Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI

In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented. Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented. The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects. Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2). Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool. Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios. Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively. The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively. Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively. Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain

Hybrid morphological-convolutional neural networks for computer-aided diagnosis

Training deep Convolutional Neural Networks (CNNs) presents challenges in terms of memory requirements and computational resources, often resulting in issues such as model overfitting and lack of generalization. These challenges can only be mitigated by using an excessive number of training images. However, medical image datasets commonly suffer from data scarcity due to the complexities involved in their acquisition, preparation, and curation. To address this issue, we propose a compact and hybrid machine learning architecture based on the Morphological and Convolutional Neural Network (MCNN), followed by a Random Forest classifier. Unlike deep CNN architectures, the MCNN was specifically designed to achieve effective performance with medical image datasets limited to a few hundred samples. It incorporates various morphological operations into a single layer and uses independent neural networks to extract information from each signal channel. The final classification is obtained by utilizing a Random Forest classifier on the outputs of the last neural network layer. We compare the classification performance of our proposed method with three popular deep CNN architectures (ResNet-18, ShuffleNet-V2, and MobileNet-V2) using two training approaches: full training and transfer learning. The evaluation was conducted on two distinct medical image datasets: the ISIC dataset for melanoma classification and the ORIGA dataset for glaucoma classification. Results demonstrate that the MCNN method exhibits reliable performance in melanoma classification, achieving an AUC of 0.94 (95% CI: 0.91 to 0.97), outperforming the popular CNN architectures. For the glaucoma dataset, the MCNN achieved an AUC of 0.65 (95% CI: 0.53 to 0.74), which was similar to the performance of the popular CNN architectures. This study contributes to the understanding of mathematical morphology in shallow neural networks for medical image classification and highlights the potential of hybrid architectures in effectively learning from medical image datasets that are limited by a small number of case samples

Metahabilidades en información y evolución conceptual en la educación virtual

Aunque internacionalmente se ha destacado la importancia que tiene la habilidad para el acceso, uso y distribución de la información en el aprendizaje de nuevos conceptos en un ambiente universitario hace falta fomentar la integración de su instrucción en el currículo e investigar sus alcances didácticos. Por ello, en este estudio de corte mixto-ex-ploratorio se buscó comprender la manera en que el desarrollo de las metahabilidades en información (MTHI) coadyuvan con la evolución conceptual en estudiantes de posgrado virtual, encontrándose elemen-tos instruccionales que muestran cierta relación entre el desarrollo de las MTHI con el desarrollo de conocimientos, además del valor de la participación del profesor bibliotecario como un cotutor que apoye a los alumnos en la adopción y perfeccionamiento de un proceso reflexivo de rastreo informativ

Centennials, ciudadanos globales y digitales

The study sought to learn how centennials communicate the moral and socio-political aspects of their global and digital citizenship. A mixed-exploratory approach with a sequential design was selected for this study. Quantitative and qualitative data were collected in different stages of the research, although they were not dependent on one another. For the quantitative section, which is directly related to the first category intended for research, the population consisted of students from the national high school system, a public high school, and two private high schools located in Nuevo León, Mexico. Convenience sampling was used to determine the population, based on available computer access in the classroom. The final number of participants was 1 696 students, 899 of which were women and 797 were men. It was found that said participants openly communicated their socio-political stance on social networks, and they also value justice and reciprocity more when making moral decisions. For this reason, it is important to raise them so that they can participate actively and properly in a context of global communication.El estudio buscó conocer cómo comunican los centennials su ciudadanía global y digital en los aspectos moral y sociopolítico. El enfoque seleccionado para llevar a cabo este estudio fue el mixto-exploratorio con un diseño secuencial ya que los datos cuantitativos y cualitativos fueron recolectados en distintos momentos de la investigación, aunque no se supeditaron entre sí. Para el apartado cuantitativo, que está directamente relacionado con la primera categoría por investigar, la población estuvo delimitada por estudiantes pertenecientes al Sistema Nacional de Bachillerato, una preparatoria pública y dos preparatorias privadas ubicadas en el estado de Nuevo León, México. La muestra de dicha población fue determinada por conveniencia teniendo como base la disponibilidad de uso del aula de cómputo en los centros educativos para responder al instrumento. El número final de participantes fue de 1 696 estudiantes, de los cuales 899 eran mujeres y 797 eran varones. Se encontró que dichos participantes comunican abiertamente su postura sociopolítica en redes sociales y valoran más la justicia y reciprocidad al tomar decisiones morales, emergiendo la importancia de formarlos para participar adecuada y activamente en un ámbito de comunicación global

LASIK monocular en pacientes adultos con ambliopía por anisometropía

ResumenObjetivoDeterminar la eficacia y la seguridad del LASIK en el tratamiento de la ambliopía por anisometropía en pacientes adultos.MétodosSerie de casos. Estudiamos a 12 pacientes adultos ambliopes por anisometropía a los cuales se realizó LASIK monocular de nuestro servicio de Córnea y Cirugía Refractiva. Evaluamos el error refractivo pre y postoperatorio, equivalente esférico (ES), la agudeza visual sin corrección (AVSC) y la agudeza visual mejor corregida (AVMC). La agudeza visual medida por la cartilla de Snellen fue convertida a LogMAR con fines de análisis estadístico.ResultadosLa edad promedio fue de 31.92 (± 12.13) años. El ES preoperatorio promedio en el ojo tratado fue de –3.49 D (± 3.24), el ES promedio del ojo no tratado fue de 0.25 D (± 0.30). La AVSC preoperatoria fue de 1.12 (± 0.3) LogMAR y la AVMC preoperatoria fue 0.31 (± 0.1) LogMAR. El seguimiento promedio fue de 19.1 (rango 6-74) meses. El ES promedio postoperatorio disminuyó a –0.28 (± 0.48). Cinco pacientes (42%) ganaron una línea de visión, un (8%) paciente ganó 2 líneas de visión y un (8%) paciente ganó 3 líneas de visión. El resto (42%) permaneció sin cambios comparados a la AVMC preoperatoria. Se encontraron diferencias estadísticamente significativas entre la AVSC preoperatoria (1.12 [±0.3]) y la AVSC postoperatoria (0.27 [±0.1]) (p=0.002, Z-Wilcoxon) y entre la AVMC postoperatoria (0.23 [±0.12]) y la AVMC preoperatoria (0.31 [±0.1]) (p=0.014, Z-Wilcoxon). No hubo complicaciones relacionadas con la cirugía.ConclusionesLa cirugía refractiva monocular en pacientes con ambliopía por anisometropía es una opción terapéutica segura y efectiva que ofrece resultados visuales satisfactorios, preservando o incluso mejorando la AVMC preoperatoria.AbstractPurposeTo investigate the efficacy and safety of LASIK for the correction of anisometropic amblyopia in adult patients.MethodsA retrospective, case series. We found 12 amblyopic adult patients that underwent monocular LASIK for anisometropía in our Cornea and Refractive service. We evaluated the preoperative and postoperative refractive error, spherical equivalent (SE), uncorrected visual acuity (UCVA) and best corrected visual acuity (BCVA). Snellen visual acuity measurements were converted to LogMAR for statistical purposes.ResultsThe mean age was 31.92 (±12.13) years. The average preoperative SE in the treated eyes was -3.49 (±3.24), the average SE of the untreated eye was 0.25(±0.30). Preoperative UCVA was 1.12 (±0.3) and average preoperative BCVA was 0.31 (±0.1). All patients had LASIK with an average follow-up time of 19.1(6-74) months. The average postoperative SE decreased to -0.28 (±0.48). Five patients (42%) gained 1 line of vision, 1 (8%) patient gained 2 lines of vision, 1 (8%) patient gained 3 lines of vision and the rest (42%) remained unchanged compared to preoperative BCVA. Statistically significant differences were observed between the preoperative UCVA [1.12 (±0.3)] with the postoperative UCVA [0.27 (±0.1)](p=0.002, Z-Wilcoxon) and between the postoperative BCVA [0.23 (±0.12)] with the preoperative BCVA [0.31 (±0.1)] (p=0.014, Z-Wilcoxon). There were no complications related to the surgical procedures.ConclusionsMonocular refractive surgery in adult patients with anisometropic amblyopia is a safe and effective therapeutic option that offers a satisfactory visual outcome, preserving or even improving the preoperative BCVA

Incorporating Breast Asymmetry Studies into CADx Systems

Breast cancer is one of the global leading causes of death among women, and an early detection is of uttermost importance to reduce mortality rates. Screening mammograms, in which radiologists rely only on their eyesight, are one of the most used early detection methods. However, characteristics, such as the asymmetry between breasts, a feature that could be very difficult to visually quantize, is key to breast cancer detection. Due to the highly heterogeneous and deformable structure of the breast itself, incorporating asymmetry measurements into an automated detection system is still a challenge. In this study, we proposed the use of a bilateral registration algorithm as an effective way to automatically measure mirror asymmetry. Furthermore, this information was fed to a machine learning algorithm to improve the accuracy of the model. In this study, 449 subjects (197 with calcifications, 207 with masses, and 45 healthy subjects) from a public database were used to train and evaluate the proposed methodology. Using this procedure, we were able to independently identify subjects with calcifications (accuracy = 0.825, AUC = 0.882) and masses (accuracy = 0.698, AUC = 0.807) from healthy subjects

Quantitative 3D MRI reveals limited intra-lesional bony overgrowth at1 year after microfracture-based cartilage repair

Objective: Intra-lesional bony overgrowth (BO) identified during or following cartilage repair treatment is being frequently described through subjective reports focusing primarily on incidence. Our objective was to quantify the exact volume of intra-lesional BO at 12 months post-cartilage repair treatment, to determine if a correlation exists between the extent of BO and clinical outcomes, and to visualize and characterize the BO. Design: MRI scans were systematically obtained during a randomized clinical trial for cartilage repair (Stanish etal., 2013) that compared two microfracture-based treatments in 78 patients. Semi-automated morphological segmentation of pre-treatment, 1 and 12 months post-treatment scans utilizing a programmed anatomical atlas for all knee bone and cartilage structures permitted three-dimensional reconstruction, quantitative analysis, as well as qualitative characterization and artistic visualization ofBO. Results: Limited intra-lesional BO representing only 5.8±5.7% of the original debrided cartilage lesion volume was found in 78 patients with available MRIs at 12 months. The majority (80%) of patients had very little BO (<10%). Most occurrences of BO carried either spotty (56.4%) or planar (6.4%) morphological features, and the remaining balance (37.2%) was qualitatively unobservable by eye. Pre-existing BO recurred at 12 months in the same intra-lesional location in 36% of patients. No statistical correlations were found between BO and clinical outcomes. Conclusions: Intra-lesional BO following microfracture-based treatments may not be as severe as previously believed, its incidence is partly explained by pre-existing conditions, and no relationship to clinical outcomes exists at 12 months. Morphologically, observable BO was categorized as comprising either spotty or planar bone. © 2014 Osteoarthritis Research Society International

Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI

In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented. Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented. The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects. Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2). Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool. Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios. Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively. The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively. Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively. Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain. © 2015 Jorge I. Galván-Tejada et al

Improved Diagnostic Multimodal Biomarkers for Alzheimer’s Disease and Mild Cognitive Impairment

The early diagnosis of Alzheimer’s disease (AD) and mild cognitive impairment (MCI) is very important for treatment research and patient care purposes. Few biomarkers are currently considered in clinical settings, and their use is still optional. The objective of this work was to determine whether multimodal and nonpreviously AD associated features could improve the classification accuracy between AD, MCI, and healthy controls, which may impact future AD biomarkers. For this, Alzheimer’s Disease Neuroimaging Initiative database was mined for case-control candidates. At least 652 baseline features extracted from MRI and PET analyses, biological samples, and clinical data up to February 2014 were used. A feature selection methodology that includes a genetic algorithm search coupled to a logistic regression classifier and forward and backward selection strategies was used to explore combinations of features. This generated diagnostic models with sizes ranging from 3 to 8, including well documented AD biomarkers, as well as unexplored image, biochemical, and clinical features. Accuracies of 0.85, 0.79, and 0.80 were achieved for HC-AD, HC-MCI, and MCI-AD classifications, respectively, when evaluated using a blind test set. In conclusion, a set of features provided additional and independent information to well-established AD biomarkers, aiding in the classification of MCI and AD