Automated Detection of Brain Metastases on MRI
- Conditions
- Brain Metastases
- Registration Number
- NCT06727032
- Lead Sponsor
- Robovision BV
- Brief Summary
This reader study aims at assessing whether the radiologist aided with AI software has at least a non-inferior performance than without AI assistance in detecting brain metastases.
200 retrospective MRI images will be included in the study with 100 positive and 100 negative exams.
Assessment will be completed by 12 readers with varying level of experience. This is a Retrospective Multiple-Reader Multiple-Case (MRMC) randomised study.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ENROLLING_BY_INVITATION
- Sex
- All
- Target Recruitment
- 12
- subjects older than 18 years with a known or possible primary extracranial cancer who undergo MRI for diagnosis, treatment planning or follow-up of brain metastases.
- subjects with primary intracranial tumor(s), with more than 10 brain metastases, with meningeal metastases, with radiation necrosis, or post brain surgery
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Detection accuracy 3 months Demonstrate that the accuracy for detecting brain metastases by radiologists on MRI using the software (AIDED) is at least non-inferior to that of radiologists not using the software (UNAIDED).
- Secondary Outcome Measures
Name Time Method Reading time 3 months Demonstrate that the AIDED radiologists reading time for detecting brain metastases is significantly lower than for UNAIDED radiologists.
Inter-reader agreement 3 months Demonstrate that AIDED reading reduces detection variation between observers/readers in brain metastasis detection.
Related Research Topics
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Trial Locations
- Locations (1)
Netherlands Cancer Institute
🇳🇱Amsterdam, Netherlands