Biomedical subjects

Hatsuho Mamata

Publications and source records attributed to Hatsuho Mamata.

8 recordsLinked to original sources

PubMed2005

In vivo visualization of white matter fiber tracts of preterm- and term-infant brains with diffusion tensor magnetic resonance imaging.

OBJECTIVE: The goal of this study was to test the feasibility of visualizing a 3-dimensional structure of cerebral white matter fiber tracts in preterm infants, postconceptional age (PCA) 28 weeks to term, by using volumetric diffusion tensor magnetic resonance imaging (DTI) data. MATERIALS AND METHOD: We combined tractography algorithms and visualization methods, currently available for adult DTI data, to trace the pixelated principal direction of a diffusion tensor originating from regions-of-interest with high fractional anisotropy. Consequently, white matter fiber bundles from the genu and the splenium of corpus callosum, the corticospinal tracts, the inferior fronto-occipital fasciculi, and optic radiations were visualized. RESULTS: Our results suggest that major white matter tracts of preterm infant brains, with PCAs ranging from 28 weeks to term (40 weeks old), can be successfully visualized despite the small brain volume and low anisotropy. CONCLUSION: The feasibility of fiber tractography in preterm neonates with DTI may add a new dimension in detection and characterization of white matter injuries of preterm infants.

Algorithms↗

PubMed2004

Biexponential diffusion tensor analysis of human brain diffusion data.

Several studies have shown that in tissues over an extended range of b-factors, the signal decay deviates significantly from the basic monoexponential model. The true nature of this departure has to date not been identified. For the current study, line scan diffusion images of brain suitable for biexponential diffusion tensor analysis were acquired in normal subjects on a clinical MR system. For each of six noncollinear directions, 32 images with b-factors ranging from 5 to 5000 s/mm2 were collected. Biexponential fits yielded parameter maps for a fast and a slow diffusion component. A subset of the diffusion data, consisting of the images obtained at the conventional range of b-factors between 5 and 972 s/mm2, was used for monoexponential diffusion tensor analysis. Fractional anisotropy (FA) of the fast-diffusion component and the monoexponential fit exhibited no significant difference. FA of the slow-diffusion biexponential component was significantly higher, particularly in areas of lower fiber density. The principal diffusion directions for the two biexponential components and the monoexponential solution were largely the same and in agreement with known fiber tracts. The second and third diffusion eigenvector directions also appeared to be aligned, but they exhibited significant deviations in localized areas.

Adult↗

PubMed2004

Characterization of central nervous system structures by magnetic resonance diffusion anisotropy.

Diffusion-weighted magnetic resonance imaging (MRI) provides information about tissue water diffusion. Diffusion anisotropy, which can be measured with diffusion tensor MRI, is a quantitative measure of the directional dependence of the diffusion restriction that is introduced by biological structures such as nerve fibers. Diffusion tensor MRI data was obtained in the brain, brain stem, and cervical spinal cord. For each region, scans were performed in four normal volunteers. Fractional anisotropy (FA), an index of diffusion anisotropy, was measured within regions of interest located in the corpus callosum, capsula interna, thalamus, caudate nucleus, putamen, brain cortex, pyramidal tract of the medulla, accessory olivary nucleus, dorsal olivary nucleus, inferior olivary nucleus, spinal white and gray matter. The highest FA value was measured in the corpus callosum (81 +/- 3%). The values of the other areas decreased in the following order: pyramidal tract in the medulla (72 +/- 1%), spinal white matter (65 +/- 4%), capsula interna (62 +/- 3%), accessory olivary nucleus (36 +/- 2%), spinal gray matter (35 +/- 5%), dorsal olivary nucleus in the medulla (29 +/- 2%), thalamus (28 +/- 2%), inferior olivary nucleus (15 +/- 2%), putamen (13 +/- 2%), caudate nucleus (13 +/- 2%), and brain cortex (9 +/- 1%). Our results indicate that the underlying fiber architecture, fiber density, and uniformity of nerve fiber direction affect anisotropy values of the various structures. Characterization of various central nervous system structures with diffusion anisotropy is possible and may be useful to monitor degenerative diseases in the central nervous system.

Anisotropy↗

PubMed2004

Comparison of single-shot echo-planar and line scan protocols for diffusion tensor imaging.

RATIONALE AND OBJECTIVES: Both single-shot diffusion-weighted echo-planar imaging (EPI) and line scan diffusion imaging (LSDI) can be used to obtain magnetic resonance diffusion tensor data and to calculate directionally invariant diffusion anisotropy indices, ie, indirect measures of the organization and coherence of white matter fibers in the brain. To date, there has been no comparison of EPI and LSDI. Because EPI is the most commonly used technique for acquiring diffusion tensor data, it is important to understand the limitations and advantages of LSDI relative to EPI. MATERIALS AND METHODS: Five healthy volunteers underwent EPI and LSDI diffusion on a 1.5 Tesla magnet (General Electric Medical Systems, Milwaukee, WI). Four-mm thick coronal sections, covering the entire brain, were obtained. In addition, one subject was tested with both sequences over four sessions. For each image voxel, eigenvectors and eigenvalues of the diffusion tensor were calculated, and fractional anisotropy (FA) was derived. Several regions of interest were delineated, and for each, mean FA and estimated mean standard deviation were calculated and compared. RESULTS: Results showed no significant differences between EPI and LSDI for mean FA for the five subjects. When intersession reproducibility for one subject was evaluated, there was a significant difference between EPI and LSDI in FA for the corpus callosum and the right uncinate fasciculus. Moreover, errors associated with each FA measure were larger for EPI than for LSDI. CONCLUSION: Results indicate that both EPI- and LSDI-derived FA measures are sufficiently robust. However, when higher accuracy is needed, LSDI provides smaller error and smaller inter-subject and inter-session variability than EPI.

Adult↗

PubMed2003

Characterization of normal brain and brain tumor pathology by chisquares parameter maps of diffusion-weighted image data.

OBJECTIVE: To characterize normal and pathologic brain tissue by quantifying the deviation of diffusion-related signal from a simple monoexponential decay, when measured over a wider than usual range of b-factors. METHODS AND MATERIALS: Line scan diffusion imaging (LSDI), with diffusion weighting at multiple b-factors between 100 and 5000 s/mm(2), was performed on 1.5 T clinical scanners. Diffusion data of single slice sections were acquired in five healthy subjects and 19 brain tumor patients. In-patients, conventional T2-weighted and contrast-enhanced T1-weighted images were obtained for reference purposes. The chisquare (chi(2)) error parameter associated with the monoexponential fits of the measured tissue water signals was then used to quantify the departure from a simple monoexponential signal decay on a pixel-by-pixel basis. RESULTS: Diffusion-weighted images over a wider b-factor range than typically used were successfully obtained in all healthy subjects and patients. Normal and pathologic tissues demonstrated signal decays, which clearly deviate from a simple monoexponential behavior. The chi(2) of cortical and deep grey matter was considerably lower than in white matter. In peritumoral edema, however, chi(2) was 68% higher than in normal white matter. In highly malignant brain tumors, such as glioblastoma multiforme (GBM) or anaplastic astrocytoma, chi(2) values were on average almost 400% higher than in normal white matter, while for one low grade astrocytoma and two cases of metastasis, chi(2) was not profoundly different from the chi(2) value of white matter. Maps of the chi(2) values provide good visualization of spatial details. However, the tumor tissue contrast generated appeared in many cases to be different from the enhancement produced by paramagnetic contrast agents. For example, in cases where the contrast agent only highlighted the rim of the tumor, chi(2) enhancement was present within the solid part of the tumor. CONCLUSION: The deviation from a purely monoexponential diffusion signal decay becomes evident as diffusion encoding is extended well beyond the normal range. The chi(2) error parameter as a measure of this deviation seems to provide sufficient lesion contrast to permit differentiation of malignant brain tumors from normal brain tissue.

Adult↗

PubMed2002

Intraoperative magnetic resonance imaging and magnetic resonance imaging-guided therapy for brain tumors.

Since their introduction into surgical practice in the mid 1990s, intraoperative MRI systems have evolved into essential, routinely used tools for the surgical treatment of brain tumors in many centers. Clear delineation of the lesion, "under-the-surface" vision, and the possibility of obtaining real-time feedback on the extent of resection and the position of residual tumor tissue (which may change during surgery due to "brain-shift") are the main strengths of this method. High-performance computing has further extended the capabilities of intraoperative MRI systems, opening the way for using multimodal information and 3D anatomical reconstructions, which can be updated in "near real time." MRI sensitivity to thermal changes has also opened the way for innovative, minimally invasive (LASER ablations) as well as noninvasive therapeutic approaches for brain tumors (focused ultrasound). Although we have not used intraoperative MRI in clinical applications sufficiently long to assess long-term outcomes, this method clearly enhances the ability of the neurosurgeon to navigate the surgical field with greater accuracy, to avoid critical anatomic structures with greater efficacy, and to reduce the overall invasiveness of the surgery itself.

Brain↗

PubMed2002

High-resolution line scan diffusion tensor MR imaging of white matter fiber tract anatomy.

BACKGROUND AND PURPOSE: MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2-weighted imaging, also provides information about fiber direction. We present findings of normal white matter fiber tract anatomy at high resolution obtained by using line scan diffusion tensor imaging. METHODS: Diffusion tensor images in axial, coronal, and sagittal sections covering the entire brain volume were obtained with line scan diffusion imaging in six healthy volunteers. Images were acquired for b factors 5 and 1000 s/mm(2) at an imaging resolution of 1.7 x 1.7 x 4 mm. For selected regions, images were obtained at a reduced field of view with a spatial resolution of 0.9 x 0.9 x 3 mm. For each pixel, the direction of maximum diffusivity was computed and used to display the course of white matter fibers. RESULTS: Fiber directions derived from diffusion tensor imaging were consistent with known white matter fiber anatomy. The principal fiber tracts were well observed in all cases. The tracts that were visualized included the following: the arcuate fasciculus; superior and inferior longitudinal fasciculus; uncinate fasciculus; cingulum; external and extreme capsule; internal capsule; corona radiata; auditory and optic radiation; anterior commissure; corpus callosum; pyramidal tract; gracile and cuneatus fasciculus; medial longitudinal fasciculus; rubrospinal, tectospinal, central tegmental, and dorsal trigeminothalamic tract; superior, inferior, and middle cerebellar peduncle; pallidonigral and strionigral fibers; and root fibers of the oculomotor and trigeminal nerve. CONCLUSION: We obtained a complete set of detailed white matter fiber anatomy maps of the normal brain by means of line scan diffusion tensor imaging at high resolution. Near large bone structures, line scan produces images with minimal susceptibility artifacts.

Adult↗

PubMedDate not supplied

Diffusion tensor imaging and its application to neuropsychiatric disorders.

Magnetic resonance diffusion tensor imaging (DTI) is a new technique that can be used to visualize and measure the diffusion of water in brain tissue; it is particularly useful for evaluating white matter abnormalities. In this paper, we review research studies that have applied DTI for the purpose of understanding neuropsychiatric disorders. We begin with a discussion of the principles involved in DTI, followed by a historical overview of magnetic resonance diffusion-weighted imaging and DTI and a brief description of several different methods of image acquisition and quantitative analysis. We then review the application of this technique to clinical populations. We include all studies published in English from January 1996 through March 2002 on this topic, located by searching PubMed and Medline on the key words "diffusion tensor imaging" and "MRI." Finally, we consider potential future uses of DTI, including fiber tracking and surgical planning and follow-up.

Anisotropy↗