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Data driven diagnostic classification in Alzheimer's disease based on different reference regions for normalization of PiB-PET images and correlation with CSF concentrations of A beta species

Artikel i vetenskaplig tidskrift
Författare F. Oliveira
A. Leuzy
J. Castelhano
K. Chiotis
S. G. Hasselbalch
J. Rinne
A. Mendonca
M. Otto
A. Lleo
I. Santana
J. Johansson
S. Anderl-Straub
C. Arnim
A. Beer
R. Blesa
J. Fortea
H. Sanna-Kaisa
Erik Portelius
Josef Pannee
Henrik Zetterberg
Kaj Blennow
A. P. Moreira
A. Abrunhosa
A. Nordberg
M. Castelo-Branco
Publicerad i Neuroimage-Clinical
Volym 20
Sidor 603-610
ISSN 2213-1582
Publiceringsår 2018
Publicerad vid Institutionen för neurovetenskap och fysiologi
Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi
Sidor 603-610
Språk en
Länkar dx.doi.org/10.1016/j.nicl.2018.08.0...
Ämnesord mild cognitive impairment, amyloid-beta, task-force, quantification, conversion, medicine, criteria, markers, mci, Neurosciences & Neurology, khann g, 1984, neurology, v34, p939
Ämneskategorier Neurovetenskap

Sammanfattning

Positron emission tomography (PET) neuroimaging with the Pittsburgh Compound_B (PiB) is widely used to assess amyloid plaque burden. Standard quantification approaches normalize PiB-PET by mean cerebellar gray matter uptake. Previous studies suggested similar pons and white-matter uptake in Alzheimer's disease (AD) and healthy controls (HC), but lack exhaustive comparison of normalization across the three regions, with data-driven diagnostic classification. We aimed to compare the impact of distinct reference regions in normalization, measured by data-driven statistical analysis, and correlation with cerebrospinal fluid (CSF) amyloid beta (A beta) species concentrations. 243 individuals with clinical diagnosis of AD, HC, mild cognitive impairment (MCI) and other dementias, from the Biomarkers for Alzheimer's/Parkinson's Disease (BIOMARKAPD) initiative were included. PiB-PET images and CSF concentrations of A beta(38), A beta(40) and A beta(42) were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF A beta concentrations were calculated. Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96%, sensitivity-96%, specificity-95%), and significantly higher than A beta concentrations (best accuracy 91%). Normalization by the white-matter showed decreased extent of statistically significant multivoxel patterns and was the only method not outperforming CSF biomarkers, suggesting statistical inferiority. A beta(38) and A beta(40) correlated negatively with PiB-PET images normalized by the white-matter, corroborating previous observations of correlations with non-AD-specific subcortical changes in white-matter. In general, when using the pons as reference region, higher voxel-wise group differences and stronger correlation with A beta(42), the A beta(42)/A beta(40) or A beta(42)/A beta(38) ratios were found compared to normalization based on cerebellar gray matter.

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