Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>With changing lifestyles, the demand for bone implantation has been increasing day by day. The deficiency of nutritious elements within the human body results in certain diseases like osteoporosis, rickets, and other skeletal disorders; lack of physical activities; and the increasing number of accidents are the primary reasons for bone damage/fracture. Metallic implants made up of chrome steel, cobalt-based alloys, and titanium-based alloys are being majorly used worldwide owing to their high strength and high corrosion resistance which makes them permanent orthopedic bioimplant materials, however, they display a stress-shielding effect and it also requires an implant removal surgery. Thus, these problems can be addressed through the employment of biodegradable materials. Among the available biodegradable metallic materials, Mg alloys have been identified as a prospective orthopedic implant material. These alloys are biodegradable as well as biocompatible, however, they experience a relatively higher rate of degradation limiting their usability as implant material. This study attempts to comprehensively assess the effects of various alloying elements such as Ca, Zn, Sn, Mn, Sr and Rare earth elements (REEs) on the mechanical and degradation behavior (both <jats:italic>in vivo</jats:italic> and <jats:italic>in vitro</jats:italic>) of Mg alloys. Since the microstructure, mechanical properties and degradation response of the Mg alloys are dependent on the processing route, hence detailed processing- property database of different Mg alloys is provided in this paper.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>A computationally simpler algorithm to reconstruct the optical property distribution of turbid media using diffuse optical tomographic principles is presented. The proposed algorithm eliminates the requirement of large Jacobian matrix inversion which otherwise is essential for tomographic imaging. The most significant Jacobians are identified based on proper thresholding of the measurement and the intersection of these Jacobians gives the approximate spatial location of the inhomogeneity. The algorithm is tested and optimized using simulations and further validated using tissue-mimicking phantom-based experiments and <jats:italic>in-vivo</jats:italic> small-animal experiments.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In intervention surgery, DSA images provide a new way to observe the vessels and catheters inside the patient. Extracting coronary artery from the dynamic complex background fast improves the effectiveness directly in clinical interventional surgery. This article proposes an incremental robust principal component analysis (IRPCA) method to extract contrast-filled vessels from x-ray coronary angiograms. RPCA is a matrix decomposition method that decomposes a video matrix into foreground and background, commonly used to model complex backgrounds and extract target objects. IRPCA pre-optimizes an x-ray image sequence. When a new x-ray sequence is received, IRPCA optimizes it based on the pre-optimized matrix according to the strategy of minimizing the energy function to obtain the foreground matrix of the new sequence. Besides, based on the idea that the new x-ray sequence introduces new information to the pre-optimized matrix, we propose UIRPCA to improve the performence of IRPCA. Compared with the traditional RPCA method, IRPCA and UIRPCA save much time while ensuring that other indicators remain basically unchanged. The experiment results based on real data show the superiority of the proposed method over other RPCA algorithms.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In this study, the performance of a two-dimensional Hénon map in predicting the interactive dynamics of the knee and hip joints emerging during a normative sit-to-stand movement was evaluated. The instantaneous values of the knee and hip joints were the model inputs, and the next values of the knee and hip joints were predicted by the Hénon map. The map predicted the desired relative behavior of the joints, showing synergetic coordination between the joints. The experimental data were recorded from four healthy participants and used to identify the Hénon map via a genetic algorithm. Model performance was quantitatively assessed by computing the calculated prediction error and analyzing the behavioral dynamics of the state spaces reconstructed via the captured kinematic data. According to the results, there was an obvious similarity between the dynamics of the state space trajectories of the identified model and those of the recorded data, not only in terms of stretching and folding dynamics, but also concerning generalized synchrony. The acceptable performance of the proposed modeling solution can also be demonstrated through these results.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose</jats:italic>. Previous studies have proposed deep-learning techniques to reconstruct CT images from sinograms. However, these techniques employ large fully-connected (FC) layers for projection-to-image domain transformation, producing large models requiring substantial computation power, potentially exceeding the computation memory limit. Our previous work proposed a geometry-guided-deep-learning (GDL) technique for CBCT reconstruction that reduces model size and GPU memory consumption. This study further develops the technique and proposes a novel multi-beamlet deep learning (GMDL) technique of improved performance. The study compares the proposed technique with the FC layer-based deep learning (FCDL) method and the GDL technique through low-dose real-patient CT image reconstruction. <jats:italic>Methods</jats:italic>. Instead of using a large FC layer, the GMDL technique learns the projection-to-image domain transformation by constructing many small FC layers. In addition to connecting each pixel in the projection domain to beamlet points along the central beamlet in the image domain as GDL does, these smaller FC layers in GMDL connect each pixel to beamlets peripheral to the central beamlet based on the CT projection geometry. We compare ground truth images with low-dose images reconstructed with the GMDL, the FCDL, the GDL, and the conventional FBP methods. The images are quantitatively analyzed in terms of peak-signal-to-noise-ratio (PSNR), structural-similarity-index-measure (SSIM), and root-mean-square-error (RMSE). <jats:italic>Results</jats:italic>. Compared to other methods, the GMDL reconstructed low-dose CT images show improved image quality in terms of PSNR, SSIM, and RMSE. The optimal number of peripheral beamlets for the GMDL technique is two beamlets on each side of the central beamlet. The model size and memory consumption of the GMDL model is less than 1/100 of the FCDL model. <jats:italic>Conclusion</jats:italic>. Compared to the FCDL method, the GMDL technique is demonstrated to be able to reconstruct real patient low-dose CT images of improved image quality with significantly reduced model size and GPU memory requirement.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>A bolus is a material equivalent to soft tissue and is directly placed on the skin surface during radiotherapy. It is commonly used to increase the dose on the skin surface in electron beam radiation. A typical material for a bolus is silicone rubber (SR). We made a bolus with dimensions of 17 × 17 × 1 cm<jats:sup>3</jats:sup> by varying silicone rubber (SR) RTV 52 and hardening material (bluesil catalyst 60 R) using a simple molded method. We characterized it using a CT scan to find the relative electron density (RED) and examined it using the electron beam of a linear accelerator (LINAC) at energies of 5 and 7 MeV to investigate the percentage of surface dose (PSD). The PSD value is relative to the dose at maximum doses (d<jats:sub>max</jats:sub>). The RED value of the bolus was from 1.168 ± 0.021 to 1.176 ± 0.019, higher than the soft tissue (muscle) value of 1.043. The percentage of surface dose (PSD) test at 5 and 7 MeV LINAC energy showed that the highest PSD without using a bolus were 84.79 <jats:inline-formula> <jats:tex-math> <?CDATA $\pm \,$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>±</mml:mo> <mml:mspace width=".25em" /> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexac6f24ieqn1.gif" xlink:type="simple" /> </jats:inline-formula>0.06% and 86.03 <jats:inline-formula> <jats:tex-math> <?CDATA $\pm \,$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>±</mml:mo> <mml:mspace width=".25em" /> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexac6f24ieqn2.gif" xlink:type="simple" /> </jats:inline-formula>0.07%, respectively. With a bolus, the PSD values were 112.52 <jats:inline-formula> <jats:tex-math> <?CDATA $\pm \,$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>±</mml:mo> <mml:mspace width=".25em" /> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexac6f24ieqn3.gif" xlink:type="simple" /> </jats:inline-formula>0.16% and 111.14 <jats:inline-formula> <jats:tex-math> <?CDATA $\pm \,$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>±</mml:mo> <mml:mspace width=".25em" /> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexac6f24ieqn4.gif" xlink:type="simple" /> </jats:inline-formula>0.03%, respectively. The results indicate that bolus fabrication using SR RTV 52 and bluesil 60R is very effective for radiotherapy in the treatment of skin cancer due to an increase in surface dose.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The transport of gases across cell membranes plays a key role in many different cell functions, from cell respiration to pH control. Mathematical models play a central role in understanding the factors affecting gas transport through membranes, and are the tool needed for testing the novel hypothesis of the preferential crossing through specific gas channels. Since the surface pH of cell membrane is regulated by the transport of gases such as CO<jats:sub>2</jats:sub> and NH<jats:sub>3</jats:sub>, inferring the membrane properties can be done indirectly from pH measurements. Numerical simulations based on recent models of the surface pH support the hypothesis that the presence of a measurement device, a liquid-membrane pH sensitive electrode on the cell surface may disturb locally the pH, leading to a systematic bias in the measured values. To take this phenomenon into account, it is necessary to equip the model with a description of the micro-environment created by the pH electrode. In this work we propose a novel, computationally lightweight numerical algorithm to simulate the surface pH data. The effect of different parameters of the model on the output are investigated through a series of numerical experiments with a physical interpretation.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The titanium alloy composition and microdesign affect the dynamic interplay between the bone cells and titanium surface in the osseointegration process. The current study aimed to evaluate the surface physicochemical properties, electrochemical stability, and the metabolic response of the MC3T3-E1 cells (pre-osteoblast cell line) cultured onto titanium-15molybdenum (Ti-15Mo) discs treated with phosphoric acid (H<jats:sub>3</jats:sub>PO<jats:sub>4</jats:sub>) and sodium hydroxide (NaOH) and/or strontium-loading by the hydrothermal method. The x-ray dispersive energy spectroscopy (EDS) and x-ray diffraction (XRD) analysis showed no trace of impurities and the possible formation of hydrated strontium oxide (H<jats:sub>2</jats:sub>O<jats:sub>2</jats:sub>Sr), respectively. The confocal laser microscopy (CLSM) analysis indicated that titanium samples treated with strontium (Sr) showed greater surface roughness. The acid/alkali treatment prior to the hydrothermal Sr deposition improved the surface free energy and resistance to corrosion of the Ti-15Mo alloy. The acid/alkali treatment also provided greater retention of the Sr particles on the Ti-15Mo surfaces accordingly with inductively coupled plasma optical emission spectrometry (ICP-OES) analysis. The AlamarBlue and fluorescence analysis indicated noncytotoxic effects against the MC3T3-E1 cells, which allowed cells’ adhesion and proliferation, with greater cells’ spreading in the Sr-loaded Ti-15Mo samples. These findings suggest that Sr deposition by the hydrothermal method has the potential to enhance the physicochemical properties of the Ti-15Mo previously etched with H<jats:sub>3</jats:sub>PO<jats:sub>4</jats:sub> and NaOH, and also improve the initial events related to cell-mediated bone deposition.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Although commercial treatment planning systems (TPSs) can automatically solve the optimization problem for treatment planning, human planners need to define and adjust the planning objectives/constraints to obtain clinically acceptable plans. Such a process is labor-intensive and time-consuming. In this work, we show an end-to-end study to train a deep reinforcement learning (DRL) based virtual treatment planner (VTP) that can behave like a human to operate a dose-volume constrained treatment plan optimization engine following the parameters used in Eclipse TPS for high-quality treatment planning. We considered the prostate cancer IMRT treatment plan as the testbed. The VTP took the dose-volume histogram (DVH) of a plan as input and predicted the optimal strategy for constraint adjustment to improve the plan quality. The training of VTP followed the state-of-the-art Q-learning framework. Experience replay was implemented with epsilon-greedy search to explore the impacts of taking different actions on a large number of automatically generated plans, from which an optimal policy can be learned. Since a major computational cost in training was to solve the plan optimization problem repeatedly, we implemented a graphical processing unit (GPU)-based technique to improve the efficiency by 2-fold. Upon the completion of training, the established VTP was deployed to plan for an independent set of 50 testing patient cases. Connecting the established VTP with the Eclipse workstation via the application programming interface, we tested the performance the VTP in operating Eclipse TPS for automatic treatment planning with another two independent patient cases. Like a human planner, VTP kept adjusting the planning objectives/constraints to improve plan quality until the plan was acceptable or the maximum number of adjustment steps was reached under both scenarios. The generated plans were evaluated using the ProKnow scoring system. The mean plan score (± standard deviation) of the 50 testing cases were improved from 6.18 ± 1.75 to 8.14 ± 1.27 by the VTP, with 9 being the maximal score. As for the two cases under Eclipse dose optimization, the plan scores were improved from 8 to 8.4 and 8.7 respectively by the VTP. These results indicated that the proposed DRL-based VTP was able to operate the in-house dose-volume constrained TPS and Eclipse TPS to automatically generate high-quality treatment plans for prostate cancer IMRT.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Attenuation correction aims to recover the underestimated tracer uptake and improve the image contrast recovery in positron emission tomography (PET). However, traditional ray-tracing-based projection of attenuation maps is inaccurate as some physical effects are not considered, such as finite crystal size, inter-crystal penetration and inter-crystal scatter. In this study, we evaluated the effects of applying resolution modeling (RM) to attenuation correction by implementing space-variant RM to complement physical effects which are usually omitted in the traditional projection model. We verified this method on a brain PET scanner developed by our group, in both Monte Carlo simulation and real-world data, in comparison with space-invariant Gaussian RM, average-depth-of-interaction, and multi-ray tracing methods. The results indicate that the space-variant RM is superior in terms of artifacts reduction and contrast recovery.</jats:p>