Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Andrew McPartlin"'
Autor:
David J. Thomson, Clare Cruickshank, Helen Baines, Russell Banner, Matthew Beasley, Guy Betts, Helen Bulbeck, Frances Charlwood, Judith Christian, Matthew Clarke, Olly Donnelly, Bernadette Foran, Callum Gillies, Clare Griffin, Jarrod J. Homer, Johannes A. Langendijk, Lip Wai Lee, James Lester, Matthew Lowe, Andrew McPartlin, Elizabeth Miles, Christopher Nutting, Nachi Palaniappan, Robin Prestwich, James M. Price, Clare Roberts, Justin Roe, Ramkumar Shanmugasundaram, Rita Simões, Anna Thompson, Catharine West, Lorna Wilson, Jane Wolstenholme, Emma Hall
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 38, Iss , Pp 147-154 (2023)
Externí odkaz:
https://doaj.org/article/efbbc2d562cf40079af68d82a83fc6b6
Autor:
Winnie Li, Jerusha Padayachee, Inmaculada Navarro, Jeff Winter, Jennifer Dang, Srinivas Raman, Vickie Kong, Alejandro Berlin, Charles Catton, Rachel Glicksman, Victor Malkov, Andrew McPartlin, Kaushik Kataki, Patricia Lindsay, Peter Chung
Publikováno v:
Technical Innovations & Patient Support in Radiation Oncology, Vol 27, Iss , Pp 100212- (2023)
Purpose: To develop a practice-based training strategy to transition from radiation oncologist to therapist-driven prostate MR-Linac adaptive radiotherapy. Methods and materials: In phase 1, 7 therapists independently contoured the prostate and organ
Externí odkaz:
https://doaj.org/article/1e33595fa04040b78897c5a677b23b08
Autor:
Andrew McPartlin, Lucy Kershaw, Alan McWilliam, Marcus Ben Taylor, Clare Hodgson, Marcel van Herk, Ananya Choudhury
Publikováno v:
Therapeutic Advances in Urology, Vol 10 (2018)
Background: Changes in prostate cancer apparent diffusion coefficient (ADC) derived from diffusion-weighted magnetic resonance imaging (MRI) provide a noninvasive method for assessing radiotherapy response. This may be attenuated by neoadjuvant hormo
Externí odkaz:
https://doaj.org/article/9e2834b970fa4f09a1bf5881e2fa9c0b
Autor:
Christian Rønn Hansen, Gareth Price, Matthew Field, Nis Sarup, Ruta Zukauskaite, Jørgen Johansen, Jesper Grau Eriksen, Farhannah Aly, Andrew McPartlin, Lois Holloway, David Thwaites, Carsten Brink
Publikováno v:
Rønn Hansen, C, Price, G, Field, M, Sarup, N, Zukauskaite, R, Johansen, J, Eriksen, J G, Aly, F, McPartlin, A, Holloway, L, Thwaites, D & Brink, C 2022, ' Larynx cancer survival model developed through open-source federated learning ', Radiotherapy and Oncology, vol. 176, pp. 179-186 . https://doi.org/10.1016/j.radonc.2022.09.023
Introduction: Federated learning has the potential to perfrom analysis on decentralised data; however, there are some obstacles to survival analyses as there is a risk of data leakage. This study demonstrates how to perform a stratified Cox regressio
Autor:
James M. Price, Hitesh B. Mistry, Guy Betts, Eleanor J. Cheadle, Lynne Dixon, Kate Garcez, Tim Illidge, Zsuzsanna Iyizoba-Ebozue, Lip Wai Lee, Andrew McPartlin, Robin J.D. Prestwich, Savvas Papageorgiou, Dylan J. Pritchard, Andrew Sykes, Catharine M. West, David J. Thomson
Publikováno v:
Journal of Clinical Oncology. 40:2203-2212
PURPOSE There is a need to refine the selection of patients with oropharyngeal squamous cell carcinoma (OPSCC) for treatment de-escalation. We investigated whether pretreatment absolute lymphocyte count (ALC) predicted overall survival (OS) benefit f
Autor:
James M. Price, Catharine M. West, Lynne M. Dixon, Zsuzsanna Iyizoba-Ebozue, Kate Garcez, Lip Wai Lee, Andrew McPartlin, Fin Slevin, Andrew Sykes, Robin J.D. Prestwich, David J. Thomson
Publikováno v:
Radiotherapy and Oncology. 172:111-117
There is renewed interest in hypofractionated radiotherapy, but limited data and a lack of consensus to support use for head and neck cancer. In this multicentre analysis we compared outcomes for patients with oropharyngeal squamous cell carcinoma (O
Autor:
Michael J. Dubec, David L. Buckley, Michael Berks, Abigael Clough, John Gaffney, Anubhav Datta, Damien J. McHugh, Nuria Porta, Ross A. Little, Susan Cheung, Christina Hague, Cynthia L. Eccles, Peter J. Hoskin, Robert G. Bristow, Julian C. Matthews, Marcel van Herk, Ananya Choudhury, Geoff J.M. Parker, Andrew McPartlin, James P.B. O'Connor
Publikováno v:
Dubec, M J, Buckley, D L, Berks, M, Clough, A, Gaffney, J, Datta, A, McHugh, D J, Porta, N, Little, R A, Cheung, S, Hague, C, Eccles, C L, Hoskin, P J, Bristow, R G, Matthews, J C, van Herk, M, Choudhury, A, Jm Parker, G, McPartlin, A & Pb O'Connor, J 2023, ' First-in-Human Technique Translation of Oxygen-Enhanced MRI to an MR Linac System in Patients with Head and Neck Cancer ', Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, pp. 109592 . https://doi.org/10.1016/j.radonc.2023.109592
BACKGROUND AND PURPOSE: Tumour hypoxia is prognostic in head and neck cancer (HNC), associated with poor loco-regional control, poor survival and treatment resistance. The advent of hybrid MRI - radiotherapy linear accelerator or 'MR Linac' systems -
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b7f73650388cb6569ade3129cfeac51
https://research.manchester.ac.uk/en/publications/606087a1-bf9b-443f-bff3-2fb57b30dd65
https://research.manchester.ac.uk/en/publications/606087a1-bf9b-443f-bff3-2fb57b30dd65
Autor:
Amanda Moreira, Jennifer Dang, Aran Kim, Vickie Kong, Winnie Li, Cathy Rocca, Andrea Shessel, Iris Wong, Aisling Barry, Alejandro Berlin, Charles Catton, Peter Chung, Laura Dawson, Rachel Glicksman, Joelle Helou, Ali Hosni, Jelena Lukovic, Andrew McPartlin, Aruz Mesci, Srinivas Raman, Michael Yan, Daniel Letourneau, Michael Milosevic, Michael Velec
Publikováno v:
Journal of Medical Imaging and Radiation Sciences. 54:8-9
Autor:
Christian Rønn Hansen, Gareth Price, Matthew Field, Nis Sarup, Ruta Zukauskaite, Jørgen Johansen, Jesper Grau Eriksen, Farhannah Aly, Andrew McPartlin, Lois Holloway, David Thwaites, Carsten Brink
Publikováno v:
Hansen, C R, Price, G, Field, M, Sarup, N, Zukauskaite, R, Johansen, J, Eriksen, J G, Aly, F, McPartlin, A, Holloway, L, Thwaites, D & Brink, C 2022, ' Open-source distributed learning validation for a larynx cancer survival model following radiotherapy ', Radiotherapy and Oncology, vol. 173, pp. 319-326 . https://doi.org/10.1016/j.radonc.2022.06.009
Prediction models are useful to design personalised treatment. However, safe and effective implementation relies on external validation. Retrospective data are available in many institutions, but sharing between institutions can be challenging due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4ec606cc3cb90879394253a4214837f
https://pure.au.dk/portal/da/publications/opensource-distributed-learning-validation-for-a-larynx-cancer-survival-model-following-radiotherapy(f9e33204-4a47-43a7-b002-29cfbacdf733).html
https://pure.au.dk/portal/da/publications/opensource-distributed-learning-validation-for-a-larynx-cancer-survival-model-following-radiotherapy(f9e33204-4a47-43a7-b002-29cfbacdf733).html
Autor:
M. van Herk, N. Slevin, Andrew McPartlin, Lip W Lee, P. Whitehurst, Andrew Green, William J Beasley, Robert Chuter, Christina Hague, C. Hughes, D. Mullan, Gareth J Price, Catharine M L West
Publikováno v:
Radiotherapy and Oncology. 158:112-117
Introduction Auto contouring models help consistently define volumes and reduce clinical workload. This study aimed to evaluate the cross acquisition of a Magnetic Resonance (MR) deep learning auto contouring model for organ at risk (OAR) delineation