LEARN: Learning Environment for Artificial Intelligence in Radiotherapy New Technology
NCT ID: NCT05184790
Last Updated: 2024-07-26
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
300 participants
OBSERVATIONAL
2023-02-28
2026-01-31
Brief Summary
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Routinely acquired patient data will be used to improve the training, testing and accuracy of a whole-of-body markerless tracking method. When the markerless tracking method is sufficiently advanced, according to the PI of each of the data collection sites, the markerless tracking method will be run in parallel to, but not intervening with, patient treatments during data acquisition.
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Detailed Description
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After the treatment, the ground truth and the variability in the ground truth will be computed. The patient images, the markerless tracking results, the ground truth and the variability will be uploaded to an in-house developed clinical trial learning system. Uploading additional data to the learning system automatically triggers the model building of the deep learning system. In this manner, the learning system gets both more accurate and more robust with each patient accrued. As the patient data accrues, the primary hypothesis of targeting accuracy can be tested.
The developed markerless tracking software will be applied by study personnel to the treatment imaging data for each anatomic site using five-fold cross-validation where 80% of the data is used for training and the remaining unseen 20% of the data is used for testing. Target positions produced by the markerless tracking will be compared with a 'ground truth'.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Brain cancer
Patients having radiation therapy for treatment of brain cancer.
No interventions assigned to this group
Breast cancer
Patients having radiation therapy for treatment of breast cancer.
No interventions assigned to this group
Head and neck cancer
Patients having radiation therapy for treatment of head and neck cancer.
No interventions assigned to this group
Kidney cancer
Patients having radiation therapy for treatment of kidney cancer.
No interventions assigned to this group
Liver cancer
Patients having radiation therapy for treatment of liver cancer.
No interventions assigned to this group
Pancreatic cancer
Patients having radiation therapy for treatment of pancreatic cancer.
No interventions assigned to this group
Prostatic cancer
Patients having radiation therapy for treatment of prostate cancer.
No interventions assigned to this group
Spinal neoplasm
Patients having radiation therapy for treatment of spinal cancer.
No interventions assigned to this group
Cardiac arrhythmia
Patients having radiation therapy for treatment of cardiac arrhythmia
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Will receive CT planning, and a cone beam CT scan for at least one fraction of radiation therapy.
* Will receive intrafraction x-ray imaging for the liver, pancreas, prostate, spine cancer treatment or cardiac arrhythmia treatment. As intrafraction imaging is not common standard of care for brain, breast, head and neck and kidney cancer treatments there is no requirement to have intrafraction x-ray imaging data for these anatomical sites.
* Provides written informed consent.
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Princess Alexandra Hospital, Brisbane, Australia
OTHER
Calvary Mater Newcastle, Australia
OTHER
Western Sydney Local Health District
OTHER
Austin Health
OTHER_GOV
Peter MacCallum Cancer Centre, Australia
OTHER
University of Sydney
OTHER
Responsible Party
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Principal Investigators
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Paul Keall
Role: STUDY_CHAIR
Professor
Locations
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Royal North Shore Hospital
Saint Leonards, New South Wales, Australia
Princess Alexandra Hospital
Woolloongabba, Queensland, Australia
Alfred Health
Melbourne, Victoria, Australia
Peter MacCallum Cancer Centre
Melbourne, Victoria, Australia
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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IX-2021-DS-LEARN
Identifier Type: -
Identifier Source: org_study_id
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