Typical 3-D localization of tumor remnants of WHO grade II hemispheric gliomas--lessons learned from the use of intraoperative high-field MRI control

Complete resection of grade II gliomas might prolong survival but is not always possible. The goal of the study was to evaluate the location of unexpected grade II gliomas remnants after assumed complete removal with intraoperative (iop) MRI and to assess the reason for their non-detection.

Intraoperative localization of tantalum markers for proton beam radiation of choroidal melanoma by an opto-electronic navigation system: a novel technique

External beam proton radiation therapy has been used since 1975 to treat choroidal melanoma. For tumor location determination during proton radiation treatment, surgical tantalum clips are registered with image data. This report introduces the intraoperative application of an opto-electronic navigation system to determine with high precision the position of the tantalum markers and their spatial relationship to the tumor and anatomical landmarks. The application of the technique in the first 4 patients is described.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Evaluation of respiratory parameters at presentation as clinical indicators of the respiratory localization in dogs and cats with respiratory distress

OBJECTIVE: To describe clinical respiratory parameters in cats and dogs with respiratory distress and identify associations between respiratory signs at presentation and localization of the disease with particular evaluation between the synchrony of abdominal and chest wall movements as a clinical indicators for pleural space disease. Design - Prospective observational clinical study. SETTING: Emergency service in a university veterinary teaching hospital. ANIMALS: Cats and dogs with respiratory distress presented to the emergency service between April 2008 and July 2009. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The following parameters were systematically determined at time of admission: respiratory rate, heart rate, temperature, type of breathing, movement of the thoracic and abdominal wall during inspiration, presence of stridor, presence and type of dyspnea, and results of thoracic auscultation. Abdominal and chest wall movement was categorized as synchronous, asynchronous, or inverse. Diagnostic test results, diagnosis, and outcome were subsequently recorded. Based on the final diagnoses, animals were assigned to 1 or more of the following groups regarding the anatomical localization of the respiratory distress: upper airways, lower airways, lung parenchyma, pleural space, thoracic wall, nonrespiratory causes, and normal animals. One hundred and seventy-six animals (103 cats and 73 dogs) were evaluated. Inspiratory dyspnea was associated with upper airway disease in dogs and expiratory dyspnea with lower airway disease in cats. Respiratory noises were significantly associated and highly sensitive and specific for upper airway disease. An asynchronous or inverse breathing pattern and decreased lung auscultation results were significantly associated with pleural space disease in both dogs and cats (P<0.001). The combination is highly sensitive (99%) but not very specific (45%). Fast and shallow breathing was not associated with pleural space disease. Increased or moist pulmonary auscultation findings were associated with parenchymal lung disease. CONCLUSIONS: Cats and dogs with pleural space disease can be identified by an asynchronous or inverse breathing pattern in combination with decreased lung sounds on auscultation.

Design techniques and analysis of high-resolution neural recording systems targeting epilepsy focus localization

The design of a high-density neural recording system targeting epilepsy monitoring is presented. Circuit challenges and techniques are discussed to optimize the amplifier topology and the included OTA. A new platform supporting active recording devices targeting wireless and high-resolution focus localization in epilepsy diagnosis is also proposed. The post-layout simulation results of an amplifier dedicated to this application are presented. The amplifier is designed in a UMC 0.18µm CMOS technology, has an NEF of 2.19 and occupies a silicon area of 0.038 mm(2), while consuming 5.8 µW from a 1.8-V supply.

Angiotensinergic innervation of the kidney: Localization and relationship with catecholaminergic postganglionic and sensory nerve fibers

We describe an angiotensin (Ang) II-containing innervation of the kidney. Cryosections of rat, pig and human kidneys were investigated for the presence of Ang II-containing nerve fibers using a mouse monoclonal antibody against Ang II (4B3). Co-staining was performed with antibodies against synaptophysin, tyrosine 3-hydroxylase, and dopamine beta-hydroxylase to detect catecholaminergic efferent fibers and against calcitonin gene-related peptide to detect sensory fibers. Tagged secondary antibodies and confocal light or laser scanning microscopy were used for immunofluorescence detection. Ang II-containing nerve fibers were densely present in the renal pelvis, the subepithelial layer of the urothelium, the arterial nervous plexus, and the peritubular interstitium of the cortex and outer medulla. They were infrequent in central veins and the renal capsule and absent within glomeruli and the renal papilla. Ang II-positive fibers represented phenotypic subgroups of catecholaminergic postganglionic or sensory fibers with different morphology and intrarenal distribution compared to their Ang II-negative counterparts. The Ang II-positive postganglionic fibers were thicker, produced typically fusiform varicosities and preferentially innervated the outer medulla and periglomerular arterioles. Ang II-negative sensory fibers were highly varicose, prevailing in the pelvis and scarce in the renal periphery compared to the rarely varicose Ang II-positive fibers. Neurons within renal microganglia displayed angiotensinergic, catecholaminergic, or combined phenotypes. Our results suggest that autonomic fibers may be an independent source of intrarenal Ang II acting as a neuropeptide co-transmitter or neuromodulator. The angiotensinergic renal innervation may play a distinct role in the neuronal control of renal sodium reabsorption, vasomotion and renin secretion.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.