PhD Scientific Days 2017

Oral Presentations: Neurosciences

DTI in early cognitive decline: Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging

Előadó neve

Gyebnár, Gyula

Előadó munkahelye

MR Research Centre

Előadó telefonszáma

+36202088580

Előadó e-mail címe

gyebnargyula@gmail.com

Az előadás címe

DTI in early cognitive decline: Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging

Szerző(k) neve és munkahelye

Gyula Gyebnár 1, Ádám Szabó 1, Enikő Sirály 2, Zsuzsanna Fodor 2, Anna Sákovics 3, Pál Salacz 2,4, Zoltán Hidasi PhD 2, Éva Csibri 2, Gábor Rudas , 1, Gábor Csukly , 2, Lajos R Kozák , 1
1 Magnetic Resonance Research Centre, Semmelweis University, Budapest
2 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest
3 National Institute of Clinical Neurosciences, Budapest
4 Department of Neurology, Péterfy Hospital and Trauma Centre, Budapest

Szekció

Oral Presentations: Neurosciences

Data of the presenter

Doctoral School: János Szentágothai Doctoral School of Neurosciences
Program: Clinical Neurological Research
Supervisor: Lajos R Kozák
E-mail address: gyebnargyula@gmail.com

Text of the abstract

Introduction
The intermediate stage between mild decrease of cognitive functioning in physiological aging and severe decline in dementia known as ‘mild cognitive impairment’ (MCI) has gained a lot of interest. The conversion rate from the amnestic subtype of MCI (aMCI) to Alzheimer Disease is much higher than from the non-amnestic subtype (naMCI), which underlines the significance of differentiation between these subtypes.
Aims
The primary aim of the study was to identify DTI-based biomarkers which can help differentiating patients with aMCI from naMCI and healthy subjects.
Method
Subjects with aMCI (n=18), naMCI (n=20), and healthy controls (n=27) were included in the study. Diffusion weighted and high resolution 3D T1W images were acquired at 3T. Thorough corrections and robust tensor fitting preceded the calculation of fractional anisotropy (FA) and mean diffusivity (MD) for voxel-wise and ROI level (Region of Interest) calculations. Study groups were compared by Analysis of Covariance (ANCOVA) with age and gender as covariates while correlations with neuropsychological tests were analyzed by Pearson correlation.
Results
Both voxel- and ROI-level approaches identified significantly higher MD in the aMCI group compared to controls or to the naMCI group in several grey and white matter regions, with most pronounced differences in the temporal lobes. FA also appeared lower in white matter ROI-s such as the left Cingulum. Voxel-wise analysis also showed increased MD in naMCI subjects relative to controls. Correlation of FA and MD with visual and verbal memory performance and verbal fluency were also found significant, with peaks in the temporal lobes, and logistic regression analysis proved that including FA improved the differentiation between MCI subtypes.
Conclusion
Our results suggest that DTI-measurements bring valuable information to conventional volumetric measurements, can aid the detection of Alzheimer’s disease in preclinical stage, and may also indicate early stages of non-Alzheimer type dementia.

Kind

Szabad

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

155

Authors (legacy)

Gyula Gyebnár 1, Ádám Szabó 1, Enikő Sirály 2, Zsuzsanna Fodor 2, Anna Sákovics 3, Pál Salacz 2,4, Zoltán Hidasi PhD 2, Éva Csibri 2, Gábor Rudas , 1, Gábor Csukly , 2, Lajos R Kozák , 1
1 Magnetic Resonance Research Centre, Semmelweis University, Budapest
2 Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest
3 National Institute of Clinical Neurosciences, Budapest
4 Department of Neurology, Péterfy Hospital and Trauma Centre, Budapest