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FDA Clears Updated AI Software for MRI Neuroimaging
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.
Seven Takeaways from New CT and MRI Guidelines for Ovarian Cancer Staging
January 20th 2025In an update of previous guidelines from the European Society of Urogenital Radiology published in 2010, a 21-expert panel offered consensus recommendations on the utility of CT, MRI and PET-CT in the staging and follow-up imaging for patients with ovarian cancer.
Can MRI-Based AI Enhance Risk Stratification in Prostate Cancer?
January 13th 2025Employing baseline MRI and clinical data, an emerging deep learning model was 32 percent more likely to predict the progression of low-risk prostate cancer (PCa) to clinically significant prostate cancer (csPCa), according to new research.
