Recent Advances in Diffuse Optical Imaging of Osteoarthritis

Zhen Yuan; Huabei Jiang

doi:10.4172/2153-0777.1000e110

ISSN: 2153-0777

Journal of Bioengineering and Bioelectronics

Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.

Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business

Recent Advances in Diffuse Optical Imaging of Osteoarthritis

*Zhen Yuan^and Huabei Jiang**
Department of Biomedical Engineering, University of Florida, Gainesville, FL32611, USA
Corresponding Author :	Zhen Yuan Department of Biomedical Engineering University of Florida Gainesville, FL32611, USA E-mail: yzhen@ad.ufl.edu
Received March 15, 2012; Accepted March 18, 2012; Published March 20, 2012
Citation: Yuan Z, Jiang H (2012) Recent Advances in Diffuse Optical Imaging of Osteoarthritis. J Biochip Tissue chip 2:e110. doi:10.4172/2153-0777.1000e110
Copyright: © 2012 Yuan Z, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Journal of Bioengineering and Bioelectronics

View PDF Download PDF Tables & Figures

Introduction

Osteoarthritis (OA) is the most common arthritic condition world- wide and is estimated to affect nearly 60 million Americans. Classically, OA is most often found in the large weight-bearing joints of the lower extremities, particularly the knees and hips. However, there is also a subset of individuals with a predilection for developing OA of the hand and a more generalized form of OA. To diagnose cartilage abnormali- ties and alterations in composition of synovial fluid in joints affected by OA, a variety of imaging methods have been developed and tested, such as x-ray, ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI). In particular, due to its numerous advan- tages of low cost, portability, and non-ionizing radiation, NIR DOT is emerging as a potential tool for imaging bones and joint tissues [1,2].

The DOT alone only imaging methods are able to provide a variety of functional and structural information with high sensitivity and spe- cificity compared to other imaging modalities. This is especially true for the joints of the fingers, where the small dimensions and much higher transmitted light intensities should result in better signal to noise ratios and greatly improved spatial resolution. In addition, an optimized ap- proach that combines x-ray and DOT imaging has been developed for a case as well as clinical study of OA in the finger joints [2]. The basic idea of this multi-modality imaging approach is to incorporate the high resolution structural x-ray images into the DOT reconstruction so that both the resolution and quantitative accuracy of optical image recon- struction are enhanced.

DOT Imaging Systems

The DOT imaging system (Figure 1) consists of laser modules, a hybrid light delivery subsystem, a fiber optics/tissue interface, a data acquisition module, and light detection modules [1]. The hybrid x-ray/ DOT imaging system integrates a modified mini C-arm x-ray system (MiniView 6800, GE-OEC, UT) with the 64x64-channel photodiodes-based DOT system (Figure 2) [2]. Tomographic x-ray images were reconstructed from 2D projections using an improved shift-and-add algorithm we developed previously [2]. In the hybrid imaging of joint tissues, the x-ray imaging was performed immediately after the DOT data acquisition.

DOT Reconstruction

When the data acquisition was finished, the next step was to gener- ate the optical images using a robust 3D reconstruction algorithm. Our existing reconstruction algorithm is based on the following diffusion equation and type-III BCs [1]:

(1)

where Φ(r) is the photon intensity, D(r) the diffusion coefficient, α is a coefficient related to the boundary, μ_a(r) is the absorption coefficient, and S(r) is the source term. The finite element discretized form of Equation (1) is written as: [A]{Φ} = {b} .

The inverse solution is obtained through the following equations:

(2)

Where χ expresses D and μ_a, and

is the Jacobian matrix formed by ∂Φ / ∂χ at the boundary measurement sites. λ is a scalar and I is the identity matrix. and is the updating vector for the optical properties.

and

where

and

are observed and computed photon intensity for i=1, 2…, M boundary locations. For x-ray guided DOT reconstruction, the following updating equation is used for the inverse problem,

(3)

Where the x-ray structural a priori information is incorporated into the iterative process using the spatially variant filter matrix L [2].

Reconstructed Results

From the absorption and scattering images shown in (Figure 3,4),we find that the bones are clearly identified. Importantly, compared with the optical parameters of the bones, we observe a significantly drop in the strength of absorption and scattering properties of the healthy joint tissues surrounding the joint space. However, relative to the optical properties of the bones, we see only a small drop for the OA joint tissues.

As shown in (Figure 4), when a subset of the x-ray prior knowledge of the joint structure was used in the DOT reconstruction, distinct boundaries separating different tissues were recovered clearly, indicating the significant improvement of DOT resolution because of the incorporation of prior x-ray structural information. These optical images show accurate delineation of the joint space and bone geometry, consistent with the x-ray findings. The image quality obtained from the hybrid system is significantly improved over that from DOT alone.

References