Quantitative assessment of training effects using EksoGT® exoskeleton in Parkinson's disease patients: A randomized single blind clinical trial.

Background: Gait alterations are among the most disabling motor-symptoms associated with Parkinson's Disease (PD): reduced stride length, stride velocity and lower limb joint range of motion are hallmarks of parkinsonian gait. Research focusing on optimal functional rehabilitation methods has been directed towards powered lower-limb exoskeletons which combines the advantages delivered from the grounded robotic devices with the ability to train the patient in a real-world environment. As gait involves both central (CNS) and peripheral nervous systems (PNS), targeted rehabilitation must restore not only mechanics but also neurophysiological gait patterns. Methods: Two cohorts of subjects will be enrolled and equally distributed between one group (n = 25) who will undergo a functional kinematic therapy, and one group (n = 25) who will undergo an overground wearable-exoskeleton training. Participants are evaluated at three time points: before the therapy (T0), after the therapy (T1), 4-weeks after T1 (T2). Comprehensive gait analysis and surface electromyography will be combined into neuromusculoskeletal modelling to determine modifications at the PNS level. Functional magnetic resonance imaging coupled with electroencephalography will be used to determine modifications at the CNS level. Conclusion: The findings of the proposed trial will likely give substantial solutions for the management of gait and postural disorders in PD where valid interventions are lacking. The coupling of movement evaluation, which assesses neuromuscular and biomechanical features, with neurological data, will better define the impact of the therapy on the relationship between PD motor alterations and brain activity. This will provide an active treatment that is personalized and shared to large populations.

Multishell Diffusion MRI-Based Tractography of the Facial Nerve in Vestibular Schwannoma.

BACKGROUND AND PURPOSE: Tractography of the facial nerve based on single-shell diffusion MR imaging is thought to be helpful before surgery for resection of vestibular schwannoma. However, this paradigm can be vitiated by the isotropic diffusion of the CSF, the convoluted path of the facial nerve, and its crossing with other bundles. Here we propose a multishell diffusion MR imaging acquisition scheme combined with probabilistic tractography that has the potential to provide a presurgical facial nerve reconstruction uncontaminated by such effects. MATERIALS AND METHODS: Five patients scheduled for vestibular schwannoma resection underwent multishell diffusion MR imaging (b-values = 0, 300, 1000, 2000 s/mm2). Facial nerve tractography was performed with a probabilistic algorithm and anatomic seeds located in the brain stem, cerebellopontine cistern, and internal auditory canal. A single-shell diffusion MR imaging (b-value = 0, 1000 s/mm2) subset was extrapolated from the multishell diffusion MR imaging data. The quality of the facial nerve reconstruction based on both multishell diffusion MR imaging and single-shell diffusion MR imaging sequences was assessed against intraoperative videos recorded during the operation. RESULTS: Single-shell diffusion MR imaging-based tractography was characterized by failures in facial nerve tracking (2/5 cases) and inaccurate facial nerve reconstructions displaying false-positives and partial volume effects. In contrast, multishell diffusion MR imaging-based tractography provided accurate facial nerve reconstructions (4/5 cases), even in the presence of ostensibly complex patterns. CONCLUSIONS: In comparison with single-shell diffusion MR imaging, the combination of multishell diffusion MR imaging-based tractography and probabilistic algorithms is a more valuable aid for surgeons before vestibular schwannoma resection, providing more accurate facial nerve reconstructions, which may ultimately improve the postsurgical patient's outcome.

High prevalence of erectile dysfunction in diabetes: a systematic review and meta-analysis of 145 studies.

Erectile dysfunction may be common among men with diabetes, but its prevalence is still debated. We aimed to assess the relative prevalence of erectile dysfunction in diabetes searching major databases from inception to November 2016 for studies reporting erectile dysfunction in men with Type 1 and Type 2 diabetes mellitus. We conducted a meta-analysis of the prevalence [and 95% confidence intervals (95% CIs)] of erectile dysfunction in diabetes compared with healthy controls, calculating the relative odds ratios (ORs) and 95% CIs. A random effect model was applied. From 3747 initial hits, 145 studies were included representing 88 577 men (age: 55.8 ± 7.9 years). The prevalence of erectile dysfunction in diabetes overall was 52.5% (95% CI, 48.8 to 56.2) after adjusting for publication bias, and 37.5%, 66.3% and 57.7% in Type 1, Type 2 and both types of diabetes, respectively (P for interaction < 0.0001). The prevalence of erectile dysfunction was highest in studies using the Sexual Health Inventory for Men (82.2%, 17 studies, P for interaction < 0.0001). Studies with a higher percentage of people with hypertension moderated our results (beta = 0.03; 95% CI, 0.008 to 0.040; P = 0.003; R2  = 0.00). Compared to healthy controls (n = 5385) men with diabetes (n = 863) were at increased odds of having erectile dysfunction (OR 3.62; 95% CI, 2.53 to 5.16; P < 0.0001; I2  = 67%, k = 8). Erectile dysfunction is common in diabetes, affecting more than half of men with the condition and with a prevalence odds of approximately 3.5 times more than controls. Our findings suggest that screening and appropriate intervention for men with erectile dysfunction is warranted.

Heterogeneity of Cortical Lesion Susceptibility Mapping in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Quantitative susceptibility mapping has been used to characterize iron and myelin content in the deep gray matter of patients with multiple sclerosis. Our aim was to characterize the susceptibility mapping of cortical lesions in patients with MS and compare it with neuropathologic observations. MATERIALS AND METHODS: The pattern of microglial activation was studied in postmortem brain tissues from 16 patients with secondary-progressive MS and 5 age-matched controls. Thirty-six patients with MS underwent 3T MR imaging, including 3D double inversion recovery and 3D-echo-planar SWI. RESULTS: Neuropathologic analysis revealed the presence of an intense band of microglia activation close to the pial membrane in subpial cortical lesions or to the WM border of leukocortical cortical lesions. The quantitative susceptibility mapping analysis revealed 131 cortical lesions classified as hyperintense; 33, as isointense; and 84, as hypointense. Quantitative susceptibility mapping hyperintensity edge found in the proximity of the pial surface or at the white matter/gray matter interface in some of the quantitative susceptibility mapping-hyperintense cortical lesions accurately mirrors the microglia activation observed in the neuropathology analysis. CONCLUSIONS: Cortical lesion susceptibility maps are highly heterogeneous, even at individual levels. Quantitative susceptibility mapping hyperintensity edge found in proximity to the pial surface might be due to the subpial gradient of microglial activation.

A Variational Bayesian inference method for parametric imaging of PET data.

In dynamic Positron Emission Tomography (PET) studies, compartmental models provide the richest information on the tracer kinetics of the tissue. Inverting such models at the voxel level is however quite challenging due to the low signal-to-noise ratio of the time activity curves. In this study, we propose the use of a Variational Bayesian (VB) approach to efficiently solve this issue and thus obtain robust quantitative parametric maps. VB was adapted to the non-uniform noise distribution of PET data. Moreover, we propose a novel hierarchical scheme to define the model parameter priors directly from the images in case such information are not available from the literature, as often happens with new PET tracers. VB was initially tested on synthetic data generated using compartmental models of increasing complexity, providing accurate (%bias<2%±2%, root mean square error<15%±5%) parameter estimates. When applied to real data on a paradigmatic set of PET tracers (L-[1-11C]leucine, [11C]WAY100635 and [18F]FDG), VB was able to generate reliable parametric maps even in presence of high noise in the data (unreliable estimates<11%±5%).

Epilepsy in multiple sclerosis: The role of temporal lobe damage.

BACKGROUND: Although temporal lobe pathology may explain some of the symptoms of multiple sclerosis (MS), its role in the pathogenesis of seizures has not been clarified yet. OBJECTIVES: To investigate the role of temporal lobe damage in MS patients suffering from epilepsy, by the application of advanced multimodal 3T magnetic resonance imaging (MRI) analysis. METHODS: A total of 23 relapsing remitting MS patients who had epileptic seizures (RRMS/E) and 23 disease duration matched RRMS patients without any history of seizures were enrolled. Each patient underwent advanced 3T MRI protocol specifically conceived to evaluate grey matter (GM) damage. This includes grey matter lesions (GMLs) identification, evaluation of regional cortical thickness and indices derived from the Neurite Orientation Dispersion and Density Imaging model. RESULTS: Regional analysis revealed that in RRMS/E, the regions most affected by GMLs were the hippocampus (14.2%), the lateral temporal lobe (13.5%), the cingulate (10.0%) and the insula (8.4%). Cortical thinning and alteration of diffusion metrics were observed in several regions of temporal lobe, in insular cortex and in cingulate gyrus of RRMS/E compared to RRMS ( p< 0.05 for all comparisons). CONCLUSIONS: Compared to RRMS, RRMS/E showed more severe damage of temporal lobe, which exceeds what would be expected on the basis of the global GM damage observed.

Automatic localization of cerebral cortical malformations using fractal analysis.

Malformations of cortical development (MCDs) encompass a variety of brain disorders affecting the normal development and organization of the brain cortex. The relatively low incidence and the extreme heterogeneity of these disorders hamper the application of classical group level approaches for the detection of lesions. Here, we present a geometrical descriptor for a voxel level analysis based on fractal geometry, then define two similarity measures to detect the lesions at single subject level. The pipeline was applied to 15 normal children and nine pediatric patients affected by MCDs following two criteria, maximum accuracy (WACC) and minimization of false positives (FPR), and proved that our lesion detection algorithm is able to detect and locate abnormalities of the brain cortex with high specificity (WACC = 85%, FPR = 96%), sensitivity (WACC = 83%, FPR = 63%) and accuracy (WACC = 85%, FPR = 90%). The combination of global and local features proves to be effective, making the algorithm suitable for the detection of both focal and diffused malformations. Compared to other existing algorithms, this method shows higher accuracy and sensitivity.

Parametric imaging of ¹8F-fluoro-3-deoxy-3-L-fluorothymidine PET data to investigate tumour heterogeneity.

PURPOSE: [(18)F]Fluoro-3'-deoxy-3'-L-fluorothymidine ([(18)F]FLT) is a tissue proliferation marker which has been widely validated as a tumour-specific imaging tracer for PET. [(18)F]FLT uptake in breast cancer is generally quantified at the region level or through first-order statistical descriptors (mean or maximum value), approaches that ignore the known complexity and heterogeneity of cancer tissues. Our aims were: (1) to validate a robust and reproducible voxel-wise approach to the quantification of [(18)F]FLT PET data in breast cancer patients, and (2) to exploit the entire distribution of the [(18)F]FLT retention estimates and their variability in the tumour region for the prediction of early treatment response. METHODS: The dataset was derived from 15 patients with stage II-IV breast cancer, scanned twice before chemotherapy and once 1 week after therapy. Using RECIST criteria (after 60 days) nine patients were categorized as responders or nonresponders to treatment. Kinetic modelling (compartmental modelling, Patlak analysis and spectral analysis with iterative filter), tissue-to-plasma ratio and standardized uptake value were applied at the voxel level. Test-retest estimates were used to assess reproducibility and reliability of the [(18)F]FLT uptake values before and after therapy for responder/nonresponder prediction. RESULTS: All the methods provided a measure of [(18)F]FLT uptake that was reliable and reproducible with ICC >0.94. Moreover, a very strong correlation was found among the methods (R (2) > 0.81). All the methods provided a limited number of outliers (<20 % in tumour), with the exception of compartmental modelling (>25 %) which was therefore excluded from the prediction analysis. Differences between before and after therapy in mean voxel-wise uptake in tumour did not allow a complete responder/nonresponder classification. In contrast, considering the full estimate distributions within the tumour (changes in median and mode between before and after therapy) improved therapy response for all the analysed methods. CONCLUSION: We showed that kinetic modelling (Patlak and spectral analysis with iterative filter) applied voxel-wise allows appropriate [(18)F]FLT uptake estimation in breast cancer with good reproducibility. Notably, this study indicated that a more comprehensive statistical investigation could improve tumour characterization and prediction of treatment response.

Modelling hemodynamic response function in epilepsy.

OBJECTIVE: Electroencephalography and functional magnetic resonance imaging (fMRI) can be combined to noninvasively map abnormal brain activation elicited by epileptic processes. A major aim was to investigate the impact of a subject-specific hemodynamic response function (HRF) to describe the differences across patients versus the use of a standard model. METHODS: We developed and applied on simulated and real data a method designed to choose optimum HRF model for identifying fMRI activation maps. In simulation, the ability of five models to reproduce data was assessed: four standard and an individual-based HRF model (ibHRF). In clinical data, drug-resistant epileptic patients underwent fMRI to investigate hemodynamic responses evoked by interictal activity. RESULTS: When data are simulated with models different from the standard ones, the results obtained with ibHRF are superior to those obtained with the standard HRFs. Results on real data indicate an increase in extent and degree of activation with the ibHRF in comparison of the results obtainable using standard HRFs. CONCLUSIONS: The use of the same HRF in all patients is inappropriate and resolves in biased extension of the activation maps. SIGNIFICANCE: The new method could represent an useful diagnostic tool for other clinical studies that may be biased because of misspecification of HRF.

Multi-scale hierarchical approach for parametric mapping: assessment on multi-compartmental models.

This paper investigates a new hierarchical method to apply basis function to mono- and multi-compartmental models (Hierarchical-Basis Function Method, H-BFM) at a voxel level. This method identifies the parameters of the compartmental model in its nonlinearized version, integrating information derived at the region of interest (ROI) level by segmenting the cerebral volume based on anatomical definition or functional clustering. We present the results obtained by using a two tissue-four rate constant model with two different tracers ([(11)C]FLB457 and [carbonyl-(11)C]WAY100635), one of the most complex models used in receptor studies, especially at the voxel level. H-BFM is robust and its application on both [(11)C]FLB457 and [carbonyl-(11)C]WAY100635 allows accurate and precise parameter estimates, good quality parametric maps and a low percentage of voxels out of physiological bound (<8%). The computational time depends on the number of basis functions selected and can be compatible with clinical use (~6h for a single subject analysis). The novel method is a robust approach for PET quantification by using compartmental modeling at the voxel level. In particular, different from other proposed approaches, this method can also be used when the linearization of the model is not appropriate. We expect that applying it to clinical data will generate reliable parametric maps.

Multi-Scale hierarchical generation of PET parametric maps: application and testing on a [11C]DPN study.

We propose a general approach to generate parametric maps. It consists in a multi-stage hierarchical scheme where, starting from the kinetic analysis of the whole brain, we then cascade the kinetic information to anatomical systems that are akin in terms of receptor densities, and then down to the voxel level. A-priori classes of voxels are generated either by anatomical atlas segmentation or by functional segmentation using unsupervised clustering. Kinetic properties are transmitted to the voxels in each class using maximum a posteriori (MAP) estimation method. We validate the novel method on a [11C]diprenorphine (DPN) test-retest data-set that represents a challenge to estimation given [11C]DPN's slow equilibration in tissue. The estimated parametric maps of volume of distribution (VT) reflect the opioid receptor distributions known from previous [11C]DPN studies. When priors are derived from the anatomical atlas, there is an excellent agreement and strong correlation among voxel MAP and ROI results and excellent test-retest reliability for all subjects but one. Voxel level results did not change when priors were defined through unsupervised clustering. This new method is fast (i.e. 15 min per subject) and applied to [11C]DPN data achieves accurate quantification of VT as well as high quality VT images. Moreover, the way the priors are defined (i.e. using an anatomical atlas or unsupervised clustering) does not affect the estimates.

Effect of median-nerve electrical stimulation on BOLD activity in acute ischemic stroke patients.

OBJECTIVE: To investigate blood oxygenation level-dependent (BOLD) activation during somatosensory electrical stimulation of the median nerve in acute stroke patients and to determine its correlation with ischemic damage and clinical recovery over time. METHODS: Fourteen acute stroke patients underwent functional magnetic resonance imaging (fMRI) during contralesional median-nerve electrical stimulation 12-48 h after stroke. Findings were then validated by diffusion tensor imaging (DTI) and motor evoked potential by transcranial magnetic stimulation (TMS). RESULTS: Poor clinical recovery at three months was noted in four patients with no activation in the early days after stroke, whereas good clinical recovery was observed in eight patients with a normal activation pattern in the primary sensory motor area in the acute phase. In two patients BOLD activation correlated weakly with clinical recovery. Findings from TMS and DTI partially correlated with clinical recovery and functional scores. CONCLUSIONS: Clinically relevant insights into the "functional reserve" of stroke patients gained with peripheral nerve stimulation during fMRI may carry prognostic value already in the acute period of a cerebrovascular accident. SIGNIFICANCE: BOLD activation maps could provide insights into the functional organization of the residual systems and could contribute to medical decision making in neurological and rehabilitative treatment.

Human papilloma virus in the sperm cryobank: an emerging problem?

Human papilloma virus (HPV) infection is very common worldwide, but the actual incidence and significance of HPV infection in sperm are poorly understood. In this study, we evaluated the presence of HPV in spermatozoa from thawed semen samples previously stored in our sperm bank. We performed polymerase chain reaction and in situ hybridization for HPV detection in cryovials belonging to 98 oncology patients and in 60 semen samples from healthy controls. Statistical analysis was performed by two-tailed Student's t-test and Fisher's exact test. The frequency of HPV semen infection was 6.1% in thawed cryovials from patients and 3.3% in semen samples from controls. Among the patients, four were found positive for high-risk HPV, one for medium-risk HPV and another for low-risk HPV. Patients had a significantly higher percentage of infected sperm than controls. In conclusion, this report shows the presence of HPV in sperm cells from cryovials of a sperm bank. It is still unclear if HPV-infected sperm are able to cross-contaminate cryovials and impair the outcome of assisted reproduction techniques or to infect partners. Further studies are needed to understand whether screening for HPV should be performed in all semen samples before sperm banking or before intra-cytoplasmic sperm injection procedures.

Identification of IVGTT minimal glucose model by nonlinear mixed-effects approaches.

Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares to each individual subject's data. Sometimes, parameter precision is not satisfactory, especially in "data poor" conditions. In this work, the use of population analysis through nonlinear-mixed effects models is evaluated and its performance tested against the parameter estimates obtained by the standard individual approach through weighted nonlinear least squares. In particular, we compared the performance of two likelihood approximation methods to estimate nonlinear mixed-effects model parameters, i.e. the first-order conditional estimation (FOCE) and the Laplace approximation (Laplace) methods. The results show that nonlinear mixed-effects population modeling using the FOCE approximation can be successfully used in order to accurately estimate individual minimal model parameters.

Kinetic modeling of [(18)F]FDG in skeletal muscle by PET: a four-compartment five-rate-constant model.

Various modeling strategies have been developed to convert regional [(18)F]fluorodeoxyglucose ([(18)F]FDG) concentration measured by positron emission tomography (PET) to a measurement of physiological parameters. However, all the proposed models have been developed and tested mostly for brain studies. The purpose of the present study is to select the most accurate model for describing [(18)F]FDG kinetics in human skeletal muscle. The database consists of basal and hyperinsulinemic-euglycemic studies performed in normal subjects. PET data were first analyzed by an input-output modeling technique (often called spectral analysis). These results provided guidelines for developing a compartmental model. A new model with four compartments and five rate constants (5K model) emerged as the best. By accounting for plasma and extracellular and intracellular kinetics, this model allows, for the first time, PET assessment of the individual steps of [(18)F]FDG kinetics in human skeletal muscle, from plasma to extracellular space to transmembrane transport into the cell to intracellular phosphorylation. Insulin is shown to affect transport and phosphorylation but not extracellular kinetics, with the transport step becoming the main site of control. The 5K model also allows definition of the domain of validity of the classic three-compartment three- or four-rate-constant models. These models are candidates for an investigative tool to quantitatively assess insulin control on individual metabolic steps in human muscle in normal and physiopathological states.

Direct measurement of the lumped constant for 2-deoxy-[1-(14)C]glucose in vivo in human skeletal muscle.

The lumped constant (LC) is used to convert the clearance rate of 2-deoxy-D-glucose (2-DG(CR)) to that of glucose (Glc(CR)). There are currently no data to validate the widely used assumption of an LC of 1.0 for human skeletal muscle. We determined the LC for 2-deoxy-[1-(14)C]glucose (2-DG) in 18 normal male subjects (age, 29+/- 2 yr; body mass index, 24.8+/-0.8 kg/m(2)) after an overnight fast and during physiological (1 mU x kg(-1) x min(-1) insulin infusion for 180 min) and supraphysiological (5 mU x kg(-1) x min(-1) insulin infusion for 180 min) hyperinsulinemic conditions. Normoglycemia was maintained with the euglycemic clamp technique. The LC was measured directly with the use of a novel triple tracer-based method. [3-(3)H]glucose, 2-[1-(14)C]DG, and [(12)C]mannitol (Man) were injected as a bolus into the brachial artery. The concentrations of [3-(3)H]glucose and 2-[1-(14)C]DG (dpm/ml plasma) and of Man (micromol/l) were determined in 50 blood samples withdrawn from the ipsilateral deep forearm vein over 15 min after the bolus injection. The LC was calculated by a formula involving blood flow calculated from Man and the Glc(CR) and 2-DG(CR). The LC averaged 1.26+/-0.08 (range 1.06-1.43), 1.15+/-0.05 (0.99-1.39), and 1.18+/-0.05 (0.97-1.37) under fasting conditions and during the 1 and 5 mU x kg(-1). min(-1) insulin infusions (not significant between the different insulin concentrations, mean LC = 1.2, P<0.01 vs. 1.0). We conclude that, in normal subjects, the LC for 2-DG in human skeletal muscle is constant over a wide range of insulin concentrations and averages 1. 2.

Evaluation of compartmental and spectral analysis models of [18F]FDG kinetics for heart and brain studies with PET.

Various models have been proposed to quantitate from [18F]-Fluoro-Deoxy-Glucose ([18F]FDG) positron emission tomography (PET) data glucose regional metabolic rate. We evaluate here four models, a three-rate constants (3K) model, a four-rate constants (4K) model, an heterogeneous model (TH) and a spectral analysis (SA) model. The data base consists of [18F]FDG dynamic data obtained in the myocardium and brain gray and white matter. All models were identified by nonlinear weighted least squares with weights chosen optimally. We show that: 1) 3K and 4K models are indistinguishable in terms of parsimony criteria and choice should be made on parameter precision and physiological plausibility; in the gray matter a more complex model than the 3K one is resolvable; 2) the TH model is resolvable in the gray but not in the white matter; 3) the classic SA approach has some unnecessary hypotheses built in and can be in principle misleading; we propose here a new SA model which is more theoretically sound; 4) this new SA approach supports the use of a 3K model in the heart with a 60 min experimental period; it also indicates that heterogeneity in the brain is modest in the white matter; 5) [18F]FDG fractional uptake estimates of the four models are very close in the heart, but not in the brain; 6) a higher than 60 min experimental time is preferable for brain studies.

Estimation of component and parameter distributions in spectral analysis.

A method is presented for estimating the distributions of the components and parameters determined with spectral analysis when it is applied to a single data set. The method uses bootstrap resampling to simulate the effect of noise on the computed spectrum and to correct for possible bias in the estimates. A number of bootstrap procedures are reviewed, and one is selected for application to the kinetic analysis of positron emission tomography dynamic studies. The technique is shown to require minimal assumptions about noise in the measurements, and its small sample properties are established through Monte-Carlo simulations. The advantages and limitations of spectral analysis with bootstrap resampling for deriving inferences for tracer kinetic modeling are illustrated through sample analyses of time-activity curves for [18F]fluorodeoxyglucose and [15O]-labeled water.