Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Caracterização de regiões encefálicas no cérebro normal por tensor de difusão e aplicação à epilepsia pós-traumática

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Structural connectivity based on diffusion Kurtosis imaging

Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm

Magnetic resonance imaging determinants of intraindividual variability in the elderly: combined analysis of grey and white matter.

Elderly individuals display a rapid age-related increase in intraindividual variability (IIV) of their performances. This phenomenon could reflect subtle changes in frontal lobe integrity. However, structural studies in this field are still missing. To address this issue, we computed an IIV index for a simple reaction time (RT) task and performed magnetic resonance imaging (MRI) including voxel based morphometry (VBM) and the tract based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) in 61 adults aged from 22 to 88 years. The age-related IIV increase was associated with decreased fractional anisotropy (FA) as well as increased radial (RD) and mean (MD) diffusion in the main white matter (WM) fiber tracts. In contrast, axial diffusion (AD) and grey matter (GM) densities did not show any significant correlation with IIV. In multivariate models, only FA has an age-independent effect on IIV. These results revealed that WM but not GM changes partly mediated the age-related increase of IIV. They also revealed that the association between WM and IIV could not be only attributed to the damage of frontal lobe circuits but concerned the majority of interhemispheric and intrahemispheric corticocortical connections.

Confirmation of functional zones within the human subthalamic nucleus: patterns of connectivity and sub-parcellation using diffusion weighted imaging.

The subthalamic nucleus (STN) is a small, glutamatergic nucleus situated in the diencephalon. A critical component of normal motor function, it has become a key target for deep brain stimulation in the treatment of Parkinson's disease. Animal studies have demonstrated the existence of three functional sub-zones but these have never been shown conclusively in humans. In this work, a data driven method with diffusion weighted imaging demonstrated that three distinct clusters exist within the human STN based on brain connectivity profiles. The STN was successfully sub-parcellated into these regions, demonstrating good correspondence with that described in the animal literature. The local connectivity of each sub-region supported the hypothesis of bilateral limbic, associative and motor regions occupying the anterior, mid and posterior portions of the nucleus respectively. This study is the first to achieve in-vivo, non-invasive anatomical parcellation of the human STN into three anatomical zones within normal diagnostic scan times, which has important future implications for deep brain stimulation surgery.

Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.

MRI tractography is the mapping of neural fiber pathways based on diffusion MRI of tissue diffusion anisotropy. Tractography based on diffusion tensor imaging (DTI) cannot directly image multiple fiber orientations within a single voxel. To address this limitation, diffusion spectrum MRI (DSI) and related methods were developed to image complex distributions of intravoxel fiber orientation. Here we demonstrate that tractography based on DSI has the capacity to image crossing fibers in neural tissue. DSI was performed in formalin-fixed brains of adult macaque and in the brains of healthy human subjects. Fiber tract solutions were constructed by a streamline procedure, following directions of maximum diffusion at every point, and analyzed in an interactive visualization environment (TrackVis). We report that DSI tractography accurately shows the known anatomic fiber crossings in optic chiasm, centrum semiovale, and brainstem; fiber intersections in gray matter, including cerebellar folia and the caudate nucleus; and radial fiber architecture in cerebral cortex. In contrast, none of these examples of fiber crossing and complex structure was identified by DTI analysis of the same data sets. These findings indicate that DSI tractography is able to image crossing fibers in neural tissue, an essential step toward non-invasive imaging of connectional neuroanatomy.

Correlation of diffusion tensor tractography and intraoperative macrostimulation during deep brain stimulation for Parkinson disease.

Object The purpose of this study was to investigate whether diffusion tensor imaging (DTI) of the corticospinal tract (CST) is a reliable surrogate for intraoperative macrostimulation through the deep brain stimulation (DBS) leads. The authors hypothesized that the distance on MRI from the DBS lead to the CST as determined by DTI would correlate with intraoperative motor thresholds from macrostimulations through the same DBS lead. Methods The authors retrospectively reviewed pre- and postoperative MRI studies and intraoperative macrostimulation recordings in 17 patients with Parkinson disease (PD) treated by DBS stimulation. Preoperative DTI tractography of the CST was coregistered with postoperative MRI studies showing the position of the DBS leads. The shortest distance and the angle from each contact of each DBS lead to the CST was automatically calculated using software-based analysis. The distance measurements calculated for each contact were evaluated with respect to the intraoperative voltage thresholds that elicited a motor response at each contact. Results There was a nonsignificant trend for voltage thresholds to increase when the distances between the DBS leads and the CST increased. There was a significant correlation between the angle and the voltage, but the correlation was weak (coefficient of correlation [R] = 0.36). Conclusions Caution needs to be exercised when using DTI tractography information to guide DBS lead placement in patients with PD. Further studies are needed to compare DTI tractography measurements with other approaches such as microelectrode recordings and conventional intraoperative MRI-guided placement of DBS leads.

Prospective and retrospective motion correction in diffusion magnetic resonance imaging of the human brain.

Diffusion-weighting in magnetic resonance imaging (MRI) increases the sensitivity to molecular Brownian motion, providing insight in the micro-environment of the underlying tissue types and structures. At the same time, the diffusion weighting renders the scans sensitive to other motion, including bulk patient motion. Typically, several image volumes are needed to extract diffusion information, inducing also inter-volume motion susceptibility. Bulk motion is more likely during long acquisitions, as they appear in diffusion tensor, diffusion spectrum and q-ball imaging. Image registration methods are successfully used to correct for bulk motion in other MRI time series, but their performance in diffusion-weighted MRI is limited since diffusion weighting introduces strong signal and contrast changes between serial image volumes. In this work, we combine the capability of free induction decay (FID) navigators, providing information on object motion, with image registration methodology to prospectively--or optionally retrospectively--correct for motion in diffusion imaging of the human brain. Eight healthy subjects were instructed to perform small-scale voluntary head motion during clinical diffusion tensor imaging acquisitions. The implemented motion detection based on FID navigator signals is processed in real-time and provided an excellent detection performance of voluntary motion patterns even at a sub-millimetre scale (sensitivity≥92%, specificity>98%). Motion detection triggered an additional image volume acquisition with b=0 s/mm2 which was subsequently co-registered to a reference volume. In the prospective correction scenario, the calculated motion-parameters were applied to perform a real-time update of the gradient coordinate system to correct for the head movement. Quantitative analysis revealed that the motion correction implementation is capable to correct head motion in diffusion-weighted MRI to a level comparable to scans without voluntary head motion. The results indicate the potential of this method to improve image quality in diffusion-weighted MRI, a concept that can also be applied when highest diffusion weightings are performed.

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.

Neurobiology of pathological gambling. Brain imaging and epidemiological studies

Pathological gambling, a form of behavioral addiction, refers to maladaptive, compulsive gambling behavior severely interfering with an individual’s normal life. The prevalence of pathological gambling has been estimated to be 1–2% in western societies. The reward deficiency hypothesis of addiction assumes that individuals that have, or are prone, to addictions have blunted mesolimbic dopamine reward signaling, which leads to compulsive reward seeking in an attempt to compensate for the malfunctioning brain reward network. In this research project, the effects of gambling were measured using brain [11C] raclopride PET during slot machine gambling and possible brain structural changes associated with pathological gambling using MRI. The subjects included pathological gamblers and healthy volunteers. In addition, impulse control disorders associated with Parkinson’s disease were investigated by using brain [18F]fluorodopa PET and conducting an epidemiological survey. The results demonstrate mesolimbic dopamine release during gambling in both pathological gamblers and healthy volunteers. Striatal dopamine was released irrespective of the gambling outcome, whether the subjects won or not. There was no difference in gambling induced dopamine release between pathological gamblers and control subjects, although the magnitude of the dopamine release correlated with gambling related symptom severity in pathological gamblers. The results also show that pathological gambling is associated with extensive abnormality of brain white matter integrity, as measured with diffusion tensor imaging, similar to substance-addictions. In Parkinson’s disease patients with impulse control disorders, enhanced brain [18F] fluorodopa uptake in the medial orbitofrontal cortex was observed, indicating increased presynaptic monoamine function in this region, which is known to influence signaling in the mesolimbic system and reward processing. Finally, a large epidemiological survey in Finnish Parkinson’s disease patients showed that compulsive behaviors are very common in Parkinson disease and they are strongly associated with depression. These findings demonstrate the role of dopamine in pathological gambling, without support for the concept of reward deficiency syndrome.

Detection of Pathologic Changes Following Traumatic Brain Injury Using Magnetic Resonance Imaging

Background: Approximately two percent of Finns have sequels after traumatic brain injury (TBI), and many TBI patients are young or middle-aged. The high rate of unemployment after TBI has major economic consequences for society, and traumatic brain injury often has remarkable personal consequences, as well. Structural imaging is often needed to support the clinical TBI diagnosis. Accurate early diagnosis is essential for successful rehabilition and, thus, may also influence the patient’s outcome. Traumatic axonal injury and cortical contusions constitute the majority of traumatic brain lesions. Several studies have shown magnetic resonance imaging (MRI) to be superior to computed tomography (CT) in the detection of these lesions. However, traumatic brain injury often leads to persistent symptoms even in cases with few or no findings in conventional MRI. Aims and methods: The aim of this prospective study was to clarify the role of conventional MRI in the imaging of traumatic brain injury, and to investigate how to improve the radiologic diagnostics of TBI by using more modern diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) techniques. We estimated, in a longitudinal study, the visibility of the contusions and other intraparenchymal lesions in conventional MRI at one week and one year after TBI. We used DWI-based measurements to look for changes in the diffusivity of the normal-appearing brain in a case-control study. DTI-based tractography was used in a case-control study to evaluate changes in the volume, diffusivity, and anisotropy of the long association tracts in symptomatic TBI patients with no visible signs of intracranial or intraparenchymal abnormalities on routine MRI. We further studied the reproducibility of different tools to identify and measure white-matter tracts by using a DTI sequence suitable for clinical protocols. Results: Both the number and extent of visible traumatic lesions on conventional MRI diminished significantly with time. Slightly increased diffusion in the normal-appearing brain was a common finding at one week after TBI, but it was not significantly associated with the injury severity. Fractional anisotropy values, that represent the integrity of the white-matter tracts, were significantly diminished in several tracts in TBI patients compared to the control subjects. Compared to the cross-sectional ROI method, the tract-based analyses had better reproducibility to identify and measure white-matter tracts of interest by means of DTI tractography. Conclusions: As conventional MRI is still applied in clinical practice, it should be carried out soon after the injury, at least in symptomatic patients with negative CT scan. DWI-related brain diffusivity measurements may be used to improve the documenting of TBI. DTI tractography can be used to improve radiologic diagnostics in a symptomatic TBI sub-population with no findings on conventional MRI. Reproducibility of different tools to quantify fibre tracts vary considerably, which should be taken into consideration in the clinical DTI applications.

Magnetic Resocance Imaging Methods in the Follow-up of Multiple Sclerosis and in Farby Disease

Multiple sclerosis (MS) is a chronic immune-mediated inflammatory disorder of the central nervous system. MS is the most common disabling central nervous system (CNS) disease of young adults in the Western world. In Finland, the prevalence of MS ranges between 1/1000 and 2/1000 in different areas. Fabry disease (FD) is a rare hereditary metabolic disease due to mutation in a single gene coding α-galactosidase A (alpha-gal A) enzyme. It leads to multi-organ pathology, including cerebrovascular disease. Currently there are 44 patients with diagnosed FD in Finland. Magnetic resonance imaging (MRI) is commonly used in the diagnostics and follow-up of these diseases. The disease activity can be demonstrated by occurrence of new or Gadolinium (Gd)-enhancing lesions in routine studies. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced MR sequences which can reveal pathologies in brain regions which appear normal on conventional MR images in several CNS diseases. The main focus in this study was to reveal whether whole brain apparent diffusion coefficient (ADC) analysis can be used to demonstrate MS disease activity. MS patients were investigated before and after delivery and before and after initiation of diseasemodifying treatment (DMT). In FD, DTI was used to reveal possible microstructural alterations at early timepoints when excessive signs of cerebrovascular disease are not yet visible in conventional MR sequences. Our clinical and MRI findings at 1.5T indicated that post-partum activation of the disease is an early and common phenomenon amongst mothers with MS. MRI seems to be a more sensitive method for assessing MS disease activity than the recording of relapses. However, whole brain ADC histogram analysis is of limited value in the follow-up of inflammatory conditions in a pregnancy-related setting because the pregnancy-related physiological effects on ADC overwhelm the alterations in ADC associated with MS pathology in brain tissue areas which appear normal on conventional MRI sequences. DTI reveals signs of microstructural damage in brain white matter of FD patients before excessive white matter lesion load can be observed on conventional MR scans. DTI could offer a valuable tool for monitoring the possible effects of enzyme replacement therapy in FD.

Imaging Neuroinflammation in Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system CNS), where inflammation and neurodegeneration lead to irreversible neuronal damage. In MS, a dysfunctional immune system causes auto‐reactive lymphocytes to migrate into CNS where they initiate an inflammatory cascade leading to focal demyelination, axonal degeneration and neuronal loss. One of the hallmarks of neuronal injury and neuroinflammation is the activation of microglia. Activated microglia are found not only in the focal inflammatory lesions, but also diffusely in the normal‐appearing white matter (NAWM), especially in progressive MS. The purine base, adenosine is a ubiquitous neuromodulator in the CNS and also participates in the regulation of inflammation. The effect of adenosine mediated via adenosine A2A receptors has been linked to microglial activation, whereas modulating A2A receptors may exert neuroprotective effects. In the majority of patients, MS presents with a relapsing disease course, later advancing to a progressive phase characterised by a worsening, irreversible disability. Disease modifying treatments can reduce the severity and progression in relapsing MS, but no efficient treatment exists for progressive MS. The aim of this research was to investigate the prevalence of adenosine A2A receptors and activated microglia in progressive MS by using in vivo positron emission tomography (PET) imaging and [11C]TMSX and [11C](R)‐PK11195 radioligands. Magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) was performed to evaluate structural brain damage. Non‐invasive input function methods were also developed for the analyses of [11C]TMSX PET data. Finally, histopathological correlates of [11C](R)‐PK11195 radioligand binding related to chronic MS lesions were investigated in post‐mortem samples of progressive MS brain using autoradiography and immunohistochemistry. [11C]TMSX binding to A2A receptors was increased in NAWM of secondary progressive MS (SPMS) patients when compared to healthy controls, and this correlated to more severe atrophy in MRI and white matter disintegration (reduced fractional anisotropy, FA) in DTI. The non‐invasive input function methods appeared as feasible options for brain [11C]TMSX images obviating arterial blood sampling. [11C](R)‐PK11195 uptake was increased in the NAWM of SPMS patients when compared to patients with relapsing MS and healthy controls. Higher [11C](R)‐PK11195 binding in NAWM and total perilesional area of T1 hypointense lesions was associated with more severe clinical disability, increased brain atrophy, higher lesion load and reduced FA in NAWM in the MS patients. In autoradiography, increased perilesional [11C](R)‐PK11195 uptake was associated with increased microglial activation identified using immunohistochemistry. In conclusion, brain [11C]TMSX PET imaging holds promise in the evaluation of diffuse neuroinflammation in progressive MS. Being a marker of microglial activation, [11C](R)‐ PK11195 PET imaging could possibly be used as a surrogate biomarker in the evaluation of the neuroinflammatory burden and clinical disease severity in progressive MS.