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.

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.

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.

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.

Simultaneous Functional and Morphological Assessment of Left Atrial Appendage by 3D Virtual Models.

Purpose: The left atrial appendage (LAA) is responsible for thrombus formation in patients with atrial fibrillation. The evaluation of both LAA function and morphology is crucial for the patient characterization and the preprocedural planning of LAA closure intervention. Despite the availability of 3D imaging modalities, the current standard image analysis is based on manual delineation of the LAA contours on 2D views. Methods: In this study, a comprehensive approach based on a full 3D analysis of the tomographic dataset by surface extraction and processing (3D-S) is presented. The proposed method allows extracting functional and morphologic information in the entire cardiac cycle by minimalizing manual user interaction. The proposed methodology has been validated on ten computer tomography datasets. Results: The proposed 3D-S method was feasible in all cases. Reproducibility was improved with respect to the reference 2D manual procedure (2D-S) (coefficient of variation 2.9 vs. 4.1% for diastolic ostium area; 3.8 vs. 6.1% for systolic ostium area; 2.4 vs. 5.3% for diastolic LAA volume; 2.7 vs. 5.9% for systolic LAA volume; and 7.7 vs. 17.1% for LAA ejection fraction). No significant differences were found between 2D-S and 3D-S measurements. Conclusions: In this study, we introduced a fully 3D approach for LAA characterization, allowing the simultaneous assessment of LAA function and geometry. The proposed approach could be used to improve the patient selection and the best sizing of the device for LAA closure and to allow a patient-specific 3D printing.

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.

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.

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.

Direct Parametric Maps Estimation from Dynamic PET Data: An Iterated Conditional Modes Approach.

We propose and test a novel approach for direct parametric image reconstruction of dynamic PET data. We present a theoretical description of the problem of PET direct parametric maps estimation as an inference problem, from a probabilistic point of view, and we derive a simple iterative algorithm, based on the Iterated Conditional Mode (ICM) framework, which exploits the simplicity of a two-step optimization and the efficiency of an analytic method for estimating kinetic parameters from a nonlinear compartmental model. The resulting method is general enough to be flexible to an arbitrary choice of the kinetic model, and unlike many other solutions, it is capable to deal with nonlinear compartmental models without the need for linearization. We tested its performance on a two-tissue compartment model, including an analytical solution to the kinetic parameters evaluation, based on an auxiliary parameter set, with the aim of reducing computation errors and approximations. The new method is tested on simulated and clinical data. Simulation analysis led to the conclusion that the proposed algorithm gives a good estimation of the kinetic parameters in any noise condition. Furthermore, the application of the proposed method to clinical data gave promising results for further studies.

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.

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.

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.

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.

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.