Optimisation of arterial spin labelling using bayesian experimental design

Large-scale neuroimaging studies often use multiple individual imaging contrasts. Due to the finite time available for imaging,there is intense competition for the time allocated to the individual modalities; thus it is crucial to maximise the utility of each method given the resources available. Arterial Spin Labelled (ASL) MRI often forms part of such studies. Measuring perfusion of oxygenated blood in the brain is valuable for several diseases,but quantification using multiple inversion time ASL is time-consuming due to poor SNR and consequently slow acquisitions. Here,we apply Bayesian principles of experimental design to clinical-length ASL acquisitions,resulting in significant improvements to perfusion estimation. Using simulations and experimental data,we validate this approach for a five-minute ASL scan. Our design procedure can be constrained to any chosen scan duration,making it well-suited to improve a variety of ASL implementations. The potential for adaptation to other modalities makes this an attractive method for optimising acquisition in the time-pressured environment of neuroimaging studies

A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience

Mobile Phone and Wearable Sensor-Based mHealth Approach for Psychiatric Disorders and Symptoms : Systematic Review and Link to the m-RESIST Project

Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration. Objective: To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy. Methods: A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied. Results: Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression. Conclusions: Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.Peer reviewe

Predictors of nonfetal reinfarction in survivors of myocardial infarction after thrombolysis Results of the gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico (GISSI-2) data base

AbstractObjectives. This study was designed to reassess the prediction of recurrent nonfatal myocardial infarction in patients recovering from acute myocardial infarction after thrombolysis.Background. Recurrent nonfatal myocardial infarction is a strong and independent predictor of subsequent mortality. Current knowledge of risk factors for nonfatal reinfarction is still largely based on data gathered before the advent of thrombolysis. Thus, this prospective study was planned to identify harbingers of nonfatal reinfarction in the postinfarction patients of the multicenter Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico (GISSI-2) trial.Methods. Predictors of nonfatal reinfarction at 6 months were analyzed by multivariate technique (Cox model) in 8,907 GISSI-2 survivors of myocardial infarction with clinical follow-up, relying on a set of prespecified variables reflecting residual ischemia, left ventricular failure or dysfunction, complex ventricular arrhythmias, comorbidity as well as demographic and historical factors.Results. The postdischarge to 6-month incidence rate of nonfetal reinfarction was 2.5%. Independent predictors of nonfatal reinfarction were cardiac ineligibility for exercise test (relative risk 2.97, 95% confidence interval [CI] 1.98 to 4.45), previous myocardial infarction (relative risk 1.70, 95% CI 1.22 to 2.36) and angina at follow-up (relative risk 1.50, 95% CI 1.10 to 2.04). On further multivariate analysis, performed in 6,580 patients with both echocardiographic and electrocardiographic monitoring data available, a history of angina emerged as an additional risk predictor (relative risk 1.58, 95% CI 1.10 to 2.25).Conclusions. The 6-month incidence of nonfatal reinfarction is rather low in survivors of myocardial infarction after thrombolysis. Cardiac ineligibility for exercise testing and a history of coronary artery disease are risk predictors. Recurrent nonfatal infarction is not predictable by qualitative variables reflecting residual ischemia, except by postdischarge angina. Prediction of nonfatal reinfarction appears less accurate than prediction of mortality, as almost 50% of reinfarctions occur in patients without any of the identified risk factors

Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson’s disease

Objectives Firstly, to identify subthalamic region stimulation clusters that predict maximum improvement in rigidity, bradykinesia and tremor, or emergence of side-effects; and secondly, to map-out the cortical fingerprint, mediated by the hyperdirect pathways which predict maximum efficacy. Methods High angular resolution diffusion imaging in twenty patients with advanced Parkinson’s disease was acquired prior to bilateral subthalamic nucleus deep brain stimulation. All contacts were screened one-year from surgery for efficacy and side-effects at different amplitudes. Voxel-based statistical analysis of volumes of tissue activated models was used to identify significant treatment clusters. Probabilistic tractography was employed to identify cortical connectivity patterns associated with treatment efficacy. Results All patients responded well to treatment (46% mean improvement off medication UPDRS-III [p<0.0001]) without significant adverse events. Cluster corresponding to maximum improvement in tremor was in the posterior, superior and lateral portion of the nucleus. Clusters corresponding to improvement in bradykinesia and rigidity were nearer the superior border in a further medial and posterior location. The rigidity cluster extended beyond the superior border to the area of the zona incerta and Forel-H2 field. When the clusters where averaged, the coordinates of the area with maximum overall efficacy was X=-10(-9.5), Y=-13(-1) and Z=-7(-3) in MNI(AC-PC) space. Cortical connectivity to primary motor area was predictive of higher improvement in tremor; whilst that to supplementary motor area was predictive of improvement in bradykinesia and rigidity; and connectivity to prefrontal cortex was predictive of improvement in rigidity. Interpretation These findings support the presence of overlapping stimulation sites within the subthalamic nucleus and its superior border, with different cortical connectivity patterns, associated with maximum improvement in tremor, rigidity and bradykinesia

Longitudinal evaluation of proton magnetic resonance spectroscopy metabolites as biomarkers in Huntington’s disease

Proton Magnetic resonance spectroscopy (1H-MRS) is a non-invasive method of exploring cerebral metabolism. In Huntington’s disease, altered 1H-MRS-determined concentrations of several metabolites have been described; however, findings are often discrepant and longitudinal studies are lacking. 1H-MRS metabolites may represent a source of biomarkers, thus their relationship with established markers of disease progression require further exploration to assess prognostic value and elucidate pathways associated with neurodegeneration. In a prospective single-site controlled cohort study with standardised collection of CSF, blood, phenotypic and volumetric imaging data, we used 3T 1H-MRS in conjunction with the linear combination of model spectra method to quantify seven metabolites (total n-acetylaspartate, total creatine, total choline, myo-inositol, GABA, glutamate and glutathione) in the putamen of 59 participants at baseline (15 healthy controls, 15 premanifest and 29 manifest Huntington’s disease gene expansion carriers) and 48 participants at 2-year follow-up (12 healthy controls, 13 premanifest and 23 manifest Huntington’s disease gene expansion carriers). Intergroup differences in concentration and associations with CSF and plasma biomarkers; including neurofilament light chain and mutant Huntingtin, volumetric imaging markers; namely whole brain, caudate, grey matter and white matter volume, measures of disease progression and cognitive decline, were assessed cross-sectionally using generalized linear models and partial correlation. We report no significant groupwise differences in metabolite concentration at baseline but found total creatine and total n-acetylaspartate to be significantly reduced in manifest compared with premanifest participants at follow-up. Additionally, total creatine and myo-inositol displayed significant associations with reduced caudate volume across both time points in gene expansion carriers. Although relationships were observed between 1H-MRS metabolites and biofluid measures, these were not consistent across time points. To further assess prognostic value, we examined whether baseline 1H-MRS values, or rate of change, predicted subsequent change in established measures of disease progression. Several associations were found but were inconsistent across known indicators of disease progression. Finally, longitudinal mixed effects models revealed glutamine + glutamate to display a slow linear decrease over time in gene expansion carriers. Altogether, our findings show some evidence of reduced total n-acetylaspartate and total creatine as the disease progresses and cross-sectional associations between select metabolites, namely total creatine and myo-inositol, and markers of disease progression, potentially highlighting the proposed roles of neuroinflammation and metabolic dysfunction in disease pathogenesis. However, the absence of consistent group differences, inconsistency between baseline and follow-up, and lack of clear longitudinal change suggests that 1H-MRS metabolites have limited potential as Huntington’s disease biomarkers

The emerging role of cancer nanotechnology in the panorama of sarcoma

In the field of nanomedicine a multitude of nanovectors have been developed for cancer application. In this regard, a less exploited target is represented by connective tissue. Sarcoma lesions encompass a wide range of rare entities of mesenchymal origin affecting connective tissues. The extraordinary diversity and rarity of these mesenchymal tumors is reflected in their classification, grading and management which are still challenging. Although they include more than 70 histologic subtypes, the first line-treatment for advanced and metastatic sarcoma has remained unchanged in the last fifty years, excluding specific histotypes in which targeted therapy has emerged. The role of chemotherapy has not been completely elucidated and the outcomes are still very limited. At the beginning of the century, nano-sized particles clinically approved for other solid lesions were tested in these neoplasms but the results were anecdotal and the clinical benefit was not substantial. Recently, a new nanosystem formulation NBTXR3 for the treatment of sarcoma has landed in a phase 2-3 trial. The preliminary results are encouraging and could open new avenues for research in nanotechnology. This review provides an update on the recent advancements in the field of nanomedicine for sarcoma. In this regard, preclinical evidence especially focusing on the development of smart materials and drug delivery systems will be summarized. Moreover, the sarcoma patient management exploiting nanotechnology products will be summed up. Finally, an overlook on future perspectives will be provided