18F-florbetaben Aβ imaging in mild cognitive impairment

Ong, Kevin; Villemagne, Victor L.; Bahar‐Fuchs, Alex; Lamb, Fiona; Chételat, Gaël; Raniga, Parnesh; Mulligan, Rachel; Salvado, Olivier; Pütz, Barbara; Roth, Katrin; Masters, Colin L.; Reininger, Cornelia; Rowe, Christopher C.

doi:10.1186/alzrt158

Cited by 50 publications

(36 citation statements)

References 54 publications

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“…In several studies, a non-amnestic MCI diagnosis has consistently low Aβ binding and therefore a non-AD phenotype [12]. While there is a general agreement that Aβ burden only displays a weak correlation with memory impairment or disease severity, MCI patients demonstrate a consistent link between elevated Aβ retention and poorer episodic memory performance [76,77].…”

Section: Aβ Imaging In Alzheimer's Diseasementioning

confidence: 99%

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

et al. 2018

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At the center of Alzheimer's disease pathogenesis is the aberrant aggregation of amyloid-β (Aβ) into oligomers, fibrils and plaques. Effective monitoring of Aβ deposition directly in patients is essential to assist anti-Aβ therapeutics in target engagement and participant selection. In the advent of approved anti-Aβ therapeutics, biomarkers will become of fundamental importance in initiating treatments having disease modifying effects at the earliest stage. Two well-established Aβ biomarkers are widely utilized: Aβ-binding ligands for positron emission tomography and immunoassays to measure Aβ42 in cerebrospinal fluid. In this review, we will discuss the current clinical, diagnostic and research state of biomarkers for Aβ pathology. Furthermore, we will explore the current application of blood-based markers to assess Aβ pathology.

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Section: Aβ Imaging In Alzheimer's Diseasementioning

confidence: 99%

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

et al. 2018

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“…The study population consisted of 45 patients with mild cognitive impairment (MCI) (mean age, 72.69 6 6.54 y; 29 men/16 women) and has previously been described in detail (20)(21)(22). This study was conducted in accordance with the Declaration of Helsinki and was approved by the Austin Health Human Research Ethics Committee.…”

Section: Participantsmentioning

confidence: 99%

Optimal Reference Region to Measure Longitudinal Amyloid-β Change with ¹⁸F-Florbetaben PET

et al. 2017

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Accurate measurement of changes in amyloid-b (Ab) deposition over time is important in longitudinal studies, particularly in anti-Ab therapeutic trials. To achieve this, the optimal reference region (RR) must be selected to reduce variance of Ab PET measurements, allowing early detection of treatment efficacy. The aim of this study was to determine the RR that allows earlier detection of subtle Ab changes using 18 Fflorbetaben PET. Methods: Forty-five patients with mild cognitive impairment (mean age 6 SD, 72.69 6 6.54 y; 29 men/16 women) who underwent up to 3 18 F-florbetaben scans were included. Baseline scans were visually classified as high (Ab1) or low (Ab2) amyloid. Six cortical regions were quantified using a standardized region-ofinterest atlas applied to the spatially normalized gray matter image obtained from segmentation of the baseline T1-weighted volumetric MRI. Four RRs (cerebellar gray matter [CGM], whole cerebellum [WCER], pons, and subcortical white matter [SWM]) were studied. The SUV ratio (SUVR) for each RR was calculated by dividing cortex activity by RR activity, with a composite SUVR averaged over 6 cortical regions. SUVR increase from baseline to 1 and 2 y, and percentage Ab deposition per year, were assessed across Ab1 and Ab2 groups. Results: SUVs for any RR were not significantly different over time. Percentage Ab accumulation per year derived from composite SUVR was 0.10 6 1.72 (Ab2) and 1.36 6 1.98 (Ab1) (P 5 0.02) for CGM and 0.13 6 1.47 and 1.32 6 1.75 (P 5 0.01), respectively, for WCER. Compared with baseline, the composite SUVR increase in Ab1 scans was significantly larger than in Ab2 scans at 1 y (P 5 0.04 [CGM]; P 5 0.03 [WCER]) and 2 y (P 5 0.02 [CGM]; P 5 0.01 [WCER]) using these 2 RRs. Significant SUVR changes using the pons as the RR were detected only at 2 y (P 5 0.46 [1 y], P 5 0.001 [2 y]). SUVR using the SWM as the RR showed no significant differences at either followup (P 5 0.39 [1 y], P 5 0.09 [2 y]). Conclusion: RR selection influences reliable early measurement of Ab changes over time. Compared with SWM and pons, which do not fulfil the RR requirements and have limited sensitivity to detect Ab changes, cerebellar RRs are recommended for 18 F-florbetaben PET because they allow earlier detection of Ab accumulation.

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“…Majority reads agreed with SUVR classification (kappa = 0.96). After 2 years, 18 (75 %) florbetaben PET-positive individuals had progressed to AD dementia compared with two (9.5 %) florbetaben PET-negative individuals, yielding a predictive accuracy of 83 % [95 % CI 61–94 %] [ 32 ] (Fig. 7 ).…”

Section: Florbetaben Efficacy Evaluation For β-Amyloid Detectionmentioning

confidence: 99%

Beta-amyloid imaging with florbetaben

Sabri

Seibyl

Rowe

et al. 2015

Clin Transl Imaging

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Florbetaben is a fluorine-18 (18F)-labeled stilbene derivative that was developed as a positron emission tomography (PET) tracer for routine clinical application to visualize β-amyloid plaques in the Alzheimer’s disease (AD) brain. The tracer successfully completed a global multicenter phase 0–III development program and was, as a consequence, recently approved by the US Food and Drug Administration and the European Medicines Agency. This review provides an overview on the florbetaben tracer characteristics and preclinical data leading to its human testing. Further, the favorable results of human pharmacokinetics, safety, and dosimetry evaluation of florbetaben are presented. Next, the results of the clinical testing of florbetaben are discussed, in which the tracer was shown to sensitively and specifically detect β-amyloid neuritic plaques, as evidenced by employing different gold standards (from clinical diagnosis to post mortem histopathology). The potential of florbetaben to predict AD dementia in cases of mild cognitive impairment and to assist in the differential diagnosis in cases of dementia is also described. Finally, potential clinical impact and clinical routine PET image acquisition and analysis protocols for florbetaben are discussed. Taken together, the evidence shows that florbetaben is a valuable β-amyloid-targeting PET tracer in the clinic with great potential to serve as a biomarker supporting clinical AD diagnosis.

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18F-florbetaben Aβ imaging in mild cognitive impairment

Cited by 50 publications

References 54 publications

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

Optimal Reference Region to Measure Longitudinal Amyloid-β Change with ¹⁸F-Florbetaben PET

Beta-amyloid imaging with florbetaben

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18F-florbetaben Aβ imaging in mild cognitive impairment

Cited by 50 publications

References 54 publications

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

Update on Biomarkers For Amyloid Pathology in Alzheimer’s Disease

Optimal Reference Region to Measure Longitudinal Amyloid-β Change with 18F-Florbetaben PET

Beta-amyloid imaging with florbetaben

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Optimal Reference Region to Measure Longitudinal Amyloid-β Change with ¹⁸F-Florbetaben PET