Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance

A roadmap towards standardized neuroimaging approaches for human thalamic nuclei

The thalamus has a key role in mediating cortical-subcortical interactions but is often neglected in neuroimaging studies, which mostly focus on changes in cortical structure and activity. One of the main reasons for the thalamus being overlooked is that the delineation of individual thalamic nuclei via neuroimaging remains controversial. Indeed, neuroimaging atlases vary substantially regarding which thalamic nuclei are included and how their delineations were established. Here, we review current and emerging methods for thalamic nuclei segmentation in neuroimaging data and consider the limitations of existing techniques in terms of their research and clinical applicability. We address these challenges by proposing a roadmap to improve thalamic nuclei segmentation in human neuroimaging and, in turn, harmonize research approaches and advance clinical applications. We believe that a collective effort is required to achieve this. We hope that this will ultimately lead to the thalamic nuclei being regarded as key brain regions in their own right and not (as often currently assumed) as simply a gateway between cortical and subcortical regions.

3T sodium-MRI as predictor of neurocognition in nondemented older adults: a cross sectional study

Dementia is a burgeoning global problem. Novel magnetic resonance imaging (MRI) metrics beyond volumetry may bring new insight and aid clinical trial evaluation of interventions early in the Alzheimer's disease course to complement existing imaging and clinical metrics. To determine whether: (i) normalized regional sodium-MRI values (Na-SI) are better predictors of neurocognitive status than volumetry (ii) cerebral amyloid PET status improves modelling. Nondemented older adult (>60 years) volunteers of known Alzheimer's Disease Assessment Scale (ADAS-Cog11), Mini-Mental State Examination (MMSE) and Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neurocognitive test scores, ApolipoproteinE (APOE) e4 +/- cerebral amyloid PET status were prospectively recruited for 3T sodium-MRI brain scans. Left and right hippocampal, entorhinal and precuneus volumes and Na-SI (using the proportional intensity scaling normalization method with field inhomogeneity and partial volume corrections) were obtained after segmentation and co-registration of 3D-T1-weighted proton images. Descriptive statistics, correlation and best-subset regression analyses were performed. In our 76 nondemented participants (mean(standard deviation) age 75(5) years; woman 47(62%); cognitively unimpaired 54/76(71%), mildly cognitively impaired 22/76(29%)), left hippocampal Na-SI, not volume, was preferentially in the best models for predicting MMSE (Odds Ratio (OR) = 0.19(Confidence Interval (CI) = 0.07,0.53), P-value = 0.001) and ADAS-Cog11 (Beta(B) = 1.2(CI = 0.28,2.1), P-value = 0.01) scores. In the entorhinal analysis, right entorhinal Na-SI, not volume, was preferentially selected in the best model for predicting ADAS-Cog11 (B = 0.94(CI = 0.11,1.8), P-value = 0.03). While right entorhinal Na-SI and volume were both selected for MMSE modelling (Na-SI OR = 0.23(CI = 0.09,0.6), P-value = 0.003; volume OR = 2.6(CI = 1.0,6.6), P-value = 0.04), independently, Na-SI explained more of the variance (Na-SI R 2 = 10.3; volume R 2 = 7.5). No imaging variable was selected in the best CERAD models. Adding cerebral amyloid status improved model fit (Akaike Information Criterion increased 2.0 for all models, P-value < 0.001-0.045). Regional Na-SI were more predictive of MMSE and ADAS-Cog11 scores in our nondemented older adult cohort than volume, hippocampal more robust than entorhinal region of interest. Positive amyloid status slightly further improved model fit.

The prosubiculum in the human hippocampus: A rostrocaudal, feature-driven, and systematic approach

The hippocampal subfield prosubiculum (ProS), is a conserved neuroanatomic region in mouse, monkey, and human. This area lies between CA1 and subiculum (Sub) and particularly lacks consensus on its boundaries; reports have varied on the description of its features and location. In this report, we review, refine, and evaluate four cytoarchitectural features that differentiate ProS from its neighboring subfields: (1) small neurons, (2) lightly stained neurons, (3) superficial clustered neurons, and (4) a cell sparse zone. ProS was delineated in all cases (n = 10). ProS was examined for its cytoarchitectonic features and location rostrocaudally, from the anterior head through the body in the hippocampus. The most common feature was small pyramidal neurons, which were intermingled with larger pyramidal neurons in ProS. We quantitatively measured ProS pyramidal neurons, which showed (average, width at pyramidal base = 14.31 µm, n = 400 per subfield). CA1 neurons averaged 15.57 µm and Sub neurons averaged 15.63 µm, both were significantly different than ProS (Kruskal-Wallis test, p < .0001). The other three features observed were lightly stained neurons, clustered neurons, and a cell sparse zone. Taken together, these findings suggest that ProS is an independent subfield, likely with distinct functional contributions to the broader interconnected hippocampal network. Our results suggest that ProS is a cytoarchitecturally varied subfield, both for features and among individuals. This diverse architecture in features and individuals for ProS could explain the long-standing complexity regarding the identification of this subfield.

Sleep duration and brain MRI measures: Results from the SOL-INCA MRI study

INTRODUCTION

Sleep duration has been associated with dementia and stroke. Few studies have evaluated sleep pattern-related outcomes of brain disease in diverse Hispanics/Latinos.

METHODS

The SOL-INCA (Study of Latinos-Investigation of Neurocognitive Aging) magnetic resonance imaging (MRI) study recruited diverse Hispanics/Latinos (35-85 years) who underwent neuroimaging. The main exposure was self-reported sleep duration. Our main outcomes were total and regional brain volumes.

RESULTS

The final analytic sample included n = 2334 participants. Increased sleep was associated with smaller brain volume (βtotal_brain  = -0.05, p < 0.01) and consistently so in the 50+ subpopulation even after adjusting for mild cognitive impairment status. Sleeping >9 hours was associated with smaller gray (βcombined_gray  = -0.17, p < 0.05) and occipital matter volumes (βoccipital_gray  = -0.18, p < 0.05).

DISCUSSION

We found that longer sleep duration was associated with lower total brain and gray matter volume among diverse Hispanics/Latinos across sex and background. These results reinforce the importance of sleep on brain aging in this understudied population.

HIGHLIGHTS

Longer sleep was linked to smaller total brain and gray matter volumes. Longer sleep duration was linked to larger white matter hyperintensities (WMHs) and smaller hippocampal volume in an obstructive sleep apnea (OSA) risk group. These associations were consistent across sex and Hispanic/Latino heritage groups.

WarpDrive: Improving spatial normalization using manual refinements

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Association Between Acoustic Features and Brain Volumes: the Framingham Heart Study

Introduction

Although brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging.

Methods

This study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation.

Results

The study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3±3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures.

Discussion

We found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.

Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus

BACKGROUND

Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.

METHODS

We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing.

RESULTS

We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01).

CONCLUSIONS

Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.

Relationships between age, fMRI correlates of familiarity and familiarity-based memory performance under single and dual task conditions

Using fMRI, we investigated the effects of age and divided attention on the neural correlates of familiarity and their relationship with memory performance. At study, word pairs were visually presented to young and older participants under the requirement to make a relational judgment on each pair. Participants were then scanned while undertaking an associative recognition test under single and dual (auditory tone detection) task conditions. The test items comprised studied, rearranged (words from different studied pairs) and new word pairs. fMRI familiarity effects were operationalized as greater activity elicited by studied pairs incorrectly identified as 'rearranged' than by correctly rejected new pairs. The reverse contrast was employed to identify 'novelty' effects. Behavioral familiarity estimates were equivalent across age groups and task conditions. Robust fMRI familiarity effects were identified in several regions, including medial and superior lateral parietal cortex, dorsal medial and left lateral prefrontal cortex, and bilateral caudate. fMRI novelty effects were identified in the anterior medial temporal lobe. Both familiarity and novelty effects were largely age-invariant and did not vary, or varied minimally, according to task condition. In addition, the familiarity effects correlated positively with a behavioral estimate of familiarity strength irrespective of age. These findings extend a previous report from our laboratory, and converge with prior behavioral reports, in demonstrating that the factors of age and divided attention have little impact on behavioral and neural estimates of familiarity.

Fine scale hippocampus morphology variation cross 552 healthy subjects from age 20 to 80

The cerebral cortex varies over the course of a person's life span: at birth, the surface is smooth, before becoming more bumpy (deeper sulci and thicker gyri) in middle age, and thinner in senior years. In this work, a similar phenomenon was observed on the hippocampus. It was previously believed the fine-scale morphology of the hippocampus could only be extracted only with high field scanners (7T, 9.4T); however, recent studies show that regular 3T MR scanners can be sufficient for this purpose. This finding opens the door for the study of fine hippocampal morphometry for a large amount of clinical data. In particular, a characteristic bumpy and subtle feature on the inferior aspect of the hippocampus, which we refer to as hippocampal dentation, presents a dramatic degree of variability between individuals from very smooth to highly dentated. In this report, we propose a combined method joining deep learning and sub-pixel level set evolution to efficiently obtain fine-scale hippocampal segmentation on 552 healthy subjects. Through non-linear dentation extraction and fitting, we reveal that the bumpiness of the inferior surface of the human hippocampus has a clear temporal trend. It is bumpiest between 40 and 50 years old. This observation should be aligned with neurodevelopmental and aging stages.

Hippocampal volume changes across developmental periods in female migraineurs

Brain-related plasticity can occur at a significant rate varying on the developmental period. Adolescence in particular has been identified as a period of growth and change across the structure and function of the nervous system. Notably, research has identified migraines as common in both pediatric and adult populations, but evidence suggests that the phenotype for migraines may differ in these cohorts due to the unique needs of each developmental period. Accordingly, primary aims of this study were to define hippocampal structure in females (7-27 years of age) with and without migraine, and to determine whether this differs across developmental stages (i.e., childhood, adolescence, and young adulthood). Hippocampal volume was quantified based on high-resolution structural MRI using FMRIB's Integrated Registration and Segmentation Tool. Results indicated that migraine and age may have an interactional relationship with hippocampal volume, such that, while hippocampal volumes were lower in female migraineurs (compared to age-matched controls) during childhood and adolescence, this contrast differed during young adulthood whereby hippocampal volumes were higher in migraineurs (compared to age-matched controls). Subsequent vertex analysis localized this interaction effect in hippocampal volume to displacement of the anterior hippocampus. The transition of hippocampal volume during adolescent development in migraineurs suggests that hippocampal plasticity may dynamically reflect components of migraine that change over the lifespan, exerting possible altered responsivity to stress related to migraine attacks thus having physiological expression and psychosocial impact.

Relationships between age, fMRI correlates of familiarity and familiarity-based memory performance under single and dual task conditions

Using fMRI, we investigated the effects of age and divided attention on the neural correlates of familiarity and their relationship with memory performance. At study, word pairs were visually presented to young and older participants under the requirement to make a relational judgment on each pair. Participants were then scanned while undertaking an associative recognition test under single and dual (auditory tone detection) task conditions. The test items comprised studied, rearranged (words from different studied pairs) and new word pairs. fMRI familiarity effects were operationalized as greater activity elicited by studied pairs incorrectly identified as 'rearranged' than by correctly rejected new pairs. The reverse contrast was employed to identify 'novelty' effects. Behavioral familiarity estimates were equivalent across age groups and task conditions. Robust fMRI familiarity effects were identified in several regions, including medial and superior lateral parietal cortex, dorsal medial and left lateral prefrontal cortex, and bilateral caudate. fMRI novelty effects were identified in the anterior medial temporal lobe. Both familiarity and novelty effects were age-invariant and did not vary according to task condition. In addition, the familiarity effects correlated positively with a behavioral estimate of familiarity strength irrespective of age. These findings extend a previous report from our laboratory, and converge with prior behavioral reports, in demonstrating that the factors of age and divided attention have minimal impact on behavioral and neural estimates of familiarity.

Automated and manual segmentation of the hippocampus in human infants

The hippocampus, critical for learning and memory, undergoes substantial changes early in life. Investigating the developmental trajectory of hippocampal structure and function requires an accurate method for segmenting this region from anatomical MRI scans. Although manual segmentation is regarded as the "gold standard" approach, it is laborious and subjective. This has fueled the pursuit of automated segmentation methods in adults. However, little is known about the reliability of these automated protocols in infants, particularly when anatomical scan quality is degraded by head motion or the use of shorter and quieter infant-friendly sequences. During a task-based fMRI protocol, we collected quiet T1-weighted anatomical scans from 42 sessions with awake infants aged 4-23 months. Two expert tracers first segmented the hippocampus in both hemispheres manually. The resulting inter-rater reliability (IRR) was only moderate, reflecting the difficulty of infant segmentation. We then used four protocols to predict these manual segmentations: average adult template, average infant template, FreeSurfer software, and Automated Segmentation of Hippocampal Subfields (ASHS) software. ASHS generated the most reliable hippocampal segmentations in infants, exceeding the manual IRR of experts. Automated methods thus provide robust hippocampal segmentations of noisy T1-weighted infant scans, opening new possibilities for interrogating early hippocampal development.

Multimodal Machine Learning for 10-Year Dementia Risk Prediction: The Framingham Heart Study

BACKGROUND

Early prediction of dementia risk is crucial for effective interventions. Given the known etiologic heterogeneity, machine learning methods leveraging multimodal data, such as clinical manifestations, neuroimaging biomarkers, and well-documented risk factors, could predict dementia more accurately than single modal data.

OBJECTIVE

This study aims to develop machine learning models that capitalize on neuropsychological (NP) tests, magnetic resonance imaging (MRI) measures, and clinical risk factors for 10-year dementia prediction.

METHODS

This study included participants from the Framingham Heart Study, and various data modalities such as NP tests, MRI measures, and demographic variables were collected. CatBoost was used with Optuna hyperparameter optimization to create prediction models for 10-year dementia risk using different combinations of data modalities. The contribution of each modality and feature for the prediction task was also quantified using Shapley values.

RESULTS

This study included 1,031 participants with normal cognitive status at baseline (age 75±5 years, 55.3% women), of whom 205 were diagnosed with dementia during the 10-year follow-up. The model built on three modalities demonstrated the best dementia prediction performance (AUC 0.90±0.01) compared to single modality models (AUC range: 0.82-0.84). MRI measures contributed most to dementia prediction (mean absolute Shapley value: 3.19), suggesting the necessity of multimodal inputs.

CONCLUSION

This study shows that a multimodal machine learning framework had a superior performance for 10-year dementia risk prediction. The model can be used to increase vigilance for cognitive deterioration and select high-risk individuals for early intervention and risk management.

Integrated 3d flow-based multi-atlas brain structure segmentation

MRI brain structure segmentation plays an important role in neuroimaging studies. Existing methods either spend much CPU time, require considerable annotated data, or fail in segmenting volumes with large deformation. In this paper, we develop a novel multi-atlas-based algorithm for 3D MRI brain structure segmentation. It consists of three modules: registration, atlas selection and label fusion. Both registration and label fusion leverage an integrated flow based on grayscale and SIFT features. We introduce an effective and efficient strategy for atlas selection by employing the accompanying energy generated in the registration step. A 3D sequential belief propagation method and a 3D coarse-to-fine flow matching approach are developed in both registration and label fusion modules. The proposed method is evaluated on five public datasets. The results show that it has the best performance in almost all the settings compared to competitive methods such as ANTs, Elastix, Learning to Rank and Joint Label Fusion. Moreover, our registration method is more than 7 times as efficient as that of ANTs SyN, while our label transfer method is 18 times faster than Joint Label Fusion in CPU time. The results on the ADNI dataset demonstrate that our method is applicable to image pairs that require a significant transformation in registration. The performance on a composite dataset suggests that our method succeeds in a cross-modality manner. The results of this study show that the integrated 3D flow-based method is effective and efficient for brain structure segmentation. It also demonstrates the power of SIFT features, multi-atlas segmentation and classical machine learning algorithms for a medical image analysis task. The experimental results on public datasets show the proposed method's potential for general applicability in various brain structures and settings.

Level of LncRNA GAS5 and Hippocampal Volume are Associated with the Progression of Alzheimer’s Disease

Purpose

We evaluated the diagnostic value of long non-coding RNA growth arrest-specific transcript 5 (GAS5) and its relationship with hippocampal volume in Alzheimer’s disease (AD).

Patients and Methods

One hundred and eight patients with AD and 83 healthy controls were included, and demographic data, biochemical parameters, GAS5 levels, and hippocampal volume were recorded. Chi-squared tests or independent sample t-tests were used to compare the baseline characteristics, relative expression of GAS5, and hippocampal volume. Correlations between variables were determined using Spearman’s rank correlation test. Receiver operating characteristic (ROC) curves were generated to compare the diagnostic value of GAS5 and total hippocampal volume in AD.

Results

The levels of GAS5 were significantly upregulated in patients with AD compared with those in controls and were negatively correlated with MMSE score. There were differences in left hippocampal volume, right hippocampal volume, and total hippocampal volume between the two groups. Total hippocampal volume was positively correlated with MMSE score and negatively correlated with GAS5 expression in patients with AD. The area under the curve (AUC) of for GAS5 expression was 0.831, the sensitivity was 61.1%, and the specificity was 95.2%. The AUC of the combined total hippocampal volume was 0.891, the sensitivity was 74.1%, and the specificity was 92.8%.

Conclusion

The results suggested that GAS5 may be an excellent indicator of AD progression alone or in combination with hippocampal volume.

Differential Effects of APOE and Modifiable Risk Factors on Hippocampal Volume Loss and Memory Decline in Aβ- and Aβ+ Older Adults

BACKGROUND AND OBJECTIVES

This prospective study sought to determine the association of modifiable/nonmodifiable components included in the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score with hippocampal volume (HV) loss and episodic memory (EM) decline in cognitively normal (CN) older adults classified as brain β-amyloid (Aβ) negative (Aβ-) or positive (Aβ+).

METHODS

Australian Imaging, Biomarkers and Lifestyle study participants (age 58-91 years) who completed ≥2 neuropsychological assessments and a brain Aβ PET scan (n = 592) were included in this study. We computed the CAIDE risk score (age, sex, APOE ε4 status, education, hypertension, body mass index [BMI], hypercholesterolemia, physical inactivity) and a modifiable CAIDE risk score (CAIDE-MR; education, hypertension, BMI, hypercholesterolemia, physical inactivity) for each participant. Aβ+ was classified using Centiloid >25. Linear mixed models assessed interactions between each CAIDE score, Aβ group, and time on HV loss and EM decline. Age, sex, and APOE ε4 were included as separate predictors in CAIDE-MR models to assess differential associations. Exploratory analyses examined relationships between individual modifiable risk factors and outcomes in Aβ- cognitively normal (CN) adults.

RESULTS

We observed a significant Aβ group × CAIDE × time interaction on HV loss (β [SE] = -0.04 [0.01]; p < 0.000) but not EM decline (β [SE] = -2.33 [9.96]; p = 0.98). Decomposition revealed a significant CAIDE × time interaction in Aβ+ participants only. When modifiable/nonmodifiable CAIDE components were considered separately, we observed a significant Aβ group × CAIDE-MR × time interaction on EM decline only (β [SE] = 3.03 [1.18]; p = 0.01). A significant CAIDE-MR score × time interaction was observed in Aβ- participants only. Significant interactions between APOE ε4 and age × time on HV loss and EM decline were observed in both groups. Exploratory analyses in Aβ- CN participants revealed a significant interaction between BMI × time on EM decline (β [SE] = -3.30 [1.43]; p = 0.02).

DISCUSSION

These results are consistent with studies showing that increasing age and APOE ε4 are associated with increased rates of HV loss and EM decline. In Aβ- CN adults, lower prevalence of modifiable cardiovascular risk factors was associated with less HV loss and EM decline over ∼10 years, suggesting interventions to reduce modifiable cardiovascular risk factors could be beneficial in this group.

An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer's disease

Amyloid positron emission tomography (PET) and hippocampal volume derived from magnetic resonance imaging may be useful clinical biomarkers for differentiating between geriatric depression and Alzheimer's disease (AD). Here we investigated the incremental value of using hippocampal volume and 18F-flutemetmol amyloid PET measures in tandem and sequentially to improve discrimination in unclassified participants. Two approaches were compared in 41 participants with geriatric depression and 27 participants with probable AD: (1) amyloid and hippocampal volume combined in one model and (2) classification based on hippocampal volume first and then subsequent stratification using standardized uptake value ratio (SUVR)-determined amyloid positivity. Hippocampal volume and amyloid SUVR were significant diagnostic predictors of depression (sensitivity: 95%, specificity: 89%). 51% of participants were correctly classified according to clinical diagnosis based on hippocampal volume alone, increasing to 87% when adding amyloid data (sensitivity: 94%, specificity: 78%). Our results suggest that hippocampal volume may be a useful gatekeeper for identifying depressed individuals at risk for AD who would benefit from additional amyloid biomarkers when available.

Agreement Between Automated and Manual MRI Volumetry in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD).

PURPOSE

To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD.

STUDY TYPE

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, and PsycINFO were searched through October 2021.

FIELD STRENGTH

1.0 T, 1.5 T, or 3.0 T.

ASSESSMENT

Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).

STATISTICAL TESTS

Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results.

RESULTS

Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value.

DATA CONCLUSION

While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and large heterogeneity suggest that there is substantial uncontrolled variance. Thus, automated methods may be used to measure these regions in patients with AD but should be used with caution.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Recommendations to Optimize the Use of Volumetric MRI in Huntington's Disease Clinical Trials

Volumetric magnetic resonance imaging (vMRI) has been widely studied in Huntington's disease (HD) and is commonly used to assess treatment effects on brain atrophy in interventional trials. Global and regional trajectories of brain atrophy in HD, with early involvement of striatal regions, are becoming increasingly understood. However, there remains heterogeneity in the methods used and a lack of widely-accessible multisite, longitudinal, normative datasets in HD. Consensus for standardized practices for data acquisition, analysis, sharing, and reporting will strengthen the interpretation of vMRI results and facilitate their adoption as part of a pathobiological disease staging system. The Huntington's Disease Regulatory Science Consortium (HD-RSC) currently comprises 37 member organizations and is dedicated to building a regulatory science strategy to expedite the approval of HD therapeutics. Here, we propose four recommendations to address vMRI standardization in HD research: (1) a checklist of standardized practices for the use of vMRI in clinical research and for reporting results; (2) targeted research projects to evaluate advanced vMRI methodologies in HD; (3) the definition of standard MRI-based anatomical boundaries for key brain structures in HD, plus the creation of a standard reference dataset to benchmark vMRI data analysis methods; and (4) broad access to raw images and derived data from both observational studies and interventional trials, coded to protect participant identity. In concert, these recommendations will enable a better understanding of disease progression and increase confidence in the use of vMRI for drug development.

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

High resolution diffusion tensor imaging of the hippocampus across the healthy lifespan

The human hippocampus is difficult to image given its small size, location, shape, and complex internal architecture. Structural magnetic resonance imaging (MRI) has shown age-related hippocampal volume changes that vary along the anterior-posterior axis. Diffusion tensor imaging (DTI) provides complementary measures related to microstructure, but there are few hippocampus DTI studies investigating change with age in healthy participants, and all have been limited by low spatial resolution. The current study uses high resolution 1 mm isotropic DTI of 153 healthy volunteers aged 5-74 years to investigate diffusion and volume trajectories of the hippocampus (whole, head, body, and tail) and correlations with memory. Hippocampal volume showed age-related changes that differed between head (peaking at midlife), body (no changes), and tail (decreasing across the age span). Fractional anisotropy (FA) and mean, axial, and radial diffusivities (MD, AD, RD) yielded peaks or minima, respectively, at ~30-35 years in all three subregions of the hippocampus. Greater magnitude changes were observed during development than in aging. Age trajectories for both volume and DTI were similar between males and females. Correlations between tests of memory and FA and/or volume were significant in younger subjects (5-17 years), but not in 18-49 year olds or 50-74 year olds. MD was significantly correlated with memory performance in 18-49 year olds, but not in other age groups. Given the diffusion-weighted image contrast and resolution, head digitations could be examined revealing that the majority of subjects had 3-4 (48%) or 2 (32%) bilaterally with no effect of age. One millimeter isotropic DTI yielded high quality diffusion-weighted maps of the human hippocampus that showed regionally specific age effects and cognitive correlations along the anterior-posterior axis from 5 to 74 years.

Association Between Leptin, Cognition, and Structural Brain Measures Among "Early" Middle-Aged Adults: Results from the Framingham Heart Study Third Generation Cohort

BACKGROUND

There is growing interest in the pathophysiological processes of preclinical Alzheimer's disease (AD), including the potential role of leptin. Human studies have shown that both low and high levels of leptin can be associated with worse neurocognitive outcomes, suggesting this relationship may be moderated by another risk factor.

OBJECTIVE

We examined the association between plasma leptin levels and both neuropsychological test performance and structural neuroimaging and assessed whether body mass index (BMI) is an effect modifier of these associations.

METHODS

Our study sample consisted of 2,223 adults from the Framingham Heart Study Third Generation Cohort (average age = 40 years, 53% women).

RESULTS

Among the entire sample, there was no association between leptin and any of the neuropsychological domain measures or any of the MRI brain volume measures, after adjustment for BMI, APOE4, and other clinical factors. However, we did observe that BMI category was an effect modifier for the association between leptin and verbal memory (p for interaction = 0.03), where higher levels of leptin were associated with better performance among normal weight participants (BMI 18.5-24.9) kg/m2 (beta = 0.12, p = 0.02). No association was observed between leptin level and verbal memory test performance among participants who were overweight or obese.

CONCLUSION

These findings suggest that the association between leptin and cognitive function is moderated by BMI category. Prospective examination of individuals transitioning from middle age to older adulthood will help to clarify the contribution of leptin to AD and other neurodegenerative conditions.

The APOE ε4 variant and hippocampal atrophy in Alzheimer's disease and Lewy body dementia: a systematic review of magnetic resonance imaging studies and therapeutic relevance

Introduction: The apolipoprotein E ɛ4-allele (APOE-ɛ4) increases the risk not only for Alzheimer's disease (AD) but also for Parkinson's disease dementia and dementia with Lewy bodies (collectively, Lewy body dementia [LBD]). Hippocampal volume is an important neuroimaging biomarker for AD and LBD, although its association with APOE-ɛ4 is inconsistently reported. We investigated the association of APOE-ε4 with hippocampal atrophy quantified using magnetic resonance imaging in AD and LBD.Areas covered: Databases were searched for volumetric and voxel-based morphometric studies published up until December 31^st, 2020. Thirty-nine studies (25 cross-sectional, 14 longitudinal) were included. We observed that (1) APOE-ε4 was associated with greater rate of hippocampal atrophy in longitudinal studies in AD and in those who progressed from mild cognitive impairment to AD, (2) association of APOE-ε4 with hippocampal atrophy in cross-sectional studies was inconsistent, (3) APOE-ɛ4 may influence hippocampal atrophy in dementia with Lewy bodies, although longitudinal investigations are needed. We comprehensively discussed methodological aspects, APOE-based therapeutic approaches, and the association of APOE-ε4 with hippocampal sub-regions and cognitive performance.Expert opinion: The role of APOE-ɛ4 in modulating hippocampal phenotypes may be further clarified through more homogenous, well-powered, and pathology-proven, longitudinal investigations. Understanding the underlying mechanisms will facilitate the development of prevention strategies targeting APOE-ɛ4.

Diagnostic Performance of Automated MRI Volumetry by icobrain dm for Alzheimer's Disease in a Clinical Setting: A REMEMBER Study

Background:

Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer’s disease (AD) dementia (ADD) patients in selected research cohorts.

Objective:

This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis.

Methods:

The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm’s (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages.

Results:

icobrain dm outperformed FreeSurfer in processing time (15–30 min versus 9–32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%).

Conclusion:

Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting.

Hippocampal vascularization patterns exert local and distant effects on brain structure but not vascular pathology in old age

The hippocampus within the medial temporal lobe is highly vulnerable to age-related pathology such as vascular disease. We examined hippocampal vascularization patterns by harnessing the ultra-high resolution of 7 Tesla magnetic resonance angiography. Dual-supply hemispheres with a contribution of the anterior choroidal artery to hippocampal blood supply were distinguished from single-supply ones with a sole dependence on the posterior cerebral artery. A recent study indicated that a dual vascular supply is related to preserved cognition and structural hippocampal integrity in old age and vascular disease. Here, we examined the regional specificity of these structural benefits at the level of medial temporal lobe sub-regions and hemispheres. In a cross-sectional study with an older cohort of 17 patients with cerebral small vessel disease (70.7  ±  9.0 years, 35.5% female) and 27 controls (71.1  ±  8.2 years, 44.4% female), we demonstrate that differences in grey matter volumes related to the hippocampal vascularization pattern were specifically observed in the anterior hippocampus and entorhinal cortex. These regions were especially bigger in dual-supply hemispheres, but also seemed to benefit from a contralateral dual supply. We further show that total grey matter volumes were greater in people with at least one dual-supply hemisphere, indicating that the hippocampal vascularization pattern has more far-reaching structural implications beyond the medial temporal lobe. A mediation analysis identified total grey matter as a mediator of differences in global cognition. However, our analyses on multiple neuroimaging markers for cerebral small vessel disease did not reveal any evidence that an augmented hippocampal vascularization conveys resistance nor resilience against vascular pathology. We propose that an augmented hippocampal vascularization might contribute to maintaining structural integrity in the brain and preserving cognition despite age-related degeneration. As such, the binary hippocampal vascularization pattern could have major implications for brain structure and function in ageing and dementia independent of vascular pathology, while presenting a simple framework with potential applicability to the clinical setting.

Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population

INTRODUCTION

Hippocampal volume is one of the main biomarkers of Alzheimer's Dementia (AD). Over the years, advanced tools that performed automatic segmentation of Magnetic Resonance Imaging (MRI) T13D scans have been developed, such as FreeSurfer (FS) and ACM-Adaboost (AA). Hippocampal volume is considered abnormal when it is below the 5th percentile of the normative population. The aim of this study was to set norms, established from the Alzheimer's Disease Neuroimaging Initiative (ADNI) population, for hippocampal volume measured with FS v.6.0 and AA tools in the neuGRID platform (www.neugrid2.eu) and demonstrate their applicability for the Italian population.

METHODS

Norms were set from a large group of 545 healthy controls belonging to ADNI. For each pipeline, subjects with segmentation errors were discarded, resulting in 532 valid segmentations for FS and 421 for AA (age range 56-90 years). The comparability of ADNI and the Italian Brain Normative Archive (IBNA), representative of the Italian general population, was assessed testing clinical variables, neuropsychological scores and normalized hippocampal volumes. Finally, percentiles were validated using the Italian Alzheimer's disease Repository Without Borders (ARWiBo) as external independent data set to evaluate FS and AA generalizability.

RESULTS

Hippocampal percentiles were checked with the chi-square goodness of fit test. P-values were not significant, showing that FS and AA algorithm distributions fitted the data well. Clinical, neuropsychological and volumetric features were similar in ADNI and IBNA (p > 0.01). Hippocampal volumes measured with both FS and AA were associated with age (p < 0.001). The 5th percentile thresholds, indicating left/right hippocampal atrophy were respectively: (i) below 3,223/3,456 mm3 at 56 years and 2,506/2,415 mm3 at 90 years for FS; (ii) below 4,583/4,873 mm3 at 56 years and 3,831/3,870 mm3 at 90 years for AA. The average volumes computed on 100 cognitively intact healthy controls (CN) selected from ARWiBo were close to the 50th percentiles, while those for 100 AD patients were close to the abnormal percentiles.

DISCUSSION

Norms generated from ADNI through the automatic FS and AA segmentation tools may be used as normative references for Italian patients with suspected AD.

Clear and Consistent Imaging of Hippocampal Internal Architecture With High Resolution Multiple Image Co-registration and Averaging (HR-MICRA)

Magnetic resonance imaging of hippocampal internal architecture (HIA) at 3T is challenging. HIA is defined by layers of gray and white matter that are less than 1 mm thick in the coronal plane. To visualize HIA, conventional MRI approaches have relied on sequences with high in-plane resolution (≤0.5 mm) but comparatively thick slices (2–5 mm). However, thicker slices are prone to volume averaging effects that result in loss of HIA clarity and blurring of the borders of the hippocampal subfields in up to 61% of slices as has been reported. In this work we describe an approach to hippocampal imaging that provides consistently high HIA clarity using a commonly available sequence and post-processing techniques that is flexible and may be applicable to any MRI platform. We refer to this approach as High Resolution Multiple Image Co-registration and Averaging (HR-MICRA). This approach uses a variable flip angle turbo spin echo sequence to repeatedly acquire a whole brain T2w image volume with high resolution in three dimensions in a relatively short amount of time, and then co-register the volumes to correct for movement and average the repeated scans to improve SNR. We compared the averages of 4, 9, and 16 individual scans in 20 healthy controls using a published HIA clarity rating scale. In the body of the hippocampus, the proportion of slices with good or excellent HIA clarity was 90%, 83%, and 67% for the 16x, 9x, and 4x HR-MICRA images, respectively. Using the 4x HR-MICRA images as a baseline, the 9x HR-MICRA images were 2.6 times and 16x HR-MICRA images were 3.2 times more likely to have high HIA ratings (p < 0.001) across all hippocampal segments (head, body, and tail). The thin slices of the HR-MICRA images allow reformatting in any plane with clear visualization of hippocampal dentation in the sagittal plane. Clear and consistent visualization of HIA will allow application of this technique to future hippocampal structure research, as well as more precise manual or automated segmentation.

Preliminary Findings Associate Hippocampal 1H-MR Spectroscopic Metabolite Concentrations with Psychotic and Manic Symptoms in Patients with Schizophrenia

BACKGROUND AND PURPOSE

Previous hippocampal proton MR spectroscopic imaging distinguished patients with schizophrenia from controls by elevated Cr levels and significantly more variable NAA and Cho concentrations. This goal of this study was to ascertain whether this metabolic variability is associated with clinical features of the syndrome, possibly reflecting heterogeneous hippocampal pathologies and perhaps variability in its "positive" (psychotic) and "negative" (social and emotional deficits) symptoms.

MATERIALS AND METHODS

In a sample of 15 patients with schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, we examined the association of NAA and Cho levels with research diagnostic interviews and clinical symptom ratings of the patients. Metabolite concentrations were previously obtained with 3D proton MR spectroscopic imaging at 3T, a technique that facilitates complete coverage of this small, irregularly shaped, bilateral, temporal lobe structure.

RESULTS

The patient cohort comprised 8 men and 7 women (mean age, 39.1 [SD, 10.8] years, with a mean disease duration of 17.2 [SD, 10.8] years. Despite the relatively modest cohort size, we found the following: 1) Elevated Cho levels predict the positive (psychotic, r = 0.590, P = .021) and manic (r = 0.686, P = .005) symptom severity; and 2) lower NAA levels trend toward negative symptoms (r = 0.484, P = .08). No clinical symptoms were associated with Cr level or hippocampal volume (all, P ≥  .055).

CONCLUSIONS

These preliminary findings suggest that NAA and Cho variations reflect different pathophysiologic processes, consistent with microgliosis/astrogliosis and/or lower vitality (reduced NAA) and demyelination (elevated Cho). In particular, the active state-related symptoms, including psychosis and mania, were associated with demyelination. Consequently, their deviations from the means of healthy controls may be a marker that may benefit precision medicine in selection and monitoring of schizophrenia treatment.

Growth Differentiation Factor 15 and NT-proBNP as Blood-Based Markers of Vascular Brain Injury and Dementia

Background

GDF15 (growth differentiation factor 15) and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) may offer promise as biomarkers for cognitive outcomes, including dementia. We determined the association of these biomarkers with cognitive outcomes in a community‐based cohort.

Methods and Results

Plasma GDF15 (n=1603) and NT‐proBNP levels (n=1590) (53% women; mean age, 68.7 years) were measured in dementia‐free Framingham Offspring cohort participants at examination 7 (1998–2001). Participants were followed up for incident dementia. Secondary outcomes included Alzheimer disease dementia, magnetic resonance imaging structural brain measures, and neurocognitive performance. During a median 11.8‐year follow‐up, 131 participants developed dementia. On multivariable Cox proportional‐hazards analysis, higher circulating GDF15 was associated with an increased risk of incident all‐cause and Alzheimer disease dementia (hazard ratio [HR] per SD increment in natural log‐transformed biomarker value, 1.54 [95% CI, 1.22–1.95] and 1.37 [95% CI, 1.03–1.81], respectively), whereas higher plasma NT‐proBNP was also associated with an increased risk of all‐cause dementia (HR, 1.32; 95% CI, 1.05–1.65). Elevated GDF15 was associated with lower total brain and hippocampal volumes, greater white matter hyperintensity volume, and poorer cognitive performance. Elevated NT‐proBNP was associated with greater white matter hyperintensity volume and poorer cognitive performance. Addition of both biomarkers to a conventional risk factor model improved dementia risk classification (net reclassification improvement index, 0.25; 95% CI, 0.05–0.45).

Conclusions

Elevated plasma GDF15 and NT‐proBNP were associated with vascular brain injury on magnetic resonance imaging, poorer neurocognitive performance, and increased risk of incident dementia in individuals aged >60 years. Both biomarkers improved dementia risk classification beyond that of traditional clinical risk factors, indicating their potential value in predicting incident dementia.

Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change

Accurate, automated white matter hyperintensity (WMH) segmentations are needed for large-scale studies to understand contributions of WMH to neurological diseases. We evaluated Bayesian Model Selection (BaMoS), a hierarchical fully-unsupervised model selection framework for WMH segmentation. We compared BaMoS segmentations to semi-automated segmentations, and assessed whether they predicted longitudinal cognitive change in control, early Mild Cognitive Impairment (EMCI), late Mild Cognitive Impairment (LMCI), subjective/significant memory concern (SMC) and Alzheimer's (AD) participants. Data were downloaded from the Alzheimer's disease Neuroimaging Initiative (ADNI). Magnetic resonance images from 30 control and 30 AD participants were selected to incorporate multiple scanners, and were semi-automatically segmented by 4 raters and BaMoS. Segmentations were assessed using volume correlation, Dice score, and other spatial metrics. Linear mixed-effect models were fitted to 180 control, 107 SMC, 320 EMCI, 171 LMCI and 151 AD participants separately in each group, with the outcomes being cognitive change (e.g. mini-mental state examination; MMSE), and BaMoS WMH, age, sex, race and education used as predictors. There was a high level of agreement between BaMoS' WMH segmentation volumes and a consensus of rater segmentations, with a median Dice score of 0.74 and correlation coefficient of 0.96. BaMoS WMH predicted cognitive change in: control, EMCI, and SMC groups using MMSE; LMCI using clinical dementia rating scale; and EMCI using Alzheimer's disease assessment scale-cognitive subscale (p < 0.05, all tests). BaMoS compares well to semi-automated segmentation, is robust to different WMH loads and scanners, and can generate volumes which predict decline. BaMoS can be applicable to further large-scale studies.

Tractostorm: The what, why, and how of tractography dissection reproducibility

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.

Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm

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icobrain dm is an automated brain MRI segmentation faster than Freesurfer.

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Significantly higher accuracy was obtained for several brain structures, including hippocampus.

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icobrain dm volumes had a test-retest error below normal annual atrophy rates.

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icobrain dm temporal lobe volume had highest sensitivity in discriminating Alzheimer's.

Brain volumes computed from magnetic resonance images have potential for assisting with the diagnosis of individual dementia patients, provided that they have low measurement error and high reliability. In this paper we describe and validate icobrain dm, an automatic tool that segments brain structures that are relevant for differential diagnosis of dementia, such as the hippocampi and cerebral lobes. Experiments were conducted in comparison to the widely used FreeSurfer software. The hippocampus segmentations were compared against manual segmentations, with significantly higher Dice coefficients obtained with icobrain dm (25–75th quantiles: 0.86–0.88) than with FreeSurfer (25–75th quantiles: 0.80–0.83). Other brain structures were also compared against manual delineations, with icobrain dm showing lower volumetric errors overall. Test-retest experiments show that the precision of all measurements is higher for icobrain dm than for FreeSurfer except for the parietal cortex volume. Finally, when comparing volumes obtained from Alzheimer's disease patients against age-matched healthy controls, all measures achieved high diagnostic performance levels when discriminating patients from cognitively healthy controls, with the temporal cortex volume measured by icobrain dm reaching the highest diagnostic performance level (area under the receiver operating characteristic curve = 0.99) in this dataset.

Common misconceptions, hidden biases and modern challenges of dMRI tractography

The human brain is a complex and organized network, where the connection between regions is not achieved with single axons crisscrossing each other but rather millions of densely packed and well-ordered axons. Reconstruction from diffusion MRI tractography is only an attempt to capture the full complexity of this network, at the macroscale. This review provides an overview of the misconceptions, biases and pitfalls present in structural white matter bundle and connectome reconstruction using tractography. The goal is not to discourage readers, but rather to inform them of the limitations present in the methods used by researchers in the field in order to focus on what they can do and promote proper interpretations of their results. It also provides a list of open problems that could be solved in future research projects for the next generation of PhD students.

Shape Information Improves the Cross-Cohort Performance of Deep Learning-Based Segmentation of the Hippocampus

Performing an accurate segmentation of the hippocampus from brain magnetic resonance images is a crucial task in neuroimaging research, since its structural integrity is strongly related to several neurodegenerative disorders, including Alzheimer's disease (AD). Some automatic segmentation tools are already being used, but, in recent years, new deep learning (DL)-based methods have been proven to be much more accurate in various medical image segmentation tasks. In this work, we propose a DL-based hippocampus segmentation framework that embeds statistical shape of the hippocampus as context information into the deep neural network (DNN). The inclusion of shape information is achieved with three main steps: (1) a U-Net-based segmentation, (2) a shape model estimation, and (3) a second U-Net-based segmentation which uses both the original input data and the fitted shape model. The trained DL architectures were tested on image data of three diagnostic groups [AD patients, subjects with mild cognitive impairment (MCI) and controls] from two cohorts (ADNI and AddNeuroMed). Both intra-cohort validation and cross-cohort validation were performed and compared with the conventional U-net architecture and some variations with other types of context information (i.e., autocontext and tissue-class context). Our results suggest that adding shape information can improve the segmentation accuracy in cross-cohort validation, i.e., when DNNs are trained on one cohort and applied to another. However, no significant benefit is observed in intra-cohort validation, i.e., training and testing DNNs on images from the same cohort. Moreover, compared to other types of context information, the use of shape context was shown to be the most successful in increasing the accuracy, while keeping the computational time in the order of a few minutes.

Clinically Significant Visual Deficits after Laser Interstitial Thermal Therapy for Mesiotemporal Epilepsy

BACKGROUND

Laser interstitial thermal therapy (LITT) has recently gained popularity as a minimally invasive surgical option for the treatment of mesiotemporal epilepsy (mTLE). Similar to traditional open procedures for epilepsy, the most frequent neurological complications of LITT are visual deficits; however, a critical analysis of these injuries is lacking.

OBJECTIVES

To evaluate the visual deficits that occur after LITT for mTLE and their etiology.

METHOD

We surveyed five academic epilepsy centers that regularly perform LITT for cases of self-reported postoperative visual deficits. For these patients all pre-, intra- and postoperative MRIs were co-registered with an anatomic atlas derived from 7T MRI data. This was used to estimate thermal injury to early visual pathways and measure imaging variables relevant to the LITT procedure. Using logistic regression, we then compared 14 variables derived from demographics, mesiotemporal anatomy, and the surgical procedure for the patients with visual deficits to a normal cohort comprised of the first 30 patients to undergo this procedure at a single institution.

RESULTS

Of 90 patients that underwent LITT for mTLE, 6 (6.7%) reported a postoperative visual deficit. These included 2 homonymous hemianopsias (HHs), 2 quadrantanopsias, and 2 cranial nerve (CN) IV palsies. These deficits localized to the posterior aspect of the ablation, corresponding to the hippocampal body and tail, and tended to have greater laser energy delivered in that region than the normal cohort. The patients with HH had insult localized to the lateral geniculate nucleus, which was -associated with young age and low choroidal fissure CSF volume. Quadrantanopsia, likely from injury to the optic radiation in Meyer's loop, was correlated with a lateral trajectory and excessive energy delivered at the tail end of the ablation. Patients with CN IV injury had extension of contrast to the tentorial edge associated with a mesial laser trajectory.

CONCLUSIONS

LITT for epilepsy may be complicated by various classes of visual deficit, each with distinct etiology and clinical significance. It is our hope that by better understanding these injuries and their mechanisms we can eventually reduce their occurrence by identifying at-risk patients and trajectories and appropriately tailoring the ablation procedure.

Effect of APOE Genotype on Plasma Docosahexaenoic Acid (DHA), Eicosapentaenoic Acid, Arachidonic Acid, and Hippocampal Volume in the Alzheimer's Disease Cooperative Study-Sponsored DHA Clinical Trial

BACKGROUND

Docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and arachidonic acid (AA) play key roles in several metabolic processes relevant to Alzheimer's disease (AD) pathogenesis and neuroinflammation. Carrying the APOEɛ4 allele (APOE4) accelerates omega-3 polyunsaturated fatty acid (PUFA) oxidation. In a pre-planned subgroup analysis of the Alzheimer's Disease Cooperative Study-sponsored DHA clinical trial, APOE4 carriers with mild probable AD had no improvements in cognitive outcomes compared to placebo, while APOE 4 non-carriers showed a benefit from DHA supplementation.

OBJECTIVE

We sought to clarify the effect of APOEɛ4/ɛ4 on both the ratio of plasma DHA and EPA to AA, and on hippocampal volumes after DHA supplementation.

METHODS

Plasma fatty acids and APOE genotype were obtained in 275 participants randomized to 18 months of DHA supplementation or placebo. A subset of these participants completed brain MRI imaging (n = 86) and lumbar punctures (n = 53).

RESULTS

After the intervention, DHA-treated APOEɛ3/ɛ3 and APOEɛ2/ɛ3 carriers demonstrated significantly greater increase in plasma DHA/AA compared to ɛ4/ɛ4 carriers. APOEɛ2/ɛ3 had a greater increase in plasma EPA/AA and less decline in left and right hippocampal volumes compared to compared to ɛ4/ɛ4 carriers. The change in plasma and cerebrospinal fluid DHA/AA was strongly correlated. Greater baseline and increase in plasma EPA/AA was associated with a lower decrease in the right hippocampal volume, but only in APOE 4 non-carriers.

CONCLUSION

The lower increase in plasma DHA/AA and EPA/AA in APOEɛ4/ɛ4 carriers after DHA supplementation reduces brain delivery and affects the efficacy of DHA supplementation.

Overview of MR Imaging Volumetric Quantification in Neurocognitive Disorders

This review article provides a general overview on the various methodologies for quantifying brain structure on magnetic resonance images of the human brain. This overview is followed by examples of applications in Alzheimer dementia and mild cognitive impairment. Other examples will include traumatic brain injury and other neurodegenerative dementias. Finally, an overview of general principles for protocol acquisition of magnetic resonance imaging for volumetric quantification will be discussed along with the current choices of FDA cleared algorithms for use in clinical practice.

Progress update from the hippocampal subfields group

INTRODUCTION

Heterogeneity of segmentation protocols for medial temporal lobe regions and hippocampal subfields on in vivo magnetic resonance imaging hinders the ability to integrate findings across studies. We aim to develop a harmonized protocol based on expert consensus and histological evidence.

METHODS

Our international working group, funded by the EU Joint Programme-Neurodegenerative Disease Research (JPND), is working toward the production of a reliable, validated, harmonized protocol for segmentation of medial temporal lobe regions. The working group uses a novel postmortem data set and online consensus procedures to ensure validity and facilitate adoption.

RESULTS

This progress report describes the initial results and milestones that we have achieved to date, including the development of a draft protocol and results from the initial reliability tests and consensus procedures.

DISCUSSION

A harmonized protocol will enable the standardization of segmentation methods across laboratories interested in medial temporal lobe research worldwide.

Assessment of longitudinal hippocampal atrophy in the first year after ischemic stroke using automatic segmentation techniques

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First-year hippocampal atrophy in stroke is more accelerated ipsi-lesionally.

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Volume estimation is not impacted by hemisphere side, study group, or scan timepoint.

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Segmentation method-hippocampal size interaction determines volume estimation.

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FreeSurfer/Subfields and fsl/FIRST segmentations agreed best with manual tracing.

We assessed first-year hippocampal atrophy in stroke patients and healthy controls using manual and automated segmentations: AdaBoost, FIRST (fsl/v5.0.8), FreeSurfer/v5.3 and v6.0, and Subfields (in FreeSurfer/v6.0). We estimated hippocampal volumes in 39 healthy controls and 124 stroke participants at three months, and 38 controls and 113 stroke participants at one year. We used intra-class correlation, concordance, and reduced major axis regression to assess agreement between automated and ‘Manual’ estimations. A linear mixed-effect model was used to characterize hippocampal atrophy.

Overall, hippocampal volumes were reduced by 3.9% in first-ever stroke and 9.2% in recurrent stroke at three months post-stroke, with comparable ipsi-and contra-lesional reductions in first-ever stroke. Mean atrophy rates between time points were 0.5% for controls and 1.0% for stroke patients (0.6% contra-lesionally, 1.4% ipsi-lesionally). Atrophy rates in left and right-hemisphere strokes were comparable. All methods revealed significant volume change in first-ever and ipsi-lesional stroke (p < 0.001).

Hippocampal volume estimation was not impacted by hemisphere, study group, or scan time point, but rather, by the interaction between the automated segmentation method and hippocampal size. Compared to Manual, Subfields and FIRST recorded the lowest bias. FreeSurfer/v5.3 overestimated volumes the most for large hippocampi, while FIRST was the most accurate in estimating small volumes. AdaBoost performance was average.

Our findings suggest that first-year ipsi-lesional hippocampal atrophy rate especially in first-ever stroke, is greater than atrophy rates in healthy controls and contra-lesional stroke. Subfields and FIRST can complementarily be effective in characterizing the hippocampal atrophy in healthy and stroke cohorts.

White Matter Hyperintensities and Hippocampal Atrophy in Relation to Cognition: The 90+ Study

OBJECTIVES

To study the interactive effect of white matter hyperintensities (WMH) and hippocampal atrophy on cognition in the oldest old.

DESIGN

Ongoing longitudinal study.

SETTING

In Southern California, brain magnetic resonance imaging (MRI) scans were conducted between May 2014 and December 2017.

PARTICIPANTS

Individuals from The 90+ Study with a valid brain MRI scan (N = 141; 94 cognitively normal and 47 with cognitive impairment).

MEASUREMENTS

Cognitive testing was performed every 6 months with a mean follow-up of 2 years and included these tests: Mini-Mental State Examination (MMSE), modified MMSE (3MS), California Verbal Learning Test (CVLT) immediate recall over four trials and delayed recall, Digit Span Backward, Animal Fluency, and Trail Making Test (TMT) A, B, and C. We used one linear mixed model for each cognitive test to study the baseline and longitudinal association of WMH and hippocampal volume (HV) with cognition. Models were adjusted for age, sex, and education.

RESULTS

Mean age was 94.3 years (standard deviation [SD] = 3.2 y). At baseline, higher WMH volumes were associated with worse scores on the 3MS, CVLT immediate and delayed recall, and TMT B. Lower HVs were associated with worse baseline scores on all cognitive tests, except for the Digit Span Backward. Longitudinally, higher WMH and lower HVs were associated with faster decline in the 3MS and MMSE, and lower HV was also associated with faster decline in the CVLT immediate recall. No association was observed between WMH and HV and no interaction between WMH and HV in their association with baseline cognition or cognitive decline.

CONCLUSION

We show that WMH and hippocampal atrophy have an independent, negative effect on cognition that make these biomarkers relevant to evaluate in the diagnostic work-up of the oldest-old individuals with cognitive complaints. However, the predictive value of WMH for cognitive decline seems to be less evident in the oldest-old compared with a younger group of older adults. J Am Geriatr Soc 67:1827-1834, 2019.

Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease

Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.

Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors.

Hippocampal sulcal cavities: prevalence, risk factors and association with cognitive performance. The SMART-Medea study and PREDICT-MR study

Hippocampal sulcal cavities (HSCs) are frequently observed on MRI, but their etiology and relevance is unclear. HSCs may be anatomical variations, or result from pathology. We assessed the presence of HSCs, and their cross-sectional association with demographics, vascular risk factors and cognitive functioning in two study samples. Within a random sample of 92 patients with vascular disease from the SMART-Medea study (mean age = 62, SD = 9 years) and 83 primary care patients from the PREDICT-MR study (mean age = 62, SD = 12 years) one rater manually scored HSCs at 1.5 T 3D T1-weighted coronal images blind to patient information. We estimated relative risks of age, sex and vascular risk factors with presence of HSCs using Poisson regression with log-link function and robust standard errors adjusted for age and sex. Using ANCOVA adjusted for age, sex, and education we estimated the association of the number of HSCs with memory, executive functioning, speed, and working memory. In the SMART-Medea study HSCs were present in 65% and in 52% in the PREDICT-MR study (χ2 = 2.99, df = 1, p = 0.08). In both samples, no significant associations were observed between presence of HSCs and age (SMART-Medea: RR = 1.00; 95%CI 0.98-1.01; PREDICT-MR: RR = 1.01; 95%CI 0.99-1.03), sex, or vascular risk factors. Also, no associations between HSCs and cognitive functioning were found in either sample. HSCs are frequently observed on 1.5 T MRI. Our findings suggest that, in patients with a history of vascular disease and primary care attendees, HSCs are part of normal anatomic variation of the human hippocampus rather than markers of pathology.

Visual Deficit From Laser Interstitial Thermal Therapy for Temporal Lobe Epilepsy: Anatomical Considerations

BACKGROUND

Laser interstitial thermal therapy (LITT) is quickly emerging as an effective surgical therapy for temporal lobe epilepsy (TLE). One of the most frequent complications of the procedure is postoperative visual field cuts, but the physiopathology of these deficits is unknown.

OBJECTIVE

To evaluate potential causes of visual deficits after LITT for TLE in an attempt to minimize this complication.

METHODS

This retrospective chart review compares the case of a 24-year-old male who developed homonymous hemianopsia following LITT for TLE to 17 prior patients who underwent the procedure and suffered no visual deficit. We examined both features of the surgical approach (trajectory, laser energy, ablation size) and of preoperative surgical anatomy, derived from volumetric tracings of mesiotemporal structures.

RESULTS

For the patient with postoperative homonymous hemianopsia imaging suggested inadvertent ablation of the lateral geniculate nucleus, although the laser was positioned entirely within the hippocampus. This patient's laser trajectory, ablation number, energy delivered, and ablation size were not significantly different from the prior patients. However, the subject with the visual deficit did have significantly smaller choroidal fissure cerebrospinal fluid volume.

CONCLUSION

Visual deficits are the most common complication of LITT for mesiotemporal epilepsy and patients at most risk may have small cerebrospinal fluid volume in the choroidal fissure, allowing heat to spread from the hippocampal body to the lateral geniculate nucleus. When such anatomy is identified on preoperative magnetic resonance imaging, we recommend lowering laser trajectory, decreasing ablation power through the hippocampal body, and using temperature safety markers at the lower thalamic border.

Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia

OBJECTIVE

To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD).

BACKGROUND

Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans.

MATERIALS AND METHODS

Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20  AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods.

RESULTS

Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other.

DISCUSSION AND CONCLUSION

Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.

Bilateral volume reduction in posterior hippocampus in psychosis of epilepsy

OBJECTIVE

Psychosis of epilepsy (POE) occurs more frequently in temporal lobe epilepsy, raising the question as to whether abnormalities of the hippocampus are aetiologically important. Despite decades of investigation, it is unclear whether hippocampal volume is reduced in POE, perhaps due to small sample sizes and methodological limitations of past research.

METHODS

In this study, we examined the volume of the total hippocampus, and the hippocampal head, body and tail, in a large cohort of patients with POE and patients with epilepsy without psychosis (EC). One hundred adults participated: 50 with POE and 50 EC. Total and subregional hippocampal volumes were manually traced and compared between (1) POE and EC; (2) POE with temporal lobe epilepsy, extratemporal lobe epilepsy and generalised epilepsy; and (3) patients with POE with postictal psychosis (PIP) and interictal psychosis (IP).

RESULTS

Compared with EC the POE group had smaller total left hippocampus volume (13.5% decrease, p<0.001), and smaller left hippocampal body (13.3% decrease, p=0.002), and left (41.5% decrease, p<0.001) and right (36.4% decrease, p<0.001) hippocampal tail volumes. Hippocampal head volumes did not differ between groups.

CONCLUSION

Posterior hippocampal volumes are bilaterally reduced in POE. Volume loss was observed on a posteroanterior gradient, with severe decreases in the tail and moderate volume decreases in the body, with no difference in the hippocampal head. Posterior hippocampal atrophy is evident to a similar degree in PIP and IP. Our findings converge with those reported for the paradigmatic psychotic disorder, schizophrenia, and suggest that posterior hippocampal atrophy may serve as a biomarker of the risk for psychosis, including in patients with epilepsy.