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The Volume of Hippocampal Subfields in correlation with Middle Age Healthy Adults1Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States, 2University of Pittsburgh, Pittsburgh, PA, United States
Synopsis
As hippocampal volume has been extensively utilized as a diagnosing tool to confirm diagnosis of many neurological disorders, this study aims to employ the high resolution 7T data to segment the hippocampal subfields then correlate their volumes with the age of healthy adults’ population. The region encompassing the subregions left DG, CA2, and CA3 showed significant correlation with age, with a volume variation of approximately -1% per year. Other regions presented a trend towards reductions that did turn into significant. Future work will investigate if differences in the hippocampus subfields are correlated with cognitive performance in this population.
Introduction
The hippocampus (HC) has a primary role in encoding memories and learning processes (1). The degeneration of the hippocampus structure and function is extensively involved in many neurological disorders and normal aging (2). Many studies have also reported that hippocampal level of atrophy is impacted by socioeconomic disadvantage and individual hardships (3). Therefore, quantitative data on the morphology of the hippocampus has become one of the important tools to correlate with cognitive decline in adulthood. 7T MRI technology has been advancing to generate higher spatial resolution and contrast images, thus enabling higher anatomical visualization of the hippocampal subfields that are divided into cornu ammonis fields (CA1, CA2, CA3), the dentate gyrus (DG), the entorhinal area (EC), and the subiculum (Sub) (4). Over the past years, many studies have presented that the contribution and function of each subfield in a cognitive task vary depending on the stimuli and the environment, therefore, they are not equally impacted during neurodegeneration. However, they are extremely functionally interconnected and communicate with each other through selective ‘electrical’ pathways, for example CA1 matches the association output from CA3 with EC afferent input (5,6). These data have driven studies to improve their automated methods to segment these subfields and extract their volumes. The multiple atlas based automated segmentation of hippocampal subfields (ASHS) package that we use has shown excellent outcomes (7). In this group statistical analysis, we correlate the hippocampal subfields volumes of community dwelling healthy adult participants with their ages.Methods
In collaboration with ‘Community socioeconomic disadvantage in midlife relates to cortical morphology via neuroendocrine and cardiometabolic pathways’ research study group, data from 74 participants (age 61 ± 5.4 years) were collected for this work. All images were acquired using a 7T MRI scanner (Siemens Magnetom, Germany) and 16Tx + 32Rx TTT RF coil system (9,10). Two high resolution sequences were acquired per subject, 0.75 mm isotropic T1-weighted (T1w) Magnetization Prepared RApid Gradient Echo (MPRAGE) and (0.375 x 0.375 x 1.5 mm3) T2-weighted slanted (perpendicular to the main hippocampal axis) 2D turbo spin echo (TSE). Hippocampus segmentation pipeline and stages are described in the flowchart shown in figure (1). Image artifacts associated with magnetic field spatial inhomogeneities and receive coil nonuniformity are corrected in the bias field correction stage by using the SPM12 package, other image artifacts are removed in the denoising stage. All used Atlases are also denoised before initiating the automated segmentation. ITK-SNAP software is used for the ‘slice-by-slice’ manual correction, this stage is important to ensure reliable delineation and add refinements when necessary following the set guidelines (8). We used Person correlation coefficient to investigate the effect of age in the hippocampus subfields volume on this population, adjusting for sex. Moreover, the p-value threshold was adjusted for multiple comparisons using Bonferroni correction.Results
Image preprocessing and preparation for the automated segmentation are shown in figure (2), we are confident that this step improved the labeling accuracy of automated segmentation process. We inspected the hippocampus delineation and found that the discrimination between the subfield’s boundaries are well defined with high precision that continues throughout all slices, figure (3, a) shows a slice view of segmented hippocampal subfields. In some cases, inaccurate delineation may happen due to anatomical abnormalities which can be corrected during the manual segmentation stage as shown in figure (3, b). Statistical results of the hippocampal subfields volumes in correlation with age are illustrated in table (1) and figure (4). As expected, we observed a reduction in volume of each subfield in both hemispheres, however, a significant difference was observed in the left (DG+CA2+CA3): p-value=0.0012, reduction percentage per year= -1.0032, reduction in volume mm3/year= -6.906. No significant difference was observed in other subfields, but the following subfields presented a trend (p-value < 0.1) towards volume reduction: Left CA1: (p-value= 0.07, reduction %/year =-0.485, mm3/year=-3.76), Left Sub: (p-value 0.0913, %/year=-0.358, mm3/year=-4.72), Right CA1: (p-value=0.0632, %/year=-0.5178, mm3/year= -4.331), Right Sub: (p-value= 0.0829, %/year= -0.342, mm3/year= -4.617), Right Tail: (p-value= 0.0632, %/year=-0.572, mm3/year= -3.222).Discussion and Conclusion
In this preliminary study we correlated age of healthy adults with their hippocampal subfields volume. Employing the 7T MRI technology to acquire high resolution images facilitated the visualization of those sub anatomical regions. Atlas based automatic segmentation produced high labeling accuracy of the subfields that was validated during the quality assurance (manual correction) stage. After performing statistical analysis on this group, we found that hippocampal subfields undergo volume reduction with age at different level of trends. Left (DG+CA2+CA3) region showed a significant correlation between volume and age. While the other subfields were not significantly associated with age, several of them presented a trend towards volume reduction with age increase. Future work of this work includes: Hippocampal subfields volume correlation with cognitive performance, investigating the relation of volume reduction in other regions of the brain, and including the intracranial volume as a covariate in our analysis.Acknowledgements
this work was supported by the National Institutes of Health under award numbers: R01AG056043, R01MH111265, R01AG063525, T32MH119168. This research was also supported in part by the University of Pittsburgh Center for Research Computing (CRC) through the resources provided.
References
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