Radiological Pathological Correlations in Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that has been increasingly linked to traumatic brain injury. The neuropathology that distinguishes CTE from other tauopathies includes hyperphosphorylated tau (pTau) tangles and tau positive astrocytes irregularly distributed in cortical sulcal depths and clustered around perivascular foci. These features are clearly identified using immunohistochemistry, but are undetectable to current clinical imaging methods. Diffusion imaging has been proposed as a noninvasive method to detect the pathognomonic lesion of CTE in vivo because of its high sensitivity to microstructural alterations in tissue structure. While several diffusion imaging approaches, ranging from diffusion tensor imaging (DTI) to more advanced schemes such as generalized q-sampling imaging (GQI) and diffusion kurtosis imaging (DKI) may prove useful, the relationship between changes in diffusion-derived metrics and the underlying pathology remains unknown. We have developed and implemented a method of perform radiological-pathological correlations in tissues with diagnoses of CTE, aimed to determine whether high spatial resolution diffusion imaging is capable of sensitively detecting pTau pathology. Human ex vivo cortical tissues diagnoses with Stage III/IV CTE, Alzheimer’s disease (AD) or frontotemporal lobar dementia (FTLD) were scanned in an 11.74T Agilent MRI scanner using DTI, GQI and DKI acquisition schemes with isotropic in-plane spatial resolution of 250µm and 500µm slice thickness. Following image acquisition, tissues were sectioned and stained for histopathological markers including AT8 (pTau), GFAP (astrocytes) and Myelin Black Gold II (myelinated white matter). A custom script was used to co-register histological to MRI images, allowing for the ability to perform high spatial resolution correlations of histological with diffusion metrics. Using this approach, we found no relationship between pTau in sulcal depths and any of our DTI, GQI and DKI based measures. Interestingly, we found that white matter underlying sulcal depths in CTE tissues showed signs of disruption, a finding that we did not observe in AD or FTLD tissues. Furthermore, white matter integrity in these regions was correlated with fractional anisotropy. These findings demonstrate that high spatial resolution diffusion imaging is capable of detecting white matter disorganization closely related to pTau pathology in CTE, and may provide a more sensitive and specific means of diagnosing CTE

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field

In vivo MRI mapping of brain iron deposition across the adult lifespan

Disruption of iron homeostasis as a consequence of aging is thought to cause iron levels to increase, potentially promoting oxidative cellular damage. Therefore, understanding how this process evolves through the lifespan could offer insights into both the aging process and the development of aging-related neurodegenerative brain diseases. This work aimed to map, in vivo for the first time with an unbiased whole-brain approach, age-related iron changes using quantitative susceptibility mapping (QSM)—a new postprocessed MRI contrast mechanism. To this end, a full QSM standardization routine was devised and a cohort of N = 116 healthy adults (20–79 years of age) was studied. The whole-brain and ROI analyses confirmed that the propensity of brain cells to accumulate excessive iron as a function of aging largely depends on their exact anatomical location. Whereas only patchy signs of iron scavenging were observed in white matter, strong, bilateral, and confluent QSM–age associations were identified in several deep-brain nuclei—chiefly the striatum and midbrain—and across motor, premotor, posterior insular, superior prefrontal, and cerebellar cortices. The validity of QSM as a suitable in vivo imaging technique with which to monitor iron dysregulation in the human brain was demonstrated by confirming age-related increases in several subcortical nuclei that are known to accumulate iron with age. The study indicated that, in addition to these structures, there is a predilection for iron accumulation in the frontal lobes, which when combined with the subcortical findings, suggests that iron accumulation with age predominantly affects brain regions concerned with motor/output functions

Prenatal stress exposure and multimodal assessment of amygdala-medial prefrontal cortex connectivity in infants

Stressful experiences are linked to neurodevelopment. There is growing interest in the role of stress in the connectivity between the amygdala and medial prefrontal cortex (mPFC), a circuit that subserves automatic emotion regulation. However, the specific timing and mechanisms that underlie the association between stress and amygdala-mPFC connectivity are unclear. Many factors, including variations in fetal exposure to maternal stress, appear to affect early developing brain circuitry. However, few studies have examined the associations of stress and amygdala-mPFC connectivity in early life, when the brain is most plastic and sensitive to environmental influence. In this longitudinal pilot study, we characterized the association between prenatal stress and amygdala-mPFC connectivity in young infants (approximately age 5 weeks). A final sample of 33 women who provided data on preconception and prenatal stress during their pregnancy returned with their offspring for a magnetic resonance imaging scan session, which enabled us to characterize amygdala-mPFC structural and functional connectivity as a function of prenatal stress. Increased prenatal stress was associated with decreased functional connectivity and increased structural connectivity between the amygdala and mPFC. These results provide insight into the influence of prenatal maternal stress on the early development of this critical regulatory circuitry

Kinetic modelling of [(11)C]PBR28 for 18 kDa translocator protein PET data:A validation study of vascular modelling in the brain using XBD173 and tissue analysis

The 18 kDa translocator protein (TSPO) is a marker of microglia activation in the central nervous system and represents the main target of radiotracers for the in vivo quantification of neuroinflammation with positron emission tomography (PET). TSPO PET is methodologically challenging given the heterogeneous distribution of TSPO in blood and brain. Our previous studies with the TSPO tracers [11C]PBR28 and [11C]PK11195 demonstrated that a model accounting for TSPO binding to the endothelium improves the quantification of PET data. Here, we performed a validation of the kinetic model with the additional endothelial compartment through a displacement study. Seven subjects with schizophrenia, all high-affinity binders, underwent two [11C]PBR28 PET scans before and after oral administration of 90 mg of the TSPO ligand XBD173. The addition of the endothelial component provided a signal compartmentalization much more consistent with the underlying biology, as only in this model, the blocking study produced the expected reduction in the tracer concentration of the specific tissue compartment, whereas the non-displaceable compartment remained unchanged. In addition, we also studied TSPO expression in vessels using 3D reconstructions of histological data of frontal lobe and cerebellum, demonstrating that TSPO positive vessels account for 30% of the vascular volume in cortical and white matter

Applications of MRI Magnetic Susceptibility Mapping in PET-MRI Brain Studies

Magnetic susceptibility mapping (SM) uses magnetic resonance imaging (MRI) phase images to produce maps of the magnetic susceptibility (χ) of tissues. This work focuses on the applications of SM-based imaging to PET-MRI, the hybrid imaging modality which combines positron emission tomography (PET) with MRI. First, the potential of using SM to aid PET attenuation correction (AC) is explored. AC for PET-MRI is challenging as PET-MRI provides no information regarding the electron density of tissues. Recently proposed SM methods for calculating the χ in regions of no MRI signal are used to segment air, bone and soft tissue in order to create AC maps. In the head, SM methods are found to produce inferior air/bone segmentations to high-performing AC methods, but result in more accurate AC than ultrashort-echo (UTE)-based air/bone segmentations, and may be able to provide additional information in subjects with atypical anatomy. Secondly, a SM pipeline for inclusion in a PET-MRI study into biomarkers for Alzheimer’s disease (AD) is developed. In the Insight46 study 500 healthy subjects from the 1946 MRC National Survey of Health and Development are undergoing a comprehensive PET-MRI protocol at two time-points. SM processing methods are compared and optimised, and a method for processing images with oblique imaging planes is developed. The effect of using different tools for automated segmentation of regions of interest (ROIs) on reported regional χ values is analysed. The ROIs resulting from different tools are found to result in large differences in χ values. FIRST is chosen as the most appropriate ROI segmentation tool for this study based on anatomical accuracy as assessed by a neuroradiologist. Initial analysis of χ values from 100 subjects using data from the first time-point is carried out. No significant association with regional χ values is found for amyloid status, PET radiotracer uptake, or APOE genotype

The sensitivity of diffusion MRI to microstructural properties and experimental factors

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic

Cortical Morphology and MRI Signal Intensity Analysis in Paediatric Epilepsy

Epilepsy encompasses a great variety of aetiologies, and as such is not a single disease but a group of diseases characterised by unprovoked seizures.The primary aim of the work presented in this thesis was to use multimodal structural imaging to improve understanding of epilepsy related brain pathology, both the epileptogenic lesions themselves and extralesional pathology, in order to improve pre-surgical planning in medicationresistant epilepsy and improve understanding of the underlying pathogenic mechanisms. The work focuses on 2 epilepsy aetiologies: focal cortical dysplasia (FCD) (chapters 2 and 3) and mesial temporal lobe epilepsy (chapters 4 & 5). Chapter 2 of this thesis develops surface-based, structural MRI post-processing techniques that can be applied to clinical T1 and FLAIR images to complement current MRI-based diagnosis of focal cortical dysplasias. Chapter 3 uses the features developed in Chapter 2 within a machine learning framework to automatically detect FCDs, obtaining 73% sensitivity using a neural network. Chapter 4 develops an in vivo method to explore neocortical gliosis in adults with TLE, while Chapter 5 applies this method to a paediatric cohort. Finally, the concluding chapter discusses contributions, main limitations and outlines options for future research

CHARACTERIZATION OF BRAIN TISSUE MICROSTRUCTURES WITH DIFFUSION MRI

Diffusion MRI is a useful medical imaging tool for noninvasive mapping of the neuroanatomy and brain connectivity. In this dissertation, we worked on developing diffusion MRI techniques to probe brain tissue microstructures from various perspectives. Spatial resolution of the diffusion MRI is the key to obtain accurate microstructural information. In Chapter 2 and 3, we focused on developing high-resolution in vivo diffusion MRI techniques, such as 3D fast imaging sequence and a localized imaging approach using selective excitation RF pulses. We demonstrated the power of the superior resolution in delineating complex microstructures in the live mouse brain. With the high resolution diffusion MRI data, we were able to map the intra-hippocampal connectivity in the mouse brain, which showed remarkable similarity with tracer studies (Chapter 4). Using the localized fast imaging technique, we were the first to achieve in utero diffusion MRI of embryonic mouse brain, which revealed the microstructures in the developing brains and the changes after inflammatory injury (Chapter 5). The second half of the dissertation explores the restricted water diffusion at varying diffusion times and microstructure scales, using the oscillating gradient spin-echo (OGSE) diffusion MRI. We showed in the live normal mouse brains that unique tissue contrasts can be obtained at different oscillating frequency. We demonstrated in a neonatal mouse model of hypoxia-ischemia, that in the edema brain tissues, diffusion MRI signal changed much faster with oscillating frequency compared to the normal tissue, indicating significant changes in cell size associated with cytotoxic edema (Chapter 6). In the mild injury mice, OGSE showed exquisite sensitivity in detecting subtle injury in the hippocampus, which may relate to microstructural changes in smaller scales, such as the subcellular organelles (Chapter 7). Finally, we addressed the technical issues of OGSE diffusion MRI, and proposed a new hybrid OGSE sequence with orthogonally placed pulsed and oscillating gradients to suppress the perfusion related pseudo-diffusion (Chapter 8). In conclusion, we developed in vivo high-resolution diffusion techniques, and time-dependent diffusion measurements to characterize brain tissue microstructures in the normal and diseased mouse brains. The knowledge gained from this dissertation study may advance our understanding on microstructural basis of diffusion MRI

Recent Developments in Fast Kurtosis Imaging

Diffusion kurtosis imaging (DKI) is an extension of the popular diffusion tensor imaging (DTI) technique. DKI takes into account leading deviations from Gaussian diffusion stemming from a number of effects related to the microarchitecture and compartmentalization in biological tissues. DKI therefore offers increased sensitivity to subtle microstructural alterations over conventional diffusion imaging such as DTI, as has been demonstrated in numerous reports. For this reason, interest in routine clinical application of DKI is growing rapidly. In an effort to facilitate more widespread use of DKI, recent work by our group has focused on developing experimentally fast and robust estimates of DKI metrics. A significant increase in speed is made possible by a reduction in data demand achieved through rigorous analysis of the relation between the DKI signal and the kurtosis tensor based metrics. The fast DKI methods therefore need only 13 or 19 images for DKI parameter estimation compared to more than 60 for the most modest DKI protocols applied today. Closed form solutions also ensure rapid calculation of most DKI metrics. Some parameters can even be reconstructed in real time, which may be valuable in the clinic. The fast techniques are based on conventional diffusion sequences and are therefore easily implemented on almost any clinical system, in contrast to a range of other recently proposed advanced diffusion techniques. In addition to its general applicability, this also ensures that any acceleration achieved in conventional DKI through sequence or hardware optimization will also translate directly to fast DKI acquisitions. In this review, we recapitulate the theoretical basis for the fast kurtosis techniques and their relation to conventional DKI. We then discuss the currently available variants of the fast kurtosis techniques, their strengths and weaknesses, as well as their respective realms of application. These range from whole body applications to methods mostly suited for spinal cord or peripheral nerve, and analysis specific to brain white matter. Having covered these technical aspects, we proceed to review the fast kurtosis literature including validation studies, organ specific optimization studies and results from clinical applications