Offering enhanced deep learning technology, the updated NeuroQuant 5.0 software reportedly bolsters segmentation capabilities for amyloid-related imaging abnormalities (ARIA) in patients with Alzheimer’s disease.
The Food and Drug Administration (FDA) has granted 510(k) clearance for the updated NeuroQuant® 5.0 software, which offers enhanced magnetic resonance imaging (MRI)-based artificial intelligence (AI) capabilities for assessing patients being treated for Alzheimer’s disease and other neurological conditions.
NeuroQuant 5.0 features advanced segmentation and quantification for amyloid-related imaging abnormalities (ARIA) detected on brain MRI scans of patients being treated with anti-amyloid therapies for Alzheimer’s disease, according to Cortechs.ai, the manufacturer of the software.
The newly FDA-cleared NeuroQuant 5.0 software reportedly features advanced segmentation and quantification for amyloid-related imaging abnormalities (ARIA) for patients with Alzheimer’s disease as well as integration of of susceptibility-sensitive MRI sequences that enhance detection of smaller brain lesions, according to Cortechs.ai, the manufacturer of the software. (Image courtesy of Cortechs.ai.)
The company adds that the deep learning capabilities within NeuroQuant 5.0 facilitate improved visualization of lesions associated with traumatic brain injury (TBI), ARIA-E, ARIA-H and cerebral amyloid angiopathy. Another benefit of the NeuroQuant 5.0 software involves the integration of susceptibility-sensitive MRI sequences that enhance detection of smaller brain lesions, according to Cortechs.ai.
"With this release, we are transforming the way radiologists and neurologists approach neurological evaluations, helping to ensure more accurate and timely diagnoses for patients,” noted Kyle Frye, the chief executive officer at Cortechs.ai.
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.