Literature DB >> 32843739

Artificial intelligence in radiation oncology.

Elizabeth Huynh1,2, Ahmed Hosny1,2, Christian Guthier2, Danielle S Bitterman1,2,3, Steven F Petit4, Daphne A Haas-Kogan1,2, Benjamin Kann1,2, Hugo J W L Aerts5,6,7,8, Raymond H Mak1,2.   

Abstract

Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised. AI platforms excel in recognizing complex patterns in medical data and provide a quantitative, rather than purely qualitative, assessment of clinical conditions. Accordingly, AI could have particularly transformative applications in radiation oncology given the multifaceted and highly technical nature of this field of medicine with a heavy reliance on digital data processing and computer software. Indeed, AI has the potential to improve the accuracy, precision, efficiency and overall quality of radiation therapy for patients with cancer. In this Perspective, we first provide a general description of AI methods, followed by a high-level overview of the radiation therapy workflow with discussion of the implications that AI is likely to have on each step of this process. Finally, we describe the challenges associated with the clinical development and implementation of AI platforms in radiation oncology and provide our perspective on how these platforms might change the roles of radiotherapy medical professionals.

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Year:  2020        PMID: 32843739     DOI: 10.1038/s41571-020-0417-8

Source DB:  PubMed          Journal:  Nat Rev Clin Oncol        ISSN: 1759-4774            Impact factor:   66.675


  109 in total

1.  The role of radiotherapy in cancer treatment: estimating optimal utilization from a review of evidence-based clinical guidelines.

Authors:  Geoff Delaney; Susannah Jacob; Carolyn Featherstone; Michael Barton
Journal:  Cancer       Date:  2005-09-15       Impact factor: 6.860

2.  A historical perspective of the radiation oncology workforce and ongoing initiatives to affect recruitment and retention.

Authors:  John J Kresl; Roshunda L Drummond
Journal:  J Am Coll Radiol       Date:  2004-09       Impact factor: 5.532

3.  Critical impact of radiotherapy protocol compliance and quality in the treatment of advanced head and neck cancer: results from TROG 02.02.

Authors:  Lester J Peters; Brian O'Sullivan; Jordi Giralt; Thomas J Fitzgerald; Andy Trotti; Jacques Bernier; Jean Bourhis; Kally Yuen; Richard Fisher; Danny Rischin
Journal:  J Clin Oncol       Date:  2010-05-17       Impact factor: 44.544

Review 4.  Knowledge-based computer systems for radiotherapy planning.

Authors:  I J Kalet; W Paluszynski
Journal:  Am J Clin Oncol       Date:  1990-08       Impact factor: 2.339

Review 5.  Applications of data bases and AI/expert systems in radiation therapy.

Authors:  G E Laramore; M D Altschuler; G Banks; I J Kalet; T F Pajak; T E Schultheiss; S Zink
Journal:  Am J Clin Oncol       Date:  1988-06       Impact factor: 2.339

6.  Radiation Therapy Quality Assurance (RTQA) of Concurrent Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer in the PROCLAIM Phase 3 Trial.

Authors:  Anthony M Brade; Frederik Wenz; Friederike Koppe; Yolande Lievens; Belen San Antonio; Neill A Iscoe; Anwar Hossain; Nadia Chouaki; Suresh Senan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-04-12       Impact factor: 7.038

7.  Supply and Demand for Radiation Oncology in the United States: Updated Projections for 2015 to 2025.

Authors:  Hubert Y Pan; Bruce G Haffty; Benjamin P Falit; Thomas A Buchholz; Lynn D Wilson; Stephen M Hahn; Benjamin D Smith
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-03-05       Impact factor: 7.038

Review 8.  Expanding global access to radiotherapy.

Authors:  Rifat Atun; David A Jaffray; Michael B Barton; Freddie Bray; Michael Baumann; Bhadrasain Vikram; Timothy P Hanna; Felicia M Knaul; Yolande Lievens; Tracey Y M Lui; Michael Milosevic; Brian O'Sullivan; Danielle L Rodin; Eduardo Rosenblatt; Jacob Van Dyk; Mei Ling Yap; Eduardo Zubizarreta; Mary Gospodarowicz
Journal:  Lancet Oncol       Date:  2015-09       Impact factor: 41.316

9.  Cancer treatment and survivorship statistics, 2016.

Authors:  Kimberly D Miller; Rebecca L Siegel; Chun Chieh Lin; Angela B Mariotto; Joan L Kramer; Julia H Rowland; Kevin D Stein; Rick Alteri; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2016-06-02       Impact factor: 508.702

10.  A systematic review of radiotherapy capacity in low- and middle-income countries.

Authors:  Surbhi Grover; Melody J Xu; Alyssa Yeager; Lori Rosman; Reinou S Groen; Smita Chackungal; Danielle Rodin; Margaret Mangaali; Sommer Nurkic; Annemarie Fernandes; Lilie L Lin; Gillian Thomas; Ana I Tergas
Journal:  Front Oncol       Date:  2015-01-22       Impact factor: 6.244

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  35 in total

1.  Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer.

Authors:  Yuan Cheng; Yahong Luo; Yue Hu; Zhaohe Zhang; Xingling Wang; Qing Yu; Guanyu Liu; Enuo Cui; Tao Yu; Xiran Jiang
Journal:  Abdom Radiol (NY)       Date:  2021-07-24

Review 2.  Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians.

Authors:  William A Hall; Eric Paulson; X Allen Li; Beth Erickson; Christopher Schultz; Alison Tree; Musaddiq Awan; Daniel A Low; Brigid A McDonald; Travis Salzillo; Carri K Glide-Hurst; Amar U Kishan; Clifton D Fuller
Journal:  CA Cancer J Clin       Date:  2021-11-18       Impact factor: 508.702

3.  Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas.

Authors:  Thibault Marin; Yue Zhuo; Rita Maria Lahoud; Fei Tian; Xiaoyue Ma; Fangxu Xing; Maryam Moteabbed; Xiaofeng Liu; Kira Grogg; Nadya Shusharina; Jonghye Woo; Ruth Lim; Chao Ma; Yen-Lin E Chen; Georges El Fakhri
Journal:  Radiother Oncol       Date:  2021-11-19       Impact factor: 6.280

Review 4.  Machine learning in neuro-oncology: toward novel development fields.

Authors:  Vincenzo Di Nunno; Mario Fordellone; Giuseppe Minniti; Sofia Asioli; Alfredo Conti; Diego Mazzatenta; Damiano Balestrini; Paolo Chiodini; Raffaele Agati; Caterina Tonon; Alicia Tosoni; Lidia Gatto; Stefania Bartolini; Raffaele Lodi; Enrico Franceschi
Journal:  J Neurooncol       Date:  2022-06-28       Impact factor: 4.506

5.  Artificial Intelligence in Radiation Therapy.

Authors:  Yabo Fu; Hao Zhang; Eric D Morris; Carri K Glide-Hurst; Suraj Pai; Alberto Traverso; Leonard Wee; Ibrahim Hadzic; Per-Ivar Lønne; Chenyang Shen; Tian Liu; Xiaofeng Yang
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2021-08-24

Review 6.  Evolving Concepts Regarding Radiation Therapy for Pancreatic Cancer.

Authors:  William A Hall; Beth Erickson; Christopher H Crane
Journal:  Surg Oncol Clin N Am       Date:  2021-10       Impact factor: 2.402

Review 7.  The future of MRI in radiation therapy: Challenges and opportunities for the MR community.

Authors:  Rosie J Goodburn; Marielle E P Philippens; Thierry L Lefebvre; Aly Khalifa; Tom Bruijnen; Joshua N Freedman; David E J Waddington; Eyesha Younus; Eric Aliotta; Gabriele Meliadò; Teo Stanescu; Wajiha Bano; Ali Fatemi-Ardekani; Andreas Wetscherek; Uwe Oelfke; Nico van den Berg; Ralph P Mason; Petra J van Houdt; James M Balter; Oliver J Gurney-Champion
Journal:  Magn Reson Med       Date:  2022-09-21       Impact factor: 3.737

8.  An Artificial Intelligence System for the Detection of Bladder Cancer via Cystoscopy: A Multicenter Diagnostic Study.

Authors:  Shaoxu Wu; Xiong Chen; Jiexin Pan; Wen Dong; Xiayao Diao; Ruiyun Zhang; Yonghai Zhang; Yuanfeng Zhang; Guang Qian; Hao Chen; Haotian Lin; Shizhong Xu; Zhiwen Chen; Xiaozhou Zhou; Hongbing Mei; Chenglong Wu; Qiang Lv; Baorui Yuan; Zeshi Chen; Wenjian Liao; Xuefan Yang; Haige Chen; Jian Huang; Tianxin Lin
Journal:  J Natl Cancer Inst       Date:  2022-02-07       Impact factor: 11.816

Review 9.  Requirements and reliability of AI in the medical context.

Authors:  Yoganand Balagurunathan; Ross Mitchell; Issam El Naqa
Journal:  Phys Med       Date:  2021-03-13       Impact factor: 2.685

Review 10.  Application of artificial intelligence-driven endoscopic screening and diagnosis of gastric cancer.

Authors:  Yu-Jer Hsiao; Yuan-Chih Wen; Wei-Yi Lai; Yi-Ying Lin; Yi-Ping Yang; Yueh Chien; Aliaksandr A Yarmishyn; De-Kuang Hwang; Tai-Chi Lin; Yun-Chia Chang; Ting-Yi Lin; Kao-Jung Chang; Shih-Hwa Chiou; Ying-Chun Jheng
Journal:  World J Gastroenterol       Date:  2021-06-14       Impact factor: 5.742

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