Automated Detection of Brain Metastases on MRI

N/AEnrolling By InvitationNCT06727032

Robovision BV12 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Brain Metastases

Interventions

Brain Metastasis AIDEVICE

There will be no intervention

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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

Locations (1)

Netherlands Cancer Institute

Amsterdam, Netherlands

Outcomes

Primary Outcomes

Detection accuracy

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).

Time frame: 3 months

Secondary Outcomes

Reading time

Demonstrate that the AIDED radiologists reading time for detecting brain metastases is significantly lower than for UNAIDED radiologists.

Time frame: 3 months

Inter-reader agreement

Demonstrate that AIDED reading reduces detection variation between observers/readers in brain metastasis detection.

Time frame: 3 months

Data from ClinicalTrials.gov

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