TY - JOUR
T1 - ARCHERY
T2 - a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol
AU - Aggarwal, Ajay
AU - Court, Laurence Edward
AU - Hoskin, Peter
AU - Jacques, Isabella
AU - Kroiss, Mariana
AU - Laskar, Sarbani
AU - Lievens, Yolande
AU - Mallick, Indranil
AU - Abdul Malik, Rozita
AU - Miles, Elizabeth
AU - Mohamad, Issa
AU - Murphy, Claire
AU - Nankivell, Matthew
AU - Parkes, Jeannette
AU - Parmar, Mahesh
AU - Roach, Carol
AU - Simonds, Hannah
AU - Torode, Julie
AU - Vanderstraeten, Barbara
AU - Langley, Ruth
N1 - Publisher Copyright:
© 2023 BMJ. All rights reserved.
PY - 2023/12/7
Y1 - 2023/12/7
N2 - Introduction Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy. Methods ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs. Ethics and dissemination The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.
AB - Introduction Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy. Methods ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs. Ethics and dissemination The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.
KW - Adult oncology
KW - ONCOLOGY
KW - RADIOTHERAPY
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U2 - 10.1136/bmjopen-2023-077253
DO - 10.1136/bmjopen-2023-077253
M3 - Article
C2 - 38149419
AN - SCOPUS:85179808654
SN - 2044-6055
VL - 13
JO - BMJ open
JF - BMJ open
IS - 12
M1 - e077253
ER -