ARCHERY: A Prospective Observational Study of Artificial Intelligence-Based Radiotherapy Treatment Planning for Cervical, Head and Neck and Prostate Cancer – Study Protocol

Authors

Ajay Aggarwal
Laurence Edward Court
Peter Hoskin
Isabella Jacques
Mariana Kroiss
Sarbani Laskar
Yolande Lievens
Indranil Mallick
Rozita Abdul Malik
Elizabeth Miles
Issa Mohamad
Claire Murphy
Matthew Nankivell
Jeannette Parkes
Mahesh Parmar
Carol Roach
Hannah Simonds
Julie Torode
Barbara Vanderstraeten
Ruth Langley

Publication Date

12-7-2023

Journal

BMJ Open

Abstract

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.

Keywords

Male, Humans, Prospective Studies, Artificial Intelligence, Prostatic Neoplasms, Software, Radiotherapy Planning, Computer-Assisted, Observational Studies as Topic, Radiotherapy, Oncology, Adult Oncology

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Supplementary Materials

PMID: 38149419