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Amyloid-related imaging abnormalities

Detect, measure and grade ARIA-E and ARIA-H

icobrain aria

icobrain aria can be used to assess side effects to amyloid-targeting therapies for Alzheimer's disease, known as amyloid-related imaging abnormalities (ARIA). It detects parenchymal vasogenic edema, gyral swelling and sulcal effusion.

Image by Lino C.

icobrain aria was thoroughly evaluated in large reader studies. It was demonstrated that the assistance of AI significantly improved radiologists’ ability to detect and classify ARIA, boosting both diagnostic sensitivity and accuracy, and adding a critical safety option for patients undergoing amyloid-targeting therapies

icobrain aria was thoroughly evaluated in large reader studies. It was demonstrated that the assistance of AI significantly improved radiologists’ ability to detect and classify ARIA, boosting both diagnostic sensitivity and accuracy, and adding a critical safety option for patients undergoing amyloid-targeting therapies

Jeffrey Cummings, Neurologist at University of Nevada

icometrix

87%

Sensitivity for ARIA-E detection
icometrix

79%

Sensitivity for ARIA-H detection
icometrix

>80%

Specificity for detection of both
Paul Parizel
Image by Lino C.

I am excited that icobrain aria has received FDA approval, clearing the way for wider use in clinical practice. New standardized tools are needed, such as icobrain aria, to assist radiologists and treating clinicians in detecting and managing ARIA to optimize patient safety.

I am excited that icobrain aria has received FDA approval, clearing the way for wider use in clinical practice. New standardized tools are needed, such as icobrain aria, to assist radiologists and treating clinicians in detecting and managing ARIA to optimize patient safety.

Stephen Salloway, Neurologist at Brown University

Key scientific publications

Monitoring of amyloid related imaging abnormalities: SWI vs T2*-GRE

Sima et al. (2025)

Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities

Sima et al. (2024)

A deep learning model for brain segmentation across pediatric and adult populations

Simarro et al. (2024)

Cost-Effectiveness Analysis of AI-Assisted Radiological Assessment in Patients With Relapsing Remitting Multiple Sclerosis in the UK

Esposito et al. (2022)

Health Economic Impact of Software-Assisted Brain MRI on Therapeutic Decision-Making and Outcomes of Relapsing-Remitting Multiple Sclerosis Patients—A Microsimulation Study

Sima et al. (2021)

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Latest news & press

brain visual AI
A Shared Language for ARIA: Standardizing Alzheimer’s Imaging in the Age of New Therapies with RSNA

With the arrival of disease-modifying therapies for Alzheimer’s disease, we are entering a new era in neurodegenerative care. But with...

brain visual AI
Tracking Alzheimer’s Disease with AI: How Technology Helps Doctors Detect Early Changes

Alzheimer’s disease is one of the most complex neurodegenerative disorders to monitor. The changes in the brain are often gradual and subtle, making early detection incredibly challenging. Traditionally, clinicians relied on cognitive tests, patient interviews, and manual analysis of MRI scans. While these methods provide useful information, they can be time-consuming, subjective, and prone to human error. This is where AI-powered brain imaging is transforming the field. By combining advanced...

brain visual AI
American College of Radiology (ACR) and icometrix collaborate to improve the quality of care for people with Alzheimer’s disease

Virginia, VA – April 2nd, 2025 The American College of Radiology (ACR), the professional medical society dedicated to advancing radiology...

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