Intracranial fluids dynamics: a quantitative evaluation by means of phase-contrast magnetic resonance imaging

El volumen intracraneal lo integran el volumen de líquido cefalorraquídeo (LCR), el de la sangre y el del parénquima cerebral. La entrada de sangre al cráneo en la sístole incrementa el volumen intracraneal. Según la ley de Monroe-Kellie debe ocurrir una descompensación en los volúmenes restantes para mantener constante el volumen total. Los desequilibrios que se producen en este proceso de la homeostasis cerebral se han asociado tanto a enfermedades neurodegenerativas como a cerebrovasculares. Por tanto, es necesario contar con metodologías adecuadas para analizar la dinámica de los fluidos intracraneales (LCR y sangre). Las secuencias dinámicas de resonancia magnética en contraste de fase (RM-CF) con sincronismo cardíaco permiten cuantificar el flujo de LCR y de sangre durante un ciclo cardíaco. La medición de flujo mediante secuencias de RM-CF es precisa y reproducible siempre que se use un protocolo de adquisición adecuado. La reproducibilidad y exactitud de las medidas dependen también del uso de técnicas adecuadas de posproceso que permitan segmentar las regiones de interés (ROI) independientemente del operador y admitan corregir los errores de fondo introducidos por la supresión imperfecta de las corrientes inducidas y la contribución a la señal de los pequeños movimientos que presenta el mesencéfalo por la transmisión del pulso vascular así como el submuestreo (aliasing), reflejado como un cambio abrupto y opuesto del sentido original del flujo. Estas técnicas de análisis deben también tener en cuenta los errores relacionados con el efecto de volumen parcial (EVP), causado por la presencia de tejido estacionario y de flujo en el interior de los vóxeles de la periferia de la región a estudiar El objetivo principal de esta tesis es desarrollar una metodología reproducible para evaluar cuantitativamente la dinámica de los fluidos intracraneales dentro de espacios de LCR (acueducto de Silvio, cisterna prepontina y espacio perimedular C2C3) y principales vaFlórez Ordóñez, YN. (2009). Intracranial fluids dynamics: a quantitative evaluation by means of phase-contrast magnetic resonance imaging [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/6029Palanci

Retinal drug delivery: rethinking outcomes for the efficient replication of retinal behavior

The retina is a highly organized structure that is considered to be "an approachable part of the brain." It is attracting the interest of development scientists, as it provides a model neurovascular system. Over the last few years, we have been witnessing significant development in the knowledge of the mechanisms that induce the shape of the retinal vascular system, as well as knowledge of disease processes that lead to retina degeneration. Knowledge and understanding of how our vision works are crucial to creating a hardware-adaptive computational model that can replicate retinal behavior. The neuronal system is nonlinear and very intricate. It is thus instrumental to have a clear view of the neurophysiological and neuroanatomic processes and to take into account the underlying principles that govern the process of hardware transformation to produce an appropriate model that can be mapped to a physical device. The mechanistic and integrated computational models have enormous potential toward helping to understand disease mechanisms and to explain the associations identified in large model-free data sets. The approach used is modulated and based on different models of drug administration, including the geometry of the eye. This work aimed to review the recently used mathematical models to map a directed retinal network.The authors acknowledge the financial support received from the Portuguese Science and Technology Foundation (FCT/MCT) and the European Funds (PRODER/COMPETE) for the project UIDB/04469/2020 (strategic fund), co-financed by FEDER, under the Partnership Agreement PT2020. The authors also acknowledge FAPESP – São Paulo Research Foundation, for the financial support for the publication of the article.info:eu-repo/semantics/publishedVersio

MRI quantification of multiple sclerosis pathology

Background: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease and a common cause of neurologic disability. MS pathology is characterized by demyelination, neuroaxonal loss and atrophy. Magnetic Resonance Imaging (MRI) is an essential tool in diagnosing and monitoring MS, but its clinical value could be even further expanded by more advanced and quantitative MRI methods, which may also provide additional pathophysiological insights. Purpose: The overall aim of this thesis was to quantify MS pathology using volumetric brain MRI, ultra-high field brain and cervical spinal cord MRI as well as a newly developed rapid myelin imaging technique in relation to cognitive and physical MS disability. Study I, a prospective 17-year longitudinal study of 37 MS participants with 23 age/sex- matched healthy controls for comparison at the last follow-up. Longitudinal volumetric brain 1.5 Tesla MRI during the second half of the study showed that lesion accumulation and corpus callosum atrophy were the most strongly associated neuroanatomical correlates of cognitive disability, with the lesion fraction being an independent predictor of cognitive performance 8.5 years later. Study II, a prospective cross-sectional study of 35 MS participants and 11 age-matched healthy controls using 3 and 7 Tesla MRI. The study demonstrated involvement of both grey and white matter in MS, not only the brain but also the cervical spinal cord, associated with MS disability. Lesions appeared in proximity to the cerebrospinal fluid (CSF), with special predilection to the periventricular and grey matter surrounding the central canal in secondary progressive MS. Study III, a prospective in vivo (71 MS participants and 21 age/sex-matched healthy controls) and ex vivo (brain tissue from 3 MS donors) study at 3 Tesla, showed that a new clinically approved and feasible rapid myelin imaging technique correlates well with myelin stainings and produces robust in vivo myelin quantification that is related to both current and future cognitive and physical disability in MS. Study IV, an in-depth topographical analysis based on Study III, mapped the distribution of demyelination, both in vivo and ex vivo, in the periventricular and perilesional regions of the brain. A gradient of demyelination with predominance near the CSF spaces was seen. Measures of clinical disability were consistently and more strongly associated with the myelin content in normal-appearing tissue compared to the intralesional myelin content. Conclusions: Lesions and atrophy contribute to cognitive and physical disability in MS but to a varying degree, likely dependent on the relative involvement of white vs. grey matter. Both focal lesions/demyelination as well as diffuse demyelination in normal-appearing white matter shows an apparent gradient from the CSF, which differ between relapsing-remitting and progressive MS subtypes/phases. The growing utility and clinical availability of advanced and quantitative MRI techniques holds promise for improved monitoring of MS pathology and likely represents a vital tool for assessing the efficacy of potential remyelinating/reparative therapies in MS

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of “radiomics and genomics” has been considered under the umbrella of “radiogenomics”. Furthermore, AI in a radiogenomics’ environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor’s characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them