Development of a diagnostic system for bilirubin detection in cerebral spinal fluid

Abstract

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.

Development of an integrated hardware and software platform for the rapid detection of cerebral aneurysm rupture

“…In our previous work [10,[13][14][15] this we have implemented a set of algorithms for bilirubin quantifications in a complex biological system. The algorithms have been based on mathematics, control theory and statistical modeling.…”

“…The entire set of control data (for use as reference curves) consists of various combinations of bilirubin (signal) and hemoglobin (noise) to generate test cases which represent high, low, and intermediate S/N. Once the spectral curves are obtained, data analysis [14,15] is performed. The analysis involves scaling, normalizing and removal of noise from the spectral curves by averaging and filtering techniques.…”