Florbetaben [F-18] 300MBq solution for injection vials

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

Abstract licence: CC BY 4.0

Several studies have demonstrated strong agreement between routine clinical visual assessment and quantification, suggesting that quantification approaches could support assessment by less experienced readers or in challenging cases. However, all studies to date have implemented a retrospective case collection, and challenging cases were generally underrepresented. Methods: We included all participants (n = 741) from the AMYPAD diagnostic and patient management study with available baseline amyloid PET quantification. Quantification was done with the PET-only AmyPype pipeline, providing global Centiloid and regional z scores. Visual assessment was performed by local readers for the entire cohort. From the total cohort, we selected a subsample of 85 cases for which the amyloid status based on the local reader's visual assessment and the Centiloid classification (cutoff = 21) was discordant or that were assessed with low confidence (i.e., ≤3 on a 5-point scale) by the local reader. In addition, concordant negative (n = 8) and positive (n = 8) scans across tracers were selected. In this sample (n = 101 cases; [18F]flutemetamol, n = 48; [18F]florbetaben, n = 53), the visual assessments and corresponding confidence by 5 certified independent central readers were captured before and after disclosure of the quantification results. Results: For the whole AMYPAD diagnostic and patient management study cohort, overall assessment by local readers highly agreed with Centiloid status (κ = 0.85, 92.3% agreement). This was consistently observed within disease stages (subjective cognitive decline-plus, κ = 0.82, 92.3% agreement; mild cognitive impairment, κ = 0.80, 89.8% agreement; dementia, κ = 0.87, 94.6% agreement). Across all central reader assessments in the challenging subsample, quantification of global Centiloid and regional z scores was considered supportive of visual reads in 70.3% and 49.3% of assessments, respectively. After disclosure of the quantitative results, we observed improvement in concordance across the 5 readers (baseline κ = 0.65, 65.3% agreement; κ after disclosure = 0.74, 73.3% agreement) and a significant increase in reader confidence (baseline mean (M) = 4.0 vs. M after disclosure = 4.34, Wilcoxon statistic (W) = 101,056, P Conclusion: In this clinical study enriched for challenging amyloid PET cases, we demonstrate the value of quantification to support visual assessment. After disclosure, both interreader agreement and confidence showed significant improvement. These results are important considering the arrival of antiamyloid therapies, which used the Centiloid metric for trial inclusion and target engagement. Moreover, quantification could support determination of amyloid-β status with high certainty, an important factor for treatment initiation.

Abstract licence: CC BY