Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Screws made up of non-biodegradable materials (Ti-alloy, etc.) have been used since long for temporary joining/fixation in applications involving skeleton damage or bone fracture. These screws need to be removed after complete healing as their sustained presence results in many complications, such as - micro-fracturing, stress shielding, etc. The removal of these screws is a little difficult too as it may result in the healed bone getting broken/damaged again. These problems can be overcome by employing metallic implants (plate, screws, etc.) made up of biodegradable metallic materials (Mg-alloy, etc.). Such implants exhibit optimal mechanical performance, are biocompatible, have adequate biodegradation rates, and rely on a unique design. Internal fracture fixation makes usage of screws with or without an accompanying plate. Buttress-threaded screws are the most frequently used ones. These screws must have the capacity to bear usually occurring loads and hold fractured segments of bone all through the process of healing. Finite element analysis (FEA) is an effective technique used for testing and validation of desired characteristics for Mg-based biodegradable buttress-threaded screw (BBTS). The characteristics of interest include maximum possible pullout resistance to tightly hold segments of bone, torsional ability for tightening or tapping, bending ability during providing plate support by screw head, and resistance to combined loading (tensile/compressive and bending) during the self-support stage using merely the screw(s). According to test results and subsequent validation through discretization error and convergence plot, BBTS made up of Mg-alloy are found safe for regular applications under usually encountered impact loads. Topological optimization and vibration analysis are also performed wherein it is observed that design of BBTS is good enough for possible usage in fracture fixation in orthopaedics.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Image registration is an inherently ill-posed problem that lacks the constraints needed for a unique mapping between voxels of the two images being registered. As such, one must regularize the registration to achieve physically meaningful transforms. The regularization penalty is usually a function of derivatives of the displacement-vector field and can be calculated either analytically or numerically. The numerical approach, however, is computationally expensive depending on the image size, and therefore a computationally efficient analytical framework has been developed. Using cubic B-splines as the registration transform, we develop a generalized mathematical framework that supports five distinct regularizers: diffusion, curvature, linear elastic, third-order, and total displacement. We validate our approach by comparing each with its numerical counterpart in terms of accuracy. We also provide benchmarking results showing that the analytic solutions run significantly faster—up to two orders of magnitude—than finite differencing based numerical implementations.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Convection-enhanced delivery of rhenium-186 (<jats:sup>186</jats:sup>Re)-nanoliposomes is a promising approach to provide precise delivery of large localized doses of radiation for patients with recurrent glioblastoma multiforme. Current approaches for treatment planning utilizing convection-enhanced delivery are designed for small molecule drugs and not for larger particles such as <jats:sup>186</jats:sup>Re-nanoliposomes. To enable the treatment planning for <jats:sup>186</jats:sup>Re-nanoliposomes delivery, we have developed a computational fluid dynamics approach to predict the distribution of nanoliposomes for individual patients. In this work, we construct, calibrate, and validate a family of computational fluid dynamics models to predict the spatio-temporal distribution of <jats:sup>186</jats:sup>Re-nanoliposomes within the brain, utilizing patient-specific pre-operative magnetic resonance imaging (MRI) to assign material properties for an advection-diffusion transport model. The model family is calibrated to single photon emission computed tomography (SPECT) images acquired during and after the infusion of <jats:sup>186</jats:sup>Re-nanoliposomes for five patients enrolled in a Phase I/II trial (NCT Number NCT01906385), and is validated using a leave-one-out bootstrapping methodology for predicting the final distribution of the particles. After calibration, our models are capable of predicting the mid-delivery and final spatial distribution of <jats:sup>186</jats:sup>Re-nanoliposomes with a Dice value of 0.69 ± 0.18 and a concordance correlation coefficient of 0.88 ± 0.12 (mean ± 95% confidence interval), using only the patient-specific, pre-operative MRI data, and calibrated model parameters from prior patients. These results demonstrate a proof-of-concept for a patient-specific modeling framework, which predicts the spatial distribution of nanoparticles. Further development of this approach could enable optimizing catheter placement for future studies employing convection-enhanced delivery.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Background and Objective: This article describes a fully automatic system for classifying various spinal degenerative phenotypes namely Modic changes, endplate defects and focal changes which are associated with lower back pain. These are obtained from T1/T2 Magnetic Resonance Imaging (MRI) scans. Lower back pain is a predominantly occurring ailment, which is prone to have various roots including the anatomical and pathophysciological aspects. Clinicians and radiologist use MRI to assess and evaluate the extent of damage, cause, and to decide on the future course of treatment. In large healthcare systems, to circumvent the manual reading of various image slices, we describe a system to automate the classification of various vertebral degeneracies that cause lower back pain. Methods: We implement a combination of feature extraction, image analysis based on geometry and classification using machine learning techniques for identifying vertebral degeneracies. Image features like local binary pattern, Hu’s moments and gray level co-occurrence matrix (GLCM) based features are extracted to identify Modic changes, endplate defects, and presence of any focal changes. A combination of feature set is used for describing the extent of Modic change on the end plate. Feature sensitivity studies towards efficient classification is presented. A STIR based acute/chronic classification is also attempted in the current work. Results: The implemented method is tested and validated over a dataset containing 100 patients. The proposed framework for detecting the extent of Modic change achieves an accuracy of 85.91%. From the feature sensitivity analysis, it is revealed that entropy based measure obtained from gray level co-occurrence matrix alone is sufficient for detection of focal changes. The classification performance for detecting endplate defect is highly sensitive to the first 2 Hu’s moments. Conclusion: A novel approach to identify the allied vertebral degenerations and extent of Modic changes in vertebrae by exploiting image features and classification through machine learning is proposed. This shall assist radiologists in detecting abnormalities and in treatment planning.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Type 2 uterine fibroids are challenging to resect surgically as ≥ 50% volume of myoma lies within the myometrium. A hysteroscopic approach for ablating fibroids is minimally-invasive, but places a considerable burden on the operator to accurately place the ablation applicator within the target. We investigated the sensitivity of transcervical microwave ablation outcome with respect to position of the ablation applicator within 1 – 3 cm type 2 fibroids. <jats:italic>Methods:</jats:italic> A finite element computer model was developed to simulate 5.8 GHz microwave ablation of fibroids and validated with experiments in <jats:italic>ex vivo</jats:italic> tissue. The ablation outcome was evaluated with respect to applicator insertion angles (30°, 45°, 60°) , depth and offset from the fibroid center (±2 mm for 3 cm fibroid and ±1 mm for 1 cm fibroid) with 35 W and 15 W applied power for 3 cm and 1 cm fibroids, respectively. Power deposition was stopped when thermal dose of 40 cumulative equivalent minutes at 43 °C (CEM43) was accrued in adjacent myometrium. <jats:italic>Results:</jats:italic> Within the range of all evaluated insertion angles, depths and offsets, the ablation coverage was less sensitive to variation in angle as compared to depth and offset, and ranged from 34.9 – 83.6% for 3 cm fibroid in 140 – 400 s and 34.1 – 67.9% for 1 cm fibroid in 30 – 50 s of heating duration. Maximum achievable ablation coverage in both fibroid cases reach ∼ 90% if thermal dose is allowed to exceed 40 CEM43 in myometrium. <jats:italic>Conclusion:</jats:italic> The study demonstrates the technical feasibility of transcervical microwave ablation for fibroid treatment and the relationship between applicator position within the fibroid and fraction of fibroid that can be ablated while limiting thermal dose in adjacent myometrium.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Accurate detection of key components plays a vital role in determining cardiovascular diseases in the ECG. In this method, we propose an enhanced T-wave delineation method using the phasor transform. Discrete Wavelet Transform (DWT) and median filters were used to suppress the high-frequency noise and baseline drift during pre-processing. The phasor transform was used to detect and locate the delineation points before and after the T-wave. The proposed method was tested on the QTDB for R-peak, T-peak, and T<jats:sub>off</jats:sub> detection. It achieved both sensitivity (Se%) and positive predictivity (+P%) values of 100 for R-peak detection. In T-peak detection, method shows Se % = 99.46 and +P % = 99.54, respectively. This method has reported Se% = 99.34 and +P% = 99.48 for T<jats:sub>off</jats:sub> detection in the ECG. The achieved results show that the method can be used for cardiac arrhythmia detection related to the morphology of T-wave.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Purpose.</jats:italic> To investigate the feasibility of using a single MRI acquisition for fiducial marker identification and synthetic CT (sCT) generation towards MRI-only treatment planning for prostate external beam radiation therapy (EBRT). <jats:italic>Methods.</jats:italic> Seven prostate cancer patients undergoing EBRT, each with three implanted gold fiducial markers, participated in this study. In addition to the planning CT scan, all patients were scanned on a 3 T MR scanner with a 3D double-echo gradient echo (GRE) sequence. Quantitative susceptibility mapping (QSM) was performed for marker localization. QSM-derived marker positions were compared to those from CT. The bulk density assignment technique for sCT generation was adopted. The magnitude GRE images were segmented into muscle, bone, fat, and air using a combination of unsupervised intensity-based classification of soft tissue and convolutional neural networks (CNN) for bone segmentation. <jats:italic>Results.</jats:italic> All implanted markers were visualized and accurately identified (average error: 0.7 ± 0.5 mm). QSM generated distinctive contrast for hemorrhage, calcifications, and gold fiducial markers. The estimated susceptibility/HU values on QSM/CT for gold and calcifications were 31.5 ± 2.9 ppm/1220 ± 100 HU and 14.6 ± 0.9 ppm/440 ± 100 HU, respectively. The intensity-based soft tissue classification resulted in an average Dice score of 0.97 ± 0.02; bone segmentation using CNN resulted in an average Dice score of 0.93 ± 0.03. <jats:italic>Conclusion.</jats:italic> This work indicates the feasibility of simultaneous fiducial marker identification and sCT generation using a single MRI acquisition. Future works includes evaluation of the proposed method in a large cohort of patients with optimized acquisition parameters as well as dosimetric evaluations.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Due to the existing demands for methods independent of patient co-operation in preventing and overcoming the incidence of white spot lesions (WSLs) and caries in fixed orthodontic treatments, several studies have considered the modification of orthodontic composites using antimicrobial nanomaterials. In this regard, the aim of this study is to investigate the effect of the addition of chitosan nanoparticles (NPs) and TiO<jats:sub>2</jats:sub> NPs on <jats:italic>Streptococcus mutans</jats:italic> (<jats:italic>S. mutans</jats:italic>) counts and the enamel mineral content in fixed orthodontic patients. A double-blind randomized clinical trial study was carried out in 24 patients (i.e., 48 upper second premolars and 48 maxillary lateral incisors) who were candidates for fixed orthodontic treatment. In the case of the control group, the bracket was bonded to the tooth with an orthodontic adhesive (Transbond XT, 3M Unitek, USA) while, in the experimental group, the bracket was bonded to the tooth with Transbond XT containing 1% chitosan NPs and 1% TiO<jats:sub>2</jats:sub> NPs. For the maxillary lateral incisor and upper second premolar teeth, the <jats:italic>S. mutans</jats:italic> counts around the brackets were measured, through the usage of real-time PCR, at the time points of 1 day, 2 months, and 6 months after bonding the brackets to the tooth. Furthermore, the enamel mineral content measurement was also performed around the brackets at 1 day, 2 months, and 6 months after bonding the brackets to the tooth. The <jats:italic>S. mutans</jats:italic> counts were analyzed using Friedman and Mann–Whitney U tests. The Repeated measures ANOVA test and Independent samples T-test were also applied, in order to evaluate the mineral content. According to the results, there was a significant reduction in the <jats:italic>S. mutans</jats:italic> counts of experimental group at the time points of 1 day, 2 months, and 6 months in both maxillary lateral incisor and upper second premolar teeth. However, we did not observe any significant differences in the control group between the reports at 1 day, 2 months, and 6 months in both maxillary lateral incisor and upper second premolar teeth. The outcomes of this study indicate that, with regard to maxillary lateral incisor teeth, there were no significant differences between the results of the experimental group and control group at the time points of 1 day, 2 months, and 6 months. Furthermore, with respect to the upper second premolar teeth, no significant differences were observed between the two groups at 1 day and 2 months; however, <jats:italic>S. mutans</jats:italic> counts were significantly lower in the experimental group than in the control group at the time point of 6 months. Moreover, our gathered data confirmed the absence of any significant differences between the experimental group and control group, in terms of enamel mineral content, at the time intervals of 1 day, 2 months, and 6 months. In conclusion, the incorporation of chitosan NPs and TiO<jats:sub>2</jats:sub> NPs in orthodontic composites induces an antibacterial property in the resultant adhesive to be used for fixed orthodontic treatment.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Objective</jats:italic>: Understanding the induced current flow from transcranial direct current stimulation (tDCS) is essential for determining the optimal dose and treatment. Head tissue conductivities play a key role in the resulting electromagnetic fields. However, there exists a complicated relationship between skull conductivity and participant age, that remains unclear. We explored how variations in skull electrical conductivities, particularly as a suggested function of age, affected tDCS induced electric fields. <jats:italic>Approach</jats:italic>: Simulations were employed to compare tDCS outcomes for different intensities across head atlases of varying age. Three databases were chosen to demonstrate differing variability in skull conductivity with age and how this may affect induced fields. Differences in tDCS electric fields due to proposed age-dependent skull conductivity variation, as well as deviations in grey matter, white matter and scalp, were compared and the most influential tissues determined. <jats:italic>Main results</jats:italic>: tDCS induced peak electric fields significantly negatively correlated with age, exacerbated by employing proposed age-appropriate skull conductivity (according to all three datasets). Uncertainty in skull conductivity was the most sensitive to changes in peak fields with increasing age. These results were revealed to be directly due to changing skull conductivity, rather than head geometry alone. There was no correlation between tDCS focality and age. <jats:italic>Significance</jats:italic>: Accurate and individualised head anatomy and <jats:italic>in vivo</jats:italic> skull conductivity measurements are essential for modelling tDCS induced fields. In particular, age should be taken into account when considering stimulation dose to precisely predict outcomes.</jats:p>