mdbrain

mediaire

Key Features

Aneurysm detection with longitudinal follow-up
Including hippocampus and ventricles) with longitudinal follow-up
Lesion detection including anatomical localization (magnims criteria) and longitudinal follow-up
Quantification of brain volume and white/gray matter (global and regional
Segmentation of brain regions
Tumor differentiation through delineation and quantification of tumor core and surrounding oedema incl. longitudinal follow-up

General Information

Product name

mdbrain

Company

mediaire

Subspeciality

Neuro

Modality

Disease targeted

Dementia, multiple sclerosis, MSA/CBD/PSA, aneursyms, glioma/glioblastoma

Main task

Not specified

Technical Specifications

Population

Early diagnostics and follow up of neurological and neurodegenerative diseases

Patient population age

Not specified

Input

1.5 or 3T MR. Brain volumetry: 3D-T1-MPRage, 1.0 x 1.0 mm²; Lesion characterization: (3D-)T1 and 3D-T2-FLAIR, 1.0 x 1.0 mm²; Aneurysm detection: TOF, 1.0 x 1.0 mm²; Tumor differentiation: 3D-T1, 3D-T2-FLAIR, 1.0 x 1.0 mm², T1 with contrast agent, 3.0 x 3.0 mm², and T2 spin-echo, 3.0 x 3.0 mm²

Input format

DICOM

Output

Structured PDF report including: diagnostically relevant slices from the current exam, tables with quantitative metrics from the current exam (and comparison with previous exam), diagrams with color-coded deviations from norm values. Color-coded segmentation overlays (static + longitudinal).

Output format

Browser-based platform, CSV-Export file, DICOM-PDF, PDF

Integration

Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform, Stand-alone third party application

Deployment

Cloud-based, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Etc., Image upload, On demand, Right after the image acquisition, Triggered by a user through e.g. a button click

Processing time

1 - 10 minutes

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

01-2019

AI Platforms

Bayer Pharmaceuticals, Deepc, Sectra

Resellers

Angionautix, Bender, Medavis, Medecon, Sanova, Supermedical, Tatramed

Countries present

11 (Germany, Switzerland, Austria, Spain, Portugal, Italy, Romania, Czech Republic, Slovakia, UAE, Israel)

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Automation bias in AI-assisted detection of cerebral aneurysms on time-of-flight MR angiography

Peer-Reviewed

View

AI-based assessment of longitudinal multiple sclerosis MRI: Strengths and weaknesses in clinical practice

Peer-Reviewed

View

Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia

Peer-Reviewed

View

Artificial intelligence can help detecting incidental intracranial aneurysm on routine brain MRI using TOF MRA data sets and improve the time required for analysis of these images

Peer-Reviewed

View

AI supported detection of cerebral multiple sclerosis lesions decreases radiologic reporting times

Peer-Reviewed

View

External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington’s disease

Peer-Reviewed

View

AI supported detection of cerebral multiple sclerosis lesions decreases radiologic reporting times

Peer-Reviewed

View

Changes in MRI Workflow of Multiple Sclerosis after Introduction of an AI-Software: A Qualitative Study

Peer-Reviewed

View

Impact of an AI software on the diagnostic performance and reading time for the detection of cerebral aneurysms on time of flight MR-angiography

Peer-Reviewed

View

Automated Detection of Cerebral Aneurysms on TOF-MRA Using a Deep Learning Approach: An External Validation Study

Peer-Reviewed

View

Triplanar U-Net with lesion-wise voting for the segmentation of new lesions on longitudinal MRI studies