プロフィール詳細

プロジェクトを作成

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Dr. Viktoria K.に依頼

Germany

Neuroscientist | Science Communicator - prepared 100+ scientists to share their research | Product Manager

プロフィール概要

I have over 10 years of experience in research (neurobiology, molecular biology, genetics) combined with international experience (Germany, Russia, USA, Israel, Switzerland). I have organized and led three science communications organizations in Munich and prepared over 100 researchers to share talks about their fields. In my current roles a Product Manager I gained insights into market research, customer development, UX and UI.

専門分野

• ★ Neurobiology
• ☆ Phylogenetics
• ☆ Cognitive Science

サービス

• Research
• Consulting
• Product Development

Research Market Research, Feasibility Study, Fact Checking, Gray Literature Search, Systematic Literature Review, Secondary Data Collection

Consulting Scientific and Technical Consulting

Product Development Formulation

職務経験

Products Manager

Product People

5月 2020 - 現在

Applications Specialist

Neurotar

6月 2019 - 5月 2020

Scientific Coordinator

Max Planck Institute for Biochemistry

11月 2017 - 6月 2019

PhD candidate

German Center for Neurodegenerative Diseases

11月 2013 - 11月 2017

学歴

PhD | Neuroscience

Ludwig-Maximilians-University Munich

10月 2014 - 9月 2019

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

Automated spatial brain normalization and hindbrain white matter reference tissue give improved [18F]-florbetaben PET quantitation in Alzheimer´s model mice @ARTICLE{10.3389/fnins.2016.00045, AUTHOR= {Overhoff, Felix and Brendel, Matthias and Jaworska, Anna and Korzhova, Viktoria and Delker, Andreas and Probst, Federico and Focke, Carola and Gildehaus, Franz-Josef and Carlsen, Janette and Baumann, Karlheinz and Haass, Christian and Bartenstein, Peter and Herms, Jochen and Rominger, Axel}, TITLE= {Automated spatial brain normalization and hindbrain white matter reference tissue give improved [18F]-florbetaben PET quantitation in Alzheimer´s model mice}, JOURNAL= {Frontiers in Neuroscience}, VOLUME= {10}, YEAR= {2016}, NUMBER= {45}, URL= {http://www.frontiersin.org/brain_imaging_methods/10.3389/fnins.2016.00045/abstract}, DOI= {10.3389/fnins.2016.00045}, ISSN= {1662-453X}, ABSTRACT= {Preclinical PET studies of β-amyloid (Aβ) accumulation are of growing importance, but comparisons between research sites require standardized and optimized methods for quantitation. Therefore we aimed to evaluate systematically the 1) impact of an automated algorithm for spatial brain normalization, and 2) intensity scaling methods of different reference regions for Aβ-PET in a large dataset of transgenic mice. PS2APP mice in a six week longitudinal setting (N = 37) and another set of PS2APP mice at a histologically assessed narrow range of Aβ burden (N = 40) were investigated by [18F]-florbetaben PET. Manual spatial normalization by three readers at different training levels was performed prior to application of an automated brain spatial normalization and inter-reader agreement was assessed by Fleiss Kappa (κ). For this method the impact of templates at different pathology stages was investigated. Four different reference regions on brain uptake normalization were used to calculate frontal cortical standardized uptake value ratios (SUVRCTX/REF), relative to raw SUVCTX. Results were compared on the basis of longitudinal stability (Cohen’s d), and in reference to gold standard histopathological quantitation (Pearson’s R). Application of an automated brain spatial normalization resulted in nearly perfect agreement (all κ ≥ 0.99) between different readers, with constant or improved correlation with histology. Templates based on inappropriate pathology stage resulted in up to 2.9% systematic bias for SUVRCTX/REF. All SUVRCTX/REF methods performed better than SUVCTX both with regard to longitudinal stability (d ≥ 1.21 vs. d = 0.23) and histological gold standard agreement (R ≥ 0.66 vs. R ≥ 0.31). Voxel-wise analysis suggested a physiologically implausible longitudinal decrease of global mean scaling. The hindbrain white matter reference (Rmean = 0.75) was slightly superior to the brainstem (Rmean = 0.74) and the cerebellum (Rmean = 0.73). Automated brain normalization with reference region templates presents an excellent method to avoid the inter-reader variability in preclinical Aβ-PET scans. Intracerebral reference regions lacking Aβ pathology serve for precise longitudinal in vivo quantification of [18F]-florbetaben PET. Hindbrain white matter reference performed best when considering the composite of quality criteria.}} . Frontiers in Neuroscience.