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A Preliminary Study of Gold Nanoparticles Enhanced Diffuse Optical Tomography

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K Xu

K Xu*, N Dogan, Y Yang, Department of Radiation Oncology, University of Miami, Miami, FL

Presentations

MO-FG-BRA-8 (Monday, July 13, 2015) 4:30 PM - 6:00 PM Room: Ballroom A


Purpose: To develop an imaging method by using gold nanoparticles (GNP) to enhance diffuse optical tomography (DOT) for better tumor detection.

Methods: Experiments were performed on a tissue-simulating cylindrical optical phantom (30mm diameter, 60mm length). The GNP used are gold nanorods (10nm diameter, 44nm length) with peak light absorption at 840nm. 0.085ml GNP colloid of 96nM concentration was loaded into a 6mm diameter cylindrical hole in the phantom. An 856nm laser beam (14mW) was used as light source to irradiate the phantom at multiple locations through rotating and elevating the phantom. A CCD camera captured the light transmission through the phantom for each irradiation with total 40 projections (8 rotation angles in 45degree steps and 5 elevations with 3mm apart). Cone beam CT of the phantom was used to generate the three-dimensional mesh for DOT reconstruction and to identify the true location of the GNP volume. A forward simulation was performed with known phantom optical properties to establish a relationship between the absorption coefficient and concentration of the GNP by matching the simulated and measured transmission. DOT image reconstruction was performed to restore the GNP within the phantom. In addition, a region-constrained reconstruction was performed by confining the solutions within the GNP volume detected from CT.

Results: The position of the GNP volume was reconstructed with <2mm error. The reconstructed average GNP concentration within an identical volume was 104nM, 8% difference from the truth. When the CT was used as “a priori”, the reconstructed average GNP concentration was 239nM, about 2.5 times of the true concentration.

Conclusion: This study is the first to demonstrate GNP enhanced DOT with phantom imaging. The GNP can be differentiated from their surrounding background. However, the reconstruction methods needs to be improved for better spatial and quantification accuracy.



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