Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>A numerical analysis of specific absorption rate (SAR) and temperature distributions in a realistic human head model is presented in this study. The key challenge is to rise cancer temperature to an optimal temperature without heating nearby healthy tissues. The model’s uniqueness is that it captures the effect of nanoparticles on both brain cancer diagnosis and treatment. A realistic human head model with a cancerous brain segmented from 2D magnetic resonance imaging (MRI) gained from an actual patient using 3D Slicer, modeled, and simulated using CST-Microwave Studio, and illuminated by Archimedes spiral antenna. At frequencies of 2450 MHz and 915 MHz, the model simulated the absence and presence of various nanoparticles. The obtained results suggest that when using nanoparticles, it is possible to achieve sufficient energy deposition and temperature rise to therapeutic values (greater than 42 °C) in brain cancers using the proposed noninvasive hyperthermia system at 915 MHz frequency, especially for gold nanoparticles, without harming surrounding healthy tissue. Our research might pave the way for a clinical applicator prototype that can heat brain cancer.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Computer aided diagnostics often requires analysis of a region of interest (ROI) within a radiology scan, and the ROI may be an organ or a suborgan. Although deep learning algorithms have the ability to outperform other methods, they rely on the availability of a large amount of annotated data. Motivated by the need to address this limitation, an approach to localisation and detection of multiple organs based on supervised and semi-supervised learning is presented here. It draws upon previous work by the authors on localising the thoracic and lumbar spine region in CT images. The method generates six bounding boxes of organs of interest, which are then fused to a single bounding box. The results of experiments on localisation of the Spleen, Left and Right Kidneys in CT Images using supervised and semi supervised learning (SSL) demonstrate the ability to address data limitations with a much smaller data set and fewer annotations, compared to other state-of-the-art methods. The SSL performance was evaluated using three different mixes of labelled and unlabelled data (i.e. 30:70,35:65,40:60) for each of lumbar spine, spleen left and right kidneys respectively. The results indicate that SSL provides a workable alternative especially in medical imaging where it is difficult to obtain annotated data.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>MOSFET dosimeters have widely been used to measure radiation doses caused by x-rays. When using the MOSFET dosimeters, calibration factors (CFs) have a direct effect on reliability of dose measurements. The aim of this paper was to study the effect of various calibration methods on the CFs of the MOSFET dosimeters. The CFs were measured on clinical digital x-ray angiography (XA) and computed tomography (CT) devices using a calibrated CT ionization chamber and a standard polymethyl methacrylate (PMMA) phantom. The measurements were conducted by having the dosimeters (1) in air, (2) on the surface of the PMMA phantom and (3) inside the phantom. A statistically significant difference was seen between the CFs measured on the XA and CT devices. The CFs measured on the CT device were 20%–165% higher than those measured with the XA device (p &lt; 0.001) in every calibration geometry. Furthermore, the calibration geometry had a notable effect on the CFs on CT. The CFs on the surface of the phantom were 18%–25% higher than in air (p &lt; 0.05), and the CFs inside the phantom were 32%–39% smaller than in air (p &lt; 0.05). These results suggest that the calibration of the MOSFET dosimeters should be conducted with the same device that is used in actual dose measurements. Also, the scattering conditions and the calibration geometry should be similar in the calibration and subsequent dose measurements.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Implants used in total hip replacements (THR) exhibit high failure rates and up to a decade of operational life. These surgical failures could be mainly attributed to the improper positioning, post-surgical stability and loading, of the implants during different phases of the gait. Typically, revised surgeries are suggested within a few years of hip implantation, which requires multiple femoral drilling operations to remove an existing implant, and to install a new implant. The pain and trauma associated with such procedures are also challenging with the existing hip implants. In this work, we designed a novel corrugated hip implant with innovative dimensioning as per ASTM standards, and grooves for directed insertion and removal (using a single femoral drilling and positioning operation). Biocompatible titanium alloy (Ti6Al4V) was chosen as the implant material, and the novel implant was placed into a femur model through a virtual surgery to study its stability and loading during a dynamic gait cycle. A detailed mesh convergence study was conducted to select a computationally accurate finite element (FE) mesh. Tight fit and frictional fit attachment conditions were simulated, and the gait induced displacements and stresses on the implant, cortical and cancellous bone sections were characterized. During walking, the implant encountered the maximum von-Mises stress of 254.97 MPa at the femoral head. The analyses indicated low micro-motions (i.e., approximately 7 <jats:italic>μ</jats:italic>m) between the femur and implant, low stresses at the implant and bone within elastic limits, and uniform stress distribution, which unlike existing hip implants, would be indispensable for bone growth and implant stability enhancement, and also for reducing implant wear.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In skin cancer diagnosis and treatment, one of the key factors is tumor depth, which is connected to the severity and the required excision depth. Optoacoustical (OA) imaging is a relatively popular technique that provides information based on the optical absorption of the sample. Although often demonstrated with <jats:italic>ex vivo</jats:italic> measurements or <jats:italic>in vivo</jats:italic> imaging on parts of small animals, <jats:italic>in vivo</jats:italic> measurements on humans are more challenging. This is presumably because it is too time consuming and the required excitation pulse energies and their number exceed the allowed maximum permissible exposure (MPE). Here, we demonstrate thickness measurements with a transparent optoacoustical detector of different suspicious skin lesions <jats:italic>in vivo</jats:italic> on patients. We develop the signal processing technique to automatically convert the raw signal into thickness via deconvolution with the impulse response function. The transparency of the detector allows optical excitation with the pulsed laser to be performed perpendicularly on the lesion, in contrast to the conventional illumination from the side. For validation, the measured results were compared to the histological thickness determined after excision. We show that this simple transparent detector allows to determine the thickness of a lesion and thus, aid the dermatologist to estimate the excision depth in the future.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The relative biological efficiency of particle irradiation could be predicted with a wide variety of radiobiological models for various end-points. We validate the forecast of modified Microdosimetric Kinetic Model <jats:italic>in vitro</jats:italic> using combined data of reference Co-60 radiation and carbon ion plateau data for specific cell line to optimize the survival function in spread-out Bragg Peak obtained with an especially designed ridge filter. We used Geant4 Monte-Carlo software to simulate the fragment contribution along Bragg curve inside water phantom, open-source toolkit Survival to predict the expected linear-quadratic model parameters for each fragment, and in-house software to form the total survival curve in spread-out Bragg Peak. The irradiation was performed at U-70 synchrotron with an especially designed Aluminum ridge filter under the control of PTW and in-house ionization chambers. The cell clonogenic assay was conducted with the B14–150 cell line. The data analysis was accomplished using scipy and CERN ROOT. The clonogenic assay represents the survival in spread-out Bragg Peak at different points and qualitatively follows the modeled survival curve very well. The quantitative difference is within 3<jats:italic>σ</jats:italic>, and the deviation might be explained by the uncertainties of physical modeling using Monte-Carlo methods. Overall, the obtained results are promising for further usage in radiobiological studies or carbon ion radiotherapy. Shaping the survival curve in the region of interest (i.e., spread-out Bragg Peak) is a comprehensive task that requires high-performance computing approaches. Nevertheless, the method’s potential application is related to the development of next-generation treatment planning systems for ion beams. This can open a wide range of improvements in patient treatment outcome, provide new optimized fractionation regimes or optimized dose delivery schemes, and serve as an entrance point to the translational science approach.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Objective</jats:italic>. To quantify the benefit of adaptive radiotherapy over non-adaptive radiotherapy it is useful to extract and compare dosimetric features of patient treatments in both scenarios. This requires Image-Guided Radiotherapy (IGRT) matching of baseline planning to adaptive fraction imaging, followed by extraction of relevant dose metrics. This can be impractical to retrospectively perform manually for multiple patients. <jats:italic>Approach</jats:italic>. Here we present an algorithm for automatic IGRT matching of baseline planning with fraction imaging and performing automated dosimetric feature extraction from adaptive and non-adaptive treatment plans, thereby allowing comparison of the two scenarios. This workflow can be done in an entirely automated way via scripting solutions given structure and dose Digital Imaging and Communications in Medicine (DICOM) files from baseline and adaptive fractions. We validate this algorithm against the results of manual IGRT matching. We also demonstrate automated dosimetric feature extraction. Lastly, we combine these two scripting solutions to extract daily adaptive and non-adaptive radiotherapy dosimetric features from an initial cohort of patients treated on an MRI guided linear accelerator (MR-LINAC). <jats:italic>Results.</jats:italic> Our results demonstrate that automated feature extraction and IGRT matching was successful and comparable to results performed by a manual operator. We have therefore demonstrated a method for easy analysis of patients treated on an adaptive radiotherapy platform. <jats:italic>Significance.</jats:italic> We believe that this scripting solution can be used for quantifying the benefits of adaptive therapy and for comparing adaptive therapy against various non-adaptive IGRT scenarios (e.g. 6 degree of freedom couch rotation).</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose</jats:italic>. The radiology department faces a large number of reconstruction algorithms and kernels during their computed tomography (CT) optimization process. These reconstruction methods are proprietary and ensuring consistent image quality between scanners is becoming increasingly difficult. This study contributes to solving this challenge in CT image quality harmonization by modifying and evaluating a reconstruction algorithm and kernel matching scheme. <jats:italic>Methods</jats:italic>. The Catphan 600 phantom was scanned with six different CT scanners from four vendors. The phantom was scanned with volumetric CT dose indices (CTDIvols) of 10 mGy and 40 mGy, and the data were reconstructed using 1 mm and 5 mm slices with each combination of reconstruction algorithm, body region kernel, and iterative and deep learning reconstruction strength. A matching scheme developed in previous research, which utilizes the noise power spectrum (NPS) and modulation transfer function (MTF), was modified based on our organization’s needs and used to identify the matching reconstruction algorithms and kernels between different scanners. <jats:italic>Results</jats:italic>. The matching paradigm produced good matching results, and the mean ± standard deviation (median) matching function values for the different acquisition settings were (a value of 1 indicates a perfect match): CTDIvol 10 mGy, 1 mm slice: 0.78 ± 0.31 (0.94); CTDIvol 10 mGy, 5 mm slice: 0.75 ± 0.33 (0.93); CTDIvol 40 mGy, 1 mm slice: 0.81 ± 0.28 (0.95); CTDIvol 40 mGy, 5 mm slice: 0.75 ± 0.33 (0.93). In general, soft reconstruction kernels, i.e., noise-reducing kernels that reduce sharpness, of one vendor were matched with the soft kernels of another vendor, and vice versa for sharper kernels. Conclusions. Combined quantitative assessment of NPS and MTF allows effective strategy for harmonization of technical image quality between different CT scanners. A software was also shared to support CT image quality harmonization in other institutions.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose</jats:italic>. This work introduces and evaluates a method for accurate in-vitro measurement of fluorescent cell burden in complex 3D-culture conditions. <jats:italic>Methods.</jats:italic> The Fluorescent Cell Burden (FCB) method was developed to analyze the burden of 4T1 mCherry-expressing cells grown in an organotypic co-culture model of brain metastasis using 400 <jats:italic>μ</jats:italic>m rat brain slices. As a first step, representative simulated image-data accurately reflecting the 4T1 experimental data, but with known ground truth burden, were created. The FCB method was then developed in the CellProfiler software to measure the integrated intensity and area of the colonies in the simulated image data. Parameters in the pipeline were varied to span the experimentally observed range (e.g. of cell colony size) and the result compared with simulation ground truth to evaluate and optimize FCB performance. The optimized CellProfiler pipeline was then applied to the original 4T1 tumor cell images to determine colony growth with time, and re-applied with upper and lower bound parameters to determine uncertainty estimates. <jats:italic>Results.</jats:italic> The FCB method measured integrated intensity across 10 simulated images with an accuracy of 99.23% ± 0.75%. When colony density was increased by increasing colony number to 450, 600, and 750, the FCB measurement was 98.68%, 100.9%, 97.6% and 113.5% of the true value respectively. For the increasing number of cells plated on the rat brain slices, the integrated intensity increased nearly linearly with cell count except for at high cell counts, where it is hypothesized that shadowing from clumped cells causes a sub-linear relationship. <jats:italic>Conclusion</jats:italic>. The FCB method accurately measured an integrated fluorescent light intensity to within 5% of ground truth for a wide range of simulated image data spanning the range of observed variability in experimental data. The method is readily customizable to in-vitro studies requiring estimation of fluorescent tumor cell burden.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The use of nanoparticles as biomaterials with applications in the biomedical field is growing every day. These nanomaterials can be used as contrast imaging agents, combination therapy agents, and targeted delivery systems in medicine and dentistry. Usually, nanoparticles are found as synthetic or natural organic materials, such as hydroxyapatite, polymers, and lipids. Besides that, they are could also be inorganic, for instance, metallic or metal-oxide-based particles. These inorganic nanoparticles could additionally present magnetic properties, such as superparamagnetic iron oxide nanoparticles. The use of nanoparticles as drug delivery agents has many advantages, for they help diminish toxicity effects in the body since the drug dose reduces significantly, increases drugs biocompatibility, and helps target drugs to specific organs. As targeted-delivery agents, one of the applications uses nanoparticles as drug delivery particles for bone-tissue to treat cancer, osteoporosis, bone diseases, and dental treatments such as periodontitis. Their application as drug delivery agents requires a good comprehension of the nanoparticle properties and composition, alongside their synthesis and drug attachment characteristics. Properties such as size, shape, core-shell designs, and magnetic characteristics can influence their behavior inside the human body and modify magnetic properties in the case of magnetic nanoparticles. Based on that, many different studies have modified the synthesis methods for these nanoparticles and developed composite systems for therapeutics delivery, adapting, and improving magnetic properties, shell-core designs, and particle size and nanosystems characteristics. This review presents the most recent studies that have been presented with different nanoparticle types and structures for bone and dental drug delivery.</jats:p>