Exploring glymphatic system alterations in iRBD and Parkinson's disease using automated DTI-ALPS analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023884%3A_____%2F25%3A00010193" target="_blank" >RIV/00023884:_____/25:00010193 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21460/25:00383327 RIV/00216208:11110/25:10498251 RIV/00064165:_____/25:10498251

Výsledek na webu

<a href="https://www.nature.com/articles/s41531-025-00921-4" target="_blank" >https://www.nature.com/articles/s41531-025-00921-4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41531-025-00921-4" target="_blank" >10.1038/s41531-025-00921-4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploring glymphatic system alterations in iRBD and Parkinson's disease using automated DTI-ALPS analysis

Popis výsledku v původním jazyce

Diffusion tensor image analysis along the perivascular space (DTI-ALPS) is a potential non-invasive marker of glymphatic function that typically relies on manual region of interest (ROI) placement. This study compared ALPS indices in treatment-na & iuml;ve, de novo diagnosed patients with Parkinson's disease (PD), patients with isolated REM behavior disorder (iRBD), and healthy controls using both manual and automatic approaches to the ROI selection used in ALPS-index calculation. ALPS indices were analyzed bilaterally and correlated with clinical severity (MDS-UPDRS) and nigrostriatal denervation (DAT-SPECT). ANCOVA revealed significant inter-group differences using both manual (p = 0.018) and automatic (p = 0.002) ROI selection methods. The automatic ROI selection approach showed significantly lower ALPS indices in PD compared to controls (p = 0.001) and iRBD (p = 0.009). ALPS indices correlated with symptom severity and nigrostriatal denervation. These findings underscore the reliability of the automatic ROI placement approach for ALPS index calculation and may indicate early glymphatic alterations in Parkinson's disease.

Název v anglickém jazyce

Exploring glymphatic system alterations in iRBD and Parkinson's disease using automated DTI-ALPS analysis

Popis výsledku anglicky

Diffusion tensor image analysis along the perivascular space (DTI-ALPS) is a potential non-invasive marker of glymphatic function that typically relies on manual region of interest (ROI) placement. This study compared ALPS indices in treatment-na & iuml;ve, de novo diagnosed patients with Parkinson's disease (PD), patients with isolated REM behavior disorder (iRBD), and healthy controls using both manual and automatic approaches to the ROI selection used in ALPS-index calculation. ALPS indices were analyzed bilaterally and correlated with clinical severity (MDS-UPDRS) and nigrostriatal denervation (DAT-SPECT). ANCOVA revealed significant inter-group differences using both manual (p = 0.018) and automatic (p = 0.002) ROI selection methods. The automatic ROI selection approach showed significantly lower ALPS indices in PD compared to controls (p = 0.001) and iRBD (p = 0.009). ALPS indices correlated with symptom severity and nigrostriatal denervation. These findings underscore the reliability of the automatic ROI placement approach for ALPS index calculation and may indicate early glymphatic alterations in Parkinson's disease.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

npj Parkinsons Disease

ISSN

2373-8057

e-ISSN

—

Svazek periodika

11

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

001467286900001

EID výsledku v databázi Scopus

2-s2.0-105003242033