Locally Optimised Contouring With AI Technology for Radiotherapy
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorRoyal North Shore Hospital
About this trial
LOCATOR is a multicentre phase II randomised clinical trial that is looking at the process of contouring in radiation treatment for breast cancer patients. This study looks at whether contouring aided by artificial intelligence (AI) is comparable in quality to that of contouring done completely manually by a radiation oncologist. We are also looking at whether AI assisted contouring saves radiation oncologists time when compared to fully manual contouring.
LOCATOR uses the LOCATOR software which is an in-house software developed locally and trained on local data.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
18 years and older who are planned for primary breast malignancy
ECOG performance 0-2
Ability to understand and willingness to sign a written informed consent document
The target volume must be able to be objectively reviewed by current published national or international clinical guidelines
Disqualifiers
Patients under 18 years of age
Patients unable to understand consent documents
Trial design
Design model
Parallel
Treatments tested in this trial
AI assisted contouring
DeviceInitial are generated automatically using software powered by artificial intelligence
Treatment groups
444 Participants
are divided into 2 treatment groupsGroup A: AI assisted contouringExperimental treatment 1 intervention
Group B: Manual contouringNo intervention 0 interventions
Trial outcomes
Primary outcomes
1
Assessment of differences in Contour Quality
To assess the contour quality of fully manual segmentation vs AI assisted segmentation. This assessment will be done using the MD Anderson Cancer Centre five-point likert scale used to validate autosegmentation models ranging from (Strongly disagree to Strongly Agree). The measure will be the proportion of unacceptable contours (as defined by MD Anderson autocontouring score \<= 2) between manual contouring and AI-assisted contouring.
Time frame
18 monthsSecondary outcomes
1
Assessment of quality of AI assisted contours with and without manual edits
To assess the contour quality of AI assisted contours with and without manual edits. This assessment will be done using the MD Anderson Cancer Centre five-point likert scale used to validate autosegmentation models ranging from (Strongly disagree to Strongly Agree). The measure will be the proportion of unacceptable contours (as defined by MD Anderson autocontouring score \<= 2) between manual contouring and AI-assisted contouring.
Time frame
18 months2
Time Savings
To evaluate the difference in time taken to contour with and without the assistance of an auto-segmentation tool.
Time frame
18 months3
To assess the differences in acute clinician reported toxicity between patients treated with contours assisted by AI contouring versus manual contouring.
Acute clinician reported toxicity will be measured using CTCAE version 5.0 across individual items (see full protocol appendix). For this study, the outcome will be the difference in the proportion of patients with grade≥3 toxicity at any point in time from the start of radiotherapy to 90 days following radiotherapy.
Time frame
18 months4
To assess the differences in late clinician reported toxicity between patients treated with contours assisted by AI contouring versus manual contouring.
Late clinician reported toxicity will be measured using CTCAE version 5.0 across individual items (see full protocol appendix). For this study, the outcome will be the difference in the proportion of patients with grade≥3 toxicity at any point in time between 90 days following radiotherapy and 5 years following radiotherapy.
Time frame
5 yearsSponsors and contacts
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Source ClinicalTrials.gov