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Abdel-Wahab M, Coleman CN, Eriksen JG, Lee P, Kraus R, Harsdorf E, Lee B, Dicker A, Hahn E, Agarwal JP, Prasanna PGS, MacManus M, Keall P, Mayr NA, Jereczek-Fossa BA, Giammarile F, Kim IA, Aggarwal A, Lewison G, Lu JJ, Guedes de Castro D, Kong FMS, Afifi H, Sharp H, Vanderpuye V, Olasinde T, Atrash F, Goethals L, Corn BW. Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities. Lancet Oncol 2024; 25:e270-e280. [PMID: 38821101 DOI: 10.1016/s1470-2045(24)00038-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 06/02/2024]
Abstract
Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.
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Affiliation(s)
- May Abdel-Wahab
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria.
| | - C Norman Coleman
- Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jesper Grau Eriksen
- Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark
| | - Peter Lee
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria
| | - Ryan Kraus
- Department of Radiation Oncology, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Ekaterina Harsdorf
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria
| | - Becky Lee
- Department of Radiation Medicine, Loma Linda University, Loma Linda, CA, USA; Department of Radiation Oncology, Summa Health, Akron, OH, USA
| | - Adam Dicker
- Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Ezra Hahn
- Department of Radiation Oncology, Radiation Medicine Program, Princess Margaret Cancer Centre, University of Toronto, ON, Canada
| | - Jai Prakash Agarwal
- Department of Radiation Oncology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
| | - Pataje G S Prasanna
- Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael MacManus
- Department of Radiation Oncology, Peter MacCallum Cancer Centre and the Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Paul Keall
- Image X Institute, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Nina A Mayr
- College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Barbara Alicja Jereczek-Fossa
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy; Division of Radiotherapy, European Institute of Oncology, IRCCS, Milan, Italy
| | | | - In Ah Kim
- Department of Radiation Oncology, Seoul National University Bundang Hospital, Seoul, South Korea; Seoul National University, College of Medicine, Seoul, South Korea
| | - Ajay Aggarwal
- Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK; Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Grant Lewison
- Institute of Cancer Policy, King's College London, London, UK
| | - Jiade J Lu
- Shanghai Proton and Heavy Ion Centre, Fudan University School of Medicine, Shanghai, China
| | | | - Feng-Ming Spring Kong
- Department of Clinical Oncology, HKU-Shenzhen Hospital and Queen Mary Hospital, Li Ka Shing Faculty of Medicine, Hong Kong Special Administrative Region, China
| | - Haidy Afifi
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria
| | - Hamish Sharp
- Institute of Cancer Policy, King's College London, London, UK
| | - Verna Vanderpuye
- National Center for Radiotherapy, Oncology and Nuclear Medicine, Korlebu Teaching Hospital, Accra, Ghana
| | | | - Fadi Atrash
- Augusta Victoria Hospital, Jerusalem, Israel
| | - Luc Goethals
- Division of Human Health, International Atomic Energy Agency, Vienna, Austria
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Komakech I, Okello D, Kavuma A, Orem J, Tagoe SNA, Wygoda A. Errors in manual radiotherapy treatment procedures and their evolution in a low resource setting: Uganda's experience. Phys Med 2024; 118:103212. [PMID: 38219559 DOI: 10.1016/j.ejmp.2024.103212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 12/05/2023] [Accepted: 01/04/2024] [Indexed: 01/16/2024] Open
Abstract
PURPOSE In Uganda, two-dimensional (2D) radiotherapy treatments have been in use since the establishment of radiotherapy in 1995. Preliminary investigations of treatment records in November 2019 showed evidence of gaps requiring urgent attention. The purpose of this study was to improve the safety of the treatments. METHODS Records of 1164 patients treated in 1387 courses (1412 sites) on Cobalt-60 units were reviewed todetermine the frequency and dosimetric implications of events that occurred at different stepsof the radiotherapy process. The results were presented and discussed with the differentprofessionals for learning purposes. RESULTS Most common dosimetric eventswere omission of block tray, bolus and couch transmission factors in time calculations, incorrect field sizes and depths, wrong beam weighting, independent calculations and prescription doses contributing 28.6 %, 10.1 %, 6.0 %,11.9 %, 10.1 %, 5.4 %, 4.8 % and 8.9 % to the 168 observed errors. Comparison of the calculated treatment doses with the prescribed doses showed that 88 % of the 1412 sites were treated with radiation doses within an accuracy of ± 5 %. However, an analysis of the evolution along the years demonstrated an improvement from 82.8 % in 2018 to 86.1 % in 2019, and 93.2 % in 2020. Most common procedural events were incomplete setup instructions and missing patient data in the record and verify system of the Co-60 units for 57 % and 60.1 % of the 1164 patients. CONCLUSIONS Opportunities for improvement of safety in the delivery of radiotherapy treatments were identified. Learning from these past errors should raise awareness in the team leading to a safer treatments.
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Affiliation(s)
- Ignatius Komakech
- Radiation Oncology Division, Uganda Cancer Institute, P.O. Box 3935, Kampala, Uganda; Department of Physics, Makerere University, P.O. Box 7062, Kampala, Uganda.
| | - Denis Okello
- Department of Physics, Makerere University, P.O. Box 7062, Kampala, Uganda
| | - Awusi Kavuma
- Radiation Oncology Division, Uganda Cancer Institute, P.O. Box 3935, Kampala, Uganda
| | - Jackson Orem
- Radiation Oncology Division, Uganda Cancer Institute, P.O. Box 3935, Kampala, Uganda
| | - Samuel Nii Adu Tagoe
- Department of Radiation Oncology, National Centre for Radiotherapy and Nuclear Medicine, Korle-Bu Teaching Hospital, Guggisberg Avenue, Korle-Bu, Accra, Ghana; Department of Radiography, School of Biomedical and Allied Health Sciences, University of Ghana, P.O. Box LG 25, Legon, Accra, Ghana
| | - Annette Wygoda
- Medical Technology, Health Information and Research Directorate, Ministry of Health P.O. Box 1176 Jerusalem, Israel
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Yang Z, Noble DJ, Shelley L, Berger T, Jena R, McLaren DB, Burnet NG, Nailon WH. Machine-learning with region-level radiomic and dosimetric features for predicting radiotherapy-induced rectal toxicities in prostate cancer patients. Radiother Oncol 2023; 183:109593. [PMID: 36870609 DOI: 10.1016/j.radonc.2023.109593] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 01/27/2023] [Accepted: 02/24/2023] [Indexed: 03/06/2023]
Abstract
BACKGROUND AND PURPOSE This study aims to build machine learning models to predict radiation-induced rectal toxicities for three clinical endpoints and explore whether the inclusion of radiomic features calculated on radiotherapy planning computerised tomography (CT) scans combined with dosimetric features can enhance the prediction performance. MATERIALS AND METHODS 183 patients recruited to the VoxTox study (UK-CRN-ID-13716) were included. Toxicity scores were prospectively collected after 2 years with grade ≥ 1 proctitis, haemorrhage (CTCAEv4.03); and gastrointestinal (GI) toxicity (RTOG) recorded as the endpoints of interest. The rectal wall on each slice was divided into 4 regions according to the centroid, and all slices were divided into 4 sections to calculate region-level radiomic and dosimetric features. The patients were split into a training set (75%, N = 137) and a test set (25%, N = 46). Highly correlated features were removed using four feature selection methods. Individual radiomic or dosimetric or combined (radiomic + dosimetric) features were subsequently classified using three machine learning classifiers to explore their association with these radiation-induced rectal toxicities. RESULTS The test set area under the curve (AUC) values were 0.549, 0.741 and 0.669 for proctitis, haemorrhage and GI toxicity prediction using radiomic combined with dosimetric features. The AUC value reached 0.747 for the ensembled radiomic-dosimetric model for haemorrhage. CONCLUSIONS Our preliminary results show that region-level pre-treatment planning CT radiomic features have the potential to predict radiation-induced rectal toxicities for prostate cancer. Moreover, when combined with region-level dosimetric features and using ensemble learning, the model prediction performance slightly improved.
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Affiliation(s)
- Zhuolin Yang
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK; School of Engineering, The University of Edinburgh, The King's Buildings, Mayfield Road, Edinburgh EH9 3JL, UK.
| | - David J Noble
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK; Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Leila Shelley
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Thomas Berger
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Raj Jena
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Duncan B McLaren
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK; Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Neil G Burnet
- The Christie NHS Foundation Trust, Manchester M20 4BX, UK
| | - William H Nailon
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK; School of Engineering, The University of Edinburgh, The King's Buildings, Mayfield Road, Edinburgh EH9 3JL, UK; School of Science and Engineering, The University of Dundee, Dundee DD1 4HN, UK
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Roos D. Research culture in Australian and New Zealand radiation oncology: Fact or fantasy? J Med Imaging Radiat Oncol 2023. [PMID: 37141455 DOI: 10.1111/1754-9485.13530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/30/2023] [Indexed: 05/06/2023]
Abstract
INTRODUCTION Fostering a research culture is a key goal of the Royal Australian and New Zealand College of Radiologists, yet there has never been an organization-wide enquiry into the extent to which this is being realized. The purpose of this work was to address that deficit for the Radiation Oncology (RO) Faculty to serve as a baseline for future comparison. The hypothesis was that such a culture is closer to fact than fantasy. METHODS With College approval, three de-identified Excel spreadsheets detailing 25 research-related sub-categories of the Faculty's Continuing Professional Development (CPD) database were interrogated for the 2019-21 triennium, accepting that research activity in 2020-21 would be COVID-19 suppressed. The numbers obligated to self-report CPD were 482, 496 and 511, respectively. Primary endpoints were the percentages of ROs claiming at least one research-related activity overall, and in each of the sub-categories individually, by year. Secondary endpoints were the "breadth" (number of sub-categories claimed/individual) and "depth" (percentages solely claiming in one of four lower-level sub-categories), by year. RESULTS ROs claimed in 23/25 sub-categories. The percentages of ROs claiming at least one research-related activity were 71%, 44%, and 62% in 2019-21, respectively. The median number of sub-categories claimed by these ROs was 2 (range 1-10) in each year. The commonest activity was journal article co-author (25%, 16% and 27%, respectively). For 2019, the most representative year, other common activities were inhouse/local meeting presentation (17%), invited lecture at state level or above (15%), manuscript peer review and research project principal investigator (14% each). The percentages of ROs solely claiming in one lower-level activity ranged between 4.4% and 5.9% per year. CONCLUSION A culture of research is arguably more fact than fantasy in ANZ. It is likely that Faculty curriculum requirements, research funding and other promotional initiatives have contributed substantively to this.
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Affiliation(s)
- Daniel Roos
- Radiation Oncology Department, Royal Adelaide Hospital, Adelaide, South Australia, Australia
- University of Adelaide, School of Medicine, Adelaide, South Australia, Australia
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Berger T, Noble DJ, Yang Z, Shelley LE, McMullan T, Bates A, Thomas S, Carruthers LJ, Beckett G, Duffton A, Paterson C, Jena R, McLaren DB, Burnet NG, Nailon WH. Sub-regional analysis of the parotid glands: model development for predicting late xerostomia with radiomics features in head and neck cancer patients. Acta Oncol 2023; 62:166-173. [PMID: 36802351 DOI: 10.1080/0284186x.2023.2179895] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 02/08/2023] [Indexed: 02/23/2023]
Abstract
BACKGROUND The irradiation of sub-regions of the parotid has been linked to xerostomia development in patients with head and neck cancer (HNC). In this study, we compared the xerostomia classification performance of radiomics features calculated on clinically relevant and de novo sub-regions of the parotid glands of HNC patients. MATERIAL AND METHODS All patients (N = 117) were treated with TomoTherapy in 30-35 fractions of 2-2.167 Gy per fraction with daily mega-voltage-CT (MVCT) acquisition for image-guidance purposes. Radiomics features (N = 123) were extracted from daily MVCTs for the whole parotid gland and nine sub-regions. The changes in feature values after each complete week of treatment were considered as predictors of xerostomia (CTCAEv4.03, grade ≥ 2) at 6 and 12 months. Combinations of predictors were generated following the removal of statistically redundant information and stepwise selection. The classification performance of the logistic regression models was evaluated on train and test sets of patients using the Area Under the Curve (AUC) associated with the different sub-regions at each week of treatment and benchmarked with the performance of models solely using dose and toxicity at baseline. RESULTS In this study, radiomics-based models predicted xerostomia better than standard clinical predictors. Models combining dose to the parotid and xerostomia scores at baseline yielded an AUCtest of 0.63 and 0.61 for xerostomia prediction at 6 and 12 months after radiotherapy while models based on radiomics features extracted from the whole parotid yielded a maximum AUCtest of 0.67 and 0.75, respectively. Overall, across sub-regions, maximum AUCtest was 0.76 and 0.80 for xerostomia prediction at 6 and 12 months. Within the first two weeks of treatment, the cranial part of the parotid systematically yielded the highest AUCtest. CONCLUSION Our results indicate that variations of radiomics features calculated on sub-regions of the parotid glands can lead to earlier and improved prediction of xerostomia in HNC patients.
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Affiliation(s)
- Thomas Berger
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - David J Noble
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
- Department of Oncology, The University of Cambridge, Cambridge, UK
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - Zhuolin Yang
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
- School of Engineering, the University of Edinburgh, the King's Buildings, Edinburgh, UK
| | - Leila Ea Shelley
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - Thomas McMullan
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - Amy Bates
- Department of Oncology, The University of Cambridge, Cambridge, UK
| | - Simon Thomas
- Department of Medical Physics and Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Linda J Carruthers
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - George Beckett
- Edinburgh Parallel Computing Centre, Bayes Centre, Edinburgh, UK
| | | | | | - Raj Jena
- Department of Oncology, The University of Cambridge, Cambridge, UK
| | - Duncan B McLaren
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | | | - William H Nailon
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
- School of Engineering, the University of Edinburgh, the King's Buildings, Edinburgh, UK
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Chen R, Xu Q, Dong B, Hou Z, Zhang Q, Zhang Y, Liu X, Chen Y, Chen M. Characteristics of Global Radiation Therapy Trials Between 2017 and 2022: A Cross-Sectional Study. Int J Radiat Oncol Biol Phys 2023:S0360-3016(22)03698-7. [PMID: 36623606 DOI: 10.1016/j.ijrobp.2022.12.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 12/20/2022] [Accepted: 12/27/2022] [Indexed: 01/09/2023]
Affiliation(s)
- Runzhe Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Qingqing Xu
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Baiqiang Dong
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China.
| | - Zan Hou
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Qun Zhang
- Department of Radiation Oncology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yuan Zhang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xu Liu
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China.
| | - Yuanyuan Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China.
| | - Ming Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China.
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Mirjolet C, Baude J, Galluzzi L. Dual impact of radiation therapy on tumor-targeting immune responses. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2023; 378:xiii-xxiv. [PMID: 37438022 DOI: 10.1016/s1937-6448(23)00114-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Affiliation(s)
- Céline Mirjolet
- Radiation Oncology Department, Preclinical Radiation Therapy and Radiobiology Unit, GF Leclerc Centre, Unicancer, Dijon, France; TIReCS Team, UMR INSERM 1231, Dijon, France.
| | - Jérémy Baude
- Radiation Oncology Department, Preclinical Radiation Therapy and Radiobiology Unit, GF Leclerc Centre, Unicancer, Dijon, France
| | - Lorenzo Galluzzi
- Department of Radiation Oncology, Weill Cornell Medical College, New York, NY, United States; Sandra and Edward Meyer Cancer Center, New York, NY, United States; Caryl and Israel Englander Institute for Precision Medicine, New York, NY, United States.
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Berger T, Noble DJ, Yang Z, Shelley LEA, McMullan T, Bates A, Thomas S, Carruthers LJ, Beckett G, Duffton A, Paterson C, Jena R, McLaren DB, Burnet NG, Nailon WH. Assessing the generalisability of radiomics features previously identified as predictive of radiation-induced sticky saliva and xerostomia. Phys Imaging Radiat Oncol 2023; 25:100404. [PMID: 36660107 PMCID: PMC9843480 DOI: 10.1016/j.phro.2022.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 11/30/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Background and purpose While core to the scientific approach, reproducibility of experimental results is challenging in radiomics studies. A recent publication identified radiomics features that are predictive of late irradiation-induced toxicity in head and neck cancer (HNC) patients. In this study, we assessed the generalisability of these findings. Materials and Methods The procedure described in the publication in question was applied to a cohort of 109 HNC patients treated with 50-70 Gy in 20-35 fractions using helical radiotherapy although there were inherent differences between the two patient populations and methodologies. On each slice of the planning CT with delineated parotid and submandibular glands, the imaging features that were previously identified as predictive of moderate-to-severe xerostomia and sticky saliva 12 months post radiotherapy (Xer12m and SS12m) were calculated. Specifically, Short Run Emphasis (SRE) and maximum CT intensity (maxHU) were evaluated for improvement in prediction of Xer12m and SS12m respectively, compared to models solely using baseline toxicity and mean dose to the salivary glands. Results None of the associations previously identified as statistically significant and involving radiomics features in univariate or multivariate models could be reproduced on our cohort. Conclusion The discrepancies observed between the results of the two studies delineate limits to the generalisability of the previously reported findings. This may be explained by the differences in the approaches, in particular the imaging characteristics and subsequent methodological implementation. This highlights the importance of external validation, high quality reporting guidelines and standardisation protocols to ensure generalisability, replication and ultimately clinical implementation.
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Affiliation(s)
- Thomas Berger
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK.,Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - David J Noble
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK.,The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK.,Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Zhuolin Yang
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK.,School of Engineering, the University of Edinburgh, the King's Buildings, Mayfield Road, Edinburgh EH9 3JL, UK
| | - Leila E A Shelley
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Thomas McMullan
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Amy Bates
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Simon Thomas
- Department of Medical Physics and Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Linda J Carruthers
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - George Beckett
- Edinburgh Parallel Computing Centre, Bayes Centre, 47 Potterrow, Edinburgh EH8 9BT, UK
| | - Aileen Duffton
- Beatson West of Scotland Cancer Centre, Great Western Road, Glasgow G12 0YN, UK
| | - Claire Paterson
- Beatson West of Scotland Cancer Centre, Great Western Road, Glasgow G12 0YN, UK
| | - Raj Jena
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Duncan B McLaren
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Neil G Burnet
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - William H Nailon
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK.,School of Engineering, the University of Edinburgh, the King's Buildings, Mayfield Road, Edinburgh EH9 3JL, UK
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Berger T, Noble DJ, Shelley LE, McMullan T, Bates A, Thomas S, Carruthers LJ, Beckett G, Duffton A, Paterson C, Jena R, McLaren DB, Burnet NG, Nailon WH. Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features. Phys Imaging Radiat Oncol 2022; 24:95-101. [PMID: 36386445 PMCID: PMC9647222 DOI: 10.1016/j.phro.2022.10.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/31/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022] Open
Abstract
Background and purpose The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC). Materials and Methods All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade ≥ 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/forward selection was used to generate combinations of predictors.Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets. Results Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively. Conclusion Our results suggest that radiomics features calculated on MVCTs from the first half of the radiotherapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.
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Affiliation(s)
- Thomas Berger
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - David J. Noble
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Leila E.A. Shelley
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Thomas McMullan
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Amy Bates
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Simon Thomas
- Department of Medical Physics and Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Linda J. Carruthers
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - George Beckett
- Edinburgh Parallel Computing Centre, Bayes Centre, 47 Potterrow, Edinburgh EH8 9BT, UK
| | - Aileen Duffton
- Beatson West of Scotland Cancer Centre, Great Western Road, Glasgow G12 0YN, UK
| | - Claire Paterson
- Beatson West of Scotland Cancer Centre, Great Western Road, Glasgow G12 0YN, UK
| | - Raj Jena
- The University of Cambridge, Department of Oncology, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK
| | - Duncan B. McLaren
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Neil G. Burnet
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, UK
| | - William H. Nailon
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
- School of Engineering, the University of Edinburgh, the King’s Buildings, Mayfield Road, Edinburgh EH9 3JL, UK
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10
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Berger T, Payan N, Fleury E, Davey A, Bryce-Atkinson A, Vasquez Osorio E, Yang Z, McMullan T, Shelley LE, Gasnier A, Bertholet J, Aznar MC, Nailon WH. Gender-related and geographic trends in interactions between radiotherapy professionals on Twitter. Phys Imaging Radiat Oncol 2022; 24:129-135. [PMID: 36439328 PMCID: PMC9696828 DOI: 10.1016/j.phro.2022.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/08/2022] Open
Abstract
Background and purpose Twitter presence in academia has been linked to greater research impact which influences career progression. The purpose of this study was to analyse Twitter activity of the radiotherapy community around ESTRO congresses with a focus on gender-related and geographic trends. Materials and methods Tweets, re-tweets and replies, here designated as interactions, around the ESTRO congresses held in 2012-2021 were collected. Twitter activity was analysed temporally and, for the period 2016-2021, the geographical span of the ESTRO Twitter network was studied. Tweets and Twitter users collated during the 10 years analysed were ranked based on number of 'likes', 're-tweets' and followers, considered as indicators of leadership/influence. Gender representation was assessed for the top-end percentiles. Results Twitter activity around ESTRO congresses was multiplied by 60 in 6 years growing from 150 interactions in 2012 to a peak of 9097 in 2018. In 2020, during the SARS-CoV-2 pandemic, activity dropped by 60 % to reach 2945 interactions and recovered to half the pre-pandemic level in 2021. Europe, North America and Oceania were strongly connected and remained the main contributors. While overall, 58 % of accounts were owned by men, this proportion increased towards top liked/re-tweeted tweets and most-followed profiles to reach up to 84 % in the top-percentiles. Conclusion During the SARS-CoV-2 pandemic, Twitter activity around ESTRO congresses substantially decreased. Men were over-represented on the platform and in most popular tweets and influential accounts. Given the increasing importance of social media presence in academia the gender-based biases observed may help in understanding the gender gap in career progression.
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Affiliation(s)
- Thomas Berger
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General
Hospital, Crewe Road South, Edinburgh, Scotland, UK
- Corresponding author at: Department of Oncology Physics, Edinburgh Cancer
Centre, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU,
UK.
| | - Neree Payan
- Patrick G Johnston Centre for Cancer Research, Queen’s University
Belfast, Belfast, UK
| | - Emmanuelle Fleury
- Department of Radiation Oncology, Erasmus Medical Center, Rotterdam,
Netherlands
- Department of Radiation Oncology, HollandPTC, Delft,
Netherlands
| | - Angela Davey
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The
University of Manchester, Manchester, England, UK
| | - Abigail Bryce-Atkinson
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The
University of Manchester, Manchester, England, UK
| | - Eliana Vasquez Osorio
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The
University of Manchester, Manchester, England, UK
| | - Zhuolin Yang
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General
Hospital, Crewe Road South, Edinburgh, Scotland, UK
- School of Engineering, the University of Edinburgh, the King’s Buildings,
Mayfield Road, Edinburgh, Scotland, UK
| | - Thomas McMullan
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General
Hospital, Crewe Road South, Edinburgh, Scotland, UK
| | - Leila E.A. Shelley
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General
Hospital, Crewe Road South, Edinburgh, Scotland, UK
| | - Anne Gasnier
- Radiotherapy Department, Gustave Roussy Cancer Campus, Villejuif,
France
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation
Oncology, Inselspital, Bern University Hospital and University of Bern, Bern,
Switzerland
| | - Marianne C. Aznar
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The
University of Manchester, Manchester, England, UK
| | - William H. Nailon
- Department of Oncology Physics, Edinburgh Cancer Centre, Western General
Hospital, Crewe Road South, Edinburgh, Scotland, UK
- School of Engineering, the University of Edinburgh, the King’s Buildings,
Mayfield Road, Edinburgh, Scotland, UK
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11
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Sceni G, Sayyad SA, Tuscano C. Letter to the editor of radiotherapy and oncology regarding the paper entitled “50 years of radiotherapy research: Evolution, trends and lessons for the future“ by berger et al. (December 2021, Volume 165). Radiother Oncol 2022; 172:149-150. [DOI: 10.1016/j.radonc.2022.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/19/2022] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
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12
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Berger T, Noble DJ, Shelley LE, Hopkins KI, McLaren DB, Burnet NG, Nailon WH. Response to letter to the editor of radiotherapy and oncology regarding the paper entitled “50 years of radiotherapy research: Evolution, trends and lessons for the future“ by Berger et al. (December 2021, Volume 165). Radiother Oncol 2022; 172:151-152. [DOI: 10.1016/j.radonc.2022.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
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