Desarrollo de ventiladores mecánicos en Chile. Crónica de la iniciativa "Un Respiro para Chile", durante la primera ola de la pandemia COVID-19 / Development of mechanical ventilators in Chile. Chronicle of the initiative "Un Respiro para Chile"

At the beginning of the COVID-19 pandemic in Chile, in March 2020, a projection indicated that a significant group of patients with pneumonia would require admission to an Intensive Care Unit and connection to a mechanical ventilator. Therefore, a paucity of these devices and other supplies was predicted. The initiative "Un respiro para Chile" brought together many people and institutions, public and private. In the course of three months, it allowed the design and building of several ventilatory assistance devices, which could be used in critically ill patients.

Estrogen, Cognitive Performance, and Functional Imaging Studies: What Are We Missing About Neuroprotection?

Menopause transition can be interpreted as a vulnerable state characterized by estrogen deficiency with detrimental systemic effects as the low-grade chronic inflammation that appears with aging and partly explains age-related disorders as cancer, diabetes mellitus and increased risk of cognitive impairment. Over the course of a lifetime, estrogen produces several beneficial effects in healthy neurological tissues as well as cardioprotective effects, and anti-inflammatory effects. However, clinical evidence on the efficacy of hormone treatment in menopausal women has failed to confirm the benefit reported in observational studies. Unambiguously, enhanced verbal memory is the most robust finding from longitudinal and cross-sectional studies, what merits consideration for future studies aiming to determine estrogen neuroprotective efficacy. Estrogen related brain activity and functional connectivity remain, however, unexplored. In this context, the resting state paradigm may provide valuable information about reproductive aging and hormonal treatment effects, and their relationship with brain imaging of functional connectivity may be key to understand and anticipate estrogen cognitive protective effects. To go in-depth into the molecular and cellular mechanisms underlying rapid-to-long lasting protective effects of estrogen, we will provide a comprehensive review of cognitive tasks used in animal studies to evaluate the effect of hormone treatment on cognitive performance and discuss about the tasks best suited to the demonstration of clinically significant differences in cognitive performance to be applied in human studies. Eventually, we will focus on studies evaluating the DMN activity and responsiveness to pharmacological stimulation in humans.

Impact of Remote Monitoring Technologies for Assisting Patients With Gestational Diabetes Mellitus: A Systematic Review.

Introduction: In Chile, 1 in 8 pregnant women of middle socioeconomic level has gestational diabetes mellitus (GDM), and in general, 5-10% of women with GDM develop type 2 diabetes after giving birth. Recently, various technological tools have emerged to assist patients with GDM to meet glycemic goals and facilitate constant glucose monitoring, making these tasks more straightforward and comfortable. Objective: To evaluate the impact of remote monitoring technologies in assisting patients with GDM to achieve glycemic goals, and know the respective advantages and disadvantages when it comes to reducing risk during pregnancy, both for the mother and her child. Methods: A total of 188 articles were obtained with the keywords "gestational diabetes mellitus," "GDM," "gestational diabetes," added to the evaluation levels associated with "glucose level," "glycemia," "glycemic index," "blood sugar," and the technological proposal to evaluate with "glucometerm" "mobile application," "mobile applications," "technological tools," "telemedicine," "technovigilance," "wearable" published during the period 2016-2021, excluding postpartum studies, from three scientific databases: PUBMED, Scopus and Web of Science. These were managed in the Mendeley platform and classified using the PRISMA method. Results: A total of 28 articles were selected after elimination according to inclusion and exclusion criteria. The main measurement was glycemia and 4 medical devices were found (glucometer: conventional, with an infrared port, with Bluetooth, Smart type and continuous glucose monitor), which together with digital technology allow specific functions through 2 identified digital platforms (mobile applications and online systems). In four articles, the postprandial glucose was lower in the Tele-GDM groups than in the control group. Benefits such as improved glycemic control, increased satisfaction and acceptability, maternal confidence, decreased gestational weight gain, knowledge of GDM, and other relevant aspects were observed. There were also positive comments regarding the optimization of the medical team's time. Conclusion: The present review offers the opportunity to know about the respective advantages and disadvantages of remote monitoring technologies when it comes to reducing risk during pregnancy. GDM centered technology may help to evaluate outcomes and tailor personalized solutions to contribute to women's health. More studies are needed to know the impact on a healthcare system.

[Development of mechanical ventilators in Chile. Chronicle of the initiative "Un Respiro para Chile"]. / Desarrollo de ventiladores mecánicos en Chile. Crónica de la iniciativa "Un Respiro para Chile", durante la primera ola de la pandemia COVID-19.

At the beginning of the COVID-19 pandemic in Chile, in March 2020, a projection indicated that a significant group of patients with pneumonia would require admission to an Intensive Care Unit and connection to a mechanical ventilator. Therefore, a paucity of these devices and other supplies was predicted. The initiative "Un respiro para Chile" brought together many people and institutions, public and private. In the course of three months, it allowed the design and building of several ventilatory assistance devices, which could be used in critically ill patients.

Four functional magnetic resonance imaging techniques for skeletal muscle exploration, a systematic review.

BACKGROUND: The study of muscle health has become more relevant lately, due to global aging and a higher incidence of musculoskeletal pathologies. Current exploration techniques, such as electromyography, do not provide accurate spatial information. OBJECTIVE: The objective of this work is to perform a systematic review of the literature to synthesize the contributions that can offer functional MRI techniques commonly used in neuroimaging, applied to skeletal muscle: Blood Oxygen Level Dependent (BOLD), IntraVoxel Incoherent Motion (IVIM), Arterial Spin Labeling (ASL) and Dynamic Contrast Enhanced (DCE). EVIDENCE ACQUISITION: Web of Science and Medline databases were searched, over the last 10 years, focused on the use of BOLD, ASL, IVIM or DCE in skeletal muscle. EVIDENCE SYNTHESIS: 59 articles were included after applying the selection criteria. 37 studies were performed in healthy subjects, and 22 in patients with different pathologies: in peripheral arterial disease, systemic sclerosis, diabetes, osteoporosis, adolescent idiopathic scoliosis, and dermatomyositis. Reference values in healthy subjects still vary in some cases. CONCLUSION: The studies show the feasibility of implementing functional MRI through BOLD, ASL, IVIM or DCE imaging in several muscles and their possible utility in different pathologies. A synthesis of how to implement such exploration is given here. CLINICAL IMPACT: These four techniques are based on sequences already present in clinical MRI scanners, therefore, their use for functional muscle exploration does not require additional investment. These techniques allow visualization and quantification of parameters associated with the vascular health of the muscles and represent interesting support for musculoskeletal exploration.

Using Machine Learning to Predict Complications in Pregnancy: A Systematic Review.

Introduction: Artificial intelligence is widely used in medical field, and machine learning has been increasingly used in health care, prediction, and diagnosis and as a method of determining priority. Machine learning methods have been features of several tools in the fields of obstetrics and childcare. This present review aims to summarize the machine learning techniques to predict perinatal complications. Objective: To identify the applicability and performance of machine learning methods used to identify pregnancy complications. Methods: A total of 98 articles were obtained with the keywords "machine learning," "deep learning," "artificial intelligence," and accordingly as they related to perinatal complications ("complications in pregnancy," "pregnancy complications") from three scientific databases: PubMed, Scopus, and Web of Science. These were managed on the Mendeley platform and classified using the PRISMA method. Results: A total of 31 articles were selected after elimination according to inclusion and exclusion criteria. The features used to predict perinatal complications were primarily electronic medical records (48%), medical images (29%), and biological markers (19%), while 4% were based on other types of features, such as sensors and fetal heart rate. The main perinatal complications considered in the application of machine learning thus far are pre-eclampsia and prematurity. In the 31 studies, a total of sixteen complications were predicted. The main precision metric used is the AUC. The machine learning methods with the best results were the prediction of prematurity from medical images using the support vector machine technique, with an accuracy of 95.7%, and the prediction of neonatal mortality with the XGBoost technique, with 99.7% accuracy. Conclusion: It is important to continue promoting this area of research and promote solutions with multicenter clinical applicability through machine learning to reduce perinatal complications. This systematic review contributes significantly to the specialized literature on artificial intelligence and women's health.

Study protocol and rationale of the "Cogni-action project" a cross-sectional and randomized controlled trial about physical activity, brain health, cognition, and educational achievement in schoolchildren.

BACKGROUND: Education and health are crucial topics for public policies as both largely determine the future wellbeing of the society. Currently, several studies recognize that physical activity (PA) benefits brain health in children. However, most of these studies have not been carried out in developing countries or lack the transference into the education field. The Cogni-Action Project is divided into two stages, a cross-sectional study and a crossover-randomized trial. The aim of the first part is to establish the associations of PA, sedentarism, and physical fitness with brain structure and function, cognitive performance and academic achievement in Chilean schoolchildren (10-13 years-old). The aim of the second part is to determinate the acute effects of three PA protocols on neuroelectric indices during a working memory and a reading task. METHODS: PA and sedentarism will be self-reported and objectively-assessed with accelerometers in a representative subsample, whilst physical fitness will be evaluated through the ALPHA fitness test battery. Brain structure and function will be assessed by magnetic resonance imaging (MRI) in a randomized subsample. Cognitive performance will be assessed through the NeuroCognitive Performance Test, and academic achievement by school grades. In the second part 32 adolescents (12-13 year-old) will be cross-over randomized to these condition (i) "Moderate-Intensity Continuous Training" (MICT), (ii) "Cooperative High-Intensity Interval Training" (C-HIIT), and (iii) Sedentary condition. Neuroelectric indices will be measures by electroencephalogram (EEG) and eye-tracking, working memory by n-back task and reading comprehension by a reading task. DISCUSSION: The main strength of this project is that, to our knowledge, this is the first study analysing the potential association of PA, sedentarism, and physical fitness on brain structure and function, cognitive performance, and academic achievement in a developing country, which presents an important sociocultural gap. For this purpose, this project will use advanced technologies in neuroimaging (MRI), electrophysiology (EEG), and eye-tracking, as well as objective and quality measurements of several physical and cognitive health outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03894241 Date of register: March 28, 2019. Retrospectively Registered.

Multiple echo multi-shot diffusion sequence.

PURPOSE: To measure both transversal relaxation time (T2 ) and diffusion coefficients within a single scan using a multi-shot approach. Both measurements have drawn interest in many applications, especially in skeletal muscle studies, which have short T2 values. Multiple echo single-shot schemes have been proposed to obtain those variables simultaneously within a single scan, resulting in a reduction of the scanning time. However, one problem with those approaches is the associated long echo read-out. Consequently, the minimum achievable echo time tends to be long, limiting the application of these sequences to tissues with relatively long T2 . MATERIALS AND METHODS: To address this problem, we propose to extend the multi-echo sequences using a multi-shot approach, so that to allow shorter echo times. A multi-shot dual-echo EPI sequence with diffusion gradients and echo navigators was modified to include independent diffusion gradients in any of the two echoes. RESULTS: The multi-shot approach allows us to drastically reduce echo times. Results showed a good agreement for the T2 and mean diffusivity measurements with gold standard sequences in phantoms and in vivo data of calf muscles from healthy volunteers. CONCLUSION: A fast and accurate method is proposed to measure T2 and diffusion coefficients simultaneously, tested in vitro and in healthy volunteers.

Quantitative description of the morphology and ossification center in the axial skeleton of 20-week gestation formalin-fixed human fetuses using magnetic resonance images.

OBJECTIVES: Human tissues are usually studied using a series of two-dimensional visualizations of in vivo or cutout specimens. However, there is no precise anatomical description of some of the processes of human fetal development. The purpose of our study is to develop a quantitative description of the normal axial skeleton by means of high-resolution three-dimensional magnetic resonance (MR) images, collected from six normal 20-week-old human fetuses fixed in formaldehyde. METHODS: Fetuses were collected after spontaneous abortion and subsequently fixed with formalin. They were imaged using a 1.5 T MR scanner with an isotropic spatial resolution of 200 µm. The correct tissue discrimination between ossified and cartilaginous bones was confirmed by comparing the images achieved by MR scans and computerized axial tomographies. The vertebral column was segmented out from each image using a specially developed semi-automatic algorithm. RESULTS: Vertebral body dimensions and inter-vertebral distances were larger in the lumbar region, in agreement with the beginning of the ossification process from the thoracolumbar region toward the sacral and cephalic ends. CONCLUSION: In this article, we demonstrate the feasibility of using MR images to study the ossification process in formalin-fixed fetal tissues. A quantitative description of the ossification centers of vertebral bodies and arches is presented.

Análisis cuantitativo de variables hemodinámicas de la aorta obtenidas de 4D flow / Quantitative analysis of hemodynamic variables of the aorta by 4D flow MRI

Objective: Hemodynamic parameters are critical to perform a proper diagnosis. However, due to the large number of variables that can be obtained, overall analysis may represent a complex task. To facilitate this, we propose to create a model for classifying different hemodynamic variables between those belonging to a healthy individual and to a pathological patient. For this purpose, we employed data mining techniques to identify relationships among various aortic hemodynamic parameters obtained through multi-dimensional (4D flow) MR imaging. Method: A 4D flow sequence of whole heart and great vessels was acquired using MRI in 19 healthy volunteers and 2 patients (one with aortic coarctation and one with repaired coarctation of the aorta). Retrospectively, data were reformatted along the aorta; three MRI acquisitions were performed for volunteers and 30 sequences for each patient. In each slice the aorta was segmented and various parameters were quantified: area, maximum velocity, minimum velocity, flow and volumen, with following values being calculated for last four parameters: maximum, average, standard deviation, kurtosis, skewness, proportion of time to reach the maximum value, among others. A total of 26 variables for each acquisition were obtained. In order to classify data, the CART Technique (Classification and Regression Trees) was applied. To validate the model, two extra projections were generated per each volunteer and 20 slice per each patient. Results: By using only 7 variables, the CART Technique allows discrimination between images performed either on volunteers or patients with an error rate of 14.1 percent, a sensitivity of 82.5 percent, and a specificity of 89.4 percent. Conclusions: 4D flow MR imaging provides a wealth of hemodynamic data that can be difficult to analyze. In this paper we demonstrate that by using data mining techniques it is possible to classify images from relevant hemodynamic parameters and their relationships in order...

Objetivo: Los parámetros hemodinámicos son de gran utilidad para realizar un adecuado diagnóstico. Sin embargo, debido a la gran cantidad de variables que pueden obtenerse, el análisis global de todas ellas puede ser complejo. Para facilitar esta tarea, nosotros proponemos crear un modelo que permita clasificar distintas variables hemodinámicas entre las pertenecientes a un individuo sano o a uno patológico. Para ello, usaremos técnicas de minería de datos que permitan identificar y encontrar relaciones entre distintos parámetros hemodinámicos de la aorta obtenidos a través de flujo multidimensional (4D flow) por resonancia magnética. Método: Una secuencia 4D flow de todo el corazón y los grandes vasos fue adquirida utilizando resonancia magnética en 19 voluntarios sanos y 2 pacientes (uno con una coartación aórtica y otro con una coartación aórtica reparada). Retrospectivamente, los datos fueron reformateados a lo largo de la aorta, originándose 3 cortes en los voluntarios y 30 cortes en cada paciente. En cada corte la aorta fue segmentada y distintos parámetros fueron cuantificados: área, velocidad máxima, velocidad mínima, flujo y volumen, calculándose en los cuatro últimos su valor máximo, promedio, desviación estándar, curtosis, sesgo, proporción de tiempo en alcanzar el valor máximo, entre otros. Teniendo un total de 26 variables por cada corte. Se aplicó la técnica de árboles de decisión tipo CART (por sus siglas en inglés) para clasificar los datos. Para validar el modelo, 2 cortes extras fueron generados por cada voluntario y 20 cortes por cada paciente. Resultados: La técnica CART, mediante la utilización de sólo 7 variables, puede clasificar las imágenes de los voluntarios y pacientes con una tasa de error del 14,1 por ciento, una sensibilidad de 82,5 por ciento y una especificidad de 89.4 por ciento. Conclusiones: 4D flow provee una gran cantidad de datos hemodinámicos que son difíciles de analizar. En este trabajo demostramos que al utilizar...

Implementación y validación de protocolo de estimulación por comprensión de lenguaje oral en resonancia magnética funcional: resultados preliminares / Implementation and validation of a stimulation protocol for oral language comprehension using functional magnetic resonance imaging: preliminary results

This study aimed at implementing a stimulation protocol using functional Magnetic Resonance Imaging (fMRI), in a Hospital in Valparaiso (V Region), Chile, to detect cortical areas activated in oral language comprehension. Seven healthy volunteers participated in this study. Average t-score and signal variation were 6.3 +/- 0.3 and 0.5 +/- 0.1 percent, respectively. In spite of these low values, activations were obtained in Wernicke area, middle temporal gyrus, and Heschl s gyrus. The extension of activated areas was small, 5.06 +/- 2.99 cm3, probably due to amplifer low signal-to-noise ratio (SNR), in addition to the cognitive complexity of the task, and to the ambient acoustic noise. Successful implementation of fMRI protocols of language comprehension is possible in a clinical context in Chile without any additional resources.

Nuestro objetivo fue implementar un protocolo de estimulación en resonancia magnética funcional en un Hospital de Valparaíso, V Región de Chile, para detectar las áreas corticales activadas en la comprensión del lenguaje oral. Siete voluntarios sanos participaron de este estudio. El t-score y variación de señal alcanzado fue de 6.3 0.3 y 0.5 +/- 0.1 por ciento respectivamente. A pesar de estos bajos valores, las activaciones se registraron en el área Wernicke, circunvolución temporal media y circunvolución d e Heschl. La extensión de las activaciones fue pequeña, 5.06 +/- 2.99 cm³, probablemente debido a la baja relación señal ruido del resonador (SNR), además de la complejidad cognitiva de la tarea y el ruido acústico ambiente. Nuestros resultados indican que la implementación de la RMf en comprensión del lenguaje es posible de realizar en Chile sin recursos adicionales.

Diffusion signal in magnetic resonance imaging: origin and interpretation in neurosciences.

Diffusion Magnetic Resonance Imaging provides images of unquestionable diagnostic value. It is commonly used in the assessment of stroke and in white matter fiber tracking, among other applications. The diffusion coefficient has been shown to depend on cell concentration, membrane permeability, and cell orientation in the case of white matter or muscle fiber tracking; yet a clear relation between diffusion measurements and known physiological parameters is not established. The aim of this paper is to review hypotheses and actual knowledge on diffusion signal origin to provide assistance in the interpretation of diffusion MR images. Focus will be set on brain images, as most common applications of diffusion MRI are found in neuroradiology. Diffusion signal does not come from two intra- or extracellular compartments, as was first assumed. Restriction of water displacement due to membranes, hindrance in the extracellular space, and tissue heterogeneity are important factors. Unanswered questions remain on how to deal with tissue heterogeneity, and how to retrieve parameters less troublesome to work with from biological and clinical points of view. Diffusion quantification should be done with care, as many variables can lead to variation in measurements.

Diffusion Signal in Magnetic Resonance Imaging: Origin and Interpretation in Neurosciences

Diffusion Magnetic Resonance Imaging provides images of unquestionable diagnostic value. It is commonly used in the assessment of stroke and in white matter fiber tracking, among other applications. The diffusion coefficient has been shown to depend on cell concentration, membrane permeability, and cell orientation in the case of white matter or muscle fiber tracking; yet a clear relation between diffusion measurements and known physiological parameters is not established. The aim of this paper is to review hypotheses and actual knowledge on diffusion signal origin to provide assistance in the interpretation of diffusion MR images. Focus will be set on brain images, as most common applications of diffusion MRI are found in neuroradiology. Diffusion signal does not come from two intra- or extracellular compartments, as was first assumed. Restriction of water displacement due to membranes, hindrance in the extracellular space, and tissue heterogeneity are important factors. Unanswered questions remain on how to deal with tissue heterogeneity, and how to retrieve parameters less troublesome to work with from biological and clinical points of view. Diffusion quantification should be done with care, as many variables can lead to variation in measurements.