RESUMEN
Ultra-high contrast (UHC) MRI describes forms of MRI in which little or no contrast is seen on conventional MRI images but very high contrast is seen with UHC techniques. One of these techniques uses the divided subtracted inversion recovery (dSIR) sequence, which, in modelling studies, can produce ten times the contrast of conventional inversion recovery (IR) sequences. When used in cases of mild traumatic brain injury (mTBI), the dSIR sequence frequently shows extensive abnormalities in white matter that appears normal when imaged with conventional T2-fluid-attenuated IR (T2-FLAIR) sequences. The changes are bilateral and symmetrical in white matter of the cerebral and cerebellar hemispheres. They partially spare the anterior and posterior central corpus callosum and peripheral white matter of the cerebral hemispheres and are described as the whiteout sign. In addition to mTBI, the whiteout sign has also been seen in methamphetamine use disorder and Grinker's myelinopathy (delayed post-hypoxic leukoencephalopathy) in the absence of abnormalities on T2-FLAIR images, and is a central component of post-insult leukoencephalopathy syndromes. This paper describes the concept of ultra-high contrast MRI, the whiteout sign, the theory underlying the use of dSIR sequences and post-insult leukoencephalopathy syndromes.
Asunto(s)
Leucoencefalopatías , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Leucoencefalopatías/diagnóstico por imagen , Lesiones Encefálicas/diagnóstico por imagen , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patologíaRESUMEN
Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a small range of tissues with specific T1 and T2 values. In the T1 domain, we describe the implementation of the divided Subtracted Inversion Recovery Sequence (dSIR), which is used to image very small changes in T1 from normal in white matter. dSIR has shown widespread changes in otherwise normal-appearing white matter in patients suffering from mild traumatic brain injury (mTBI), substance abuse, and ischemic leukoencephalopathy. It can also be targeted to measure small changes in T1 from normal in other tissues. In the T2 domain, we describe the divided echo subtraction (dES) sequence that is used to image musculoskeletal tissues with a very short T2*. These tissues include fascia, tendons, and aponeuroses. In this manuscript, we explain how this contrast is generated, review how these techniques are used in our research, and discuss the current challenges and limitations of this technique.
RESUMEN
Averaging is commonly used for data reduction/aggregation to analyse high-dimensional MRI data, but this often leads to information loss. To address this issue, we developed a novel technique that integrates diffusion tensor metrics along the whole volume of the fibre bundle using a 3D mesh-morphing technique coupled with principal component analysis for delineating case and control groups. Brain diffusion tensor MRI scans of high school rugby union players (n = 30, age 16-18) were acquired on a 3â T MRI before and after the sports season. A non-contact sport athlete cohort with matching demographics (n = 12) was also scanned. The utility of the new method in detecting differences in diffusion tensor metrics of the right corticospinal tract between contact and non-contact sport athletes was explored. The first step was to run automated tractography on each subject's native space. A template model of the right corticospinal tract was generated and morphed into each subject's native shape and space, matching individual geometry and diffusion metric distributions with minimal information loss. The common dimension of the 20 480 diffusion metrics allowed further data aggregation using principal component analysis to cluster the case and control groups as well as visualization of diffusion metric statistics (mean, ±2 SD). Our approach of analysing the whole volume of white matter tracts led to a clear delineation between the rugby and control cohort, which was not possible with the traditional averaging method. Moreover, our approach accounts for the individual subject's variations in diffusion tensor metrics to visualize group differences in quantitative MR data. This approach may benefit future prediction models based on other quantitative MRI methods.
RESUMEN
Large animal models of mild traumatic brain injury (mTBI) are needed to elucidate the pathophysiology of mechanical insult to a gyrencephalic brain. Sheep (ovis aries) are an attractive model for mTBI because of their neuroanatomical similarity to humans; however, few histological studies of sheep mTBI models have been conducted. We previously developed a sheep mTBI model to pilot methods for investigating the mechanical properties of brain tissue after injury. Here, we sought to histologically characterize the cortex under the impact site in this model. Three animals received a closed skull mTBI with unconstrained head motion, delivered with an impact stunner, and 3 sham animals were anesthetized but did not receive an impact. Magnetic resonance imaging (MRI) of the brain was performed before and after the impact and revealed variable degrees of damage to the skull and brain. Fluorescent immunohistochemistry revealed regions of hemorrhage in the cortex underlying the impact site in 2 of 3 mTBI sheep, the amount of which correlated with the degree of damage observed on the post-impact MRI scans. Labeling for microtubule-associated protein 2 and neuronal nuclear protein revealed changes in cellular anatomy, but, unexpectedly, glial fibrillary acidic protein and ionized calcium-binding adaptor molecule 1 labeling were relatively unchanged compared to sham animals. Our findings provide preliminary evidence of vascular and neuronal damage with limited glial reactivity and highlight the need for further in-depth histological assessment of large animal mTBI models.
RESUMEN
Background: Delayed Post-Hypoxic Leukoencephalopathy (DPHL), or Grinker's myelinopathy, is a syndrome in which extensive changes are seen in the white matter of the cerebral hemispheres with MRI weeks or months after a hypoxic episode. T2-weighted spin echo (T2-wSE) and/or T2-Fluid Attenuated Inversion Recovery (T2-FLAIR) images classically show diffuse hyperintensities in white matter which are thought to be near pathognomonic of the condition. The clinical features include Parkinsonism and akinetic mutism. DPHL is generally regarded as a rare condition. Methods and Results: Two cases of DPHL imaged with MRI nine months and two years after probable hypoxic episodes are described. No abnormalities were seen on the T2-FLAIR images with MRI, but very extensive changes were seen in the white matter of the cerebral and cerebellar hemisphere on divided Subtraction Inversion Recovery (dSIR) images. dSIR sequences may produce ten times the contrast of conventional inversion recovery (IR) sequences from small changes in T1. The clinical findings in both cases were of cognitive impairment without Parkinsonism or akinetic mutism. Conclusion: The classic features of DPHL may only represent the severe end of a spectrum of diseases in white matter following global hypoxic injury to the brain. The condition may be much more common than is generally thought but may not be recognized using conventional clinical and MRI criteria for diagnosis. Reappraisal of the syndrome of DPHL to include clinically less severe cases and to encompass recent advances in MRI is advocated.
RESUMEN
Automated 3D brain segmentation methods have been shown to produce fast, reliable, and reproducible segmentations from magnetic resonance imaging (MRI) sequences for the anatomical structures of the human brain. Despite the extensive experimental research utility of large animal species such as the sheep, there is limited literature on the segmentation of their brains relative to that of humans. The availability of automatic segmentation algorithms for animal brain models can have significant impact for experimental explorations, such as treatment planning and studying brain injuries. The neuroanatomical similarities in size and structure between sheep and humans, plus their long lifespan and docility, make them an ideal animal model for investigating automatic segmentation methods.This work, for the first time, proposes an atlas-free fully automatic sheep brain segmentation tool that only requires structural MR images (T1-MPRAGE images) to segment the entire sheep brain in less than one minute. We trained a convolutional neural network (CNN) model - namely a four-layer U-Net - on data from eleven adult sheep brains (training and validation: 8 sheep, testing: 3 sheep), with a high overall Dice overlap score of 93.7%.Clinical relevance- Upon future validation on larger datasets, our atlas-free automatic segmentation tool can have clinical utility and contribute towards developing robust and fully automatic segmentation tools which could compete with atlas-based tools currently available.
Asunto(s)
Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Adulto , Humanos , Animales , Ovinos , Procesamiento de Imagen Asistido por Computador/métodos , Imagen por Resonancia Magnética/métodos , Redes Neurales de la Computación , Encéfalo/diagnóstico por imagen , AlgoritmosRESUMEN
Our study methodology is motivated from three disparate needs: one, imaging studies have existed in silo and study organs but not across organ systems; two, there are gaps in our understanding of paediatric structure and function; three, lack of representative data in New Zealand. Our research aims to address these issues in part, through the combination of magnetic resonance imaging, advanced image processing algorithms and computational modelling. Our study demonstrated the need to take an organ-system approach and scan multiple organs on the same child. We have pilot tested an imaging protocol to be minimally disruptive to the children and demonstrated state-of-the-art image processing and personalized computational models using the imaging data. Our imaging protocol spans brain, lungs, heart, muscle, bones, abdominal and vascular systems. Our initial set of results demonstrated child-specific measurements on one dataset. This work is novel and interesting as we have run multiple computational physiology workflows to generate personalized computational models. Our proposed work is the first step towards achieving the integration of imaging and modelling improving our understanding of the human body in paediatric health and disease.
RESUMEN
Traumatic brain injury (TBI) is defined as brain damage due to an external force that negatively impacts brain function. Up to 90% of all TBI are considered in the mild severity range (mTBI) but there is still no therapeutic solution available. Therefore, further understanding of the mTBI pathology is required. To assist with this understanding, we developed a cell injury device (CID) based on a dielectric elastomer actuator (DEA), which is capable of modeling mTBI via injuring cultured cells with mechanical stretching. Our injury model is the first to use patient-derived brain pericyte cells, which are ubiquitous cells in the brain involved in injury response. Pericytes were cultured in our CIDs and mechanically strained up to 40%, and by at least 20%, prior to gene expression analysis. Our injury model is a platform capable of culturing and stretching primary human brain pericytes. The heterogeneous response in gene expression changes in our result may suggest that the genes implicated in pathological changes after mTBI could be a patient-dependent response, but requires further validation. The results of this study demonstrate that our CID is a suitable tool for simulating mTBI as an in vitro stretch injury model, that is sensitive enough to induce responses from primary human brain pericytes due to mechanical impacts.
RESUMEN
Mild traumatic brain injury (mTBI), commonly known as concussion, is a complex neurobehavioral phenomenon affecting six in 1000 people globally each year. Symptoms last between days and years as microstructural damage to axons and neurometabolic changes result in brain network disruption. There is no clinically available objective biomarker to diagnose the severity of injury or monitor recovery. However, emerging evidence suggests eye movement dysfunction (e.g., saccades and smooth pursuits) in patients with mTBI. Patients with a higher symptom burden and prolonged recovery time following injury may show higher degrees of eye movement dysfunction. Likewise, recent advances in magnetic resonance imaging (MRI) have revealed both white matter tract damage and functional network alterations in mTBI patients, which involve areas responsible for the ocular motor control. This scoping review is presented in three sections: Section 1 explores the anatomical control of eye movements to aid the reader with interpreting the discussion in subsequent sections. Section 2 examines the relationship between abnormal MRI findings and eye tracking after mTBI based on the available evidence. Finally, Section 3 communicates gaps in our knowledge about MRI and eye tracking, which should be addressed in order to substantiate this emerging field.