Cerebral white matter status and resting state functional MRI.

White Matter (WM) is a pivotal component of the Central Nervous System (CNS), and its main role is the transmission of the neural impulses within the CNS and between CNS and Peripheral Nervous System (PNS). It is note from literature that changes in the WM affects the function of the CNS with effects on the higher neurological function, included cognition. Further, it has been theorized in the last decades that ageing-associated decline in higher neurological functions, in particular in the neurocognitive sphere, could be at least partly explained by the “disconnection” of the cortical areas of the brain due to the WM degeneration. Although standard “in-vivo” imaging biomarkers of WM integrity have not been validated yet for clinical purposes, several researches have demonstrated the correlation between different potential imaging biomarkers and WM integrity. The aim of the PhD project is to explore and better understanding the effects of WM status on the brain structure, networking and cognition. In particular, we designed three distinct explorative and cross-sectional studies; more specifically, we analyzed the effects of two Magnetic Resonance Imaging (MRI) markers of WM degeneration (the global Fractional Anisotropy (gFA) and the white matter hyperintensities burden (WMHb), respectively) on the brain activity measured with the Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) technique. The project was conducted by analyzing a human population of healthy subjects extracted from the public available dataset “Leipzig Study for Mind-Body-Emotion Interactions” (LEMON). The results of these studies have been published during the PhD course on three distinct international scientific papers

Volumetric analysis of carotid plaque components and cerebral microbleeds: a correlative study

PURPOSE: The purpose of this work was to explore the association between carotid plaque volume (total and the subcomponents) and cerebral microbleeds (CMBs). MATERIALS AND METHODS: Seventy-two consecutive (male 53; median age 64) patients were retrospectively analyzed. Carotid arteries were studied by using a 16-detector-row computed tomography scanner whereas brain was explored with a 1.5 Tesla system. CMBs were studied using a T2*-weighted gradient-recalled echo sequence. CMBs were classified as from absent (grade 1) to severe (grade 4). Component types of the carotid plaque were defined according to the following Hounsfield unit (HU) ranges: lipid less than 60 HU; fibrous tissue from 60 to 130 HU; calcification greater than 130 HU, and plaque volumes of each component were calculated. Each carotid artery was analyzed by 2 observers. RESULTS: The prevalence of CMBs was 35.3%. A statistically significant difference was observed between symptomatic (40%) and asymptomatic (11%) patients (P value = .001; OR = 6.07). Linear regression analysis demonstrated an association between the number of CMBs and the symptoms (P = .0018). Receiver operating characteristics curve analysis found an association between the carotid plaque subcomponents and CMBs (Az = .608, .621, and .615 for calcified, lipid, and mixed components, respectively), and Mann-Whitney test confirmed this association in particular for the lipid components (P value = .0267). CONCLUSIONS: Results of this study confirm the association between CMBs and symptoms and that there is an increased number of CMBs in symptomatic patients. Moreover, we found that an increased volume of the fatty component is associated with the presence and number of CMBs

Association between carotid artery and abdominal aortic aneurysm plaque

The correlation between AAA and carotid artery plaque is unknown and a common etiology and pathophysiology is suspected by some authors. The purpose of this work was to explore the association between the features of a) carotid artery plaque and b) abdominal aortic aneurysm (AAA) plaques using multi-detector-CT Angiography (MDCTA). Forty-eight (32 males; median age 72 years) patients studied using a 16-detectors CT scanner were retrospectively analyzed. A region of interest (ROI) ≥ 2 mm2 was used to quantify the HU value of the plaque by two readers independently. Inter-observer reproducibility was calculated and Pearson correlation analysis was performed. The Bland-Altman plots showed the inter-observer reproducibility to be good. The Pearson correlation was 0.224 (95 % CI = 0.071 to 0.48), without statistically significant association between HU measured in the carotid artery plaque and in the AAA plaques (p = 0.138); after exclusion of the calcified plaques from the analysis, the rho values resulted 0.494 (95 % CI = 0.187 to 0.713) with a statistically significant association (p = 0.003). In this study, we found an association between the features of the non calcific carotid plaque and the features of AAA plaque

A new system of authorship best assessment

Purpose:The standard bibliometric indexes ("m-quotient "H-," "H2-," "g-," "a-," "m-," and "r-" index) do not considered the research' position in the author list of the paper. We proposed a new methodology, System of Authorship Best Assessment (SABA), to characterize the scientific output based on authors' position. Material and Methods:Four classes S1A, S1B, S2A, and S2B include only papers where the researcher is in first, first/last, first/second/last, and first/second/second-last/last position respectively were used for the calculation of H-index and number of citations The system was tested with Noble prize winners controlled with researchers matched for H-index. The different in percentage between standard bibliometric index and S2B was calculated and compared. Results:The percentage differences in Noble prize winners between S2B-H-index versus Global H-index and number of citations is very lower comparing with control group (median 4.15% [adjusted 95% CI, 2.54-5.30] vs 9.00 [adjusted 95% CI, 7.16-11.84], p < 0.001; average difference 8.7% vs 20.3%). All different in percentage between standard bibliometric index and S2B except two (H2- and m-index) were significantly lower among Noble prize compared with control group. Conclusion:The SABA methodology better weight the research impact by showing that for excellent profiles the S2B is similar to global values whereas for other researchers there is a significant difference

Clinical neuroimaging markers of response to treatment in mood disorders.

Mood disorders (MD) are important and frequent psychiatric illness. The management of patients affected by these conditions represents an important factor of disability as well as a significant social and economic burden. The "in-vivo" studies can help researchers to understand the first developmental events of the pathology and to identify the molecular and non-molecular targets of therapies. However, they have strong limitations due to the fact that human brain circuitry can not be reproduced in animal models. In addition, these neural pathways are difficult to be selectively studied with the modern imaging (such as Magnetic Resonance and Positron Emitted Tomography/Computed Tomography) and non-imaging (such as electroencephalography, magnetoencephalography, transcranial magnetic stimulation and evoked potentials) methods. In comparison with other methods, the "in-vivo" imaging investigations have higher temporal and spatial resolution compared to the "in-vivo" non-imaging techniques. All these factors make difficult to fully understand the aetiology and pathophysiology of these disorders, and consequently hinder the analysis of the effects of pharmacological and non-pharmacological therapies, which have been demonstrated effective in clinical settings. In this review, we will focus our attention on the current state of the art of imaging in the assessment of treatment efficacy in MD. We will analyse briefly the actual classification of MD; then we will focus on the "in vivo" imaging methods used in research and clinical activity, the current knowledge about the neural models at the base of MD. Finally the last part of the review will focus on the analysis of the main markers of response to treatment

Review of imaging biomarkers for the vulnerable carotid plaque

Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. As a result of the rapid technological evolution in medical imaging, several important steps have been taken in the field of carotid plaque imaging allowing us to visualize the carotid atherosclerotic plaque and its composition in great detail. For computed tomography, magnetic resonance imaging, positron emission tomography, and ultrasound scan, evidence has accumulated on novel imaging-based markers that confer information on carotid plaque vulnerability, such as intraplaque hemorrhage and lipid-rich necrotic cores. In terms of the imaging-based identification of individuals at high risk of stroke, routine assessments of such imaging markers are the way forward for improving current clinical practice. The current review highlights the main characteristics of the vulnerable plaque indicating their role in the etiology of ischemic stroke as identified by intensive plaque imaging

Connectometry evaluation in patients undergoing carotid endarterectomy: an exploratory study.

This research investigated local brain connectivity changes following Carotid Endarterectomy (CEA) by connectometry. Seventeen subjects (15 males and 2 females, mean age 74.1 years), all eligible for CEA, were prospectively recruited in this exploratory study. On the same day within the week before the CEA, each patient underwent a cognitive evaluation with a Mini Mental State Examination (MMSE) and a Magnetic Resonance Imaging (MRI) exam that included a DTI sequence for the connectometry analysis. A second MMSE and the same MRI protocol were performed on follow-up, 3-6 months after CEA. The MMSE scores were analyzed using T-Student tests. The connectometry analysis was performed using a multiple regression model to consider the effect of CEA, choosing three different T-score threshold (T-threshold) values (1, 2 and 3). Results were considered statistically valid for p value adjusted for False Discovery Rate (p-FDR) < 0.05. Comparison of pre-CEA and post-CEA MMSE scores showed improvement of MMSE scores after CEA. Connectometry analysis revealed no areas of statistically significant increased connectivity related to CEA for T-threshold value = 1 and 2, but showed statistically significant increase of connectivity after CEA in both cerebellar hemispheres and corpus callosum for T-threshold value = 3 (p-FDR = 0.0106667). The network property analysis showed improved small worldness (2.14%), clustering coefficient (1.64%), local (1.94%) and global efficiency (0.56%), and reduced characteristic path length (-0.52%) after CEA. These results suggest that CEA is associated both with cognitive performance improvement and changes in interhemispheric local connectivity in the corpus callosum and cerebellum

Safety and efficacy of direct-acting antivirals in transfusion-dependent thalassemic patients with chronic hepatitis C

Background: Hepatitis C virus (HCV) infection is a major cause of liver-related morbidity and mortality among thalassemic patients. New treatments based on direct-acting antivirals (DAAs) are highly effective and well-tolerated by patients; nonetheless, they have not been studied in thalassemic populations. In this study, we evaluated the safety and efficacy of these treatments in a cohort of Sardinian thalassemic patients with chronic HCV infection. Methods: We consecutively recruited thalassemic patients with HCV infection, who were eligible for DAA therapy at 3 liver units. Different drug combinations, depending on HCV genotype and hepatic disease severity, were used according to the current guidelines. Sustained virological response was assessed at 12 weeks posttreatment. Data regarding the side effects and transfusion requirements were also collected. Results: We recruited 49 patients, including 29 males (59.2%), with the mean age of 43 years (genotype 1, 55.1%). Twenty-one (42.9%) patients had a history of interferon-based treatment. Cirrhosis was detected in 28 (57.1%) patients; only 1 patient had ascites and hypoalbuminemia (Child-Pugh B7). On the other hand, 35 (71.4%) patients received a sofosbuvir-based regimen. Ribavirin treatment was reported in 26 (53.1%) cases. All the patients were followed-up for at least 12 weeks after therapy, and sustained virological response was observed in 98% of the patients. No treatment discontinuation was required due to adverse events. The most common side effects included fatigue (24.5%), headache (10.2%), and anaemia (77%), requiring further blood transfusion in patients receiving ribavirin. Conclusions: This prospective study showed that DAAs are safe and effective agents in thalassemic patients with advanced liver fibrosis, regardless of previous antiviral treatment responses

Predictors of long-term response to abiraterone in patients with metastastic castration-resistant prostate cancer: a retrospective cohort study

We aimed to identify clinical predictors of long-term response to abiraterone (defined as &gt;12 months drug exposure) in a retrospective cohort of metastatic castration-resistant prostate cancer patients treated in post-docetaxel setting at 24 Italian centers. The Cox proportional hazards model was used to analyze the association between clinical features and the duration of drug exposure. Results were expressed as hazard ratios (HR) with associated 95% confidence intervals (CI). A total of 143 patients met the inclusion criteria. Their median age was 73 years, median Gleason score 8 and median abiraterone exposure 20 months. At the univariate analysis, a significant correlation with the duration of abiraterone exposure was found for Gleason score (HR 0.82, 95% CI 0.71-0.96; p=0.012), PSA (HR 1.10, 95% CI 1.03-1.18; p=0.08) and lactic dehydrogenase levels (HR 1.22, 95% CI 1.02-1.46; p=0.027), while the association between lower alkaline phosphatase levels and treatment duration was marginally significant (HR 1.07, 95% CI 0.99-1.16; p=0.074). Only PSA and Gleason score were predictive of long-term treatment duration in the multivariate analysis. No other clinical factors resulted to be predictive of sustained response to abiraterone, including metastatic disease at diagnosis and visceral disease, suggesting that all subgroups of patients may derive a substantial clinical benefit from abiraterone treatment. These findings need to be validated in prospective, larger studies

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors