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

Sämann, Philipp G.; Iglesias, Juan Eugenio; Gutman, Boris A.; Grotegerd, Dominik; Leenings, Ramona; Flint, Claas; Dannlowski, Udo; Clarke-Rubright, Emily K.; Morey, Rajendra A.; Erp, Theo G.M. van; Whelan, Christopher D.; Han, Laura K.M.; Velzen, Laura S. van; Cao, Bo; Augustinack, Jean C.; Thompson, Paul M.; Jahanshad, Neda; Schmaal, Lianne

doi:10.1002/hbm.25326

Cited by 79 publications

(62 citation statements)

References 267 publications

(254 reference statements)

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“…In FreeSurfer v.5.3, the atlas is built in vivo scans at 0.38 × 0.38 × 0.80 mm 3 resolution (without manual delineation), yielding voxels larger than the ex vivo protocol (version 6.0). 16 Moreover, 2 studies used MAGeT-Brain (Multiple Automatically-GEnerated Templates). 17,18 In MAGeT, hippocampal subfield segmentation is driven by propagating atlas segmentations (optimal number of atlases, 9) to a template library, formed from a subset of target images (with several types of image acquisition and disease populations), via transformations estimated by nonlinear image registration.…”

Section: Segmentation Softwarementioning

confidence: 99%

Genetic Influences on Hippocampal Subfields

et al. 2021

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There is clear evidence that hippocampal subfield volumes have partly distinct genetic determinants associated with specific biological processes. The identification of genetic correlates of hippocampal subfield volumes may help to elucidate the mechanisms of neurologic diseases, as well as aging and neurodegenerative processes. However, despite the emerging interest in this area of research, the current knowledge of the genetic architecture of hippocampal subfields has not yet been consolidated. We aimed to provide a review of the current evidence from genetic studies of hippocampal subfields, highlighting current priorities and upcoming challenges. The limited number of studies investigating the influential genetic effects on hippocampal subfields, a lack of replicated results and longitudinal designs, and modest sample sizes combined with insufficient standardization of protocols are identified as the most pressing challenges in this emerging area of research.

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Section: Segmentation Softwarementioning

confidence: 99%

Genetic Influences on Hippocampal Subfields

et al. 2021

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“…Several papers in this Special Issue focus on technical challenges in harmonizing brain data from different sources worldwide. These challenges were addressed by developing harmonized protocols to analyze specific brain measures, such as hippocampal subfields (Sämann et al, 2020). As many disorders studied by ENIGMA have found abnormalities in the hippocampus, Sämann et al (2020) offer a comprehensive review of approaches and methods used to study hippocampal subfields in clinical populations, offering a finer-grained analysis of hippocampal structure.…”

Section: Methods For Data Integration and Technical Issues In Harmonizing Brain Datamentioning

confidence: 99%

“…These challenges were addressed by developing harmonized protocols to analyze specific brain measures, such as hippocampal subfields (Sämann et al, 2020). As many disorders studied by ENIGMA have found abnormalities in the hippocampus, Sämann et al (2020) offer a comprehensive review of approaches and methods used to study hippocampal subfields in clinical populations, offering a finer-grained analysis of hippocampal structure. Based on experience applying subfield analysis to diverse data worldwide, they present in-depth guidelines for segmentation and quality control of subfield measures as part of an illustrated and validated protocol for the quality control and analysis of subfield data-one that is widely used across ENIGMA.…”

Section: Methods For Data Integration and Technical Issues In Harmonizing Brain Datamentioning

confidence: 99%

The Enhancing NeuroImaging Genetics through Meta‐Analysis Consortium: 10 Years of Global Collaborations in Human Brain Mapping

Thompson

Jahanshad

Schmaal

et al. 2021

Human Brain Mapping

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This Special Issue of Human Brain Mapping is dedicated to a 10-year anniversary of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large-scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task-based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically wellpowered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting largescale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke.

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“…Volume measurements of hippocampal s underwent a correction process using the estimated total intracranial volum [17,18]. We carefully inspected the automatic hippocampal subfield segmentatio of all participants on axial, sagittal, coronal images referring the quality control suggested by Samman et al, and confirmed that the segmentations were pe properly [19]. The white matter connectivity of the hippocampus was acquired based on DT DSI studio [20].…”

Section: Image Analysismentioning

confidence: 99%

Hippocampal Subfields and White Matter Connectivity in Patients with Subclinical Geriatric Depression

Lee

Park

et al. 2022

Brain Sciences

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Despite an abundance of research related to the functional and structural changes of the brain in patients with geriatric depression, knowledge related to early alterations such as decreased white matter connectivity and their association with cognitive decline remains lacking. We aimed to investigate early alterations in hippocampal microstructure and identify their associations with memory function in geriatric patients with subclinical depression. Nineteen participants with subclinical geriatric depression and 19 healthy controls aged ≥65 years exhibiting general cognitive function within the normal range were included in the study and underwent assessments of verbal memory. Hippocampal subfield volumes were determined based on T1-weighted magnetization-prepared rapid gradient echo (T1-MPRAGE) images, while group tractography and connectometry analyses were conducted using diffusion tensor images. Our findings indicated that the volumes of whole bilateral hippocampus, cornus ammonis (CA) 1, molecular layer, left subiculum, CA3, hippocampal tail, right CA4, and granule cell/molecular layers of the dentate gyrus (GC-ML-DG) were significantly smaller in the subclinical depression group than in the control group. In the subclinical depression group, verbal learning was positively correlated with the volumes of the CA1, GC-ML-DG, molecular layer, and whole hippocampus in the right hemisphere. The fractional anisotropy of the bilateral fornix was also significantly lower in the subclinical depression group and exhibited a positive correlation with verbal learning and recall in both groups. Our results suggest that hippocampal microstructure is disrupted and associated with memory in patients with subclinical depression.

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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

Cited by 79 publications

References 267 publications

Genetic Influences on Hippocampal Subfields

Genetic Influences on Hippocampal Subfields

The Enhancing NeuroImaging Genetics through Meta‐Analysis Consortium: 10 Years of Global Collaborations in Human Brain Mapping

Hippocampal Subfields and White Matter Connectivity in Patients with Subclinical Geriatric Depression

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