ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer – study protocol
Hannah Simonds,
Ruth Langley,
Indranil Mallick,
Peter Hoskin,
Elizabeth Miles,
Rozita Abdul Malik,
Claire Murphy,
Mahesh Parmar,
Matthew Nankivell,
Jeannette Parkes,
Julie Torode,
Issa Mohamad,
Laurence Edward Court,
Isabella Jacques,
Mariana Kroiss,
Sarbani Laskar,
Yolande Lievens,
Carol Roach,
Barbara Vanderstraeten
Affiliations
Hannah Simonds
Stellenbosch University, Stellenbosch, Western Cape, South Africa
Ruth Langley
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
Indranil Mallick
Department of Radiation Oncology, Tata Memorial Center, Kolkata, West Bengal, India
Peter Hoskin
Department of Oncology, The Christie NHS Foundation Trust, Manchester, UK
Elizabeth Miles
National Radiotherapy Trials Quality Assurance Group, Mount Vernon Hospital, Northwood, UK
Rozita Abdul Malik
University of Malaya, Kuala Lumpur, Wilayah Persekutuan, Malaysia
Claire Murphy
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
Mahesh Parmar
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
Matthew Nankivell
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
Jeannette Parkes
University of Cape Town, Rondebosch, South Africa
Julie Torode
King’s College London, London, UK
Issa Mohamad
King Hussein Cancer Center, Amman, Jordan
Laurence Edward Court
MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
Isabella Jacques
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
Mariana Kroiss
National Radiotherapy Trials Quality Assurance Group, Mount Vernon Hospital, Northwood, UK
Sarbani Laskar
Department of Radiation Oncology, Tata Memorial Hospital, Mumbai, Maharashtra, India
Yolande Lievens
Ghent University Hospital, Gent, Belgium
Carol Roach
Institute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK
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.
