Automated subfield volumetric analysis of hippocampus in temporal lobe epilepsy using high-resolution T2-weighed MR imaging

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Abstract

Background and purpose

Automated subfield volumetry of hippocampus is desirable for use in temporal lobe epilepsy (TLE), but its utility has not been established. Automatic segmentation of hippocampal subfields (ASHS) and the new version of FreeSurfer software (ver.6.0) using high-resolution T2-weighted MR imaging are candidates for this volumetry. The aim of this study was to evaluate hippocampal subfields in TLE patients using ASHS as well as the old and new versions of FreeSurfer.

Materials and methods

We recruited 50 consecutive unilateral TLE patients including 25 with hippocampal sclerosis (TLE-HS) and 25 without obvious etiology (TLE-nonHS). All patients and 45 healthy controls underwent high-resolution T2-weighted and 3D-volume T1-weighted MRI scanning. We analyzed all of their MR images by FreeSurfer ver.5.3, ver.6.0 and ASHS. For each subfield, normalized z-scores were calculated and compared among groups.

Results

In TLE-HS groups, ASHS and FreeSurfer ver.6.0 revealed maximal z-scores in ipsilateral cornu ammonis (CA) 1, CA4 and dentate gyrus (DG), whereas in FreeSurfer ver.5.3 ipsilateral subiculum showed maximal z-scores. In TLE-nonHS group, there was no significant volume reduction by either ASHS or FreeSurfer.

Conclusions

ASHS and the new version of FreeSurfer may have an advantage in compatibility with existing histopathological knowledge in TLE patients with HS compared to the old version of FreeSurfer (ver.5.3), although further investigations with pathological findings and/or surgical outcomes are desirable.

Highlights

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Automated hippocampal subfield analysis is needed in temporal lobe epilepsy (TLE).
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Automatic segmentation hippocampal subfields (ASHS) and FreeSurfer are available.
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50 TLE patients (25 with hippocampal sclerosis (HS)) were analyzed.
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ASHS and new version of FreeSurfer may have an advantage in compatibility.
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High-resolution T2-weighted images might help better automatic segmentation in TLE.

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Most cited references 30

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Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment.

Paul Yushkevich, John Pluta, Hongzhi Wang … (2015)

We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm(3) resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross-validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions.

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Review: Hippocampal sclerosis in epilepsy: a neuropathology review

Maria Thom (2014)

Hippocampal sclerosis (HS) is a common pathology encountered in mesial temporal lobe epilepsy (MTLE) as well as other epilepsy syndromes and in both surgical and post-mortem practice. The 2013 International League Against Epilepsy (ILAE) classification segregates HS into typical (type 1) and atypical (type 2 and 3) groups, based on the histological patterns of subfield neuronal loss and gliosis. In addition, granule cell reorganization and alterations of interneuronal populations, neuropeptide fibre networks and mossy fibre sprouting are distinctive features of HS associated with epilepsies; they can be useful diagnostic aids to discriminate from other causes of HS, as well as highlighting potential mechanisms of hippocampal epileptogenesis. The cause of HS remains elusive and may be multifactorial; the contribution of febrile seizures, genetic susceptibility, inflammatory and neurodevelopmental factors are discussed. Post-mortem based research in HS, as an addition to studies on surgical samples, has the added advantage of enabling the study of the wider network changes associated with HS, the long-term effects of epilepsy on the pathology and associated comorbidities. It is likely that HS is heterogeneous in aspects of its cause, epileptogenetic mechanisms, network alterations and response to medical and surgical treatments. Future neuropathological studies will contribute to better recognition and understanding of these clinical and patho-aetiological subtypes of HS.

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Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI.

Christine Benner, Koen Van den Heede, Bradford Dickerson … (2009)

Recent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies. 2009 Wiley-Liss, Inc.

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Author and article information

Contributors

Noriko Sato

Journal

Journal ID (nlm-ta): Neuroimage Clin

Journal ID (iso-abbrev): Neuroimage Clin

Title: NeuroImage : Clinical

Publisher: Elsevier

ISSN (Electronic): 2213-1582

Publication date PMC-release: 13 June 2016

Publication date Collection: 2016

Publication date (Electronic): 13 June 2016

Volume: 12

Pages: 57-64

Affiliations

[a ]Department of Radiology, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan

[b ]Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo, Tokyo 113-8654, Japan

[c ]Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan

[d ]Department of Psychiatry, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan

[e ]Musashino-Kokubunji Clinic, 4-1-9-3, Honcho, Kokubunji, Tokyo 185-0012, Japan

Author notes

[* ]Corresponding author at: Department of Radiology, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8551, Japan.Department of RadiologyNational Center of Neurology and Psychiatry4-1-1 Ogawa-HigashiKodairaTokyo187-8551Japan snoriko@ 123456ncnp.go.jp

Article

Publisher ID: S2213-1582(16)30106-1

DOI: 10.1016/j.nicl.2016.06.008

PMC ID: 4960104

PubMed ID: 27489767

SO-VID: 2ae61d61-2f47-4269-a956-a917f2b98905

License:

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

History

Date received : 22 January 2016

Date revision received : 7 June 2016

Date accepted : 11 June 2016

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Automated subfield volumetric analysis of hippocampus in temporal lobe epilepsy using high-resolution T2-weighed MR imaging

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Abstract

Background and purpose

Materials and methods

Results

Conclusions

Highlights

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HR-EBSD (High Resolution - Electron Back Scatter Diffraction)

Most cited references 30

Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment.

Review: Hippocampal sclerosis in epilepsy: a neuropathology review

Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI.

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Cited by 23

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