92 research outputs found

    Early CT detection of intracranial seeding from medulloblastoma

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    Since 1975, intracranial subarachnoid metastases of medulloblastoma have been detected in seven of 23 initial contrast-enhanced computed tomographic (CT) scans in children with proven medulloblastoma. Furthermore, four of the seven cases with subarachnoid seeding were diagnosed after the introduction of high-resolution contrastenhanced CT. Only three cases of seeding had been detected in the previous 17 lowresolution cases studied with CT. Thus, it is quite likely that the incidence of subarachnoid metastases may be substantially more than the overall figure of 30% indicated by this series. This may have an impact on the treatment of these patients, since the frequent appearance of metastases may indicate the need for more vigorous chemotherapeutic regimens. One should be aware of the possibility of early intracranial subarachnoid seeding and that it can be demonstrated by contrast-enhanced CT. This is particularly true when using high-resolution scanners in conjunction with 5 mm sections through the posterior fossa . At the Childrens Hospital of Los Angeles , medulloblastoma is the most common posterior fossa brain tumor Materials and Methods We retrospecti vely reviewed surgically proven cases of medullobl astoma at Childrens Hospital of Los Angeles between 1975 and September 1983 . Since 1975 . when an EMI scanner was installed at this institution . 23 cases of medulloblastoma have been diagnosed with the aid of an initial CT scan . Several other cases either had no ini tial CT , or the initial record s could not be retrieved. The 23 cases that were available for review were scruti ni zed for evidence of subarachnoid seeding of tu mor . The primary criterion of metastases was subarachnoid enhancement on the postcontrast scan. An area of increased density on the precontrast scan and obliteration of the subarachnoid space were also considered manifestations of metastases. The scanning procedure recommended with high-resolution CT machines includes 5 mm slices through the posterior fossa before and after infusion of contrast material. Conray 60 was admini stered by drip infusion at the rate of 2 ml/ kg . It should be mentioned that this protocol was not in use during the earlier phases of this retrospective survey (before the introduction of high-resolution scanning)

    Human blood-brain barrier receptors for Alzheimer's amyloid-beta 1- 40. Asymmetrical binding, endocytosis, and transcytosis at the apical side of brain microvascular endothelial cell monolayer.

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    This is the published version. Copyright 1998 by American Society for Clinical Investigation.A soluble monomeric form of Alzheimer's amyloid-beta (1-40) peptide (sAbeta1-40) is present in the circulation and could contribute to neurotoxicity if it crosses the brain capillary endothelium, which comprises the blood-brain barrier (BBB) in vivo. This study characterizes endothelial binding and transcytosis of a synthetic peptide homologous to human sAbeta1-40 using an in vitro model of human BBB. 125I-sAbeta1-40 binding to the brain microvascular endothelial cell monolayer was time dependent, polarized to the apical side, and saturable with high- and low-affinity dissociation constants of 7.8+/-1.2 and 52.8+/-6.2 nM, respectively. Binding of 125I-sAbeta1-40 was inhibited by anti-RAGE (receptor for advanced glycation end products) antibody (63%) and by acetylated low density lipoproteins (33%). Consistent with these data, transfected cultured cells overexpressing RAGE or macrophage scavenger receptor (SR), type A, displayed binding and internalization of 125I-sAbeta1-40. The internalized peptide remains intact > 94%. Transcytosis of 125I-sAbeta1-40 was time and temperature dependent, asymmetrical from the apical to basolateral side, saturable with a Michaelis constant of 45+/-9 nM, and partially sensitive to RAGE blockade (36%) but not to SR blockade. We conclude that RAGE and SR mediate binding of sAbeta1-40 at the apical side of human BBB, and that RAGE is also involved in sAbeta1-40 transcytosis

    The morphology and biochemistry of nanostructures provide evidence for synthesis and signaling functions in human cerebrospinal fluid

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    <p>Abstract</p> <p>Background</p> <p>Cerebrospinal fluid (CSF) contacts many brain regions and may mediate humoral signaling distinct from synaptic neurotransmission. However, synthesis and transport mechanisms for such signaling are not defined. The purpose of this study was to investigate whether human CSF contains discrete structures that may enable the regulation of humoral transmission.</p> <p>Methods</p> <p>Lumbar CSF was collected prospectively from 17 participants: with no neurological or psychiatric disease, with Alzheimer's disease, multiple sclerosis, or migraine; and ventricular CSF from two cognitively healthy participants with long-standing shunts for congenital hydrocephalus. Cell-free CSF was subjected to ultracentrifugation to yield supernatants and pellets that were examined by transmission electron microscopy, shotgun protein sequencing, electrophoresis, western blotting, lipid analysis, enzymatic activity assay, and immuno-electron microscopy.</p> <p>Results</p> <p>Over 3,600 CSF proteins were identified from repeated shotgun sequencing of cell-free CSF from two individuals with Alzheimer's disease: 25% of these proteins are normally present in membranes. Abundant nanometer-scaled structures were observed in ultracentrifuged pellets of CSF from all 16 participants examined. The most common structures included synaptic vesicle and exosome components in 30-200 nm spheres and irregular blobs. Much less abundant nanostructures were present that derived from cellular debris. Nanostructure fractions had a unique composition compared to CSF supernatant, richer in omega-3 and phosphoinositide lipids, active prostanoid enzymes, and fibronectin.</p> <p>Conclusion</p> <p>Unique morphology and biochemistry features of abundant and discrete membrane-bound CSF nanostructures are described. Prostaglandin H synthase activity, essential for prostanoid production and previously unknown in CSF, is localized to nanospheres. Considering CSF bulk flow and its circulatory dynamics, we propose that these nanostructures provide signaling mechanisms <it>via </it>volume transmission within the nervous system that are for slower, more diffuse, and of longer duration than synaptic transmission.</p

    Accurate image-based CSF volume calculation of the lateral ventricles

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    Abstract The size/volume of the brain’s ventricles is essential in diagnosing and treating many neurological disorders, with various forms of hydrocephalus being some of the most common. Initial ventricular size and changes, if any, in response to disease progression or therapeutic intervention are monitored by serial imaging methods. Significant variance in ventricular size is readily noted, but small incremental changes can be challenging to appreciate. We have previously reported using artificial intelligence to determine ventricular volume. The values obtained were compared with those calculated using the inaccurate manual segmentation as the “gold standard”. This document introduces a strategy to measure ventricular volumes where manual segmentation is not employed to validate the estimations. Instead, we created 3D printed models that mimic the lateral ventricles and measured those 3D models’ volume with a tuned water displacement device. The 3D models are placed in a gel and taken to the magnetic resonance scanner. Images extracted from the phantoms are fed to an artificial intelligence-based algorithm. The volumes yielded by the automation must equal those yielded by water displacement to assert validation. Then, we provide certified volumes for subjects in the age range (1–114) months old and two hydrocephalus patients

    Automatically measuring brain ventricular volume within PACS using artificial intelligence

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    <div><p>The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and access it at a voxel level, decrypted and uncompressed that allows analytical capabilities while not perturbing the system’s daily operation. Additionally, the strategy is secure and vendor independent. Cerebral ventricular volume is important for the diagnosis and treatment of many neurological disorders. A significant change in ventricular volume is readily recognized, but subtle changes, especially over longer periods of time, may be difficult to discern. Clinical imaging protocols and parameters are often varied making it difficult to use a general solution with standard segmentation techniques. Presented is a segmentation strategy based on an algorithm that uses four features extracted from the medical images to create a statistical estimator capable of determining ventricular volume. When compared with manual segmentations, the correlation was 94% and holds promise for even better accuracy by incorporating the unlimited data available. The volume of any segmentable structure can be accurately determined utilizing the machine learning strategy presented and runs fully automatically within the PACS.</p></div
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