Neuro
What if the earliest signs of neurodegenerative disease could be identified before symptoms emerge?
Neurodegenerative conditions are hard to detect and track with visual assessment alone, often hiding until a patient’s health is in decline. By enabling earlier intervention and coordinated care, AI-powered innovation can transform how clinicians assess and manage these conditions.
Get the latest research insights on how advances in AI are opening new possibilities with earlier intervention for neurodegenerative disease.
Automated quantification and localization of white matter hyperintensities in FLAIR MRI to support disease risk stratification and longitudinal assessment
ECR: Poster Presentation
Moeskops et al. 2026
White matter hyperintensities (WMHs) are clinically actionable imaging markers of several neurological conditions, including cognitive impairment and multiple sclerosis (MS). Manual segmentation of WMHs on Fluid-Attenuated Inversion Recovery (FLAIR) MRI is time-consuming and impractical for routine clinical practice, limiting consistent use in risk stratification and longitudinal assessment. This study evaluates an AI algorithm for automated quantification and localization by identifying, segmenting, and labelling anatomical location of WMHs.
Artificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms
Elisa R. Berson, Mariam S. Aboian, Ajay Malhotra, Seyedmehdi Payabvash
Combining semi‑quantitative rating and automated brain volumetry in MRI evaluation of patients with probable behavioural variant of frontotemporal dementia: an added value for clinical practise?
Sonia Francesca Calloni, Paolo Quintiliano Vezzulli, Antonella Castellano, Riccardo Leone, Silvia Basaia, Almar von Loon, Edoardo Gioele Spinelli, Giuseppe Magnani, Francesca Caso, Federica Agosta, Massimo Filippi & Andrea Falini
Twenty-four hour blood pressure variability and the prevalence and the progression of cerebral white matter hyperintensities
Naomi LP Starmans et al.