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Os avanços dos softwares cirúrgicos e de imagem permitiram a introdução do planejamento em ambiente tridimensional virtual em cirurgia ortognática, o qual tem auxiliado os cirurgiões na tomada de decisões. Nesse contexto, o objetivo deste trabalho é ilustrar um caso clínico de um paciente padrão face III assimétrico utilizando os recursos de diagnóstico e planejamento em ambiente virtual. Neste contexto, a evolução do planejamento virtual auxilia o cirurgião em casos complexos, entretanto é necessária uma curva de aprendizado e melhores estudos clínicos independentes, para avançarmos na obtenção de maior previsibilidade dos resultados em planejamentos em cirurgia ortognática em âmbito virtual... (AU)

Advances in surgical and imaging software allowed the introduction of three-dimensional virtual planning in orthognathic surgery, assisting surgeons in decision making. In this context, the objective was to demonstrate a case report of a facial pattern face III asymmetric patient using diagnostic tools and planning in virtual environment. In this context, the evolution of virtual planning helps the surgeon in complex cases, however, a learning curve and better independent clinical studies are necessary to advance in obtaining greater predictability of results in orthognathic surgery planning in a virtual environment... (AU)

Los avances en software quirúrgico y de imagen han permitido introducir la planificación en un entorno virtual tridimensional en cirugía ortognática, lo que ha ayudado a los cirujanos en la toma de decisiones. En este contexto, el objetivo de este trabajo es ilustrar un caso clínico de un paciente con patrón cara III asimétrico utilizando recursos de diagnóstico y planificación en un entorno virtual. En este contexto, la evolución de la planificación virtual ayuda al cirujano en casos complejos, sin embargo, es necesaria una curva de aprendizaje y mejores estudios clínicos independientes para avanzar en la obtención de una mayor previsibilidad de los resultados en la planificación de la cirugía ortognática en un entorno virtual... (AU)

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This study explores the efficacy of texture analysis by using preoperative multi-slice spiral computed tomography (MSCT) to non-invasively determine the grade of cellular differentiation in head and neck squamous cell carcinoma (HNSCC). In a retrospective study, MSCT scans of patients with HNSCC were analyzed and classified based on its histological grade as moderately differentiated, well-differentiated, or poorly differentiated. The location of the tumor was categorized as either in the bone or in soft tissues. Segmentation of the lesion areas was conducted, followed by texture analysis. Eleven GLCM parameters across five different distances were calculated. Median values and correlations of texture parameters were examined in relation to tumor differentiation grade by using Spearman's correlation coefficient and Kruskal-Wallis and Dunn tests. Forty-six patients were included, predominantly female (87%), with a mean age of 66.7 years. Texture analysis revealed significant parameter correlations with histopathological grades of tumor differentiation. The study identified no significant age correlation with tumor differentiation, which underscores the potential of texture analysis as an age-independent biomarker. The strong correlations between texture parameters and histopathological grades support the integration of this technique into the clinical decision-making process.

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PURPOSE: This work aims to assess standard evaluation practices used by the research community for evaluating medical imaging classifiers, with a specific focus on the implications of class imbalance. The analysis is performed on chest X-rays as a case study and encompasses a comprehensive model performance definition, considering both discriminative capabilities and model calibration. MATERIALS AND METHODS: We conduct a concise literature review to examine prevailing scientific practices used when evaluating X-ray classifiers. Then, we perform a systematic experiment on two major chest X-ray datasets to showcase a didactic example of the behavior of several performance metrics under different class ratios and highlight how widely adopted metrics can conceal performance in the minority class. RESULTS: Our literature study confirms that: (1) even when dealing with highly imbalanced datasets, the community tends to use metrics that are dominated by the majority class; and (2) it is still uncommon to include calibration studies for chest X-ray classifiers, albeit its importance in the context of healthcare. Moreover, our systematic experiments confirm that current evaluation practices may not reflect model performance in real clinical scenarios and suggest complementary metrics to better reflect the performance of the system in such scenarios. CONCLUSION: Our analysis underscores the need for enhanced evaluation practices, particularly in the context of class-imbalanced chest X-ray classifiers. We recommend the inclusion of complementary metrics such as the area under the precision-recall curve (AUC-PR), adjusted AUC-PR, and balanced Brier score, to offer a more accurate depiction of system performance in real clinical scenarios, considering metrics that reflect both, discrimination and calibration performance. CLINICAL RELEVANCE STATEMENT: This study underscores the critical need for refined evaluation metrics in medical imaging classifiers, emphasizing that prevalent metrics may mask poor performance in minority classes, potentially impacting clinical diagnoses and healthcare outcomes. KEY POINTS: Common scientific practices in papers dealing with X-ray computer-assisted diagnosis (CAD) systems may be misleading. We highlight limitations in reporting of evaluation metrics for X-ray CAD systems in highly imbalanced scenarios. We propose adopting alternative metrics based on experimental evaluation on large-scale datasets.

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In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and perform classification between Parkinson's disease patients and healthy participants using Machine Learning algorithms. In addition, the proposed approach provides insights into the brain regions affected by the disease. The functional Magnetic Resonance Imaging from the PPMI and 1000-FCP datasets were pre-processed to extract time series from 200 brain regions per participant, resulting in 11,600 features. Causal Forest and Wrapper Feature Subset Selection algorithms were used for dimensionality reduction, resulting in a subset of features based on their heterogeneity and association with the disease. We utilized Logistic Regression and XGBoost algorithms to perform PD detection, achieving 97.6% accuracy, 97.5% F1 score, 97.9% precision, and 97.7%recall by analyzing sets with fewer than 300 features in a population including men and women. Finally, Multiple Correspondence Analysis was employed to visualize the relationships between brain regions and each group (women with Parkinson, female controls, men with Parkinson, male controls). Associations between the Unified Parkinson's Disease Rating Scale questionnaire results and affected brain regions in different groups were also obtained to show another use case of the methodology. This work proposes a methodology to (1) classify patients and controls with Machine Learning and Causal Forest algorithm and (2) visualize associations between brain regions and groups, providing high-accuracy classification and enhanced interpretability of the correlation between specific brain regions and the disease across different groups.

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BACKGROUND: Navigated augmented reality (AR) through a head-mounted display (HMD) has led to accurate glenoid component placement in reverse shoulder arthroplasty (RSA) in an in-vitro setting. The purpose of this study is to evaluate the deviation between planned, intraoperative, and postoperative inclination, retroversion, entry point, and depth of the glenoid component placement during RSA, assisted by navigated AR through an HMD, in a surgical setting. METHODS: A prospective, multicenter study was conducted. All consecutive patients undergoing RSA in 2 institutions, between August 2021 and January 2023, were considered potentially eligible for inclusion in the study. Inclusion criteria were as follows: age >18 years, surgery assisted by AR through an HMD, and postoperative computed tomography (CT) scans at 6 weeks. All participants agreed to participate in the study and informed consent was provided in all cases. Preoperative CT scans were undertaken for all cases and used for 3-dimensional (3D) planning. Intraoperatively, glenoid preparation and component placement were assisted by a navigated AR system through an HMD in all patients. Intraoperative parameters were recorded by the system. A postoperative CT scan was undertaken at 6 weeks, and 3D reconstruction was performed to obtain postoperative parameters. The deviation between planned, intraoperative, and postoperative inclination, retroversion, entry point, and depth of the glenoid component placement was calculated. Outliers were defined as >5° for inclination and retroversion and >5 mm for entry point. RESULTS: Seventeen patients (9 females, 12 right shoulders) with a mean age of 72.8 ± 9.1 years (range, 47.0-82.0) met inclusion criteria. The mean deviation between intra- and postoperative measurements was 1.5° ± 1.0° (range, 0.0°-3.0°) for inclination, 2.8° ± 1.5° (range, 1.0°-4.5°) for retroversion, 1.8 ± 1.0 mm (range, 0.7-3.0 mm) for entry point, and 1.9 ± 1.9 mm (range, 0.0-4.5 mm) for depth. The mean deviation between planned and postoperative values was 2.5° ± 3.2° (range, 0.0°-11.0°) for inclination, 3.4° ± 4.6° (range, 0.0°-18.0°) for retroversion, 2.0 ± 2.5 mm (range, 0.0°-9.7°) for entry point, and 1.3 ± 1.6 mm (range, 1.3-4.5 mm) for depth. There were no outliers between intra- and postoperative values and there were 3 outliers between planned and postoperative values. The mean time (minutes : seconds) for the tracker unit placement and the scapula registration was 03:02 (range, 01:48 to 04:26) and 08:16 (range, 02:09 to 17:58), respectively. CONCLUSION: The use of a navigated AR system through an HMD in RSA led to low deviations between planned, intraoperative, and postoperative parameters for glenoid component placement.

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OBJECTIVES: To evaluate the feasibility of using the pulp volume (Pv) to total volume (Tv) ratio (Pv:Tv), obtained from cone beam computed tomography (CBCT) scans of single-rooted teeth, for age estimation in a Brazilian population sample. METHODS: After obtaining approval from the ethics committee, the study commenced by applying inclusion criteria to screen CBCT scans, resulting in a probability-based sample of participants aged 18 years and older (ranging from 18 to 82 years, with a mean age of 46.44 years). A total of 517 single-rooted teeth, including maxillary central incisors (CI), mandibular canines (C), and mandibular first premolars (FP), were chosen based on excellent agreement values (> 0.9). Pv and Tv measurements were conducted using semi-automatic segmentation with ITK-SNAP 3.8 software. Statistical analysis was performed using Jamovi software, with a significance level set at 5% (α = 0.05). RESULTS: A strong negative correlation (r > -0.7) was observed between chronological age and the Pv:Tv ratio across all examined teeth. However, when conducting regression analysis with Pv:Tv data and chronological age as the independent variable, only the mandibular FP teeth exhibited a normal distribution. The resulting linear model demonstrated moderate predictive value (approximately 64%) in explaining the variance in chronological age, but caution should be exercised when interpreting these findings. CONCLUSIONS: The method of measuring individual tooth volume using CBCT to estimate chronological age via Pv:Tv has been demonstrated as effective and reproducible within the Brazilian population sample.

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OBJECTIVES: The aim of this study is to presents an experimental method for surgical guide confection using an intraoral scanner to obtain a 3D model of the patient's complete denture and compare its accuracy with the conventional methodology using computed tomography. STUDY DESIGN: This prospective in-vitro study used 30 polyurethane pre-manufactured mandibles which were divided into two groups, conventional technique (group I) and a new method using intraoral scanner (group II), establishing the virtually planned position of the dental implants as a control group, considered as the gold standard for postoperative comparison. RESULTS: The difference between these methods is close to zero and not statistically significant (p > 0.05), being heigh deviation (Xh) with p:0.130 and angulation difference of dental implants between the groups (Ang) with p:0.396. CONCLUSION: The acquisition of stereolithography image of the prosthesis using an intraoral scanner has a clinically acceptable accuracy, being in agreement with the conventional method.

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Resumen La mayor accesibilidad a los tratamientos de reproducción asistida (RA) y los avances de la criobiología produjeron cambios en los laboratorios de andrología. El objetivo de este trabajo fue analizar la demanda y evolución de las variables seminales en las últimas dos décadas, caracterizar el laboratorio andrológico actual, evaluar el impacto de la incorporación del aseguramiento de la calidad y la inclusión de los sistemas computarizados (CASA). Se utilizaron datos de las medias mensuales del control de calidad interno (n=22 528) y encuestas a profesionales de laboratorios andrológicos (n=65) y a médicos especialistas en fertilidad (n=33). La demanda global se redujo significativamente con el aumento de las solicitudes de primera vez. El volumen y recuento, variables dependientes de andrógenos, disminuyeron con los años. El criterio estricto en morfología disminuyó el porcentaje de normales; la mitad de los médicos encuestados recibieron resultados entre 0 y 10% y el 40% consideró que ponía en riesgo el valor clínico de la variable. El sistema CASA permitió objetivar la cinética espermática e incrementar el porcentaje de progresivos rápidos, pero pocos laboratorios lo incorporaron. El 66% de los médicos resuelven el factor andrológico severo por tratamientos clínicos y el 95% utiliza técnicas de RA. El análisis de semen es ejecutado fundamentalmente por bioquímicos especializados, con baja adhesión a la automatización y acreditación del laboratorio, pero con participación en programas de evaluación externa de calidad. La demanda disminuyó como consecuencia del aumento del tratamiento por RA. La reducción del porcentaje de formas normales compromete su utilidad clínica.

Abstract Increasing availability to assisted reproduction (AR) treatments in Argentina and advances in cryobiology resulted in changes in andrology laboratories. The aim of this study was to evaluate the demand and evolution of seminal variables in the last two decades, characterise the current andrology laboratory, evaluate the impact of the incorporation of quality assurance and the introduction of computer assisted semen analysis (CASA). Data were taken from internal quality control (IQC) monthly means (n=22 528) and professionals in charge of laboratories (n=65) and fertility physicians' (n=33) surveys. Overall demand decreased significantly while first-time orders increased. Sperm volume and sperm count -androgen dependent parameters- decreased over the years. Strict morphology criteria reduced the percentage of normal results; half of the physicians received results between 0 and 10% and 40% considered that it compromised the clinical value of the variable. The CASA system made it possible to objectify sperm kinetic, increasing the percentage of fast progressives, but few laboratories have incorporated it. Sixty-six percent of physicians resolve severe andrological factor by clinical treatments and 95% use AR techniques in those cases. Semen analysis is mainly performed by specialised biochemists, with low adherence to laboratory automatisation and accreditation, but with participation in external quality assessment programmes. The demand decreased because of the increase in AR treatment. The lower percentage of normal forms compromises their clinical utility.

Resumo O aumento do acesso aos tratamentos de reprodução assistida (RA) e os avanços na criobiologia levaram a mudanças nos laboratórios de andrologia. O objetivo deste trabalho foi analisar a demanda e a evolução das variáveis de sêmen nas últimas duas décadas, caracterizar o laboratório de andrologia atual, avaliar o impacto da incorporação da garantia da qualidade e a inclusão dos sistemas computadorizados (CASA). Foram utilizados dados das médias mensais do controle de qualidade interno (n= 22 528) e pesquisas a profissionais de laboratórios andrológicos e a médicos especialistas em fertilidade (n=33). A demanda geral diminuiu significativamente com o aumento das solicitações de primeira vez. O volume e a contagem de esperma, parâmetros dependentes de andrógenos, diminuíram ao longo dos anos. O critério morfológico rigoroso diminuiu a porcentagem de normais; metade dos médicos entrevistados recebeu resultados entre 0 e 10% e 40% considerou que isso comprometía o valor clínico do parâmetro. O sistema CASA, permitiu objetivar a cinética espermática e aumentar o percentual de progressões rápidas, mas poucos laboratórios o incorporaram. 66% dos médicos resolvem o fator andrológico grave por tratamentos clínicos e 95% utilizam técnicas de RA nesses casos. A análise do sêmen é realizada principalmente por bioquímicos especializados, com baixa aderência à automação e acreditação laboratorial, mas com participação em programas de avalação externa de qualidade. A demanda diminuiu como consequência do aumento do tratamento por RA. A diminuição em percentagem de formas normais compromete sua utilidade clínica.

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Virtual surgical planning and three-dimensional (D) printing are rapidly becoming essential for challenging and complex surgeries around the world. An Ibero-American survey reported a lack of awareness of technology benefits and scarce financial resources as the two main barriers to widespread adoption of 3-D technologies. The Pereira Rossell Hospital Center is a publicly funded maternal and pediatric academic clinical center in Uruguay, a low-resource Latin American country, that successfully created and has been running a 3-D unit for 4 years. The present work is a step-by-step review of the 3-D technology implementation process in a hospital with minimal financial investment. References to training, software, hardware, and the management of human resources are included. Difficulties throughout the process and future challenges are also discussed.

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ABSTRACT Purpose: To assess the effect of the coronavirus disease 2019 (COVID-19) pandemic on cataract surgery by residents who had mandatory surgical simulator training during residency. Methods: In this retrospective, observational analytical study, the total number of cataract surgeries and surgical complications by all senior residents of 2019 (2019 class; prepandemic) and 2020 (2020 class; affected by the reduced number of elective surgeries due to the COVID-19 pandemic) were collected and compared. All residents had routine mandatory cataract surgery training on a virtual surgical simulator during residency. The total score obtained by these residents on cataract challenges of the surgical simulator was also evaluated. Results: The 2020 and 2019 classes performed 1275 and 2561 cataract surgeries, respectively. This revealed a reduction of 50.2% in the total number of procedures performed by the 2020 class because of the pandemic. The incidence of surgical complications was not statistically different between the two groups (4.2% in the 2019 class and 4.9% in the 2020 class; p=0.314). Both groups also did not differ in their mean scores on the simulator's cataract challenges (p<0.696). Conclusion: Despite the reduction of 50.2% in the total number of cataract surgeries performed by senior residents of 2020 during the COVID-19 pandemic, the incidence of surgical complications did not increase. This suggests that surgical simulator training during residency mitigated the negative effects of the reduced surgical volume during the pandemic.

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ABSTRACT Purpose: Evaluation of lid contour and marginal peak point changes to compare outcomes of external levator advancement and Müller's muscle conjunctival resection surgery in unilateral ptosis. Methods: We reviewed the charts of unilateral ptosis patients who underwent external levator advancement or Müller's muscle conjunctival resection. Eyelid contour analysis was conducted on preoperative and 6-month postoperative digital images. This was performed with the multiple margin reflex distances technique, measuring the vertical distance from a line intersecting the center of the pupil to the eyelid margin at 10 positions at 2 mm intervals. The marginal peak point changes were analyzed digitally using the coordinates of the peak point according to the pupil center. Each position's mean distance was compared preoperatively, postoperatively, and with the fellow eyelid. Results: Sixteen patients underwent external levator advancement and 16 patients had Müller's muscle conjunctival resection. The mean margin reflex distance was improved by both techniques (1.46 vs. 2.43 mm and 1.12 vs. 2.25 mm, p=0.008 and p=0.0001 respectively) and approached that of the fellow eyelid (2.43 vs. 2.88 and 2.25 vs. 2.58 mm, p=0.23 and p=0.19, respectively). However, statistically significant lid margin elevation was limited to between the N6 and T6 points in the external levator advancement group. Whereas, significant elevation was achieved along the whole lid margin in the Müller's muscle conjunctival resection group. The marginal peak point was shifted slightly laterally in the external levator advancement group (p=0.11). Conclusions: Both techniques provide effective lid elevation, however, the external levator advancement's effect lessens toward the canthi while Müller's muscle conjunctival resection provides more uniform elevation across the lid margin. The margin reflex distance alone is not sufficient to reflect contour changes.

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ABSTRACT Purpose: This study aimed to evaluate the classification performance of pretrained convolutional neural network models or architectures using fundus image dataset containing eight disease labels. Methods: A publicly available ocular disease intelligent recognition database has been used for the diagnosis of eight diseases. This ocular disease intelligent recognition database has a total of 10,000 fundus images from both eyes of 5,000 patients for the following eight diseases: healthy, diabetic retinopathy, glaucoma, cataract, age-related macular degeneration, hypertension, myopia, and others. Ocular disease classification performances were investigated by constructing three pretrained convolutional neural network architectures including VGG16, Inceptionv3, and ResNet50 models with adaptive moment optimizer. These models were implemented in Google Colab, which made the task straight-forward without spending hours installing the environment and supporting libraries. To evaluate the effectiveness of the models, the dataset was divided into 70%, 10%, and 20% for training, validation, and testing, respectively. For each classification, the training images were augmented to 10,000 fundus images. Results: ResNet50 achieved an accuracy of 97.1%; sensitivity, 78.5%; specificity, 98.5%; and precision, 79.7%, and had the best area under the curve and final score to classify cataract (area under the curve = 0.964, final score = 0.903). By contrast, VGG16 achieved an accuracy of 96.2%; sensitivity, 56.9%; specificity, 99.2%; precision, 84.1%; area under the curve, 0.949; and final score, 0.857. Conclusions: These results demonstrate the ability of the pretrained convolutional neural network architectures to identify ophthalmological diseases from fundus images. ResNet50 can be a good architecture to solve problems in disease detection and classification of glaucoma, cataract, hypertension, and myopia; Inceptionv3 for age-related macular degeneration, and other disease; and VGG16 for normal and diabetic retinopathy.

RESUMO Objetivo: Avaliar o desempenho de classificação de modelos ou arquiteturas de rede neural convolucional pré--treinadas usando um conjunto de dados de imagem de fundo de olho contendo oito rótulos de doenças diferentes. Métodos: Neste artigo, o conjunto de dados de reconhecimento inteligente de doenças oculares publicamente disponível foi usado para o diagnóstico de oito rótulos de doenças diferentes. O banco de dados de reconhecimento inteligente de doenças oculares tem um total de 10.000 imagens de fundo de olho de ambos os olhos de 5.000 pacientes para oito categorias que contêm rótulos saudáveis, retinopatia diabética, glaucoma, catarata, degeneração macular relacionada à idade, hipertensão, miopia, outros. Investigamos o desempenho da classificação de doenças oculares construindo três arquiteturas de rede neural convolucional pré-treinadas diferentes, incluindo os modelos VGG16, Inceptionv3 e ResNet50 com otimizador de Momento Adaptativo. Esses modelos foram implementados no Google Colab o que facilitou a tarefa sem gastar horas instalando o ambiente e suportando bibliotecas. Para avaliar a eficácia dos modelos, o conjunto de dados é dividido em 70% para treinamento, 10% para validação e os 20% restantes utilizados para teste. As imagens de treinamento foram expandidas para 10.000 imagens de fundo de olho para cada tal. Resultados: Observou-se que o modelo ResNet50 alcançou acurácia de 97,1%, sensibilidade de 78,5%, especificidade de 98,5% e precisão de 79,7% e teve a melhor área sob a curva e pontuação final para classificar a categoria da catarata (área sob a curva=0,964, final=0,903). Em contraste, o modelo VGG16 alcançou uma precisão de 96,2%, sensibilidade de 56,9%, especificidade de 99,2% e precisão de 84,1%, área sob a curva 0,949 e pontuação final de 0,857. Conclusão: Esses resultados demonstram a capacidade das arquiteturas de rede neural convolucional pré-treinadas em identificar doenças oftalmológicas a partir de imagens de fundo de olho. ResNet50 pode ser uma boa solução para resolver problemas na detecção e classificação de doenças como glaucoma, catarata, hipertensão e miopia; Inceptionv3 para degeneração macular relacionada à idade e outras doenças; e VGG16 para retinopatia normal e diabética.

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Objective: To assess the reliability of phase-sensitive inversion recovery (PSIR) magnetic resonance imaging (MRI) and its accuracy for determining the topography of demyelinating cortical lesions in patients with multiple sclerosis (MS). Materials and Methods: This was a cross-sectional study conducted at a tertiary referral center for MS and other demyelinating disorders. We assessed the agreement among three raters for the detection and topographic classification of cortical lesions on fluid-attenuated inversion recovery (FLAIR) and PSIR sequences in patients with MS. Results: We recruited 71 patients with MS. The PSIR sequences detected 50% more lesions than did the FLAIR sequences. For detecting cortical lesions, the level of interrater agreement was satisfactory, with a mean free-response kappa (κFR) coefficient of 0.60, whereas the mean κFR for the topographic reclassification of the lesions was 0.57. On PSIR sequences, the raters reclassified 366 lesions (20% of the lesions detected on FLAIR sequences), with excellent interrater agreement. There was a significant correlation between the total number of lesions detected on PSIR sequences and the Expanded Disability Status Scale score (ρ = 0.35; p < 0.001). Conclusion: It seems that PSIR sequences perform better than do FLAIR sequences, with clinically satisfactory interrater agreement, for the detection and topographic classification of cortical lesions. In our sample of patients with MS, the PSIR MRI findings were significantly associated with the disability status, which could influence decisions regarding the treatment of such patients.

Objetivo: Avaliar a confiabilidade da sequência PSIR e sua precisão no diagnóstico topográfico de lesões corticais desmielinizantes em pacientes com esclerose múltipla (EM). Materiais e Métodos: Estudo transversal realizado em centro de referência terciário para EM e distúrbios desmielinizantes. Avaliamos a concordância entre três avaliadores na identificação e classificação topográfica de lesões corticais na ressonância magnética de pacientes com EM, utilizando as sequências FLAIR e PSIR. Resultados: Foram incluídos 71 pacientes com EM. Em PSIR detectou-se 1,5× mais lesões do que em FLAIR, com concordância satisfatória entre examinadores na identificação de lesões corticais, com coeficiente kappa de resposta livre (κFR) = 0,60, e na reclassificação topográfica das lesões, com κFR médio = 0,57. Os avaliadores reclassificaram 366 lesões em PSIR (20% das lesões detectadas em FLAIR), com excelente concordância. Houve correlação significativa do total de lesões detectadas em PSIR e o escore da escala de incapacidade EDSS (ρ = 0,35; p < 0,001). Conclusão: PSIR mostrou-se superior na detecção de lesões corticais e na classificação topográfica destas em comparação ao FLAIR, com concordâncias entre examinadores clinicamente satisfatórias. A associação significativa entre o número de lesões corticais em PSIR e o grau de incapacidade dos pacientes pode influenciar em decisões terapêuticas.

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In the wake of studies targeting atherosclerotic plaques and searching for quantifiable variables that contribute additional information to therapeutic decision-making, plaque assessment using Shear Wave Elastography (SWE) is emerging as a reproducible and promising alternative. We used a single Logiq S8 device (General Electric, Boston, Massachusetts, United States) with an 8.5-11MHz multifrequency linear transducer at 10MHz in longitudinal section. We considered relevant criteria for image acquisition: adequate longitudinal insonation, differentiation of the intima-media complex, delineation of proximal and distal tunica adventitia and the vascular lumen, good visualization of the atherosclerotic plaque, cardiac cycle in ventricular diastole, and absence of incongruous changes. SWE is an emerging and extremely promising method for assessment of carotid plaques that may contribute to therapeutic decision-making based on characteristics related to the atherosclerotic plaque, with inter-device and inter-examiner reproducibility.

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BACKGROUND: Poor assessment of anaesthetic depth (AD) has led to overdosing or underdosing of the anaesthetic agent, which requires continuous monitoring to avoid complications. The evaluation of the central nervous system activity and autonomic nervous system could provide additional information on the monitoring of AD during surgical procedures. METHODS: Observational analytical single-centre study, information on biological signals was collected during a surgical procedure under general anaesthesia for signal preprocessing, processing and postprocessing to feed a pattern classifier and determine AD status of patients. The development of the electroencephalography index was carried out through data processing and algorithm development using MATLAB V.8.1. RESULTS: A total of 25 men and 35 women were included, with a total time of procedure average of 109.62 min. The results show a high Pearson correlation between the Complexity Brainwave Index and the indices of the entropy module. A greater dispersion is observed in the state entropy and response entropy indices, a partial overlap can also be seen in the boxes associated with deep anaesthesia and general anaesthesia in these indices. A high Pearson correlation might be explained by the coinciding values corresponding to the awake and general anaesthesia states. A high Pearson correlation might be explained by the coinciding values corresponding to the awake and general anaesthesia states. CONCLUSION: Biological signal filtering and a machine learning algorithm may be used to classify AD during a surgical procedure. Further studies will be needed to confirm these results and improve the decision-making of anaesthesiologists in general anaesthesia.

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Abstract Objective: To develop a convolutional neural network (CNN) model, trained with the Brazilian "Estudo Longitudinal de Saúde do Adulto Musculoesquelético" (ELSA-Brasil MSK, Longitudinal Study of Adult Health, Musculoskeletal) baseline radiographic examinations, for the automated classification of knee osteoarthritis. Materials and Methods: This was a cross-sectional study carried out with 5,660 baseline posteroanterior knee radiographs from the ELSA-Brasil MSK database (5,660 baseline posteroanterior knee radiographs). The examinations were interpreted by a radiologist with specific training, and the calibration was as established previously. Results: The CNN presented an area under the receiver operating characteristic curve of 0.866 (95% CI: 0.842-0.882). The model can be optimized to achieve, not simultaneously, maximum values of 0.907 for accuracy, 0.938 for sensitivity, and 0.994 for specificity. Conclusion: The proposed CNN can be used as a screening tool, reducing the total number of examinations evaluated by the radiologists of the study, and as a double-reading tool, contributing to the reduction of possible interpretation errors.

Resumo Objetivo: Desenvolver um modelo computacional - rede neural convolucional (RNC) - treinado com radiografias da linha de base do Estudo Longitudinal de Saúde do Adulto Musculoesquelético (ELSA-Brasil Musculoesquelético), para a classificação automática de osteoartrite dos joelhos. Materiais e Métodos: Trata-se de um estudo transversal abrangendo todos os exames da linha de base do ELSA-Brasil Musculoesquelético (5.660 radiografias dos joelhos em incidência posteroanterior). Os exames foram interpretados por médico radiologista com treinamento específico e calibração previamente publicada. Resultados: A RNC desenvolvida apresentou área sob a curva característica de operação do receptor de 0,866 (IC 95%: 0,842-0,882). O modelo pode ser calibrado para alcançar, não simultaneamente, valores máximos de 0,907 para acurácia, 0,938 para sensibilidade e 0,994 para especificidade. Conclusão: A RNC desenvolvida pode ser utilizada como ferramenta de triagem, reduzindo o número total de exames avaliados pelos radiologistas do estudo, e/ou como ferramenta de segunda leitura, contribuindo com a redução de possíveis erros de interpretação.

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Objetivo: Presentar el relato de un caso clínico de cirugía virtual guiada para rehabilitación implantosoportada de maxilar edéntulo con carga inmediata. Relato del caso: Paciente, edéntulo total en ambos maxilares, expresó su deseo de cambiar la prótesis total superior removible por una prótesis total fija sobre implantes. Durante la evaluación clínica, se observaron condiciones biológicas favorables al tratamiento como, adecuada faja de tejido queratinizado y leve reabsorción ósea. Como tratamiento se le sugiere al paciente, una planificación inversa, asistida por cirugía virtual guiada, utilizando un prototipo de guía quirúrgica para la colocación de seis implantes dentales en el maxilar y la instalación de una prótesis protocolo de carga inmediata. Conclusiones: Los resultados nos permiten concluir que la cirugía virtual guiada por computadora para rehabilitación protésica implantosoportada de maxilar edéntulo, con carga inmediata, proporciona precisión en los procedimientos quirúrgicos, es fundamental para la confección de prótesis inmediatas, representa una alternativa mínimamente invasiva y el resultado complace a los pacientes.

Objective: present the report of a clinical case of a virtual guided surgery for implant-supported rehabilitation of the edentulous maxilla with immediate loading. Case report: Patient, bi-maxillary edentulous expressed the desire to replace the removable upper total prothesis for a total fixed prothesis on implants. During the clinical evaluation, favorable biological conditions for treatment were observed, such as adequate keratinized tissue band and mild bone resorption. As part of the treatment, the patient was recommended a reverse planning approach, assisted by virtual guided surgery. This involved a prototype surgical guide for the fixation of six dental implants in the maxilla and the installation of an immediate loading protocol prosthesis. Conclusions: The results lead us to conclude that computer-guided virtual surgery for implant-supported prosthetic rehabilitation of the edentulous maxilla with immediate loading, provides a high precision in surgical procedures. It is essential to fabrication of immediate prostheses, represents a minimally invasive alternative, and results in patient satisfaction.

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Objective: To develop an automated co-registration system and test its performance, with and without a fiducial marker, on single-photon emission computed tomography (SPECT) images. Materials and Methods: Three SPECT/CT scans were acquired for each rotation of a Jaszczak phantom (to 0°, 5°, and 10° in relation to the bed axis), with and without a fiducial marker. Two rigid co-registration software packages-SPM12 and NMDose-coreg-were employed, and the percent root mean square error (%RMSE) was calculated in order to assess the quality of the co-registrations. Uniformity, contrast, and resolution were measured before and after co-registration. The NMDose-coreg software was employed to calculate the renal doses in 12 patients treated with 177Lu-DOTATATE, and we compared those with the values obtained with the Organ Level INternal Dose Assessment for EXponential Modeling (OLINDA/EXM) software. Results: The use of a fiducial marker had no significant effect on the quality of co-registration on SPECT images, as measured by %RMSE (p = 0.40). After co-registration, uniformity, contrast, and resolution did not differ between the images acquired with fiducial markers and those acquired without. Preliminary clinical application showed mean total processing times of 9 ± 3 min/patient for NMDose-coreg and 64 ± 10 min/patient for OLINDA/EXM, with a strong correlation between the two, despite the lower renal doses obtained with NMDose-coreg. Conclusion: The use of NMDose-coreg allows fast co-registration of SPECT images, with no loss of uniformity, contrast, or resolution. The use of a fiducial marker does not appear to increase the accuracy of co-registration on phantoms.

Objetivo: Desenvolver corregistro automático e testar seu desempenho com ou sem marcador fiducial em imagens de tomografia computadorizada de emissão de fóton único (SPECT). Materiais e Métodos: Três SPECT/CTs foram adquiridas para cada rotação de um simulador de Jaszczak em relação ao eixo da maca (0°, 5° e 10°), com e sem fiducial. Dois métodos de corregistro inelástico foram aplicados - SPM12 e NMDose-coreg -, e a porcentagem do erro quadrático médio (%RMSE) foi usada para analisar a qualidade do corregistro. Uniformidade, contraste e resolução foram medidos antes e após o corregistro. NMDose com corregistro automático foi usado para calcular a dose renal de 12 pacientes tratados com 177Lu-DOTATATE e comparado com OLINDA/EXM. Resultados: A marcação fiducial não modificou a qualidade do corregistro das imagens SPECT, medida pela %RMSE (p = 0,40). Não houve impacto na uniformidade, contraste e resolução após o corregistro de imagens adquiridas com ou sem fiduciais. Aplicação clínica preliminar mostrou tempo total de processamento de 9 ± 3 min/paciente para NMDose e 64 ± 10 min/paciente para OLINDA/EXM, com alta correlação entre ambos, apesar de menor dose renal em NMDose. Conclusão: NMDose-coreg permite o corregistro rápido de imagens SPECT, sem perda de uniformidade, contraste ou resolução. O uso da marcação fiducial não aumentou a precisão do corregistro em fantomas.

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The advent of the COVID-19 pandemic forced medical schools around the world to adopt emergency remote learning as a resort to avoid interruption of courses. However, the effectiveness of online classes as an educational strategy has been questioned by medical educators and students. In a prospective observational study design, students enrolled in a renal physiology and pathophysiology course were exposed to either face-to-face or remote synchronous classes. Students taught online obtained significantly higher mean scores than the group who had in-person classes, both groups assessed with identical exams. Appropriate screening tests suggested that fraud is unlikely to have significantly influenced these results and that the observed differences in performance reflected increased learning by the remote group. These observations suggest that online classes can help to maintain the continuity of physiology and pathophysiology courses during periods of social isolation and may contribute to improving learning under normal conditions.NEW & NOTEWORTHY In this study, we were able to make a rare direct comparison of face-to-face and remote strategies for the teaching of undergraduate medical students in a specific area, namely, renal pathophysiology. Unexpectedly, students who attended the remote course had significantly higher grades than those who had mostly in-person classes.

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Purpose: The aim of this study was to evaluate changes in the trabecular bone through texture analysis and compare the texture analysis characteristics of different areas in patients with medication-related osteonecrosis of the jaw (MRONJ). Materials and Methods: Cone-beam computed tomographic images of 16 patients diagnosed with MRONJ were used. In sagittal images, 3 regions were chosen: active osteonecrosis (AO); intermediate tissue (IT), which presented a zone of apparently healthy tissue adjacent to the AO area; and healthy bone tissue (HT) (control area). Texture analysis was performed evaluating 7 parameters: secondary angular momentum, contrast, correlation, sum of squares, inverse moment of difference, sum of entropies, and entropy. Data were analyzed using the Kruskal-Wallis test with a significance level of 5%. Results: Comparing the areas of AO, IT, and HT, significant differences (P<0.05) were observed. The IT and AO area images showed higher values for parameters such as contrast, entropy, and secondary angular momentum than the HT area, indicating greater disorder in these tissues. Conclusion: Through texture analysis, changes in the bone pattern could be observed in areas of osteonecrosis. The texture analysis demonstrated that areas visually identified and classified as IT still had necrotic tissue, thereby increasing the accuracy of delimiting the real extension of MRONJ.