Cardiac-induced cerebral pulsatility, brain structure, and cognition in middle and older-aged adults

NeuroImage

卷:233

Vikas Agarwal¹  Sang-Young Kim²  Jack Doman³  M. Ilyas Kamboh⁴  Yu Cheng⁵  James T. Becker⁵  Anto Bagic⁵  Beth Snitz⁶  Yue-Fang Chang⁷  Tae Kim⁸  Annie Cohen⁸  Rebecca Roush⁸  Theodore J Huppert⁹ 

[1] Corresponding author at: Department of Radiology, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, USA.;

[2] Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA;

[3] Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, USA;

[4] Department of Neurology, University of Pittsburgh, Pittsburgh, USA;

[5] Department of Neurosurgery, University of Pittsburgh, Pittsburgh, USA;

[6] Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA;

[7] Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA;

[8] Departments of Statistics and Biostatistics, University of Pittsburgh, Pittsburgh, USA;

关键词: Cerebral pulsatility;    Resting-state functional MRI;    Brain volume;    Volume segmentation;    Atrophy;    Hippocampus;   

DOI  :  

来源: DOAJ

【 摘 要 】

Changes of cardiac-induced regional pulsatility can be associated with specific regions of brain volumetric changes, and these are related with cognitive alterations. Thus, mapping of cardiac pulsatility over the entire brain can be helpful to assess these relationships. A total of 108 subjects (age: 66.5 ± 8.4 years, 68 females, 52 healthy controls, 11 subjective cognitive decline, 17 impaired without complaints, 19 MCI and 9 AD) participated. The pulsatility map was obtained directly from resting-state functional MRI time-series data at 3T. Regional brain volumes were segmented from anatomical MRI. Multidomain neuropsychological battery was performed to test memory, language, attention and visuospatial construction. The Montreal Cognitive Assessment (MoCA) was also administered. The sparse partial least square (SPLS) method, which is desirable for better interpreting high-dimensional variables, was applied for the relationship between the entire brain voxels of pulsatility and 45 segmented brain volumes. A multiple holdout SPLS framework was used to optimize sparsity for assessing the pulsatility-volume relationship model and to test the reliability by fitting the models to 9 different splits of the data. We found statistically significant associations between subsets of pulsatility voxels and subsets of segmented brain volumes by rejecting the omnibus null hypothesis (any of 9 splits has p < 0.0056 (=0.05/9) with the Bonferroni correction). The pulsatility was positively associated with the lateral ventricle, choroid plexus, inferior lateral ventricle, and 3rd ventricle and negatively associated with hippocampus, ventral DC, and thalamus volumes for the first pulsatility-volume relationship. The pulsatility had an additional negative relationship with the amygdala and brain stem volumes for the second pulsatility-volume relationship. The spatial distribution of correlated pulsatility was observed in major feeding arteries to the brain regions, ventricles, and sagittal sinus. The indirect mediating pathways through the volumetric changes were statistically significant between the pulsatility and multiple cognitive measures (p < 0.01). Thus, the cerebral pulsatility, along with volumetric measurements, could be a potential marker for better understanding of pathophysiology and monitoring disease progression in age-related neurodegenerative disorders.

【 授权许可】

Unknown