Zhen Fan (United Kingdom)
Invicro, A Konica Minolta Company
Imaging Analysis
Dr Zhen Fan works as a senior PET Modeller at Invicro (a Konica Minolta company) and an Honorary Research Fellow at Imperial College London. She gained her PhD in neuroimaging modelling and previously worked as a research assistant at the Faculty of medicine at Imperial College London. She possesses around 12 years of experience working with PET/MRI imaging analysis in human and preclinical trails, for which she maintains an excellent track record of publications and international awards. She worked in the development team in IQ analytics (e.g. lead on DAT-IQ and VMAT-IQ), a novel mathematical modelling to improve imaging biomarker quantification in neurodegenerative disease in Invicro. Possessing advanced knowledge of medical image modelling skills and rich working experience with PET, MRI and fMRI data in novel tracer development, discovery, observational, cross-sectional, longitudinal, blocking and drug intervention trials. She works as the Analysis Lead for both preclinical and clinical imaging projects with multiple pharmaceutical companies, including GlaxoSmithKline, Biogen, Boehringer Ingelheim, Roche, Michael J. Fox Foundation, Axovant Sciences Inc, Lundbeck, Morphic Therapeutics, Acadia Pharmaceuticals, Curasen, Asceneuron.S.A, Heptares Therapeutics, Inflazome, Cortexyme, Yumanity Therapeutics, Origenis GmbH, Eisai, Pliant Therapeutics, Saniona et al. 1 – Invicro, Needham, MA, USA 2 – Imperial College London, London UK

Presenter of 1 Presentation

 Conference Calendar

INCREASING THE POWER OF [18F]AV133 PET TO MEASURE LONGITUDINAL CHANGES IN PARKINSON’S DISEASE: IDENITIFICATION OF OPTIMAL REFERENCE AND TARGET REGIONS

Session Name
4330 - SYMPOSIUM: PET 01 (ID 117)
Session Type
SYMPOSIUM
Date
Sat, 01.04.2023
Session Time
08:40 - 10:40
Room
ONSITE - HALL G3
Presenter
Lecture Time
08:40 - 08:55

Abstract

Aims

[18F]AV133 PET is a biomarker of nigral-striatal dopaminergic function that putatively measures reduced vesicular monoamine transporter (VMAT-2) density in progressing Parkinson’s disease. This study aimed to identify the optimal target and reference regions for quantifying [18F]AV133 so as to maximise power in future clinical imaging trials of novel therapies.

Methods

The Parkinson Progression Marker Initiative (PPMI) is a multicentre, international observational clinical study to assess PD biomarkers, including [18F]AV133 PET and Ioflupane (DaT). Longitudinal [18F]AV133 PET imaging data was available for 38 subjects, each of whom were followed for up to 4 years. Emission data were acquired for 10 mins between 80--90 post-injection of the tracer. Each subject had an associated T1 MRI which was used for inter-subject registration into stereotaxic space (MNI152). Data were quantified using an SUVR approach – permutations of five reference and six target regions were evaluated to determine maximal power of longitudinal signal change (S:N) (Fig1). [18F]AV133 data were also compared with the DaT data obtained from the same subjects.

fig1.longitudinal_analysis.jpg

Results

[18F]AV133 quantification using the cerebral white matter as the reference region and putamen as the target region showed the highest power (S:N = 1.1). [18F]AV133 showed a 75% and 71% increase in statistical power in year 1 and year 2 follow up when compared with DaT leading to a ~46% reduction in sample size required to detect the same pharmacodynamic changes (Fig2).

fig2.power_analysis.jpg

Conclusions

Cerebral white matter and putamen were selected as the optimal reference and target regions for [18F]AV133 quantification. With the limitation of small sample size, [18F]AV133 provides increased sensitivity to longitudinal changes in PD over existing DaT imaging, increasing power to detect pharmacodynamic responses and likely reduced sample sizes in future clinical imaging trials.

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