Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Prostate cancer surgery risks erectile problems and incontinence for the patient. An instrument for guiding surgeons to avoid nerve bundle damage and ensure complete cancer removal is desirable. We present a tactile resonance sensor made of PZT ceramics, mounted in a 3D motorized translation stage for scanning and measuring tissue stiffness for detecting cancer in human prostate. The sensor may be used during surgery for guidance, scanning the prostate surface for the presence of cancer, indicating migration of cancer cells into surrounding tissue. Ten fresh prostates, obtained from patients undergoing prostate cancer surgery, were cut into 0.5 cm thick slices. Each slice was measured for tissue stiffness at about 25 different sites and compared to histology for validation cancer prediction by stiffness. The statistical analysis was based on a total of 148 sites with non-cancer and 40 sites with cancer. Using a generalized linear mixed model (GLMM), the stiffness data predicted cancer with an area under the curve of 0.74, after correcting for overfitting using bootstrap validation. Mean prostate stiffness on the logarithmic scale (p = 0.015) and standardized Z-scores (p = 0.025) were both significant predictors of cancer. This study concludes that stiffness measured by the tactile resonance sensor is a significant predictor of prostate cancer with potential for future development towards a clinical instrument for surgical guidance.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The aim of this paper is to present the use of a portable, unshielded magnetocardiograph (MCG) and identify key characteristics of MCG scans that could be used in future studies to identify parameters that are sensitive to cardiac pathology. We recruited 50 patients with confirmed myocardial infarction (MI) within the past 12 weeks and 46 volunteers with no history of cardiac disease. A set of 38 parameters were extracted from MCG features including both signals from the sensor array and from magnetic images obtained from the device and principal component analysis was used to concentrate the information contained in these parameters into uncorrelated predictors. Linear fits of these parameters were then used to examine the ability of MCG to distinguish between sub-groups of patients. In the first instance, the primary aim of this study was to ensure that MCG has a basic ability to separate a highly polarised patient group (young controls from post infarction patients) and to identify parameters that could be used in future studies to build a formal diagnostic tool kit. Parameters that parameterised left ventricular ejection fraction (LVEF) were identified and an example is presented to show differential low and high ejection fractions.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose</jats:italic>: Estimate organs doses (ODs) of patients subjected to unenhanced (S1) and enhanced (S2) chest CT studies relying on image parameters such as Hounsfield Units (HUs). <jats:italic>Materials and Methods</jats:italic>: CT scans and images of a total of 16 patients who underwent two series of chest CT studies were obtained and retrospectively examined. OD increments of liver and pancreas for both series (S1 &amp; S2) were estimated using two different independent methods, namely simulation approach using CT-EXPO and Amato’s phantom-based fitting model (APFM). HUs were quantified for each organ by manually drawing fixed area-sized regions of interest (ROIs). The mean HUs were collected to obtain the ODs increments following APFM. Regression analysis was applied to find and assess the relationship between the HUs and the OD increments estimated using APFM and that using CT-EXPO. Spearman Coefficient and Wilcoxon Matched Paired <jats:italic>t-test</jats:italic> were conducted to show statistical correlation and difference between ODs increments using the two methods. <jats:italic>Results:</jats:italic> A strong significant difference was depicted between S1 and S2 scan series of liver and pancreas using CT-EXPO simulation. Mean HU values for S1 were lower than S2, resulting in statistically significant (p &lt; 0.0001) HU changes. CT-EXPO simulation yielded significantly higher difference in ODs compared to the APFM for liver (p = 0.0455) and pancreas (p = 0.0031). Regression analysis revealed a strong relationship between HU of S1 and S2 and ODs increments using APFM in both organs (<jats:italic>R</jats:italic> <jats:sup> <jats:italic>2</jats:italic> </jats:sup> = 0.99), dissimilar to CT-EXPO (<jats:italic>R</jats:italic> <jats:sup> <jats:italic>2</jats:italic> </jats:sup>= 0.39 in liver and <jats:italic>R</jats:italic> <jats:sup> <jats:italic>2</jats:italic> </jats:sup>= 0.05 in pancreas). <jats:italic>Conclusions</jats:italic>: Although CT-EXPO allows for estimating ODs accounting for major acquisition scan parameters, it is not a reliable tool to evaluate the impact of contrast enhancement on ODs. On the other hand, the APFM accounts for contrast enhancement accumulation yet only provides relative OD increments, an information of limited clinical use.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Background and purpose.</jats:italic> Replacing CT imaging with MR imaging for MR-only radiotherapy has sparked the interest of many scientists and is being increasingly adopted in radiation oncology. Although many studies have focused on generating CT images from MR images, only models on data with the same dataset were tested. Therefore, how well the trained model will work for data from different hospitals and MR protocols is still unknown. In this study, we addressed the model generalization problem for the MR-to-CT conversion task. <jats:italic>Materials and methods.</jats:italic> Brain T2 MR and corresponding CT images were collected from SZSPH (source domain dataset), brain T1-FLAIR, T1-POST MR, and corresponding CT images were collected from The University of Texas Southwestern (UTSW) (target domain dataset). To investigate the model’s generalizability ability, four potential solutions were proposed: source model, target model, combined model, and adapted model. All models were trained using the CycleGAN network. The source model was trained with a source domain dataset from scratch and tested with a target domain dataset. The target model was trained with a target domain dataset and tested with a target domain dataset. The combined model was trained with both source domain and target domain datasets, and tested with the target domain dataset. The adapted model used a transfer learning strategy to train a CycleGAN model with a source domain dataset and retrain the pre-trained model with a target domain dataset. MAE, RMSE, PSNR, and SSIM were used to quantitatively evaluate model performance on a target domain dataset. <jats:italic>Results.</jats:italic> The adapted model achieved best quantitative results of 74.56 ± 8.61, 193.18 ± 17.98, 28.30 ± 0.83, and 0.84 ± 0.01 for MAE, RMSE, PSNR, and SSIM using the T1-FLAIR dataset and 74.89 ± 15.64, 195.73 ± 31.29, 27.72 ± 1.43, and 0.83 ± 0.04 for MAE, RMSE, PSNR, and SSIM using the T1-POST dataset. The source model had the poorest performance. <jats:italic>Conclusions.</jats:italic> This work indicates high generalization ability to generate synthetic CT images from small training datasets of MR images using pre-trained CycleGAN. The quantitative results of the test data, including different scanning protocols and different acquisition centers, indicated the proof of this concept.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose</jats:italic>. In this study, Monte Carlo (MC) simulations were done to relate the dose-response of the film to that in water. The effect of backscattering materials (PMMA, lead, polystyrene, and air) was investigated on its influence on film density for radionuclides including Am-241, Tc-99m, I-131, Cs-137. <jats:italic>Methods</jats:italic>. A BEAMnrc MC simulation was designed to score a phase-space file (PSF) below the container of the radionuclide under consideration to use as an input file for the subsequent DOSXYZnrc MC simulation. The geometry of the container holding the radionuclide was built using the component modules available in BEAMnrc. BEAMDP was used to investigate the container effect on the radionuclide spectrum as well as the fluence. The DOSXYZnrc simulation produced the absorbed dose in XR-QA2 and RT-QA2 Gafchromic<jats:sup>TM</jats:sup> films. The DOSXYZnrc simulations were repeated for the Gafchromic<jats:sup>TM</jats:sup> film now replaced with water to get the absorbed dose in water. From these results, conversion factors for the dose in water to the film dose for the different radionuclides, Am-241, Tc-99m, I-131, and Cs-137 were obtained. The actual film dose was calculated using the specific gamma exposure constant (Γ) at a distance of 50 cm for a point source approximation. From the BEAMnrc simulations, the particle fluence was extracted from PSFs to correct for the fluence at 0.1 cm below the sources from the fluence 50 cm away since the inverse square law will not apply to finite-size sources. The absorbed dose profiles in the film were compared to the absorbed dose profiles from the MC simulations. <jats:italic>Results</jats:italic>. A fitting function based on the neutron depletion model fits the optical density versus absorbed film dose data well and can be used as a calibration tool to obtain the film dose from its optical density. Lead as a backscatter material results in a higher optical density change but a lower absorbed dose. The XR-QA2 Gafchromic<jats:sup>TM</jats:sup> film is more sensitive than the RT-QA2 Gafchromic<jats:sup>TM</jats:sup> film, showing a more responsive optical density (OD) change in the energy range of radionuclides used in this study. Conversion factors were determined to convert the dose in water to the dose in Gafchromic<jats:sup>TM</jats:sup> film. The Am-241 and I-131 simulated absorbed dose in the film to dose in water does not fluctuate as much as the simulated absorbed dose in film and water when using Tc-99m and Cs-137. Validation was shown for the comparison of the film and MC simulation absorbed dose profiles. <jats:italic>Conclusions</jats:italic>. MC BEAMnrc simulations are useful to simulate radionuclides and their containers. BEAMDP extracted energy spectra showed that the radionuclide containers produced a Compton effect on the energy spectra and added filtration on the lower spectral photon components. Extracted fluence ratios from PSFs were used to calculate the absorbed dose value at 0.1 cm distance from the source. By using the fit function, the dose in the film can be determined for known optical density values. The effect of the backscatter materials showed that the XR-QA2 Gafchromic<jats:sup>TM</jats:sup> film results in higher optical density values than the RT-QA2 Gafchromic<jats:sup>TM</jats:sup> film. The absorbed dose in both the films is comparable but not for a radionuclide such as Am-241 with an activity of 74MBq. The lead backscatter material showed to be the most prominent in optical density enhancement, and the air equivalent material was the least prominent. The XR-QA2 Gafchromic<jats:sup>TM</jats:sup> film is the most sensitive and will be the best option if working with low energies. The absorbed dose in the XR-QA2 Gafchromic<jats:sup>TM</jats:sup> film also showed a good comparison to the absorbed dose in water for the Am-241 radionuclide with an activity of 74MBq. The absorbed dose in the films compares well to the MC simulated doses.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In this work we introduce a technique to speed up the interpretation of bone scans with the aim of determining the presence or absence of metastatic disease. We use gray tone histograms, resembling the use of band-pass filters, in order to ensure a reliable interpretation of the bone scan, therefore providing an accurate diagnosis. We draw particular attention to three cases. The first case corresponds to shifted histograms. If the histogram is shifted toward the origin, the bone scan is free of metastasis. If it is shifted to the right and slightly broadened, this indicates the presence of a bone scan anomaly other than metastasis. On the other hand, if the histogram is broadened and shifted to the left, this suggests the presence of metastatic disease. The second case corresponds to a histogram with noticeable fluctuations, indicating the presence of metastasis. Such fluctuations could become local maxima peaks, indicating the advance of the metastasis. The third case corresponds to the false color results, displayed in terms of the gray tones, observed in the histogram. Such false color is assigned from the construction of a 7-color palette and is selected in terms of the gray tones range. This eases the ad hoc false color assignation for visualization purposes. The final diagnosis is carried out in terms of the color, geometry, extension, and location of the region of interest in the images. Our proposed technique has the potential to be used in high-demand oncology centers due to its simplicity and diagnostic efficiency, confirmed and tested by specialists in the Centro Medico Siglo XXI (XXI Century Medical Center), CDMX-México.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Logan graphical analysis (LGA) is a method for <jats:italic>in vivo</jats:italic> quantification of tracer kinetics in positron emission tomography (PET). The shortcoming of LGA is the presence of a negative bias in the estimated parameters for noisy data. Various approaches have been proposed to address this issue. We recently applied an alternative regression method called least-squares cubic (LSC), which considers the errors in both the predictor and response variables to estimate the LGA slope. LSC reduced the bias in non-displaceable binding potential estimates while causing slight increases in the variance. In this study, we combined LSC with a principal component analysis (PCA) denoising technique to counteract the effects of variance on parametric image quality, which was assessed in terms of the contrast between gray and white matter. Tissue time–activity curves were denoised through PCA, prior to estimating the regression parameters using LSC. We refer to this approach as LSC–PCA. LSC–PCA was assessed against OLS–PCA (PCA with ordinary least-squares (OLS)), LSC, and conventional OLS-based LGA. Comparisons were made for simulated <jats:sup>11</jats:sup> C-carfentanil and <jats:sup>11</jats:sup>C Pittsburgh compound B (<jats:sup>11</jats:sup>C-PiB) data, and clinical <jats:sup>11</jats:sup> C-PiB PET images. PCA-based methods were compared over a range of principal components, varied by the percentage variance they account for in the data. The results showed reduced variances in distribution volume ratio estimates in the simulations for LSC–PCA compared to LSC, and lower bias compared to OLS–PCA and OLS. Contrasts were not significantly improved in clinical data, but they showed a significant improvement in simulation data —indicating a potential advantage of LSC–PCA over OLS–PCA. The effects of bias reintroduction when many principal components are used were also observed in OLS–PCA clinical images. We therefore encourage the use of LSC–PCA. LSC–PCA can allow the use of many principal components with minimal risk of bias, thereby strengthening the interpretation of PET parametric images.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Geometric distortions in magnetic resonance can introduce significant uncertainties into applications such as radiotherapy treatment planning and need to be assessed as part of a comprehensive quality assurance program. We report the design, fabrication, and imaging of a custom 3D printed unibody MR distortion phantom along with quantitative image analysis. <jats:italic>Methods</jats:italic>: The internal cavity of the phantom is an orthogonal three-dimensional planar lattice, composed of 3 mm diameter rods spaced equidistantly at a 20 mm centre-centre offset repeating along the X, Y, and Z axes. The phantom featured an overall length of 308.5 mm, a width of 246 mm, and a height of 264 mm with lines on the external surface for phantom positioning matched to external lasers. The MR phantom was 3D printed in Nylon-12 using an advancement on traditional selective laser sintering (SLS) (HP Jet Fusion 3D—4200 machine). The phantom was scanned on a Toshiba Aquilion CT scanner to check the integrity of the 3D print and correct for any resultant issues. The phantom was then filled with NiSO<jats:sub>4</jats:sub> solution and scanned on a 3T PET-MR Siemens scanner for selected T1 and T2 sequences, from which distortion vectors were generated and analysed using in-house software written in Python. <jats:italic>Results</jats:italic>: All deviations of the node positions from the print design were less than 1 mm, with an average displacement of 0.228 mm. The majority of the deviations were smaller than the 0.692 mm pixel size for this dataset. <jats:italic>Conclusion</jats:italic>: A customised 3D printed MRI-phantom was successfully printed and tested for assessing geometric distortion on MRI scanners. 3D printed phantoms can be considered for clinics wishing to assess geometric distortions under specific conditions, but require resources for design, fabrication, commissioning, and verification.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Poly(lactic acid) (PLA) and poly(<jats:italic>ε</jats:italic>-caprolactone) (PCL) are two important aliphatic esters known for their biodegradability and bioresorbability properties; the former is stiffer and brittle while the smaller modulus of the latter allows a suitable elongation. The new biomaterials being developed from the blend of these two polymers (PLA and PCL) is opportune due to the reducing interfacial tension between their immiscible phases. In a previous study, PLA/PCL immiscible blend when compatibilized with poly(<jats:italic>ε</jats:italic>-caprolactone-<jats:italic>b</jats:italic>-tetrahydrofuran) resulted in enhanced ductility and toughness no cytotoxic effect in <jats:italic>vitro</jats:italic> tests. There is little published data on the effect of poly(<jats:italic>ε</jats:italic>-caprolactone-<jats:italic>b</jats:italic>-tetrahydrofuran) on PLA and PCL biocompatibility and biodegradability <jats:italic>in vivo</jats:italic> tests. This study focuses on evaluating the behavioral response and polymer-tissue interaction of compatibilized PLA/PCL blend compared to neat PLA implanted via intraperitoneal (IP) and subcutaneous (SC) in male Wistar rats, distributed in four experimental groups: neat PLA, PLA/PCL blend, sham, and control at 2-, 8- and 24-weeks post-implantation (WPI). An open-field test was performed to appraise emotionality and spontaneous locomotor activity. Histopathological investigation using hematoxylin-eosin (H&amp;E) and picrosirius-hematoxylin (PSH) was used to assess polymer-tissue interaction. Modifications in PLA and the PLA/PCL blend’s surface morphology were determined by scanning electron microscopy (SEM). PLA group defecated more often than PLA/PCL rats 2 and 8 WPI. Conjunctive capsule development around implants, cell adhesion, angiogenesis, and giant cells of a foreign body to the biomaterial was observed in light microscopy. Both groups displayed a fibrous reaction along with collagen deposition around the biomaterials. In the SEM, the images showed a higher degradation rate for the PLA/PCL blend in both implantation routes. The polymers implanted via IP exhibited a higher degradation rate compared to SC. These findings emphasize the biocompatibility of the PLA/PCL blend compatibilized with poly(<jats:italic>ε</jats:italic>-caprolactone-<jats:italic>b</jats:italic>-tetrahydrofuran), making this biopolymer an acceptable alternative in a variety of biomedical applications.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Magnetocardiograms (MCG) provide clinically useful diagnostic information in a variety of cardiac dysfunctions. Low frequency baseline drifts and high frequency noise are inevitably present in routine MCG even for those measured inside magnetically shielded rooms. These interferences sometimes exceed subtle cardiac features in MCG recorded on subjects with implanted devices like cardiac pacemakers; this makes interpretation of cardiac magnetic fields difficult. The present study proposes a correlation-based beat-by-beat approach and principal component analysis to eliminate drifts and high frequency noise respectively; the approach is suitable for denoising both single and multi-channel MCG data. The methodology is critically evaluated on simulated noisy measurements using a 37 channel MCG system, when objects such as implantable permanent pacemaker and stainless-steel wire are sequentially kept externally on the chests of five healthy subjects. By characterizing the noise introduced by each of these objects, the deterioration in the quality of MCG and its subsequent restoration by using the proposed method is assessed. The performance of the proposed method is also compared with other conventional denoising techniques namely, bandpass filters, wavelets and ensemble empirical mode decomposition. The proposed method not only exhibits least distortion, but also preserves the beat-by-beat dynamics of cardiac time series. The method has also been illustrated on actual MCG measurements on two subjects with implanted pacemaker which highlight the ability of the proposed method for denoising MCG in general and during extremely noisy measurement situations.</jats:p>