IC‐P2‐090: Longitudinal progression of AD‐like patterns of brain atrophy in a normal elderly cohort and in MCI: A high‐imensinal pattern classification study
Notice bibliographique
Résumé
MRI is an established AD biomarker. Methods for computational neuroanatomy, including high-dimensional pattern analysis and classification, have been demonstrated by several studies to achieve excellent classification of individuals, thereby offering the potential for diagnosis and prognosis. This study was based on two large neuroimaging studies of normal aging and AD: the Baltimore Longitudinal Study of Aging (BLSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). We investigated longitudinal progression of AD-like patterns of atrophy, determined from ADNI, in the BLSA cohort of cognitively normal (CN) elderly and of MCI. A high-dimensional pattern classifier was trained on 66 CN and 56 AD ADNI patients, and was subsequently applied to 109 CN and 15 MCI individuals from the BLSA study over a period of 9 years. The longitudinal progression of AD-like patterns of atrophy was determined for different age brackets. 98.7% of all BLSA participants that remained CN were correctly classified as CN, thereby cross-validating the accuracy of ADNI-derived classification on datasets from a different study. CN subjects of ages above 80 progressively displayed AD-like patterns of brain atrophy. The rates of change of classification-derived abnormality scores of CN's were fairly well clustered around 0, except a small subgroup of them (especially older subjects), generally indicating lack of progression of CN towards AD-like phenotypes. In contrast, rates of change of individuals that developed MCI were more variable and positive, indicating gradual progression of many, but not all, to AD-like structure. Moreover, cognitive scores of CN and MCI that were determined to have AD-like classification scores were significantly lower than their counterparts classified as normal-like. A biomarker of structural abnormality distinguishing CN from AD was derived using sophisticated high-dimensional pattern classification, and was tested on longitudinal MRI scans from cognitively normal elderly and of MCI individuals. Although most CN's that remain cognitively stable display normal and stable patterns of atrophy, individuals that develop MCI show steady increases in AD-like atrophy patterns. Structural abnormality scores and their rates of change define subgroups of CN and MCI individuals whose cognitive scores differ significantly, further indicating the clinical relevance of this structural biomarker.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 ».