kristensen; Johan Skönevik; Magnus Karlsson; Ulf Isacsson; Anna Flejmer; Edvard Abel; Fredrik Nordström; Leif Nyström; Kjell Bergfeldt; Björn Zackrisson; Alexander Valdman
Journal:  Phys Imaging Radiat Oncol       Date:  2019-09-23

7.  Estimation of planning organ at risk volumes for ocular structures in dogs undergoing three-dimensional image-guided periocular radiotherapy with rigid bite block immobilization.

Authors:  Friederike Wolf; Carla Rohrer Bley; Jürgen Besserer; Valeria Meier
Journal:  Vet Radiol Ultrasound       Date:  2021-01-18       Impact factor: 1.363

8.  Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy.

Authors:  Hwa Kyung Byun; Jee Suk Chang; Min Seo Choi; Jaehee Chun; Jinhong Jung; Chiyoung Jeong; Jin Sung Kim; Yongjin Chang; Seung Yeun Chung; Seungryul Lee; Yong Bae Kim
Journal:  Radiat Oncol       Date:  2021-10-14       Impact factor: 3.481

9.  Acknowledge uncertainties.

Authors:  Per H Halvorsen
Journal:  J Appl Clin Med Phys       Date:  2020-10-01       Impact factor: 2.102

10.  Physician review of image registration and normal structure delineation.

Authors:  William Tyler Turchan; Ritu Arya; Robert Hight; Hania Al-Hallaq; Michael Dominello; Dan Joyce; Bradley P McCabe; Anne R McCall; Eugenia Perevalova; Christopher Stepaniak; Kamil Yenice; Jay Burmeister; Daniel W Golden
Journal:  J Appl Clin Med Phys       Date:  2020-09-28       Impact factor: 2.243

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.