In North America, approximately 30,000 people annually suffer an aneurismal subarachnoid hemorrhage (SAH). Using computerized tomography (CT), the blood is generally not visible after 12 hours. Currently lumbar puncture (LP) results are equivocal for diagnosing SAH largely because of technical limitations in performing a quick and objective evaluation. Having ruptured once, an aneurysm is statistically more likely to rupture again. Therefore, for those individuals with a sentinel (or warning) hemorrhage, detection within the first 12 hours is paramount. We present a diagnostic technology based on visible spectroscopy to quickly and objectively assess low-blood volume SAH from a diagnostic spinal tap. This technology provides clinicians, with the resources necessary for assessing patients with suspected aneurismal SAH beyond the current 12-hour limitation imposed by CT scans. This aids in the improvement of patient care and results in rapid and appropriate treatment of the patient. To perform this diagnosis, we quantify bilirubin and hemoglobin in human CSF over a range of concentrations. Because the bilirubin and hemoglobin spectra overlap quantification is problematic. To solve this problem, two algorithmic approaches are presented: a statistical or a random stochastic component known as Partial Least Square (PLS) and a control theory based mathematical model. These algorithms account for the noise and distortion from blood in CSF leading to the quantification of bilirubin and methemoglobin spectroscopically. The configurations for a hardware platform is introduced, that is portable and user-friendly composed of specific components designed to have the sensitivity and specificity required. This aids in measuring bilirubin in CSF, hemorrhagic-CSF and CSF-like solutions. The prototype uses purpose built algorithms contained within the platform, such that physicians can use it in the hospital and lab as a point of care diagnostic test.
A weakened portion of an artery in the brain leads to a medical condition known as a cerebral aneurysm. A subarachnoid hemorrhage (SAH) occurs when an aneurysm ruptures. For those individuals suspected of having a SAH, a computerized tomography (CT) scan of the brain usually demonstrates evidence of the bleeding. However, in a considerable portion of people, the CT scan is unable to detect the blood that has escaped from the blood vessel. Recent studies have indicated nearly 30% of patients with a SAH are initially misdiagnosed. For circumstances when a SAH is suspected despite a normal CT scan, physicians make the diagnosis of SAH by performing a spinal tap. A spinal tap uses a needle to sample the cerebrospinal fluid (CSF) collected from the patient’s lumbar spine. However, it is also possible for blood to be introduced into the CSF as a result of the spinal tap procedure. Therefore, an effective solution is required to help medical personnel differentiate between the blood that results from a tap and that from a ruptured aneurysm. In this paper, the development of a prototype is described which is sensitive and specific for measuring bilirubin in CSF, hemorrhagic-CSF and CSF-like solutions. To develop this instrument a combination of spectrophotometric analysis, custom data analysis software and other hardware interfaces are assembled that lay the foundation for the development of portable and user-friendly equipment suitable for assisting trained medical personnel with the diagnosis of a ruptured cerebral aneurysm.
KEYWORDS: Data modeling, Absorption, Signal to noise ratio, Cerebral aneurysms, Blood, Spectrophotometry, Chemical analysis, Computed tomography, Absorbance, Signal processing
An accurate quantification of bilirubin in cerebrospinal fluid (CSF) will provide a simple, sensitive and rapid mechanism for detecting subarachnoid hemorrhage (SAH) and for its differentiation from a traumatic spinal tap. Derivative analysis of the spectrophotometric data provides a model for determining bilirubin in CSF where the primary contaminant is Methemoglobin. Bilirubin values are determined in the range 0-9mg/dl within a methemoglobin concentration of 4.6g/dl using the derivative analysis method. The algorithm is also implemented on test samples in which the bilirubin value is constant (4.6mg/dl) and the methemoglobin varies between 0-9g/dl. The performance of the derivative analysis method is compared to the modified minimum distance method developed in reference one. We suggest a combination of these methods for accurate bilirubin estimation in CSF/hemoglobin. This will provide the foundation for the development of a portable user friendly device for diagnosis of SAH.
A cerebral aneurysm is a weakened portion of an artery in the brain. When a cerebral aneurysm ruptures, a specific type of bleeding known as a subarachnoid hemorrhage (SAH) occurs. No test exists currently to screen people for the presence of an aneurysm. The diagnosis of a SAH is made after an aneurysm ruptures, and the literature indicates that nearly one-third of patients with a SAH are initially misdiagnosed and subjected to the risks associated with aneurysm re-rupture. For those individuals with a suspected SAH, a computerized tomography (CT) scan of the brain usually demonstrates evidence of the bleeding. However, in a considerable portion of people, the CT scan is unable to detect the blood that has escaped from the blood vessel. For circumstances when a SAH is suspected despite a normal CT scan, physicians make the diagnosis of SAH by performing a spinal tap. A spinal tap uses a needle to sample the cerebrospinal fluid (CSF) collected from the patient’s back; CSF is tainted with blood after the aneurysm ruptures. To distinguish between a common headache and a SAH, a fast and an effective solution is required. We describe the development of an effective detection system integrating hardware and a powerful software interface solution. Briefly, CSF from the patient is aspirated and excited with an appropriate wavelength of light. The software employs spectrophotometric analysis of the output spectra and lays the foundation for the development of portable and user-friendly equipment for detection of a ruptured cerebral aneurysm.
Angles of arrival (AOAs) of a signal transmitted by a mobile station (MS) are estimated at two or more base stations (BSs) by employing directive antennas or antenna arrays. In traditional location algorithms, the MS position is determined by solving for the intersecting points of at least two lines of position given by these angles and the known positions of the BSs or using a Taylor series (TS) based algorithm to get a least squares (LS) solution. Obstruction of the direct path leading to non-line-of-sight (NLOS) propagation and the presence of multipaths due to scattering objects near and around the MS and BSs lead to errors in the measured AOAs
that cause these algorithms to perform poorly. In this paper, we propose an algorithm that makes use of AOA measurements at only 3 BSs including the serving BS. The algorithm mitigates the angular error by computing normalized scale factors or weights that adjust the corrupted angle measurements to near their true values. Utilizing the constraints imposed by the geometry of the cell layout and bounds obtained using the multipath angles, the scale factor estimation is formulated as a constrained optimization problem. Bounds on the scale
factors are obtained by making use of the known maximum angular spread at the NLOS BSs and the objective function to be minimized is the angle error norm at the serving BS. Our proposed algorithm has the advantage of not being limited to any particular network and can be adopted universally. Simulations show that the proposed
algorithm performs significantly better than the traditional algorithms especially when multipath information is incorporated.
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