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Basic concepts in the physiopathology of edema are reviewed. The mechanisms of fluid exchange across the capillary endothelium are explained. Interstitial flow and lymph formation are examined. Clinical disorders of tissue and lymphatic transport, microcirculatory derangements in venous disorders, protein disorders, and lymphatic system disorders are explored. Techniques for investigational imaging of the lymphatic system are explained.
We have analyzed the geometry, geography, and functional organization of human cerebral cortex using surface reconstructions and cortical flat maps of the left and right hemispheres generated from a digital atlas (the Visible Man). The total surface area of the reconstructed Visible Man neocortex is 1570 cm2 (both hemispheres), approximately 70% of which is buried in sulci. By linking the Visible Man cerebrum to the Talairach stereotaxic coordinate space, the locations of activation foci reported in neuroimaging studies can be readily visualized in relation to the cortical surface. The associated spatial uncertainty was empirically shown to have a radius in three dimensions of approximately 10 mm. Application of this approach to studies of visual cortex reveals the overall patterns of activation associated with different aspects of visual function and the relationship of these patterns to topographically organized visual areas. Our analysis supports a distinction between an anterior region in ventral occipito-temporal cortex that is selectively involved in form processing and a more posterior region (in or near areas VP and V4v) involved in both form and color processing. Foci associated with motion processing are mainly concentrated in a region along the occipito-temporal junction, the ventral portion of which overlaps with foci also implicated in form processing. Comparisons between flat maps of human and macaque monkey cerebral cortex indicate significant differences as well as many similarities in the relative sizes and positions of cortical regions known or suspected to be homologous in the two species.
The task of evaluating and designing space gloves requires accurate biomechanical characterization of the hand. The availability of magnetic resonance (MR) imaging has created new opportunities for in vivo analysis of physiological phenomena such as the relationship between circulation and fatigue. An MR imaging technique originally proposed to quantitatively evaluate cerebral perfusion has been modified to evaluate the capillary microcirculation in hand muscles. An experimental protocol was developed to acquire perfusion-weighted images in the hand before and after various levels of exercise. Preliminary results on the feasibility of applying the MR imaging technique to the study of microcirculation and fatigue in the hand are presented. The potential of this method for space glove testing and design is also discussed.
The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.
Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.
Using a novel NMR scheme we observed persistence in 1D gas diffusion. Analytical approximations and numerical simulations have indicated that for an initially random array of spins undergoing diffusion, the probability p(t) that the average spin magnetization in a given region has not changed sign (i.e., "persists") up to time t follows a power law t(-straight theta), where straight theta depends on the dimensionality of the system. Using laser-polarized 129Xe gas, we prepared an initial "quasirandom" 1D array of spin magnetization and then monitored the ensemble's evolution due to diffusion using real-time NMR imaging. Our measurements are consistent with analytical and numerical predictions of straight theta approximately 0.12.
A simple spatial filter for 2D projection MR imaging is introduced. It works in the third (unresolved) direction to eliminate uniform or slowly varying interfering background signals. A constant amplitude gradient pulse in the unresolved direction is applied at the same time as the usual phase encode gradient during 2D acquisition. The filter is demonstrated for root imaging in soil, where background soil water signals can be troublesome. The filter suppresses the soil water signal while preserving the desired signal of plant roots. Fundamental to the operation of the filter is that the roots are sparse in the image domain, meaning there are relatively few pixels with multiple roots present. Here, the performance of the through-plane filter is demonstrated and compares favorably to more conventional in-plane spatial filtering.
Some non-Fourier encoding methods such as wavelet and direct encoding use spatially localized bases. The spatial localization feature of these methods enables optimized encoding for improved spatial and temporal resolution during dynamically adaptive MR imaging. These spatially localized bases, however, have inherently reduced image signal-to-noise ratio compared with Fourier or Hadamad encoding for proton imaging. Hyperpolarized noble gases, on the other hand, have quite different MR properties compared to proton, primarily the nonrenewability of the signal. It could be expected, therefore, that the characteristics of image SNR with respect to encoding method will also be very different from hyperpolarized noble gas MRI compared to proton MRI. In this article, hyperpolarized noble gas image SNRs of different encoding methods are compared theoretically using a matrix description of the encoding process. It is shown that image SNR for hyperpolarized noble gas imaging is maximized for any orthonormal encoding method. Methods are then proposed for designing RF pulses to achieve normalized encoding profiles using Fourier, Hadamard, wavelet, and direct encoding methods for hyperpolarized noble gases. Theoretical results are confirmed with hyperpolarized noble gas MRI experiments. Copyright 2001 Academic Press.
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This paper describes methods for white matter segmentation in brain images and the generation of cortical surfaces from the segmentations. We have developed a system that allows a user to start with a brain volume, obtained by modalities such as MRI or cryosection, and constructs a complete digital representation of the cortical surface. The methodology consists of three basic components: local parametric modeling and Bayesian segmentation; surface generation and local quadratic coordinate fitting; and surface editing. Segmentations are computed by parametrically fitting known density functions to the histogram of the image using the expectation maximization algorithm [DLR77]. The parametric fits are obtained locally rather than globally over the whole volume to overcome local variations in gray levels. To represent the boundary of the gray and white matter we use triangulated meshes generated using isosurface generation algorithms [GH95]. A complete system of local parametric quadratic charts [JWM+95] is superimposed on the triangulated graph to facilitate smoothing and geodesic curve tracking. Algorithms for surface editing include extraction of the largest closed surface. Results for several macaque brains are presented comparing automated and hand surface generation. Copyright 1999 Academic Press.
We pursued advanced technology development of laser-polarized noble gas nuclear magnetic resonance (NMR) as a novel biomedical imaging tool for ground-based and eventually space-based application. This new multidisciplinary technology enables high-resolution gas-space magnetic resonance imaging (MRI)-e.g., of lung ventilation-as well as studies of tissue perfusion. In addition, laser-polarized noble gases (3He and 129Xe) do not require a large magnetic field for sensitive detection, opening the door to practical MRI at very low magnetic fields with an open, lightweight, and low-power device. We pursued two technology development specific aims: (1) development of low-field (less than 0.01 T) noble gas MRI of humans; and (2) development of functional MRI of the lung using laser-polarized noble gas and related techniques.
We are developing laser-polarized noble gas nuclear magnetic resonance (NMR) as a novel biomedical imaging tool for ground-based and eventually space-based application. This emerging multidisciplinary technology enables high-resolution gas-space magnetic resonance imaging (MRI) (e.g., of lung ventilation) as well as studies of tissue perfusion. In addition, laser-polarized noble gases (He-3 and Xe-129) do not require a large magnetic field for sensitive detection, opening the door to practical MRI at very low magnetic fields with an open, lightweight, and low-power device. We are pursuing two specific aims in this research. The first aim is to develop a low-field (< 0.01 T) instrument for noble gas MRI of humans, and the second aim is to develop functional MRI of the lung using laser-polarized Xe-129 and related techniques.
OBJECTIVE: Many exercise protocols used in physiological studies assume homogeneous and diffuse muscle recruitment. To test this assumption during a "standard" wrist flexion protocol, variations in muscle recruitment were assessed using MRI in eight healthy subjects. MATERIALS AND METHODS: Variations were assessed by comparing the right to the left forearms and the effect of slight (15 degrees) pronation or supination at the wrist. RESULTS: Postexercise imaging showed focal regions of increased signal intensity (SI), indicating relatively strong recruitment, most often in entire muscles, although occasionally only in subvolumes of muscles. In 15 of 26 studies, flexor carpi radialis (FCR) showed more SI than flexor carpi ulnaris, while in 11 studies SI in these muscles increased equivalently. Relatively greater FCR recruitment was seen during pronation and/or use of the nondominant side. Palmaris longus, a wrist flexor, did not appear recruited in 4 of 11 forearms in which it was present. A portion of the superficial finger flexor became hyperintense in 89% of studies, while recruitment of the deep finger flexor was seen only in 43%. CONCLUSION: Inter- and intraindividual variations in forearm muscle recruitment should be anticipated in physiological studies of standard wrist flexion exercise protocols.
The panel of fluid- and imaging-based biomarkers available for neurodegenerative disease research is growing and has the potential to close important gaps in research and the clinic. With this growth and increasing use, appropriate implementation and interpretation are paramount. Various biomarkers feature nuanced differences in strengths, limitations, and biases that must be considered when investigating disease etiology and clinical utility. For example, neuropathological investigations of Alzheimer’s disease pathogenesis can fall in disagreement with conclusions reached by biomarker-based investigations. Considering the varied strengths, limitations, and biases of different research methodologies and approaches may help harmonize disciplines within the neurodegenerative disease field.
Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.
This prospective study is, to our knowledge, the first report of daily adaptive radiation therapy (ART) for head and neck cancer (HNC) using a 1.5T magnetic resonance imaging-linear accelerator (MR-linac) with particular focus on safety and feasibility and dosimetric results of an online rigid registration-based adapt to position (ATP) workflow.
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