Brain Metastases
Conditions
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.
Interventions
DEVICEBrain Metastasis AI
There will be no intervention
Sponsors
Netherlands Cancer Institute - NKI
Robovision BV
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* 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.
Exclusion criteria
* subjects with primary intracranial tumor(s), with more than 10 brain metastases, with meningeal metastases, with radiation necrosis, or post brain surgery
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| 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
| Measure | Time frame | Description |
|---|---|---|
| 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. |
Countries
Netherlands
Outcome results
None listed