Supervised method to build an atlas database for multi-atlas segmentation-propagation

Multi-atlas based segmentation-propagation approaches have been shown to obtain accurate parcelation of brain structures. However, this approach requires a large number of manually delineated atlases, which are often not available. We propose a supervised method to build a population specific atlas database, using the publicly available Internet Brain Segmentation Repository (IBSR). The set of atlases grows iteratively as new atlases are added, so that its segmentation capability may be enhanced in the multi-atlas based approach. Using a dataset of 210 MR images of elderly subjects (170 elderly controls, 40 Alzheimer's disease) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, 40 MR images were segmented to build a population specific atlas database for the purpose of multi-atlas segmentation-propagation. The population specific atlases were used to segment the elderly population of 210 MR images, and were evaluated in terms of the agreement among the propagated labels. The agreement was measured by using the entropy H of the probability image produced when fused by voting rule and the partial moment mu(2) of the histogram. Compared with using IBSR atlases, the population specific atlases obtained a higher agreement when dealing with images of elderly subjects

Proteinosis alveolar pulmonarn rol de los anticuerpos ANTI-GM-CSF

La proteinosis alveolar pulmonar (PAP) es una enfermedad infrecuente caracterizada por una alteración en la depuración del surfactante pulmonar. Este proceso es dependiente del factor estimulante de colonias granulocito-monocito (GM-CSF). Aproximadamente un 90 % de los pacientes con PAP presentan anticuerpos que neutralizan este factor, impidiendo la normal homeostasis del surfactante. El tratamiento incluye la realización de lavados pulmonares totales y la administración de GM-CSF cuando los lavados fracasan. A pesar de que el dosaje de los anticuerpos séricos anti-GM-CSF podría contribuir a comprender el origen auto-inmune de la enfermedad, no es una práctica de rutina en ningún centro de salud. Presentamos una revisión sistemática de esta desafiante enfermedad. </p

Cross-sectional and Longitudinal Analysis of the Relationship Between A beta Deposition, Cortical Thickness, and Memory in Cognitively Unimpaired Individuals and in Alzheimer Disease

IMPORTANCE beta-amyloid (A beta) deposition is one of the hallmarks of Alzheimer disease. A beta deposition accelerates gray matter atrophy at early stages of the disease even before objective cognitive impairment is manifested. Identification of at-risk individuals at the presymptomatic stage has become a major research interest because it will allow early therapeutic interventions before irreversible synaptic and neuronal loss occur. We aimed to further characterize the cross-sectional and longitudinal relationship between A beta deposition, gray matter atrophy, and cognitive impairment

Sensitivity of composite scores to amyloid burden in preclinical Alzheimer\u27s disease: Introducing the Z-scores of Attention, Verbal fluency, and Episodic memory for Nondemented older adults composite score

Introduction: Cognitive composite scores developed for preclinical Alzheimer\u27s disease (AD) often consist of multiple cognitive domains as they may provide greater sensitivity to detect β-amyloid (Aβ)-related cognitive decline than episodic memory (EM) composite scores alone. However, this has never been empirically tested. We compared the rate of cognitive decline associated with high Aβ (Aβ+) and very high Aβ (Aβ++) in cognitively normal (CN) older adults on three multidomain cognitive composite scores and one single-domain (EM) composite score. Methods: CN older adults (n = 423) underwent Aβ neuroimaging and completed neuropsychological assessments at baseline, and at 18-, 36-, 54-, and 72-month follow-ups. Four cognitive composite scores were computed: the ADCS-PACC (ADCS-Preclinical Alzheimer Cognitive Composite), ADCS-PACC without the inclusion of the mini-mental state examination (MMSE), an EM composite, and the Z-scores of Attention, Verbal fluency, and Episodic memory for Nondemented older adults (ZAVEN) composite. Results: Compared with Aβ+ CN older adults, Aβ++ CN older adults showed faster rates of decline across all cognitive composites, with the largest decline observed for ZAVEN composite (d = 1.07). Similarly, compared with Aβ- CN older adults, Aβ+ CN older adults also showed faster rates of cognitive decline, but only for the ADCS-PACC no MMSE (d = 0.43), EM (d = 0.53), and ZAVEN (d = 0.50) composites. Discussion: Aβ-related cognitive decline is best detected using validated neuropsychological instruments. Removal of the MMSE from the ADCS-PACC and replacing it with a test of executive function (verbal fluency; i.e., the ZAVEN) rendered this composite more sensitive even in detecting Aβ-related cognitive decline between Aβ+ and Aβ++ CN older adults

Aβ-related memory decline in APOE ϵ4 noncarriers: Implications for Alzheimer disease

Objective: As the absence of Aβ-related memory decline in APOE ϵ4 noncarriers may be due to the relative brevity of previous studies, we aimed to characterize Aβ-related cognitive decline over 72 months in APOE ϵ4 carriers and noncarriers who were cognitively normal (CN). Methods: CN older adults (n 423) underwent Aβ imaging and APOE genotyping. Participants completed comprehensive neuropsychological testing at baseline 18-, 36-, 54-, and 72-month assessments. Results: Relative to Aβ- CN ϵ4 noncarriers, both Aβ+ CN ϵ4 carriers and noncarriers showed significantly increased decline in measures of memory, language, and executive function as well as higher rates of progression to a clinical classification of mild cognitive impairment. Memory decline was greater in Aβ+ CN ϵ4 carriers than in Aβ+ CN ϵ4 noncarriers. No cognitive decline was evident in Aβ- CN ϵ4 carriers. Conclusions: In CN older adults, Aβ+ is associated with memory decline in ϵ4 noncarriers; however, the rate of this decline is much slower than that observed in ϵ4 carriers. These data indicate that the processes by which ϵ4 carriage increases the rate of Aβ-related cognitive decline occur in the preclinical stage of Alzheimer disease. © 2016 American Academy of Neurology

A blood-based predictor for neocortical Aβ burden in Alzheimer\u27s disease: results from the AIBL study

Dementia is a global epidemic with Alzheimer’s disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based scree

COMT val158met is not associated with Aβ-amyloid and APOE ε4 related cognitive decline in cognitively normal older adults

The non-synonymous single nucleotide polymorphism (SNP), Val158Met within the Catechol-O-methyltransferase (COMT) gene has been associated with altered levels of cognition and memory performance in cognitively normal adults. This study aimed to investigate the independent and interactional effects of COMT Val158Met on cognitive performance. In particular, it was hypothesised that COMT Val158Met would modify the effect of neocortical Aβ-amyloid (Aβ) accumulation and carriage of the apolipoprotein E (APOE) ε4 allele on cognition in preclinical Alzheimer’s disease (AD). In 598 cognitively normal older adults with known neocortical Aβ levels, linear mixed modelling revealed no significant independent or interactional associations between COMT Val158Met and cognitive decline. These findings do not support previous associations between COMT Val158Met and cognitive performance and suggest this variant does not influence Aβ-amyloid or APOE ε4 driven cognitive decline in a well characterised cohort of cognitively normal older adults

En Attendant Centiloid

Aims: Test the robustness of a linear regression transformation of semiquantitative values from different Aβ tracers into a single continuous scale. Study Design: Retrospective analysis. Place and Duration of Study: PET imaging data acquired in Melbourne and Perth, Australia, between August 2006 and May 2014. Methodology: Aβ imaging in 633 participants was performed with four different radiotracers: flutemetamol (n=267), florbetapir (n=195), florbetaben (n=126) and NAV4694 (n=45). SUVR were generated with the methods recommended for each tracer, and classified as high (Aβ+) or low (Aβ-) based on their respective thresholds. Linear regression transformation based on reported head-to-head comparisons of each tracer with PiB was applied to each tracer result. Each tracer native classification was compared with the classification derived from the transformed data into PiB-like SUVR units (or BeCKeT: Before the Centiloid Kernel Transformation) using 1.50 as a cut-off. Results: Misclassification after transformation to PiB-like SUVR compared to native classification was extremely low with only 3/267 (1.1%) of flutemetamol, 1/195 (0.5%) of florbetapir, 1/45 (2.2%) of NAV4694, and 1/126 (0.8%) of florbetaben cases assigned into the wrong category. When misclassification occurred (Conclusion: While a definitive transformation into centesimal units is being established, application of linear regression transformations provide an interim, albeit robust, way of converting results from different Aβ imaging tracers into more familiar PiB-like SUVR units

Elementary sensory-motor transformations underlying olfactory navigation in walking fruit-flies.

Odor attraction in walking Drosophila melanogaster is commonly used to relate neural function to behavior, but the algorithms underlying attraction are unclear. Here, we develop a high-throughput assay to measure olfactory behavior in response to well-controlled sensory stimuli. We show that odor evokes two behaviors: an upwind run during odor (ON response), and a local search at odor offset (OFF response). Wind orientation requires antennal mechanoreceptors, but search is driven solely by odor. Using dynamic odor stimuli, we measure the dependence of these two behaviors on odor intensity and history. Based on these data, we develop a navigation model that recapitulates the behavior of flies in our apparatus, and generates realistic trajectories when run in a turbulent boundary layer plume. The ability to parse olfactory navigation into quantifiable elementary sensori-motor transformations provides a foundation for dissecting neural circuits that govern olfactory behavior