Literature DB >> 28932174

Internet-based computer technology on radiotherapy.

James C L Chow1.   

Abstract

Recent rapid development of Internet-based computer technologies has made possible many novel applications in radiation dose delivery. However, translational speed of applying these new technologies in radiotherapy could hardly catch up due to the complex commissioning process and quality assurance protocol. Implementing novel Internet-based technology in radiotherapy requires corresponding design of algorithm and infrastructure of the application, set up of related clinical policies, purchase and development of software and hardware, computer programming and debugging, and national to international collaboration. Although such implementation processes are time consuming, some recent computer advancements in the radiation dose delivery are still noticeable. In this review, we will present the background and concept of some recent Internet-based computer technologies such as cloud computing, big data processing and machine learning, followed by their potential applications in radiotherapy, such as treatment planning and dose delivery. We will also discuss the current progress of these applications and their impacts on radiotherapy. We will explore and evaluate the expected benefits and challenges in implementation as well.

Keywords:  Big data; Cloud computing; Computer technology; Machine learning; Radiotherapy

Year:  2017        PMID: 28932174      PMCID: PMC5596257          DOI: 10.1016/j.rpor.2017.08.005

Source DB:  PubMed          Journal:  Rep Pract Oncol Radiother        ISSN: 1507-1367


  36 in total

1.  Picture archiving and communication systems.

Authors:  R L Arenson
Journal:  West J Med       Date:  1992-03

2.  Toward a web-based real-time radiation treatment planning system in a cloud computing environment.

Authors:  Yong Hum Na; Tae-Suk Suh; Daniel S Kapp; Lei Xing
Journal:  Phys Med Biol       Date:  2013-09-03       Impact factor: 3.609

Review 3.  Advances and future of Radiation Oncology.

Authors:  Carlos A Perez; Sasa Mutic
Journal:  Rep Pract Oncol Radiother       Date:  2013-11-08

4.  Introduction to Big Data in Radiation Oncology: Exploring Opportunities for Research, Quality Assessment, and Clinical Care.

Authors:  Stanley H Benedict; Issam El Naqa; Eric E Klein
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-07-01       Impact factor: 7.038

5.  A machine learning approach to the accurate prediction of multi-leaf collimator positional errors.

Authors:  Joel N K Carlson; Jong Min Park; So-Yeon Park; Jong In Park; Yunseok Choi; Sung-Joon Ye
Journal:  Phys Med Biol       Date:  2016-03-07       Impact factor: 3.609

Review 6.  GPU-based high-performance computing for radiation therapy.

Authors:  Xun Jia; Peter Ziegenhein; Steve B Jiang
Journal:  Phys Med Biol       Date:  2014-02-03       Impact factor: 3.609

7.  Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

Authors:  Henry Wang; Yunzhi Ma; Guillem Pratx; Lei Xing
Journal:  Phys Med Biol       Date:  2011-08-12       Impact factor: 3.609

8.  Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods.

Authors:  Noorazrul Yahya; Martin A Ebert; Max Bulsara; Michael J House; Angel Kennedy; David J Joseph; James W Denham
Journal:  Med Phys       Date:  2016-05       Impact factor: 4.071

Review 9.  Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets.

Authors:  Tomas Skripcak; Claus Belka; Walter Bosch; Carsten Brink; Thomas Brunner; Volker Budach; Daniel Büttner; Jürgen Debus; Andre Dekker; Cai Grau; Sarah Gulliford; Coen Hurkmans; Uwe Just; Mechthild Krause; Philippe Lambin; Johannes A Langendijk; Rolf Lewensohn; Armin Lühr; Philippe Maingon; Michele Masucci; Maximilian Niyazi; Philip Poortmans; Monique Simon; Heinz Schmidberger; Emiliano Spezi; Martin Stuschke; Vincenzo Valentini; Marcel Verheij; Gillian Whitfield; Björn Zackrisson; Daniel Zips; Michael Baumann
Journal:  Radiother Oncol       Date:  2014-10-28       Impact factor: 6.280

Review 10.  Big Data Analytics for Prostate Radiotherapy.

Authors:  James Coates; Luis Souhami; Issam El Naqa
Journal:  Front Oncol       Date:  2016-06-14       Impact factor: 6.244

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  1 in total

1.  Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

Authors:  Xudong Xue; Yi Ding; Jun Shi; Xiaoyu Hao; Xiangbin Li; Dan Li; Yuan Wu; Hong An; Man Jiang; Wei Wei; Xiao Wang
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  1 in total

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