Study of probe-sample distance for biomedical spectra measurement
© Wang et al; licensee BioMed Central Ltd. 2011
Received: 31 August 2011
Accepted: 2 November 2011
Published: 2 November 2011
Fiber-based optical spectroscopy has been widely used for biomedical applications. However, the effect of probe-sample distance on the collection efficiency has not been well investigated.
In this paper, we presented a theoretical model to maximize the illumination and collection efficiency in designing fiber optic probes for biomedical spectra measurement. This model was in general applicable to probes with single or multiple fibers at an arbitrary incident angle. In order to demonstrate the theory, a fluorescence spectrometer was used to measure the fluorescence of human finger skin at various probe-sample distances. The fluorescence spectrum and the total fluorescence intensity were recorded.
The theoretical results show that for single fiber probes, contact measurement always provides the best results. While for multi-fiber probes, there is an optimal probe distance. When a 400- μm excitation fiber is used to deliver the light to the skin and another six 400- μm fibers surrounding the excitation fiber are used to collect the fluorescence signal, the experimental results show that human finger skin has very strong fluorescence between 475 nm and 700 nm under 450 nm excitation. The fluorescence intensity is heavily dependent on the probe-sample distance and there is an optimal probe distance.
We investigated a number of probe-sample configurations and found that contact measurement could be the primary choice for single-fiber probes, but was very inefficient for multi-fiber probes. There was an optimal probe-sample distance for multi-fiber probes. By carefully choosing the probe-sample distance, the collection efficiency could be enhanced by 5-10 times. Our experiments demonstrated that the experimental results of the probe-sample distance dependence of collection efficiency in multi-fiber probes were in general agreement with our theory.
Optical spectroscopy including reflectance, fluorescence and Raman spectroscopy has been used for biomedical applications, such as for cervical cancer [1, 2], lung cancer  and skin cancer diagnosis . Fiber-based probes have been widely used in biomedical spectroscopy and biomedical imaging, which provide an effective and flexible optical interface between the spectroscopic device and the samples to be measured [5–7]. The fibers have double roles in these systems: (i) delivery of illumination light to the target; and (ii) collection and delivery of signal to the spectrometer or detector. These fiber-based probes are flexible and thus can be miniaturized and put into cavities for endoscopic measurement, or inserted into microstructures such as needles. So far, fiber probes can be made with an outer diameter less than 0.5 mm . The optical probe is not only limited by size, but also the illumination and collection efficiency. However, most of the probes reported in literature are lack of optimization in illumination and collection efficiency, although this is critical for low signal detection such as fluorescence and Raman spectroscopy measurement [8, 9]. In this paper, we presented a theoretical model in designing fiber optic probes for biomedical applications to maximize the illumination and collection efficiency. This model is applicable to probes with single or multiple fibers at an arbitrary incident angle. We investigated a number of probe configurations and find that contact measurement for such kind of probes is very inefficient for fiber bundles. By carefully choosing the probe and sample distance, the collection efficiency can be enhanced by 5-10 fold. Experimental results are also presented to demonstrate the probe-sample distance dependence.
2. Methods and experiments
2.1 Single fiber probe
We start from a single, bare optical fiber, which can be used as light source delivery and signal collection. This is the simplest form of optical fiber based probe, but of important practical usage . When light is incident onto the sample, it will be subject to specular reflection due to refractive index mismatching at the interface and diffuse reflection due to scattering. To study the collection efficiency, it can be divided into two separate processes: (1) implementation of light transport model in the tissue and (2) light coupling between the tissue and the fiber probe. Light transport in tissue has been studied , which can be modeled using Monte Carlo simulations . We will focus on the light coupling issues between the tissue and the fiber probe.
where I esc represents the light escaped from sample surface (including specular reflection). The light collected, R collect , should be split into two parts: the light that enters the optical fiber with an angle smaller than the half-angle of the acceptance angle (R core ), and the light that enters the optical fiber with an angle larger than the half-acceptance angle (R cladding ). R core is guided to the detector by the fiber core, and the R cladding is lost by fiber from fiber cladding. Equation (3) can be reduced as f = R core /R diffuse . Both R core and R diffuse can be determined numerically by Monte Carlo simulations . This is a reverse problem in that the collection efficiency is determined by measuring the collected signal divided by the total signal simulated from the sample surface. In reality, particularly for probe designing, people want to design the probe so that it can collect as much signal as possible, given the signal (R diffuse ) from the surface is known (or constant).
where I out is the intensity out of the fiber surface. r is the radius of the fiber core, d is the distance from the fiber tip to the tissue surface (center of fiber core to the tissue surface along optical axis of the fiber). θ is the acceptance angle, determined by the numerical aperture of the fiber, θ = arcsin(NA/n 0). If there is no water or other medium between fiber probe and tissue surface, n 0 is refractive index of air n 0 = 1. NA is the numerical aperture of the fiber. For the commonly used fiber with NA = 0.22, the acceptance angle is 12.7°. β is the tilt angle of the fiber probe. Notice that the intensity on the sample surface maximizes for normal illumination (β = 0), because the illumination surface is the smallest for any given probe-sample distance. In equation (4), we assume the light is uniformly illuminated on the tissue surface.
In Equation (6), I esc is determined by the tissue properties that can not affected by the fiber probe. I out is the illumination intensity from the fiber output which is determined by the laser power.
2.2 Multi-fiber probe
In equation (9), I esc is determined by the tissue properties that can not be affected by the fiber probe. I out is the illumination intensity out of the illumination fiber, which is determined by the laser power. r is the radius of the fiber, d' is the equivalent fiber probe distance defined by equation (5b), r c is the distance between the illumination fiber and the collection fiber. θ is determined by the fiber NA. In the above analysis, we assume both the illumination and collection have same numerical apertures.
2.3 Fluorescence measurement
3. Results and discussions
In summary, we studied the collection efficiency of fiber probes in biomedical spectroscopy and biomedical imaging. It was found that for single fiber probes, contact measurement always provides the best results. While for multi-fiber probes, there is an optimal probe distance. This optimal distance depends on the diameter of the fiber, and the distance between illumination and collection fibers. Tilted probes may also increase the collection efficiency but not as much as probe-distance effect. For normal illumination and collection, signals can be improved by 5 fold at the optimal distance than contact measurement.
- Richards-Kortum R, Sevick-Muraca E: Quantitative optical spectroscopy for tissue diagnosis. Annu Rev Phys Chem 1996, 47: 555–606. 10.1146/annurev.physchem.47.1.555View ArticleGoogle Scholar
- Utzinger U, Heintzelman DL, Mahadevan-Jansen A, Malpica A, Follen M, Richards-Kortum R: Near-infrared Raman spectroscopy for in vivo detection of cervical precancers. Appl Spectrosc 2001, 55: 955–959. 10.1366/0003702011953018View ArticleGoogle Scholar
- Lam S, MacAulay C, IeRiche JC, Palcic B: Detection and localization of early lung cancer by fluorescence bronchoscopy. Cancer 2000, 89: 2468–2473. 10.1002/1097-0142(20001201)89:11+<2468::AID-CNCR25>3.0.CO;2-VView ArticleGoogle Scholar
- Brancaleon L, Durkin AJ, Tu JH, Menaker G, Fallon JD, Kollias N: In vivo fluorescence spectroscopy of nonmelanoma skin cancer. Photochem Phobiol 2001, 73: 178–183. 10.1562/0031-8655(2001)073<0178:IVFSON>2.0.CO;2View ArticleGoogle Scholar
- Utzinger U, Richards-Kortum R: Fiber optic probes for biomedical optical spectroscopy. J Biomed Opt 2003, 8: 121–147. 10.1117/1.1528207View ArticleGoogle Scholar
- Moffitt TP, Prahl SA: Sized-fiber reflectomery for measuring local optical properties. IEEE J Quantum Electron 2001, 7: 952–958. 10.1109/2944.983299View ArticleGoogle Scholar
- Pogue BW, G B: Fiber-optic bundle design for quantitative fluorescence measurement from tissue. Appl Opt 1998, 37: 7429–7436. 10.1364/AO.37.007429View ArticleGoogle Scholar
- Bargo PR, Prahl SA, Jacques SL: Collection efficiency of a single fiber in turbid media. Appl Opt 2003, 42: 3187–3197. 10.1364/AO.42.003187View ArticleGoogle Scholar
- Bargo PR, Prahl SA, Jacques SL: Optical properties effects upon the collection efficiency of optical fibers in disfferent probe configurations. IEEE Journal of Selected Topics in Quantum Electronics 2003, 9: 314–321. 10.1109/JSTQE.2003.811287View ArticleGoogle Scholar
- Jacques SL: Modeling light transport in tissue. In Biomedical optical instrumentation and laser-assisted biotechnology. Edited by: Pratesi R. Kluwer Academic, Dordrecht; 1996:21–32.View ArticleGoogle Scholar
- Wang L, Jacques SL, Zheng L: MCML-Monte Carlo modeling of light transport in multi-layered tissues. Computer Methods and Programs in Biomedicine 1995, 47: 131–146. 10.1016/0169-2607(95)01640-FView ArticleGoogle Scholar
- Richards-Kortum R, Drezek R, Sokolov K, Pavlova I, Follen M: Survey of endogenous biological fluorophores. In Handbook of biomedical fluorescence. Edited by: Mycek M, Pogue BW. Marcel Dekker; 2003:237–264.Google Scholar
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