Imperial College London
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ProfessorDavidSharp

Faculty of Medicine, Department of Brain Sciences

Professor of Neurology
 
 
 
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Contact

 

+44 (0)20 7594 7991david.sharp Website

 
 
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Location

 

UREN.927Sir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Underwood:2018:10.1097/QAI.0000000000001687,
author = {Underwood, J and Cole, JH and Leech, R and Sharp, DJ and Winston, A},
doi = {10.1097/QAI.0000000000001687},
journal = {Journal of Acquired Immune Deficiency Syndromes},
pages = {429--436},
title = {Multivariate pattern analysis of volumetric neuroimaging data and its relationship with cognitive function in treated HIV-disease},
url = {http://dx.doi.org/10.1097/QAI.0000000000001687},
volume = {78},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BACKGROUND: Accurate prediction of longitudinal changes in cognitive function would potentially allow targeted intervention in those at greatest risk of cognitive decline. We sought to build a multivariate model using volumetric neuroimaging data alone to accurately predict cognitive function. METHODS: Volumetric T1-weighted neuroimaging data from virally suppressed HIV-positive individuals from the CHARTER cohort (n=139) were segmented into grey and white matter and spatially normalised before were entering into machine learning models. Prediction of cognitive function at baseline and longitudinally was determined using leave-one-out cross validation. Additionally, a multivariate model of brain ageing was used to measure the deviation of apparent brain age from chronological age and assess its relationship with cognitive function. RESULTS: Cognitive impairment, defined using the global deficit score, was present in 37.4%. However, it was generally mild and occurred more commonly in those with confounding comorbidities (p<0.001). Although multivariate prediction of cognitive impairment as a dichotomous variable at baseline was poor (AUC 0.59), prediction of the global T-score was better than a comparable linear model (adjusted R=0.08, p<0.01 vs. adjusted R=0.01, p=0.14). Accurate prediction of longitudinal changes in cognitive function was not possible (p=0.82).Brain-predicted age exceeded chronological age by mean (95% confidence interval) 1.17 (-0.14-2.53) years, but was greatest in those with confounding comorbidities (5.87 [1.74-9.99] years) and prior AIDS (3.03 [0.00-6.06] years). CONCLUSION: Accurate prediction of cognitive impairment using multivariate models using only T1-weighted data was not achievable, which may reflect the small sample size, heterogeneity of the data or that impairment was usually mild.
AU  - Underwood,J
AU  - Cole,JH
AU  - Leech,R
AU  - Sharp,DJ
AU  - Winston,A
DO  - 10.1097/QAI.0000000000001687
EP  - 436
PY  - 2018///
SN  - 1525-4135
SP  - 429
TI  - Multivariate pattern analysis of volumetric neuroimaging data and its relationship with cognitive function in treated HIV-disease
T2  - Journal of Acquired Immune Deficiency Syndromes
UR  - http://dx.doi.org/10.1097/QAI.0000000000001687
UR  - https://www.ncbi.nlm.nih.gov/pubmed/29608444
UR  - http://hdl.handle.net/10044/1/58653
VL  - 78
ER  -
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