Performance of computed tomography and magnetic resonance morphometry in evaluating brain atrophy in Down syndrome
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: To compare the performance of computed tomography (CT) with that of magnetic resonance imaging (MRI) in assessing brain atrophy in Down syndrome (DS). METHODS: Retrospective comparison of CT-derived gray and white matter measurements with those obtained by MRI using voxel-based morphometry (VBM) in adults with DS who underwent both scanning modalities with a maximum interval of 1 year. The concordance of both tests was compared across sample quartiles. RESULTS: Eleven of 23 participants had some degree of cognitive decline. When comparing VBM outputs of both imaging techniques, an overlap of voxels negatively correlated with dementia severity was observed in the right temporal lobe. Observed agreement was 92.3% (quadratic-weighted kappa index 0.71) for both gray and white matter. DISCUSSION: CT and MRI analyses showed a similar decrease in brain volume as cognitive decline increased. Our results highlight the potential use of CT in computational neuroanatomy studies of DS. HIGHLIGHTS: Voxel-based morphometry shows that computed tomography (CT) and magnetic resonance imaging (MRI) yield similar brain atrophy patterns in DS. Strong agreement (kappa index 0.71) was found between CT and MRI assessments. CT-identified right temporal lobe volume loss linked to cognitive decline in DS. CT offers a practical, accessible alternative to MRI for brain imaging in DS. Artificial intelligence-based CT analysis enhances neuroimaging for DS with reduced motion issues.
Source: Alzheimer s & Dementia
DOI: 10.1002/alz.70296
Institutions: Hospital Universitario de La Princesa, Universidad Autónoma de Madrid, Fundacion Centro De Investigacion De Enfermedades Neurologicas, Universitat Autònoma de Barcelona, Hospital de Sant Pau, Institut de Recerca Sant Pau, Nvidia (United Kingdom), Wellcome Centre for Human Neuroimaging, University College London, UCL Queen Square Institute of Neurology, Universidad Politécnica de Madrid
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,200
OpenAlex ID: W4412954040
