Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain

Experimental Ischemic Stroke Induces Secondary Bihemispheric White Matter Degeneration and Long-Term Cognitive Impairment

Clinical studies have identified widespread white matter degeneration in ischemic stroke patients. However, contemporary research in stroke has predominately focused on the infarct and periinfarct penumbra regions. The involvement of white matter degeneration after ischemic stroke and its contribution to post-stroke cognitive impairment and dementia (PSCID) has remained less explored in experimental models. In this study, we examined the progression of locomotor and cognitive function up to 4 months after inducing ischemic stroke by middle cerebral artery occlusion in young adult rats. Despite evident ongoing locomotor recovery, long-term cognitive and affective impairments persisted after ischemic stroke, as indicated by Morris water maze, elevated plus maze, and open field performance. At 4 months after stroke, multimodal MRI was conducted to assess white matter degeneration. T2-weighted MRI (T2WI) unveiled bilateral cerebroventricular enlargement after ischemic stroke. Fluid Attenuated Inversion Recovery MRI (FLAIR) revealed white matter hyperintensities in the corpus callosum and fornix across bilateral hemispheres. A positive association between the volume of white matter hyperintensities and total cerebroventricular volume was noted in stroke rats. Further evidence of bilateral white matter degeneration was indicated by the reduction of fractional anisotropy and quantitative anisotropy at bilateral corpus callosum in diffusion-weighted MRI (DWI) analysis. Additionally, microglia and astrocyte activation were identified in the bilateral corpus callosum after stroke. Our study suggests that experimental ischemic stroke induced by MCAO in young rat replicate long-term cognitive impairment and bihemispheric white matter degeneration observed in ischemic stroke patients. This model provides an invaluable tool for unraveling the mechanisms underlying post-stroke secondary white matter degeneration and its contribution to PSCID.

Aging and urinary control: Alterations in the brain-bladder axis

Age-associated alterations in bladder control affect millions of older adults, with a heavy burden added to families both economically and in quality of life. Therapeutic options are limited with poor efficacy in older adults, lending to a growing need to address the gaps in our current understanding of urinary tract aging. This review summarizes the current knowledge of age-associated alterations in the structure and function of the brain-bladder axis and identifies important gaps in the field that have yet to be addressed. Urinary aging is associated with decreased tissue responsiveness, decreased control over the voiding reflex, signaling dysfunction along the brain-bladder axis, and structural changes within the bladder wall. Studies are needed to improve our understanding of how age affects the brain-bladder axis and identify genetic targets that correlate with functional outcomes.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62×10-32; T1: r=0.61, p=1.45×10-26, FW+T1: r=0.77, p=6.48×10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32×10-7; T1: β=-1.331, p=6.52×10-7; FW+T1: β=-1.476, p=2.53×10-10; executive function, FW: β=-1.276, p=1.46×10-9; T1: β=-1.337, p=2.52×10-7; FW+T1: β=-1.850, p=3.85×10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62×10-11; T1: β=-0.097, p=1.40×10-8; FW+T1: β=-0.101, p=1.35×10-11; executive function, FW: β=-0.125, p=1.20×10-10; T1: β=-0.163, p=4.25×10-12; FW+T1: β=-0.158, p=1.65×10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Increased risk for ex-vacuo ventriculomegaly with leukoencephalopathy (EVL) in whole brain radiation therapy and repeat radiosurgery treated brain metastasis patients

INTRODUCTION

Cerebral atrophy with leukoencephalopathy is a known morbidity after whole brain radiation therapy (WBRT), resulting in ex-vacuo ventriculomegaly with leukoencephalopathy (EVL). Here we studied the correlation between WBRT, stereotactic radiosurgery (SRS), and risk for EVL in brain metastases patients.

METHODS

In a retrospective study, we identified 195 patients (with 1,018 BM) who underwent SRS for BM (2007-2017) and had > 3 months of MRI follow-up. All patients who underwent ventriculoperitoneal shunting were excluded. Cerebral atrophy was measured by ex-vacuo-ventriculomegaly, defined based on Evans' criteria. Demographic and clinical variables were analyzed using logistic regression models.

RESULTS

Ex-vacuo ventriculomegaly was observed on pre-radiosurgery imaging in 29.7% (58/195) of the study cohort. On multivariate analysis, older age was the only variable associated with pre-radiosurgery ventriculomegaly. Of the 137 patients with normal ventricular size before radiosurgery, 27 (19.7 %) developed ex-vacuo ventriculomegaly and leukoencephalopathy (EVL) post-SRS. In univariate analysis, previous whole brain radiation therapy was the main factor associated with increased risk for developing EVL (OR = 5.08, p < 0.001). In bivariate models that included prior receipt of WBRT, both the number of SRS treatments (OR = 1.499, p = 0.025) and WBRT (OR = 11.321, p = 0.003 were independently associated with increased EVL risk.

CONCLUSIONS

While repeat radiosurgery contributes to the risk of EVL in BM patients, this risk is ∼20-fold lower than that associated with WBRT.

Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration

Progressive white matter degeneration in periventricular and deep white matter regions appears as white matter hyperintensities (WMH) on MRI scans. To date, periventricular WMHs are often associated with vascular dysfunction. Here, we demonstrate that ventricular inflation resulting from cerebral atrophy and hemodynamic pulsation with every heartbeat leads to a mechanical loading state of periventricular tissues that significantly affects the ventricular wall. Specifically, we present a physics-based modeling approach that provides a rationale for ependymal cell involvement in periventricular WMH formation. Building on eight previously created 2D finite element brain models, we introduce novel mechanomarkers for ependymal cell loading and geometric measures that characterize lateral ventricular shape. We show that our novel mechanomarkers, such as maximum ependymal cell deformations and maximum curvature of the ventricular wall, spatially overlap with periventricular WMH locations and are sensitive predictors for WMH formation. We also explore the role of the septum pellucidum in mitigating mechanical loading of the ventricular wall by constraining the radial expansion of the lateral ventricles during loading. Our models consistently show that ependymal cells are stretched thin only in the horns of the ventricles irrespective of ventricular shape. We therefore pose that periventricular WMH etiology is strongly linked to the deterioration of the over-stretched ventricular wall resulting in CSF leakage into periventricular white matter. Subsequent secondary damage mechanisms, including vascular degeneration, exacerbate lesion formation and lead to progressive growth into deep white matter regions.

The Olfactory Bulb in Companion Animals-Anatomy, Physiology, and Clinical Importance

The Olfactory Bulb is a component of the Olfactory System, in which it plays an essential role as an interface between the peripheral components and the cerebral cortex responsible for olfactory interpretation and discrimination. It is in this element that the first selective integration of olfactory stimuli occurs through a complex cell interaction that forwards the received olfactory information to higher cortical centers. Considering its position in the organizational hierarchy of the olfactory system, it is now known that changes in the Olfactory Bulb can lead to olfactory abnormalities. Through imaging techniques, it was possible to establish relationships between the occurrence of changes secondary to brain aging and senility, neurodegenerative diseases, head trauma, and infectious diseases with a decrease in the size of the Olfactory Bulb and in olfactory acuity. In companion animals, this relationship has also been identified, with observations of relations between the cranial conformation, the disposition, size, and shape of the Olfactory Bulb, and the occurrence of structural alterations associated with diseases with different etiologies. However, greater difficulty in quantitatively assessing olfactory acuity in animals and a manifestly smaller number of studies dedicated to this topic maintain a lack of concrete and unequivocal results in this field of veterinary sciences. The aim of this work is to revisit the Olfactory Bulb in companion animals in all its dimensions, review its anatomy and histological characteristics, physiological integration in the olfactory system, importance as a potential early indicator of the establishment of specific pathologies, as well as techniques of imaging evaluation for its in vivo clinical exploration.

Venous Collagenosis as Pathogenesis of White Matter Hyperintensity

OBJECTIVE

Periventricular white matter hyperintensities (pvWMHs) are commonly observed on MRI in older individuals and are associated with cognitive and motor decline. The etiology of pvWMH remains unknown. Venous collagenosis has been implicated, which may also interfere with perivascular fluid flow leading to dilation of perivascular spaces (PVS). Here, we examine relationships between in vivo pvWMH volume and ex vivo morphological quantification of collagenosis and the PVS in veins and arteries.

METHODS

Brain tissue from 25 Oregon Alzheimer's Disease Research Center subjects was selected to cover the full range of WMH burden. Tissue from white matter abutting the ventricle was stained with Masson's trichrome and smooth muscle actin. An automated hue based algorithm identified and segmented vessel into collagenized vessel walls, lumen, and PVS. Multiple linear regressions with pvWMH volume as the dependent variable and either collagen thickness or PVS width were performed with covariates of vessel diameter, age at death, sex, and interval between MRI and death.

RESULTS

PVS width and collagen thickness were significantly correlated in both arteries (r = 0.21, p = 0.001) and veins (r = 0.23, p = 0.001). Increased venous collagen (p = 0.017) was a significant predictor of higher pvWMH burden while arterial collagen was not (p = 0.128). Neither PVS width in arteries (p = 0.937) nor veins (p = 0.133) predicted pvWMH burden.

INTERPRETATION

These findings are consistent with a model in which venous collagenosis mediates the relationship between vascular risk factors and pvWMH. This study confirms the importance of changes to the venous system in contributing to MRI white matter lesions commonly observed with advanced age. ANN NEUROL 2022;92:992-1000.

Ependymal cells and neurodegenerative disease: outcomes of compromised ependymal barrier function

Within the central nervous system, ependymal cells form critical components of the blood-cerebrospinal fluid barrier and the cerebrospinal fluid-brain barrier. These barriers provide biochemical, immunological and physical protection against the entry of molecules and foreign substances into the cerebrospinal fluid while also regulating cerebrospinal fluid dynamics, such as the composition, flow and removal of waste from the cerebrospinal fluid. Previous research has demonstrated that several neurodegenerative diseases, such as Alzheimer's disease and multiple sclerosis, display irregularities in ependymal cell function, morphology, gene expression and metabolism. Despite playing key roles in maintaining overall brain health, ependymal barriers are largely overlooked and understudied in the context of disease, thus limiting the development of novel diagnostic and treatment options. Therefore, this review explores the anatomical properties, functions and structures that define ependymal cells in the healthy brain, as well as the ways in which ependymal cell dysregulation manifests across several neurodegenerative diseases. Specifically, we will address potential mechanisms, causes and consequences of ependymal cell dysfunction and describe how compromising the integrity of ependymal barriers may initiate, contribute to, or drive widespread neurodegeneration in the brain.

3D finite-element brain modeling of lateral ventricular wall loading to rationalize periventricular white matter hyperintensity locations

Aging-related periventricular white matter hyperintensities (pvWMHs) are a common observation in medical images of the aging brain. The underlying tissue damage is part of the complex pathophysiology associated with age-related microstructural changes and cognitive decline. PvWMH formation is linked to blood-brain barrier dysfunction from cerebral small vessel disease as well as the accumulation of cerebrospinal fluid in periventricular tissue due to progressive denudation of the ventricular wall. In need of a unifying theory for pvWMH etiology, image-based finite-element modeling is used to demonstrate that ventricular expansion from age-related cerebral atrophy and hemodynamic loading leads to maximum mechanical loading of the ventricular wall in the same locations that show pvWMHs. Ventricular inflation, induced via pressurization of the ventricular wall, creates significant ventricular wall stretch and stress on the ependymal cells lining the wall, that are linked to cerebrospinal fluid leaking from the lateral ventricles into periventricular white matter tissue. Eight anatomically accurate 3D brain models of cognitively healthy subjects with a wide range of ventricular shapes are created. For all models, our simulations show that mechanomarkers of mechanical wall loading are consistently highest in pvWMHs locations (p < 0.05). Maximum principal strain, the ependymal cell thinning ratio, and wall curvature are on average 14%, 8%, and 24% higher in pvWMH regions compared to the remaining ventricular wall, respectively. Computational modeling provides a powerful framework to systematically study pvWMH formation and growth with the goal to develop pharmacological interventions in the future.

Imaging of Normal Brain Aging

Understanding normal brain aging physiology is essential to improving healthy human longevity, differentiation, and early detection of diseases, such as neurodegenerative diseases, which are an enormous social and economic burden. Functional decline, such as reduced physical activity and cognitive abilities, is typically associated with brain aging. The authors summarize the aging brain mechanism and effects of aging on the brain observed by brain structural MR imaging and advanced neuroimaging techniques, such as diffusion tensor imaging and functional MR imaging.

Effects of acrobatic training on spatial memory and astrocytic scar in CA1 subfield of hippocampus after chronic cerebral hypoperfusion in male and female rats

Chronic cerebral hypoperfusion leads to neuronal loss in the hippocampus and spatial memory impairments. Physical exercise is known to prevent cognitive deficits in animal models; and there is evidence of sex differences in behavioral neuroprotective approaches. The aim of present study was to investigate the effects of acrobatic training in male and female rats submitted to chronic cerebral hypoperfusion. Males and females rats underwent 2VO (two-vessel occlusion) surgery and were randomly allocated into 4 groups of males and 4 groups of females, as follows: 2VO acrobatic, 2VO sedentary, Sham acrobatic and Sham sedentary. The acrobatic training started 45 days after surgery and lasted 4 weeks; animals were then submitted to object recognition and water maze testing. Brain samples were collected for histological and morphological assessment and flow cytometry. 2VO causes cognitive impairments and acrobatic training prevented spatial memory deficits assessed in the water maze, mainly for females. Morphological analysis showed that 2VO animals had less NeuN labeling and acrobatic training prevented it. Increased number of GFAP positive cells was observerd in females; moreover, males had more branched astrocytes and acrobatic training prevented the branching after 2VO. Flow cytometry showed higher mitochondrial potential in trained animals and more reactive oxygen species production in males. Acrobatic training promoted neuronal survival and improved mitochondrial function in both sexes, and influenced the glial scar in a sex-dependent manner, associated to greater cognitive benefit to females after chronic cerebral hypoperfusion.

Glioblastoma disrupts the ependymal wall and extracellular matrix structures of the subventricular zone

Background

Glioblastoma (GBM) is the most aggressive and common type of primary brain tumor in adults. Tumor location plays a role in patient prognosis, with tumors proximal to the lateral ventricles (LVs) presenting with worse overall survival, increased expression of stem cell genes, and increased incidence of distal tumor recurrence. This may be due in part to interaction of GBM with factors of the subventricular zone (SVZ), including those contained within the cerebrospinal fluid (CSF). However, direct interaction of GBM tumors with CSF has not been proved and would be hindered in the presence of an intact ependymal cell layer.

Methods

Here, we investigate the ependymal cell barrier and its derived extracellular matrix (ECM) fractones in the vicinity of a GBM tumor. Patient-derived GBM cells were orthotopically implanted into immunosuppressed athymic mice in locations distal and proximal to the LV. A PBS vehicle injection in the proximal location was included as a control. At four weeks post-xenograft, brain tissue was examined for alterations in ependymal cell health via immunohistochemistry, scanning electron microscopy, and transmission electron microscopy.

Results

We identified local invading GBM cells within the LV wall and increased influx of CSF into the LV-proximal GBM tumor bulk compared to controls. In addition to the physical disruption of the ependymal cell barrier, we also identified increased signs of compromised ependymal cell health in LV-proximal tumor-bearing mice. These signs include increased accumulation of lipid droplets, decreased cilia length and number, and decreased expression of cell channel proteins. We additionally identified elevated numbers of small fractones in the SVZ within this group, suggesting increased indirect CSF-contained molecule signaling to tumor cells.

Conclusions

Our data is the first to show that LV-proximal GBMs physically disrupt the ependymal cell barrier in animal models, resulting in disruptions in ependymal cell biology and increased CSF interaction with the tumor bulk. These findings point to ependymal cell health and CSF-contained molecules as potential axes for therapeutic targeting in the treatment of GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-022-00354-8.

An Intelligent System for Early Recognition of Alzheimer's Disease Using Neuroimaging

Alzheimer's disease (AD) is a neurodegenerative disease that affects brain cells, and mild cognitive impairment (MCI) has been defined as the early phase that describes the onset of AD. Early detection of MCI can be used to save patient brain cells from further damage and direct additional medical treatment to prevent its progression. Lately, the use of deep learning for the early identification of AD has generated a lot of interest. However, one of the limitations of such algorithms is their inability to identify changes in the functional connectivity in the functional brain network of patients with MCI. In this paper, we attempt to elucidate this issue with randomized concatenated deep features obtained from two pre-trained models, which simultaneously learn deep features from brain functional networks from magnetic resonance imaging (MRI) images. We experimented with ResNet18 and DenseNet201 to perform the task of AD multiclass classification. A gradient class activation map was used to mark the discriminating region of the image for the proposed model prediction. Accuracy, precision, and recall were used to assess the performance of the proposed system. The experimental analysis showed that the proposed model was able to achieve 98.86% accuracy, 98.94% precision, and 98.89% recall in multiclass classification. The findings indicate that advanced deep learning with MRI images can be used to classify and predict neurodegenerative brain diseases such as AD.

Contribution of white matter hyperintensities to ventricular enlargement in older adults

Lateral ventricles might increase due to generalized tissue loss related to brain atrophy. Alternatively, they may expand into areas of tissue loss related to white matter hyperintensities (WMH). We assessed longitudinal associations between lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, history of stroke, cardiovascular disease, diabetes and smoking at ages 73, 76 and 79, in participants from the Lothian Birth Cohort 1936, including MRI data from all available time points. Lateral ventricle volume increased steadily with age, WMH volume change was more variable. WMH volume decreased in 20% and increased in remaining subjects. Over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in blood pressure, 3.2% per 1% decrease of total brain volume, and 4.5% per 1% increase of WMH volume. Over time, lateral ventricle volumes were 19% smaller in women than men. Ventricular and WMH volume changes are modestly associated and independent of general brain atrophy, suggesting that their underlying processes do not fully overlap.

Leptomeningeal disease and tumor dissemination in a murine diffuse intrinsic pontine glioma model: implications for the study of the tumor-cerebrospinal fluid-ependymal microenvironment

Background

Leptomeningeal disease and hydrocephalus are present in up to 30% of patients with diffuse intrinsic pontine glioma (DIPG), however there are no animal models of cerebrospinal fluid (CSF) dissemination. As the tumor-CSF-ependymal microenvironment may play an important role in tumor pathogenesis, we identified characteristics of the Nestin-tumor virus A (Nestin-Tva) genetically engineered mouse model that make it ideal to study the interaction of tumor cells with the CSF and its associated pathways with implications for the development of treatment approaches to address CSF dissemination in DIPG.

Methods

A Nestin-Tva model of DIPG utilizing the 3 most common DIPG genetic alterations (H3.3K27M, PDGF-B, and p53) was used for this study. All mice underwent MR imaging and a subset underwent histopathologic analysis with H&E and immunostaining.

Results

Tumor dissemination within the CSF pathways (ventricles, leptomeninges) from the subependyma was present in 76% (25/33) of mice, with invasion of the choroid plexus, disruption of the ciliated ependyma and regional subependymal fluid accumulation. Ventricular enlargement consistent with hydrocephalus was present in 94% (31/33). Ventricle volume correlated with region-specific transependymal CSF flow (periventricular T2 signal), localized anterior to the lateral ventricles.

Conclusions

This is the first study to report CSF pathway tumor dissemination associated with subependymal tumor in an animal model of DIPG and is representative of CSF dissemination seen clinically. Understanding the CSF-tumor-ependymal microenvironment has significant implications for treatment of DIPG through targeting mechanisms of tumor spread within the CSF pathways.

Brain aging mechanisms with mechanical manifestations

Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.

Peak ependymal cell stretch overlaps with the onset locations of periventricular white matter lesions

Deep and periventricular white matter hyperintensities (dWMH/pvWMH) are bright appearing white matter tissue lesions in T2-weighted fluid attenuated inversion recovery magnetic resonance images and are frequent observations in the aging human brain. While early stages of these white matter lesions are only weakly associated with cognitive impairment, their progressive growth is a strong indicator for long-term functional decline. DWMHs are typically associated with vascular degeneration in diffuse white matter locations; for pvWMHs, however, no unifying theory exists to explain their consistent onset around the horns of the lateral ventricles. We use patient imaging data to create anatomically accurate finite element models of the lateral ventricles, white and gray matter, and cerebrospinal fluid, as well as to reconstruct their WMH volumes. We simulated the mechanical loading of the ependymal cells forming the primary brain-fluid interface, the ventricular wall, and its surrounding tissues at peak ventricular pressure during the hemodynamic cycle. We observe that both the maximum principal tissue strain and the largest ependymal cell stretch consistently localize in the anterior and posterior horns. Our simulations show that ependymal cells experience a loading state that causes the ventricular wall to be stretched thin. Moreover, we show that maximum wall loading coincides with the pvWMH locations observed in our patient scans. These results warrant further analysis of white matter pathology in the periventricular zone that includes a mechanics-driven deterioration model for the ventricular wall.

Transependymal Edema as a Predictor of Endoscopic Third Ventriculostomy Success in Pediatric Hydrocephalus

BACKGROUND

The Endoscopic Third Ventriculostomy Success Score (ETVSS) is based on the clinical features of hydrocephalus except for radiological findings. A previous study suggested that transependymal edema (TEE) as a radiological finding may be a reliable predictor of endoscopic third ventriculostomy (ETV) success in patients of all ages. We aimed to investigate whether TEE on preoperative magnetic resonance imaging can predict ETV success in pediatric patients.

METHODS

Medical and radiological records of all pediatric patients with an initial ETV in our hospital between 2013 and 2019 were retrospectively reviewed.

RESULTS

This study included 32 patients with hydrocephalus. The median age at surgery was 10.0 years (interquartile range: 5.6-12.9 years). There were 20 patients in the high ETVSS (90-80) group and 12 patients in the moderate ETVSS (70-50) group. The median follow-up period was 29.0 months (interquartile range: 12.9-46.2 months). The ETV success rate at the final follow-up was 81%. Preoperative brain magnetic resonance imaging revealed TEE in 20 patients and third ventricle floor ballooning in 25 patients, of whom 19 (95%) and 22 (88%), respectively, achieved successful ETV. Patients with TEE had a significantly better outcome than patients without TEE (95% vs. 58%, P = 0.018). Multivariate analysis demonstrated that the presence of TEE (odds ratio 13.6, 95% confidence interval 1.3-137.5, P = 0.027) is a significant predictor of ETV success.

CONCLUSIONS

In our cohort with a high or moderate ETVSS, the ETV success rate in patients with TEE was significantly higher than in patients without TEE, suggesting that TEE may be a useful predictor of ETV success in pediatric hydrocephalus.

Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer's Disease

Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer's disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer's disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer's disease and related dementias, in order to allow for earlier and more effective interventions.

Brain ventricular volume changes in schizophrenia. A narrative review

Brain ventricles are among the most studied structures in psychotic illness. In our mini-review we present available evidence on brain ventricle changes during the course of schizophrenia, from high-risk subjects and the first episode of schizophrenia to patients with chronic schizophrenia. We present current findings on the relationship between ventricle changes and level of psychopathology. The potential pathophysiological background of ventricle changes is also discussed. Understanding the dynamics of brain ventricle changes could resolve long-standing questions on the proportion of neurodegenerative and neurodevelopmental processes in the pathophysiology of schizophrenia.

White Matter Hyperintensities Contribute to Language Deficits in Primary Progressive Aphasia

OBJECTIVE

To determine the contribution of white matter hyperintensities (WMH) to language deficits while accounting for cortical atrophy in individuals with primary progressive aphasia (PPA).

METHOD

Forty-three individuals with PPA completed neuropsychological assessments of nonverbal semantics, naming, and sentence repetition plus T2-weighted and fluid-attenuated inversion recovery scans. Using three visual scales, we rated WMH and cerebral ventricle size for both scan types. We used Spearman correlations to evaluate associations between the scales and scans. To test whether visual ratings-particularly of WMH-are associated with language, we compared a base model (including gray matter component scores obtained via principal component analysis, age, and days between assessment and MRI as independent variables) with full models (ie, the base model plus visual ratings) for each language variable.

RESULTS

Visual ratings were significantly associated within and between scans and were significantly correlated with age but not with other vascular risk factors. Only the T2 scan ratings were associated with language abilities. Specifically, controlling for other variables, poorer naming was significantly related to larger ventricles (P = 0.033) and greater global (P = 0.033) and periventricular (P = 0.049) WMH. High global WMH (P = 0.034) were also correlated with worse sentence repetition skills.

CONCLUSION

Visual ratings of global brain health were associated with language deficits in PPA independent of cortical atrophy and age. While WMH are not unique to PPA, measuring WMH in conjunction with cortical atrophy may elucidate more accurate brain structure-behavior relationships in PPA than cortical atrophy measures alone.

Lateral ventricle volume trajectories predict response inhibition in older age-A longitudinal brain imaging and machine learning approach

Objective

In a three-wave 6 yrs longitudinal study we investigated if the expansion of lateral ventricle (LV) volumes (regarded as a proxy for brain tissue loss) predicts third wave performance on a test of response inhibition (RI).

Participants and methods

Trajectories of left and right lateral ventricle volumes across the three waves were quantified using the longitudinal stream in Freesurfer. All participants (N = 74;48 females;mean age 66.0 yrs at the third wave) performed the Color-Word Interference Test (CWIT). Response time on the third condition of CWIT, divided into fast, medium and slow, was used as outcome measure in a machine learning framework. Initially, we performed a linear mixed-effect (LME) analysis to describe subject-specific trajectories of the left and right LV volumes (LVV). These features were input to a multinomial logistic regression classification procedure, predicting individual belongings to one of the three RI classes. To obtain results that might generalize, we evaluated the significance of a k-fold cross-validated f1-score with a permutation test, providing a p-value that approximates the probability that the score would be obtained by chance. We also calculated a corresponding confusion matrix.

Results

The LME-model showed an annual ∼ 3.0% LVV increase. Evaluation of a cross-validated score using 500 permutations gave an f1-score of 0.462 that was above chance level (p = 0.014). 56% of the fast performers were successfully classified. All these were females, and typically older than 65 yrs at inclusion. For the true slow performers, those being correctly classified had higher LVVs than those being misclassified, and their ages at inclusion were also higher.

Conclusion

Major contributions were: (i) a longitudinal design, (ii) advanced brain imaging and segmentation procedures with longitudinal data analysis, and (iii) a data driven machine learning approach including cross-validation and permutation testing to predict behaviour, solely from the individual’s brain “signatures” (LVV trajectories).

Characterization of the ventricular-subventricular stem cell niche during human brain development

Human brain development proceeds via a sequentially transforming stem cell population in the ventricular-subventricular zone (V-SVZ). An essential, but understudied, contributor to V-SVZ stem cell niche health is the multi-ciliated ependymal epithelium, which replaces stem cells at the ventricular surface during development. However, reorganization of the V-SVZ stem cell niche and its relationship to ependymogenesis has not been characterized in the human brain. Based on comprehensive comparative spatiotemporal analyses of cytoarchitectural changes along the mouse and human ventricle surface, we uncovered a distinctive stem cell retention pattern in humans as ependymal cells populate the surface of the ventricle in an occipital-to-frontal wave. During perinatal development, ventricle-contacting stem cells are reduced. By 7 months few stem cells are detected, paralleling the decline in neurogenesis. In adolescence and adulthood, stem cells and neurogenesis are not observed along the lateral wall. Volume, surface area and curvature of the lateral ventricles all significantly change during fetal development but stabilize after 1 year, corresponding with the wave of ependymogenesis and stem cell reduction. These findings reveal normal human V-SVZ development, highlighting the consequences of disease pathologies such as congenital hydrocephalus.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials.

METHODS

We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/).

RESULTS

(1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies.

DISCUSSION

ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.