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Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging.
Neuroimage Clin 2019; 22:101771NC

Abstract

Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and 18F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the 18F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on 18F-FDG SUVR. CSF measures included Aβ1-42, Aβ1-40, T-tau, P-tau181, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = -0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters.

Authors+Show Affiliations

Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium.Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium.Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium.Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Icometrix, R&D, Leuven, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium.Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium. Electronic address: steven.staelens@uantwerpen.be.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30927601

Citation

Ottoy, Julie, et al. "Association of Short-term Cognitive Decline and MCI-to-AD Dementia Conversion With CSF, MRI, Amyloid- and 18F-FDG-PET Imaging." NeuroImage. Clinical, vol. 22, 2019, p. 101771.
Ottoy J, Niemantsverdriet E, Verhaeghe J, et al. Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging. Neuroimage Clin. 2019;22:101771.
Ottoy, J., Niemantsverdriet, E., Verhaeghe, J., De Roeck, E., Struyfs, H., Somers, C., ... Staelens, S. (2019). Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging. NeuroImage. Clinical, 22, p. 101771. doi:10.1016/j.nicl.2019.101771.
Ottoy J, et al. Association of Short-term Cognitive Decline and MCI-to-AD Dementia Conversion With CSF, MRI, Amyloid- and 18F-FDG-PET Imaging. Neuroimage Clin. 2019;22:101771. PubMed PMID: 30927601.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging. AU - Ottoy,Julie, AU - Niemantsverdriet,Ellis, AU - Verhaeghe,Jeroen, AU - De Roeck,Ellen, AU - Struyfs,Hanne, AU - Somers,Charisse, AU - Wyffels,Leonie, AU - Ceyssens,Sarah, AU - Van Mossevelde,Sara, AU - Van den Bossche,Tobi, AU - Van Broeckhoven,Christine, AU - Ribbens,Annemie, AU - Bjerke,Maria, AU - Stroobants,Sigrid, AU - Engelborghs,Sebastiaan, AU - Staelens,Steven, Y1 - 2019/03/13/ PY - 2018/09/13/received PY - 2019/01/08/revised PY - 2019/03/10/accepted PY - 2019/3/31/pubmed PY - 2020/1/22/medline PY - 2019/3/31/entrez KW - Alzheimer's disease KW - Biomarkers KW - Cerebrospinal fluid KW - Florbetapir KW - Hippocampal volume KW - Mild cognitive impairment KW - Positron emission tomography SP - 101771 EP - 101771 JF - NeuroImage. Clinical JO - Neuroimage Clin VL - 22 N2 - Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and 18F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the 18F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on 18F-FDG SUVR. CSF measures included Aβ1-42, Aβ1-40, T-tau, P-tau181, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = -0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters. SN - 2213-1582 UR - https://www.unboundmedicine.com/medline/citation/30927601/Association_of_short_term_cognitive_decline_and_MCI_to_AD_dementia_conversion_with_CSF_MRI_amyloid__and_18F_FDG_PET_imaging_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S2213-1582(19)30121-4 DB - PRIME DP - Unbound Medicine ER -