Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI

Abstract

Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI, subfield delineation in MRI literature has largely relied on heuristic geometric rules, the validity of which with respect to the underlying anatomy is largely unknown. The development and evaluation of such rules are challenged by the limited availability of data linking MRI appearance to microscopic hippocampal anatomy, particularly in three dimensions (3D). The present paper, for the first time, demonstrates the feasibility of labeling hippocampal subfields in a high resolution volumetric MRI dataset based directly on microscopic features extracted from histology. It uses a combination of computational techniques and manual post-processing to map subfield boundaries from a stack of histology images (obtained with 200μm spacing and 5μm slice thickness; stained using the Kluver-Barrera method) onto a postmortem 9.4Tesla MRI scan of the intact, whole hippocampal formation acquired with 160μm isotropic resolution. The histology reconstruction procedure consists of sequential application of a graph-theoretic slice stacking algorithm that mitigates the effects of distorted slices, followed by iterative affine and diffeomorphic co-registration to postmortem MRI scans of approximately 1cm-thick tissue sub-blocks acquired with 200μm isotropic resolution. These 1cm blocks are subsequently co-registered to the MRI of the whole HF. Reconstruction accuracy is evaluated as the average displacement error between boundaries manually delineated in both the histology and MRI following the sequential stages of reconstruction. The methods presented and evaluated in this single-subject study can potentially be applied to multiple hippocampal tissue samples in order to construct a histologically informed MRI atlas of the hippocampal formation.

Keywords: Hippocampus; Histology; MRI; Postmortem; Reconstruction; Subfields.

Figure 1

Examples of MRI segmentation protocols of subfields in the hippocampal body: (A) Van Leemput et al. (2009), (B) Mueller and Weiner (2009), (C) Yushkevich et al. (2010), (D) La Joie et al. (2010), (E) Bonnici et al. (2012), (F) Wisse et al. (2012). (Images reproduced with permission from publishers.)

Figure 2

Postmortem MR and histological imaging protocol of the human hippocampal formation (SEMS: spin echo multi-slice sequence).

Figure 3

Schematic of graph-theoretic slice stacking. The least-cost sequence of transformations from slice h_i to the reference slice are concatenated, thereby skipping distorted slices.

Figure 4

Zoomed-in views of histology slice displaying cell types in the hippocampal formation: pyramidal cell layer of cornu Ammonis subfields (A) CA1, (B) CA2, (C) CA3; (D) granule cell layer of dentate gyrus (DG); (E) pyramidal cell layer of subiculum

Figure 5

Histology image of hippocampal body shown (A) with subfield transition regions and (B) full segmentation. Zoomed-in views of transition regions are shown at 5× (left column) and 10× (right column): (C, D) SUB/CA1; (E, F) CA1/CA2; (G, H) CA2/CA3; (I, J) CA3/DG

Figure 6

Major stages of histology reconstruction pipeline shown schematically for one tissue sub-block.

Figure 7

Schematic of Diffeomorphic registration of histology slice h_i simultaneously to its neighbors h_i−1, h_i+1, and to corresponding MRI slice m_i.

Figure 8

Corresponding coronal MRI (left) and histology (right) sections following Diffeomorphic reconstruction. Sample evaluation curves for boundary displacement error computation are shown for the cornu Ammonis (CA, red) and stratum radiatum, stratum lacunosum-moleculare, and hippocampal sulcus (SRLM-HS, green).

Figure 9

Axial and sagittal views of reconstructed histology from two tissue sub-blocks following stages of reconstruction: slice stacking (A) with and (B) without graph-theoretic slice-skipping, (C) affine co-registration refinement with reference MRI, and (D) Diffeomorphic co-registration refinement with reference MRI. The reference MRI of each sub-block is shown in row (E).

Figure 10

Mean boundary displacement errors between stratum radiatum, lacunosum-moleculare, and hippocampal sulcus (SRLM-HS) and cornu Ammonis (CA) boundaries in reconstructed histology sub-blocks following application of sequential stages of volumetric reconstruction (error bars indicate standard deviation).

Figure 11

Coronal slices at level of hippocampal head, body, and tail comparing (A) tissue sub-block MRI with reconstructed histology following (B) affine and (C) Diffeomorphic co-registration refinement. Subfield labels are overlaid following affine and Diffeomorphic warping in column (D).

Figure 12

Axial and sagittal views of (A) whole-HF MRI; (B) tissue sub-block MRIs co-registered to whole-HF MRI using 9-degree-of-freedom scaling transforms; and (C) reconstructed histology resampled to the whole-HF MRI.

Figure 13

Hippocampal subfield labels derived from histology shown before and after manual refinement. All images and labels are in the anatomical space of the whole-HF MRI: (A) whole-HF MRI; (B) final reconstructed histology; and whole-HF MRI overlaid with subfield labels (C) before and (D) after manual refinement.

Figure 14

Hippocampal subfield labels derived from histology reconstructed in 3D (A) before and (B) after manual label refinement.

Figure 15

Coronal slices of whole-HF MRI overlaid with final subfield labels derived from histology following volumetric reconstruction. Slice positions are depicted on an axial section of whole-HF MRI.