Emerging AI Software for Brain MRI Gets FDA Nod
Pixyl.Neuro reportedly leverages generative artificial intelligence (AI) technology to accelerate brain MRI assessment and improve early detection of abnormal atrophy.
The Food and Drug Administration (FDA) has granted 510(k) clearance for Pixyl.Neuro™, an adjunctive artificial intelligence (AI)-powered software that may enhance magnetic resonance imaging (MRI) detection and follow-up of patients with neurological disorders including Alzheimer’s disease and multiple sclerosis (MS).
Reportedly providing automated brain MRI analysis in less than five minutes, Pixyl.Neuro may help quantify brain region volume to aid in the differential diagnosis and facilitate earlier identification of atrophy, according to Pixyl, the developer of the software.
Lotfi Hacein-Bey, M.D, said adjunctive AI support reinforces radiology workflows for the assessment of patients with neurological disorders.
“The recent FDA approval of Pixyl's software is a very positive step toward improved diagnosis, management and longitudinal follow up of neurodegenerative and neuroinflammatory disorders, especially with the advent of disease-modifying treatments for MS, NMO (neuromyelitis optica) and Alzheimer's disease,” noted Dr. Hacein-Bey, the director of the Division of Neuroradiology the the University of California, Davis (UC Davis) School of Medicine in Sacramento, Calif.
Pixyl added that the Pixyl.Neuro software, currently utilized in more than 12 countries, has seen a four-fold increase in use since December 2022.
Considering Breast- and Lesion-Level Assessments with Mammography AI: What New Research Reveals
June 27th 2025While there was a decline of AUC for mammography AI software from breast-level assessments to lesion-level evaluation, the authors of a new study, involving 1,200 women, found that AI offered over a seven percent higher AUC for lesion-level interpretation in comparison to unassisted expert readers.
Can CT-Based Deep Learning Bolster Prognostic Assessments of Ground-Glass Nodules?
June 19th 2025Emerging research shows that a multiple time-series deep learning model assessment of CT images provides 20 percent higher sensitivity than a delta radiomic model and 56 percent higher sensitivity than a clinical model for prognostic evaluation of ground-glass nodules.
FDA Clears Ultrasound AI Detection for Pleural Effusion and Consolidation
June 18th 2025The 14th FDA-cleared AI software embedded in the Exo Iris ultrasound device reportedly enables automated detection of key pulmonary findings that may facilitate detection of pneumonia and tuberculosis in seconds.
