Image Sequence Fusion and Denoising Based on 3D Shearlet Transform

We propose a novel algorithm for image sequence fusion and denoising simultaneously in 3D shearlet transform domain. In general, the most existing image fusion methods only consider combining the important information of source images and do not deal with the artifacts. If source images contain noises, the noises may be also transferred into the fusion image together with useful pixels. In 3D shearlet transform domain, we propose that the recursive filter is first performed on the high-pass subbands to obtain the denoised high-pass coefficients. The high-pass subbands are then combined to employ the fusion rule of the selecting maximum based on 3D pulse coupled neural network (PCNN), and the low-pass subband is fused to use the fusion rule of the weighted sum. Experimental results demonstrate that the proposed algorithm yields the encouraging effects

Quantitative and textural analysis of magnetization transfer and diffusion images in the early detection of brain metastases

Purpose: The sensitivity of the magnetization transfer ratio (MTR) and apparent diffusion coefficient (ADC) for early detection of brain metastases was investigated in mice and humans. Methods: Mice underwent MRI twice weekly for up to 31 days following intra-cardiac injection of the brain-homing breast cancer cell line MDA-MB231-BR. Patients with small cell lung cancer underwent quarterly MRI for a year. MTR and ADC were measured in regions of metastasis and matched contralateral tissue at the final time-point and in registered regions at earlier time-points. Texture analysis and linear discriminant analysis were performed to detect metastasis-containing slices. Results: Compared with contralateral tissue, mouse metastases had significantly lower MTR and higher ADC at the final time-point. Some lesions were visible at earlier time-points on the MTR and ADC maps: 24% of these were not visible on corresponding T2-weighted images. Texture analysis using the MTR maps showed 100% specificity and 98% sensitivity for metastasis at the final time-point, with 77% sensitivity 2-4 days earlier and 46% 5-8 days earlier. Only 2/16 patients developed metastases, and their penultimate scans were normal. Conclusion: Some brain metastases may be detected earlier on MTR than conventional T2; however, the small gain is unlikely to justify ‘predictive’ MRI.The authors gratefully acknowledge the Cambridge Institute Biological Resources Unit for expert animal care and technical assistance, the Histopathology Core Facility, Drs Joe Frank and Diane Palmieri for providing the cell line, the advice of Dr. Dan Tozer, and the support of Cancer Research UK [grant number C14303/A17197], the Brian Cross Memorial Trust, the Addenbrooke’s Charitable Trust, the University of Cambridge, Hutchison Whampoa Ltd, the Cambridge Experimental Cancer Medicine Centre, and the NIHR Cambridge Biomedical Research Centre.This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/mrm.2625

Robust Automatic Rodent Brain Extraction Using 3-D Pulse-Coupled Neural Networks (PCNN)

Brain extraction is an important preprocessing step for further processing (e. g., registration and morphometric analysis) of brain MRI data. Due to the operator-dependent and time-consuming nature of manual extraction, automated or semi-automated methods are essential for large-scale studies. Automatic methods are widely available for human brain imaging, but they are not optimized for rodent brains and hence may not perform well. To date, little work has been done on rodent brain extraction. We present an extended pulse-coupled neural network algorithm that operates in 3-D on the entire image volume. We evaluated its performance under varying SNR and resolution and tested this method against the brain-surface extractor (BSE) and a level-set algorithm proposed for mouse brain. The results show that this method outperforms existing methods and is robust under low SNR and with partial volume effects at lower resolutions. Together with the advantage of minimal user intervention, this method will facilitate automatic processing of large-scale rodent brain studies

Segmentación automática de tejido cerebral en imagen preclínica

En estudios preclínicos neurológicos de imagen de resonancia magnética (MRI) en pequeños animales es común el uso de la segmentación cerebral para su posterior análisis volumétrico y/o registro con otras modalidades de imagen. Este proceso suele realizarse de forma manual, por lo que a menudo se emplea una gran cantidad de tiempo dependiendo del estudio. En este trabajo se propone un nuevo método de segmentación automática basado en registro para facilitar dicho proceso. La propuesta se ha comparado con dos métodos: segmentación manual, que se emplea como referencia, y una segmentación basada en PCNN (Pulse Couple Neural Network) propuesta específicamente para imágenes de rata. El método propuesto consigue buenos resultados en índice de solapamiento y volumen cerebral comparado con el manual, y ofrece además una reducción considerable en el tiempo de ejecución comparado con PCNN.Ingeniería Técnica en Sistemas de Telecomunicació

Development and Maturation of the Brain Following Pediatric mTBI

Pediatric mild traumatic brain injury (mTBI) is a major public health concern with the potential to produce long-lasting cognitive, adaptive, and socio-behavioral outcomes. However, our understanding of how TBI pathophysiology evolves in the developing brain is lacking. Our central hypothesis was that pediatric mTBI results in evolving microstructural dysregulation that leads to functional and structural deficits late in life. To test this hypothesis, we first sought to assess the influence of pediatric mTBI on white matter (WM) dysregulation in early adulthood. To accomplish this, we investigated the effects of single and repeated pediatric mTBI on white matter, focusing on the anterior commissure (AC), a white matter structure distant from the injury site. We demonstrated that mTBI leads to myelin-related diffusion changes in white matter and abnormal oligodendrocyte (OL) development in the AC which are accompanied by behavioral deficits two months after the initial injury. Second, we sought to examine the lifespan evolution of pediatric mTBI. To accomplish this, we investigated the long-term effects of pediatric mTBI at postnatal day 17 and mapped the temporal evolution of the long-term behavioral and associated structural deficits up to late adulthood (18 m) using clinically relevant in-vivo diffusion tensor imaging (DTI) in mice. We demonstrated that a single exposure to a pediatric mTBI in childhood can result in early temporally evolving structural deficits detectable through early diffusion neuroimaging and are correlated to spatial learning and memory impairments late in life. Our results suggest that early in life mTBIs elicit long-term behavioral alterations and OL-associated white matter dysregulation in the developing brain and that such early injuries have the potential to elicit temporally-evolving behavioral and structural deficits late in life. This dissertation provides new insights into how post-pediatric mTBI deficits are manifested both in early adulthood and later in life and describe how such injury evolves over a lifespan resulting in modified tissue characteristics and behavioral profile following pediatric mTBI. Such information will not only provide a deeper understanding of the complex pediatric mTBI pathophysiological development but can serve as the basis for long-term outcome prediction in pediatric mTBI

Neurite Orientation Dispersion and Density Imaging in a Rodent Model of Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) has become a focal point within the medical community due to its increased prevalence in recent years. Unfortunately, there is currently no neuroimaging technique able to accurately diagnose and monitor mTBI in-vivo. One technique that has shown great promise is neurite orientation dispersion and density imaging (NODDI). NODDI is a diffusion MRI (dMRI) technique used to characterize microstructural complexity through the compartmental modelling of neural water fractions into Intra-neurite, Extra-neurite and CSF volume fractions. The overreaching theme of this thesis was to validate NODDI in a preclinical setting to then be applied to imaging of early mTBI. In the first study, NODDI was shown to have high precision and repeatability both between and within subject. Furthermore, it was found that small biological changes

Development of imaging methods for the lithium-pilocarpine model of epilepsy

Anti-inflammatory therapies are promising candidates for the prevention of brain injury following prolonged seizures (status epilepticus). Biomarkers for therapy monitoring are needed to translate these recent findings to the clinic. The aim of this thesis was to develop imaging methods that can be used to monitor anti-inflammatory therapies and monitor disease progression following prolonged seizures. In order to achieve these goals, the lithium-pilocarpine model was used as a model of status epilepticus and novel MRI imaging methods were employed. Various imaging approaches including: quantitative, structural, molecular and functional imaging were tested for their possible investigative utility as imaging biomarkers for neuroprotective therapies. Alongside this, two different anti-inflammatory therapies were tested for their effectiveness to alter brain injury following status epilepticus. This thesis demonstrates that molecular imaging has potential to monitor neuroprotective therapies. Surprisingly, there was little evidence that the anti-inflammatory therapies tested here had beneficial effects. However, this thesis shows that employing novel imaging approaches and automated analysis methods can enable accurate in vivo assessment of disease altering therapies

DETECTING BRAIN-WIDE INTRINSIC CONNECTIVITY NETWORKS USING fMRI IN MICE

Functional neuroimaging methods in mice are essential for unraveling complex neuronal networks that underlie maladaptive behavior in neurological disorder models. By using fMRI to detect intrinsic connectivity networks in mice, we can examine large scale alteration in brain activity and functional connectivity to establish causal associations in brain network changes. The work presented in this dissertation is organized into five chapters. Chapter 1 provides the necessary background required to understand how functional neuroimaging tools such as fMRI detect signal changes attributed to spontaneous neuronal activity of intrinsic connectivity networks in mice. Chapter 2 describes the development of our isotropic fMRI acquisition sequence in mice and semi-automated pipeline for mouse fMRI data. Naïve mouse fMRI scans were used to validated the pipeline by reliably and reproducibly extracting intrinsic connectivity networks. Chapter 3 establishes the development and validation of a novel superparamagenetic iron-oxide nanoparticle to enhance fMRI signal sensitivity. Chapter 4 studies the effects norepinephrine released by locus coeruleus neurons on the default mode network in mice. Norepinephrine release selectively enhanced neuronal activity and connectivity in the Frontal module of the default mode network by suppressing information flow from the Retrosplenial-Hippocampal to the Association modules. Chapter 5 addresses the implications of our findings and addresses the limitations and future studies that can be conducted to expand on this research.Doctor of Philosoph

Multicentre evaluation of MRI variability in the quantification of infarct size in experimental focal cerebral ischaemia

Ischaemic stroke is a leading cause of death and disability in the developed world. Despite that considerable advances in experimental research enabled understanding of the pathophysiology of the disease and identified hundreds of potential neuroprotective drugs for treatment, no such drug has shown efficacy in humans. The failure in the translation from bench to bedside has been partially attributed to the poor quality and rigour of animal studies. Recently, it has been suggested that multicentre animal studies imitating the design of randomised clinical trials could improve the translation of experimental research. Magnetic resonance imaging (MRI) could be pivotal in such studies due to its non-invasive nature and its high sensitivity to ischaemic lesions, but its accuracy and concordance across centres has not yet been evaluated. This thesis focussed on the use of MRI for the assessment of late infarct size, the primary outcome used in stroke models. Initially, a systematic review revealed that a plethora of imaging protocols and data analysis methods are used for this purpose. Using meta-analysis techniques, it was determined that T2-weighted imaging (T2WI) was best correlated with gold standard histology for the measurement of infarctbased treatment effects. Then, geometric accuracy in six different preclinical MRI scanners was assessed using structural phantoms and automated data analysis tools developed in-house. It was found that geometric accuracy varies between scanners, particularly when centre-specific T2WI protocols are used instead of a standardised protocol, though longitudinal stability over six months is high. Finally, a simulation study suggested that the measured geometric errors and the different protocols are sufficient to render infarct volumes and related group comparisons across centres incomparable. The variability increases when both factors are taken into account and when infarct volume is expressed as a relative estimate. Data in this study were analysed using a custom-made semi-automated tool that was faster and more reliable in repeated analyses than manual analysis. Findings of this thesis support the implementation of standardised methods for the assessment and optimisation of geometric accuracy in MRI scanners, as well as image acquisition and analysis of in vivo data for the measurement of infarct size in multicentre animal studies. Tools and techniques developed as part of the thesis show great promise in the analysis of phantom and in vivo data and could be a step towards this endeavour