Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors

Quattrini, Giulia; Pievani, Michela; Jovicich, Jorge; Aiello, Marco; Bargalló, Núria; Barkhof, Frederik; Bartrés‐Faz, David; Beltramello, Alberto; Pizzini, Francesca; Blin, Olivier; Bordet, Régis; Caulo, Massimo; Constantinides, Manos; Didic, Mira; Drevelegas, Antonios; Ferretti, Andrea; Fiedler, Ute; Floridi, Piero; Gros‐Dagnac, Hélène; Hensch, Tilman; Hoffmann, Karl‐Titus; Kuijer, Joost P.A.; Lopes, Renaud; Marra, Camillo; Müller, Bernhard; Nobili, Flavio; Parnetti, Lucilla; Payoux, Pierre; Picco, Agnese; Ranjeva, Jean Philippe; Roccatagliata, Luca; Rossini, Paolo Maria; Salvatore, Marco; Schönknecht, Peter; Schott, Björn H.; Sein, Julien; Soricelli, Andrea; Tarducci, R.; Tsolaki, Magda; Visser, Pieter Jelle; Wiltfang, Jens; Richardson, Jill C.; Frisoni, Giovanni B.; Marizzoni, Moira

doi:10.1016/j.neuroimage.2020.116932

Cited by 42 publications

(52 citation statements)

References 88 publications

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“…In the interest of this report, based on published results (Whelan et al (2016), Table 2), we correlated the rank of the average subregion size with corresponding ICC values for two FS6.0 samples (unweighted averages across both samples and both hemispheres), and found a high positive rank correlation (Spearman's rho 0.85). This pattern was further confirmed and extended to the Dice overlap index for FS6.0 by Quattrini et al (2020) who also concluded that the best test-retest reproducibility was achieved for hippocampal subfields > 300 mm 3 (see typical size ranking in Figure 2A). This could imply that the power to detect group differences or other clinical correlations may be biased towards larger subregions, and this should be considered when interpreting results.…”

Section: Relationship Between Average Subregion Size and Measurement supporting

confidence: 54%

“…FS5.3 has also been investigated with regard to its reliability properties: based on 65 subjects scanned at 13 sites, Marizzoni et al (2015) reported good or very good volumetric (reproducibility errors 2-5%) and spatial reproducibility (Dice indices ~0.9 or >0.9) for all subregions except for the hippocampal fissure and fimbria. Quattrini et al (2020) also reported good volume reliability (mean error < 5%, ICC>0.92) and excellent spatial agreement (mean Dice index > 0.92) for different 3 Tesla scanner platforms.…”

Section: Test-retest Reliability (Same Scanner)mentioning

confidence: 78%

“…This approach reduces measurement noise compared with two separate segmentations, increases test-retest reliability and thus leads to higher sensitivity to longitudinal changes (Iglesias et al, 2016). The two more recent reports strongly confirmed this finding both for within-and across-scanner comparisons, particularly for older subjects (Brown et al, 2020;Quattrini et al, 2020). For repeated measures, this approach is thus clearly recommended.…”

Section: Test-retest Reliability (Same Scanner)mentioning

confidence: 79%

“…Multivariate analyses of hippocampal subfield data are still rarely used but have begun to show promising results, for example for predicting treatment response in MDD (Cao et al, 2018). In conjunction with good across-site and across-vendor reliability (Brown et al, 2020;Quattrini et al, 2020), this strengthens the potential of subfield volumes as a biomarker for clinical trials. One possible advantage of subregional volumes over voxel-wise or vertex-wise features is a higher degree of interpretability, as effect weights can be translated back to histology or other levels of validation.…”

Section: Summary Discussion and Outlookmentioning

confidence: 96%

“…Another small trans-platform analysis (1.5 and 3 Tesla, FS5.3, performed on seven children) was included in the report of Tamnes et al (2014), showing high linear correlations (r values 0.80-0.97) for all subfields except the fimbria. More recently, reliability across vendors (or before and after typical hardware upgrades) has been reported in great detail (Brown et al, 2020;Quattrini et al, 2020). As a general pattern, these studies show that there is higher sensitivity of the spatial reproducibility to MR scanner effects, compared to the subfield volumes.…”

Section: Trans-platform (Vendor) Reliabilitymentioning

confidence: 88%

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FreeSurfer based segmentation of hippocampal subfields: a review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Sämann¹,

Iglesias²,

Gutman³

et al. 2020

Preprint

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Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and even variation within the normal range is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the ENIGMA Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with major depressive disorder, bipolar disorders, posttraumatic stress disorder, and other conditions, along with data from matched controls. In this overview, we explain the algorithm’s principle, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modelled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, schizophrenia, childhood trauma and posttraumatic stress disorder, inflammatory and systemic disease, alcoholism, stress regulation, neurotoxicity, as well as assessments of heritability, effects of candidate genes, genome-wide association studies and epigenetic effects. Lastly, we highlight points where FreeSurfer-based hippocampal subfield studies may be optimized.

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Section: Relationship Between Average Subregion Size and Measurement supporting

confidence: 54%

Section: Test-retest Reliability (Same Scanner)mentioning

confidence: 78%

Section: Test-retest Reliability (Same Scanner)mentioning

confidence: 79%

Section: Summary Discussion and Outlookmentioning

confidence: 96%

Section: Trans-platform (Vendor) Reliabilitymentioning

confidence: 88%

See 3 more Smart Citations

FreeSurfer based segmentation of hippocampal subfields: a review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Sämann¹,

Iglesias²,

Gutman³

et al. 2020

Preprint

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Alterations of the intrinsic amygdala‐hippocampal network in juvenile myoclonic epilepsy

Lee

et al. 2021

Brain and Behavior

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Introduction: Several lines of evidence suggest that the amygdala-hippocampus is involved in the epileptogenic network of juvenile myoclonic epilepsy (JME). The aim of this study was to investigate the alterations in the individual nuclei of the amygdala and hippocampal subfields, and the intrinsic amygdala-hippocampal network of patients with JME compared to healthy controls.Methods: This retrospective study conducted at a single tertiary hospital involved 35 patients with newly diagnosed JME, and 34 healthy subjects. We calculated the individual structural volumes of 18 nuclei in the amygdala, and 38 hippocampal subfields using three-dimensional volumetric T1-weighted imaging and FreeSurfer program. We also performed an analysis of the intrinsic amygdala-hippocampal global and local network based on these volumes using a graph theory and Brain Analysis using Graph Theory (BRAPH) program. We investigated the differences in these volumes and network measures between patients with JME and healthy controls.Results: There were no significant volume differences in the nuclei of the amygdala and hippocampal subfields between patients with JME and healthy controls. However, we found significant differences in the global network between patients with JME and healthy controls. The mean clustering coefficient was significantly decreased in patients with JME compared to healthy controls (0.473 vs. 0.653, p = .047). In addition, specific regions in the hippocampal subfields showed significant differences in the local network between the two groups. The betweenness centrality of the right CA1-head, right hippocampus-amygdala-transition area, left hippocampal fissure, left fimbria, and left CA3-head, was increased in patients with JME compared to healthy controls. Conclusion:The intrinsic amygdala-hippocampal global and local networks differed in patients with JME compared to healthy controls, which may be related to the pathogenesis of JME, and memory dysfunction in patients with JME.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Volumetric development of hippocampal subfields and hippocampal white matter connectivity: Relationship with episodic memory

Dick

Ralph

Farrant

et al. 2022

Developmental Psychobiology

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The hippocampus is a complex structure composed of distinct subfields. It has been central to understanding neural foundations of episodic memory. In the current crosssectional study, using a large sample of 830, 3-to 21-year-olds from a unique, publicly available dataset we examined the following questions: (1) Is there elevated grey matter volume of the hippocampus and subfields in late compared to early development?(2) How does hippocampal volume compare with the rest of the cerebral cortex at different developmental stages? and (3) What is the relation between hippocampal volume and connectivity with episodic memory performance? We found hippocampal subfield volumes exhibited a nonlinear relation with age and showed a lag in volumetric change with age when compared to adjacent cortical regions (e.g., entorhinal cortex).We also observed a significant reduction in cortical volume across older cohorts, while hippocampal volume showed the opposite pattern. In addition to age-related differences in gray matter volume, dentate gyrus/cornu ammonis 3 volume was significantly related to episodic memory. We did not, however, find any associations with episodic memory performance and connectivity through the uncinate fasciculus, fornix, or cingulum. The results are discussed in the context of current research and theories of hippocampal development and its relation to episodic memory.

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Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors

Cited by 42 publications

References 88 publications

FreeSurfer based segmentation of hippocampal subfields: a review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

FreeSurfer based segmentation of hippocampal subfields: a review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Alterations of the intrinsic amygdala‐hippocampal network in juvenile myoclonic epilepsy

Volumetric development of hippocampal subfields and hippocampal white matter connectivity: Relationship with episodic memory

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