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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 3, Iss. 5 — May. 1, 2012
  • pp: 1086–1100
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Scattering phase function spectrum makes reflectance spectrum measured from Intralipid phantoms and tissue sensitive to the device detection geometry

S. C. Kanick, V. Krishnaswamy, U. A. Gamm, H. J. C. M. Sterenborg, D. J. Robinson, A. Amelink, and B. W. Pogue  »View Author Affiliations


Biomedical Optics Express, Vol. 3, Issue 5, pp. 1086-1100 (2012)
http://dx.doi.org/10.1364/BOE.3.001086


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Abstract

Reflectance spectra measured in Intralipid (IL) close to the source are sensitive to wavelength-dependent changes in reduced scattering coefficient (μs) and scattering phase function (PF). Experiments and simulations were performed using device designs with either single or separate optical fibers for delivery and collection of light in varying concentrations of IL. Spectral reflectance is not consistently linear with varying IL concentration, with PF-dependent effects observed for single fiber devices with diameters smaller than ten transport lengths and for separate source-detector devices that collected light at less than half of a transport length from the source. Similar effects are thought to be seen in tissue, limiting the ability to quantitatively compare spectra from different devices without compensation.

© 2012 OSA

1. Introduction

Reflectance spectroscopy provides estimates of optical properties within a turbid medium such as tissue. This modality has an important role in the field of biomedical optics, as reflectance spectra can be used to extract information about aspects of the tissue physiology (e.g. vascular oxygen saturation and blood volume fraction) [1

1. A. Amelink, O. P. Kaspers, H. J. C. M. Sterenborg, J. E. van der Wal, J. L. N. Roodenburg, and M. J. H. Witjes, “Non-invasive measurement of the morphology and physiology of oral mucosa by use of optical spectroscopy,” Oral Oncol. 44(1), 65–71 (2008). [CrossRef] [PubMed]

,2

2. J. Q. Brown, K. Vishwanath, G. M. Palmer, and N. Ramanujam, “Advances in quantitative UV-visible spectroscopy for clinical and pre-clinical application in cancer,” Curr. Opin. Biotechnol. 20(1), 119–131 (2009). [CrossRef] [PubMed]

] and morphology (e.g. cell, organelle size and density) [3

3. J. R. Mourant, A. H. Hielscher, A. A. Eick, T. M. Johnson, and J. P. Freyer, “Evidence of intrinsic differences in the light scattering properties of tumorigenic and nontumorigenic cells,” Cancer 84(6), 366–374 (1998). [CrossRef] [PubMed]

6

6. P. B. Garcia-Allende, V. Krishnaswamy, P. J. Hoopes, K. S. Samkoe, O. M. Conde, and B. W. Pogue, “Automated identification of tumor microscopic morphology based on macroscopically measured scatter signatures,” J. Biomed. Opt. 14(3), 034034 (2009). [CrossRef] [PubMed]

] and can be used to correct raw fluorescence measurements for the influences of background scattering and absorption [7

7. R. Weersink, M. S. Patterson, K. Diamond, S. Silver, and N. Padgett, “Noninvasive measurement of fluorophore concentration in turbid media with a simple fluorescence /reflectance ratio technique,” Appl. Opt. 40(34), 6389–6395 (2001). [CrossRef] [PubMed]

9

9. S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Semi-empirical model of the effect of scattering on single fiber fluorescence intensity measured on a turbid medium,” Biomed. Opt. Express 3(1), 137–152 (2012). [CrossRef] [PubMed]

]. Spectra measured in reference media such as the fat emulsion commercialized as Intralipid (IL) are often used to calibrate or understand instrument performance [10

10. B. W. Pogue and M. S. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. 11(4), 041102 (2006). [CrossRef] [PubMed]

], yet the spectra recorded by different devices can be dramatically affected by device-specific sensitivities to the scattering properties. In this study, the influence of detection geometry with respect to IL concentration is studied in detail using measurements and Monte Carlo studies, to illustrate and interpret how the spectra can change.

Fiber optic reflectance devices are designed to sample light from a location of interest where typically the size and shape is customized for the biological application. Devices that collect reflectance remitted at large distances from the source can achieve (relatively) deep sampling and therefore are capable of monitoring volume averaged quantities in bulk tissues such as blood oxygenation in the brain [11

11. D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23(Suppl 1), S275–S288 (2004). [CrossRef] [PubMed]

] or breast [12

12. T. O. McBride, B. W. Pogue, E. D. Gerety, S. B. Poplack, U. L. Osterberg, and K. D. Paulsen, “Spectroscopic diffuse optical tomography for the quantitative assessment of hemoglobin concentration and oxygen saturation in breast tissue,” Appl. Opt. 38(25), 5480–5490 (1999). [CrossRef] [PubMed]

]. Conversely, devices that collect reflectance close to the light source sample highly localized volumes, and therefore can provide selective sampling of superficial tissue layers [13

13. J. R. Mourant, T. Fuselier, J. Boyer, T. M. Johnson, and I. J. Bigio, “Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms,” Appl. Opt. 36(4), 949–957 (1997). [CrossRef] [PubMed]

19

19. V. Krishnaswamy, A. M. Laughney, K. D. Paulsen, and B. W. Pogue, “Dark-field scanning in situ spectroscopy platform for broadband imaging of resected tissue,” Opt. Lett. 36(10), 1911–1913 (2011). [CrossRef] [PubMed]

]. Validation of these devices with tissue-simulating optical phantoms in vitro is critical to allow characterization of the observed reflectance in response to controlled optical properties within the phantom. Phantom measurements may also be a valuable method to calibrate the wavelength-specific device response for use in analyzing measurements of media with unknown optical properties, such as tissue. Perhaps the most commonly adopted scattering phantom is IL [10

10. B. W. Pogue and M. S. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. 11(4), 041102 (2006). [CrossRef] [PubMed]

,20

20. P. D. Ninni, F. Martelli, and G. Zaccanti, “Intralipid: towards a diffusive reference standard for optical tissue phantoms,” Phys. Med. Biol. 56(2), N21–N28 (2011). [CrossRef] [PubMed]

], because it is stable across batches, readily purchased and has been extensively investigated to characterize the wavelength-dependent optical properties [21

21. H. J. van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. van Gemert, “Light scattering in Intralipid-10% in the wavelength range of 400-1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991). [CrossRef] [PubMed]

24

24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

]. Dilutions of IL can yield wavelength-dependent reduced scattering coefficients (μs) that are similar to values reported in tissue. These characteristics have led to wide acceptance of IL as a tissue-simulating scattering standard for the investigation of many types of reflectance devices [13

13. J. R. Mourant, T. Fuselier, J. Boyer, T. M. Johnson, and I. J. Bigio, “Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms,” Appl. Opt. 36(4), 949–957 (1997). [CrossRef] [PubMed]

,15

15. A. Amelink and H. J. C. M. Sterenborg, “Measurement of the local optical properties of turbid media by differential path-length spectroscopy,” Appl. Opt. 43(15), 3048–3054 (2004). [CrossRef] [PubMed]

19

19. V. Krishnaswamy, A. M. Laughney, K. D. Paulsen, and B. W. Pogue, “Dark-field scanning in situ spectroscopy platform for broadband imaging of resected tissue,” Opt. Lett. 36(10), 1911–1913 (2011). [CrossRef] [PubMed]

]. However, as this study shows, spectra measured in the same IL phantom by different reflectance geometries may show substantially different spectral features.

To understand how scattering properties influence reflectance spectra measured by different device geometries differently, it is important to consider the influence of scattering on the transport of light being collected during measurements. Light that travels relatively large distances in scattering media is termed diffuse, with photon transport occurring in the direction of fluence (concentration) gradients within the medium [25

25. T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992). [CrossRef] [PubMed]

,26

26. S. L. Jacques and B. W. Pogue, “Tutorial on diffuse light transport,” J. Biomed. Opt. 13(4), 041302 (2008). [CrossRef] [PubMed]

]. Collected diffuse reflectance intensities can be described analytically by the diffusion approximation to the radiative transport equation, which allows estimation of both μs and the absorption coefficient (μa) [18

18. A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express 18(6), 5580–5594 (2010). [CrossRef] [PubMed]

,25

25. T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992). [CrossRef] [PubMed]

]. The heuristic guideline for diffuse transport is light that has travelled 1 to 2 mean free transport lengths from the source [26

26. S. L. Jacques and B. W. Pogue, “Tutorial on diffuse light transport,” J. Biomed. Opt. 13(4), 041302 (2008). [CrossRef] [PubMed]

]; here, the term transport length is defined as (μs+μa)1. Analysis of diffuse light is insensitive to the form of the scattering phase function (PF), as changes to the scatter frequency (given by μs) and directionality (given by PF) interchangeably influence diffuse light transport in the form of the reduced scattering coefficient μs=μs(1g), where g is the anisotropy given as g=cos(Θs). As the distance between source and collection location decreases, the sampled transport regime shifts from the collection of multiply scattered light to the collection of photons that may have undergone few (or single) scattering events [27

27. J. R. Mourant, J. Boyer, A. H. Hielscher, and I. J. Bigio, “Influence of the scattering phase function on light transport measurements in turbid media performed with small source-detector separations,” Opt. Lett. 21(7), 546–548 (1996). [CrossRef] [PubMed]

,28

28. F. Bevilacqua and C. Depeursinge, “Monte Carlo study of diffuse reflectance at source–detector separations close to one transport mean free path,” J. Opt. Soc. Am. A 16(12), 2935–2945 (1999). [CrossRef]

]. Light transport in this semi- to non-diffuse regime is not exclusively characterized by μs, but is also influenced by the probability of large angle backscattering events, which is defined by the scattering PF [28

28. F. Bevilacqua and C. Depeursinge, “Monte Carlo study of diffuse reflectance at source–detector separations close to one transport mean free path,” J. Opt. Soc. Am. A 16(12), 2935–2945 (1999). [CrossRef]

,29

29. A. Kienle, F. K. Forster, and R. Hibst, “Influence of the phase function on determination of the optical properties of biological tissue by spatially resolved reflectance,” Opt. Lett. 26(20), 1571–1573 (2001). [CrossRef] [PubMed]

].

2. Methods

2.1. Single fiber reflectance experimental setup

The experimental apparatus for the reflectance device that uses a single fiber optic to deliver and collect light during measurements has been described in detail previously [35

35. S. C. Kanick, U. A. Gamm, M. Schouten, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence,” Biomed. Opt. Express 2(6), 1687–1702 (2011). [CrossRef] [PubMed]

,36

36. S. C. Kanick, H. J. C. M. Sterenborg, and A. Amelink, “Empirical model of the photon path length for a single fiber reflectance spectroscopy device,” Opt. Express 17(2), 860–871 (2009). [CrossRef] [PubMed]

]. The device consists of a halogen light source (HL-2000-FHSA, Ocean Optics, Duiven, Netherlands), a spectrometer (SD2000, Ocean Optics, Duiven, Netherlands) and a solid core single fiber probe that is connected to the light source and the spectrometer via a bifurcated fiber. The probe tip is polished at an angle of 15 degrees to remove specular reflections within the collected reflectance intensity due to the index of refraction mismatch at the probe/medium interface. This study used a calibration procedure to account for variations in the output of the lamp, transmission characteristics of the fiber, and sensitivity of the spectrometer. Calibration measurements were performed in a calibration phantom containing 20% IL diluted to a volume particle concentration of 1.5%, which yielded μs (800 nm) = 1.2 mm−1 (IILcal(λ)), and in a dark container filled with water (Iwater(λ)):

RSFo(λ)=IILsim(λ)(Iphantom(λ)Iwater(λ)IILcal(λ)Iwater(λ))
(1)

Here, Iphantom(λ) is the raw signal of a sampled optical phantom, and IILsim(λ) is the absolute single fiber reflectance (SFR) signal, expressed in % of incident photons, obtained by Monte Carlo (MC) simulations of the IL calibration phantom. Importantly, for these simulations the wavelength-specific PFs and μs values reported by [24

24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

] were used. The calculation results in the calibrated single fiber reflectance intensity, RSFo(λ).

2.2. Intralipid tissue simulating phantom preparation

The liquid phantoms were prepared by mixing 0.9% NaCl (Baxter, Utrecht, Netherlands) with different amounts of Intralipid 20% (Fresenius Kabi, s-Hertogenbosch, Netherlands); this stock solution has a volume particle concentration percentage (ILp) of 22.7% [22

22. G. Zaccanti, S. Del Bianco, and F. Martelli, “Measurements of optical properties of high-density media,” Appl. Opt. 42(19), 4023–4030 (2003). [CrossRef] [PubMed]

]. Phantoms were prepared in volumes of 20 ml with dilutions resulting in ILp values of [0.455, 0.568, 0.908, 1.135, 1.476, 2.951, 4.540] %. The reduced scattering coefficient of the Intralipid stock solution was determined to be μs (800 nm) = 18.6 mm−1 by using the formula given by Michels et al. [24

24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

]. The dependence of μs on the Intralipid concentration was assumed to be linear (for the range of concentrations investigated) and the resulting wavelength-dependent μs is given for selected phantoms in Fig. 2 (A). The dilutions selected for this study resulted in a range of μs = [0.4-8] mm−1 that is representative of the values reported in tissue [37

37. W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990). [CrossRef]

].

Reflectance measurements were performed by submerging the probe tip a few millimeters into the phantom and suspending it multiple centimeters from the container bottom or sides, such that the probe would not collect reflections from container surfaces. The measurement was repeated 3 times for each phantom, with these spectra averaged for each phantom. All measurements were performed with 5 fiber probes of diameter: [0.2, 0.4, 0.6, 0.8, 1.0] mm. The phantom was gently agitated before collecting each spectrum to ensure homogeneity. Measurements were reproducible, with variation between repeated measurements of < 3%.

2.3. Monte Carlo simulations of reflectance measurements

The Monte Carlo code utilized in this study is based on the steady state light transport in multi-layered structures (MCML) approach to stochastically simulate photon propagation within a turbid medium [35

35. S. C. Kanick, U. A. Gamm, M. Schouten, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence,” Biomed. Opt. Express 2(6), 1687–1702 (2011). [CrossRef] [PubMed]

,38

38. L. Wang, S. L. Jacques, and L. Zheng, “MCML--Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995). [CrossRef] [PubMed]

,39

39. S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Monte Carlo analysis of single fiber reflectance spectroscopy: photon path length and sampling depth,” Phys. Med. Biol. 54(22), 6991–7008 (2009). [CrossRef] [PubMed]

]. The code was adapted to simulate the measurement of reflectance intensity from a turbid medium with homogeneously distributed optical properties; this model of photon propagation has previously been described in detail and will be reviewed here briefly. Photons were initialized by selecting a location on the fiber face in contact with the medium and were launched into a direction within the fiber cone of acceptance, given as θa=sin1(NAn), with the fiber numerical aperture (NA) and the index of refraction of the medium given by n. Both location and direction were sampled from uniform distributions. The fiber probes were modeled in contact with the turbid medium at an air interface, with n of the medium set to 1.33 and that of the fiber to 1.45. The fiber NA was specified as 0.22. Reflection and refraction at the boundary between fiber face and medium were accounted for by using Fresnel’s equation and Snell’s law. The photons were propagated through the medium in discrete steps selected from an exponential distribution that was weighted by the scattering coefficient. Each scattering event resulted in a change in propagation direction that was sampled from a discrete user-specified PF distribution. Photons that contacted the detector fiber within the cone of acceptance were collected. For all simulations, photons that propagated far from the fiber face did not contribute to the collected reflectance intensity and were terminated at a hemispherical limit from the source fiber at a distance great enough to not influence the model outputs for the range of optical properties investigated in this study. The collection area for the single fiber simulations overlapped the source fiber location, with df specified in the range [0.2, 0.4, 0.6, 0.8, 1.0] mm. For separate source detector devices, source and detector fiber diameters were fixed to 0.2 mm, and photons were collected using annular areas at appropriate radial distance such that the core-to-core separation ρ was specified in the range [0.2, 0.4, 0.6, 1.0, 2.0] mm. Simulations returned collected reflectance intensity in the absence of absorption, and also returned the weighted average number of scattering events experienced by collected photons from each measurement. Reflectance intensity returned for separate source detector simulations was calculated by the ratio of the total number of photons collected (TPC) by the total number of photons launched (TPL) and corrected for differences in collection area (A), as

RSDN(λ)=(1A)(TPCTPL)
(2)

The optical properties of the simulated medium were selected to mimic IL phantoms. The reduced scattering coefficient was specified by linearly scaling the μs of the IL 20% stock solution, given in [24

24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

] for the selected IL dilutions. Simulations of single fiber reflectance probes were performed to match the measured optical phantoms, and simulations for the separate source detector device were performed for IL dilutions resulting in ILp values of [0.454, 0.568, 1.135, 2.270, 3.405, 4.540, 5.675]. Wavelength-dependent PFs were specified using empirical formulas also reported in [24

24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

], with simulations performed at discrete wavelengths between 400 and 800 nm at 100 nm increments. Each simulation initialized between 10 and 100 million photons.

3. Results

3.1. Reflectance measurement of IL phantoms with a single fiber device

3.2. Reflectance measurement of IL phantoms with separate source-detector fibers

Figure 5
Fig. 5 Analysis of spectral scattering features observed in simulated reflectance spectra collected by devices with separate source and detector. Left hand column shows dimensionless reflectance spectra returned using selected source detector separations of A) 0.2 (x marks), B) 0.4 (circle marks), and C) 1.0 mm (square marks). Each panel shows spectra simulated from dilutions of IL resulting in volume particle concentrations of [0.455, 0.568, 0.908, 1.135, 1.476, 2.951, 4.540]% that are indicated by colors [blue, red, green, yellow, magenta, cyan, and black], respectively. Middle column shows spectra returned by 3 selected source-detector separations in D) 4.54% and E) 0.454% phantoms, with the spectra normalized at 400 nm for comparative purposes. Right hand column shows the average number of scattering events experienced by photons at discrete wavelengths for spectra in F) 4.54% and G) 0.454% phantoms.
shows simulated reflectance measurements in IL optical phantoms performed with separate source and detector fibers. Here, panels (A), (B), and (C) contain spectra measured in a dilution series of IL phantoms, in the range [0.454–5.675]%, with each panel showing data obtained by a source-detector separation from the series ρ = [0.2, 0.4, 2.0] mm. Initial inspection of these data show a complicated dependence of RSDN(λ) on the phantom ILp. For adjacent source-detector fibers (ρ = 0.2 mm), an increase in ILp results in an increased reflectance intensity across the entire spectrum. This is not the case for source detectors with large separation (ρ = 2.0 mm), as increases in ILp from 0.4 to 1.0% result in increased RSDN, but increases in ILp from 2 to 5% result in decreased RSDN; this nonlinear dependence of RSDN on μs is described by diffusion theory and has been characterized in detail previously [18

18. A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express 18(6), 5580–5594 (2010). [CrossRef] [PubMed]

]. In order to understand the influence of scattering properties on the spectral response, we first compare spectra measured in the same phantom with different ρ. Figure 5 panels (D) and (E) show reflectance spectra measured at 3 different source detector separations in phantoms with ILp of 4.54% and 0.454%. The panels (F) and (G) show the average number of scattering events corresponding to discrete wavelengths in the spectra plotted on panels (D) and (E), respectively. The normalized spectra from the 4.54% ILp phantom show decreases in RSDN(λ) vs. wavelength for the small fiber separations (ρ = [0.2, 0.4] mm), but an increase of RSDN(λ) vs. wavelength for the large ρ (2.0 mm). The latter spectrum can be described by increases in μs vs. wavelength increasingly attenuating the collected reflectance intensity; therefore RSDN(λ) follows the inverse trend of μs(λ) vs. wavelength over the sampled wavelength range. Inspection of the scattering data for these spectra in panel (F) show that these measurements sample diffuse light, and are independent of PF. Figure 5 panel (E) shows normalized reflectance spectra measured in the 0.454% ILp phantom at different ρ. These data show a transition from RSDN(λ) monotonically decreasing vs. wavelength (for ρ = 2.0 mm) to biphasic behavior (for ρ = 0.2). Inspection of the number of scattering events experienced by collected photons in panel (G), shows a transition from sampling multiply scattered light in the diffuse regime (for ρ = 2.0 mm) to the sampling of fewer scattering events in the semi-diffuse regime (for ρ = 0.2 mm). These observations are consistent with the concept that measurements close to the source are more likely to be sensitive to the frequency of large angle backscatter events, and therefore the collected spectrum is influenced by PF-effects.

Figure 6
Fig. 6 Relationship between reflectance intensity returned by simulations of separate source-detector geometries and scattering properties in IL phantoms. Left hand column shows reflectance intensities vs. reduced scattering coefficient for source-detector separations of A) 0.2, B) 0.4, and C) 2.0 mm. Panel D) shows reflectance intensities vs. dimensionless reduced scattering for all measured separations. In this plot color indicates different wavelengths with [400, 500, 600, 700, 800] nm indicated by [blue, green yellow, black, red], respectively. Vertical dashed lines indicate the empirically identified threshold for observed PF-sensitivity of the reflectance at small dimensionless scattering values.
shows analysis of the relationship between RSDN and μs for separate source detector devices. Panels (A), (B), and (C) show RSDN vs. μs for measurements of phantoms with a wide range of ILp, with each panel showing measurements from a device with ρ = [0.2, 0.4, 2.0] mm. RSDN measurements close to the source (ρ = 0.2 and 0.4 mm) show a sensitivity to PF effects for small μs values; this is characterized by the non-unique relationship between RSDN and μs in the low scattering region. For ρ = 0.2 and 0.4 mm devices, as μs increases the RSDN shows less stratification due to PF-effects and the data transition to PF-insensitivity for large μs values; this transition follows the shift from sampling predominantly in the semi- diffuse regime to the diffuse regime as scattering increases. The data for the large source detector separation of ρ = 2.0 mm shows a distinct nonlinear dependence on μs, with the RSDN  vs. μs showing a monotonically increasing region that transitions through a peak into a monotonically decreasing region; this transition occurs for measurements sampling diffuse light that are independent of PF effects. Inspection of the reflectance data measured at different ρ shows an underlying relationship that is identified by conversion of the x-axis to the dimensionless reduced scattering coefficient, here given as μsρ, and conversion of the y-axis to RSDNρ2. Figure 6 panel (D) contains measurements from all investigated source-detector separationsρ = [0.2, 0.4, 0.6, 1.0, 2.0] mm in all simulated IL phantoms ILp = [0.454-5.675] %. These data show that RSDNρ2 is influenced similarly by μsρ for different ρ.

Inspection of these data showed that for μsρ>0.5, RSDN showed less than 10% variation about the mean value, and are therefore considered independent of PF influences at different wavelengths. This threshold was used to identify the smallest μs that could be sampled independent of PF for each ρ. For separate source detectors of ρ = [0.2, 0.4, 2.0] mm, the lower bound of μs was estimated as [2.5, 1.25, 0.25] mm−1, respectively. These thresholds are included as vertical dashed lines on plots in Fig. 6 to allow visualization of scattering regions influenced by PF and independent of PF.

4. Discussion

Tissue simulating optical phantoms are commonly used for two purposes: 1) characterization of observed reflectance response to controlled optical properties within the phantom, and 2) calibration of the wavelength-specific reflectance device response to allow system independent interpretation of measurements made in samples with uncontrolled optical properties. The results presented in this study have implications for both of these uses. Device characterization studies may seek to establish or validate a relationship between observed reflectance and μs [16

16. M. Johns, C. A. Giller, D. C. German, and H. Liu, “Determination of reduced scattering coefficient of biological tissue from a needle-like probe,” Opt. Express 13(13), 4828–4842 (2005). [CrossRef] [PubMed]

18

18. A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express 18(6), 5580–5594 (2010). [CrossRef] [PubMed]

]. However, the data presented in this study show that scattering PF can profoundly influence observed relationships between reflectance intensity and μs. The data in Figs. 4 and 6 show that for reflectance measurements that sample dimensionless reduced scattering coefficients below empirically identified threshold values (μsdf=10 for single fiber devices and μsρ=0.5 for separate source detector devices) the collected reflectance intensities are sensitive to PF-effects. Reflectance measurements performed below these thresholds collect a substantial component of light that has undergone few, or single, scattering events, making the probability of collecting light in that regime (at least somewhat) dependent on the backscattering features of the scattering PF. These data indicate that a proportionality established between reflectance intensity and μs in IL at a single wavelength will not hold at other wavelengths. Moreover, proportionalities are not directly extensible to another scattering medium that may contain an unknown wavelength-dependent PF, such as tissue.

IL optical phantoms are also commonly used for system calibration purposes [10

10. B. W. Pogue and M. S. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. 11(4), 041102 (2006). [CrossRef] [PubMed]

]. While this approach can be valid, care must be taken to consider influences of the PF. As shown in Figs. 3 and 5, spectral remission features can depend strongly on the IL dilution of the phantom. It is possible to account for these features by characterizing the response of the investigated device to the moments of the PF. This can be investigated either by experimental measurements in another scattering medium with a controlled wavelength-dependent PF, such as a phantom constructed with polystyrene beads [42

42. B. Gélébart, E. Tinet, J. Tualle, and S. Avrillier, “Phase function simulation in tissue phantoms: a fractal approach,” Pure Appl. Opt. 5(4), 377–388 (1996). [CrossRef]

], or simulation, where variation of PF can be completely controlled. The experimental data for single fiber reflectance spectra in this study were calibrated with measurements in IL, by using a Monte Carlo analysis to convert the measured reflectance spectra to an absolute scale (in units of % of incident photons) [35

35. S. C. Kanick, U. A. Gamm, M. Schouten, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence,” Biomed. Opt. Express 2(6), 1687–1702 (2011). [CrossRef] [PubMed]

], a conversion that accounts for the wavelength-dependent PF influence. Such a calibration becomes independent of ILp. This approach to spectral analysis requires sufficient information to estimate PF effects; such information could be provided by spectral information measured at an additional length scale such as with multiple fiber diameters [34

34. S. C. Kanick, U. A. Gamm, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Method to quantitatively estimate wavelength-dependent scattering properties from multidiameter single fiber reflectance spectra measured in a turbid medium,” Opt. Lett. 36(15), 2997–2999 (2011). [CrossRef] [PubMed]

,35

35. S. C. Kanick, U. A. Gamm, M. Schouten, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence,” Biomed. Opt. Express 2(6), 1687–1702 (2011). [CrossRef] [PubMed]

,41

41. U. A. Gamm, S. C. Kanick, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of tissue scattering properties using multi-diameter single fiber reflectance spectroscopy: in silico sensitivity analysis,” Biomed. Opt. Express 2(11), 3150–3166 (2011). [CrossRef] [PubMed]

] or at multiple distances from the source [14

14. P. Thueler, I. Charvet, F. Bevilacqua, M. St. Ghislain, G. Ory, P. Marquet, P. Meda, B. Vermeulen, and C. Depeursinge, “In vivo endoscopic tissue diagnostics based on spectroscopic absorption, scattering, and phase function properties,” J. Biomed. Opt. 8(3), 495–503 (2003). [CrossRef] [PubMed]

,33

33. F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, and C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38(22), 4939–4950 (1999). [CrossRef] [PubMed]

], or spectral information measured with an angular resolution [43

43. J. Pyhtila, R. Graf, and A. Wax, “Determining nuclear morphology using an improved angle-resolved low coherence interferometry system,” Opt. Express 11(25), 3473–3484 (2003). [CrossRef] [PubMed]

,44

44. Y. L. Kim, Y. Liu, R. K. Wali, H. K. Roy, M. J. Goldberg, A. K. Kromin, K. Chen, and V. Backman, “Simultaneous measurement of angular and spectral properties of light scattering for characterization of tissue microarchitecture and its alteration in early precancer,” IEEE J. Sel. Top. Quantum Electron. 9(2), 243–256 (2003). [CrossRef]

]. The use of IL as a calibration phantom without correction for PF-effects may introduce a substantial bias into quantitative estimates of scattering parameters, especially if applied to measurements in a sample of unknown optical properties, such as tissue.

This study identified an interesting difference in the relationship between reflectance intensity and μs for device geometries that utilize a single fiber as a source and detector compared with a device that utilizes separate source and detector fibers. Reflectance intensity collected by single fiber devices shows a monotonically increasing response to increases in μs, as displayed in Fig. 4. In contrast, reflectance intensity collected by separate source detectors shows a nonlinear response that increases or decreases based on μsρ, as shown in Fig. 6. These limiting behaviors can be intuitively explained. The single fiber geometry allows collection of light that has scattered an infinitesimally small distance into the medium prior to collection. Therefore, in the limit of highly scattering media, the single fiber reflectance device is no less likely to collect light in response to increased μs. In contrast, the collection geometry with separate source and detector fibers has a geometrical minimum path that light must travel within the medium prior to collection. Therefore, in the limit of highly scattering media, the collected signal will be attenuated in response to increases in μs. These differences in the required light path travelled by light collected by either device leads to different threshold sensitivities to PF, which empirically are μsdf=10 and μsρ=0.5 for each device-type, respectively. This means that for single fiber measurements, the transport length, defined by the inverse of the reduced scattering coefficient, must be an order of magnitude greater than the collection length to be independent of PF effects. A device with separate source detectors is (in general) less sensitive to PF, with collection at locations up to half of the transport length showing insensitivity to PF. This threshold is expected to be dependent on the source and detector fiber diameters, which were fixed at 0.2 mm in the current study; the exact value of the threshold may vary for different fibers sizes. It should be noted that in IL phantoms constructed to mimic the range of μs expected in tissue, in the range of [0.5-2.0] mm−1 [37

37. W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990). [CrossRef]

], devices that collect with ρ as large as 1 mm can be influenced by PF effects. Moreover, inspection of the data in Figs. 5 and 6 show that measurements made in such phantoms with adjacent source and detector fibers (ρ=0.2 mm) may contain a spectral signature that shows little to no wavelength-dependence on μs.

While this study specifically investigates the spectral response of specific reflectance geometries, the findings are important for other measurement devices as well. This study characterized the response over a set range of geometrical perturbations to single fiber size and source-detector distance. This study does not perform a comprehensive evaluation of all possible geometrical configurations of fiber probes (e.g. all possible source and detector fiber sizes, inter-fiber distances, or numerical apertures). The results of this study are applicable to reflectance spectra measured by any probe configuration: the sampled transport regime will determine sensitivity to wavelength-dependent changes in PF. The results are also important for devices that sample reflectance at a single wavelength. In this case, care must be taken to correctly interpret the collected signal to avoid mischaracterizing the observed reflectance intensity as influenced exclusively by μs. For example, the use of raw reflectance intensity at a single wavelength to correct fluorescence for the influence of optical properties will be problematic considering that μs and PF will influence reflectance and fluorescence intensities differently [9

9. S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Semi-empirical model of the effect of scattering on single fiber fluorescence intensity measured on a turbid medium,” Biomed. Opt. Express 3(1), 137–152 (2012). [CrossRef] [PubMed]

]. Ongoing work will characterize the PF-specific influences of fluorescence correction algorithms.

5 Conclusions

This study investigates the influence of the wavelength-dependent scattering properties μs and PF on spectral features of reflectance collected near the source location in IL optical phantoms. Experiments and simulations are used to characterize features in the 400-800 nm wavelength range from IL optical phantoms with ILp in the range 0.454-5.675%, which relates to a wide range of μs = [0.3–8] mm−1. Data were measured or simulated for reflectance geometries that 1) utilized a single fiber optic for both source and detector with the df = [0.2–1.0] mm, and 2) separate source and detector fibers with core to core separations in the range ρ = [0.2–2.0] mm. Results for both collection configurations showed a dependence of spectral scattering features on the transport regime sampled during measurement. PF-dependent effects were observed in reflectance spectra measured below a dimensionless threshold of μsdf=10 (i.e. ten transport lengths) for single fiber devices and μsρ=0.5 (i.e. half a transport length) for separate source detector devices. The results show the need to consider the influence of PF when using measurements of IL to either characterize or calibrate a reflectance device that collects light close to the source.

Acknowledgments

This work has been funded by NIH grants PO1 CA084203 and PO1 CA080139.

References and Links

1.

A. Amelink, O. P. Kaspers, H. J. C. M. Sterenborg, J. E. van der Wal, J. L. N. Roodenburg, and M. J. H. Witjes, “Non-invasive measurement of the morphology and physiology of oral mucosa by use of optical spectroscopy,” Oral Oncol. 44(1), 65–71 (2008). [CrossRef] [PubMed]

2.

J. Q. Brown, K. Vishwanath, G. M. Palmer, and N. Ramanujam, “Advances in quantitative UV-visible spectroscopy for clinical and pre-clinical application in cancer,” Curr. Opin. Biotechnol. 20(1), 119–131 (2009). [CrossRef] [PubMed]

3.

J. R. Mourant, A. H. Hielscher, A. A. Eick, T. M. Johnson, and J. P. Freyer, “Evidence of intrinsic differences in the light scattering properties of tumorigenic and nontumorigenic cells,” Cancer 84(6), 366–374 (1998). [CrossRef] [PubMed]

4.

K. Sokolov, M. Follen, and R. Richards-Kortum, “Optical spectroscopy for detection of neoplasia,” Curr. Opin. Chem. Biol. 6(5), 651–658 (2002). [CrossRef] [PubMed]

5.

I. J. Bigio and S. G. Bown, “Spectroscopic sensing of cancer and cancer therapy: current status of translational research,” Cancer Biol. Ther. 3(3), 259–267 (2004). [CrossRef] [PubMed]

6.

P. B. Garcia-Allende, V. Krishnaswamy, P. J. Hoopes, K. S. Samkoe, O. M. Conde, and B. W. Pogue, “Automated identification of tumor microscopic morphology based on macroscopically measured scatter signatures,” J. Biomed. Opt. 14(3), 034034 (2009). [CrossRef] [PubMed]

7.

R. Weersink, M. S. Patterson, K. Diamond, S. Silver, and N. Padgett, “Noninvasive measurement of fluorophore concentration in turbid media with a simple fluorescence /reflectance ratio technique,” Appl. Opt. 40(34), 6389–6395 (2001). [CrossRef] [PubMed]

8.

M. G. Müller, I. Georgakoudi, Q. Zhang, J. Wu, and M. S. Feld, “Intrinsic fluorescence spectroscopy in turbid media: disentangling effects of scattering and absorption,” Appl. Opt. 40(25), 4633–4646 (2001). [CrossRef] [PubMed]

9.

S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Semi-empirical model of the effect of scattering on single fiber fluorescence intensity measured on a turbid medium,” Biomed. Opt. Express 3(1), 137–152 (2012). [CrossRef] [PubMed]

10.

B. W. Pogue and M. S. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. 11(4), 041102 (2006). [CrossRef] [PubMed]

11.

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23(Suppl 1), S275–S288 (2004). [CrossRef] [PubMed]

12.

T. O. McBride, B. W. Pogue, E. D. Gerety, S. B. Poplack, U. L. Osterberg, and K. D. Paulsen, “Spectroscopic diffuse optical tomography for the quantitative assessment of hemoglobin concentration and oxygen saturation in breast tissue,” Appl. Opt. 38(25), 5480–5490 (1999). [CrossRef] [PubMed]

13.

J. R. Mourant, T. Fuselier, J. Boyer, T. M. Johnson, and I. J. Bigio, “Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms,” Appl. Opt. 36(4), 949–957 (1997). [CrossRef] [PubMed]

14.

P. Thueler, I. Charvet, F. Bevilacqua, M. St. Ghislain, G. Ory, P. Marquet, P. Meda, B. Vermeulen, and C. Depeursinge, “In vivo endoscopic tissue diagnostics based on spectroscopic absorption, scattering, and phase function properties,” J. Biomed. Opt. 8(3), 495–503 (2003). [CrossRef] [PubMed]

15.

A. Amelink and H. J. C. M. Sterenborg, “Measurement of the local optical properties of turbid media by differential path-length spectroscopy,” Appl. Opt. 43(15), 3048–3054 (2004). [CrossRef] [PubMed]

16.

M. Johns, C. A. Giller, D. C. German, and H. Liu, “Determination of reduced scattering coefficient of biological tissue from a needle-like probe,” Opt. Express 13(13), 4828–4842 (2005). [CrossRef] [PubMed]

17.

R. Reif, O. A’Amar, and I. J. Bigio, “Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media,” Appl. Opt. 46(29), 7317–7328 (2007). [CrossRef] [PubMed]

18.

A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express 18(6), 5580–5594 (2010). [CrossRef] [PubMed]

19.

V. Krishnaswamy, A. M. Laughney, K. D. Paulsen, and B. W. Pogue, “Dark-field scanning in situ spectroscopy platform for broadband imaging of resected tissue,” Opt. Lett. 36(10), 1911–1913 (2011). [CrossRef] [PubMed]

20.

P. D. Ninni, F. Martelli, and G. Zaccanti, “Intralipid: towards a diffusive reference standard for optical tissue phantoms,” Phys. Med. Biol. 56(2), N21–N28 (2011). [CrossRef] [PubMed]

21.

H. J. van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. van Gemert, “Light scattering in Intralipid-10% in the wavelength range of 400-1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991). [CrossRef] [PubMed]

22.

G. Zaccanti, S. Del Bianco, and F. Martelli, “Measurements of optical properties of high-density media,” Appl. Opt. 42(19), 4023–4030 (2003). [CrossRef] [PubMed]

23.

F. Martelli and G. Zaccanti, “Calibration of scattering and absorption properties of a liquid diffusive medium at NIR wavelengths. CW method,” Opt. Express 15(2), 486–500 (2007). [CrossRef] [PubMed]

24.

R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express 16(8), 5907–5925 (2008). [CrossRef] [PubMed]

25.

T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992). [CrossRef] [PubMed]

26.

S. L. Jacques and B. W. Pogue, “Tutorial on diffuse light transport,” J. Biomed. Opt. 13(4), 041302 (2008). [CrossRef] [PubMed]

27.

J. R. Mourant, J. Boyer, A. H. Hielscher, and I. J. Bigio, “Influence of the scattering phase function on light transport measurements in turbid media performed with small source-detector separations,” Opt. Lett. 21(7), 546–548 (1996). [CrossRef] [PubMed]

28.

F. Bevilacqua and C. Depeursinge, “Monte Carlo study of diffuse reflectance at source–detector separations close to one transport mean free path,” J. Opt. Soc. Am. A 16(12), 2935–2945 (1999). [CrossRef]

29.

A. Kienle, F. K. Forster, and R. Hibst, “Influence of the phase function on determination of the optical properties of biological tissue by spatially resolved reflectance,” Opt. Lett. 26(20), 1571–1573 (2001). [CrossRef] [PubMed]

30.

I. S. Saidi, S. L. Jacques, and F. K. Tittel, “Mie and Rayleigh modeling of visible-light scattering in neonatal skin,” Appl. Opt. 34(31), 7410–7418 (1995). [CrossRef] [PubMed]

31.

P. R. Bargo, S. A. Prahl, T. T. Goodell, R. A. Sleven, G. Koval, G. Blair, and S. L. Jacques, “In vivo determination of optical properties of normal and tumor tissue with white light reflectance and an empirical light transport model during endoscopy,” J. Biomed. Opt. 10(3), 034018 (2005). [CrossRef] [PubMed]

32.

E. L. Hull and T. H. Foster, “Steady-state reflectance spectroscopy in the P3 approximation,” J. Opt. Soc. Am. A 18(3), 584–599 (2001). [CrossRef]

33.

F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, and C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38(22), 4939–4950 (1999). [CrossRef] [PubMed]

34.

S. C. Kanick, U. A. Gamm, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Method to quantitatively estimate wavelength-dependent scattering properties from multidiameter single fiber reflectance spectra measured in a turbid medium,” Opt. Lett. 36(15), 2997–2999 (2011). [CrossRef] [PubMed]

35.

S. C. Kanick, U. A. Gamm, M. Schouten, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence,” Biomed. Opt. Express 2(6), 1687–1702 (2011). [CrossRef] [PubMed]

36.

S. C. Kanick, H. J. C. M. Sterenborg, and A. Amelink, “Empirical model of the photon path length for a single fiber reflectance spectroscopy device,” Opt. Express 17(2), 860–871 (2009). [CrossRef] [PubMed]

37.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990). [CrossRef]

38.

L. Wang, S. L. Jacques, and L. Zheng, “MCML--Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995). [CrossRef] [PubMed]

39.

S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Monte Carlo analysis of single fiber reflectance spectroscopy: photon path length and sampling depth,” Phys. Med. Biol. 54(22), 6991–7008 (2009). [CrossRef] [PubMed]

40.

B. W. Pogue and G. Burke, “Fiber-optic bundle design for quantitative fluorescence measurement from tissue,” Appl. Opt. 37(31), 7429–7436 (1998). [CrossRef] [PubMed]

41.

U. A. Gamm, S. C. Kanick, H. J. C. M. Sterenborg, D. J. Robinson, and A. Amelink, “Measurement of tissue scattering properties using multi-diameter single fiber reflectance spectroscopy: in silico sensitivity analysis,” Biomed. Opt. Express 2(11), 3150–3166 (2011). [CrossRef] [PubMed]

42.

B. Gélébart, E. Tinet, J. Tualle, and S. Avrillier, “Phase function simulation in tissue phantoms: a fractal approach,” Pure Appl. Opt. 5(4), 377–388 (1996). [CrossRef]

43.

J. Pyhtila, R. Graf, and A. Wax, “Determining nuclear morphology using an improved angle-resolved low coherence interferometry system,” Opt. Express 11(25), 3473–3484 (2003). [CrossRef] [PubMed]

44.

Y. L. Kim, Y. Liu, R. K. Wali, H. K. Roy, M. J. Goldberg, A. K. Kromin, K. Chen, and V. Backman, “Simultaneous measurement of angular and spectral properties of light scattering for characterization of tissue microarchitecture and its alteration in early precancer,” IEEE J. Sel. Top. Quantum Electron. 9(2), 243–256 (2003). [CrossRef]

OCIS Codes
(170.3660) Medical optics and biotechnology : Light propagation in tissues
(170.6510) Medical optics and biotechnology : Spectroscopy, tissue diagnostics
(170.7050) Medical optics and biotechnology : Turbid media

ToC Category:
Calibration, Validation and Phantom Studies

History
Original Manuscript: March 2, 2012
Revised Manuscript: April 12, 2012
Manuscript Accepted: April 20, 2012
Published: April 24, 2012

Virtual Issues
Phantoms for the Performance Evaluation and Validation of Optical Medical Imaging Devices (2012) Biomedical Optics Express

Citation
S. C. Kanick, V. Krishnaswamy, U. A. Gamm, H. J. C. M. Sterenborg, D. J. Robinson, A. Amelink, and B. W. Pogue, "Scattering phase function spectrum makes reflectance spectrum measured from Intralipid phantoms and tissue sensitive to the device detection geometry," Biomed. Opt. Express 3, 1086-1100 (2012)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-3-5-1086


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References

  1. A. Amelink, O. P. Kaspers, H. J. C. M. Sterenborg, J. E. van der Wal, J. L. N. Roodenburg, and M. J. H. Witjes, “Non-invasive measurement of the morphology and physiology of oral mucosa by use of optical spectroscopy,” Oral Oncol.44(1), 65–71 (2008). [CrossRef] [PubMed]
  2. J. Q. Brown, K. Vishwanath, G. M. Palmer, and N. Ramanujam, “Advances in quantitative UV-visible spectroscopy for clinical and pre-clinical application in cancer,” Curr. Opin. Biotechnol.20(1), 119–131 (2009). [CrossRef] [PubMed]
  3. J. R. Mourant, A. H. Hielscher, A. A. Eick, T. M. Johnson, and J. P. Freyer, “Evidence of intrinsic differences in the light scattering properties of tumorigenic and nontumorigenic cells,” Cancer84(6), 366–374 (1998). [CrossRef] [PubMed]
  4. K. Sokolov, M. Follen, and R. Richards-Kortum, “Optical spectroscopy for detection of neoplasia,” Curr. Opin. Chem. Biol.6(5), 651–658 (2002). [CrossRef] [PubMed]
  5. I. J. Bigio and S. G. Bown, “Spectroscopic sensing of cancer and cancer therapy: current status of translational research,” Cancer Biol. Ther.3(3), 259–267 (2004). [CrossRef] [PubMed]
  6. P. B. Garcia-Allende, V. Krishnaswamy, P. J. Hoopes, K. S. Samkoe, O. M. Conde, and B. W. Pogue, “Automated identification of tumor microscopic morphology based on macroscopically measured scatter signatures,” J. Biomed. Opt.14(3), 034034 (2009). [CrossRef] [PubMed]
  7. R. Weersink, M. S. Patterson, K. Diamond, S. Silver, and N. Padgett, “Noninvasive measurement of fluorophore concentration in turbid media with a simple fluorescence /reflectance ratio technique,” Appl. Opt.40(34), 6389–6395 (2001). [CrossRef] [PubMed]
  8. M. G. Müller, I. Georgakoudi, Q. Zhang, J. Wu, and M. S. Feld, “Intrinsic fluorescence spectroscopy in turbid media: disentangling effects of scattering and absorption,” Appl. Opt.40(25), 4633–4646 (2001). [CrossRef] [PubMed]
  9. S. C. Kanick, D. J. Robinson, H. J. C. M. Sterenborg, and A. Amelink, “Semi-empirical model of the effect of scattering on single fiber fluorescence intensity measured on a turbid medium,” Biomed. Opt. Express3(1), 137–152 (2012). [CrossRef] [PubMed]
  10. B. W. Pogue and M. S. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt.11(4), 041102 (2006). [CrossRef] [PubMed]
  11. D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage23(Suppl 1), S275–S288 (2004). [CrossRef] [PubMed]
  12. T. O. McBride, B. W. Pogue, E. D. Gerety, S. B. Poplack, U. L. Osterberg, and K. D. Paulsen, “Spectroscopic diffuse optical tomography for the quantitative assessment of hemoglobin concentration and oxygen saturation in breast tissue,” Appl. Opt.38(25), 5480–5490 (1999). [CrossRef] [PubMed]
  13. J. R. Mourant, T. Fuselier, J. Boyer, T. M. Johnson, and I. J. Bigio, “Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms,” Appl. Opt.36(4), 949–957 (1997). [CrossRef] [PubMed]
  14. P. Thueler, I. Charvet, F. Bevilacqua, M. St. Ghislain, G. Ory, P. Marquet, P. Meda, B. Vermeulen, and C. Depeursinge, “In vivo endoscopic tissue diagnostics based on spectroscopic absorption, scattering, and phase function properties,” J. Biomed. Opt.8(3), 495–503 (2003). [CrossRef] [PubMed]
  15. A. Amelink and H. J. C. M. Sterenborg, “Measurement of the local optical properties of turbid media by differential path-length spectroscopy,” Appl. Opt.43(15), 3048–3054 (2004). [CrossRef] [PubMed]
  16. M. Johns, C. A. Giller, D. C. German, and H. Liu, “Determination of reduced scattering coefficient of biological tissue from a needle-like probe,” Opt. Express13(13), 4828–4842 (2005). [CrossRef] [PubMed]
  17. R. Reif, O. A’Amar, and I. J. Bigio, “Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media,” Appl. Opt.46(29), 7317–7328 (2007). [CrossRef] [PubMed]
  18. A. Kim, M. Roy, F. Dadani, and B. C. Wilson, “A fiberoptic reflectance probe with multiple source-collector separations to increase the dynamic range of derived tissue optical absorption and scattering coefficients,” Opt. Express18(6), 5580–5594 (2010). [CrossRef] [PubMed]
  19. V. Krishnaswamy, A. M. Laughney, K. D. Paulsen, and B. W. Pogue, “Dark-field scanning in situ spectroscopy platform for broadband imaging of resected tissue,” Opt. Lett.36(10), 1911–1913 (2011). [CrossRef] [PubMed]
  20. P. D. Ninni, F. Martelli, and G. Zaccanti, “Intralipid: towards a diffusive reference standard for optical tissue phantoms,” Phys. Med. Biol.56(2), N21–N28 (2011). [CrossRef] [PubMed]
  21. H. J. van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. van Gemert, “Light scattering in Intralipid-10% in the wavelength range of 400-1100 nm,” Appl. Opt.30(31), 4507–4514 (1991). [CrossRef] [PubMed]
  22. G. Zaccanti, S. Del Bianco, and F. Martelli, “Measurements of optical properties of high-density media,” Appl. Opt.42(19), 4023–4030 (2003). [CrossRef] [PubMed]
  23. F. Martelli and G. Zaccanti, “Calibration of scattering and absorption properties of a liquid diffusive medium at NIR wavelengths. CW method,” Opt. Express15(2), 486–500 (2007). [CrossRef] [PubMed]
  24. R. Michels, F. Foschum, and A. Kienle, “Optical properties of fat emulsions,” Opt. Express16(8), 5907–5925 (2008). [CrossRef] [PubMed]
  25. T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys.19(4), 879–888 (1992). [CrossRef] [PubMed]
  26. S. L. Jacques and B. W. Pogue, “Tutorial on diffuse light transport,” J. Biomed. Opt.13(4), 041302 (2008). [CrossRef] [PubMed]
  27. J. R. Mourant, J. Boyer, A. H. Hielscher, and I. J. Bigio, “Influence of the scattering phase function on light transport measurements in turbid media performed with small source-detector separations,” Opt. Lett.21(7), 546–548 (1996). [CrossRef] [PubMed]
  28. F. Bevilacqua and C. Depeursinge, “Monte Carlo study of diffuse reflectance at source–detector separations close to one transport mean free path,” J. Opt. Soc. Am. A16(12), 2935–2945 (1999). [CrossRef]
  29. A. Kienle, F. K. Forster, and R. Hibst, “Influence of the phase function on determination of the optical properties of biological tissue by spatially resolved reflectance,” Opt. Lett.26(20), 1571–1573 (2001). [CrossRef] [PubMed]
  30. I. S. Saidi, S. L. Jacques, and F. K. Tittel, “Mie and Rayleigh modeling of visible-light scattering in neonatal skin,” Appl. Opt.34(31), 7410–7418 (1995). [CrossRef] [PubMed]
  31. P. R. Bargo, S. A. Prahl, T. T. Goodell, R. A. Sleven, G. Koval, G. Blair, and S. L. Jacques, “In vivo determination of optical properties of normal and tumor tissue with white light reflectance and an empirical light transport model during endoscopy,” J. Biomed. Opt.10(3), 034018 (2005). [CrossRef] [PubMed]
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