Factores de riesgo y biomarcadores de la enfermedad de Alzheimer / Risk factors and biomarkers of Alzheimer's disease

Introducción: La enfermedad de Alzheimer, constituye un problema sanitario y social de gran magnitud; precisa de diagnóstico y terapéutica precoces. Se realizó una búsqueda de artículos sobre factores de riesgo y biomarcadores de la enfermedad en las bases de datos PubMed/Medline, Scopus, Scielo y Lilacs, y mediante el buscador Google académico; desde el año 2017 hasta el 2023, en idioma español, inglés y portugués. Objetivo: Analizar los factores de riesgo y los biomarcadores de la enfermedad de Alzheimer. Desarrollo: Los principales factores de riesgo encontrados son edad avanzada, menor educación, poca actividad física, hábito de fumar, consumo excesivo de alcohol, hipertensión arterial, diabetes, obesidad, depresión, pérdida o disminución de la audición, aislamiento social, los traumas craneales y la contaminación ambiental. Los biomarcadores fundamentales son: los marcadores que se utilizan en los estudios de neuroimágenes como la PET Amiloide, PET tau, PET FDG; y en LCR y plasma: Aß42, Aß42/Aß40, p tau 217, p tau 181, GFAP, y neurofilamentos de cadena ligeras. Conclusiones: Se requieren estudios longitudinales, a partir de la presencia de los factores de riesgo asociados a biomarcador, desde edades pregeriátricas en pacientes sanos, que tengan como salidas el deterioro cognitivo y el desarrollo de la demencia, para construir un modelo de predicción(AU)

Introduction: Alzheimer's disease is a health and social problem of great magnitude; it requires early diagnosis and therapy. A search for articles on risk factors and biomarkers of the disease was conducted; in the databases PubMed/Medline, Scopus, Scielo and Lilacs, and through the Google scholar search engine; from 2017 to 2023, in Spanish, English and Portuguese. Objective: To analyze the risk factors and biomarkers of Alzheimer's disease. Development: The main risk factors found are advanced age, lower education, little physical activity, smoking, excessive alcohol consumption, high blood pressure, diabetes, obesity, depression, hearing loss or decrease, social isolation, head trauma and environmental pollution. The fundamental biomarkers are: markers used in neuroimaging studies such as amyloid PET, tau PET, FDG PET; and in CSF and plasma: Aß42, Aß42/Aß40, p tau 217, p tau 181, GFAP, and light chain neurofilaments. Conclusions: Longitudinal studies are required, based on the presence of risk factors associated with biomarkers, from pregeriatric ages in healthy patients, which have cognitive impairment and the development of dementia as outputs, to build a prediction model(AU)

Research on classification method of multimodal magnetic resonance images of Alzheimer's disease based on generalized convolutional neural networks / 生物医学工程学杂志

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer's disease.

Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning / 神经科学通报·英文版

Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.

Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders-a comprehensive review / 国际口腔科学杂志·英文版

Chronic Painful Temporomandibular Disorders (TMD) are challenging to diagnose and manage due to their complexity and lack of understanding of brain mechanism. In the past few decades' neural mechanisms of pain regulation and perception have been clarified by neuroimaging research. Advances in the neuroimaging have bridged the gap between brain activity and the subjective experience of pain. Neuroimaging has also made strides toward separating the neural mechanisms underlying the chronic painful TMD. Recently, Artificial Intelligence (AI) is transforming various sectors by automating tasks that previously required humans' intelligence to complete. AI has started to contribute to the recognition, assessment, and understanding of painful TMD. The application of AI and neuroimaging in understanding the pathophysiology and diagnosis of chronic painful TMD are still in its early stages. The objective of the present review is to identify the contemporary neuroimaging approaches such as structural, functional, and molecular techniques that have been used to investigate the brain of chronic painful TMD individuals. Furthermore, this review guides practitioners on relevant aspects of AI and how AI and neuroimaging methods can revolutionize our understanding on the mechanisms of painful TMD and aid in both diagnosis and management to enhance patient outcomes.

Alzheimer's disease classification based on nonlinear high-order features and hypergraph convolutional neural network / 生物医学工程学杂志

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that damages patients' memory and cognitive abilities. Therefore, the diagnosis of AD holds significant importance. The interactions between regions of interest (ROIs) in the brain often involve multiple areas collaborating in a nonlinear manner. Leveraging these nonlinear higher-order interaction features to their fullest potential contributes to enhancing the accuracy of AD diagnosis. To address this, a framework combining nonlinear higher-order feature extraction and three-dimensional (3D) hypergraph neural networks is proposed for computer-assisted diagnosis of AD. First, a support vector machine regression model based on the radial basis function kernel was trained on ROI data to obtain a base estimator. Then, a recursive feature elimination algorithm based on the base estimator was applied to extract nonlinear higher-order features from functional magnetic resonance imaging (fMRI) data. These features were subsequently constructed into a hypergraph, leveraging the complex interactions captured in the data. Finally, a four-dimensional (4D) spatiotemporal hypergraph convolutional neural network model was constructed based on the fMRI data for classification. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrated that the proposed framework outperformed the Hyper Graph Convolutional Network (HyperGCN) framework by 8% and traditional two-dimensional (2D) linear feature extraction methods by 12% in the AD/normal control (NC) classification task. In conclusion, this framework demonstrates an improvement in AD classification compared to mainstream deep learning methods, providing valuable evidence for computer-assisted diagnosis of AD.

Encephalic ventricular volumetry in multislice computed tomography images in adults with normal cognitive functions / Volumetría ventricular encefálica en imágenes de tomografía computarizada multicorte en adultos con funciones cognitivas normales

Introducción: Debido a la necesidad de un diagnóstico precoz de los trastornos neurodegenerativos, se ha intentado armonizar los criterios diagnósticos mediante métodos morfométricos basados en técnicas de neuroimagen, pero aún no se han obtenido resultados concluyentes. Objetivo: Determinar el volumen ventricular debido a su amplio uso como marcador de atrofia cerebral e identificar el efecto del sexo sobre estas estructuras, según el tipo de cráneo, estimado a partir de técnicas de imagen de tomografía computarizada multicorte. Métodos: Se desarrolló un estudio observacional y descriptivo en 30 sujetos con funciones neurocognitivas y exploración neuropsiquiátrica normales, con edades comprendidas entre 45 y 54 años, a los que se les realizó una tomografía computarizada multicorte simple de cráneo. Se utilizó un método de segmentación de imágenes basado en la homogeneidad. Resultados: Los volúmenes ventriculares mostraron una correlación significativa y positiva entre ellos, excepto entre el tercer y cuarto ventrículo y el tercero y el volumen ventricular derecho. Los estadísticos del modelo lineal multivariante aplicado mostraron que sólo eran significativos en función del sexo y del tipo de cráneo. No se encontraron diferencias significativas con respecto al sexo en ningún volumen, excepto en el tercer ventrículo (p= 0,01). Lo mismo ocurrió por tipo de cráneo (p= 0,005). Conclusiones: El método de morfometría del sistema ventricular encefálico a partir de imágenes de Tomografía Computarizada / Segmentación por homogeneidad, permitió cuantificar los cambios volumétricos cerebrales asociados al envejecimiento normal y puede ser utilizado como biomarcador de la relación entre la estructura cerebral y las funciones cognitivas(AU)

Introduction: Due to the need for an early diagnosis of neurodegenerative disorders, attempts have been made to harmonize diagnostic criteria using morphometric methods based on neuroimaging techniques, but conclusive results have not yet been obtained. Objective: To determine the ventricular volume due to its wide use as a marker of cerebral atrophy and to identify the effect of sex on these structures, according to the type of skull, estimated from multislice computed tomography imaging techniques. Methods: An observational and descriptive study was developed in 30 subjects with normal neurocognitive functions and neuropsychiatric examination, aged between 45 and 54 years, who underwent a simple multislice CT scan of the skull. An image segmentation method based on homogeneity was used. Results: The ventricular volumes showed a significant and positive correlation between them, except between the third and fourth ventricles and the third and the right ventricular volume. The statistics in the multivariate linear model applied showed that they were only significant in terms of sex and type of skull. No significant differences were found regarding sex in any volume except in the third ventricle (p= 0.01). The same occurred by type of skull (p= 0.005). Conclusions: The morphometry method of the encephalic ventricular system from Computed Tomography images / Segmentation by homogeneity, allowed to quantify the cerebral volumetric changes associated with normal aging and can be used as a biomarker of the relationship between brain structure and cognitive functions(AU)

Contribución de la neuroimagen al diagnóstico y seguimiento de la esquizofrenia: una breve revisión sistemática / The neuroimaging contribution to the schizophrenia diagnosis and monitoring: a brief systematic review

RESUMEN: Introducción: La neuroimagen estructural y funcional en la esquizofrenia ha tomado fuerza en los últimos años, por lo que esta revisión tiene por objetivo describir hallazgos de esta técnica que contribuyen a la fisiopatología, diagnóstico y pronóstico de esta patología. Métodos: Se realizó una búsqueda en PubMed/Medline de estudios clínicos que abordan el estudio con neuroimágenes en la esquizofrenia. Resultados: La búsqueda arrojó 2200 resultados, de los cuales fueron incluidos 13 estudios, los que arrojaron hallazgos que se tradujeron en alteraciones neurocognitivas, tales como alteraciones funcionales y estructurales de la amígdala asociada a síntomas negativos, reducción morfométrica de la región frontal, alteraciones en la perfusión del giro del cíngulo anterior y la corteza parietal inferior izquierda, desregulación de la enzima histona deacetilasa, entre otros. Conclusiones: Esta revisión brinda una visión actualizada sobre los hallazgos de la neuroimagenología que pueden aportar a la comprensión de los mecanismos patológicos detrás de este trastorno psicótico, así como su utilidad diagnóstica y potencial contribución al seguimiento de esta enfermedad.

ABSTRACT Introduction: Structural and functional neuroimaging in schizophrenia has gained strength in recent years, so this review aims to describe neuroimaging findings that contribute to the physiopathological understanding, monitoring, and diagnosis of this pathology. Methods: A PubMed/Medline search was conducted for clinical studies addressing neuroimaging in schizophrenia. Results: The search yielded 2200 results, from which 13 studies were included, which provided findings, such as functional and structural alterations of the amygdala, which have shown to be associated with negative symptoms; morphometric reduction of the frontal region, alterations in the perfusion of the anterior cingulate gyrus and the lower-left parietal cortex, deregulation of the histone deacetylase enzyme, among others which translate clinically in neurocognitive deficits. Conclusions: This review provides an updated view on the findings of neuroimaging that can contribute to the understanding of the pathological mechanisms behind this psychotic disorder, its diagnostic usefulness, and its potential contribution to the prognosis and follow-up of this disease.

Influence of Islamic religion and spirituality on the well-being and quality of life of cancer patients: a meta-analysis and a hypothetical model of cerebral mechanisms / Influência da religião e da espiritualidade islâmica no bem-estar e na qualidade de vida de pacientes com câncer: uma metanálise e um modelo hipotético de mecanismos cerebrais

OBJECTIVE: To systematically analyze quantitative data about the effects of religion/spirituality and the well-being/quality of life of cancer patients. The second aim was to hypothesize a neurophysiological model of the association between religion/spirituality and the brain. METHODS: This study met the PRISMA Statement and was registered at PROSPERO database. Randomized and Controlled trials investigating religion/spirituality and well-being/quality of life of cancer patients were included. Based on neuroimaging and neurophysiology studies, a neuroanatomical model was developed to hypothesize the relationship between neuroscience and religion/spirituality. RESULTS: A large effect size was found on the improvement of well-being/quality of life (SMD = 3.90 [2.43-5.38], p < 0.01). Heterogeneity was high among studies (I2 = 98%, p < 0.01). Specific regions of the brain, such as the temporal lobes, amygdalae and hippocampus, regions from the limbic system, were hypothesized to take part in the religion/spirituality phenomena and the well-being/quality of life improvement. CONCLUSION: Religion/spirituality intervention, mainly the Islamic, promotes an improvement on wellbeing/quality of life of cancer patients.

OBJETIVO: Analisar sistematicamente dados quantitativos sobre os efeitos da religião/espiritualidade e o bem-estar/qualidade de vida de pacientes com câncer. O segundo objetivo foi levantar a hipótese de um modelo neurofisiológico da associação entre religião/espiritualidade e o cérebro. MÉTODOS: Este estudo seguiu as recomendações do PRISMA e foi registrado no PROSPERO. Estudos randomizados e controlados investigando religião/espiritualidade e o bem-estar/qualidade de vida de pacientes com câncer foram incluídos. Com base em estudos de neuroimagem e neurofisiologia, um modelo neuroanatômico foi desenvolvido para hipotetizar relações entre neurociência e religião/espiritualidade. RESULTADOS: Um tamanho de efeito grande foi encontrado na melhoria do bem-estar/qualidade de vida (SMD = 3,90 [2,43-5,38], p < 0,01). A heterogeneidade foi alta entre os estudos (I2 = 98%, p < 0,01). Regiões específicas do cérebro, como lobos temporais, amídalas e hipocampo, regiões do sistema límbico, foram hipotetizadas como participantes dos fenômenos religião/espiritualidade e melhoria do bem-estar/qualidade de vida. CONCLUSÃO: A intervenção religiosa/espiritual, principalmente islâmica, promove melhora no bem-estar/qualidade de vida em pacientes com câncer.

Dor neuropática na prática clínica: ênfase nos instrumentos diagnósticos / Neuropathic pain in clinical practice: emphasis on diagnostic tools

A dor neuropática é causada por uma lesão ou doença do sistema nervoso somatossensitivo. Trata-se de uma manifestação sindrômica que envolve mecanismos inflamatórios e imunes com fisiopatologia ainda pouco esclarecida. O espectro de apresentação da dor neuropática é amplo e, assim, constitui um desafio na prática clínica. Este problema de saúde pública necessita de ampla capacidade técnica dos clínicos generalistas. Torna-se relevante identificar o potencial de cronificação do sintoma e adotar abordagens mitigantes do processo lesivo, estrutural e emocional. Nesse sentido, o diagnóstico adequado da dor neuropática é o primeiro passo na abordagem ao paciente. Diante disso, essa revisão objetiva facilitar a melhor escolha dos métodos diagnósticos no manejo clínico do paciente. Dentre estes, é possível citar a imagem por ressonância magnética funcional, eletroneuromiografia, tomografia por emissão de pósitrons, microneurografia, teste quantitativo sensorial, biópsias de pele, estudos de condução nervosa e de potencial somatossensorial evocado. A dor, por ser um processo sensorial subjetivo, apresenta amplo espectro de manifestações clínicas. Por essa razão, é possível fazer uso de técnicas como métodos de triagem e exames complementares para um diagnóstico mais específico.

Neuropathic pain is caused by an injury or illness of the somatosensory nervous system. It is a syndromic manifestation that involves inflammatory and immune mechanisms, whose pathophysiology is still poorly understood. The spectrum of presentation of neuropathic pain is wide and, therefore, it is a challenge in clinical practice. This public health problem requires the broad technical capacity of general practitioners. It is relevant to identify the potential for chronicity of the symptom and adopt mitigating approaches to the harmful, structural, and emotional process. In this sense, the proper diagnosis of neuropathic pain is the first step in approaching the patient. Therefore, this review aims to facilitate the best choice of diagnostic methods in the clinical management of the patient. Among these, functional magnetic resonance imaging, electroneuromyography, positron emission tomography, microneurography, quantitative sensory testing, skin biopsies, nerve conduction and evoked somatosensory potential studies are possible. Pain, being a subjective sensory process, has a wide spectrum of clinical manifestations. For this reason, it is possible to make use of techniques such as screening methods and complementary exams for a more specific diagnosis.

Parkinson's disease and periodic limb movement in sleep / Doença de Parkinson e movimentos periódicos dos membros durante o sono

Parkinson's disease is a neurodegenerative disease understood as a complex syndrome with motor and non-motor symptoms, including sleep-related conditions, such as periodic limb movements in sleep (PLMS). This paper presents issues regarding Parkinson's disease, motor and non-motor symptoms, sleep physiology, and PLMS. In conclusion, both conditions seem to be correlated through impairment of the dopaminergic system.

A doença de Parkinson é uma doença neurodegenerativa entendida como uma síndrome complexa com sintomas motores e não motores, incluindo condições relacionadas ao sono, como movimentos periódicos dos membros durante o sono (MPMS). Este artigo apresenta questões relacionadas à doença de Parkinson, sintomas motores e não motores, fisiologia do sono e MPMS. Em conclusão, ambas as condições parecem estar correlacionadas por comprometimento do sistema dopaminérgico.

Clinical and radiological features of main dementias / Aspectos clínicos e radiológicos das principais demências

Dementia is a syndrome characterized by a decline of two or more cognitive functions, affecting social or professional life. Alzheimer's Disease is a neurodegenerative disorder that represents 53% of dementia cases; memory loss, inability to recognize faces, impaired judgement, disorientation and confusion are possible common symptoms. Vascular Dementia is responsible for 42% of dementia cases, due to cerebrovascular pathologies, and the clinical aspects are related to the extension and location of the brain injury. Lewy Bodies Dementia is a neurodegenerative disorder that represents 15% of dementia cases, and its symptoms include visual hallucinations, parkinsonism and fluctuating cognitive decline. Frontotemporal dementia is a group of clinical syndromes, divided in Behavioral-variant, characterized by disinhibition, compulsions, apathy, aberrant sexual behavior and executive dysfunction; and Primary Progressive Aphasia, which is subdivided in Nonfluentvariant and Semantic-variant. Vitamin B12 deficiency is a reversible cause of dementia, with a wide clinical feature, that includes psychiatric symptoms such as depression and irritability, hematological symptoms related to anemia (e.g. dyspnea and fatigue), and neurological symptoms including dementia and neuropathy. Normal pressure hydrocephalus is also reversible, presenting forgetfulness, changes in mood, decline of executive functions, reduced attention, and a lack of interest in daily activities as symptoms. The radiological findings vary depending on the etiology of dementia. For that reason, understanding neuroimaging and clinical aspects is important to diagnose effectively.

A demência é uma síndrome que consiste em um declínio de um ou mais domínios cognitivos, que afeta o desempenho social ou profissional do indivíduo. A Doença de Alzheimer é um transtorno neurocognitivo que representa 53% dos casos de demência; seus sintomas podem incluir perda de memória, incapacidade de reconhecer rostos familiares, julgamento comprometido desorientação e confusão mental. A Demência Vascular é responsável por 42% dos casos de demência e é causada por doenças cerebrovasculares, seus achados clínicos são relacionados com o local e com a extensão do dano cerebral. Já a Demência por Corpos de Lewy é uma doença neurocognitiva que representa 15% dos casos de demência, cujos sintomas incluem alucinações visuais, parkinsonismo e flutuação cognitiva. A Demência Frontotemporal, por sua vez, é um grupo de síndromes, que se dividem em variante comportamental ­ caracterizada por desinibição, compulsão, apatia, hipersexualidade e disfunções executivas ­ e Afasia Progressiva Primária, subdividida em variante não-fluente e variante semântica, que cursam com disfunções da linguagem. Há, ainda, a Deficiência de Vitamina B12, uma causa reversível de demência. Ela possui um quadro clínico variado, que inclui sintomas psiquiátricos, como depressão e irritabilidade, sintomas hematológicos relacionados a anemia, como dispneia e fadiga) e sintomas neurológicos, que incluem demência e neuropatias. Uma outra causa reversível é a Hidrocefalia de Pressão Normal, que se apresenta com esquecimentos, alterações de humor, perda de função executiva e redução da atenção e do interesse nas atividades cotidianas. Os achados de neuroimagem variam dependendo da etiologia da demência. Assim, compreender os aspectos clínicos e radiológicos é importante para um diagnóstico efetivo..

White matter hyperintensities: initial assessments / Hiperintensidades da substância branca: avaliações iniciais

The white matter hyperintensities (WMH, leucoaraiosis) represent the most common kind of ischemic vascular lesion of the white matter due to small vessel diseases, and occurs frequently in the elderly. Consequent to the neuroimaging identification arouse the need for their assessment. The group of Fazekas proposed a systematized semi-quantitative visual scale to score such lesions where two parameters were considered, extent and localization. The original scale was further modified, to a simplified version. Although other more complex scales have appeared, researchers remarked that the relatively simple Fazekas scale, in comparison to the complex ones and to volumetric measures, appeared to be sufficient when analyzing relationships between clinical parameters and WMH load in a clinical setting.

As hiperintensidades da substância branca (HSB, leucoaraiose) representam o tipo de lesão isquêmica mais comum da substância branca decorrente de doenças de pequenos vasos e ocorre frequentemente em idosos. Consequente à identificação por neuroimagem surgiu a necessidade de sua avaliação. O grupo de Fazekas propos uma escala visual semiquantitativa sistematizada para pontuar tais lesões, onde foram considerados dois parâmetros, extensão e localização. A escala original foi modificada para constituir uma versão mais simplificada. Embora outras escalas mais complexas tenham aparecido, pesquisadores comentaram que a relativamente simples escala de Fazekas, em comparação às mais complexas e a método volumétrico, mostrou-se suficiente quando é analisada a relação entre parâmetros clínicos e a carga de HSB em um cenário clínico.

Proceso para la fusión de neuroimágenes de Tomografía por Emisión de Positrones y Resonancia Magnética / Process for the fusion of Positron Emission Tomography and Magnetic Resonance neuroimaging

En radiología se utilizan varias técnicas imagenológicas para el diagnóstico de enfermedades y la asistencia en intervenciones quirúrgicas con el objetivo de determinar la ubicación y dimensión exacta de un tumor cerebral. Técnicas como la Tomografía por Emisión de Positrones y la Resonancia Magnética permiten determinar la naturaleza maligna o benigna de un tumor cerebral y estudiar las estructuras del cerebro con neuroimágenes de alta resolución. Investigadores a nivel internacional han utilizado diferentes técnicas para la fusión de la Tomografía por Emisión de Positrones y Resonancia Magnética al permitir la observación de las características fisiológicas en correlación con las estructuras anatómicas. La presente investigación tiene como objetivo elaborar un proceso para la fusión de neuroimágenes de Tomografía por Emisión de Positrones y Resonancia Magnética. Para ello se definieron 5 actividades en el proceso y los algoritmos a utilizar en cada una, lo cual propició identificar los más eficientes para aumentar la calidad en el proceso de fusión. Como resultado se obtuvo un proceso de fusión de neuroimágenes basado en un esquema híbrido Wavelet y Curvelet que garantiza obtener imágenes fusionadas de alta calidad(AU)

In radiology, various imaging techniques are used for the diagnosis of diseases and assistance in surgical interventions with the aim of determining the exact location and dimension of a brain tumor. Techniques such as Positron Emission Tomography and Magnetic Resonance can determine the malignant or benign nature of a brain tumor and study brain structures with high-resolution neuroimaging. International researchers have used different techniques for the fusion of Positron Emission Tomography and Magnetic Resonance, allowing the observation of physiological characteristics in correlation with anatomical structures. The present research aims to develop a process for the fusion of neuroimaging of Positron Emission Tomography and Magnetic Resonance Imaging. Five activities were defined in the process and the algorithms to be used in each one, which led identifying the most efficient ones to increase the quality in the fusion process. As a result, a neuroimaging fusion process was obtained based on a hybrid Wavelet and Curvelet scheme that guarantees high quality merged images(AU)

Neuroimaging adolescents with depression in a middle-income country: feasibility of an fMRI protocol and preliminary results

Objective: To test the feasibility and to present preliminary results of a neuroimaging protocol to evaluate adolescent depression in a middle-income setting. Methods: We assessed psychotropic medication-free adolescents (age range 14-16 years) with a diagnosis of major depressive disorder (MDD). Participants underwent a comprehensive clinical evaluation and both structural and functional magnetic resonance imaging (fMRI). In this pilot study, a preliminary single-group analysis of resting-state fMRI (rs-fMRI) data was performed, with a focus on the default mode network (DMN), cognitive control network (CCN), and salience network (SN). Results: The sample included 29 adolescents with MDD (mean age 16.01, SD 0.78) who completed the protocol. Only two participants were excluded due to MRI quality issues (head movement), and were not included in the analyses. The scans showed significant connectivity between the medial prefrontal cortex and posterior cingulate cortex (DMN), the ACC and anterior insula (SN), and the lateral prefrontal cortex and dorsal parietal cortex (CCN). Conclusion: We demonstrated the feasibility of implementing a complex neuroimaging protocol in a middle-income country. Further, our preliminary rs-fMRI data revealed patterns of resting-state connectivity consistent with prior research performed in adolescents from high-income countries.