Automatically computed rating scales from MRI for patients with cognitive disorders.
Aged
Alzheimer Disease
/ diagnostic imaging
Atrophy
Biomarkers
Cerebral Cortex
/ diagnostic imaging
Cognition Disorders
/ diagnostic imaging
Diagnosis, Differential
Female
Humans
Magnetic Resonance Imaging
/ methods
Male
Middle Aged
Temporal Lobe
/ diagnostic imaging
White Matter
/ diagnostic imaging
Atrophy
Cognition disorders
Magnetic resonance imaging
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
Sep 2019
Sep 2019
Historique:
received:
13
09
2018
accepted:
04
02
2019
revised:
09
01
2019
pubmed:
24
2
2019
medline:
28
11
2019
entrez:
24
2
2019
Statut:
ppublish
Résumé
The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics. A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers. We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort (ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752) cohorts were used for independent validation to test generalizability. The correlation coefficients between visual and computed rating scale values were 0.83/0.78 (MTA-left), 0.83/0.79 (MTA-right), 0.64/0.64 (GCA), and 0.76/0.75 (Fazekas) in ADC/PredictND cohorts. When performance in differential diagnostics was studied for the main types of dementia, the highest balanced accuracy, 0.75-0.86, was observed for separating different dementias from cognitively normal subjects using computed GCA. The lowest accuracy of about 0.5 for all the visual and computed scales was observed for the differentiation between Alzheimer's disease and frontotemporal lobar degeneration. Computed scales produced higher balanced accuracies than visual scales for MTA and GCA (statistically significant). MTA, GCA, and WMHs can be reliably estimated automatically helping to provide consistent imaging biomarkers for diagnosing cognitive disorders, even among less experienced readers. • Visual rating scales used in diagnostics of cognitive disorders can be estimated computationally from MRI images with intraclass correlations ranging from 0.64 (GCA) to 0.84 (MTA). • Computed scales provided high diagnostic accuracy with single-subject data (area under the receiver operating curve range, 0.84-0.94).
Identifiants
pubmed: 30796570
doi: 10.1007/s00330-019-06067-1
pii: 10.1007/s00330-019-06067-1
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4937-4947Subventions
Organisme : European Union's Seventh Framework Programme for research, technological development and demonstration
ID : 611005
Organisme : European Union's Seventh Framework Programme for research, technological development and demonstration
ID : 601055
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