Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures

X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches.     

Effect of alternative C2 carbon sources on the growth, lipid, and γ-linolenic acid production of spirulina (Arthrospira platensis)

The influence of different organic carbon sources (glucose, ethanol, and acetic acid) at different concentrations (0.1, 0.5, and 1.0 g/L for batch and 1.0, 2.0, and 3.0 g/L for fed-batch) were studied in the mixotrophic production (using both light and carbon source) of γ-linolenic acid (GLnA) by spirulina (Arthrospira platensis). The obtained spirulina was analyzed in terms of biomass, lipid, and GLnA production. In the batch media, increasing the concentrations of glucose, ethanol, and acetic acid led to an increase in the biomass, lipid, and GLnA production. However, carbon sources at concentrations greater than 1.0 g/L in fed-batch media appeared to have no significant effects on the above parameters. It was also demonstrated that biomass, lipid, and GLnA production using ethanol and acetic acid could be as good as those achieved with the classic glucose-based culture media.     

Use of sourdough to reduce phytic acid and improve zinc bioavailability of a traditional flat bread (sangak) from Iran

In this study, effects of 8 different sourdough starters prepared with Saccharomyces cerevisiae, Lactobacillus plantarum, L. acidophilus, and Leuconostoc mesenteroides were investigated on the phytic acid level and mole ratio of phytic acid to zinc in a traditional Iranian bread (sangak). Different sourdough preparations were made and incubated at 30°C for 16 h and added to the dough at 10, 20, and 30% replacement levels. Use of sourdough resulted in a decrease in phytic acid level (also in a decrease in the phytic acid to zinc mole ratio) and corresponding increase in zinc bioavailability index when compared to the commercial sangak bread. The lowest phytic acid concentration and highest zinc bioavailability index were achieved when S. cerevisiae, L. plantarum, and Leu. mesenteroides were used at 30.0% dough replacement with sourdough. This study provides awareness about the negative impacts of higher phytic acid level in the breads, which is particularly the case for sangak bread, and also provides a solution for such issue.     

MRI-compatible intensity-modulated force sensor for cardiac catheterization procedures

This paper presents a novel, magnetic resonance imaging (MRI)-compatible, force sensor suitable for cardiac catheterization procedures. The miniature, fiber-optic sensor is integrated with the tip of a catheter to allow the detection of interaction forces with the cardiac walls. The optical fiber light intensity is modulated when a force acting at the catheter tip deforms an elastic element, which, in turn, varies the distance between a reflector and the optical fiber. The tip sensor has an external diameter of 9 Fr (3?mm) and can be used during cardiac catheterization procedures. The sensor is able to measure forces in the range of 0-0.85?N, with relatively small hysteresis. A nonlinear method for calibration is used and real-time MRI in vivo experiments are carried out, to prove the feasibility of this low-cost sensor, enabling the detection of catheter-tip contact forces under dynamic conditions.     

Use of Artificial Neural Network and Image Analysis to Predict Physical Properties of Osmotically Dehydrated Pumpkin

The objectives of this research were to predict, using neural networks, the color intensity (ΔE), percentage of shrinkage as well as the Heywood shape factor, which is the representative of deformation, of osmotically dehydrated and air dried pumpkin pieces. Several osmotic solutions were used including 50% (w/w) sorbitol solution, 50% (w/w) glucose solution, and 50% (w/w) sucrose solution. Optimum artificial neural network (ANN) models were developed based on one to two hidden layers and 10–20 neurons per hidden layer. The ANN models were then tested against an independent data set. The measured values of the color intensity, percentage of shrinkage, and the Heywood shape factor were predicted with R² > 0.90 in all cases, except when all the drying methods were combined in one data set.     

Application of Fractal Theory for Prediction of Shrinkage of Dried Kiwifruit Using Artificial Neural Network and Genetic Algorithm

In current research, fractal theory has been applied for estimation of shrinkage of osmotically dehydrated and air-dried kiwifruit using a combination of neural network and genetic algorithm. Kiwifruits were dehydrated at different conditions and digital images of final dried products were taken. Kiwifruit-background interface lines were detected using a threshold combined with an edge detection approach and their corresponding fractal dimensions were calculated based on a box counting method. A neural network was constructed using fractal dimension and moisture content as inputs to predict shrinkage of dried kiwifruit and a genetic algorithm was applied for optimization of the neural network's parameters. The results indicated good accuracy of optimal model (correlation coefficient of 0.95) and high potential application of fractal theory and described intelligent model for shrinkage estimation of dried kiwifruit.     

Mechanical Behavior of Lentil Seeds in Relation to their Physicochemical and Microstructural Characteristics

The mechanical characteristics (rupture force, maximal deformation, and rupture energy) of red and green lentils under compression loading were determined as a function of moisture content ranging from 9.5 to 21.1% (w.b.). Scanning electron microscopy, laser diffraction particle size analysis, and instrumental texture evaluation were successfully applied to relate the microstructure and texture of different lentil seed varieties. Results demonstrated that all of the mechanical parameters of the green lentils, which have smaller starch granules, were significantly (p < 0.05) higher than those of the red lentils. At a loading rate of 4 mm min^?1, the force required for initiating seed rupture decreased with an increase in moisture content, for vertical and horizontal orientations (p < 0.05). The scanning electron microscopy observations also revealed that seeds were more flexible in a horizontal orientation.     

A fuzzy grey goal programming approach for aggregate production planning

Aggregate planning is a medium-range capacity planning that suggests the production strategies in order to meet the forecasted demand considering the capacity constraints. As the period of planning length increases, the uncertainty of information will grow. Regarding this point, in this paper, a multi-objective model is proposed for aggregate planning problem in which the parameters of the model are expressed in the form of grey numbers. The suggested grey multi-objective model is solved based on a goal programming problem with fuzzy aspiration levels. The model is applied in a real-world problem, and its results are illustrated. The obtained results give a range for decision variables, and decision makers can handle the inevitable uncertainty of information by using these ranges.     

Effect of Solid Solution Supersaturation on Precipitation of γ′ in Rapidly Quenched Ni-Al Binary Alloys

The effect of solid solution supersaturation on the precipitation of γ′ in rapidly quenched Ni-Al binary alloys containing 11.6, 14.2 and 16.5 at. pct Al was investigated. The samples were solutioned at 1250°C, quenched in iced brine, and then analyzed by electron microscopy and XRD (X-ray diffraction) techniques. In Ni-11.6 at. pct Al alloy, ordering and phase separation took place simultaneously, resulting in a uniform distribution of γ′ . A transition from uniform to bimodal γ′ phase distribution occurred in the composition range between 14.2 and 16.5 at. pct Al. This transition was accompanied by changes in the morphology of γ′ precipitates. The microstructural observations were discussed in view of both kinetics and crystallographic considerations.