From clinics to methods and back: a tale of amyloid-PET quantification

The in-vivo assessment of cerebral amyloid load is taking a leading role in the early differential diagnosis of neurodegenerative diseases. With the hopefully near introduction of disease-modifying drugs, we expect a paradigm shift in the current diagnostic pathway with an unprecedented surge in the request of exams and detailed analysis

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Background: Structural MRI measures for monitoring Alzheimer's Disease (AD) progression are becoming instrumental in the clinical practice, and more so in the context of longitudinal studies. This investigation addresses the impact of four image analysis approaches on the longitudinal performance of the hippocampal volume. Methods: We present a hippocampal segmentation algorithm and validate it on a gold-standard manual tracing database. We segmented 460 subjects from ADNI, each subject having been scanned twice at baseline, 12-month and 24month follow-up scan (1.5T, T1 MRI). We used the bilateral hippocampal volume v and its variation, measured as the annualized volume change Λ=δv/year(mm3/y). Four processing approaches with different complexity are compared to maximize the longitudinal information, and they are tested for cohort discrimination ability. Reference cohorts are Controls vs. Alzheimer's Disease (CTRL/AD) and CTRL vs. Mild Cognitive Impairment who subsequently progressed to AD dementia (CTRL/MCI-co). We discuss the conditions on v and the added value of Λ in discriminating subjects. Results: The age-corrected bilateral annualized atrophy rate (%/year) were: -. 1.6 (0.6) for CTRL, -. 2.2 (1.0) for MCI-. nc, -. 3.2 (1.2) for MCI-. co and -. 4.0 (1.5) for AD. Combined (. v, Λ) discrimination ability gave an Area under the ROC curve (. auc). =. 0.93 for CTRL vs AD and auc=. 0.88 for CTRL vs MCI-. co. Conclusions: Longitudinal volume measurements can provide meaningful clinical insight and added value with respect to the baseline provided the analysis procedure embeds the longitudinal information

On the use of hyperbranched aramids as support of Pt nanoparticles

AbstractA hyperbranched (HB) aromatic polyamide (aramid) synthesized from A2 (p-phenylenediamine) + B3 (trimesic acid) reactants has been used as Pt nanoparticle support. TEM measurements verified the possibility to obtain a high metallic dispersion (MD) using H2PtCl6 as metal precursor. The amount of Pt retained by the polymer support turned out to be lower than the Pd loading deposited on the same HB aramid from a different metal precursor, i.e. PdCl2, under the same exchange and reduction conditions, namely by the procedure reported in a previous paper of ours [1]. Moreover, Pt nanoparticle diameters have been found to depend on the reducing agent used. As compared to bubbling H2, NaBH4 allowed obtaining of metal particles characterized by smaller dimensions

The Free and Cued Selective Reminding Test: Discriminative Values in a Naturalistic Cohort

Background: Neuropsychological assessment is still the basis for the first evaluation of patients with cognitive complaints. The Free and Cued Selective Reminding Test (FCSRT) generates several indices that could have different accuracy in the differential diagnosis between Alzheimer's disease (AD) and other disorders. Objective: In a consecutive series of naturalistic patients, the accuracy of the FCSRT indices in differentiating patients with either mild cognitive impairment (MCI) due to AD or AD dementia from other competing conditions was evaluated. Methods: We evaluated the accuracy of the seven FCSRT indices in differentiating patients with AD from other competing conditions in 434 consecutive outpatients, either at the MCI or at the early dementia stage. We analyzed these data through the receiver operating characteristics curve, and we then generated the odds-ratio map of the two indices with the best discriminative value between pairs of disorders. Results: The immediate and the delayed free total recall, the immediate total recall, and the index of sensitivity of cueing were the most useful indices and allowed to distinguish AD from dementia with Lewy bodies and psychiatric conditions with very high accuracy. Accuracy was instead moderate in distinguishing AD from behavioral variant frontotemporal dementia, vascular cognitive impairment, and other conditions. Conclusion: By using odd-ratio maps and comparison-customized cut-off scores, we confirmed that the FCSRT represents a useful tool to characterize the memory performance of patients with MCI and thus to assist the clinician in the diagnosis process, though with different accuracy values depending on the clinical hypothesis

Halpha rotation curves: the soft core question

We present high resolution Halpha rotation curves of 4 late-type dwarf galaxies and 2 low surface brightness galaxies (LSB) for which accurate HI rotation curves are available from the literature. Observations are carried out at Telescopio Nazionale Galileo (TNG). For LSB F583-1 an innovative dispersing element was used, the Volume Phase Holographic (VPH) with a dispersion of about 0.35 A/pxl. We find good agreement between the Halpha data and the HI observations and conclude that the HI data for these galaxies suffer very little from beam smearing. We show that the optical rotation curves of these dark matter dominated galaxies are best fitted by the Burkert profile. In the centers of galaxies, where the N-body simulations predict cuspy cores and fast rising rotation curves, our data seem to be in better agreement with the presence of soft cores.Comment: Accepted for Publication in ApJ with minor changes require

effects of three different diets on the fatty acid profile and sensory properties of fresh pecorino cheese primo sale

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Patterns of amyloid accumulation in amyloid-negative cases

Amyloid staging models showed that regional abnormality occurs before global positivity. Several studies assumed that the trajectory of amyloid spread is homogeneous, but clinical evidence suggests that it is highly heterogeneous. We tested whether different amyloid-β (Aβ) patterns exist by applying clustering on negative scans and investigating their demographics, clinical, cognitive, and biomarkers correlates, and cognitive trajectories. 151 individuals from Geneva and Zurich cohorts with T1-MRI, negative Aβ positron emission tomography (PET,centiloid<12) and clinical assessment were included. N=123 underwent tau PET, and N=65 follow-up neuropsychological assessment. We performed k-means clustering using 33 Aβ regional Standardized Uptake Vales ratio. Demographics, clinical, cognitive, and biomarkers differences were investigated. Longitudinal cognitive changes by baseline cluster status were estimated using a linear mixed model. The cluster analysis identified two clusters: temporal predominant (TP) and cingulate predominant (CP). TP tau deposition was higher than CP. A trend for a higher cognitive decline in TP compared to CP was observed. This study suggests the existence of two Aβ deposition patterns in the earliest phases of Aβ accumulation, differently prone to tau pathology and cognitive decline

Correction to: The role of molecular imaging in the frame of the revised dementia with Lewy body criteria

In the article mentioned above all authors were assigned affiliation 14, which is wrong. Affiliation 14 belongs only to author Agostino Chiaravalloti

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones