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 Aβ species
| dc.contributor.author | Francisco Oliveira | |
| dc.contributor.author | Antoine Leuzy | |
| dc.contributor.author | João Castelhano | |
| dc.contributor.author | Konstantinos Chiotis | |
| dc.contributor.author | Steen Gregers Hasselbalch | |
| dc.contributor.author | Juha Rinne | |
| dc.contributor.author | Alexandre Mendonça | |
| dc.contributor.author | Markus Otto | |
| dc.contributor.author | Alberto Lleó | |
| dc.contributor.author | Isabel Santana | |
| dc.contributor.author | Jarkko Johansson | |
| dc.contributor.author | Sarah Anderl-Straub | |
| dc.contributor.author | Christine Arnim | |
| dc.contributor.author | Ambros Beer | |
| dc.contributor.author | Rafael Blesa | |
| dc.contributor.author | Juan Fortea | |
| dc.contributor.author | Herukka Sanna-Kaisa | |
| dc.contributor.author | Erik Portelius | |
| dc.contributor.author | Josef Pannee | |
| dc.contributor.author | Henrik Zetterberg | |
| dc.contributor.author | Kaj Blennow | |
| dc.contributor.author | Ana P. Moreira | |
| dc.contributor.author | Antero Abrunhosa | |
| dc.contributor.author | Agneta Nordberg | |
| dc.contributor.author | Miguel Castelo-Branco | |
| dc.contributor.organization | fi=PET-keskus|en=Turku PET Centre| | |
| dc.contributor.organization | fi=kliininen laitos|en=Department of Clinical Medicine| | |
| dc.contributor.organization | fi=tyks, vsshp|en=tyks, varha| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.14646305228 | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.61334543354 | |
| dc.converis.publication-id | 35828224 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/35828224 | |
| dc.date.accessioned | 2025-08-28T01:19:05Z | |
| dc.date.available | 2025-08-28T01:19:05Z | |
| dc.description.abstract | 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.<br /><br />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 β (Aβ) species concentrations.<br /><br />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 Aβ38, Aβ40 and Aβ42 were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF Aβ concentrations were calculated.<br /><br />Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96%, sensitivity-96%, specificity-95%), and significantly higher than Aβ 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. Aβ38 and Aβ40 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 Aβ42, the Aβ42/Aβ40 or Aβ42/Aβ38 ratios were found compared to normalization based on cerebellar gray matter.<br /> | |
| dc.format.pagerange | 603 | |
| dc.format.pagerange | 610 | |
| dc.identifier.eissn | 2213-1582 | |
| dc.identifier.jour-issn | 2213-1582 | |
| dc.identifier.olddbid | 207380 | |
| dc.identifier.oldhandle | 10024/190407 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/51110 | |
| dc.identifier.urn | URN:NBN:fi-fe2021042719732 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Rinne, Juha | |
| dc.okm.affiliatedauthor | Johansson, Jarkko | |
| dc.okm.affiliatedauthor | Dataimport, tyks, vsshp | |
| dc.okm.discipline | 3112 Neurosciences | en_GB |
| dc.okm.discipline | 3112 Neurotieteet | fi_FI |
| dc.okm.internationalcopublication | international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher | Elsevier Inc. | |
| dc.relation.doi | 10.1016/j.nicl.2018.08.023 | |
| dc.relation.ispartofjournal | NeuroImage: Clinical | |
| dc.relation.volume | 20 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/190407 | |
| dc.title | 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 Aβ species | |
| dc.year.issued | 2018 |
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