Background: Early detection of amyloid-β (Aβ) positivity is essential for an accurate diagnosis and treatment of Alzheimer's disease (AD), but it is currently costly and/or invasive.
Objective: We aimed to classify Aβ positivity (Aβ+) using morphometric features from magnetic resonance imaging (MRI), a more accessible and non-invasive technique, in two clinical population scenarios: one containing AD, mild cognitive impairment (MCI) and cognitively normal (CN) subjects, and another only cognitively impaired subjects (AD and MCI).
Methods: Demographic, cognitive (Mini-Mental State Examination [MMSE] scores), regional morphometry MRI (volumes, areas, and thicknesses), and derived morphometric graph theory (GT) features from all subjects (302 Aβ+, age: 73.
Background: 3D surgical planning for the treatment of tumors in pediatrics using different neuroimaging methods is witnessing an accelerating and dynamic development. Until now, there have been many reports on the use of 3D printing techniques in different aspects of medical practice. Pediatric tumors mainly in the abdomen are among the most medical specialties that benefit from using this technique.
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