Literature DB >> 25160607

Automation and intensity modulated radiation therapy for individualized high-quality tangent breast treatment plans.

Thomas G Purdie1, Robert E Dinniwell2, Anthony Fyles2, Michael B Sharpe3.   

Abstract

PURPOSE: To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). METHODS AND MATERIALS: Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to define and simplify the technical aspects of the treatment planning process.
RESULTS: Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method.
CONCLUSIONS: Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented improvements in care for breast cancer patients, using technologies that are widely available and already in clinical use.
Copyright © 2014 Elsevier Inc. All rights reserved.

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Mesh:

Year:  2014        PMID: 25160607     DOI: 10.1016/j.ijrobp.2014.06.056

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  22 in total

Review 1.  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

2.  Technology for Innovation in Radiation Oncology.

Authors:  Indrin J Chetty; Mary K Martel; David A Jaffray; Stanley H Benedict; Stephen M Hahn; Ross Berbeco; James Deye; Robert Jeraj; Brian Kavanagh; Sunil Krishnan; Nancy Lee; Daniel A Low; David Mankoff; Lawrence B Marks; Daniel Ollendorf; Harald Paganetti; Brian Ross; Ramon Alfredo C Siochi; Robert D Timmerman; John W Wong
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-07-11       Impact factor: 7.038

3.  Predicting 3D dose distribution with scale attention network for prostate cancer radiotherapy.

Authors:  Saba Adabi; Tzu-Chi Tsen; Yading Yuan
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

4.  Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy.

Authors:  Pier Giorgio Esposito; Roberta Castriconi; Paola Mangili; Sara Broggi; Andrei Fodor; Marcella Pasetti; Alessia Tudda; Nadia Gisella Di Muzio; Antonella Del Vecchio; Claudio Fiorino
Journal:  Phys Imaging Radiat Oncol       Date:  2022-06-23

5.  Improving the efficiency of breast radiotherapy treatment planning using a semi-automated approach.

Authors:  Robert A Mitchell; Philip Wai; Ruth Colgan; Anna M Kirby; Ellen M Donovan
Journal:  J Appl Clin Med Phys       Date:  2016-11-30       Impact factor: 2.102

6.  Dosimetric evaluation of deep inspiration breath hold for left-sided breast cancer: analysis of patient-specific parameters related to heart dose reduction.

Authors:  Ryohei Yamauchi; Norifumi Mizuno; Tomoko Itazawa; Hidetoshi Saitoh; Jiro Kawamori
Journal:  J Radiat Res       Date:  2020-05-22       Impact factor: 2.724

7.  Dosimetric analysis of tangent-based volumetric modulated arc therapy with deep inspiration breath-hold technique for left breast cancer patients.

Authors:  Pei-Chieh Yu; Ching-Jung Wu; Yu-Lun Tsai; Suzun Shaw; Shih-Yu Sung; Louis Tak Lui; Hsin-Hua Nien
Journal:  Radiat Oncol       Date:  2018-11-26       Impact factor: 3.481

8.  Goal-Driven Beam Setting Optimization for Whole-Breast Radiation Therapy.

Authors:  Wentao Wang; Yang Sheng; Sua Yoo; Rachel C Blitzblau; Fang-Fang Yin; Q Jackie Wu
Journal:  Technol Cancer Res Treat       Date:  2019-01-01

9.  Automatic Planning of Whole Breast Radiation Therapy Using Machine Learning Models.

Authors:  Yang Sheng; Taoran Li; Sua Yoo; Fang-Fang Yin; Rachel Blitzblau; Janet K Horton; Yaorong Ge; Q Jackie Wu
Journal:  Front Oncol       Date:  2019-08-07       Impact factor: 6.244

10.  Evaluation of an automated knowledge based treatment planning system for head and neck.

Authors:  Jerome Krayenbuehl; Ian Norton; Gabriela Studer; Matthias Guckenberger
Journal:  Radiat Oncol       Date:  2015-11-10       Impact factor: 3.481

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