Effect of troxerutin in counteracting hyperglycemia-induced VEGF upregulation in endothelial cells: a new option to target early stages of diabetic retinopathy?

Diabetic retinopathy (DR), one of the most common complications of diabetes mellitus, is characterized by degeneration of retinal neurons and neoangiogenesis. Until today, the pharmacological approaches for DR are limited and focused on counteracting the end-stage of this neurodegenerative disease, therefore efforts should be carried out to discover novel pharmacological targets useful to prevent DR development. Hyperglycemia is a major risk factor for endothelial dysfunction and vascular complication, which subsequently may trigger neurodegeneration. We previously demonstrated that, in the rat retina, hyperglycemia activates a new molecular cascade implicating, up-stream, protein kinase C βII (PKC βII), which in turn leads to a higher expression of vascular endothelial growth factor (VEGF), via the mRNA-binding Hu-antigen R (HuR) protein. VEGF is a pivotal mediator of neovascularization and a well-known vasopermeability factor. Blocking the increase of VEGF via modulation of this cascade can thus represent a new pharmacological option to prevent DR progression. To this aim, proper in vitro models are crucial for drug discovery, as they allow to better identify promising effective molecules. Considering that endothelial cells are key elements in DR and that hyperglycemia triggers the PKCβII/HuR/VEGF pathway, we set up two distinct in vitro models applying two different stimuli. Namely, human umbilical vein endothelial cells were exposed to phorbol 12-myristate 13-acetate, which mimics diacylglycerol whose synthesis is triggered by diabetic hyperglycemia, while human retinal endothelial cells were treated with high glucose for different times. After selecting the optimal experimental conditions able to determine an increased VEGF production, in search of molecules useful to prevent DR development, we investigated the capability of troxerutin, an antioxidant flavonoid, to counteract not only the rise of VEGF but also the activation of the PKCβII/HuR cascade in both in vitro models. The results show the capability of troxerutin to hinder the hyperglycemia-induced increase in VEGF in both models through PKCβII/HuR pathway modulation. Further, these data confirm the key engagement of this cascade as an early event triggered by hyperglycemia to promote VEGF expression. Finally, the present findings also suggest the potential use of troxerutin as a preventive treatment during the early phases of DR.

Cardiac amyloidosis characterization by kinetic model fitting on [18F]florbetaben PET images

OBJECTIVE

To evaluate the feasibility of kinetic modeling-based approaches from [18F]-Flobetaben dynamic PET images as a non-invasive diagnostic method for cardiac amyloidosis (CA) and to identify the two AL- and ATTR-subtypes.

METHODS AND RESULTS

Twenty-one patients with diagnoses of CA (11 patients with AL-subtype and 10 patients with ATTR-subtype of CA) and 15 Control patients with no-CA conditions underwent PET/CT imaging after [18F]Florbetaben bolus injection. A two-tissue-compartment (2TC) kinetic model was fitted to time-activity curves (TAC) obtained from left ventricle wall and left atrium cavity ROIs to estimate kinetic micro- and macro-parameters. Combinations of kinetic parameters were evaluated with the purpose of distinguishing Control subjects and CA patients, and to correctly label the last ones as AL- or ATTR-subtype. Resulting sensitivity, specificity, and accuracy for Control subjects were: 0.87, 0.9, 0.89; as far as CA patients, the sensitivity, specificity, and accuracy were respectively 0.9, 1, and 0.97 for AL-CA patients and 0.9, 0.92, 0.97 for ATTR-CA patients.

CONCLUSION

Pharmacokinetic analysis based on a 2TC model allows cardiac amyloidosis characterization from dynamic [18F]Florbetaben PET images. Estimated model parameters allows to not only distinguish between Control subjects and patients, but also between AL- and ATTR-amyloid patients.

Cardiac amyloidosis detection by early bisphosphonate (99mTc-HMDP) scintigraphy

OBJECTIVE

To determine one or more indexes able to detect the presence of cardiac amyloidosis (CA) from planar scintigraphy images after injection of 99mTc-HMDP tracer and to identify the earliest acquisition time able to ensure an accurate diagnosis of amyloid transthyretin CA.

METHODS AND RESULTS

A total of 38 patients were included: 18 subjects with a final diagnosis of ATTR-CA and 20 controls. Dynamic planar images of the anterior thorax were acquired, starting at intravenous injection of ≈ 700 MBq of 99mTc-HMDP. From time/activity curves (TAC) of regions of interest such as heart, vascular region, right ribcage, and soft tissues, several indices were considered. From the analysis, it resulted that both TACHeart/Bone(t) and RIheart-bone(t), for t > 6 minutes, well distinguish ATTR-CA patients from controls subjects. This is confirmed by the area under curves (AUC) analysis giving AUC values =.9 at t ≅ 6 minutes and AUC ≅ 1 for t > 10 minutes.

CONCLUSIONS

The method proposed allows determining the presence of ATTR-CA, in an inexpensive manner both in terms of examination costs and time spent.

Occupational exposure to electromagnetic fields in magnetic resonance environment: an update on regulation, exposure assessment techniques, health risk evaluation, and surveillance

Magnetic resonance imaging (MRI) is one of the most-used diagnostic imaging methods worldwide. There are ∼50,000 MRI scanners worldwide each of which involves a minimum of five workers from different disciplines who spend their working days around MRI scanners. This review analyzes the state of the art of literature about the several aspects of the occupational exposure to electromagnetic fields (EMF) in MRI: regulations, literature studies on biological effects, and health surveillance are addressed here in detail, along with a summary of the main approaches for exposure assessment. The original research papers published from 2013 to 2021 in international peer-reviewed journals, in the English language, are analyzed, together with documents published by legislative bodies. The key points for each topic are identified and described together with useful tips for precise safeguarding of MRI operators, in terms of exposure assessment, studies on biological effects, and health surveillance.

Imaging Techniques as an Aid in the Early Detection of Cardiac Amyloidosis

The idea that performing a proper succession of imaging tests and techniques allows an accurate and early diagnosis of cardiac amyloidosis, avoiding the need to perform the myocardial biopsy, is becoming increasingly popular. Furthermore, being imaging techniques non-invasive, it is possible to perform the follow-up of the pathology through repeated image acquisitions. In the present review, the various innovative imaging methodologies are presented, and it is discussed how they have been applied for early diagnosis of cardiac amyloidosis (CA), also to distinguish the two most frequent subtypes in CA: immunoglobulin light chain amyloidosis (AL) and transthyretin amyloidosis (ATTR); this allows to perform the therapy in a targeted and rapid manner.

Combined functional magnetic resonance imaging and skin conductance to detect localized neural response to psychological stress: a pilot study

OBJECTIVE

This preliminary study aims at investigating the neural correlates of the stress response, intended as an emotional and cognitive response, through the description of the activation of the autonomic nervous system in a problem-solving task and central functional data; in particular, we recorded skin conductance level (SCL) and response (SCR) and observed the correlation with fMRI data.

MATERIALS AND METHODS

The results obtained from 6 healthy subjects, 3 males and 3 females, aged between 18 and 45 (average = 27, SD = 7.08) who voluntarily offered to participate in the study were examined. They were previously subjected to a brief clinical psychological assessment (MMPI-2) and then to a psychophysiological evaluation. The real experiment consisted in subjecting the participants to an adapted version of the Raven's Coloured Progressive Matrices 47 (CPM 47) test to evaluate some consequences on brain activity of attention, orientation, reflex and response to stress during fMRI data acquisition and SCL-SCR recording.

RESULTS

SCR changes were found to be related to the activity of different brain regions such as bilateral precentral gyrus, right inferior frontal gyrus, right medial frontal gyrus, bilateral superior frontal gyri and left anterior cingulate suggesting a specific relationship between attentive processing and autonomic arousal.

CONCLUSION

The association of SC measurement with neuroimaging allows to highlight the interaction between emotional and cognitive processes: although preliminary, these results partially confirm what previously found in literature on the neural correlates of psychological stress and underline the interaction between cognitive function and autonomic arousal system during a stressful problem-solving task.

Deep-learning-based cardiac amyloidosis classification from early acquired pet images

The objective of the present work was to evaluate the potential of deep learning tools for characterizing the presence of cardiac amyloidosis from early acquired PET images, i.e. 15 min after [18F]-Florbetaben tracer injection. 47 subjects were included in the study: 13 patients with transthyretin-related amyloidosis cardiac amyloidosis (ATTR-CA), 15 patients with immunoglobulin light-chain amyloidosis (AL-CA), and 19 control-patients (CTRL). [18F]-Florbetaben PET/CT images were acquired in list mode and data was sorted into a sinogram, covering a time interval of 5 min starting 15 min after the injection. The resulting sinogram was reconstructed using OSEM iterative algorithm. A deep convolutional neural network (CAclassNet) was designed and implemented, consisting of five 2D convolutional layers, three fully connected layers and a final classifier returning AL, ATTR and CTRL scores. A total of 1107 2D images (375 from AL-subtype patients, 312 from ATTR-subtype, and 420 from Controls) have been considered in the study and used to train, validate and test the proposed network. CAclassNet cross-validation resulted with train error mean ± sd of 2.001% ± 0.96%, validation error of 4.5% ± 2.26%, and net accuracy of 95.49% ± 2.26%. Network test error resulted in a mean ± sd values of 10.73% ± 0.76%. Sensitivity, specificity, and accuracy evaluated on the test dataset were respectively for AL-CA sub-type: 1, 0.912, 0.936; for ATTR-CA: 0.935, 0.897, 0.972; for control subjects: 0.809, 0.971, 0.909. In conclusion, the proposed CAclassNet model seems very promising as an aid for the clinician in the diagnosis of CA from cardiac [18F]-Florbetaben PET images acquired a few minutes after the injection.

Correlation between micro and macrostructural biaxial behavior of ascending thoracic aneurysm: a novel experimental technique

Mechanical properties and microstructural modifications of vessel tissues are strongly linked, as established in the state of the art of cardiovascular diseases. Techniques to obtain both mechanical and structural information are reported, but the possibility to obtain real-time microstructural and macrostructural data correlated is still lacking. An experimental approach to characterize the aortic tissue is presented. A setup integrating biaxial traction and Small Angle Light Scattering (SALS) analysis is described. The system was adopted to test ex-vivo aorta specimens from healthy and aneusymatic (aTAA) cases. A significant variation of the fiber dispersion with respect to the unloaded state was encountered during the material traction. The corresponding microstructural and mechanical data were successfully used to fit a given anisotropic constitutive model, with satisfactory R² values (0.97±0.11 and 0.96±0.17, for aTAA and healthy population, respectively) and fiber dispersion parameters variations between the aTAA and healthy populations (0.39±0.23 and 0.15±0.10). The method integrating the biaxial/SALS technique was validated, allowing for real-time synchronization between mechanical and microstructural analysis of anisotropic biological tissues.

A Proof of Concept of a Non-Invasive Image-Based Material Characterization Method for Enhanced Patient-Specific Computational Modeling

PURPOSE

Computational models of cardiovascular structures rely on their accurate mechanical characterization. A validated method able to infer the material properties of patient-specific large vessels is currently lacking. The aim of the present study is to present a technique starting from the flow-area (QA) method to retrieve basic material properties from magnetic resonance (MR) imaging.

METHODS

The proposed method was developed and tested, first, in silico and then in vitro. In silico, fluid-structure interaction (FSI) simulations of flow within a deformable pipe were run with varying elastic modules (E) between 0.5 and 32 MPa. The proposed QA-based formulation was assessed and modified based on the FSI results to retrieve E values. In vitro, a compliant phantom connected to a mock circulatory system was tested within MR scanning. Images of the phantom were acquired and post-processed according to the modified formulation to infer E of the phantom. Results of in vitro imaging assessment were verified against standard tensile test.

RESULTS

In silico results from FSI simulations were used to derive the correction factor to the original formulation based on the geometrical and material characteristics. In vitro, the modified QA-based equation estimated an average E = 0.51 MPa, 2% different from the E derived from tensile tests (i.e. E = 0.50 MPa).

CONCLUSION

This study presented promising results of an indirect and non-invasive method to establish elastic properties from solely MR images data, suggesting a potential image-based mechanical characterization of large blood vessels.

Modeling biomechanical interaction between soft tissue and soft robotic instruments: importance of constitutive anisotropic hyperelastic formulations

Cardiovascular diseases are the leading cause of death in the western countries. Robotic surgery recently emerged as a confirmed strategy in the cardiovascular field, especially thanks to the improvement of soft robotics. These techniques have demonstrated their potential in terms of speed of execution and precision. In this context, a deeper knowledge of the material properties of the blood vessels is required, especially for computational soft robotics applications. A constitutive model including the contribution of the collagen fibers families is needed to take hyperelasticity and anisotropy into account. For this purpose, four different models are presented: two fiber families with dispersion (2FFD), two fiber families without dispersion (2FF), four fiber families with dispersion (4FFD), and four fiber families without dispersion (4FF). A set of experimental biaxial data obtained from ex-vivo specimens was used to assess the model performances. Two fitting procedures were imposed: a procedure with no weighting of scores and a procedure with a weight set to enhance the model performances in the contact range. A finite element simulation of a contact procedure was developed to evaluate the effect on the contact pressures and forces according to the different model implementations. In particular, a minimally invasive aortic valve positioning process through a previously designed soft robot was simulated. The results confirmed the overall fitting procedure. The adoption of the weighting process for the fitting was successful, as it permitted an accurate prediction in the region of interest through models with less parameters.

Analysis, comparison and representation of occupational exposure to a static magnetic field in a 3-T MRI site

The purpose of this study is to analyze exposure to the time-varying magnetic field caused by worker movements in a 3-T clinical magnetic resonance imaging (MRI) scanner. Measurements of the static magnetic field (B) in the proximity of the MRI scanner were performed to create a detailed map of the spatial gradient of B, in order to indicate the areas at high risk of exposure. Moreover, a personal exposure recording system was used in order to analyze and compare exposure to the static magnetic field during different routine procedures in MRI. We found that for all of the performed work activities, exposure was compliant with International Commission on Non-Ionizing Radiation Protection levels. However, our findings confirm that there is great variability of exposure between different workers and suggest the importance of performing personal exposure measurements and of detailed knowledge of the magnetic field spatial distribution.

The Procedure for Quantitative Characterization and Analysis of Magnetic Fields in Magnetic Resonance Sites for Protection of Workers: A Pilot Study

Concerning the occupational exposure in magnetic resonance imaging (MRI) facilities, the worker behavior in the magnetic resonance (MR) room is of such particular importance that there is the need for a simple but reliable method to alert the worker of the highest magnetic field exposure. Here, we describe a quantitative analysis of occupational exposure in different MRI working environments: in particular, we present a field measurement method integrated with a software tool for an accurate mapping of the fringe field in the proximity of the magnetic resonance bore. Three illustrative assessment studies are finally presented, compared and discussed, considering an example of a realistic path followed by an MRI worker during the daily procedure. The results show that the basic restrictions set by ICNIRP can be exceeded during standard procedure even in 1.5 T scanners. Using the described simplified metrics, it is possible to introduce behavioral rules on how to move around an MRI room that could be more useful than a numerical limit to aid magnetic field risk mitigation strategies.

Ld-EEG Effective Brain Connectivity in Patients With Cheyne-Stokes Respiration

The characterization of brain cortical activity in heart-failure patients affected by Cheyne-Stokes Respiration might provide relevant information about the mechanism underlying this pathology. Central autonomic network is gaining increasing attention for its role in the regulation of breathing and cardiac functions. In this scenario, evaluating changes in cortical connectivity associated with Cheyne-Stokes Respiration may be of interest in the study of specific brain-activity related to such disease. Nonetheless, the inter subject variability, the temporal dynamics of Central-Apnea/Hyperpnea cycles and the limitations of clinical setups lead to different methodological challenges. To this aim, we present a framework for the assessment of cortico-cortical interactions from Electroencephalographic signals acquired using low-density caps and block-design paradigms, arising from endogenous triggers. The framework combines ICA-decomposition, unsupervised clustering, MVAR modelling and a permutation-bootstrap strategy for evaluating significant connectivity differences between conditions. A common network, lateralized towards the left hemisphere, was depicted across 8 patients exhibiting Cheyne-Stokes Respiration patterns during acquisitions. Significant differences in connectivity at the group level were observed based on patients' ventilatory condition. Interactions were significantly higher during hyperpnea periods with respect to central apneas and occurred mainly in the delta band. Opposite-sign differences were observed for higher frequencies (i.e. beta, low-gamma).

Probabilistic Graphical Models for Dynamic PET: A Novel Approach to Direct Parametric Map Estimation and Image Reconstruction

In the context of dynamic emission tomography, the conventional processing pipeline consists of independent image reconstruction of single-time frames, followed by the application of a suitable kinetic model to time-activity curves (TACs) at the voxel or region-of-interest level. Direct 4D positron emission tomography (PET) reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple time frames within the reconstruction task. Established direct methods are based on a deterministic description of voxelwise TACs, captured by the chosen kinetic model, considering the photon counting process the only source of uncertainty. In this paper, we introduce a new probabilistic modeling strategy based on the key assumption that activity time course would be subject to uncertainty even if the parameters of the underlying dynamic process are known. This leads to a hierarchical model that we formulate using the formalism of probabilistic graphical modeling. The inference is addressed using a new iterative algorithm, in which kinetic modeling results are treated as prior expectation of activity time course, rather than as a deterministic match, making it possible to control the trade-off between a data-driven and a model-driven reconstruction. The proposed method is flexible to an arbitrary choice of (linear and nonlinear) kinetic models, it enables the inclusion of arbitrary (sub)differentiable priors for parametric maps, and it is simple to implement. Computer simulations and an application to a real-patient scan show how the proposed method is able to generalize over conventional indirect and direct approaches, providing a bridge between them by properly tuning the impact of the kinetic modeling step on image reconstruction.

Negative binomial maximum likelihood expectation maximization (NB-MLEM) algorithm for reconstruction of pre-corrected PET data

PURPOSE

Positron emission tomography (PET) image reconstruction is usually performed using maximum likelihood (ML) iterative reconstruction methods, under the assumption of Poisson distributed data. Pre-correcting raw measured counts, this assumption is no longer realistic. The goal of this work is to develop a reconstruction algorithm based on the Negative Binomial (NB) distribution, which can generalize over the Poisson distribution in case of over-dispersion of raw data, that may occur if sinogram pre-correction is used.

METHODS

The mathematical derivation of a Negative Binomial Maximum Likelihood Expectation-Maximization (NB-MLEM) algorithm is presented. A simulation study to compare the performance of the proposed NB-MLEM algorithm with respect to a Poisson-based MLEM (P-MLEM) method was performed, in reconstructing PET data. The proposed NB-MLEM reconstruction was tested on a real phantom and human brain data.

RESULTS

For the property of NB distribution, it is a generalization of the conventional P-MLEM: for not over dispersed data, the proposed NB-MLEM algorithm behaves like the conventional P-MLEM; for over-dispersed PET data, the additional evaluation of the dispersion parameter after each reconstruction iteration leads to a more accurate final image with respect to P-MLEM.

CONCLUSIONS

A novel approach for PET image reconstruction from pre-corrected data has been developed, which exhibits a statistical behavior that deviates from the Poisson distribution. Simulation study and preliminary tests on real data showed how the NB-MLEM algorithm, being able to explain the over-dispersion of pre-corrected data, can outperform other algorithms that assume no over-dispersion of pre-corrected data, while still not accounting for the presence of negative data, such as P-MLEM.

Design, simulation, and fabrication of a three-dimensional printed pump mimicking the left ventricle motion

The development of accurate replicas of the circulatory and cardiac system is fundamental for a deeper understanding of cardiovascular diseases and the testing of new devices. Although numerous works concerning mock circulatory loops are present in the current state of the art, still some limitations are present. In particular, a pumping system able to reproduce the left ventricle motion and completely compatible with the magnetic resonance environment to permit the four-dimensional flow monitoring is still missing. The aim of this work was to evaluate the feasibility of an actuator suitable for cardiovascular mock circuits. Particular attention was given to the ability to mimic the left ventricle dynamics including both compression and twisting with the magnetic resonance compatibility. In our study, a left ventricle model to be actuated through vacuum was designed. The realization of the system was evaluated with finite element analysis of different design solutions. After the in silico evaluation phase, the most suitable design in terms of physiological values reproduction was fabricated through three-dimensional printing for in vitro validation. A pneumatic experimental setup was developed to evaluate the pump performances in terms of actuation, in particular ventricle radial and longitudinal displacement, twist rotation, and ejection fraction. The study demonstrated the feasibility of a custom pneumatic pump for mock circulatory loops able to reproduce the physiological ventricle movement and completely suitable for the magnetic resonance environment.

Exploring the supra linear relationship between PetCO2 and fMRI signal change with ICA

The relationships between brain functions and the respiratory system are complex. Disentangling brain activity related to CO₂ changes from nonspecific vasoreactivity is a challenge when studying brain activity involved in the control of breathing with fMRI. In this work, we analyzed a dose dependent relationship between arterial CO₂ levels and brain response. To accomplish this goal, we developed a gas administration protocol, together with multi-subject ICA and specific nonlinear post-processing analysis. Our results highlighted a supra-linear response to CO₂ challenges in brainstem, thalamus and putamen. Results were discussed in the light of current knowledge about the central respiratory network.

TOWARDS A PERSONALISED AND INTERACTIVE ASSESSMENT OF OCCUPATIONAL EXPOSURE TO MAGNETIC FIELD DURING DAILY ROUTINE IN MAGNETIC RESONANCE

Magnetic resonance imaging (MRI) is one of the most common sources of electromagnetic (EM) fields as a diagnostic technique widely used in medicine. MRI staff during the working day is constantly exposed to static and spatially heterogeneous magnetic field. Also, moving around the MRI room to perform their functions, workers are exposed to slowly time-varying magnetic fields that induce electrical currents and fields in the body. The development of new exposure assessment methodologies to collect exposure data at a personal level using simple everyday equipment is hence necessary, also in view of future epidemiological studies. This paper describes the design and testing of a novel device for assessing personal exposure to static and time-varying magnetic fields during daily clinical practice. The dosemeter will be also used to ensure effective training of technicians who will be instructed to avoid, where possible, risk behaviour in terms of high exposure.

Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach

We present a novel framework for the fluid dynamics analysis of healthy subjects and patients affected by ascending thoracic aorta aneurysm (aTAA). Our aim is to obtain indications about the effect of a bulge on the hemodynamic environment at different enlargements. Three-dimensional (3D) surface models defined from healthy subjects and patients with aTAA, selected for surgical repair, were generated. A representative shape model for both healthy and pathological groups has been identified. A morphing technique based on radial basis functions (RBF) was applied to mold the shape relative to healthy patient into the representative shape of aTAA dataset to enable the parametric simulation of the aTAA formation. Computational fluid dynamics (CFD) simulations were performed by means of a finite volume solver using the mean boundary conditions obtained from three-dimensional (PC-MRI) acquisition. Blood flow helicity and flow descriptors were assessed for all the investigated models. The feasibility of the proposed integrated approach pertaining the coupling between an RBF morphing technique and CFD simulation for aTAA was demonstrated. Significant hemodynamic changes appear at the 60% of the bulge progression. An impingement of the flow toward the bulge was observed by analyzing the normalized flow eccentricity (NFE) index.

Accelerated PET kinetic maps estimation by analytic fitting method

In this work, we propose and test a new approach for non-linear kinetic parameters' estimation from dynamic PET data. A technique is discussed, to derive an analytical closed-form expression of the compartmental model used for kinetic parameters' evaluation, using an auxiliary parameter set, with the aim of reducing the computational burden and speeding up the fitting of these complex mathematical expressions to noisy TACs. Two alternative algorithms based on numeric calculations are considered and compared to the new proposal. We perform a simulation study aimed at (i) assessing agreement between the proposed method and other conventional ways of implementing compartmental model fitting, and (ii) quantifying the reduction in computational time required for convergence. It results in a speed-up factor of ∼120 when compared to a fully numeric version, or ∼38, with respect to a more conventional implementation, while converging to very similar values for the estimated model parameters. The proposed method is also tested on dynamic 3D PET clinical data of four control subjects. The results obtained supported those of the simulation study, and provided input and promising perspectives for the application of the proposed technique in clinical practice.

Estimation of pancreatic R2* for iron overload assessment in the presence of fat: a comparison of different approaches

OBJECTIVES

To propose a method for estimating pancreatic relaxation rate, R2*, from conventional multi-echo MRI, based on the nonlinear fitting of the acquired magnitude signal decay to MR signal models that take into account both the signal oscillations induced by fat and the different R2* values of pancreatic parenchyma and fat.

MATERIALS AND METHODS

Single-peak fat (SPF) and multi-peak fat (MPF) models were introduced. Single-R2* and dual-R2* assumptions were considered as well. Analyses were conducted on simulated data and 20 thalassemia major patients.

RESULTS

Simulations revealed the ability of the MPF model to correctly estimate the R2* value in a large range of fat fractions and R2* values. From the comparison between the results obtained with a single R2* value for water and fat and the dual-R2* approach, the latter is more accurate in both water R2* and fat fraction estimation. In patient's data analysis, a strong concordance was found between SPF and MPF estimated data with measurements done with manual signal correction and from fat-saturated images. The MPF method showed better reproducibility.

CONCLUSION

The MPF dual-R2* approach improves reproducibility and reduces image analysis time in the assessment of pancreatic R2* value in patients with iron overload.

Biomolecular imaging of 13C-butyrate with dissolution-DNP: Polarization enhancement and formulation for in vivo studies

Magnetic Resonance Spectroscopy of hyperpolarized isotopically enriched molecules facilitates the non-invasive real-time investigation of in vivo tissue metabolism in the time-frame of a few minutes; this opens up a new avenue in the development of biomolecular probes. Dissolution Dynamic Nuclear Polarization is a hyperpolarization technique yielding a more than four orders of magnitude increase in the ¹³C polarization for in vivo Magnetic Resonance Spectroscopy studies. As reported in several studies, the dissolution Dynamic Nuclear Polarization polarization performance relies on the chemico-physical properties of the sample. In this study, we describe and quantify the effects of the different sample components on the dissolution Dynamic Nuclear Polarization performance of [1-¹³C]butyrate. In particular, we focus on the polarization enhancement provided by the incremental addition of the glassy agent dimethyl sulfoxide and gadolinium chelate to the formulation. Finally, preliminary results obtained after injection in healthy rats are also reported, showing the feasibility of an in vivo Magnetic Resonance Spectroscopy study with hyperpolarized [1-¹³C]butyrate using a 3T clinical set-up.

Numerical evaluation of human exposure to WiMax patch antenna in tablet or laptop

The use of wireless communication devices, such as tablets or laptops, is increasing among children. Only a few studies assess specific energy absorption rate (SAR) due to exposure from wireless-enabled tablets and laptops, in particular with Worldwide Interoperability for Microwave Access (WiMax) technology. This paper reports the estimation of the interaction between an E-shaped patch antenna (3.5 GHz) and human models, by means of finite-difference time-domain (FDTD) method. Specifically, four different human models (young adult male, young adult female, pre-teenager female, male child) in different exposure conditions (antenna at different distances from the human model, in different positions, and orientations) were considered and whole-body, 10 and 1 g local SAR and magnetic field value (Bmax) were evaluated. From our results, in some worst-case scenarios involving male and female children's exposure, the maximum radiofrequency energy absorption (hot spots) is located in more sensitive organs such as eye, genitals, and breast. Bioelectromagnetics. 39:414-422, 2018. © 2018 Wiley Periodicals, Inc.

New Imaging Frontiers in Cardiology: Fast and Quantitative Maps from Raw Data

BACKGROUND

Among the novelties in the field of cardiovascular imaging, the construction of quantitative maps in a fast and efficient way is one of the most interesting aspects of the clinical research. Quantitative parametric maps are typically obtained by post processing dynamic images, that is, sets of images usually acquired in different temporal intervals, where several images with different contrasts are obtained. Magnetic resonance imaging, and emission tomography (positron emission and single photon emission) are the imaging techniques best suited for the formation of quantitative maps.

METHODS

In this review article we present several methods that can be used for obtaining parametric maps, in a fast way, starting from the acquired raw data. We describe both methods commonly used in clinical research, and more innovative methods that build maps directly from the raw data, without going through the image reconstruction.

RESULTS

We briefly described recently developed methods in magnetic resonance imaging that accelerate further the MR raw data generation, based on appropriate sub-sampling of k-space; then, we described recently developed methods for generating MR parametric maps. With regard to the emission tomography techniques, we gave an overview of both conventional methods, and more recently developed direct estimation algorithms for parametric image reconstruction from dynamic positron emission tomography data.

CONCLUSION

We have provided an overview of the possible approaches that can be followed to realize useful parametric maps from imaging raw data. We moved from the conventional approaches to more recent and efficient methods for accelerating the raw data generation and the of parametric maps formation.

Measured PET Data Characterization with the Negative Binomial Distribution Model

Accurate statistical model of PET measurements is a prerequisite for a correct image reconstruction when using statistical image reconstruction algorithms, or when pre-filtering operations must be performed. Although radioactive decay follows a Poisson distribution, deviation from Poisson statistics occurs on projection data prior to reconstruction due to physical effects, measurement errors, correction of scatter and random coincidences. Modelling projection data can aid in understanding the statistical nature of the data in order to develop efficient processing methods and to reduce noise. This paper outlines the statistical behaviour of measured emission data evaluating the goodness of fit of the negative binomial (NB) distribution model to PET data for a wide range of emission activity values. An NB distribution model is characterized by the mean of the data and the dispersion parameter α that describes the deviation from Poisson statistics. Monte Carlo simulations were performed to evaluate: (a) the performances of the dispersion parameter α estimator, (b) the goodness of fit of the NB model for a wide range of activity values. We focused on the effect produced by correction for random and scatter events in the projection (sinogram) domain, due to their importance in quantitative analysis of PET data. The analysis developed herein allowed us to assess the accuracy of the NB distribution model to fit corrected sinogram data, and to evaluate the sensitivity of the dispersion parameter α to quantify deviation from Poisson statistics. By the sinogram ROI-based analysis, it was demonstrated that deviation on the measured data from Poisson statistics can be quantitatively characterized by the dispersion parameter α, in any noise conditions and corrections.

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO₂ (P_ETCO₂) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings.

A Conway-Maxwell-Poisson (CMP) model to address data dispersion on positron emission tomography

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy.

Voice quality in patients suffering from bipolar disease

People suffering from bipolar disease are more and more common. Such pathology can severely affect patients' lifestyle by wide, and sometimes extreme, mood swings. Biosignals can be very useful to understand this disease. Specifically, speech-related features have been seen to vary in depressed people with respect to healthy subjects. Usually prosodic, spectral and energy-related features are studied. Some further information, instead, can be provided studying voice quality. According to Laver's model, voice quality is sensitive and depends on both anatomic/physiologic issues and long-term muscular adjustments of the larynx or the supraglottal vocal tract. A pilot study on both bipolar patients and healthy control subjects, performed by means of the Long-Term Average Spectrum (LTAS) is presented. The effects on LTAS estimation of a F0-correction procedure are discussed. Pairwise statistical comparisons between subjects in euthymic and depressed states and euthymic and hypomanic states were performed. Significant differences were found in some frequency intervals in both cases. The F0-correction procedure modified the values of the significant frequency intervals in the euthymic/depressed comparison, that also was characterized by a change of F0. Noticeably, no statistically significant differences were found in control subjects acquired in the same mood state. Though the number of subjects is small, the results are encouraging given their coherence across patients and the lack of differences in the control group. Finally, this work suggests that particular vocal settings might be involved in different mood states.

Analysis of the microcirculatory pulse wave: age-related alterations

Morphological analysis of the pulse wave of central blood pressure signal is commonly used for the study of cardiac and vascular properties, but very few attempts were performed for analyzing the peripheral pulse wave of blood flow. In this work, we analyzed this waveform using classical methods, based on the application of FFT, followed by principal components analysis, for assessing the properties of the blood flow. As a sample problem, we evaluated the capability of the proposed method of assessing the alterations correlated with the aging of the vascular system. Results show a good discrimination between the different age groups, confirming the validity of the approach.

A novel 3D Cartesian random sampling strategy for Compressive Sensing Magnetic Resonance Imaging

In this work we propose a novel acquisition strategy for accelerated 3D Compressive Sensing Magnetic Resonance Imaging (CS-MRI). This strategy is based on a 3D cartesian sampling with random switching of the frequency encoding direction with other K-space directions. Two 3D sampling strategies are presented. In the first strategy, the frequency encoding direction is randomly switched with one of the two phase encoding directions. In the second strategy, the frequency encoding direction is randomly chosen between all the directions of the K-Space. These strategies can lower the coherence of the acquisition, in order to produce reduced aliasing artifacts and to achieve a better image quality after Compressive Sensing (CS) reconstruction. Furthermore, the proposed strategies can reduce the typical smoothing of CS due to the limited sampling of high frequency locations. We demonstrated by means of simulations that the proposed acquisition strategies outperformed the standard Compressive Sensing acquisition. This results in a better quality of the reconstructed images and in a greater achievable acceleration.

Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise

The central mechanism of breathing control is not totally understood. Several studies evaluated the correlation between electroencephalographic (EEG) power spectra and respiratory signals by performing resting state tasks or adopting hypercapnic/hypoxic stimuli. The observation of brain activity during voluntary breath hold tasks, might be an useful approach to highlight the areas involved in mechanism of breath regulation. Nevertheless, studies of brain activity with EEG could present some limitations due to presence of severe artifacts. When artifact rejection methods, as independent component analysis, cannot reliably clean EEG data, it is necessary to exclude noisy segments. In this study, global field power in the delta band and end-tidal CO2 were derived from EEG and CO2 signals respectively in 4 healthy subjects during a breath-hold task. The cross correlation function between the two signals was estimated taking into account the presence of missing samples. The statistical significance of the correlation coefficients at different time lags was assessed using surrogate data. Some simulations are introduced to evaluate the effect of missing data on the correlational analysis and their results are discussed. Results obtained on subjects show a significant correlation between changes in EEG power in the delta band and end-tidal CO2. Moreover, the changes in end-tidal CO2 were found to precede those of global field power. These results might help to better understand the cortical mechanisms involved in the control of breathing.

Technological Innovations in Magnetic Resonance for Early Detection of Cardiovascular Diseases

Most recent technical innovations in cardiovascular MR imaging (CMRI) are presented in this review. They include hardware and software developments, and novelties in parametric mapping. All these recent improvements lead to high spatial and temporal resolution and quantitative information on the heart structure and function. They make it achievable ambitious goals in the field of magnetic resonance, such as the early detection of cardiovascular pathologies. In this review article, we present recent innovations in CMRI, emphasizing the progresses performed and the solutions proposed to some yet opened technical problems.

Variable density randomized stack of spirals (VDR-SoS) for compressive sensing MRI

PURPOSE

To develop a 3D sampling strategy based on a stack of variable density spirals for compressive sensing MRI.

METHODS

A random sampling pattern was obtained by rotating each spiral by a random angle and by delaying for few time steps the gradient waveforms of the different interleaves. A three-dimensional (3D) variable sampling density was obtained by designing different variable density spirals for each slice encoding. The proposed approach was tested with phantom simulations up to a five-fold undersampling factor. Fully sampled 3D dataset of a human knee, and of a human brain, were obtained from a healthy volunteer. The proposed approach was tested with off-line reconstructions of the knee dataset up to a four-fold acceleration and compared with other noncoherent trajectories.

RESULTS

The proposed approach outperformed the standard stack of spirals for various undersampling factors. The level of coherence and the reconstruction quality of the proposed approach were similar to those of other trajectories that, however, require 3D gridding for the reconstruction.

CONCLUSION

The variable density randomized stack of spirals (VDR-SoS) is an easily implementable trajectory that could represent a valid sampling strategy for 3D compressive sensing MRI. It guarantees low levels of coherence without requiring 3D gridding. Magn Reson Med 76:59-69, 2016. © 2015 Wiley Periodicals, Inc.