Details

Autor(en) / Beteiligte

• Thal, Dietmar Rudolf
• Beach, Thomas G
• Zanette, Michelle
• Lilja, Johan
• Heurling, Kerstin
• Chakrabarty, Aruna
• Ismail, Azzam

Titel

Estimation of amyloid distribution by [.sup.18F]flutemetamol PET predicts the neuropathological phase of amyloid [beta]-protein deposition

Ist Teil von

• Acta neuropathologica, 2018-10, Vol.136 (4), p.557

Ort / Verlag

Springer

Erscheinungsjahr

2018

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The deposition of the amyloid [beta]-protein (A[beta]) in senile plaques is one of the histopathological hallmarks of Alzheimer's disease (AD). A[beta]-plaques arise first in neocortical areas and, then, expand into further brain regions in a process described by 5 phases. Since it is possible to identify amyloid pathology with radioactive-labeled tracers by positron emission tomography (PET) the question arises whether it is possible to distinguish the neuropathological A[beta]-phases with amyloid PET imaging. To address this question we reassessed 97 cases of the end-of-life study cohort of the phase 3 [.sup.18F]flutemetamol trial (ClinicalTrials.gov identifiers NCT01165554, and NCT02090855) by combining the standardized uptake value ratios (SUVRs) with pons as reference region for cortical and caudate nucleus-related [.sup.18F]flutemetamol-retention. We tested them for their prediction of the neuropathological pattern found at autopsy. By defining threshold levels for cortical and caudate nucleus SUVRs we could distinguish different levels of [.sup.18F]flutemetamol uptake termed PET-A[beta] phase estimates. When comparing these PET-A[beta] phase estimates with the neuropathological A[beta]-phases we found that PET-A[beta] phase estimate 0 corresponded with A[beta]-phases 0-2, 1 with A[beta]-phase 3, 2 with A[beta]-phase 4, and 3 with A[beta]-phase 5. Classification using the PET-A[beta] phase estimates predicted the correct A[beta]-phase in 72.16% of the cases studied here. Bootstrap analysis was used to confirm the robustness of the estimates around this association. When allowing a range of ± 1 phase for a given A[beta]-phase correct classification was given in 96.91% of the cases. In doing so, we provide a novel method to convert SUVR-levels into PET-A[beta] phase estimates that can be easily translated into neuropathological phases of A[beta]-deposition. This method allows direct conclusions about the pathological distribution of amyloid plaques (A[beta]-phases) in vivo. Accordingly, this method may be ideally suited to detect early preclinical AD-patients, to follow them with disease progression, and to provide a more precise prognosis for them based on the knowledge about the underlying pathological phase of the disease.