Thalamic connectivity in patients with essential tremor treated with MR imaging-guided focused ultrasound: in vivo fiber tracking by using diffusion-tensor MR imaging.

PURPOSE: To use diffusion-tensor (DT) magnetic resonance (MR) imaging in patients with essential tremor who were treated with transcranial MR imaging-guided focused ultrasound lesion inducement to identify the structural connectivity of the ventralis intermedius nucleus of the thalamus and determine how DT imaging changes correlated with tremor changes after lesion inducement. MATERIALS AND METHODS: With institutional review board approval, and with prospective informed consent, 15 patients with medication-refractory essential tremor were enrolled in a HIPAA-compliant pilot study and were treated with transcranial MR imaging-guided focused ultrasound surgery targeting the ventralis intermedius nucleus of the thalamus contralateral to their dominant hand. Fourteen patients were ultimately included. DT MR imaging studies at 3.0 T were performed preoperatively and 24 hours, 1 week, 1 month, and 3 months after the procedure. Fractional anisotropy (FA) maps were calculated from the DT imaging data sets for all time points in all patients. Voxels where FA consistently decreased over time were identified, and FA change in these voxels was correlated with clinical changes in tremor over the same period by using Pearson correlation. RESULTS: Ipsilateral brain structures that showed prespecified negative correlation values of FA over time of -0.5 or less included the pre- and postcentral subcortical white matter in the hand knob area; the region of the corticospinal tract in the centrum semiovale, in the posterior limb of the internal capsule, and in the cerebral peduncle; the thalamus; the region of the red nucleus; the location of the central tegmental tract; and the region of the inferior olive. The contralateral middle cerebellar peduncle and bilateral portions of the superior vermis also showed persistent decrease in FA over time. There was strong correlation between decrease in FA and clinical improvement in hand tremor 3 months after lesion inducement (P < .001). CONCLUSION: DT MR imaging after MR imaging-guided focused ultrasound thalamotomy depicts changes in specific brain structures. The magnitude of the DT imaging changes after thalamic lesion inducement correlates with the degree of clinical improvement in essential tremor.

Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

Forensic application of postmortem diffusion-weighted and diffusion tensor MR imaging of the human brain in situ

DWI and DTI of the brain have proved to be useful in many neurologic disorders and in traumatic brain injury. This prospective study aimed at the evaluation of the influence of the PMI and the cause of death on the ADC and FA for the application of DWI and DTI in forensic radiology.

An evaluation of the time dependence of the anisotropy of the water diffusion tensor in acute human ischemia

We have performed MRI examinations to determine the water diffusion tensor in the brain of six patients who were admitted to the hospital within 12 h after the onset of cerebral ischemic symptoms. The examinations have been carried out immediately after admission, and thereafter at varying intervals up to 90 days post admission. Maps of the trace of the diffusion tensor, the fractional anisotropy and the lattice index, as well as maps of cerebral blood perfusion parameters, were generated to quantitatively assess the character of the water diffusion tensor in the infarcted area. In patients with significant perfusion deficits and substantial lesion volume changes, four of six cases, our measurements show a monotonic and significant decrease in the diffusion anisotropy within the ischemic lesion as a function of time. We propose that retrospective analysis of this quantity, in combination with brain tissue segmentation and cerebral perfusion maps, may be used in future studies to assess the severity of the ischemic event. (C) 1999 Elsevier Science Inc.

MR Spectroscopy Detects Lipid Peaks in Cerebrotendinous Xanthomatosis

CTX is a rare lipid-storage disease. Novel MRS findings from 3 patients, using a short TE, were the presence of lipid peaks at 0.9 and 1.3 ppm in the depth of the cerebellar hemisphere; this might represent an additional marker of disease that is CNS-specific and noninvasive. A decrease in NAA concentration was also detected and attributed to neuroaxonal damage. One patient presented an increase in mlns concentration, pointing to gliosis and astrocytic proliferation.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Direct three-dimensional myocardial strain tensor quantification and tracking using zHARP.

Images of myocardial strain can be used to diagnose heart disease, plan and monitor treatment, and to learn about cardiac structure and function. Three-dimensional (3D) strain is typically quantified using many magnetic resonance (MR) images obtained in two or three orthogonal planes. Problems with this approach include long scan times, image misregistration, and through-plane motion. This article presents a novel method for calculating cardiac 3D strain using a stack of two or more images acquired in only one orientation. The zHARP pulse sequence encodes in-plane motion using MR tagging and out-of-plane motion using phase encoding, and has been previously shown to be capable of computing 3D displacement within a single image plane. Here, data from two adjacent image planes are combined to yield a 3D strain tensor at each pixel; stacks of zHARP images can be used to derive stacked arrays of 3D strain tensors without imaging multiple orientations and without numerical interpolation. The performance and accuracy of the method is demonstrated in vitro on a phantom and in vivo in four healthy adult human subjects.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Multi-slice three-dimensional myocardial strain tensor quantification using zHARP.

In this article we propose a novel method for calculating cardiac 3-D strain. The method requires the acquisition of myocardial short-axis (SA) slices only and produces the 3-D strain tensor at every point within every pair of slices. Three-dimensional displacement is calculated from SA slices using zHARP which is then used for calculating the local displacement gradient and thus the local strain tensor. There are three main advantages of this method. First, the 3-D strain tensor is calculated for every pixel without interpolation; this is unprecedented in cardiac MR imaging. Second, this method is fast, in part because there is no need to acquire long-axis (LA) slices. Third, the method is accurate because the 3-D displacement components are acquired simultaneously and therefore reduces motion artifacts without the need for registration. This article presents the theory of computing 3-D strain from two slices using zHARP, the imaging protocol, and both phantom and in-vivo validation.

Development of cardiovascular magnetic resonance imaging techniques for improved characterization of atherosclerotic disease

Atherosclerosis is a chronic cardiovascular disease that involves the thicken¬ing of the artery walls as well as the formation of plaques (lesions) causing the narrowing of the lumens, in vessels such as the aorta, the coronary and the carotid arteries. Magnetic resonance imaging (MRI) is a promising modality for the assessment of atherosclerosis, as it is a non-invasive and patient-friendly procedure that does not use ionizing radiation. MRI offers high soft tissue con¬trast already without the need of intravenous contrast media; while modifica¬tion of the MR pulse sequences allows for further adjustment of the contrast for specific diagnostic needs. As such, MRI can create angiographic images of the vessel lumens to assess stenoses at the late stage of the disease, as well as blood flow-suppressed images for the early investigation of the vessel wall and the characterization of the atherosclerotic plaques. However, despite the great technical progress that occurred over the past two decades, MRI is intrinsically a low sensitive technique and some limitations still exist in terms of accuracy and performance. A major challenge for coronary artery imaging is respiratory motion. State- of-the-art diaphragmatic navigators rely on an indirect measure of motion, per¬form a ID correction, and have long and unpredictable scan time. In response, self-navigation (SM) strategies have recently been introduced that offer 100% scan efficiency and increased ease of use. SN detects respiratory motion di¬rectly from the image data obtained at the level of the heart, and retrospectively corrects the same data before final image reconstruction. Thus, SN holds po-tential for multi-dimensional motion compensation. To this regard, this thesis presents novel SN methods that estimate 2D and 3D motion parameters from aliased sub-images that are obtained from the same raw data composing the final image. Combination of all corrected sub-images produces a final image with reduced motion artifacts for the visualization of the coronaries. The first study (section 2.2, 2D Self-Navigation with Compressed Sensing) consists of a method for 2D translational motion compensation. Here, the use of com- pressed sensing (CS) reconstruction is proposed and investigated to support motion detection by reducing aliasing artifacts. In healthy human subjects, CS demonstrated an improvement in motion detection accuracy with simula¬tions on in vivo data, while improved coronary artery visualization was demon¬strated on in vivo free-breathing acquisitions. However, the motion of the heart induced by respiration has been shown to occur in three dimensions and to be more complex than a simple translation. Therefore, the second study (section 2.3,3D Self-Navigation) consists of a method for 3D affine motion correction rather than 2D only. Here, different techniques were adopted to reduce background signal contribution in respiratory motion tracking, as this can be adversely affected by the static tissue that surrounds the heart. The proposed method demonstrated to improve conspicuity and vi¬sualization of coronary arteries in healthy and cardiovascular disease patient cohorts in comparison to a conventional ID SN method. In the third study (section 2.4, 3D Self-Navigation with Compressed Sensing), the same tracking methods were used to obtain sub-images sorted according to the respiratory position. Then, instead of motion correction, a compressed sensing reconstruction was performed on all sorted sub-image data. This process ex¬ploits the consistency of the sorted data to reduce aliasing artifacts such that the sub-image corresponding to the end-expiratory phase can directly be used to visualize the coronaries. In a healthy volunteer cohort, this strategy improved conspicuity and visualization of the coronary arteries when compared to a con¬ventional ID SN method. For the visualization of the vessel wall and atherosclerotic plaques, the state- of-the-art dual inversion recovery (DIR) technique is able to suppress the signal coming from flowing blood and provide positive wall-lumen contrast. How¬ever, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. In response and as a fourth study of this thesis (chapter 3, Vessel Wall MRI of the Carotid Arteries), a phase-sensitive DIR method has been implemented and tested in the carotid arteries of a healthy volunteer cohort. By exploiting the phase information of images acquired after DIR, the proposed phase-sensitive method enhances wall-lumen contrast while widens the window of opportunity for image acquisition. As a result, a 3-fold increase in volumetric coverage is obtained at no extra cost in scanning time, while image quality is improved. In conclusion, this thesis presented novel methods to address some of the main challenges for MRI of atherosclerosis: the suppression of motion and flow artifacts for improved visualization of vessel lumens, walls and plaques. Such methods showed to significantly improve image quality in human healthy sub¬jects, as well as scan efficiency and ease-of-use of MRI. Extensive validation is now warranted in patient populations to ascertain their diagnostic perfor¬mance. Eventually, these methods may bring the use of atherosclerosis MRI closer to the clinical practice. Résumé L'athérosclérose est une maladie cardiovasculaire chronique qui implique le épaississement de la paroi des artères, ainsi que la formation de plaques (lé¬sions) provoquant le rétrécissement des lumières, dans des vaisseaux tels que l'aorte, les coronaires et les artères carotides. L'imagerie par résonance magné¬tique (IRM) est une modalité prometteuse pour l'évaluation de l'athérosclérose, car il s'agit d'une procédure non-invasive et conviviale pour les patients, qui n'utilise pas des rayonnements ionisants. L'IRM offre un contraste des tissus mous très élevé sans avoir besoin de médias de contraste intraveineux, tan¬dis que la modification des séquences d'impulsions de RM permet en outre le réglage du contraste pour des besoins diagnostiques spécifiques. À ce titre, l'IRM peut créer des images angiographiques des lumières des vaisseaux pour évaluer les sténoses à la fin du stade de la maladie, ainsi que des images avec suppression du flux sanguin pour une première enquête des parois des vais¬seaux et une caractérisation des plaques d'athérosclérose. Cependant, malgré les grands progrès techniques qui ont eu lieu au cours des deux dernières dé¬cennies, l'IRM est une technique peu sensible et certaines limitations existent encore en termes de précision et de performance. Un des principaux défis pour l'imagerie de l'artère coronaire est le mou¬vement respiratoire. Les navigateurs diaphragmatiques de pointe comptent sur une mesure indirecte de mouvement, effectuent une correction 1D, et ont un temps d'acquisition long et imprévisible. En réponse, les stratégies d'auto- navigation (self-navigation: SN) ont été introduites récemment et offrent 100% d'efficacité d'acquisition et une meilleure facilité d'utilisation. Les SN détectent le mouvement respiratoire directement à partir des données brutes de l'image obtenue au niveau du coeur, et rétrospectivement corrigent ces mêmes données avant la reconstruction finale de l'image. Ainsi, les SN détiennent un poten¬tiel pour une compensation multidimensionnelle du mouvement. A cet égard, cette thèse présente de nouvelles méthodes SN qui estiment les paramètres de mouvement 2D et 3D à partir de sous-images qui sont obtenues à partir des mêmes données brutes qui composent l'image finale. La combinaison de toutes les sous-images corrigées produit une image finale pour la visualisation des coronaires ou les artefacts du mouvement sont réduits. La première étude (section 2.2,2D Self-Navigation with Compressed Sensing) traite d'une méthode pour une compensation 2D de mouvement de translation. Ici, on étudie l'utilisation de la reconstruction d'acquisition comprimée (compressed sensing: CS) pour soutenir la détection de mouvement en réduisant les artefacts de sous-échantillonnage. Chez des sujets humains sains, CS a démontré une amélioration de la précision de la détection de mouvement avec des simula¬tions sur des données in vivo, tandis que la visualisation de l'artère coronaire sur des acquisitions de respiration libre in vivo a aussi été améliorée. Pourtant, le mouvement du coeur induite par la respiration se produit en trois dimensions et il est plus complexe qu'un simple déplacement. Par conséquent, la deuxième étude (section 2.3, 3D Self-Navigation) traite d'une méthode de cor¬rection du mouvement 3D plutôt que 2D uniquement. Ici, différentes tech¬niques ont été adoptées pour réduire la contribution du signal du fond dans le suivi de mouvement respiratoire, qui peut être influencé négativement par le tissu statique qui entoure le coeur. La méthode proposée a démontré une amélioration, par rapport à la procédure classique SN de correction 1D, de la visualisation des artères coronaires dans le groupe de sujets sains et des pa¬tients avec maladies cardio-vasculaires. Dans la troisième étude (section 2.4,3D Self-Navigation with Compressed Sensing), les mêmes méthodes de suivi ont été utilisées pour obtenir des sous-images triées selon la position respiratoire. Au lieu de la correction du mouvement, une reconstruction de CS a été réalisée sur toutes les sous-images triées. Cette procédure exploite la cohérence des données pour réduire les artefacts de sous- échantillonnage de telle sorte que la sous-image correspondant à la phase de fin d'expiration peut directement être utilisée pour visualiser les coronaires. Dans un échantillon de volontaires en bonne santé, cette stratégie a amélioré la netteté et la visualisation des artères coronaires par rapport à une méthode classique SN ID. Pour la visualisation des parois des vaisseaux et de plaques d'athérosclérose, la technique de pointe avec double récupération d'inversion (DIR) est capa¬ble de supprimer le signal provenant du sang et de fournir un contraste posi¬tif entre la paroi et la lumière. Pourtant, il est difficile d'obtenir un contraste optimal car cela est soumis à la variabilité du rythme cardiaque. Par ailleurs, l'imagerie DIR est inefficace du point de vue du temps et les acquisitions "mul- tislice" peuvent conduire à des temps de scan prolongés. En réponse à ce prob¬lème et comme quatrième étude de cette thèse (chapitre 3, Vessel Wall MRI of the Carotid Arteries), une méthode de DIR phase-sensitive a été implémenté et testé

Autocrine loop in the purinergic control of airway surface liquid volume : monitoring with a novel side-view imaging technique

La Fibrose Kystique (FK) est une maladie dégénérative qui entraine une dégénération des poumons dû au problème de clairance mucociliaire (CMC). Le volume de surface liquide (SL) couvrant les cellules pulmonaires est essentiel à la clairance de mucus et au combat contre les infections. Les nucléotides extracellulaires jouent un rôle important dans la CMC des voies aériennes, en modifiant le volume de la SL pulmonaire. Cependant, les mécanismes du relâchement de l’ATP et de leurs déplacements à travers la SL, restent inconnus. Des études ultérieures démontrent que l’exocytose d’ATP mécano-sensible et Ca2+-dépendant, dans les cellules A549, est amplifié par les actions synergétiques autocrine/paracrine des cellules avoisinantes. Nous avions comme but de confirmer la présence de la boucle purinergique dans plusieurs modèles de cellules épithéliales et de développer un système nous permettant d’observer directement la SL. Nous avons démontrés que la boucle purinergique est fonctionnelle dans les modèles de cellules épithéliales examinés, mis appart les cellules Calu-3. L’utilisation de modulateur de la signalisation purinergique nous a permis d’observer que le relâchement d’ATP ainsi que l’augmentation du [Ca2+]i suivant un stress hypotonique, sont modulés par le biais de cette boucle purinergique et des récepteurs P2Y. De plus, nous avons développé un système de microscopie qui permet d’observer les changements de volume de SL en temps réel. Notre système permet de contrôler la température et l’humidité de l’environnement où se trouvent les cellules, reproduisant l’environnement pulmonaire humain. Nous avons démontré que notre système peut identifier même les petits changements de volume de SL.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Analyzing diffusion tensor images with ghosting artifacts: the effects of direct and indirect normalization

The current study aims to assess the applicability of direct or indirect normalization for the analysis of fractional anisotropy (FA) maps in the context of diffusion-weighted images (DWIs) contaminated by ghosting artifacts. We found that FA maps acquired by direct normalization showed generally higher anisotropy than indirect normalization, and the disparities were aggravated by the presence of ghosting artifacts in DWIs. The voxel-wise statistical comparisons demonstrated that indirect normalization reduced the influence of artifacts and enhanced the sensitivity of detecting anisotropy differences between groups. This suggested that images contaminated with ghosting artifacts can be sensibly analyzed using indirect normalization.

CHANDRA AND SPITZER IMAGING OF THE INFRARED CLUSTER IN NGC 2071

We present results of a sensitive Chandra X-ray observation and Spitzer mid-infrared (mid-IR) observations of the IR cluster lying north of the NGC 2071 reflection nebula in the Orion B molecular cloud. We focus on the dense cluster core known as NGC 2071-IR, which contains at least nine IR sources within a 40 `` x 40 `` region. This region shows clear signs of active star formation including powerful molecular outflows, Herbig-Haro objects, and both OH and H(2)O masers. We use Spitzer Infrared Array Camera (IRAC) images to aid in X-ray source identification and to determine young stellar object (YSO) classes using mid-IR colors. Spitzer IRAC colors show that the luminous source IRS 1 is a class I protostar. IRS 1 is believed to be driving a powerful bipolar molecular outflow and may be an embedded B-type star or its progenitor. Its X-ray spectrum reveals a fluorescent Fe emission line at 6.4 keV, arising in cold material near the protostar. The line is present even in the absence of large flares, raising questions about the nature of the ionizing mechanism responsible for producing the 6.4 keV fluorescent line. Chandra also detects X-ray sources at or near the positions of IRS 2, IRS 3, IRS 4, and IRS 6 and a variable X-ray source coincident with the radio source VLA 1, located just 2 `` north of IRS 1. No IR data are yet available to determine a YSO classification for VLA 1, but its high X-ray absorption shows that it is even more deeply embedded than IRS 1, suggesting that it could be an even younger, less-evolved protostar.