A (Sub)field Guide to Quality Control in Hippocampal Subfield Segmentation on Highresolution T2-weighted MRI.

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.

Tau-Neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum.

Variability in the relationship of tau-based neurofibrillary tangles (T) and degree of neurodegeneration (N) in Alzheimer's Disease (AD) is likely attributable to the non-specific nature of N, which is also modulated by such factors as other co-pathologies, age-related changes, and developmental differences. We studied this variability by partitioning patients within the Alzheimer's continuum into data-driven groups based on their regional T-N dissociation, which reflects the residuals after the effect of tau pathology is "removed". We found six groups displaying distinct spatial T-N mismatch and thickness patterns despite similar tau burden. Their T-N patterns resembled the neurodegeneration patterns of non-AD groups partitioned on the basis of z-scores of cortical thickness alone and were similarly associated with surrogates of non-AD factors. In an additional sample of individuals with antemortem imaging and autopsy, T-N mismatch was associated with TDP-43 co-pathology. Finally, T-N mismatch training was then applied to a separate cohort to determine the ability to classify individual patients within these groups. These findings suggest that T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability to Alzheimer's disease.

Downstream effects of polypathology on neurodegeneration of medial temporal lobe subregions.

The medial temporal lobe (MTL) is a nidus for neurodegenerative pathologies and therefore an important region in which to study polypathology. We investigated associations between neurodegenerative pathologies and the thickness of different MTL subregions measured using high-resolution post-mortem MRI. Tau, TAR DNA-binding protein 43 (TDP-43), amyloid-ß and α-synuclein pathology were rated on a scale of 0 (absent)-3 (severe) in the hippocampus and entorhinal cortex (ERC) of 58 individuals with and without neurodegenerative diseases (median age 75.0 years, 60.3% male). Thickness measurements in ERC, Brodmann Area (BA) 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare (SRLM) were derived from 0.2 × 0.2 × 0.2 mm3 post-mortem MRI scans of excised MTL specimens from the contralateral hemisphere using a semi-automated approach. Spearman's rank correlations were performed between neurodegenerative pathologies and thickness, correcting for age, sex and hemisphere, including all four proteinopathies in the model. We found significant associations of (1) TDP-43 with thickness in all subregions (r = - 0.27 to r = - 0.46), and (2) tau with BA35 (r = - 0.31) and SRLM thickness (r = - 0.33). In amyloid-ß and TDP-43 negative cases, we found strong significant associations of tau with ERC (r = - 0.40), BA35 (r = - 0.55), subiculum (r = - 0.42) and CA1 thickness (r = - 0.47). This unique dataset shows widespread MTL atrophy in relation to TDP-43 pathology and atrophy in regions affected early in Braak stageing and tau pathology. Moreover, the strong association of tau with thickness in early Braak regions in the absence of amyloid-ß suggests a role of Primary Age-Related Tauopathy in neurodegeneration.

Pathological drivers of neurodegeneration in suspected non-Alzheimer's disease pathophysiology.

BACKGROUND: Little is known about the heterogeneous etiology of suspected non-Alzheimer's pathophysiology (SNAP), a group of subjects with neurodegeneration in the absence of ß-amyloid. Using antemortem MRI and pathological data, we investigated the etiology of SNAP and the association of neurodegenerative pathologies with structural medial temporal lobe (MTL) measures in ß-amyloid-negative subjects. METHODS: Subjects with antemortem MRI and autopsy data were selected from ADNI (n=63) and the University of Pennsylvania (n=156). Pathological diagnoses and semi-quantitative scores of MTL tau, neuritic plaques, α-synuclein, and TDP-43 pathology and MTL structural MRI measures from antemortem T1-weighted MRI scans were obtained. ß-amyloid status (A+/A-) was determined by CERAD score and neurodegeneration status (N+/N-) by hippocampal volume. RESULTS: SNAP reflects a heterogeneous group of pathological diagnoses. In ADNI, SNAP (A-N+) had significantly more neuropathological diagnoses than A+N+. In the A- group, tau pathology was associated with hippocampal, entorhinal cortex, and Brodmann area 35 volume/thickness and TDP-43 pathology with hippocampal volume. CONCLUSION: SNAP had a heterogeneous profile with more mixed pathologies than A+N+. Moreover, a role for TDP-43 and tau pathology in driving MTL neurodegeneration in the absence of ß-amyloid was supported.

Defining SNAP by cross-sectional and longitudinal definitions of neurodegeneration.

Introduction: Suspected non-Alzheimer's pathophysiology (SNAP) is a biomarker driven designation that represents a heterogeneous group in terms of etiology and prognosis. SNAP has only been identified by cross-sectional neurodegeneration measures, whereas longitudinal measures might better reflect "active" neurodegeneration and might be more tightly linked to prognosis. We compare neurodegeneration defined by cross-sectional 'hippocampal volume' only (SNAP/L-) versus both cross-sectional and longitudinal 'hippocampal atrophy rate' (SNAP/L+) and investigate how these definitions impact prevalence and the clinical and biomarker profile of SNAP in Mild Cognitive Impairment (MCI). Methods: 276 MCI patients from ADNI-GO/2 were designated amyloid "positive" (A+) or "negative" (A-) based on their florbetapir scan and neurodegeneration 'positive' or 'negative' based on cross-sectional hippocampal volume and longitudinal hippocampal atrophy rate. Results: 74.1% of all SNAP participants defined by the cross-sectional definition of neurodegeneration also met the longitudinal definition of neurodegeneration, whereas 25.9% did not. SNAP/L+ displayed larger white matter hyperintensity volume, a higher conversion rate to dementia over 5 years and a steeper decline on cognitive tasks compared to SNAP/L- and the A- CN group. SNAP/L- had more abnormal values on neuroimaging markers and worse performance on cognitive tasks than the A- CN group, but did not show a difference in dementia conversion rate or longitudinal cognition. Discussion: Using a longitudinal definition of neurodegeneration in addition to a cross-sectional one identifies SNAP participants with significant cognitive decline and a worse clinical prognosis for which cerebrovascular disease may be an important driver.

Bergmann glia translocation: a new disease marker for vanishing white matter identifies therapeutic effects of Guanabenz treatment.

AIM: Vanishing White Matter (VWM) is a devastating leucoencephalopathy without effective treatment options. Patients have mutations in the EIF2B1-5 genes, encoding the five subunits of eIF2B, a guanine exchange factor that is an important regulator of protein translation. We recently developed mouse models for VWM that replicate the human disease. To study disease improvement after treatment in these mice, it is essential to have sensitive biomarkers related to disease stage. The Bergmann glia of the cerebellum, an astrocytic subpopulation, translocate into the molecular layer in symptomatic VWM mice and patients. This study looked at the prospects of using Bergmann glia pathology as an objective disease marker for VWM. METHODS: We defined a new quantitative measurement of Bergmann glia pathology in the cerebellum of VWM mice and patients. To test the sensitivity of this new marker for improvement, VWM mutant mice received long-term treatment with Guanabenz, an FDA-approved anti-hypertensive agent affecting eIF2B activity. RESULTS: Bergmann glia translocation was significantly higher in symptomatic VWM mice and VWM patients than in controls and worsened over the disease course. Both Bergmann glia pathology and cerebellar myelin pathology improved with Guanabenz treatment in mice, showing that Bergmann glia translocation is a sensitive measurement for improvement. CONCLUSIONS: Bergmann glia translocation can be used to objectively assess effects of treatment in VWM mice. Future treatment strategies involving compounds regulating eIF2 phosphorylation might benefit VWM patients.

A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI.

Recent advances in MRI and increasing knowledge on the characterization and anatomical variability of medial temporal lobe (MTL) anatomy have paved the way for more specific subdivisions of the MTL in humans. In addition, recent studies suggest that early changes in many neurodegenerative and neuropsychiatric diseases are better detected in smaller subregions of the MTL rather than with whole structure analyses. Here, we developed a new protocol using 7 Tesla (T) MRI incorporating novel anatomical findings for the manual segmentation of entorhinal cortex (ErC), perirhinal cortex (PrC; divided into area 35 and 36), parahippocampal cortex (PhC), and hippocampus; which includes the subfields subiculum (Sub), CA1, CA2, as well as CA3 and dentate gyrus (DG) which are separated by the endfolial pathway covering most of the long axis of the hippocampus. We provide detailed instructions alongside slice-by-slice segmentations to ease learning for the untrained but also more experienced raters. Twenty-two subjects were scanned (19-32 yrs, mean age = 26 years, 12 females) with a turbo spin echo (TSE) T2-weighted MRI sequence with high-resolution oblique coronal slices oriented orthogonal to the long axis of the hippocampus (in-plane resolution 0.44 × 0.44 mm2) and 1.0 mm slice thickness. The scans were manually delineated by two experienced raters, to assess intra- and inter-rater reliability. The Dice Similarity Index (DSI) was above 0.78 for all regions and the Intraclass Correlation Coefficients (ICC) were between 0.76 to 0.99 both for intra- and inter-rater reliability. In conclusion, this study presents a fine-grained and comprehensive segmentation protocol for MTL structures at 7 T MRI that closely follows recent knowledge from anatomical studies. More specific subdivisions (e.g. area 35 and 36 in PrC, and the separation of DG and CA3) may pave the way for more precise delineations thereby enabling the detection of early volumetric changes in dementia and neuropsychiatric diseases.

Comparison of In Vivo and Ex Vivo MRI of the Human Hippocampal Formation in the Same Subjects.

Multiple techniques for quantification of hippocampal subfields from in vivo MRI have been proposed. Linking in vivo MRI to the underlying histology can help validate and improve these techniques. High-resolution ex vivo MRI can provide an intermediate modality to map information between these very different imaging modalities. This article evaluates the ability to match information between in vivo and ex vivo MRI in the same subjects. We perform rigid and deformable registration on 10 pairs of in vivo (3 T, 0.4 × 0.4 × 2.6 mm3) and ex vivo (9.4 T, 0.2 × 0.2 × 0.2 mm3) scans, and describe differences in MRI appearance between these modalities qualitatively and quantitatively. The feasibility of using this dataset to validate in vivo segmentation is evaluated by applying an automatic hippocampal subfield segmentation technique (ASHS) to in vivo scans and comparing SRLM (stratum/radiatum/lacunosum/moleculare) surface to manual tracing on corresponding ex vivo scans (and in 2 cases, histology). Regional increases in thickness are detected in ex vivo scans adjacent to the ventricles and were not related to scanner, resolution differences, or susceptibility artefacts. Satisfactory in vivo/ex vivo registration and subvoxel accuracy of ASHS segmentation of hippocampal SRLM demonstrate the feasibility of using this dataset for validation, and potentially, improvement of in vivo segmentation methods.

Automated Hippocampal Subfield Segmentation at 7T MRI.

BACKGROUND AND PURPOSE: High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI. MATERIALS AND METHODS: The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm(3) T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation. RESULTS: Comparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields. CONCLUSIONS: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/.

Major depressive episodes over the course of 7 years and hippocampal subfield volumes at 7 tesla MRI: the PREDICT-MR study.

INTRODUCTION: Smaller hippocampal volumes have been associated with major depressive disorder (MDD). The hippocampus consists of several subfields that may be differentially related to MDD. We investigated the association of occurrence of major depressive episodes (MDEs), assessed five times over seven years, with hippocampal subfield and entorhinal cortex volumes at 7 tesla MRI. METHODS: In this prospective study of randomly selected general practice attendees, MDEs according to DSM-IV-R criteria were assessed at baseline and after 6, 12, 39 and 84 months follow-up. At the last follow-up, a T2 (0.7 mm(3)) 7 tesla MRI scan was obtained in 47 participants (60±10 years). The subiculum, cornu ammonis (CA) 1 to 3, dentate gyrus&CA4 and entorhinal cortex volumes were manually segmented according a published protocol. RESULTS: Of the 47 participants, 13 had one MDE and 5 had multiple MDEs. ANCOVAs, adjusted for age, sex, education and intracranial volume, revealed no significant differences in hippocampal subfield or entorhinal cortex volumes between participants with and without an MDE in the preceding 84 months. Multiple episodes were associated with smaller subiculum volumes (B=-0.03 mL/episode; 95% CI -0.06; -0.003), but not with the other hippocampal subfield volumes, entorhinal cortex, or total hippocampal volume. LIMITATIONS: A limitation of this study is the small sample size which makes replication necessary. CONCLUSIONS: In this exploratory study, we found that an increasing number of major depressive episodes was associated with smaller subiculum volumes in middle-aged and older persons, but not with smaller volumes in other hippocampal subfields or the entorhinal cortex.

Subfields of the hippocampal formation at 7 T MRI: in vivo volumetric assessment.

Animal and human autopsy studies suggest that subfields of the hippocampal formation are differentially affected by neuropsychiatric diseases. Therefore, subfield volumes may be more sensitive to effects of disease processes. The few human studies that segmented subfields of the hippocampal formation in vivo either assessed the subfields only in the body of the hippocampus, assessed only three subfields, or did not take the differential angulation of the head of the hippocampus into account. We developed a protocol using 7 Tesla MRI with isotropic voxels to reliably delineate the entorhinal cortex (ERC), subiculum (SUB), CA1, CA2, CA3, dentate gyrus (DG)&CA4 along the full-length of the hippocampus. Fourteen subjects (aged 54-74 years, 2 men and 12 women) were scanned with a 3D turbo spin echo (TSE) sequence with isotropic voxels of 0.7 × 0.7 × 0.7 mm(3) on a 7 T MRI whole body scanner. Based on previous protocols and extensive anatomic atlases, a new protocol for segmentation of subfields of the hippocampal formation was formulated. ERC, SUB, CA1, CA2, CA3 and DG&CA4 were manually segmented twice by one rater from coronal MR images. Good-to-excellent consistency was found for all subfields (Intraclass Correlation Coefficient's (ICC) varying from 0.74 to 0.98). Accuracy as measured with the Dice Similarity Index (DSI) was above 0.82 for all subfields, with the exception of the smaller subfield CA3 (0.68-0.70). In conclusion, this study shows that it is possible to delineate the main subfields of the hippocampal formation along its full-length in vivo at 7 T MRI. Our data give evidence that this can be done in a reliable manner. Segmentation of subfields in the full-length of the hippocampus may bolster the study of the etiology neuropsychiatric diseases.

The role of the second and third extracellular loops of the adenosine A1 receptor in activation and allosteric modulation.

The adenosine A1 receptor is a member of the large membrane protein family that signals through G proteins, the G protein-coupled receptors (GPCRs). GPCRs consist of seven transmembrane domains connected by three intracellular and three extracellular loops. Their N-terminus is extracellular, the C-terminal tail is in the cytoplasm. The transmembrane domains in receptor subfamilies that bind the same endogenous ligand, such as dopamine or adenosine, tend to be highly similar. In contrast, the loop regions can vary greatly, both in sequence and in length, and the role these loops have in the activation mechanism of the receptors remains unclear. Here, we investigated the activating role of the second and third extracellular loop of the human adenosine A1 receptor. By means of an (Ala)3 mutagenic scan in which consecutive sets of three amino acids were mutated into alanine residues in EL2 and a classical alanine scan in EL3, we revealed a strong regulatory role for the second extracellular loop (EL2) of the human adenosine A1 receptor. Besides many residues in the second and the third extracellular loops important for adenosine A1 receptor activation, we also identified two residues in EL2, a tryptophan and a glutamate, that affect the influence of the allosteric modulator PD81,723. These results, combined with a comparison of the different receptor loop regions, provide insight in the activation mechanism of this typical class A GPCR and further emphasize the unique pharmacological profile the loops can provide to individual receptors, even within subfamilies of GPCRs.