Raul Gonzalez Lima

Can Fiber Posts Increase Root Stresses and Reduce Fracture

The clinical success of fiber posts has been attributed to their lower elastic modulus. The tested hypothesis was that fiber posts could lead to lower risk of post debonding and lower risk of root fracture, despite an increase in root stresses. Stress analyses were carried out with a 3D finite element model of a premolar restored with a metallic or a fiber post. Bonded and non-bonded post/cement interface conditions were simulated. We calculated risk-of-fracture indices by determining the highest principal stress values divided by the tensile strength. Shear stresses along the post/cement interface were analyzed for the bonded models. Compared with the premolar restored with a metallic post, the fiber post generated lower stresses along the interface and higher stresses in the root. However, with the fiber post, fracture was less likely to occur in the root, since its core and post fracture indices were higher.

Real-time detection of pneumothorax using electrical impedance tomography*

Objectives:Pneumothorax is a frequent complication during mechanical ventilation. Electrical impedance tomography (EIT) is a noninvasive tool that allows real-time imaging of regional ventilation. The purpose of this study was to 1) identify characteristic changes in the EIT signals associated with pneumothoraces; 2) develop and fine-tune an algorithm for their automatic detection; and 3) prospectively evaluate this algorithm for its sensitivity and specificity in detecting pneumothoraces in real time. Design:Prospective controlled laboratory animal investigation. Setting:Experimental Pulmonology Laboratory of the University of São Paulo. Subjects:Thirty-nine anesthetized mechanically ventilated supine pigs (31.0 ± 3.2 kg, mean ± sd). Interventions:In a first group of 18 animals monitored by EIT, we either injected progressive amounts of air (from 20 to 500 mL) through chest tubes or applied large positive end-expiratory pressure (PEEP) increments to simulate extreme lung overdistension. This first data set was used to calibrate an EIT-based pneumothorax detection algorithm. Subsequently, we evaluated the real-time performance of the detection algorithm in 21 additional animals (with normal or preinjured lungs), submitted to multiple ventilatory interventions or traumatic punctures of the lung. Measurements and Main Results:Primary EIT relative images were acquired online (50 images/sec) and processed according to a few imaging-analysis routines running automatically and in parallel. Pneumothoraces as small as 20 mL could be detected with a sensitivity of 100% and specificity 95% and could be easily distinguished from parenchymal overdistension induced by PEEP or recruiting maneuvers. Their location was correctly identified in all cases, with a total delay of only three respiratory cycles. Conclusions:We created an EIT-based algorithm capable of detecting early signs of pneumothoraces in high-risk situations, which also identifies its location. It requires that the pneumothorax occurs or enlarges at least minimally during the monitoring period. Such detection was operator-free and in quasi real-time, opening opportunities for improving patient safety during mechanical ventilation.

Vertical root fracture in upper premolars with endodontic posts: finite element analysis.

Upper premolars restored with endodontic posts present a high incidence of vertical root fracture (VRF). Two hypotheses were tested: (1) the smaller mesiodistal diameter favors stress concentration in the root and (2) the lack of an effective bonding between root and post increases the risk of VRF. Using finite element analysis, maximum principal stress was analyzed in 3-dimensional intact upper second premolar models. From the intact models, new models were built including endodontic posts of different elastic modulus (E = 37 or E = 200 GPa) with circular or oval cross-section, either bonded or nonbonded to circular or oval cross-section root canals. The first hypothesis was partially confirmed because the conditions involving nonbonded, low-modulus posts showed lower tensile stress for oval canals compared to circular canals. Tensile stress peaks for the nonbonded models were approximately three times higher than for the bonded or intact models, therefore confirming the second hypothesis.

Spontaneous Effort During Mechanical Ventilation: Maximal Injury With Less Positive End-Expiratory Pressure.

Objectives:We recently described how spontaneous effort during mechanical ventilation can cause “pendelluft,” that is, displacement of gas from nondependent (more recruited) lung to dependent (less recruited) lung during early inspiration. Such transfer depends on the coexistence of more recruited (source) liquid-like lung regions together with less recruited (target) solid-like lung regions. Pendelluft may improve gas exchange, but because of tidal recruitment, it may also contribute to injury. We hypothesize that higher positive end-expiratory pressure levels decrease the propensity to pendelluft and that with lower positive end-expiratory pressure levels, pendelluft is associated with improved gas exchange but increased tidal recruitment. Design:Crossover design. Setting:University animal research laboratory. Subjects:Anesthetized landrace pigs. Interventions:Surfactant depletion was achieved by saline lavage in anesthetized pigs, and ventilator-induced lung injury was produced by ventilation with high tidal volume and low positive end-expiratory pressure. Ventilation was continued in each of four conditions: positive end-expiratory pressure (low or optimized positive end-expiratory pressure after recruitment) and spontaneous breathing (present or absent). Tidal recruitment was assessed using dynamic CT and regional ventilation/perfusion using electric impedance tomography. Esophageal pressure was measured using an esophageal balloon manometer. Measurements and Results:Among the four conditions, spontaneous breathing at low positive end-expiratory pressure not only caused the largest degree of pendelluft, which was associated with improved ventilation/perfusion matching and oxygenation, but also generated the greatest tidal recruitment. At low positive end-expiratory pressure, paralysis worsened oxygenation but reduced tidal recruitment. Optimized positive end-expiratory pressure decreased the magnitude of spontaneous efforts (measured by esophageal pressure) despite using less sedation, from –5.6 ± 1.3 to –2.0 ± 0.7 cm H2O, while concomitantly reducing pendelluft and tidal recruitment. No pendelluft was observed in the absence of spontaneous effort. Conclusions:Spontaneous effort at low positive end-expiratory pressure improved oxygenation but promoted tidal recruitment associated with pendelluft. Optimized positive end-expiratory pressure (set after lung recruitment) may reverse the harmful effects of spontaneous breathing by reducing inspiratory effort, pendelluft, and tidal recruitment.

Image Reconstruction Using Interval Simulated Annealing in Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Three-Dimensional Electrical Impedance Tomography: A Topology Optimization Approach

Electrical impedance tomography is a technique to estimate the impedance distribution within a domain, based on measurements on its boundary. In other words, given the mathematical model of the domain, its geometry and boundary conditions, a nonlinear inverse problem of estimating the electric impedance distribution can be solved. Several impedance estimation algorithms have been proposed to solve this problem. In this paper, we present a three-dimensional algorithm, based on the topology optimization method, as an alternative. A sequence of linear programming problems, allowing for constraints, is solved utilizing this method. In each iteration, the finite element method provides the electric potential field within the model of the domain. An electrode model is also proposed (thus, increasing the accuracy of the finite element results). The algorithm is tested using numerically simulated data and also experimental data, and absolute resistivity values are obtained. These results, corresponding to phantoms with two different conductive materials, exhibit relatively well-defined boundaries between them, and show that this is a practical and potentially useful technique to be applied to monitor lung aeration, including the possibility of imaging a pneumothorax.

Electrical impedance tomography reconstruction through Simulated Annealing with incomplete evaluation of the objective function

The EIT reconstruction problem is approached as an optimization problem where the difference between a simulated impedance domain and the observed one is minimized. This optimization problem is often solved by Simulated Annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function. We propose here, a variation of SA applied to EIT where the objective function is evaluated only partially, while ensuring upper boundaries on the deviation on the behavior of the modified SA. The reconstruction method is evaluated with simulated and experimental data.

Electrical impedance tomography through constrained sequential linear programming: a topology optimization approach

Electrical impedance tomography (EIT) is an imaging method that estimates conductivity distribution inside a body. In EIT, images are obtained by applying a sequence of low intensity electrical currents through electrodes attached to the body. Although in EIT there are serious difficulties to obtain a high-quality conductivity image, for medical applications this technology is safer and cheaper than other tomography techniques. The EIT deals with an inverse problem in which given the measured voltages on electrodes and a finite element (FE) model, it estimates the conductivity distribution, which are parameters of the FE model. In this work, the topology optimization method is applied as a reconstruction algorithm to obtain absolute images in EIT. It is an optimization method that has been applied successfully to structural mechanical applications and consists of systematically finding a conductivity distribution (or material distribution) in the domain that minimizes the difference between measured voltages and voltages calculated by using a computational model. This algorithm combines the finite element method and sequential linear programming (SLP) to solve the inverse problem of EIT. The SLP allows us to easily apply some regularization schemes based on included constraints in the topology optimization problem. Constraints based on image tuning control and weighted distance interpolation (WDI) are proposed, while a material model is applied to ensure the relaxation of the optimization problem. A new formulation to analytically perform the sensitivity analysis is proposed, using Maxwells reciprocity theorem. To illustrate, the implemented algorithm is applied to obtain conductivity image distributions of some 2D examples using numerical and experimental data.

Direct 2-D Reconstructions of Conductivity and Permittivity From EIT Data on a Human Chest

A novel direct D-bar reconstruction algorithm is presented for reconstructing a complex conductivity distribution from 2-D EIT data. The method is applied to simulated data and archival human chest data. Permittivity reconstructions with the aforementioned method and conductivity reconstructions with the previously existing nonlinear D-bar method for real-valued conductivities depicting ventilation and perfusion in the human chest are presented. This constitutes the first fully nonlinear D-bar reconstructions of human chest data and the first D-bar permittivity reconstructions of experimental data. The results of the human chest data reconstructions are compared on a circular domain versus a chest-shaped domain.