ARCHERY - Artificial Intelligence Based Radiotherapy Treatment Planning for Cervical, Head and Neck and Prostate Cancer
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity College, London
About this trial
The aim of this study is to look at whether an Artificial Intelligence (AI) based computer program can automate two components of the radiotherapy treatment pathway to a sufficient quality standard to enable its routine clinical use. The two components include the delineation (outlining) of anatomical areas that are at risk of tumour spread and at risk of radiation damage, and the definition of the position, size and shape of the radiation beams.
The AI-based computer programs have been developed to perform tasks that would normally require direct human involvement by oncologists and medical physicists. 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, which this study will test.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Consecutive patients with histologically confirmed head and neck cancers of the oropharynx, larynx, hypopharynx and nasopharynx (Stage I-III) that have given consent for radical radiotherapy.
Consecutive histologically confirmed primary cervical cancer patients (Stage IB-IIIB including pelvic node positive) that have given consent for radical radiotherapy.
Consecutive histologically confirmed primary prostate cancer patients (T1-4N0M0) that have given consent for radical radiotherapy.
Mental capacity to understand and consent to participate in the study.
Disqualifiers
Patients requiring radiotherapy after curative surgery or surgery that is intended to remove as much of the tumour as possible.
Patients receiving palliative radiotherapy
Patients aged < 18years.
Trial population
Patients eligible for radiotherapy for head and neck, cervical or prostate cancer.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
A web-based artificial intelligence (AI) auto-planning tool
Other interventionThe CT scan taken at the time of treatment planning is uploaded to a web server called the Radiotherapy planning assistant which automates the contouring of target organs and areas of high-risk disease as well as defining the size, shape and number of radiotherapy beams to treat the cancer. The final plan is downloaded to the local treatment planning system where the doses are recalculated and clinical peer review is undertaken before the plan can be used clinically. In this study patients will not be treated with the AI tool but the manual plan created by the local teams.
Treatment groups
No treatment groups listed
Trial outcomes
Primary outcomes
1
Proportion of radiotherapy treatment plans that have contours and dosimetry that meet pre-defined criteria for clinical acceptability
Time frame
Prior to first treatmentSecondary outcomes
1
comparison of time and human resource requirements between producing automated radiotherapy treatment plans using artificial intelligence and producing treatment plans using the standard manual pathway
Time frame
radiotherapy plan preparation process pre treatment2
Comparison of radiotherapy treatment costs using the artificial intelligence automated pathway and standard manual planning pathway
Time frame
radiotherapy treatment plan preparation process and treatment intervalSponsors and contacts
Click on the lead sponsor to view all of their trials.
University College, London
Lead sponsor
National Institutes of Health (NIH)
Collaborator
Rising Tide Foundation
Collaborator
Medical Research Council
Collaborator
Tata Memorial Hospital
Collaborator
Tata Memorial Centre
Collaborator
University of Stellenbosch
Collaborator
King Hussein Cancer Center
Collaborator
University of Malaya
Collaborator
University Ghent
Collaborator
M.D. Anderson Cancer Center
Collaborator
Mount Vernon Cancer Centre at Mount Vernon Hospital
Collaborator
University of Cape Town
Collaborator
National Cancer Institute (NCI)
Collaborator
Source ClinicalTrials.gov