Development of a histologically validated segmentation protocol for the hippocampal body

Steve, Trevor A.; Yasuda, Clarissa Lin; Coras, Roland; Lail, Mohjevan; Blümcke, Ingmar; Livy, Daniel J.; Malykhin, Nikolai; Gross, Donald

doi:10.1016/j.neuroimage.2017.06.008

Cited by 15 publications

(23 citation statements)

References 39 publications

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“…Given the above-mentioned contribution of different hippocampal subfields to brain function, imaging studies using non-invasive MRI techniques with anatomically adjusted hippocampal annotation may unravel still unobserved clinical-pathological correlations. In fact, several studies have employed automatic, semiautomatic, and manual segmentation techniques to evaluate volumetric changes in the hippocampal subfields in conditions such as Alzheimer's disease, post-traumatic stress disorder, schizophrenia, major depression, epilepsy, and aging ( 45 – 51 ). However, most techniques fail to properly delineate hippocampal subfields, which can induce misleading conclusions.…”

Section: Discussionmentioning

confidence: 99%

Manual Hippocampal Subfield Segmentation Using High-Field MRI: Impact of Different Subfields in Hippocampal Volume Loss of Temporal Lobe Epilepsy Patients

et al. 2018

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In patients with temporal lobe epilepsy (TLE), presurgical magnetic resonance imaging (MRI) often reveals hippocampal atrophy, while neuropathological assessment indicates the different types of hippocampal sclerosis (HS). Different HS types are not discriminated in MRI so far. We aimed to define the volume of each hippocampal subfield on MRI manually and to compare automatic and manual segmentations for the discrimination of HS types. The T2-weighted images from 14 formalin-fixed age-matched control hippocampi were obtained with 4.7T MRI to evaluate the volume of each subfield at the anatomical level of the hippocampal head, body, and tail. Formalin-fixed coronal sections at the level of the body of 14 control cases, as well as tissue samples from 24 TLE patients, were imaged with a similar high-resolution sequence at 3T. Presurgical three-dimensional (3D) T1-weighted images from TLE went through a FreeSurfer 6.0 hippocampal subfield automatic assessment. The manual delineation with the 4.7T MRI was identified using Luxol Fast Blue stained 10-μm-thin microscopy slides, collected at every millimeter. An additional section at the level of the body from controls and TLE cases was submitted to NeuN immunohistochemistry for neuronal density estimation. All TLE cases were classified according to the International League Against Epilepsy's (ILAE's) HS classification. Manual volumetry in controls revealed that the dentate gyrus (DG)+CA4 region, CA1, and subiculum accounted for almost 90% of the hippocampal volume. The manual 3T volumetry showed that all TLE patients with type 1 HS (TLE-HS1) had lower volumes for DG+CA4, CA2, and CA1, whereas those TLE patients with HS type 2 (TLE-HS2) had lower volumes only in CA1 (p ≤ 0.038). Neuronal cell densities always decreased in CA4, CA3, CA2, and CA1 of TLE-HS1 but only in CA1 of TLE-HS2 (p ≤ 0.003). In addition, TLE-HS2 had a higher volume (p = 0.016) and higher neuronal density (p < 0.001) than the TLE-HS1 in DG + CA4. Automatic segmentation failed to match the manual or histological findings and was unable to differentiate TLE-HS1 from TLE-HS2. Total hippocampal volume correlated with DG+CA4 and CA1 volumes and neuronal density. For the first time, we also identified subfield-specific pathology patterns in the manual evaluation of volumetric MRI scans, showing the importance of manual segmentation to assess subfield-specific pathology patterns.

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Section: Discussionmentioning

confidence: 99%

Manual Hippocampal Subfield Segmentation Using High-Field MRI: Impact of Different Subfields in Hippocampal Volume Loss of Temporal Lobe Epilepsy Patients

et al. 2018

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“…Aim : To determine the location of the borders of SUB/CA1, CA1/CA2, and CA2/CA3 relative to the length of the dark band in the hippocampal body, repeating the study by Steve et al ().…”

Section: Resultsmentioning

confidence: 99%

“…The freehand line tool in ImageJ (Schneider et al, ) was used to measure the length of the dark band, drawing a line through the midpoint of the dark band starting at the most medial point of the DG (inferior anchor point) and ending at the most superior medial point in the curvature of CA3 (superior anchor point; Figure b). Note that we chose to draw the line through the midpoint of the dark band, in contrast to Steve et al () who drew their line at the outer border of the SRLM on histology sections, as this boundary cannot be observed on MRI (see previous section). An advantage of using the midpoint is that the dark band is also visible on in vivo MRI, which would allow for in vivo application of this method in the future.…”

Section: Resultsmentioning

confidence: 99%

Characterization of hippocampal subfields using ex vivo MRI and histology data: Lessons for in vivo segmentation

et al. 2019

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Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing.Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2-weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA-stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body-like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols. K E Y W O R D S ex vivo, hippocampal subfields, histology, in vivo, MRI, segmentation Robin de Flores and David Berron contributed equally to this work.

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“…Hippocampal subfield segmentation is based on distinct histological differences which define the subfield boundaries (Ding & Van Hoesen, ; Duvernoy et al, ). As these histological features are not visible on MRI, segmentation protocols have been developed based on geometric rules derived from anatomical specimens with recent studies providing histological validation of some segmentation protocols (Steve et al, ). The majority of hippocampal segmentation protocols have been developed for the hippocampal body with the segmentation of the hippocampal head having been demonstrated to show the greatest disagreement among protocols (Yushkevich et al, ).…”

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confidence: 99%

“…The feasibility of applying a single common method of hippocampal subfield segmentation to the hippocampal head, body, and tail was assessed for Hippocampus 1. Subfield segmentation was performed on slices obtained with CMPR for the head, body, and tail based on our previously published manual protocol providing the following subfields: CA1, CA2, and CA3/CA4/dentate gyrus (Figure 6) (Steve et al, ).…”

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Curved multiplanar reformatting provides improved visualization of hippocampal anatomy

et al. 2019

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There is a growing body of literature studying changes in hippocampal subfields in a variety of different neurological conditions, but this work has mainly focused on the hippocampal body given challenges in visualization of hippocampal anatomy in the head and tail when sectioned in the typical coronal image plane. Curved multiplanar reformatting (CMPR) is an image reconstruction method that can improve visualization of complex three‐dimensional structures. The objective of this study was to determine whether CMPR could facilitate visualization of the human hippocampal anatomy along the entire caudal–rostral axis. CMPR was applied to high‐resolution magnetic resonance imaging acquired ex vivo on four cadaveric hippocampal specimens at 4.7 T (T2‐weighted, 0.2 × 0.2 × 0.5 mm3). CMPR provided clear visualization of the classic “interlocking C” appearance of the dentate gyrus and cornu ammonis along the entire caudal–rostral axis including the head and tail, which otherwise show complex anatomy on the standard coronal slices. CMPR facilitated visualization of hippocampal anatomy providing the impetus to develop simplified approaches to delineate subfields along the entire hippocampus including the usually neglected head and tail.

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Development of a histologically validated segmentation protocol for the hippocampal body

Cited by 15 publications

References 39 publications

Manual Hippocampal Subfield Segmentation Using High-Field MRI: Impact of Different Subfields in Hippocampal Volume Loss of Temporal Lobe Epilepsy Patients

Manual Hippocampal Subfield Segmentation Using High-Field MRI: Impact of Different Subfields in Hippocampal Volume Loss of Temporal Lobe Epilepsy Patients

Characterization of hippocampal subfields using ex vivo MRI and histology data: Lessons for in vivo segmentation

Curved multiplanar reformatting provides improved visualization of hippocampal anatomy

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