11 research outputs found

    Craniosynostosis: primary and secondary brain anomalies:A radiologic investigation

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    Craniosynostosis: primary and secondary brain anomalies:A radiologic investigation

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    Neuroimaging young children and associations with neurocognitive development in a South African birth cohort study.

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    Magnetic resonance imaging (MRI) is an indispensable tool for investigating brain development in young children and the neurobiological mechanisms underlying developmental risk and resilience. Sub-Saharan Africa has the highest proportion of children at risk of developmental delay worldwide, yet in this region there is very limited neuroimaging research focusing on the neurobiology of such impairment. Furthermore, paediatric MRI imaging is challenging in any setting due to motion sensitivity. Although sedation and anesthesia are routinely used in clinical practice to minimise movement in young children, this may not be ethical in the context of research. Our study aimed to investigate the feasibility of paediatric multimodal MRI at age 2-3 years without sedation, and to explore the relationship between cortical structure and neurocognitive development at this understudied age in a sub-Saharan African setting. A total of 239 children from the Drakenstein Child Health Study, a large observational South African birth cohort, were recruited for neuroimaging at 2-3 years of age. Scans were conducted during natural sleep utilising locally developed techniques. T1-MEMPRAGE and T2-weighted structural imaging, resting state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy sequences were included. Child neurodevelopment was assessed using the Bayley-III Scales of Infant and Toddler Development. Following 23 pilot scans, 216 children underwent scanning and T1-weighted images were obtained from 167/216 (77%) of children (median age 34.8 months). Furthermore, we found cortical surface area and thickness within frontal regions were associated with cognitive development, and in temporal and frontal regions with language development (beta coefficient ?0.20). Overall, we demonstrate the feasibility of carrying out a neuroimaging study of young children during natural sleep in sub-Saharan Africa. Our findings indicate that dynamic morphological changes in heteromodal association regions are associated with cognitive and language development at this young age. These proof-of-concept analyses suggest similar links between the brain and cognition as prior literature from high income countries, enhancing understanding of the interplay between cortical structure and function during brain maturation

    Phase Image Texture Analysis for Motion Detection in Diffusion MRI (PITA-MDD)

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    Purpose Pronounced spin phase artifacts appear in diffusion-weighted imaging (DWI) with only minor subject motion. While DWI data corruption is often identified as signal drop out in diffusion-weighted (DW) magnitude images, DW phase images may have higher sensitivity for detecting subtle subject motion. Methods This article describes a novel method to return a metric of subject motion, computed using an image texture analysis of the DW phase image. This Phase Image Texture Analysis for Motion Detection in dMRI (PITA-MDD) method is computationally fast and reliably detects subject motion from diffusion-weighted images. A threshold of the motion metric was identified to remove motion-corrupted slices, and the effect of removing corrupted slices was assessed on the reconstructed FA maps and fiber tracts. Results Using a motion-metric threshold to remove the motion-corrupted slices results in superior fiber tracts and fractional anisotropy maps. When further compared to a state-of-the-art magnitude-based motion correction method, PITA-MDD was able to detect comparable corrupted slices in a more computationally efficient manner. Conclusion In this study, we evaluated the use of DW phase images to detect motion corruption. The proposed method can be a robust and fast alternative for automatic motion detection in the brain with multiple applications to inform prospective motion correction or as real-time feedback for data quality control during scanning, as well as after data is already acquired

    "MASSIVE" Brain Dataset: Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation

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    PURPOSE: In this work, we present the MASSIVE (Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation) brain dataset of a single healthy subject, which is intended to facilitate diffusion MRI (dMRI) modeling and methodology development. METHODS: MRI data of one healthy subject (female, 25 years) were acquired on a clinical 3 Tesla system (Philips Achieva) with an eight-channel head coil. In total, the subject was scanned on 18 different occasions with a total acquisition time of 22.5 h. The dMRI data were acquired with an isotropic resolution of 2.5 mm(3) and distributed over five shells with b-values up to 4000 s/mm(2) and two Cartesian grids with b-values up to 9000 s/mm(2) . RESULTS: The final dataset consists of 8000 dMRI volumes, corresponding B0 field maps and noise maps for subsets of the dMRI scans, and ten three-dimensional FLAIR, T1 -, and T2 -weighted scans. The average signal-to-noise-ratio of the non-diffusion-weighted images was roughly 35. CONCLUSION: This unique set of in vivo MRI data will provide a robust framework to evaluate novel diffusion processing techniques and to reliably compare different approaches for diffusion modeling. The MASSIVE dataset is made publically available (both unprocessed and processed) on www.massive-data.org. Magn Reson Med, 2016

    Artificial Systems Can Complement Human Vision in Medical Imaging

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    Texture analysis is an emerging field; and it is just beginning to integrate with radiology. Carrying out research with thousands of images can be overwhelming, without an effective and efficient sorting algorithm. The aim of this experiment was to develop a sample selection-elimination protocol for a large research project seeking to compare fetal 1.5- tesla versus 3-tesla magnetic resonance images. Firstly, we had to find optimal methods for image selection. In a compiled database of 1.5-tesla and 3-tesla images, we began by manually selecting sequences based on discernible-anatomical structures (ventricle, thalamus, grey matter, white matter). Then 1.5-tesla and 3-tesla image batches were categorized into two groups based on gestational age (i.e. first group: 20-28 week; second group: 29 week). The final stage was sample elimination by variance and by real bit-dept

    Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images

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    Despite its great potential in studying brain anatomy and structure, diffusion magnetic resonance imaging (dMRI) is marred by artefacts more than any other commonly used MRI technique. In this paper we present a non-parametric framework for detecting and correcting dMRI outliers (signal loss) caused by subject motion.Signal loss (dropout) affecting a whole slice, or a large connected region of a slice, is frequently observed in diffusion weighted images, leading to a set of unusable measurements. This is caused by bulk (subject or physiological) motion during the diffusion encoding part of the imaging sequence. We suggest a method to detect slices affected by signal loss and replace them by a non-parametric prediction, in order to minimise their impact on subsequent analysis. The outlier detection and replacement, as well as correction of other dMRI distortions (susceptibility-induced distortions, eddy currents (EC) and subject motion) are performed within a single framework, allowing the use of an integrated approach for distortion correction. Highly realistic simulations have been used to evaluate the method with respect to its ability to detect outliers (types 1 and 2 errors), the impact of outliers on retrospective correction of movement and distortion and the impact on estimation of commonly used diffusion tensor metrics, such as fractional anisotropy (FA) and mean diffusivity (MD). Data from a large imaging project studying older adults (the Whitehall Imaging sub-study) was used to demonstrate the utility of the method when applied to datasets with severe subject movement.The results indicate high sensitivity and specificity for detecting outliers and that their deleterious effects on FA and MD can be almost completely corrected

    Traumatic spinal cord injury; Theranostic applications of advanced MRI techniques

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    Imaging technology is an important part of the diagnosis and management of spinal trauma. However, many efforts have been made to develop new diagnostic biomarkers through advanced imaging techniques. Unfortunately, there is still no consensus for practical use of biomarkers in SCI patients. The authors conducted an all-encompassing literature review and relevant images were included as examples. Spinal cord and soft-tissue injuries are best evaluated by magnetic resonance imaging (MRI). However, advanced MRI techniques provide researchers with a noninvasive approach that allows evaluation of physiological and biochemical condition of the spinal cord and the brain at cellular and molecular level. The advent of new rehabilitation and treatment strategies could demand more precise and advanced techniques to approach the pathophysiology and anatomy of the spinal cord, offering more accurate and non-invasive support to research and clinical follow up

    Estudio espectroscópico de los núcleos basales mediante técnicas de neuroimagen de último generación

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    [ES]El importante desarrollo tecnológico global y la evolución de las técnicas de diagnóstico por imagen en las últimas décadas permite el estudio detallado del conjunto de órgano-sistemas del ser humano. La actualización constante en el ámbito de la neuroimagen ofrece al neurorradiólogo un amplio abanico de exploraciones para llevar a cabo una valoración detallada, incluso a nivel molecular, de la anatomía y fisiología humanas, cuyo conocimiento en profundidad le capacita para detectar alteraciones que orienten a una determinada patología. La adecuada interpretación de la información obtenida mediante las diversas técnicas radiológicas es un elemento clave para el buen funcionamiento del proceso diagnóstico integrado y multidisciplinar que en última instancia posibilite la mejor atención del paciente. De este modo la imagen posee un papel crucial tanto en el acto diagnóstico como en el ámbito de la investigación. Los núcleos de la base estudiados en este trabajo no son una mera estación de relevo entre la corteza y otras regiones del sistema nervioso central, sino que se trata de estructuras con capacidad de procesamiento de información. Por este motivo es fundamental no sólo el conocimiento puramente anatómico de estas estructuras, sino también el conocimiento de su fisiología a través de múltiples circuitos que globalmente integran y redistribuyen la información recibida. El término núcleos de la base engloba numerosas estructuras profundas, existiendo gran controversia y diversidad de opiniones entre diferentes investigadores a la hora de incluir o no determinadas estructuras bajo esta denominación. En este trabajo se ha decidido incluir como tales los núcleos reconocidos por la Sociedad Internacional de los Ganglios Basales (IBAGS) y los añadidos posteriomente a la luz de nuevas investigaciones. La técnica de elección para reflejar las características morfológicas de estos núcleos ha sido la resonancia magnética (RM), que permite una mayor diferenciación de sus componentes y la adquisición en los diversos planos del espacio con un mayor volumen de información y mejor calidad en el postprocesado que las imágenes de tomografía computarizada (TC), relegadas a una valoración inicial de estos elementos, si bien es cierto que el estudio de la vascularización de los núcleos grises de la base puede ser evaluada con gran exactitud mediante angio-TC. Debido a la localización y dimensiones de varias de estas agrupaciones celulares cabe destacar que en muchos casos su representación ha requerido un importante esfuerzo mediante la realización de varias adquisiciones y múltiples reconstrucciones tanto en las estaciones de trabajo como a través de programas de postprocesado de libre acceso, para su posterior estudio comparativo con los resultados de publicaciones actuales. Se ha realizado tanto un estudio global de los diversos componentes como una evaluación pormenorizada de cada uno de ellos y sus relaciones con estructuras adyacentes. Las dimensiones medias de los núcleos grises de la base obtenidas en sujetos libres de enfermedad concuerdan en términos generales con las referidas en la literatura en las agrupaciones de mayor volumen. La valoración de la región subtalámica ha sido de mayor dificultad dado el pequeño tamaño de sus componentes, por lo que conviene ser cautelosos en el análisis de los mismos. La composición molecular de los núcleos grises profundos, los neurotransmisores y neuromoduladores implicados en las vías directa e indirecta y circuitos paralelos, determina su función, aspecto de mayor relevancia a valorar en este trabajo, para lo que se ha empleado la espectroscopia por RM (ERM), detectando la concentración de los metabolitos de interés médico habitualmente estudiados. Esta técnica no se emplea de modo rutinario en la práctica diaria por lo que las publicaciones acerca de la misma y más concretamente de su aplicación en el ámbito de los núcleos basales no son abundantes, este trabajo supone una nueva aportación en este ámbito. Se han recogido además las alteraciones espectroscópicas que pueden generar las diferentes noxas patológicas al actuar sobre los núcleos de la base, con modificación de los niveles de metabolitos habituales registrados, e incluso ausencia de los mismos, que en definitiva se traducirá en diversos tratornos del movimiento. La ERM posibilita incluso la detección de alteraciones metabólicas antes de que la noxa patológica origine alteraciones morfológicas susceptibles de ser detectadas en los estudios de imagen convencional. Así, esta información molecular, añadida a la de la imagen "clásica", supone una buena herramienta diagnóstica, aportando información adicional que mejora la capacidad diagnóstica y facilita la toma de decisiones por parte del equipo interdisciplinar
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