White matter tract correlations with spoken language in cerebrovascular disease
Notice bibliographique
Résumé
Abstract Assessment of spoken language is a promising marker for cognitive impairment in individuals with cerebrovascular disease. However, the underlying neurological basis for spoken language beyond single words and sentences remains poorly defined in this cohort, particularly with respect to white matter. This study aimed to examine and compare white matter hyperintensity volumes and diffusion tensor metrics in normal-appearing white matter (NAWM) as potential correlates of spoken language performance. Baseline imaging and spoken language data were obtained from the cerebrovascular disease cohort of the Ontario Neurodegenerative Disease Research Initiative (n = 127; age: 55–85 years). Most participants had subclinical or very mild strokes, with very little to no aphasia symptoms. Spoken language samples were analysed to compute 10 different measures related to syntax, productivity, lexical diversity, fluency, and information content. Structural and diffusion MRI data were analysed to segment white matter hyperintensities and tracts. Normalized white matter hyperintensity volume, as well as average fractional anisotropy and mean diffusivity in the normal-appearing portion of eight white matter tracts, were correlated with the 10 spoken language measures using canonical correlation analyses. White matter and spoken language variate scores for individual participants then were correlated separately in male (n = 86) and female (n = 41) participants to probe potential sex differences. Spoken language performance was significantly associated with the fractional anisotropy (rc = 0.51, P = 0.041) and mean diffusivity (rc = 0.56, P = 0.011) of NAWM, particularly in the left superior longitudinal fasciculus, but not with white matter hyperintensity volumes (rc = 0.41, P = 0.80) in the same tracts. Measures related to syntax, fluency, and information content loaded most strongly in the spoken language variate. No significant sex differences were found in NAWM microstructure, and female and male participants exhibited similarly strong associations between spoken language and NAWM microstructure (fractional anisotropy: z = 1.44, P = 0.15; mean diffusivity: z = 1.03, P = 0.30). These results suggest that diffusion MRI in NAWM may be superior to white matter hyperintensity volumetrics when evaluating the role of white matter tract integrity on cognitive outcomes in people with relatively mild cerebrovascular pathology. These results also demonstrate that multi-domain spoken language analysis is sensitive to underlying white matter microstructure in participants with cerebrovascular disease without significant aphasia, supporting its value as a tool for assessing cognitive status.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».