Biomedical subjects

Anastasia Yendiki

Publications and source records attributed to Anastasia Yendiki.

3 recordsLinked to original sources

PubMed2025

The cellular associates of late life changes in white matter microstructure.

The microstructural architecture of white matter supporting information flow across local circuits and large-scale networks changes throughout the lifespan. However, the genetic and cellular factors underlying age-related variations in white matter microstructure have yet to be established. Here, we examined the genetic associates of individual differences in diffusion-based measures of white matter in a population-based cohort (N=29,862) from the UK Biobank. Estimates of heritability from Genome-Wide Association Study (GWAS) data revealed that genetic factors are linked to population variability in 96.1% of 432 tract microstructural measures. The presence of shared genetic influences was observed to be greater within, relative to between, broad tract classes (commissural, association, projection, and complex cerebellar). Age associations with microstructural changes were estimated across diffusivity measures, with association class tracts showing the greatest vulnerability to age-related decline in older adults. Analyses of imputed cellular associates of age-related changes in white matter revealed a preferential relationship with cell gene markers of oligodendrocytes and other glial cell types, with sparse relationships observed for inhibitory and excitatory cells. These data indicate that white matter tract microstructure is shaped by genetic factors and suggest a role for glial cell-related transcripts in late-life changes in the structural wiring properties of the human brain.

Aging↗

PubMed2007

Recovery of total I-131 activity within focal volumes using SPECT and 3D OSEM.

We experimentally investigated the SPECT recovery of I-131 activity in multiple spheres located simultaneously at different locations within a cylindrical phantom that had an elliptical cross section. The sphere volumes ranged from 209 cc down to 4.2 cc. A Prism 3000 camera and two types of parallel-hexagonal-hole collimation were employed: high energy (HE) and ultra high energy (UHE). Using appropriately-different 3D models of the point source response function for the two types of collimation, approximately the same recovery of activity could be achieved with either collimation by 3D OSEM reconstruction. The recovery coefficient was greater with no background activity in the phantom by 0.10, on average, compared to that with background. In the HE collimation case, the activity recovery was considerably better for all volumes using 3D OSEM reconstruction than it had been in the past using 1D SAGE reconstruction. Recovery-coefficient-based correction in a simulated patient case involving spherical tumours moderately improved the activity estimates (average error reduced from 14% to 9% for UHE collimation, and from 15% to 11% for HE collimation). For a test case with HE collimation, increasing the projection-image sampling density while decreasing the image voxel size increased the recovery coefficient by 0.075 on average, and, if used in a full set of calibration measurements of recovery coefficient versus volume, might lead to further improvement in accuracy for the patient case.

Biophysical Phenomena↗

PubMed2006

Analysis of observer performance in known-location tasks for tomographic image reconstruction.

We consider the task of detecting a statistically varying signal of known location on a statistically varying background in a reconstructed tomographic image. We analyze the performance of linear observer models in this task. We show that, if one chooses a suitable reconstruction method, a broad family of linear observers can exactly achieve the optimal detection performance attainable with any combination of a linear observer and linear reconstructor. This conclusion encompasses several well-known observer models from the literature, including models with a frequency-selective channel mechanism and certain types of internal noise. Interestingly, the "optimal" reconstruction methods are unregularized and in some cases quite unconventional. These results suggest that, for the purposes of designing regularized reconstruction methods that optimize lesion detectability, known-location tasks are of limited use.

Algorithms↗