Insights into hippocampal perfusion using high-resolution, multi-modal 7T MRI

Abstract

We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 tesla arterial spin labeling (ASL) data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and already detectable with 50 perfusion-weighted images per subject, acquired in 5 min. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometric properties, macrovasculature, and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterizing hippocampal perfusion.

Keywords: 7 tesla MRI; hippocampus; perfusion; subfields; vasculature.

Fig. 1.

Perfusion mapping in the hippocampus. (A) The figure displays perfusion values (mL/100 g/min) mapped on folded and unfolded hippocampal surfaces. The dotted and solid arrows indicate the anterior–posterior and proximal–distal (from neocortical tissue) axes, respectively. Subfield boundaries, derived from cytoarchitectonic features of the BigBrain atlas, are overlaid on the unfolded map. (B) Subfield averages, color-coded based on the subfield atlas overlaid on maps in A, are presented for each subject and hemisphere (circles for the left hemisphere, diamonds for the right hemisphere), as well as per vertex (semi-transparent dots averaged across subjects and hemispheres). Pairwise comparisons between subfield averages are depicted as heatmaps, with FDR_BH-corrected P-values indicated by asterisks: *P< 0.05, **P< 0.01, ***P< 0.005.

Fig. 2.

Evolution of high-resolution perfusion maps. The figure illustrates the progression of high-resolution perfusion maps, showcasing the percentage difference in mean perfusion (solid lines, Top) and variability (dotted lines, Bottom) across the entire hippocampus (in black) and individual subfields (color-coded). The evolution is presented as a function of (A) the number of included subjects or (B) runs. (C) Additionally, the figure depicts the unfolding of the average perfusion map and its evolution as a function of the number of included runs (rows) and subjects (columns) in consecutive order.

Fig. 3.

Hippocampal vasculature and perfusion relationship. (A) Three-dimensional reconstruction of a subject’s macrovasculature in close proximity to the right hippocampus, showcasing delineated vessel segments. (B) Hippocampal vessel distance (mm) depicted on an unfolded hippocampal surface. Strip plots display color-coded subfield averages for each subject, including left hemisphere (circles) and right hemisphere (diamonds), along with per-vertex values (i.e., averages across subjects and hemispheres shown as semi-transparent dots). Heatmaps illustrate pairwise comparisons between subfield averages, with FDR_BH-corrected P-values indicated by asterisks: *P< 0.05, **P< 0.01, ***P< 0.005. (C) Similar to (B), but representing vessel diameter (mm) of the nearest vessel. (D) Scatter plot illustrating the relationship between vertex-wise mean perfusion (mL/100 g/min) and the shortest distance to a vessel (mm), stratified by respective vessel diameter (color-coded as thinner or thicker than 2 mm). Linear fits for each group are depicted by solid and dashed black lines. (E) Similar to (D), but contrasting with perfusion variability determined by the coefficient of variation across all maps (i.e., across runs and subjects).

Fig. 4.

Between-feature correlations. (A and B) Heatmaps depicting the correlations between different features (SI Appendix, Figs. S3 and S4) on their vertex-wise averages, with corresponding Pearson’s correlation coefficients annotated. Significant correlations, after correcting for spatial autocorrelation and multiple comparisons, are indicated by bold annotations. Panels (C–E) illustrate the correlations between perfusion and various hippocampal morphometric and staining intensity-based features derived from the BigBrain sample. In panel (E), the point plot displays permuted Pearson’s correlation coefficients represented by semi-transparent black markers, which were used to calculate color-coded significance levels.