ContouringLOCATORNCT06546592
Locally Optimised Contouring With AI Technology for Radiotherapy
A study testing AI assisted contouring in people with Contouring and Segmentation, run by Royal North Shore Hospital at 3 sites in Australia.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Contouring, Segmentation, Radiation Therapy
- What is being tested?
- AI assisted contouring
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 444 participants
- Where
- 3 sitesAustralia
- Study dates
- 11 Feb 2025to 30 Apr 2030
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- Patients under 18 years of age
- Patients unable to understand consent documents
Trial locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Australia3 sites, 3 recruiting
- Recruiting
Western Cancer Centre Dubbo
Dubbo, New South Wales, 2830
Denise Andree-Evarts
- Recruiting
Central West Cancer Centre
Orange, New South Wales, 2800
Denise Andree-Evarts
- Recruiting
Department of Radiation Oncology, Royal North Shore Hospital
St Leonards, New South Wales, 2065
Heidi Tsang, 9463 1340, heidi.tsang@health.nsw.gov.au
About this study
Official title: LOCATOR - Locally Optimised Contouring With AI Technology for Radiotherapy
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.
Read the detailed description
LOCATOR is a multicentre phase II non-inferiority randomised controlled trial looking at comparing AI assisted contours (with in-house LOCATOR software) against fully manual contouring in breast cancer patients. The primary endpoint is to show non inferiority in grade of AI assisted contouring when compared to fully manual contouring with a poor contour (score <= 2) as per the MD Anderson Contouring Grade Scale. Secondary endpoints include geometric assessments of contour accuracy, dosimetric differences based on contours, performance (geometric) when compared to commercially available tools as well as economic cost-benefit analysis if in-house AI contouring tools.
The study will randomise patients 3:1 to the intervention arm of LOCATOR assisted contours to manual contours. An initial AI contouring model for each tumor type will be trained on contours from 45 previous breast cases using a nnUNetv2 framework. The model will then be iteratively updated every 20-50 patients.
- Being tested
- AI assisted contouring
- Keywords
- Contouring, Segmentation, Radiation Therapy, Artificial Intelligence, Deep Learning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI assisted contouringDevice
Also called autocontouring, autosegmentation, AI contouring
Initial are generated automatically using software powered by artificial intelligence
| Study group | Role | What they receive |
|---|---|---|
| AI assisted contouring | Experimental | Patients in this arm will have their contours/segmentations generated by a combination of the LOCATOR (AI) software before manual edits and checks by a radiation oncologist. Receives: Device: AI assisted contouring |
| Manual contouring | No intervention | Patients in this arm will have standard of care which is fully manual contours/segmentations generated and checked by a radiation oncologist. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 18 months
Secondary outcomes (21)
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.
Measured: 18 months
Time Savings
To evaluate the difference in time taken to contour with and without the assistance of an auto-segmentation tool.
Measured: 18 months
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.
Measured: 18 months
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.
Measured: 5 years
To assess the differences in patient reported general acute quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
General acute patient quality of life outcomes will be measured using the EORTC QLQ-C30 instrument. For this study, the outcome will be the difference in total scores and by domain at any point in time from the start of radiotherapy to 90 days following radiotherapy.
Measured: 18 months
To assess the differences in patient reported general late quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Acute patient reported toxicity will be measured using the EORTC QLQ-C30 and QLQ-BR45. For this study, the outcome will be the difference in total scores and by domain at any point in time between 90 days following radiotherapy and 5 years following radiotherapy.
Measured: 5 years
To assess the differences in patient reported breast specific acute quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Breast specific acute patient quality of life outcomes will be measured using the EORTC QLQ-BR45 instrument. For this study, the outcome will be the difference in total scores and by domain at any point in time from the start of radiotherapy to 90 days following radiotherapy.
Measured: 18 months
To assess the differences in patient reported breast specific late quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Breast specific late patient quality of life outcomes will be measured using the EORTC QLQ-BR45 instrument. For this study, the outcome will be the difference in total scores and by domain at any point in time between 90 days following radiotherapy and 5 years following radiotherapy.
Measured: 5 years
Assessment of accuracy of AI assisted contours before and after manual edits using surface dice similarity coefficient (sDSC).
To assess accuracy (geometrically) of AI segmentation before and after manual correction. This will be done by comparing the change in surface dice similarity coefficient (sDSC).
Measured: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using dice similarity coefficient (DSC).
To assess accuracy (geometrically) of AI segmentation before and after manual correction. This will be done by comparing the change in dice similarity coefficient (DSC).
Measured: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using added path length (APL)
To assess accuracy (geometrically) of AI segmentation before and after manual correction. This will be done by comparing the change in APL.
Measured: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using mean slice-wise Hausdorff distance (MSHD).
To assess accuracy (geometrically) of AI segmentation before and after manual correction. This will be done by comparing the change in MSHD.
Measured: 18 months
Assessment of dosimetric differences between patient planned with AI-contours and those planned with manual contours.
To compare the dose volume histogram metrics per contoured structure between patient planned with AI contours and those planned with manual contours.
Measured: 18 months
Assessment of dosimetric differences in plans optimised on AI assisted contours before and after manual edits.
We will assess dosimetric differences to the clinical tumour volume (CTV), planning target volume (PTV) and organs at risk (OARs) between AI assisted contours before and after manual edits. The measure will be in the proportion of patients who pass all planning constraints as per the FAST FORWARD protocol.
Measured: 18 months
Assessment of accuracy in contours with an initial and retrained AI model using surface dice similarity coefficient (sDSC).
To assess improvements, if any, in accuracy (geometrically) on contours generated on an initial AI model versus models re-trained on clinical trial data every 20-50 patients. Comparisons will be made using the change in surface dice similarity coefficient (sDSC) when the initially generated AI contour is compared with the final edited contour.
Measured: 18 months
Assessment of accuracy in contours with an initial and retrained AI model using dice similarity coefficient (DSC).
To assess improvements, if any, in accuracy (geometrically) on contours generated on an initial AI model versus models re-trained on clinical trial data every 50-100 patients. Comparisons will be made using the change in dice similarity coefficient (DSC) when the initially generated AI contour is compared with the final edited contour.
Measured: 18 months
Assessment of accuracy in contours between different AI systems using surface dice similarity coefficient (sDSC).
To compare the accuracy of an in-house AI segmentation tool (LOCATOR) against commercially available tools on geometric accuracy. Comparisons will be made using the difference in surface dice similarity coefficient (sDSC) with the initially generated AI contours when compared with the final manual contour.
Measured: 18 months
Assessment of accuracy in contours between different AI systems using dice similarity coefficient (DSC).
To compare the accuracy of an in-house AI segmentation tool (LOCATOR) against commercially available tools on geometric accuracy. Comparisons will be made using the difference in dice similarity coefficient (DSC) with the initially generated AI contours when compared with the final manual contour.
Measured: 18 months
Assessment of quality in contours between different AI systems
To compare the quality of contours of an in-house AI segmentation tool (LOCATOR) against commercially available tools. 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.
Measured: 18 months
Assessment of patient perception and attitudes on AI use in their care
We will perform a brief assessment of patient perception on AI use in their care with a six question survey following their treatment on a five-point likert scale (strongly agree to strongly disagree).
Measured: 18 months
Economic Cost Benefit Analysis
To perform an economic cost-benefit analysis of using an in-house auto-segmentation (LOCATOR) tool compared to manual segmentation and commercial auto-segmentation systems. This will be done using direct dollar (US and Australian) cost comparisons. Direct costs will be calculated for the LOCATOR system including labor, hardware and maintenance costs for 1 and 3 years. The direct dollar cost for a commercial system will be compared against the overall direct cost of the LOCATOR system. The direct cost of retaining a manual system will be calculated based on the direct cost of extra hours of labor required.
Measured: 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Aug 2024
- Study start11 Feb 2025
- Primary completion1 Feb 2026 (estimated)
- Study completion30 Apr 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ContouringStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 444 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Royal North Shore Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06546592
- Sponsor's protocol ID
- 2024/PID01401
- Acronym
- LOCATOR
- Status last verified
- Jan 2026
- First submitted
- 25 Jul 2024
- Last updated
- 29 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- LOCATOR - Locally Optimised Contouring With AI Technology for Radiotherapy
- ClinicalTrials.gov ID
- NCT06546592
- Acronym / sponsor ID
- LOCATOR / 2024/PID01401
- Keywords
- Contouring, Segmentation, Radiation Therapy, Artificial Intelligence, Deep Learning
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 444 participants (estimated)
- Lead sponsor
- Royal North Shore HospitalUniversity, hospital or other
- Study start
- 11 Feb 2025 (actual)
- Primary completion
- 1 Feb 2026 (estimated)
- Study completion
- 30 Apr 2030 (estimated)
- First posted
- 9 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
LOCATOR is a multicentre phase II non-inferiority randomised controlled trial looking at comparing AI assisted contours (with in-house LOCATOR software) against fully manual contouring in breast cancer patients. The primary endpoint is to show non inferiority in grade of AI assisted contouring when compared to fully manual contouring with a poor contour (score <= 2) as per the MD Anderson Contouring Grade Scale. Secondary endpoints include geometric assessments of contour accuracy, dosimetric differences based on contours, performance (geometric) when compared to commercially available tools as well as economic cost-benefit analysis if in-house AI contouring tools.
The study will randomise patients 3:1 to the intervention arm of LOCATOR assisted contours to manual contours. An initial AI contouring model for each tumor type will be trained on contours from 45 previous breast cases using a nnUNetv2 framework. The model will then be iteratively updated every 20-50 patients.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI assisted contouring | Experimental | Device: AI assisted contouringPatients in this arm will have their contours/segmentations generated by a combination of the LOCATOR (AI) software before manual edits and checks by a radiation oncologist. |
| Manual contouring | No intervention | –Patients in this arm will have standard of care which is fully manual contours/segmentations generated and checked by a radiation oncologist. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (2 listed)
- Patients under 18 years of age
- Patients unable to understand consent documents
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI assisted contouringAlso: autocontouring, autosegmentation, AI contouringInitial are generated automatically using software powered by artificial intelligence | Device | AI assisted contouring |
Primary outcome
Assessment of differences in Contour Quality
Time frame: 18 months
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.
21 secondary outcomes
Assessment of quality of AI assisted contours with and without manual edits
Time frame: 18 months
Time Savings
Time frame: 18 months
To assess the differences in acute clinician reported toxicity between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 18 months
To assess the differences in late clinician reported toxicity between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 5 years
To assess the differences in patient reported general acute quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 18 months
To assess the differences in patient reported general late quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 5 years
To assess the differences in patient reported breast specific acute quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 18 months
To assess the differences in patient reported breast specific late quality of life outcomes between patients treated with contours assisted by AI contouring versus manual contouring.
Time frame: 5 years
Assessment of accuracy of AI assisted contours before and after manual edits using surface dice similarity coefficient (sDSC).
Time frame: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using dice similarity coefficient (DSC).
Time frame: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using added path length (APL)
Time frame: 18 months
Assessment of accuracy of AI assisted contours before and after manual edits using mean slice-wise Hausdorff distance (MSHD).
Time frame: 18 months
Assessment of dosimetric differences between patient planned with AI-contours and those planned with manual contours.
Time frame: 18 months
Assessment of dosimetric differences in plans optimised on AI assisted contours before and after manual edits.
Time frame: 18 months
Assessment of accuracy in contours with an initial and retrained AI model using surface dice similarity coefficient (sDSC).
Time frame: 18 months
Assessment of accuracy in contours with an initial and retrained AI model using dice similarity coefficient (DSC).
Time frame: 18 months
Assessment of accuracy in contours between different AI systems using surface dice similarity coefficient (sDSC).
Time frame: 18 months
Assessment of accuracy in contours between different AI systems using dice similarity coefficient (DSC).
Time frame: 18 months
Assessment of quality in contours between different AI systems
Time frame: 18 months
Assessment of patient perception and attitudes on AI use in their care
Time frame: 18 months
Economic Cost Benefit Analysis
Time frame: 18 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Jan 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI assisted contouring in people with Contouring and Segmentation, run by Royal North Shore Hospital at 3 sites in Australia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 29 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Australia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Joseph Chan, BSc MBBS PhD FRANZCR (94631300, joseph.chan@health.nsw.gov.au), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Assessment of differences in Contour Quality (time frame: 18 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Jan 2026.