RecruitingNCT05653063

ARCHERY - Artificial Intelligence Based Radiotherapy Treatment Planning for Cervical, Head and Neck and Prostate Cancer

Sponsor

University College, London

Enrollment

990 participants

Start Date

Dec 7, 2023

Study Type

OBSERVATIONAL

Conditions

Cancer of Prostate Cancer Head Neck Cancer Cervix

Summary

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

Min Age: 18 Years

Inclusion Criteria5

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.
Patients aged ≥18years.

Exclusion Criteria3

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.

Interventions

OTHERA web-based artificial intelligence (AI) auto-planning tool

The 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.