Quantitative MRI to understand Alzheimer's disease pathophysiology

The dopaminergic system promotes neprilysin-mediated degradation of amyloid-β in the brain

Deposition of amyloid-β (Aβ) in the brain can impair neuronal function and contribute to cognitive decline in Alzheimer's disease (AD). Here, we found that dopamine and the dopamine precursor levodopa (also called l-DOPA) induced Aβ degradation in the brain. Chemogenetic approaches in mice revealed that the activation of dopamine release from ventral tegmental area (VTA) neurons increased the abundance and activity of the Aβ-degrading enzyme neprilysin and reduced the amount of Aβ deposits in the prefrontal cortex in a neprilysin-dependent manner. Aged mice had less dopamine and neprilysin in the anterior cortex, a decrease that was accentuated in AD model mice. Treating AD model mice with levodopa reduced Aβ deposition and improved cognitive function. These observations demonstrate that dopamine promotes brain region-specific, neprilysin-dependent degradation of Aβ, suggesting that dopamine-associated strategies have the potential to treat this aspect of AD pathology.

Altered white matter functional pathways in Alzheimer's disease

Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.

A multi-cohort study of the hippocampal radiomics model and its associated biological changes in Alzheimer's Disease

There have been no previous reports of hippocampal radiomics features associated with biological functions in Alzheimer's Disease (AD). This study aims to develop and validate a hippocampal radiomics model from structural magnetic resonance imaging (MRI) data for identifying patients with AD, and to explore the mechanism underlying the developed radiomics model using peripheral blood gene expression. In this retrospective multi-study, a radiomics model was developed based on the radiomics discovery group (n = 420) and validated in other cohorts. The biological functions underlying the model were identified in the radiogenomic analysis group using paired MRI and peripheral blood transcriptome analyses (n = 266). Mediation analysis and external validation were applied to further validate the key module and hub genes. A 12 radiomics features-based prediction model was constructed and this model showed highly robust predictive power for identifying AD patients in the validation and other three cohorts. Using radiogenomics mapping, myeloid leukocyte and neutrophil activation were enriched, and six hub genes were identified from the key module, which showed the highest correlation with the radiomics model. The correlation between hub genes and cognitive ability was confirmed using the external validation set of the AddneuroMed dataset. Mediation analysis revealed that the hippocampal radiomics model mediated the association between blood gene expression and cognitive ability. The hippocampal radiomics model can accurately identify patients with AD, while the predictive radiomics model may be driven by neutrophil-related biological pathways.

A Predictive Model of the Progression to Alzheimer's Disease in Patients with Mild Cognitive Impairment Based on the MRI Enlarged Perivascular Spaces

Background

Mild cognitive impairment (MCI) is a heterogeneous condition that can precede various forms of dementia, including Alzheimer's disease (AD). Identifying MCI subjects who are at high risk of progressing to AD is of major clinical relevance. Enlarged perivascular spaces (EPVS) on MRI are linked to cognitive decline, but their predictive value for MCI to AD progression is unclear.

Objective

This study aims to assess the predictive value of EPVS for MCI to AD progression and develop a predictive model combining EPVS grading with clinical and laboratory data to estimate conversion risk.

Methods

We analyzed 358 patients with MCI from the ADNI database, consisting of 177 MCI-AD converters and 181 non-converters. The data collected included demographic information, imaging data (including perivascular spaces grade), clinical assessments, and laboratory test results. Variable selection was conducted using the Least Absolute Shrinkage and Selection Operator (LASSO) method, followed by logistic regression to develop predictive model.

Results

In the univariate logistic regression analysis, both moderate (OR = 5.54, 95% CI [3.04-10.18]) and severe (OR = 25.04, 95% CI [10.07-62.23]) enlargements of the centrum semiovale perivascular space (CSO-PVS) were found to be strong predictors of disease progression. LASSO analyses yielded 12 variables, refined to six in the final model: APOE4 genotype, ADAS11 score, CSO-PVS grade, and volumes of entorhinal, fusiform, and midtemporal regions, with an AUC of 0.956 in the training and 0.912 in the validation cohort.

Conclusions

Our predictive model, emphasizing EPVS assessment, provides clinicians with a practical tool for early detection and management of AD risk in MCI patients.

Evaluation of bumetanide as a potential therapeutic agent for Alzheimer's disease

Therapeutics discovery and development for Alzheimer's disease (AD) has been an area of intense research to alleviate memory loss and the underlying pathogenic processes. Recent drug discovery approaches have utilized in silico computational strategies for drug candidate selection which has opened the door to repurposing drugs for AD. Computational analysis of gene expression signatures of patients stratified by the APOE4 risk allele of AD led to the discovery of the FDA-approved drug bumetanide as a top candidate agent that reverses APOE4 transcriptomic brain signatures and improves memory deficits in APOE4 animal models of AD. Bumetanide is a loop diuretic which inhibits the kidney Na+-K+-2Cl- cotransporter isoform, NKCC2, for the treatment of hypertension and edema in cardiovascular, liver, and renal disease. Electronic health record data revealed that patients exposed to bumetanide have lower incidences of AD by 35%-70%. In the brain, bumetanide has been proposed to antagonize the NKCC1 isoform which mediates cellular uptake of chloride ions. Blocking neuronal NKCC1 leads to a decrease in intracellular chloride and thus promotes GABAergic receptor mediated hyperpolarization, which may ameliorate disease conditions associated with GABAergic-mediated depolarization. NKCC1 is expressed in neurons and in all brain cells including glia (oligodendrocytes, microglia, and astrocytes) and the vasculature. In consideration of bumetanide as a repurposed drug for AD, this review evaluates its pharmaceutical properties with respect to its estimated brain levels across doses that can improve neurologic disease deficits of animal models to distinguish between NKCC1 and non-NKCC1 mechanisms. The available data indicate that bumetanide efficacy may occur at brain drug levels that are below those required for inhibition of the NKCC1 transporter which implicates non-NKCC1 brain mechansims for improvement of brain dysfunctions and memory deficits. Alternatively, peripheral bumetanide mechanisms may involve cells outside the central nervous system (e.g., in epithelia and the immune system). Clinical bumetanide doses for improved neurological deficits are reviewed. Regardless of mechanism, the efficacy of bumetanide to improve memory deficits in the APOE4 model of AD and its potential to reduce the incidence of AD provide support for clinical investigation of bumetanide as a repurposed AD therapeutic agent.

Hybrid PET/MRI with Flutemetamol and FDG in Alzheimer's Disease Clinical Continuum

AIMS

We aimed to investigate the interaction between β -amyloid (Aβ) accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes in the Alzheimer's disease (AD) clinical continuum.

BACKGROUND

Utility of positron emission tomography (PET) / magnetic resonance imaging (MRI) hybrid imaging for diagnostic categorization of the AD clinical continuum including subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD) has not been fully crystallized.

OBJECTIVE

To evaluate the interaction between Aβ accumulation and cerebral glucose metabolism, cerebral perfusion, and cerebral structural changes such as cortex thickness or cerebral white matter disease burden and to detect the discriminative yields of these imaging modalities in the AD clinical continuum.

METHODS

Fifty patients (20 women and 30 men; median age: 64 years) with clinical SCD (n=11), aMCI (n=17) and ADD (n=22) underwent PET/MRI with [18F]-fluoro-D-glucose (FDG) and [18F]- Flutemetamol in addition to cerebral blood flow (CBF) and quantitative structural imaging along with detailed cognitive assessment.

RESULTS

High Aβ deposition (increased temporal [18F]-Flutemetamol standardized uptake value ratio (SUVr) and centiloid score), low glucose metabolism (decreased temporal lobe and posterior cingulate [18F]-FDG SUVr), low parietal CBF and right hemispheric cortical thickness were independent predictors of low cognitive test performance.

CONCLUSION

Integrated use of structural, metabolic, molecular (Aβ) and perfusion (CBF) parameters contribute to the discrimination of SCD, aMCI, and ADD.

Nosustrophine: An Epinutraceutical Bioproduct with Effects on DNA Methylation, Histone Acetylation and Sirtuin Expression in Alzheimer's Disease

Alzheimer's disease (AD), the most common cause of dementia, causes irreversible memory loss and cognitive deficits. Current AD drugs do not significantly improve cognitive function or cure the disease. Novel bioproducts are promising options for treating a variety of diseases, including neurodegenerative disorders. Targeting the epigenetic apparatus with bioactive compounds (epidrugs) may aid AD prevention treatment. The aims of this study were to determine the composition of a porcine brain-derived extract Nosustrophine, and whether treating young and older trigenic AD mice produced targeted epigenetic and neuroprotective effects against neurodegeneration. Nosustrophine regulated AD-related APOE and PSEN2 gene expression in young and older APP/BIN1/COPS5 mice, inflammation-related (NOS3 and COX-2) gene expression in 3-4-month-old mice only, global (5mC)- and de novo DNA methylation (DNMT3a), HDAC3 expression and HDAC activity in 3-4-month-old mice; and SIRT1 expression and acetylated histone H3 protein levels in 8-9-month-old mice. Mass spectrometric analysis of Nosustrophine extracts revealed the presence of adenosylhomocysteinase, an enzyme implicated in DNA methylation, and nicotinamide phosphoribosyltransferase, which produces the NAD+ precursor, enhancing SIRT1 activity. Our findings show that Nosustrophine exerts substantial epigenetic effects against AD-related neurodegeneration and establishes Nosustrophine as a novel nutraceutical bioproduct with epigenetic properties (epinutraceutical) that may be therapeutically effective for prevention and early treatment for AD-related neurodegeneration.

Motion-corrected 3D-EPTI with efficient 4D navigator acquisition for fast and robust whole-brain quantitative imaging

PURPOSE

To develop a motion estimation and correction method for motion-robust three-dimensional (3D) quantitative imaging with 3D-echo-planar time-resolved imaging.

THEORY AND METHODS

The 3D-echo-planar time-resolved imaging technique was designed with additional four-dimensional navigator acquisition (x-y-z-echoes) to achieve fast and motion-robust quantitative imaging of the human brain. The four-dimensional-navigator is inserted into the relaxation-recovery deadtime of the sequence in every pulse TR (∼2 s) to avoid extra scan time, and to provide continuous tracking of the 3D head motion and B0 -inhomogeneity changes. By using an optimized spatiotemporal encoding combined with a partial-Fourier scheme, the navigator acquires a large central k-t data block for accurate motion estimation using only four small-flip-angle excitations and readouts, resulting in negligible signal-recovery reduction to the 3D-echo-planar time-resolved imaging acquisition. By incorporating the estimated motion and B0 -inhomogeneity changes into the reconstruction, multi-contrast images can be recovered with reduced motion artifacts.

RESULTS

Simulation shows the cost to the SNR efficiency from the added navigator acquisitions is <1%. Both simulation and in vivo retrospective experiments were conducted, that demonstrate the four-dimensional navigator provided accurate estimation of the 3D motion and B0 -inhomogeneity changes, allowing effective reduction of image artifacts in quantitative maps. Finally, in vivo prospective undersampling acquisition was performed with and without head motion, in which the motion corrupted data after correction show close image quality and consistent quantifications to the motion-free scan, providing reliable quantitative measurements even with head motion.

CONCLUSION

The proposed four-dimensional navigator acquisition provides reliable tracking of the head motion and B0 change with negligible SNR cost, equips the 3D-echo-planar time-resolved imaging technique for motion-robust and efficient quantitative imaging.

Plasma p-tau181 associated with structural changes in mild cognitive impairment

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with dementia and is a serious concern for the health of individuals and government health care systems worldwide. Gray matter atrophy and white matter damage are major contributors to cognitive deficits in AD patients, as demonstrated by magnetic resonance imaging (MRI). Many of these brain changes associated with AD begin to occur about 15 years before the onset of initial clinical symptoms. Therefore, it is critical to find biomarkers reflective of these brain changes associated with AD to identify this disease and monitor its prognosis and development. The increased plasma level of hyperphosphorylated tau 181 (p-tau181) has been recently considered a novel biomarker for the diagnosis of AD, preclinical AD, and mild cognitive impairment (MCI). In the current study, we examined the association of cerebrospinal fluid (CSF) and plasma levels of p-tau181 with structural brain changes in cortical thickness, cortical volume, surface area, and subcortical volume in MCI patients. In this cross-sectional study, we included the information of 461 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. The results of voxel-wise partial correlation analyses showed a significant negative correlation between the increased levels of plasma p-tau181, CSF total tau, and CSF p-tau181 with structural changes in widespread brain regions. These results provide evidence for the use of plasma p-tau181 as a diagnostic marker for structural changes in the brain associated with the early stages of AD and neurodegeneration.

Effects of a 12-Week Periodized Resistance Training Program on Resting Brain Activity and Cerebrovascular Function: A Nonrandomized Pilot Trial

Resistance training is a promising strategy to promote healthy cognitive aging; however, the brain mechanisms by which resistance training benefits cognition have yet to be determined. Here, we examined the effects of a 12-week resistance training program on resting brain activity and cerebrovascular function in 20 healthy older adults (14 females, mean age 69.1 years). In this single group clinical trial, multimodal 3 T magnetic resonance imaging was performed at 3 time points: baseline (preceding a 12-week control period), pre-intervention, and post-intervention. Along with significant improvements in fluid cognition (d = 1.27), 4 significant voxelwise clusters were identified for decreases in resting brain activity after the intervention (Cerebellum, Right Middle Temporal Gyrus, Left Inferior Parietal Lobule, and Right Inferior Parietal Lobule), but none were identified for changes in resting cerebral blood flow. Using a separate region of interest approach, we provide estimates for improved cerebral blood flow, compared with declines over the initial control period, in regions associated with cognitive impairment, such as hippocampal blood flow (d = 0.40), and posterior cingulate blood flow (d = 0.61). Finally, resistance training had a small countermeasure effect on the age-related progression of white matter lesion volume (rank-biserial = -0.22), a biomarker of cerebrovascular disease. These proof-of-concept data support larger trials to determine whether resistance training can attenuate or even reverse salient neurodegenerative processes.

3D Echo Planar Time-resolved Imaging (3D-EPTI) for ultrafast multi-parametric quantitative MRI

Multi-parametric quantitative MRI has shown great potential to improve the sensitivity and specificity of clinical diagnosis and to enhance our understanding of complex brain processes, but suffers from long scan time especially at high spatial resolution. To address this longstanding challenge, we introduce a novel approach, termed 3D Echo Planar Time-resolved Imaging (3D-EPTI), which significantly increases the acceleration capacity of MRI sampling, and provides high acquisition efficiency for multi-parametric MRI. This is achieved by exploiting the spatiotemporal correlation of MRI data at multiple timescales through new encoding strategies within and between efficient continuous readouts. Specifically, an optimized spatiotemporal CAIPI encoding within the readouts combined with a radial-block sampling strategy across the readouts enables an acceleration rate of 800 fold in the k-t space. A subspace reconstruction was employed to resolve thousands of high-quality multi-contrast images. We have demonstrated the ability of 3D-EPTI to provide robust and repeatable whole-brain simultaneous T1, T2, T2*, PD and B1+ mapping at high isotropic resolution within minutes (e.g., 1-mm isotropic resolution in 3 minutes), and to enable submillimeter multi-parametric imaging to study detailed brain structures.

Greater diffusion restriction in white matter in Preclinical Alzheimer's disease

OBJECTIVE

The Alzheimer's Continuum is biologically defined by beta-amyloid deposition which, at the earliest stages, is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes are characterized is relatively under-explored. The goal of this study was to use Diffusional Kurtosis Imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer's disease (AD).

METHODS

Cognitively unimpaired participants ages 45-85 completed brain MRI, amyloid PET (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta amyloid-negative (AB-) and -positive (AB+) participants differed on DKI-based conventional (i.e. Fractional Anisotropy [FA], Mean Diffusivity [MD], Mean Kurtosis [MK]) and modeling (i.e. Axonal Water Fraction [AWF], extra-axonal radial diffusivity [D_e,⊥ ]) metrics, and whether these metrics were associated with other biomarkers.

RESULTS

We found significantly greater diffusion restriction (higher FA/AWF, lower MD/ D_e,⊥ ) in white matter in AB+ than AB- (partial η² = 0.08-0.19), more notably in the extra-axonal space within primarily late-myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (AUC=0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas D_e,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume.

INTERPRETATION

These results support prior evidence of a non-monotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration. This article is protected by copyright. All rights reserved.

Cerebellar White Matter Disruption in Alzheimer's Disease Patients: A Diffusion Tensor Imaging Study

The cognitive role of the cerebellum has recently gained much attention, and its pivotal role in Alzheimer's disease (AD) has now been widely recognized. Diffusion tensor imaging (DTI) has been used to evaluate the disruption of the microstructural milieu in AD, and though several white matter (WM) tracts such as corpus callosum, inferior and superior longitudinal fasciculus, cingulum, fornix, and uncinate fasciculus have been evaluated in AD, data on cerebellar WM tracts are currently lacking. We performed a tractography-based DTI reconstruction of the middle cerebellar peduncle (MCP), and the left and right superior cerebellar peduncles separately (SCPL and SCPR) and addressed the differences in fractional anisotropy (FA), axial diffusivity (Dax), radial diffusivity (RD), and mean diffusivity (MD) in the three tracts between 50 patients with AD and 25 healthy subjects. We found that AD patients showed a lower FA and a higher RD compared to healthy subjects in MCP, SCPL, and SCPR. Moreover, higher MD was found in SCPR and SCPL and higher Dax in SCPL. This result is important as it challenges the traditional view that WM bundles in the cerebellum are unaffected in AD and might identify new targets for therapeutic interventions.

Prediction of the progression from mild cognitive impairment to Alzheimer's disease using a radiomics-integrated model

Objective:

This study aimed to build and validate a radiomics-integrated model with whole-brain magnetic resonance imaging (MRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD).

Methods:

357 patients with MCI were selected from the ADNI database, which is an open-source database for AD with multicentre cooperation, of which 154 progressed to AD during the 48-month follow-up period. Subjects were divided into a training and test group. For each patient, the baseline T₁WI MR images were automatically segmented into white matter, gray matter and cerebrospinal fluid (CSF), and radiomics features were extracted from each tissue. Based on the data from the training group, a radiomics signature was built using logistic regression after dimensionality reduction. The radiomics signatures, in combination with the apolipoprotein E4 (APOE4) and baseline neuropsychological scales, were used to build an integrated model using machine learning. The receiver operating characteristics (ROC) curve and data of the test group were used to evaluate the diagnostic accuracy and reliability of the model, respectively. In addition, the clinical prognostic efficacy of the model was evaluated based on the time of progression from MCI to AD.

Results:

Stepwise logistic regression analysis showed that the APOE4, clinical dementia rating, AD assessment scale, and radiomics signature were independent predictors of MCI progression to AD. The integrated model was constructed based on independent predictors using machine learning. The ROC curve showed that the accuracy of the model in the training and the test sets was 0.814 and 0.807, with a specificity of 0.671 and 0.738, and a sensitivity of 0.822 and 0.745, respectively. In addition, the model had the most significant diagnostic efficacy in predicting MCI progression to AD within 12 months, with an AUC of 0.814, sensitivity of 0.726, and specificity of 0.798.

Conclusion:

The integrated model based on whole-brain radiomics can accurately identify and predict the high-risk population of MCI patients who may progress to AD. Radiomics biomarkers are practical in the precursory stage of such disease.

Tracking white-matter brain modifications in chronic non-bothersome acoustic trauma tinnitus

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Tractography was compared between two groups of tinnitus and control participants.

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Diffusion was modeled with ss3t-CSD allowing apparent fiber density (AFD) calculation.

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27 bundles of interest were chosen for their link to the auditory and limbic systems.

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AFD was significantly increased in the tinnitus group in the right frontal isthmus.

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AFD in the acoustic radiations was not significantly different between the groups.

Subjective tinnitus is a symptom characterized by the perception of sound with no external acoustic source, most often accompanied by co-morbidities. To date, the specific role of white matter abnormalities related to tinnitus reaches no consensus in the literature. The goal of this study was to explore the structural connectivity related to tinnitus percept per se, thus focusing on a specific population presenting chronic non-bothersome tinnitus of similar etiology (noise induced) without co-morbidities. We acquired diffusion-weighted images with high angular resolution in a homogeneous group of mildly impacted tinnitus participants (n = 19) and their matched controls (n = 19). We focused the study on two subsets of fiber bundles of interest: on one hand, we extracted the acoustic radiation and further included any intersecting fiber bundles; on the other hand, we explored the tracts related to the limbic system. We modeled the diffusion signal using constrained spherical deconvolution. We conducted a deep-learning based tractography segmentation and mapped Apparent Fiber Density (AFD) on the bundles of interest. C, as well as Fractional Anisotropy (FA) and FOD peak amplitude for comparison. Between group statistical comparison was performed along the 27 tracts of interest controlling for confounding hearing loss, tinnitus severity, and duration since onset. We tested a potential correlation with hearing loss, tinnitus duration and tinnitus handicap score along these tracts. In the tinnitus group, we observed increased AFD related to chronic tinnitus percept after acoustic trauma in two main white matter regions. First, in the right hemisphere, in the isthmus between inferior temporal and inferior frontal cortices, in the uncinate fasciculus (UF), and in the inferior fronto-occipital bundle (IFO). Second, in the left hemisphere, underneath the superior parietal region in the thalamo parietal tract and parieto-occipital pontine tract. Between-group differences in the acoustic radiations were not significant with AFD but were with FA. Furthermore, significant correlations with hearing loss were found in the left hemisphere in the inferior longitudinal fasciculus and in the fronto-pontine tract. No additional correlation was found with tinnitus duration nor with tinnitus handicap, as reflected by THI scores. The regions that displayed tinnitus related increased AFD also displayed increased FA. The isthmus of the UF and IFO in the right hemisphere appear to be involved with a number of neuropsychiatric and traumatic disorders confirming the involvement of the limbic system even in chronic non-bothersome tinnitus subjects, potentially suggesting a common pathway between these pathologies. White matter changes underneath the superior parietal cortex found here in tinnitus participants supports the implication of an auditory-somatosensory pathway in tinnitus perception.

Neuropathology of the Brainstem to Mechanistically Understand and to Treat Alzheimer's Disease

Alzheimer’s disease (AD) is a devastating neurodegenerative disorder as yet without effective therapy. Symptoms of this disorder typically reflect cortical malfunction with local neurohistopathology, which biased investigators to search for focal triggers and molecular mechanisms. Cortex, however, receives massive afferents from caudal brain structures, which do not only convey specific information but powerfully tune ensemble activity. Moreover, there is evidence that the start of AD is subcortical. The brainstem harbors monoamine systems, which establish a dense innervation in both allo- and neocortex. Monoaminergic synapses can co-release neuropeptides either by precisely terminating on cortical neurons or, when being “en passant”, can instigate local volume transmission. Especially due to its early damage, malfunction of the ascending monoaminergic system emerges as an early sign and possible trigger of AD. This review summarizes the involvement and cascaded impairment of brainstem monoaminergic neurons in AD and discusses cellular mechanisms that lead to their dysfunction. We highlight the significance and therapeutic challenges of transmitter co-release in ascending activating system, describe the role and changes of local connections and distant afferents of brainstem nuclei in AD, and summon the rapidly increasing diagnostic window during the last few years.

Autophagy status as a gateway for stress-induced catecholamine interplay in neurodegeneration

The catecholamine-containing brainstem nuclei locus coeruleus (LC) and ventral tegmental area (VTA) are critically involved in stress responses. Alterations of catecholamine systems during chronic stress may contribute to neurodegeneration, including cognitive decline. Stress-related catecholamine alterations, while contributing to anxiety and depression, might accelerate neuronal degeneration by increasing the formation of toxic dopamine and norepinephrine by-products. These, in turn, may impair proteostasis within a variety of cortical and subcortical areas. In particular, the molecular events governing neurotransmission, neuroplasticity, and proteostasis within LC and VTA affect a variety of brain areas. Therefore, we focus on alterations of autophagy machinery in these nuclei as a relevant trigger in this chain of events. In fact, these catecholamine-containing areas are mostly prone to autophagy-dependent neurodegeneration. Thus, we propose a dynamic hypothesis according to which stress-induced autophagy alterations within the LC-VTA network foster a cascade towards early neurodegeneration within these nuclei.

GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology

INTRODUCTION

During the last decade, a multitude of novel quantitative and semiquantitative MRI techniques have provided new information about the pathophysiology of neurological diseases. Yet, selection of the most relevant contrasts for a given pathology remains challenging. In this work, we developed and validated a method, Gated-Attention MEchanism Ranking of multi-contrast MRI in brain pathology (GAMER MRI), to rank the relative importance of MR measures in the classification of well understood ischemic stroke lesions. Subsequently, we applied this method to the classification of multiple sclerosis (MS) lesions, where the relative importance of MR measures is less understood.

METHODS

GAMER MRI was developed based on the gated attention mechanism, which computes attention weights (AWs) as proxies of importance of hidden features in the classification. In the first two experiments, we used Trace-weighted (Trace), apparent diffusion coefficient (ADC), Fluid-Attenuated Inversion Recovery (FLAIR), and T1-weighted (T1w) images acquired in 904 acute/subacute ischemic stroke patients and in 6,230 healthy controls and patients with other brain pathologies to assess if GAMER MRI could produce clinically meaningful importance orders in two different classification scenarios. In the first experiment, GAMER MRI with a pretrained convolutional neural network (CNN) was used in conjunction with Trace, ADC, and FLAIR to distinguish patients with ischemic stroke from those with other pathologies and healthy controls. In the second experiment, GAMER MRI with a patch-based CNN used Trace, ADC and T1w to differentiate acute ischemic stroke lesions from healthy tissue. The last experiment explored the performance of patch-based CNN with GAMER MRI in ranking the importance of quantitative MRI measures to distinguish two groups of lesions with different pathological characteristics and unknown quantitative MR features. Specifically, GAMER MRI was applied to assess the relative importance of the myelin water fraction (MWF), quantitative susceptibility mapping (QSM), T1 relaxometry map (qT1), and neurite density index (NDI) in distinguishing 750 juxtacortical lesions from 242 periventricular lesions in 47 MS patients. Pair-wise permutation t-tests were used to evaluate the differences between the AWs obtained for each quantitative measure.

RESULTS

In the first experiment, we achieved a mean test AUC of 0.881 and the obtained AWs of FLAIR and the sum of AWs of Trace and ADC were 0.11 and 0.89, respectively, as expected based on previous knowledge. In the second experiment, we achieved a mean test F1 score of 0.895 and a mean AW of Trace = 0.49, of ADC = 0.28, and of T1w = 0.23, thereby confirming the findings of the first experiment. In the third experiment, MS lesion classification achieved test balanced accuracy = 0.777, sensitivity = 0.739, and specificity = 0.814. The mean AWs of T1map, MWF, NDI, and QSM were 0.29, 0.26, 0.24, and 0.22 (p < 0.001), respectively.

CONCLUSIONS

This work demonstrates that the proposed GAMER MRI might be a useful method to assess the relative importance of MRI measures in neurological diseases with focal pathology. Moreover, the obtained AWs may in fact help to choose the best combination of MR contrasts for a specific classification problem.

The Italian INTERCEPTOR Project: From the Early Identification of Patients Eligible for Prescription of Antidementia Drugs to a Nationwide Organizational Model for Early Alzheimer's Disease Diagnosis

Alzheimer's disease is the most common age-related neurodegenerative disorder and its burden on patients, families, and society grows significantly with lifespan. Early modifications of risk-enhancing lifestyles and treatment initiation expand personal autonomy and reduce management costs. Many clinical trials with potentially disease-modifying drugs are devoted to mild cognitive impairment (MCI) prodromal-to-Alzheimer's disease. The identification of biomarkers for early diagnosis may thus be crucial for early intervention and identification of high-risk subjects, the most appropriate target of new drugs as soon as they will be discovered. INTERCEPTOR is a strategic project by the Italian Ministry of Health and the Italian Medicines Agency (AIFA), aiming to validate the best combination (highly accurate, non-invasive, available on the whole national territory and financially sustainable) of biomarkers and organizational model for early diagnosis. 500 MCI subjects will be enrolled at baseline and followed-up for 3 years for at least 400 of them in order to define a "hub & spoke" nationwide model with recruiting (spokes) centers for MCI identification and expert (hubs) centers for risk diagnosis.

Pre-clinical dose-ranging efficacy, pharmacokinetics, tissue biodistribution, and toxicity of a targeted contrast agent for MRI of amyloid deposition in Alzheimer's disease

In these preclinical studies, we describe ADx-001, an Aβ-targeted liposomal macrocyclic gadolinium (Gd) imaging agent, for MRI of amyloid plaques. The targeting moiety is a novel lipid-PEG conjugated styryl-pyrimidine. An MRI-based contrast agent such as ADx-001 is attractive because of the lack of radioactivity, ease of distribution, long shelf life, and the prevalence of MRI scanners. Dose-ranging efficacy studies were performed on a 1 T MRI scanner using a transgenic APP/PSEN1 mouse model of Alzheimer's disease. ADx-001 was tested at 0.10, 0.15, and 0.20 mmol Gd/kg. Gold standard post-mortem amyloid immunostaining was used for the determination of sensitivity and specificity. ADx-001 toxicity was evaluated in rats and monkeys at doses up to 0.30 mmol Gd/kg. ADx-001 pharmacokinetics were determined in monkeys and its tissue distribution was evaluated in rats. ADx-001-enhanced MRI demonstrated significantly higher (p < 0.05) brain signal enhancement in transgenic mice relative to wild type mice at all dose levels. ADx-001 demonstrated high sensitivity at 0.20 and 0.15 mmol Gd/kg and excellent specificity at all dose levels for in vivo imaging of β amyloid plaques. ADx-001 was well tolerated in rats and monkeys and exhibited the slow clearance from circulation and tissue biodistribution typical of PEGylated nanoparticles.

A Connectomic Atlas of the Human Cerebrum-Chapter 17: Tractographic Description of the Cingulum

In this supplement, we show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In this chapter, we specifically address regions integrating to form the cingulum.

A Connectomic Atlas of the Human Cerebrum-Chapter 15: Tractographic Description of the Uncinate Fasciculus

In this supplement, we show a comprehensive anatomic atlas of the human cerebrum demonstrating all 180 distinct regions comprising the cerebral cortex. The location, functional connectivity, and structural connectivity of these regions are outlined, and where possible a discussion is included of the functional significance of these areas. In this chapter, we specifically address the regions integrating to form the uncinate fasciculus.

Thalamocortical disconnection affects the somatic marker and social cognition: a case report

Thalamo-cortical connectivity was characterised in a patient with bilateral infarct of the thalami, without evidence of cognitive deficits in everyday life. Patient underwent social and emotional tests, Iowa Gambling Task (IGT), with and without concomitant heart rate variability (HRV) recording and at 3T-MRI to assess thalamo-cortical connectivity. Patient showed impairment at the IGT, in somatic marker, in emotions and theory of mind. MRI documented a bilateral damage of the centromedian-parafascicular complex. Patient's thalamic lesions disconnected brain areas involved in decision-making and autonomic regulation, affecting the somatic marker and resulting in the neuropsychological deficit exhibited by L.C.

Connectome-derived diffusion characteristics of the fornix in Alzheimer's disease

The fornix bundle is a major white matter pathway of the hippocampus. While volume of the hippocampus has been a primary imaging biomarker of Alzheimer's disease progression, recent research has suggested that the volume and microstructural characteristics of the fornix bundle connecting the hippocampus could add relevant information for diagnosing and staging Alzheimer's disease. Using a robust fornix bundle isolation technique in native diffusion space, this study investigated whether diffusion measurements of the fornix differed between normal older adults and Alzheimer's disease patients when controlling for volume measurements. Data were collected using high gradient multi-shell diffusion-weighted MRI from a Siemens CONNECTOM scanner in 23 Alzheimer's disease and 23 age- and sex-matched control older adults (age range = 53–92). These data were used to reconstruct a continuous fornix bundle in every participant's native diffusion space, from which tract-derived volumetric and diffusion metrics were extracted and compared between groups. Diffusion metrics included those from a tensor model and from a generalized q-sampling imaging model. Results showed no significant differences in tract-derived fornix volumes but did show altered diffusion metrics within tissue classified as the fornix in the Alzheimer's disease group. Comparisons to a manual tracing method indicated the same pattern of results and high correlations between the methods. These results suggest that in Alzheimer's disease, diffusion characteristics may provide more sensitive measures of fornix degeneration than do volume measures and may be a potential early marker for loss of medial temporal lobe connectivity.

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An enhanced method for measurement of continuous fornix bundles is described.

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Diffusion characteristics of the fornix were degraded in Alzheimer's disease.

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Alzheimer's disease primarily affected the crus and body of the fornix.

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Diffusion differences were observed controlling for fornix volume differences.

CSF β-amyloid and white matter damage: a new perspective on Alzheimer's disease

OBJECTIVE

To assess the connection between amyloid pathology and white matter (WM) macrostructural and microstructural damage in demented patients compared with controls.

METHODS

Eighty-five participants were recruited: 65 with newly diagnosed Alzheimer's disease (AD), non-AD dementia or mild cognitive impairment and 20 age-matched and sex-matched healthy controls. β-amyloid_1-42 (Aβ) levels were determined in cerebrospinal fluid (CSF) samples from all patients and five controls. Among patients, 42 had pathological CSF Aβ levels (Aβ(+)), while 23 had normal CSF Aβ levels (Aβ(-)). All participants underwent neurological examination, neuropsychological testing and brain MRI. We used T2-weighted scans to quantify WM lesion loads (LLs) and diffusion-weighted images to assess their microstructural substrate. Non-parametric statistical tests were used for between-group comparisons and multiple regression analyses.

RESULTS

We found an increased WM-LL in Aβ(+) compared with both, healthy controls (p=0.003) and Aβ(-) patients (p=0.02). Interestingly, CSF Aβ concentration was the best predictor of patients' WM-LL (r=-0.30, p<0.05) when using age as a covariate. Lesion apparent diffusion coefficient value was higher in all patients than in controls (p=0.0001) and correlated with WM-LL (r=0.41, p=0.001). In Aβ(+), WM-LL correlated with WM microstructural damage in the left peritrigonal WM (p<0.0001).

CONCLUSIONS

WM damage is crucial in AD pathogenesis. The correlation between CSF Aβ levels and WM-LL suggests a direct link between amyloid pathology and WM macrostructural and microstructural damage.

Imaging plus X: multimodal models of neurodegenerative disease

PURPOSE OF REVIEW

This article argues that the time is approaching for data-driven disease modelling to take centre stage in the study and management of neurodegenerative disease. The snowstorm of data now available to the clinician defies qualitative evaluation; the heterogeneity of data types complicates integration through traditional statistical methods; and the large datasets becoming available remain far from the big-data sizes necessary for fully data-driven machine-learning approaches. The recent emergence of data-driven disease progression models provides a balance between imposed knowledge of disease features and patterns learned from data. The resulting models are both predictive of disease progression in individual patients and informative in terms of revealing underlying biological patterns.

RECENT FINDINGS

Largely inspired by observational models, data-driven disease progression models have emerged in the last few years as a feasible means for understanding the development of neurodegenerative diseases. These models have revealed insights into frontotemporal dementia, Huntington's disease, multiple sclerosis, Parkinson's disease and other conditions. For example, event-based models have revealed finer graded understanding of progression patterns; self-modelling regression and differential equation models have provided data-driven biomarker trajectories; spatiotemporal models have shown that brain shape changes, for example of the hippocampus, can occur before detectable neurodegeneration; and network models have provided some support for prion-like mechanistic hypotheses of disease propagation. The most mature results are in sporadic Alzheimer's disease, in large part because of the availability of the Alzheimer's disease neuroimaging initiative dataset. Results generally support the prevailing amyloid-led hypothetical model of Alzheimer's disease, while revealing finer detail and insight into disease progression.

SUMMARY

The emerging field of disease progression modelling provides a natural mechanism to integrate different kinds of information, for example from imaging, serum and cerebrospinal fluid markers and cognitive tests, to obtain new insights into progressive diseases. Such insights include fine-grained longitudinal patterns of neurodegeneration, from early stages, and the heterogeneity of these trajectories over the population. More pragmatically, such models enable finer precision in patient staging and stratification, prediction of progression rates and earlier and better identification of at-risk individuals. We argue that this will make disease progression modelling invaluable for recruitment and end-points in future clinical trials, potentially ameliorating the high failure rate in trials of, e.g., Alzheimer's disease therapies. We review the state of the art in these techniques and discuss the future steps required to translate the ideas to front-line application.