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Imaging markers for Alzheimer disease: Which vs how

Frisoni, G B; Bocchetta, M; Chetelat, G; Rabinovici, G D; de Leon, M J; Kaye, J; Reiman, E M; Scheltens, P; Barkhof, F; Black, S E; Brooks, D J; Carrillo, M C; Fox, N C; Herholz, K; Nordberg, A; Jack, C R, Jr; Jagust, W J; Johnson, K A; Rowe, C C; Sperling, R A; Thies, W; Wahlund, L O; Weiner, M W; Pasqualetti, P; Decarli, C

Neurology. 2013;81(5):487-500.

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Abstract

Revised diagnostic criteria for Alzheimer disease (AD) acknowledge a key role of imaging biomarkers for early diagnosis. Diagnostic accuracy depends on which marker (i.e., amyloid imaging, 18F-fluorodeoxyglucose [FDG]-PET, SPECT, MRI) as well as how it is measured ("metric": visual, manual, semiautomated, or automated segmentation/computation). We evaluated diagnostic accuracy of marker vs metric in separating AD from healthy and prognostic accuracy to predict progression in mild cognitive impairment. The outcome measure was positive (negative) likelihood ratio, LR+ (LR-), defined as the ratio between the probability of positive (negative) test outcome in patients and the probability of positive (negative) test outcome in healthy controls. Diagnostic LR+ of markers was between 4.4 and 9.4 and LR- between 0.25 and 0.08, whereas prognostic LR+ and LR- were between 1.7 and 7.5, and 0.50 and 0.11, respectively. Within metrics, LRs varied up to 100-fold: LR+ from approximately 1 to 100; LR- from approximately 1.00 to 0.01. Markers accounted for 11% and 18% of diagnostic and prognostic variance of LR+ and 16% and 24% of LR-. Across all markers, metrics accounted for an equal or larger amount of variance than markers: 13% and 62% of diagnostic and prognostic variance of LR+, and 29% and 18% of LR-. Within markers, the largest proportion of diagnostic LR+ and LR- variability was within 18F-FDG-PET and MRI metrics, respectively. Diagnostic and prognostic accuracy of imaging AD biomarkers is at least as dependent on how the biomarker is measured as on the biomarker itself. Standard operating procedures are key to biomarker use in the clinical routine and drug trials.

Bibliographic metadata

Type of resource:
Content type:
Published date:
Language:
eng
Journal title:
Volume:
81
Issue:
5
Start page:
487
End page:
500
Total:
14
Pagination:
487-500
Digital Object Identifier:
81/5/487 [pii] 10.1212/WNL.0b013e31829d86e8
ISI Accession Number:
23897875
Related website(s):
  • Related website http://www.ncbi.nlm.nih.gov/pubmed/23897875
General notes:
  • Frisoni, Giovanni B Bocchetta, Martina Chetelat, Gael Rabinovici, Gil D de Leon, Mony J Kaye, Jeffrey Reiman, Eric M Scheltens, Philip Barkhof, Frederik Black, Sandra E Brooks, David J Carrillo, Maria C Fox, Nick C Herholz, Karl Nordberg, Agneta Jack, Clifford R Jr Jagust, William J Johnson, Keith A Rowe, Christopher C Sperling, Reisa A Thies, William Wahlund, Lars-Olof Weiner, Michael W Pasqualetti, Patrizio Decarli, Charles For ISTAART's NeuroImaging Professional Interest Area Journal article Neurology Neurology. 2013 Jul 30;81(5):487-500.
Access state:
Active

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:214659
Created by:
Herholz, Karl
Created:
10th December, 2013, 16:19:31
Last modified by:
Herholz, Karl
Last modified:
10th December, 2013, 16:19:31

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