Modeling seeding and neuroanatomic spread of pathology in amyotrophic lateral sclerosis.

The neurodegenerative disorder amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of upper and lower motor neurons, with pathological involvement of cerebral motor and extra-motor areas in a clinicopathological spectrum with frontotemporal dementia (FTD). A key unresolved issue is how the non-random distribution of pathology in ALS reflects differential network vulnerability, including molecular factors such as regional gene expression, or preferential spread of pathology via anatomical connections. A system of histopathological staging of ALS based on the regional burden of TDP-43 pathology observed in postmortem brains has been supported to some extent by analysis of distribution of in vivo structural MRI changes. In this paper, computational modeling using a Network Diffusion Model (NDM) was used to investigate whether a process of focal pathological 'seeding' followed by structural network-based spread recapitulated postmortem histopathological staging and, secondly, whether this had any correlation to the pattern of expression of a panel of genes implicated in ALS across the healthy brain. Regionally parcellated T1-weighted MRI data from ALS patients (baseline n=79) was studied in relation to a healthy control structural connectome and a database of associated regional cerebral gene expression. The NDM provided strong support for a structural network-based basis for regional pathological spread in ALS, but no simple relationship to the spatial distribution of ALS-related genes in the healthy brain. Interestingly, OPTN gene was identified as a significant but a weaker non-NDM contributor within the network-gene interaction model (LASSO). Intriguingly, the critical seed regions for spread within the model were not within the primary motor cortex but basal ganglia, thalamus and insula, where NDM recapitulated aspects of the postmortem histopathological staging system. Within the ALS-FTD clinicopathological spectrum, non-primary motor structures may be among the earliest sites of cerebral pathology.

Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients.

BACKGROUND: Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients. OBJECTIVE: We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients. METHODS: Ninety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA). RESULTS: One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337). CONCLUSIONS: These results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.

Structural disconnectivity from paramagnetic rim lesions is related to disability in multiple sclerosis.

BACKGROUND: In people with multiple sclerosis (pwMS), lesions with a hyperintense rim (rim+) on Quantitative Susceptibility Mapping (QSM) have been shown to have greater myelin damage compared to rim- lesions, but their association with disability has not yet been investigated. Furthermore, how QSM rim+ and rim- lesions differentially impact disability through their disruptions to structural connectivity has not been explored. We test the hypothesis that structural disconnectivity due to rim+ lesions is more predictive of disability compared to structural disconnectivity due to rim- lesions. METHODS: Ninety-six pwMS were included in our study. Individuals with Expanded Disability Status Scale (EDSS) <2 were considered to have lower disability (n = 59). For each gray matter region, a Change in Connectivity (ChaCo) score, that is, the percent of connecting streamlines also passing through a rim- or rim+ lesion, was computed. Adaptive Boosting was used to classify the pwMS into lower versus greater disability groups based on ChaCo scores from rim+ and rim- lesions. Classification performance was assessed using the area under ROC curve (AUC). RESULTS: The model based on ChaCo from rim+ lesions outperformed the model based on ChaCo from rim- lesions (AUC = 0.67 vs 0.63, p-value < .05). The left thalamus and left cerebellum were the most important regions in classifying pwMS into disability categories. CONCLUSION: rim+ lesions may be more influential on disability through their disruptions to the structural connectome than rim- lesions. This study provides a deeper understanding of how rim+ lesion location/size and resulting disruption to the structural connectome can contribute to MS-related disability.

Longitudinal change in TSPO PET imaging in progressive multiple sclerosis.

The objective of this pilot study was to assess a 2-year change in innate immune burden in 15 progressive multiple sclerosis (MS) patients using PK11195-PET. Sixteen age-matched healthy controls (HC) were included for baseline comparison. PK11195 uptake was higher in MS patients compared to HC within normal-appearing white matter (NAWM) and multiple gray matter regions. In patients, PK11195 uptake increased in NAWM (p = 0.01), cortex (p = 0.04), thalamus (p = 0.04), and putamen (p = 0.02) at 12 months. Among patients remaining at 24 months, there was no further increase in PK11195. Our data suggest that innate immune activity may increase over time in patients with progressive MS.

Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713.

INTRODUCTION: Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF. MATERIALS AND METHODS: Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed. RESULTS: Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%). CONCLUSIONS: PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

Molecular Imaging of Striatal Dopaminergic Neuronal Loss and the Neurovascular Unit in Parkinson Disease.

Parkinson disease (PD) is the second most common neurodegenerative disorder, characterized by loss of nigrostriatal dopaminergic neurons. Impairment of the neurovascular unit (NVU) has been hypothesized to play a critical role in early PD pathophysiology, and to precede neurodegenerative mechanisms. [C-11]-PE2I (N-(3-iodoprop-2E-enyl)-2b-carbomethoxy-3b-(4-methyl-phenyl)nortropane) (PE2I) is a PET radiotracer targeting neuronal dopamine transporters (DaT) with high specificity, allowing for highly accurate and specific DaT quantification. We investigated NVU integrity using arterial spin labeling (ASL) MRI in a prospective cohort of 26 patients with PD, and correlated our findings with analysis of striatal DaT density using PE2I PET in a subcohort of 17 patients. Analysis was performed in FreeSurfer to obtain rCBF and mean standardized regional PET avidity. Pearson correlations and Mann-Whitney tests were performed. Significantly lower mean normalized striatal PE2I SUV values were seen in multiple regions in patients with greater disease duration (p < 0.05). PET uptake in the putamen correlated with disease duration independent of patient age. Stratifying patients based on Montreal Cognitive Assessment (MoCA) scores (stratified into ≥ 27 vs. < 27), there was statistically significantly lower PE2I PET avidity in the higher MoCA score group in both more and less affected sides of the caudate, putamen and pallidum (p < 0.05). A moderate negative correlation between MDS-UPDRS part 3 (motor) "off" and rCBF values was also seen in the L and R cerebellum WM (r = -0.43 and -0.47, p < 0.05). A statistically significant negative correlation was found between dominant hand pegboard test results and rCBF in the less affected pallidum (r = -0.41; p = 0.046). A statistically significant negative correlation of ASL MRI with [11C]-PE2I PET was also found (r = -0.53 to -0.58; p-value 0.017-0.033) between left cerebral WM rCBF and more and less affected striatal PET regions. Our ROI-based analyses suggest that longer disease duration is associated with lower rCBF and lower PE2I mean SUV, implying greater NVU dysfunction and dopaminergic neuronal loss, respectively. Combined ASL MRI and PE2I PET imaging could inform future prospective clinical trials providing an improved mechanistic understanding of the disease, laying the foundation for the development of early disease biomarkers and potential therapeutic targets.

Network mediation of pathology pattern in sporadic Creutzfeldt-Jakob disease.

Sporadic Creutzfeldt-Jakob disease is a rare fatal rapidly progressive dementia caused by the accumulation and spread of pathologically misfolded prions. Evidence from animal models and in vitro experiments suggests that prion pathology propagates along neural connectivity pathways, with the transmission of misfolded prions initiating a corruptive templating process in newly encountered brain regions. Although particular regional patterns of disease have been recognized in humans, the underlying mechanistic basis of these patterns remains poorly understood. Here, we demonstrate that the spatial pattern of disease derived from publicly available human diffusion-weighted MRI data demonstrates stereotypical features across patient cohorts and can be largely explained by intrinsic connectivity properties of the human structural brain network. Regional diffusion-weighted MRI signal abnormalities are predicted by graph theoretical measures of centrality, with highly affected regions such as cingulate gyrus demonstrating strong structural connectivity to other brain regions. We employ network diffusion modelling to demonstrate that the spatial pattern of disease can be predicted by a diffusion process originating from a single regional pathology seed and operating on the structural connectome. The most likely seeds correspond to the most highly affected brain regions, suggesting that pathological prions could originate in a single brain region and spread throughout the brain to produce the regional distribution of pathology observed on MRI. Further investigation of top seed regions and associated connectivity pathways may be a useful strategy for developing therapeutic approaches.

Origins of atrophy in Parkinson linked to early onset and local transcription patterns.

There is enormous clinical value in inferring the brain regions initially atrophied in Parkinson disease for individual patients and understanding its relationship with clinical and genetic risk factors. The aim of this study is to leverage a new seed-inference algorithm demonstrated for Alzheimer's disease to the Parkinsonian context and to cluster patients in meaningful subgroups based on these incipient atrophy patterns. Instead of testing brain regions separately as the likely initiation site for each patient, we solve an L1-penalized optimization problem that can return a more predictive heterogeneous, multi-locus seed patterns. A cluster analysis of the individual seed patterns reveals two distinct subgroups (S1 versus S2). The S1 subgroup is characterized by the involvement of the brainstem and ventral nuclei, and S2 by cortex and striatum. Post hoc analysis in features not included in the clustering shows significant differences between subgroups regarding age of onset and local transcriptional patterns of Parkinson-related genes. Top genes associated with regional microglial abundance are strongly associated with subgroup S1 but not with S2. Our results suggest two distinct aetiological mechanisms operative in Parkinson disease. The interplay between immune-related genes, lysosomal genes, microglial abundance and atrophy initiation sites may explain why the age of onset for patients in S1 is on average 4.5 years later than for those in S2. We highlight and compare the most prominently affected brain regions for both subgroups. Altogether, our findings may improve current screening strategies for early Parkinson onsetters.

Impact of Lesion Location on Longitudinal Myelin Water Fraction Change in Chronic Multiple Sclerosis Lesions.

BACKGROUND AND PURPOSE: To examine the impact of lesion location on longitudinal myelin water fraction (MWF) changes in chronic multiple sclerosis (MS) lesions. Relative hypoxia, due to vascular watershed regions of the cerebrum, has been implicated in lesion development but impact on ongoing demyelination is unknown. METHODS: Forty-eight patients with relapsing-remitting and secondary progressive MS had two MWF scans with fast acquisition, spiral trajectory, and T2prep (FAST-T2) sequence, at an interval of 2.0 (±.3) years. Lesion location was identified based upon cerebral lobe and relation to the ventricles. Change in MWF was assessed using a mixed effects model, controlling for lesion location and patient covariates. RESULTS: Average age was 42.3 (±12) years, mean disease duration was 9.7 (±9.1) years, and median Expanded Disability Status Score (EDSS) was 2.5 (±2.3). The majority of 512 chronic lesions was located in the frontal and parietal lobes (75.6%) and more often periventricular (44.7%). All occipital lesions were periventricular. The average lesion MWF decreased from baseline (.07 ± .03) to 2 years (.06 ±.03) P < .01. Lesions within the occipital lobe showed a significant reduction in MWF as compared to other lobes. CONCLUSIONS: Chronic lesions in the occipital lobe showed the greatest reduction in MWF. Neuroanatomical localization of lesions to the occipital horns of the lateral ventricles, a watershed region, may contribute to ongoing demyelination in this lesion type.

Regional transcriptional architecture of Parkinson's disease pathogenesis and network spread.

Although a significant genetic contribution to the risk of developing sporadic Parkinson's disease has been well described, the relationship between local genetic factors, pathogenesis, and subsequent spread of pathology throughout the brain has been largely unexplained in humans. To address this question, we use network diffusion modelling to infer probable pathology seed regions and patterns of disease spread from MRI atrophy maps derived from 232 de novo subjects in the Parkinson's Progression Markers Initiative study. Allen Brain Atlas regional transcriptional profiles of 67 Parkinson's disease risk factor genes were mapped to the inferred seed regions to determine the local influence of genetic risk factors. We used hierarchical clustering and L1 regularized regression analysis to show that transcriptional profiles of immune-related and lysosomal risk factor genes predict seed region location and the pattern of disease propagation from the most likely seed region, substantia nigra. By leveraging recent advances in transcriptomics, we show that regional microglial abundance quantified by high fidelity gene expression also predicts seed region location. These findings suggest that early disease sites are genetically susceptible to dysfunctional lysosomal α-synuclein processing and microglia-mediated neuroinflammation, which may initiate the disease process and contribute to spread of pathology along neural connectivity pathways.

Quantitative susceptibility mapping identifies inflammation in a subset of chronic multiple sclerosis lesions.

Chronic active multiple sclerosis lesions, characterized by a hyperintense rim of iron-enriched, activated microglia and macrophages, have been linked to greater tissue damage. Post-mortem studies have determined that chronic active lesions are primarily related to the later stages of multiple sclerosis; however, the occurrence of these lesions, and their relationship to earlier disease stages may be greatly underestimated. Detection of chronic active lesions across the patient spectrum of multiple sclerosis requires a validated imaging tool to accurately identify lesions with persistent inflammation. Quantitative susceptibility mapping provides efficient in vivo quantification of susceptibility changes related to iron deposition and the potential to identify lesions harbouring iron-laden inflammatory cells. The PET tracer 11C-PK11195 targets the translocator protein expressed by activated microglia and infiltrating macrophages. Accordingly, this study aimed to validate that lesions with a hyperintense rim on quantitative susceptibility mapping from both relapsing and progressive patients demonstrate a higher level of innate immune activation as measured on 11C-PK11195 PET. Thirty patients were enrolled in this study, 24 patients had relapsing remitting multiple sclerosis, six had progressive multiple sclerosis, and all patients had concomitant MRI with a gradient echo sequence and PET with 11C-PK11195. A total of 406 chronic lesions were detected, and 43 chronic lesions with a hyperintense rim on quantitative susceptibility mapping were identified as rim+ lesions. Susceptibility (relative to CSF) was higher in rim+ (2.42 ± 17.45 ppb) compared to rim- lesions (-14.6 ± 19.3 ppb, P < 0.0001). Among rim+ lesions, susceptibility within the rim (20.04 ± 14.28 ppb) was significantly higher compared to the core (-5.49 ± 14.44 ppb, P < 0.0001), consistent with the presence of iron. In a mixed-effects model, 11C-PK11195 uptake, representing activated microglia/macrophages, was higher in rim+ lesions compared to rim- lesions (P = 0.015). Validating our in vivo imaging results, multiple sclerosis brain slabs were imaged with quantitative susceptibility mapping and processed for immunohistochemistry. These results showed a positive translocator protein signal throughout the expansive hyperintense border of rim+ lesions, which co-localized with iron containing CD68+ microglia and macrophages. In conclusion, this study provides evidence that suggests that a hyperintense rim on quantitative susceptibility measure within a chronic lesion is a correlate for persistent inflammatory activity and that these lesions can be identified in the relapsing patients. Utilizing quantitative susceptibility measure to differentiate chronic multiple sclerosis lesion subtypes, especially chronic active lesions, would provide a method to assess the impact of these lesions on disease progression.

Regional expression of genes mediating trans-synaptic alpha-synuclein transfer predicts regional atrophy in Parkinson disease.

Multiple genes have been implicated in Parkinson disease pathogenesis, but the relationship between regional expression of these genes and regional dysfunction across the brain is unknown. We address this question by joint analysis of high resolution magnetic resonance imaging data from the Parkinson's Progression Markers Initiative and regional genetic microarray expression data from the Allen Brain Atlas. Regional brain atrophy and genetic expression was co-registered to a common 86 region brain atlas and robust multivariable regression analysis was performed to identify genetic predictors of regional brain atrophy. Top candidate genes from GWAS analysis, as well as genes implicated in trans-synaptic alpha-synuclein transfer and autosomal recessive PD were included in our analysis. We identify three genes with expression patterns that are highly significant predictors of regional brain atrophy. The two most significant predictors are LAG3 and RAB5A, genes implicated in trans-synaptic synuclein transfer. Other well-validated PD-related genes do not have expression patterns that predict regional atrophy, suggesting that they may serve other roles such as disease initiation factors.

A method for inferring regional origins of neurodegeneration.

Alzheimer's disease, the most common form of dementia, is characterized by the emergence and spread of senile plaques and neurofibrillary tangles, causing widespread neurodegeneration. Though the progression of Alzheimer's disease is considered to be stereotyped, the significant variability within clinical populations obscures this interpretation on the individual level. Of particular clinical importance is understanding where exactly pathology, e.g. tau, emerges in each patient and how the incipient atrophy pattern relates to future spread of disease. Here we demonstrate a newly developed graph theoretical method of inferring prior disease states in patients with Alzheimer's disease and mild cognitive impairment using an established network diffusion model and an L1-penalized optimization algorithm. Although the 'seeds' of origin using our inference method successfully reproduce known trends in Alzheimer's disease staging on a population level, we observed that the high degree of heterogeneity between patients at baseline is also reflected in their seeds. Additionally, the individualized seeds are significantly more predictive of future atrophy than a single seed placed at the hippocampus. Our findings illustrate that understanding where disease originates in individuals is critical to determining how it progresses and that our method allows us to infer early stages of disease from atrophy patterns observed at diagnosis.

Combination photo and electron beam lithography with polymethyl methacrylate (PMMA) resist.

We describe techniques for performing photolithography and electron beam lithography in succession on the same resist-covered substrate. Larger openings are defined in the resist film through photolithography whereas smaller openings are defined through conventional electron beam lithography. The two processes are carried out one after the other and without an intermediate wet development step. At the conclusion of the two exposures, the resist film is developed once to reveal both large and small openings. Interestingly, these techniques are applicable to both positive and negative tone lithographies with both optical and electron beam exposure. Polymethyl methacrylate, by itself or mixed with a photocatalytic cross-linking agent, is used for this purpose. We demonstrate that such resists are sensitive to both ultraviolet and electron beam irradiation. All four possible combinations, consisting of optical and electron beam lithographies, carried out in positive and negative tone modes have been described. Demonstration grating structures have been shown and process conditions have been described for all four cases.

MRI Analysis of White Matter Myelin Water Content in Multiple Sclerosis: A Novel Approach Applied to Finding Correlates of Cortical Thinning.

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m1 of the gamma component shown to relate to lesion, the mode m2 of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R2, both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m1 (ß = 1.56, p < 0.005), λ (ß = -0.30, p < 0.0005) and age (ß = -0.0031, p < 0.005) for the RRMS group (adjusted R2 = 0.16), and m2 (ß = 4.72, p < 0.0005) for the SPMS group (adjusted R2 = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m1, than to an ROI associated with m2 (p < 0.00001), and vice versa for the NAWM mask (p < 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks.

Predictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion.

Several neurodegenerative disorders including Alzheimer's disease (AD), frontotemporal dementia (FTD), Parkinson's disease (PD), amyotrophic lateral sclerosis, and Huntington's disease report aggregation and transmission of pathogenic proteins between cells. The topography of these diseases in the human brain also, therefore, displays a well-characterized and stereotyped regional pattern, and a stereotyped progression over time. This is most commonly true for AD and other dementias characterized by hallmark misfolded tau or alpha-synuclein pathology. Both tau and synuclein appear to propagate within brain circuits using a shared mechanism. The most canonical synucleopathy is PD; however, much less studied is a rare disorder called progressive supranuclear palsy (PSP). The hallmark pathology and atrophy in PSP are, therefore, also highly stereotyped: initially appearing in the striatum, followed by its neighbors and connected cortical areas. In this study, we explore two mechanistic aspects hitherto unknown about the canonical network diffusion model (NDM) of spread: (a) whether the NDM can apply to other common degenerative pathologies, specifically PSP, and (b) whether the directionality of spread is important in explaining empirical data. Our results on PSP reveal two important findings: first, that PSP is amenable to the connectome-based ND modeling in the same way as previously applied to AD and FTD and, second, that the NDM fit with empirical data are significantly enhanced by using the directional rather than the non-directional form of the human connectome. Specifically, we show that both the anterograde model of transmission (some to axonal terminal) and retrograde mode explain PSP topography more accurately than non-directional transmission. Collectively, these data show that the intrinsic architecture of the structural network mediates disease spread in PSP, most likely via a process of trans-neuronal transmission. These intriguing results have several ramifications for future studies.

The Brain's Structural Connectome Mediates the Relationship between Regional Neuroimaging Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD), one of the most common causes of dementia in adults, is a progressive neurodegenerative disorder exhibiting well-defined neuropathological hallmarks. It is known that disease pathology involves misfolded amyloid-ß (Aß) and tau proteins, and exhibits a relatively stereotyped progression over decades. The relationship between AD neuropathological hallmarks (Aß, hypometabolism, and tau proteins) and imaging biomarkers (MRI, AV-45/FDG-PET) is not fully understood. In addition, biomarker pathologies are oftentimes discordant, wherein it may show varying levels of abnormality across brain regions. Evidence based on recent elucidation of trans-neuronal "prion-like" transmission and other available data already suggests that disease spread follows the brain's fiber connectivity network. Thereby, the brain's connectome information can be used to predict the process of disease spread in AD. A recently established mathematical model of AD pathology spread using a connectome-based network diffusion model was successful in encapsulating neurodegenerative progression. Motivated by these network-based findings, the current study explores whether and how network connectivity mediates the interactions between various AD biomarkers. We hypothesized that the structural connectivity matrix will mediate the cross-sectional association between regional AD-associated hypometabolism and Aß deposition. Given recent reports of inherent or lifetime activity of brain regions as strong predictors of Aß deposition in patients, we also tested whether healthy metabolism exerts a network-mediated effect on Aß deposition and hypometabolism in AD patients. We found that regional Aß deposition is best predicted by a linear combination of both regional healthy local metabolism and connectome-mediated regional healthy metabolism.

Cognitive deficits in non-demented diabetic elderly appear independent of brain amyloidosis.

BACKGROUND: To determine the effects of Type 2 diabetes (DM2) on levels of brain amyloidosis and cognition in a community-dwelling cohort of nondemented elderly individuals. METHODS: 33 subjects (16 DM2, 17 nondiabetic) were prospectively recruited. Subjects underwent a PET scan using the amyloid tracer, Pittsburgh Compound B, and a neuropsychological evaluation. Associations between DM2, brain amyloidosis, and cognition were assessed using multivariate regressions, adjusting for age and APOE4 status. RESULTS: DM2 subjects had lower global cognitive function (p=0.018), as measured by the Repeatable Battery for the Assessment of Neuropsychological Status. There was no difference in brain amyloidosis between groups (p=0.25). CONCLUSIONS: Community-dwelling, nondemented individuals with DM2 had greater cognitive deficits, which do not appear to be mediated by brain amyloidosis. Further studies exploring potential mediators of these cognitive deficits should be performed.

Feasibility and reproducibility of whole brain myelin water mapping in 4 minutes using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) at 3T.

PURPOSE: To develop and measure the reproducibility of 4-min whole brain myelin water fraction (MWF) mapping using fast acquisition with spiral trajectory and T2prep (FAST-T2) sequence at 3T. METHODS: Experiments were performed on phantoms, 13 volunteers, and 16 patients with multiple sclerosis. MWF maps were extracted using a spatially constrained non-linear algorithm. The proposed adiabatic modified BIR-4 (mBIR-4) T2prep was compared with the conventional composite T2prep (COMP). The effect of reducing the number of echo times (TEs) from 15 to 6 (reducing scan time from 10 to 4 min) was evaluated. Reproducibility was assessed using correlation analysis, coefficient of variation (COV), and Bland-Altman plots. RESULTS: Compared with COMP, mBIR-4 provided more accurate T2 in phantoms and better MWF maps in human brains. Reducing the number of TEs had a negligible effect on MWF map quality, with a regional MWF difference of <0.8%. Regional MWFs obtained by repeated scans showed excellent correlation (R = 0.99), low COV (1.3%-2.4%), and negligible bias within ±1% limits of agreement. On a voxel-wise basis, the agreement remained strong (correlation R = 0.89 ± 0.03, bias = 0.01% ± 0.29%, limits of agreement = [-3.35% ± 0.73%, 3.33% ± 0.61%]). CONCLUSION: Whole brain MWF mapping with adiabatic FAST-T2 is feasible in 4 min and provides good intrasite reproducibility. Magn Reson Med 76:456-465, 2016. © 2015 Wiley Periodicals, Inc.

Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis.

AIMS: describe a new "profilometry" framework for the multimetric analysis of white matter tracts, and demonstrate its application to multiple sclerosis (MS) with radial diffusivity (RD) and myelin water fraction (MWF). METHODS: A cohort of 15 normal controls (NC) and 141 MS patients were imaged with T1, T2 FLAIR, T2 relaxometry and diffusion MRI (dMRI) sequences. T1 and T2 FLAIR allowed for the identification of patients having lesion(s) on the tracts studied, with a special focus on the forceps minor. T2 relaxometry provided MWF maps, while dMRI data yielded RD maps and the tractography required to compute MWF and RD tract profiles. The statistical framework combined a multivariate analysis of covariance (MANCOVA) and a linear discriminant analysis (LDA) both accounting for age and gender, with multiple comparison corrections. RESULTS: In the single-case case study the profilometry visualization showed a clear departure of MWF and RD from the NC normative data at the lesion location(s). Group comparison from MANCOVA demonstrated significant differences at lesion locations, and a significant age effect in several tracts. The follow-up LDA analysis suggested MWF better discriminates groups than RD. DISCUSSION AND CONCLUSION: While progress has been made in both tract-profiling and metrics for white matter characterization, no single framework for a joint analysis of multimodality tract profiles accounting for age and gender is known to exist. The profilometry analysis and visualization appears to be a promising method to compare groups using a single score from MANCOVA while assessing the contribution of each metric with LDA.