Longitudinal reproducibility of automatically segmented hippocampal subfields: A multisite European 3T study on healthy elderly

Syn_SegNet: A Joint Deep Neural Network for Ultrahigh-Field 7T MRI Synthesis and Hippocampal Subfield Segmentation in Routine 3T MRI

Precise delineation of hippocampus subfields is crucial for the identification and management of various neurological and psychiatric disorders. However, segmenting these subfields automatically in routine 3T MRI is challenging due to their complex morphology and small size, as well as the limited signal contrast and resolution of the 3T images. This research proposes Syn_SegNet, an end-to-end, multitask joint deep neural network that leverages ultrahigh-field 7T MRI synthesis to improve hippocampal subfield segmentation in 3T MRI. Our approach involves two key components. First, we employ a modified Pix2PixGAN as the synthesis model, incorporating self-attention modules, image and feature matching loss, and ROI loss to generate high-quality 7T-like MRI around the hippocampal region. Second, we utilize a variant of 3D-U-Net with multiscale deep supervision as the segmentation subnetwork, incorporating an anatomic weighted cross-entropy loss that capitalizes on prior anatomical knowledge. We evaluate our method on hippocampal subfield segmentation in paired 3T MRI and 7T MRI with seven different anatomical structures. The experimental findings demonstrate that Syn_SegNet's segmentation performance benefits from integrating synthetic 7T data in an online manner and is superior to competing methods. Furthermore, we assess the generalizability of the proposed approach using a publicly accessible 3T MRI dataset. The developed method would be an efficient tool for segmenting hippocampal subfields in routine clinical 3T MRI.

Forecasting individual progression trajectories in Alzheimer's disease

The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical trial. We show that enriching the population with the predicted progressors decreases the required sample size by 38% to 50%, depending on trial duration, outcome, and targeted disease stage, from asymptomatic individuals at risk of AD to subjects with early and mild AD. We show that the method introduces no biases regarding sex or geographic locations and is robust to missing data. It performs best at the earliest stages of disease and is therefore highly suitable for use in prevention trials.

Deep phenotyping and genomic data from a nationally representative study on dementia in India

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is a nationally representative in-depth study of cognitive aging and dementia. We present a publicly available dataset of harmonized cognitive measures of 4,096 adults 60 years of age and older in India, collected across 18 states and union territories. Blood samples were obtained to carry out whole blood and serum-based assays. Results are included in a venous blood specimen datafile that can be linked to the Harmonized LASI-DAD dataset. A global screening array of 960 LASI-DAD respondents is also publicly available for download, in addition to neuroimaging data on 137 LASI-DAD participants. Altogether, these datasets provide comprehensive information on older adults in India that allow researchers to further understand risk factors associated with cognitive impairment and dementia.

Relationships Between Memory Impairments and Hippocampal Structure in Patients With Subcortical Ischemic Vascular Disease

Background and Purpose

Patients with subcortical ischemic vascular disease (SIVD) suffer from memory disorders that are thought to be associated with the hippocampus. We aimed to explore changes in hippocampal subfields and the relationship between different hippocampal subfield volumes and different types of memory dysfunction in SIVD patients.

Methods

A total of 77 SIVD patients with cognitive impairment (SIVD-CI, n = 39) or normal cognition (HC-SIVD, n = 38) and 41 matched healthy controls (HCs) were included in this study. Memory function was measured in all subjects, and structural magnetic resonance imaging (MRI) was performed. Then, the hippocampus was segmented and measured by FreeSurfer 6.0 software. One-way ANOVA was used to compare the volume of hippocampal subfields among the three groups while controlling for age, sex, education and intracranial volume (ICV). Then, post hoc tests were used to evaluate differences between each pair of groups. Finally, correlations between significantly different hippocampal subfield volumes and memory scores were tested in SIVD patients.

Results

Almost all hippocampal subfields were significantly different among the three groups except for the bilateral hippocampal fissure (p = 0.366, p = 0.086, respectively.) and left parasubiculum (p = 0.166). Furthermore, the SIVD-CI patients showed smaller volumes in the right subiculum (p < 0.001), CA1 (p = 0.002), presubiculum (p = 0.002) and molecular layer of the hippocampus (p = 0.017) than the HC-SIVD patients. In addition, right subiculum volumes were positively related to Rey’s Auditory Verbal Learning Test (RAVLT) word recognition (r = 0.230, p = 0.050), reverse digit span test (R-DST) (r = 0.326, p = 0.005) and Rey–Osterrieth Complex Figure Test (ROCF) immediate recall (r = 0.247, p = 0.035) scores, right CA1 volumes were positively correlated with RAVLT word recognition (r = 0.261, p = 0.026), and right presubiculum volumes showed positive relationships with R-DST (r = 0.254, p = 0.030) and ROCF immediate recall (r = 0.242, p = 0.039) scores.

Conclusion

SIVD might lead to general reductions in volume in multiple hippocampal subfields. However, SIVD-CI patients showed atrophy in specific subfields, which might be associated with memory deficits.

Structural Alteration of Medial Temporal Lobe Subfield in the Amnestic Mild Cognitive Impairment Stage of Alzheimer’s Disease

Objective. Volume reduction and structural abnormality is the most replicated finding in neuroimaging studies of Alzheimer’s disease (AD). Amnestic mild cognitive impairment (aMCI) is the early stage of AD development. Thus, it is necessary to investigate the link between atrophy of regions of interest (ROIs) in medial temporal lobe, the variation trend of ROI densities and volumes among patients with cognitive impairment, and the distribution characteristics of ROIs in the aMCI group, Alzheimer’s disease (AD) group, and normal control (NC) group. Methods. 30 patients with aMCI, 16 patients with AD, and 30 NC are recruited; magnetic resonance imaging (MRI) brain scans are conducted. Voxel-based morphometry was employed to conduct the quantitative measurement of gray matter densities of the hippocampus, amygdala, entorhinal cortex, and mammillary body (MB). FreeSurfer was utilized to automatically segment the hippocampus into 21 subregions and the amygdala into 9 subregions. Then, their subregion volumes and total volume were calculated. Finally, the ANOVA and multiple comparisons were performed on the above-mentioned data from these three groups. Results. AD had lower GM densities than MCI, and MCI had lower GM densities than NC, but not all of the differences were statistically significant. In the comparisons of AD-aMCI-NC, AD-aMCI, and AD-NC, the hippocampus, amygdala, and entorhinal cortex showed differences in the gray matter densities ( $p<0.05$ ); the differences of mammillary body densities were not significant in the random comparison between these three groups ( $p>0.05$ ). The hippocampus densities and volumes of the subjects from the aMCI group and the AD group were bilaterally symmetric. The gray matter densities of the right side of the entorhinal cortex inside each group and the hippocampus from the NC group were higher than those of the left side ( $p<0.05$ ), and the gray matter densities of the amygdala and mammillary body were bilaterally symmetric in the three groups ( $p>0.05$ ). There were no gender differences of four ROIs in the AD, aMCI, and NC groups ( $p>0.05$ ). The volume differences of the hippocampus presubiculum-body and parasubiculum manifest no statistical significance ( $p>0.05$ ) in the random comparison between these three groups. Volume differences of the left amygdala basal nucleus, the left lateral nucleus, the left cortical amygdala transitional area, the left paravamnion nucleus, and bilateral hippocampal amygdala transition area (HATA) had statistical differences only between the AD group and the NC group ( $p<0.05$ ). Conclusion. Structural defects of medial temporal lobe subfields were revealed in the aMCI and AD groups. Decreased gray matter densities of the hippocampus, entorhinal cortex, and amygdala could distinguish patients with early stage of AD between aMCI and NC. Volume decline of the hippocampus and amygdala subfields could only distinguish AD between NC.

Comparison and Reliability of Hippocampal Subfield Segmentations Within FreeSurfer Utilizing T1- and T2-Weighted Multispectral MRI Data

The accurate segmentation of in vivo magnetic resonance imaging (MRI) data is a crucial prerequisite for the reliable assessment of disease progression, patient stratification or the establishment of putative imaging biomarkers. This is especially important for the hippocampal formation, a brain area involved in memory formation and often affected by neurodegenerative or psychiatric diseases. FreeSurfer, a widely used automated segmentation software, offers hippocampal subfield delineation with multiple input options. While a single T1-weighted (T1) sequence is regularly used by most studies, it is also possible and advised to use a high-resolution T2-weighted (T2H) sequence or multispectral information. In this investigation it was determined whether there are differences in volume estimations depending on the input images and which combination of these deliver the most reliable results in each hippocampal subfield. 41 healthy participants (age = 25.2 years ± 4.2 SD) underwent two structural MRIs at three Tesla (time between scans: 23 days ± 11 SD) using three different structural MRI sequences, to test five different input configurations (T1, T2, T2H, T1 and T2, and T1 and T2H). We compared the different processing pipelines in a cross-sectional manner and assessed reliability using test-retest variability (%TRV) and the dice coefficient. Our analyses showed pronounced significant differences and large effect sizes between the processing pipelines in several subfields, such as the molecular layer (head), CA1 (head), hippocampal fissure, CA3 (head and body), fimbria and CA4 (head). The longitudinal analysis revealed that T1 and multispectral analysis (T1 and T2H) showed overall higher reliability across all subfields than T2H alone. However, the specific subfields had a substantial influence on the performance of segmentation results, regardless of the processing pipeline. Although T1 showed good test-retest metrics, results must be interpreted with caution, as a standard T1 sequence relies heavily on prior information of the atlas and does not take the actual fine structures of the hippocampus into account. For the most accurate segmentation, we advise the use of multispectral information by using a combination of T1 and high-resolution T2-weighted sequences or a T2 high-resolution sequence alone.

Stability of hippocampal subfield volumes after trauma and relationship to development of PTSD symptoms

BACKGROUND

The hippocampus plays a central role in post-traumatic stress disorder (PTSD) pathogenesis, and the majority of neuroimaging research on PTSD has studied the hippocampus in its entirety. Although extensive literature demonstrates changes in hippocampal volume are associated with PTSD, fewer studies have probed the relationship between symptoms and the hippocampus' functionally and structurally distinct subfields. We utilized data from a longitudinal study examining post-trauma outcomes to determine whether hippocampal subfield volumes change post-trauma and whether specific subfields are significantly associated with, or prospectively related to, PTSD symptom severity. As a secondary aim, we leveraged our unique study design sample to also investigate reliability of hippocampal subfield volumes using both cross-sectional and longitudinal pipelines available in FreeSurfer v6.0.

METHODS

Two-hundred and fifteen traumatically injured individuals were recruited from an urban Emergency Department. Two-weeks post-injury, participants underwent two consecutive days of neuroimaging (time 1: T1, and time 2: T2) with magnetic resonance imaging (MRI) and completed self-report assessments. Six-months later (time 3: T3), participants underwent an additional scan and were administered a structured interview assessing PTSD symptoms. First, we calculated reliability of hippocampal measurements at T1 and T2 (automatically segmented with FreeSurfer v6.0). We then examined the prospective (T1 subfields) and cross-sectional (T3 subfields) relationship between volumes and PTSD. Finally, we tested whether change in subfield volumes between T1 and T3 explained PTSD symptom variability.

RESULTS

After controlling for sex, age, and total brain volume, none of the subfield volumes (T1) were prospectively related to T3 PTSD symptoms nor were subfield volumes (T3) associated with current PTSD symptoms (T3). Tl - T2 reliability of all hippocampal subfields ranged from good to excellent (intraclass correlation coefficient (ICC) values > 0.83), with poorer reliability in the hippocampal fissure.

CONCLUSION

Our study was a novel examination of the prospective relationship between hippocampal subfield volumes in relation to PTSD in a large trauma-exposed urban sample. There was no significant relationship between subfield volumes and PTSD symptoms, however, we confirmed FreeSurfer v6.0 hippocampal subfield segmentation is reliable when applied to a traumatically-injured sample, using both cross-sectional and longitudinal analysis pipelines. Although hippocampal subfield volumes may be an important marker of individual variability in PTSD, findings are likely conditional on the timing of the measurements (e.g. acute or chronic post-trauma periods) and analysis strategy (e.g. cross-sectional or prospective).

Morphometry of the Hippocampus Across the Adult Life-Span in Patients with Depressive Disorders: Association with Neuroticism

Neuroticism is one of the main endophenotypes of major depressive disorder (MDD) and is closely related to the negative effect systems of Research Domain Criteria (RDoC) domains. The relationship between neuroticism and aging is dynamic and complex. Moreover, reduced hippocampal volumes are probably the most frequently reported structural neuroimaging finding associated with MDD. However, it remains unclear to what extent hippocampal abnormalities are linked with age and neuroticism changes in people with depression through the adult life span. This study aimed to examine the interplay between aging and neuroticism on hippocampal morphometric across the adult life-span in a relative large sample of patients with depressive disorders (114 patients, 73 females, age range: 18-74 years) and healthy control (HC) subjects (112 healthy controls, 72 females, age range: 19-72 years). MDD patients showed reduced bilateral hippocampal volumes. The effect of aging on the left hippocampal showed linear and the right hippocampal volume non-linear trajectories throughout the adult life span in healthy groups and MDD groups respectively. The hippocampal atrophy was dynamically impacted by depression at the early stages of adult life. Furthermore, we observed that right hippocampal volume reduction was associated with higher neuroticism in depressive patients younger than 30.65 years old. Our results suggest that the age-related atrophy in the right hippocampal volume was more affected by individual differences in neuroticism among younger depressive patients. Hippocampal volume reduction as a vulnerability factor for early-onset and major geriatric depression may have a distinct endophenotype.

FreeSurfer 5.3 versus 6.0: are volumes comparable? A Chronic Effects of Neurotrauma Consortium study

Automated neuroimaging methods like FreeSurfer ( https://surfer.nmr.mgh.harvard.edu/ ) have revolutionized quantitative neuroimaging analyses. Such analyses provide a variety of metrics used for image quantification, including magnetic resonance imaging (MRI) volumetrics. With the release of FreeSurfer version 6.0, it is important to assess its comparability to the widely-used previous version 5.3. The current study used data from the initial 249 participants in the ongoing Chronic Effects of Neurotrauma Consortium (CENC) multicenter observational study to compare the volumetric output of versions 5.3 and 6.0 across various regions of interest (ROI). In the current investigation, the following ROIs were examined: total intracranial volume, total white matter volume, total ventricular volume, total gray matter volume, and right and left volumes for the thalamus, pallidum, putamen, caudate, amygdala and hippocampus. Absolute ROI volumes derived from FreeSurfer 6.0 differed significantly from those obtained using version 5.3. We also employed a clinically-based evaluation strategy to compare both versions in their prediction of age-mediated volume reductions (or ventricular increase) in the aforementioned structures. Statistical comparison involved both general linear modeling (GLM) and random forest (RF) methods, where cross-validation error was significantly higher using segmentations from FreeSurfer version 5.3 versus version 6.0 (GLM: t = 4.97, df = 99, p value = 2.706e-06; RF: t = 4.85, df = 99, p value = 4.424e-06). Additionally, the relative importance of ROIs used to predict age using RFs differed between FreeSurfer versions, indicating substantial differences in the two versions. However, from the perspective of correlational analyses, fitted regression lines and their slopes were similar between the two versions, regardless of version used. While absolute volumes are not interchangeable between version 5.3 and 6.0, ROI correlational analyses appear to yield similar results, suggesting the interchangeability of ROI volume for correlational studies.

Test-retest reliability of hippocampal subfield volumes in a developmental sample: Implications for longitudinal developmental studies

The hippocampus (Hc) is composed of cytoarchitectonically distinct subfields: dentate gyrus (DG), cornu ammonis sectors 1-3 (CA1-3), and subiculum. Limited evidence suggests differential maturation rates across the Hc subfields. While longitudinal studies are essential in demonstrating differential development of Hc subfields, a prerequisite for interpreting meaningful longitudinal effects is establishing test-retest consistency of Hc subfield volumes measured in vivo over time. Here, we examined test-retest consistency of Hc subfield volumes measured from structural MR images in two independent developmental samples. Sample One (n = 28, ages 7-20 years, M = 12.64, SD = 3.35) and Sample Two (n = 28, ages 7-17 years, M = 11.72, SD = 2.88) underwent MRI twice with a 1-month and a 2-year delay, respectively. High-resolution PD-TSE-T₂ -weighted MR images (0.4 × 0.4 × 2 mm³ ) were collected and manually traced using a longitudinal manual demarcation protocol. In both samples, we found excellent consistency of Hc subfield volumes between the two visits, assessed by two-way mixed intraclass correlation (ICC (3) single measures ≥ 0.87), and no difference between children and adolescents. The results further indicated that discrepancies between repeated measures were not related to Hc subfield volumes, or visit number. In addition to high consistency, with the applied longitudinal protocol, we detected significant variability in Hc subfield volume changes over the 2-year delay, implying high sensitivity of the method in detecting individual differences. Establishing unbiased, high longitudinal consistency of Hc subfield volume measurements optimizes statistical power of a hypothesis test and reduces standard error of the estimate, together improving external validity of the measures in constructing theoretical models of memory development.

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

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures 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 Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, 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 modeled, 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, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.

Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility

Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm³ had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was -0.22[IQR = 0.50] for LGA-SPM8, -0.12[0.57] for LGA-SPM12, -0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.

Sex differences in the association of photoperiod with hippocampal subfield volumes in older adults: A cross-sectional study in the UK Biobank cohort

INTRODUCTION

Even though seasonal and sex-dependent changes in hippocampal and subfield volumes are well known in animals, little is known about changes in humans. We hypothesized that changes in photoperiod would predict changes in hippocampal subfield volumes and that this association would be different between females and males.

METHODS

A total of 10,033 participants ranging in age from 45 to 79 years were scanned by MRI in a single location as part of the UK Biobank project. Hippocampal subfield volumes were obtained using automated processing and segmentation algorithms using the developmental version of the FreeSurfer v 6.0. Photoperiod was defined as the number of hours between sunrise and sunset on the day of scan.

RESULTS

Photoperiod correlated positively with total hippocampal volume and all subfield volumes across participants as well as in each sex individually, with females showing greater seasonal variation in a majority of left subfield volumes compared with males. ANCOVAs revealed significant differences in rate of change in only left subiculum, CA-4, and GC-ML-DG between females and males. PLS showed highest loadings of hippocampal subfields in both females and males in GC-ML-DG, CA1, CA4, subiculum, and CA3 for left hemisphere and CA1, GC-ML-DG, CA4; subiculum and CA3 for right hemisphere in females; GC-ML-DG, CA1, subiculum, CA4 and CA3 for left hemisphere; CA1, GC-ML-DG, subiculum, CA4 and CA3 for right hemisphere in males.

CONCLUSION

The influence of day length on hippocampal volume has implications for modeling age-related decline in memory in older adults, and sex differences suggest an important role for hormones in these effects.

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

BACKGROUND

The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.

METHODS

Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.

RESULTS

Significant MRI site and vendor effects (p ​< ​.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p ​< ​1.39E-36). In particular, volumes larger than 200 ​mm³ (for amygdalar nuclei) and 300 ​mm³ (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε ​< ​5% and DICE ​> ​0.80).

CONCLUSION

Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

miR-146a and miR-181a are involved in the progression of mild cognitive impairment to Alzheimer's disease

The identification of mechanisms associated with Alzheimer's disease (AD) development in mild cognitive impairment (MCI) would be of great usefulness to clarify AD pathogenesis and to develop preventive and therapeutic strategies. In this study, blood levels of the candidate microRNAs (small noncoding RNAs that play a pivotal role in gene expression) miR-146a, miR-181a, miR-181b, miR-24-3p, miR-186a, miR-101, miR-339, miR-590, and miR-22 have been investigated for association to AD conversion within 2 years in a group of 45 patients with MCI. Baseline miR-146a (p = 0.036) and miR-181a (p = 0.026) showed a significant upregulation in patients with MCI who later converted to AD. These alterations were related to AD hallmarks: a significant negative correlation was found with amyloid beta cerebrospinal fluid concentration for miR-146a (p = 0.006) and miR-181a (p = 0.001). Moreover, higher levels of miR-146a were associated to apolipoprotein E ε4 allele presence, smaller volume of the hippocampus (p = 0.045) and of the CA1 (p = 0.013) and the subiculum (p = 0.027) subfields. Increased levels of miR-146a (p = 0.031) and miR-181a (p = 0.002) were also linked with diffusivity alterations in the cingulum. These data support a role for miR-146a and miR-181a in the mechanisms of AD progression.

Hippocampus subfield volumetry after microsurgical or endovascular treatment of intracranial aneurysms-an explorative study

BACKGROUND

To study hippocampus subfield volumes in patients after microsurgical clipping (MC) and/or endovascular coiling (EC) of intracranial aneurysms.

METHODS

Hippocampus subfield volumetry was performed using FreeSurfer v6.0 in 51 patients (35 females, mean age 54.9 ± 11.9 years, range 24-78 years). Visual inspection of image and segmentation quality was performed prior to statistical analyses. Multiple regression analysis, controlled for age, sex, and side of treatment, was used to assess the impact of prior MC and history of subarachnoid haemorrhage (SAH) on hippocampus subfield volumes (cornu ammonis (CA)-2/3, CA-4, subiculum). Partial correlation analyses were used to assess effect of multiple treatments on hippocampus subfield volumes.

RESULTS

Prior MC was significantly associated with lower hippocampal subfield volumes in MC patients for right and left CA-2/3 (β = -22.32 [-40.18, -4.45]; p = 0.016 and β = -20.03 [-39.38, -0.68]; p = 0.043) and right CA-4 (β = -17.00 [-33.86, 0.12]; p = 0.048). History of SAH was not significantly associated with hippocampal subfield volumes. We observed a higher disease burden in the MC cohort. The number of aneurysms correlated with right-sided hippocampal subfield volumes while the number of treatment interventions did not.

CONCLUSION

In this explorative study, we found that history of MC was significantly associated with lower volumes in distinct hippocampal subfields, which may be a consequence of a more extensive treatment. This could indicate specific atrophy of CA-2/3 after MC and should motivate hippocampal subfield assessment in larger cohorts.

Can measuring hippocampal atrophy with a fully automatic method be substantially less noisy than manual segmentation over both 1 and 3 years?

To quantify the "segmentation noise" of several widely used fully automatic methods for measuring longitudinal hippocampal atrophy in Alzheimer's disease and compare the results to the segmentation noise of manual segmentation over both 1 and 3 years. The segmentation noise of 5 longitudinal hippocampal atrophy measurement methods was quantified, including checking its Gaussianity, using 264 subjects from the ADNI1 back-to-back (BTB) data set over both 1 year and 3 year intervals. The segmentation methods were FreeSurfer 5.3.0 both cross sectional and longitudinal, FreeSurfer 6.0.0 longitudinal, MAPS-HBSI and FSL/FIRST 5.0.8. The BTB manual segmentation of 75 ADNI subjects from a previous study provided the manual distributions for comparison. All methods, including the manual segmentation, violated the Gaussianity assumption. Two methods, FreeSurfer 6.0.0 and MAPS-HBSI, had a segmentation noise substantially less than a surrogate for manual segmentation. FreeSurfer 5.3.0 longitudinal was confirmed as a surrogate for manual segmentation. The violation of the Gaussian assumption by the segmentation methods assessed, including manual, suggests results of previous studies that assumed Gaussian statistics without confirmation may need review. Fully automatic FreeSurfer 6.0.0 and MAPS-HBSI both have lower segmentation noise than manual requiring less than two thirds of the subjects to detect the same treatment effect.

Optimization and validation of automated hippocampal subfield segmentation across the lifespan

Automated segmentation of hippocampal (HC) subfields from magnetic resonance imaging (MRI) is gaining popularity, but automated procedures that afford high speed and reproducibility have yet to be extensively validated against the standard, manual morphometry. We evaluated the concurrent validity of an automated method for hippocampal subfields segmentation (automated segmentation of hippocampal subfields, ASHS; Yushkevich et al., ) using a customized atlas of the HC body, with manual morphometry as a standard. We built a series of customized atlases comprising the entorhinal cortex (ERC) and subfields of the HC body from manually segmented images, and evaluated the correspondence of automated segmentations with manual morphometry. In samples with age ranges of 6-24 and 62-79 years, 20 participants each, we obtained validity coefficients (intraclass correlations, ICC) and spatial overlap measures (dice similarity coefficient) that varied substantially across subfields. Anterior and posterior HC body evidenced the greatest discrepancies between automated and manual segmentations. Adding anterior and posterior slices for atlas creation and truncating automated output to the ranges manually defined by multiple neuroanatomical landmarks substantially improved the validity of automated segmentation, yielding ICC above 0.90 for all subfields and alleviating systematic bias. We cross-validated the developed atlas on an independent sample of 30 healthy adults (age 31-84) and obtained good to excellent agreement: ICC (2) = 0.70-0.92. Thus, with described customization steps implemented by experts trained in MRI neuroanatomy, ASHS shows excellent concurrent validity, and can become a promising method for studying age-related changes in HC subfield volumes.

Reduced volumes of the CA1 and CA4-dentate gyrus hippocampal subfields in systemic lupus erythematosus

Introduction There is evidence for hippocampal dysfunctions in systemic lupus erythematosus (SLE), which may contribute to neuropsychiatric impairments. However, fine structural alterations of the hippocampus have not been investigated in SLE. Methods We measured the volume of hippocampal subfields in 18 SLE patients and 20 healthy control individuals matched for age, gender, and education. The MRI protocol included structural T1 volumes (Philips Achieva 3T scanner, magnetization-prepared rapid acquisition gradient echo (MPRAGE)). For image processing, we used the neuGRID platform and the longitudinal pipeline of FreeSurfer v6.0 with the "hipposubfields" flag. Results Patients with SLE showed reduced volumes of CA1 (Cornu Ammonis 1) and CA4-dentate gyrus subfields relative to the control individuals. Smaller CA1 volumes were associated with worse performance on the Addenbrooke's Cognitive Examination. Conclusions These preliminary results indicate a prominent vulnerability and functional relevance of the CA1 hippocampal subfield in SLE.

Reduced CA2-CA3 Hippocampal Subfield Volume Is Related to Depression and Normalized by l-DOPA in Newly Diagnosed Parkinson's Disease

Hippocampal dysfunctions may play an important role in the non-motor aspects of Parkinson’s disease (PD), including depressive and cognitive symptoms. Fine structural alterations of the hippocampus and their relationship with symptoms and medication effects are unknown in newly diagnosed PD. We measured the volume of hippocampal subfields in 35 drug-naïve, newly diagnosed PD patients without cognitive impairment and 30 matched healthy control individuals. Assessments were performed when the patients did not receive medications and after a 24-week period of l-DOPA treatment. We obtained a T1-weighted 3D magnetization-prepared rapid acquisition gradient echo image at each assessment. FreeSurfer v6.0 was used for image analysis. Results revealed a selectively decreased CA2–CA3 volume in non-medicated PD patients, which was normalized after the 24-week treatment period. Higher depressive symptoms were associated with smaller CA2–CA3 volumes. These results indicate that the CA2–CA3 subfield is structurally affected in the earliest stage of PD in the absence of cognitive impairment. This structural anomaly, normalized by l-DOPA, is related to depressive non-motor symptoms.

Association between CSF biomarkers, hippocampal volume and cognitive function in patients with amnestic mild cognitive impairment (MCI)

Few studies have examined the relationship between CSF and structural biomarkers, and cognitive function in MCI. We examined the relationship between cognitive function, hippocampal volume and cerebrospinal fluid (CSF) Aβ₄₂ and tau in 145 patients with MCI. Patients were assessed on cognitive tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB), the Geriatric Depression Scale and the Functional Activities Questionnaire. Hippocampal volume was measured using magnetic resonance imaging (MRI), and CSF markers of Aβ₄₂, tau and p-tau₁₈₁ were also measured. Worse performance on a wide range of memory and sustained attention tasks were associated with reduced hippocampal volume, higher CSF tau and p-tau₁₈₁ and increased tau/Aβ₄₂ ratio. Memory tasks were also associated with lower ability to conduct functional activities of daily living, providing a link between AD biomarkers, memory performance and functional outcome. These results suggest that biomarkers of Aβ and tau are strongly related to cognitive performance as assessed by the CANTAB, and have implications for the early detection and characterization of incipient AD.

Dentate gyrus-cornu ammonis (CA) 4 volume is decreased and associated with depressive episodes and lipid peroxidation in bipolar II disorder: Longitudinal and cross-sectional analyses

OBJECTIVES

Reduced dentate gyrus volume and increased oxidative stress have emerged as potential pathophysiological mechanisms in bipolar disorder. However, the relationship between dentate gyrus volume and peripheral oxidative stress markers remains unknown. Here, we examined dentate gyrus-cornu ammonis (CA) 4 volume longitudinally in patients with bipolar II disorder (BD-II) and healthy controls and investigated whether BD-II is associated with elevated peripheral levels of oxidative stress.

METHODS

We acquired high-resolution structural 3T-magnetic resonance imaging (MRI) images and quantified hippocampal subfield volumes using an automated segmentation algorithm in individuals with BD-II (n=29) and controls (n=33). The participants were scanned twice, at study inclusion and on average 2.4 years later. In addition, we measured peripheral levels of two lipid peroxidation markers (4-hydroxy-2-nonenal [4-HNE] and lipid hydroperoxides [LPH]).

RESULTS

First, we demonstrated that the automated hippocampal subfield segmentation technique employed in this work reliably measured dentate gyrus-CA4 volume. Second, we found a decreased left dentate gyrus-CA4 volume in patients and that a larger number of depressive episodes between T1 and T2 predicted greater volume decline. Finally, we showed that 4-HNE was elevated in BD-II and that 4-HNE was negatively associated with left and right dentate gyrus-CA4 volumes in patients.

CONCLUSIONS

These results are consistent with a role for the dentate gyrus in the pathophysiology of bipolar disorder and suggest that depressive episodes and elevated oxidative stress might contribute to hippocampal volume decreases. In addition, these findings provide further support for the hypothesis that peripheral lipid peroxidation markers may reflect brain alterations in bipolar disorders.

Brain atrophy in Alzheimer's Disease and aging

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.

Clinical and biomarker profiling of prodromal Alzheimer's disease in workpackage 5 of the Innovative Medicines Initiative PharmaCog project: a 'European ADNI study'

BACKGROUND

In the field of Alzheimer's disease (AD), the validation of biomarkers for early AD diagnosis and for use as a surrogate outcome in AD clinical trials is of considerable research interest.

OBJECTIVE

To characterize the clinical profile and genetic, neuroimaging and neurophysiological biomarkers of prodromal AD in amnestic mild cognitive impairment (aMCI) patients enrolled in the IMI WP5 PharmaCog (also referred to as the European ADNI study).

METHODS

A total of 147 aMCI patients were enrolled in 13 European memory clinics. Patients underwent clinical and neuropsychological evaluation, magnetic resonance imaging (MRI), electroencephalography (EEG) and lumbar puncture to assess the levels of amyloid β peptide 1-42 (Aβ42), tau and p-tau, and blood samples were collected. Genetic (APOE), neuroimaging (3T morphometry and diffusion MRI) and EEG (with resting-state and auditory oddball event-related potential (AO-ERP) paradigm) biomarkers were evaluated.

RESULTS

Prodromal AD was found in 55 aMCI patients defined by low Aβ42 in the cerebrospinal fluid (Aβ positive). Compared to the aMCI group with high Aβ42 levels (Aβ negative), Aβ positive patients showed poorer visual (P = 0.001), spatial recognition (P < 0.0005) and working (P = 0.024) memory, as well as a higher frequency of APOE4 (P < 0.0005), lower hippocampal volume (P = 0.04), reduced thickness of the parietal cortex (P < 0.009) and structural connectivity of the corpus callosum (P < 0.05), higher amplitude of delta rhythms at rest (P = 0.03) and lower amplitude of posterior cingulate sources of AO-ERP (P = 0.03).

CONCLUSION

These results suggest that, in aMCI patients, prodromal AD is characterized by a distinctive cognitive profile and genetic, neuroimaging and neurophysiological biomarkers. Longitudinal assessment will help to identify the role of these biomarkers in AD progression.

Test-retest reliability of the default mode network in a multi-centric fMRI study of healthy elderly: Effects of data-driven physiological noise correction techniques

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016. © 2016 Wiley Periodicals, Inc.