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Proceedings Paper

Optoacoustic sensing for target detection inside cylindrical catheters
Author(s): Behnoosh Tavakoli; Xiaoyu Guo; Russell H. Taylor; Jin U. Kang; Emad M. Boctor
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Paper Abstract

Optoacoustic sensing is a hybrid technique that combines the advantages of high sensing depth of ultrasound with contrast of optical absorption. In this study a miniature optoacoustic probe that can characterize the target properties located at the distal end of a catheter is investigated. The probe includes an optical fiber to illuminate the target with the pulsed laser light and a hydrophone to detect the generated optoacoustic signal. The probe is designed for the forwardsensing and therefore the acoustic signal propagates along the tube before being detected. Due to the circular geometry, the waves inside the tube are highly complex. A three dimensional numerical simulation is performed to model the optoacoustic wave generation and propagation inside the water filled cylindrical tubes. The effect of the boundary condition, tube diameter and target size on the detected signal is systematically evaluated. A prototype of the probe is made and tested for detecting an absorbing target inside a 2mm diameter tube submerged in water. The preliminary experimental results corresponding to the simulation is acquired. Although many different medical applications for this miniature probe may exist, our main focus is on detecting the occlusion inside the ventricular shunts. These catheters are used to divert the excess cerebrospinal fluid to the absorption site and regulate inter cranial pressure of hydrocephalous patients. Unfortunately the malfunction rate of these catheters due to blockage is very high. This sensing tool could locate the occluding tissue non-invasively and can potentially characterize the occlusion composites by scanning at different wavelengths of the light.

Paper Details

Date Published: 12 March 2014
PDF: 6 pages
Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 90360G (12 March 2014); doi: 10.1117/12.2043614
Show Author Affiliations
Behnoosh Tavakoli, Johns Hopkins Univ. (United States)
Xiaoyu Guo, Johns Hopkins Univ. (United States)
Russell H. Taylor, Johns Hopkins Univ. (United States)
Jin U. Kang, Johns Hopkins Univ. (United States)
Emad M. Boctor, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 9036:
Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling
Ziv R. Yaniv; David R. Holmes, Editor(s)

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