Validation of Diffusion Kurtosis Imaging as an Early-Stage Biomarker of Parkinson’s Disease in Animal Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F22%3A00548440" target="_blank" >RIV/68081731:_____/22:00548440 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/protocol/10.1007%2F978-1-0716-1712-0_18" target="_blank" >https://link.springer.com/protocol/10.1007%2F978-1-0716-1712-0_18</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-1-0716-1712-0_18" target="_blank" >10.1007/978-1-0716-1712-0_18</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Validation of Diffusion Kurtosis Imaging as an Early-Stage Biomarker of Parkinson’s Disease in Animal Models

Popis výsledku v původním jazyce

Diffusion kurtosis imaging (DKI), which is a mathematical extension of diffusion tensor imaging (DTI), assesses non-Gaussian water diffusion in the brain. DKI proved to be effective in supporting the diagnosis of different neurodegenerative disorders. Its sensitively detects microstructural changes in the brain induced by either protein accumulation, glial cell activation or neurodegeneration as observed in mouse models of Parkinson’s disease. We applied two experimental models of Parkinson’s disease to validate the diagnostic utility of DKI in early and late stage of disease pathology. We present two DKI analysis methods: (1) tract based spatial statistics (TBSS), which is a hypothesis independent data driven approach intended to evaluate white matter changes, and (2) region of interest (ROI) based analysis based on hypothesis of ROIs relevant for Parkinson’s disease, which is specifically used for gray matter changes. The main aim of this chapter is to provide detailed information of how to perform the DKI imaging acquisition and analysis in the mouse brain, which can be, to some extent translated to humans.

Název v anglickém jazyce

Validation of Diffusion Kurtosis Imaging as an Early-Stage Biomarker of Parkinson’s Disease in Animal Models

Popis výsledku anglicky

Diffusion kurtosis imaging (DKI), which is a mathematical extension of diffusion tensor imaging (DTI), assesses non-Gaussian water diffusion in the brain. DKI proved to be effective in supporting the diagnosis of different neurodegenerative disorders. Its sensitively detects microstructural changes in the brain induced by either protein accumulation, glial cell activation or neurodegeneration as observed in mouse models of Parkinson’s disease. We applied two experimental models of Parkinson’s disease to validate the diagnostic utility of DKI in early and late stage of disease pathology. We present two DKI analysis methods: (1) tract based spatial statistics (TBSS), which is a hypothesis independent data driven approach intended to evaluate white matter changes, and (2) region of interest (ROI) based analysis based on hypothesis of ROIs relevant for Parkinson’s disease, which is specifically used for gray matter changes. The main aim of this chapter is to provide detailed information of how to perform the DKI imaging acquisition and analysis in the mouse brain, which can be, to some extent translated to humans.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

<a href="/cs/project/EF16_013%2F0001775" target="_blank" >EF16_013/0001775: Modernizace a podpora výzkumných aktivit národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Neurodegenerative Diseases Biomarkers

ISBN

978-1-0716-1712-0

Počet stran výsledku

27

Strana od-do

429-455

Počet stran knihy

565

Název nakladatele

Humana

Místo vydání

New York

Kód UT WoS kapitoly

000868553200020