This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
This phase II trial tests the effectiveness and safety of artificial intelligence (AI) to determine dose recommendation during stereotactic body radiation therapy (SBRT) planning in patients with primary lung cancer or tumors that has spread from another primary site to the lung (metastatic). SBRT uses special equipment to position a patient and deliver radiation to tumors with high precision. This method may kill tumor cells with fewer doses over a shorter period and cause less damage to normal tissue. Even with the high precision of SBRT, disease persistence or reappearance (local recurrence) can still occur, which could be attributed to the radiation dose. AI has been used in other areas of healthcare to automate and improve various aspects of medical science. Because the relationship of dose and local recurrence indicates that dose prescriptions matter, decision support systems to help guide dose based on personalized prediction AI algorithms could better assist providers in prescribing the radiation dose of lung stereotactic body radiation therapy treatment.
A Single-Arm Phase II Study of Personalized Dose Guidance for Stereotactic Body Radiotherapy (SBRT) in Patients With Lung Tumors
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: Northwestern University
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.