Whole-body MRI and AI for Neurofibromatosis Type 1 in Children
This study is looking at a new way to find pre-cancerous growths in children with Neurofibromatosis Type 1 (NF1). Researchers are using special whole-body Magnetic Resonance Imaging (MRI) scans combined with Artificial Intelligence (AI) to do this. They want to see how reliable the MRI scans are and how well the AI can detect changes over time. You can join if you are between 5 and 17 years old and have a confirmed diagnosis of NF1. The study aims to enroll 15 children at Cedars-Sinai Medical Center. The main goal is to check if the MRI scans give consistent results and if the AI can accurately spot changes in the scans over a year.
- Study design
- This is a single-arm pilot study, meaning all 15 participants will receive the same intervention. It is not specified if it is blinded or open-label.
- What's involved
- You would have whole-body MRI scans at the beginning of the study, again at 1 month, and a final scan at 12 months.
- Compensation
- Not stated in the trial record.
- Follow-up
- Participants will be followed for 12 months after the baseline scan, with the primary endpoint measured within 4 weeks of baseline.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Identification of Pre-Malignant Lesions In Pediatric Patients With Neurofibromatosis Type 1 Using Novel Magnetic Resonance Imaging Techniques Paired With Artificial Intelligence
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Nicole Baca, MD · PRINCIPAL_INVESTIGATOR · Cedars-Sinai Medical Center
Who to contact
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Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- For scan re-scan reliability, utilize T2 imaging to evaluate the agreement between the baseline scan and the 1 Month scan, which is performed within 4 weeks of the baseline scan.From Baseline to within 4 weeks of baseline
T2 is a type of high-resolution multiparametric tissue mapping that measures quantitative metrics of the physical properties of tissue and allows comparison in longitudinal follow-up