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Sökning: id:"swepub:oai:lup.lub.lu.se:61e6b0cc-e23f-4e7e-b64e-e55e674eec0e" > Latent atrophy fact...

Latent atrophy factors related to phenotypical variants of posterior cortical atrophy

Groot, Colin (författare)
Vrije Universiteit Amsterdam
Yeo, B. T.Thomas (författare)
National University of Singapore
Vogel, Jacob W. (författare)
Montreal Neurological Institute & Hospital
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Zhang, Xiuming (författare)
National University of Singapore
Sun, Nanbo (författare)
National University of Singapore
Mormino, Elizabeth C. (författare)
Stanford University
Pijnenburg, Yolande A.L. (författare)
Vrije Universiteit Amsterdam
Miller, Bruce L. (författare)
University of California, San Francisco
Rosen, Howard J. (författare)
University of California, San Francisco
La Joie, Renaud (författare)
University of California, San Francisco
Barkhof, Frederik (författare)
University College London
Scheltens, Philip (författare)
Vrije Universiteit Amsterdam
van der Flier, Wiesje M. (författare)
Vrije Universiteit Amsterdam
Rabinovici, Gil D. (författare)
University of California, San Francisco
Ossenkoppele, Rik (författare)
Lund University,Lunds universitet,Klinisk minnesforskning,Forskargrupper vid Lunds universitet,Clinical Memory Research,Lund University Research Groups
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 (creator_code:org_t)
2020
2020
Engelska.
Ingår i: Neurology. - 1526-632X. ; 95:12, s. 1672-1685
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • OBJECTIVE: To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria (i.e., dorsal, ventral, dominant-parietal, and caudal) we assessed associations between latent atrophy factors and cognition. METHODS: We employed a data-driven Bayesian modeling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multicenter cohort of 119 individuals with PCA (age 64 ± 7 years, 38% male, Mini-Mental State Examination 21 ± 5, 71% β-amyloid positive, 29% β-amyloid status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, MRI scanner field strength, and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a priori classification. Individual factor expressions were correlated to 4 PCA-specific cognitive domains (object perception, space perception, nonvisual/parietal functions, and primary visual processing) using general linear models. RESULTS: The model revealed 4 distinct yet partially overlapping atrophy factors: right-dorsal, right-ventral, left-ventral, and limbic. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the large majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiologic phenotype. CONCLUSION: Our results indicate that specific brain behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain regions and symptoms, indicating that classification into 4 mutually exclusive variants is unlikely to be clinically useful.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Neurosciences (hsv//eng)

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