Open Access
3 April 2017 Short wavelength infrared optical windows for evaluation of benign and malignant tissues
Author Affiliations +
Abstract
There are three short wavelength infrared (SWIR) optical windows outside the conventionally used first near-infrared (NIR) window (650 to 950 nm). They occur in the 1000- to 2500-nm range and may be considered second, third, and fourth NIR windows. The second (1100 to 1350 nm) and third windows (1600 to 1870 nm) are now being explored through label-free linear and multiphoton imaging. The fourth window (2100 to 2350 nm) has been mostly ignored because of water absorption and the absence of sensitive detectors and ultrafast lasers. With the advent of new technology, use of window IV is now possible. Absorption and scattering properties of light through breast and prostate cancer, bone, lipids, and intralipid solutions at these windows were investigated. We found that breast and prostate cancer and bone have longer total attenuation lengths at NIR windows III and IV, whereas fatty tissues and intralipid have longest lengths at windows II and III. Since collagen is the major chromophore at 2100 and 2350 nm, window IV could be especially valuable in evaluating cancers and boney tissues, whereas windows II and III may be more useful for tissues with high lipid content. SWIR windows may be utilized as additional optical tools for the evaluation of collagen in tissues.

1.

Introduction

Near-infrared (NIR) spectroscopy (650 to 950 nm) has become an important modality for imaging and medical diagnostics, with applications that include cancer detection, assessing changes in tumors, measurement of blood flow to the brain, and evaluation of patients with Paget’s disease of bone.17 Short wavelength infrared (SWIR) spectroscopy, with wavelengths from 1000 to 2500 nm, may offer better penetration into turbid media, while minimizing radiation exposure. Biomolecules in tissue, such as oxyhemoglobin, hemoglobin, and water, have distinct absorption spectral patterns, thus they give optical fingerprints. The SWIR optical windows, which correspond to second, third, and fourth windows in the 1000- to 2500-nm wavelength range, occur between water absorption peak maxima and can reveal the presence of lipids, fats, glucose, and collagen, as well as of many other molecules, due to their distinct optical absorption spectral profiles.

Water absorption, as well as light scattering, limits the information collected by a detector. Rayleigh scattering is known to decrease with longer wavelength, varying as 1/λ4. Mie scattering will also decrease [varying as 1/λn for n1, where n varies with particle size for μs, not for reduced scattering coefficient μs=μs(1g)]. Details on Mie scattering are available elsewhere.8 Because of this, the utilization of SWIR wavelengths could present the opportunity to study chromophores beyond the conventional, first, NIR window.911 Utilizing SWIR wavelengths can result in decreased scattering, might allow for less blurring, and result in better penetration into the tissue media; therefore, better contrast images might be obtained. Recently, NIR windows II (located between water peak maxima at 970 and 1444 nm) and III (located between water peak maxima of 1444 and 1950 nm) have been used for medical applications, such as in vivo imaging of small animals and the detection and monitoring of intestinal ischemia in vivo in a porcine model.913 Window II occurs between 1100 and 1350 nm and window III between 1600 and 1870 nm. Window III has been referred to as the “golden window.”12

A fourth NIR window, occurring between 2100 and 2350 nm (shown in Fig. 1), has been mostly ignored because of greater absorption by water at these wavelengths. However, Yoo et al. have shown that a small amount of absorption can limit the detection of diffusive photons, which may cause a blurring of images, and can highlight the ballistic and snake photons, which are responsible for producing clearer images.14 Indeed, water absorption is less at shorter NIR wavelengths, but, due to the inverse wavelength dependence, scattering is minimal; this may result in a balance between absorption and scattering events. The fourth NIR window has also been discounted due to a lack of sensitive detectors. The advent of new photodetectors and laser sources now makes window IV a viable spectral domain (Table 1). The photodetector of choice in window IV is InSb (either as single and array photodiodes). Ultrafast lasers that utilize wavelengths from window IV include the supercontinuum laser, with spectral range from 400 to 2500 nm, the Cr 2+:ZnSe/S lasers, and GaSb laser diodes.15,16 Femtosecond Cr2+-doped ZnS and ZnSe lasers can be used at wavelengths from 1800 to 3400 nm, with Kerr mode locking that can generate ultrashort (41 fs) pulses. Room-temperature Cr2+-based lasers can provide tens of Watts of power and ultrabroad tunability (1400  nm between 2 and 3.4  μm).16 GaSb laser diodes are available from 1800 to 3000 nm. Brolis semiconductors now offer 2100 and 2200 nm GaSb diode lasers for SWIR microscopes. In window III, the 200-fs laser from Calmar [called Bodega femtosecond optical parametric laser (FLOPA)] is available at 1700  nm. Recently, Sordillo et al. reported on the use of the fourth NIR window for the assessment of bone, at the 2016 SPIE Photonics West Conference.17 As an extension of our work, we have measured the absorbance and have calculated the total attenuation lengths from lipid or collagen rich tissues, including breast and prostate cancer, bone, lipids, and intralipid solutions, at the first NIR and SWIR windows. The molecules that absorb by excitation of combination vibrations in the SWIR are presented.

Fig. 1

(a) Optical density (O.D.) spectrum of water molecules in the NIR spectral range; (b) OD spectra of collagen and water at the first NIR and the three SWIR windows.11

JBO_22_4_045002_f001.png

Table 1

Ultrafast and continuous wave (CW) laser light sources for window III and IV.

TypeWavelength range (nm)Brand
Supercontinuum source400 to 2500 nmLeukos, NKT Photonics, Thorlabs
Er:YAG laser1645 nmIPG Photonics
“Bodega” femtosecond optical parametric laser (FLOPA)1700  nmCalmar
Cr2+:ZnSe/S CW lasers1800 to 3400 nmIPG Photonics
GaSb laser diode lasers1870 to 2230 nmDILAS
GaSb-based laser diodes1800 to 3000Brolis semiconductors

2.

Methods

The absorbance spectra from the samples were acquired using the UV–vis–NIR Cary 500 spectrophotometer (Varian, Inc., Palo Alto, California). The Cary 500 is a commercially available, research grade, spectrophotometer with a PbS detector, a deuterium arc UV lamp, and a tungsten halogen visible light. To produce a narrow band, nearly monochromatic, light beam, light from these sources is diffracted using a grating. This light is then allowed to hit the sample, which is placed at a fixed position in the sample compartment. Finally, optical density (OD) or percent transmission of light through the sample is recorded on the computer. These conditions were kept constant for all samples. The wavelength range was between 600 and 2500 nm, covering the first NIR and the SWIR ranges. Total attenuation lengths (lt) were measured in windows I (λ=750  nm), II (λ=1200  nm), III (λ=1700  nm), and IV (λ=2200  nm). A sample of cleaned human fibula was obtained from a cadaver and cut to 150  μm. 20% intralipid was diluted to concentrations of 0.5%, 1%, 1.5%, and 2%. Tissue samples were purchased from National Disease Research Interchange and Cooperative Human Tissue Network after approval by an institutional review board. The samples were neither fixed nor treated chemically. Samples were cut to thicknesses of 50, 100, and 200  μm.

3.

Theoretical Background

Light through turbid media is described by the trajectories of three components: diffusive, ballistic, and quasiballistic (snake) photons.8,18 When the media is thin, the decay of ballistic photons (Ib) is described by the differential equation:19

Eq. (1)

dIb/dz=μtIb
with the solution

Eq. (2)

Ib=I0exp(μtz),
where μt, the total attenuation coefficient, is defined as the sum of the absorption coefficient μa and the scattering coefficient μs(μt=μa+μs), I0 is the incident light (light entering the media), and z is the tissue thickness. Equation (2) is known as Beer–Lambert’s law.

For thicker media, the diffusive photons (Id) are governed by the diffusion equation, which can be approximated by19

Eq. (3)

2Idz2=3(μs+μa)μaId
with the solution

Eq. (4)

Id=  I0exp[(3μa(μs+μa)z],
where μs=μs(1g) is the reduced scattering coefficient, ltr=1/μs is defined as the transport mean-free path,20 and g=cosθ is the mean cosine of the scattering angle (anisotropy factor).21

When the solid angle δΩ is small, the total transmitted light intensity I can be written as the sum of the number of ballistic photons (Ib) and of a fraction of the diffusive photons (Id)22

Eq. (5)

I=Ib+(δΩ  4π)Id.
Substituting Eqs. (2) and (4) into Eq. (5) and dividing by I023 we obtain

Eq. (6)

II0=exp(μtz)+(δΩ  4π)exp  [(3μa(μs+μa)z].

Yoo et al. have studied photon transport through random media utilizing ultrafast laser pulses and time-resolved detection.14,24 The authors showed that for z/ltr<10, the diffusion approximation deviated monotonically from the measured scattered pulse, and that scattered photons arrived earlier than the diffusion approximation had predicted. Zhang et al. found that, at z/ltr3, there is a sharp transition from ballistic to diffusive behavior.25 The thickness zc where the ballistic and diffusive photons are equal is given as19

Eq. (7)

zc1μsμeffln(4πδΩ),
for μeff=3μa(μs+μa). When z<zc, the ballistic photons will govern over the diffusive ones; therefore, using tissue samples (<1  mm) will allow for better image quality.

4.

Results

The measured percent transmission intensities and corresponding OD through a sample of human fibula using the four windows are plotted in Figs. 2(a) and 2(b). From these plots, the total attenuation coefficient (μt) obtained from the bone sample is calculated using Beer–Lambert’s law

Eq. (8)

T=II0=exp[(μtz)].
The total attenuation length (lt) is the inverse of the total attenuation coefficients (μt) and is acquired by substituting μt=1/lt into the above equation

Eq. (9)

lt=z/ln(T).

Fig. 2

(a) Percent transmission (T) and (b) OD spectra from a bone sample.

JBO_22_4_045002_f002.png

Figures 3(a) and 3(b) show the spectrum of the total attenuation coefficients (μt) and the spectrum of total attenuation lengths (lt) from bone. Longest relative total attenuation lengths occur at wavelengths within the third and fourth windows. A salient feature is an oscillating structure about window IV. These spectra reveal small oscillations at wavelengths above 1800 nm, which are most likely due to the vibrational combination modes from collagen.

Fig. 3

(a) Total attenuation coefficients (μtotal) and (b) total attenuation lengths (ltotal).

JBO_22_4_045002_f003.png

Figure 4 shows the spectra obtained from different concentrations of intralipid solution. For 0.5% and 1% intralipid solution, longest total attenuation lengths occur at window II. For 1.5% and 2% intralipid solution, longest total attenuation lengths are seen at window III. For 20% intralipid, longest total attenuation lengths occur at the third and fourth windows. Similarly, longest total attenuation lengths for both prostate and breast tissues are seen at window III. The oscillation in absorption plots beyond 1800 nm is attributed to collagen and lipids [see Fig. 1(b)]. Table 2 shows lt for tissues with high collagen. Table 3 shows total attenuation lengths for chicken fat and for intralipid solution of different concentrations.

Fig. 4

lt for 0.5%, 1%, 1.5%, 2%, and 20% concentrations of intralipid solution.

JBO_22_4_045002_f004.png

Table 2

Total attenuation lengths from high collagen tissues at the first NIR and the SWIR optical windows.

Total attenuation lengths lt (μm)
SpecimenThickness (μm)IIIIIIIV
Bone1505892114114
Human prostate cancer100161168206209
200101159217213
Human breast cancer (patient 1)100169311438365
20066758686
Human breast cancer (patient 2)5023303333
1006699127132
20079105117101
Human breast cancer (patient 3)20039424032
20049515652
Human breast cancer (patient 4)20075838472
20051667361
200171184170176
Human breast cancer (patient 5)200167182214255
200143154173193
200737696119
Human breast cancer (patient 6)200102104133162
20013482012622607

Table 3

Total attenuation lengths of chicken fat and of solutions of intralipid at the first NIR and the SWIR optical windows.

Total attenuation lengths lt (μm)
Tissue detailsIIIIIIIV
Chicken fat200  μm thick (%)9011811799
Intralipid solution0.557012501046472
1.04091000979468
1.5237622797446
2.0198497709433
20147164323357

5.

Discussion

Limited studies have been done utilizing wavelengths in the SWIR range, especially wavelengths above 2000 nm. Using samples of human skin, Troy et al. have reported the absorption and reduced scattering coefficients obtained at wavelengths between 1000 and 2200 nm. However, at wavelengths from 1900 to 2050 nm, the coefficients were not calculated because of increased water absorption (peak at λ=1920  nm).26 These authors also determined that, for wavelengths less than 1800 nm, a 2% intralipid solution was an appropriate skin tissue phantom. For wavelengths greater than 2100 nm, a 2% to 4% intralipid solution would be an appropriate phantom. Zamora-Rojas et al. investigated porcine skin in the SWIR range from 1150 to 2250 nm.27 Due to a large water band, the authors could not obtain absorption coefficients in the spectral range from 1880 to 2040 nm but otherwise showed that scattering decreased with increasing SWIR wavelengths. Wang et al. looked at samples of human carotid atherosclerotic plaque at several SWIR regions (1130 to 1260 nm, 1620 to 1820 nm, and 2200 to 2330 nm). Ratios of lipid to protein were used to distinguish stable, vulnerable, and intermediate plaque.28

Bone has not been studied previously at wavelengths within window IV. The reduced scattering and absorption coefficients of temporal bones were studied at wavelengths of 635, 690, 780, and 830 nm, but the authors did not go beyond these wavelengths.29 Likewise, optical properties of the bones in the skull in the range from 650 to 950 nm were investigated, but the authors did not extend their studies to higher wavelengths.30 In another study, changes in bone density at wavelengths 520 to 960 nm were reported. Again, they did not reach wavelengths in the SWIR range.31 Pifferi et al. looked at the human calcaneus at different wavelengths between 650 and 1000 nm. They were able to estimate the concentration of key tissue constituents, such as bone mineral, water, lipids, oxy-, and deoxyhemoglobin in human calcaneus, using the absorption spectral profiles of these constituents. It was concluded that the amount of bone mineral matrix decreased in older patients while lipids increased.32 Others have studied cranial bones at wavelengths extending from 800 to 2000 nm. The absorption spectra showed major absorption peaks located at 978, 1192, 1745, and 1930 nm. These investigators felt the peaks were secondary to increased lipid content.33 Although the authors were able to reach wavelengths at the second and third NIR optical windows, they were not able to study window IV.

Numerous studies have utilized noninvasive, NIR, optical techniques to distinguish and to assess diseased versus healthy tissues. One study used light between 610 and 1040 nm to obtain the absorption spectra of benign and malignant breast tissues. Based on the absorption profiles of these tissues, it was found that the collagen and lipid content varied significantly among the patients. Women with highly adipose breasts were found to have relatively little collagen in their breasts, while relatively more collagen was found in women with very small breasts.34 Another group used light from the visible to the NIR range (500 to 1600 nm) to distinguish breast cancer, benign tumors, and normal tissues, by utilizing comparisons of the relative fractions of collagen, water, and fat. Average lipid volume (%) at areas of normal tissue was 80%, whereas it was only 10% for carcinoma in situ (a very early stage of cancer) and <5% for fibroadenoma or for carcinoma, whereas collagen volume was higher for carcinoma than for fibroadenoma or for adipose tissues.35 These results were consistent with those we have previously reported, which showed increased tryptophan emission in breast cancer samples compared to their paired normal samples, and revealed higher levels of tryptophan in grade III cancers compared to grade I cancers.36,37 Since carcinomas of the prostate and breast demonstrate decreased fat content and increased protein content in comparison to their adjoining nonmalignant tissues, the minimal water absorption occurring at window IV may allow better assessment of diseased versus healthy tissue, based on the relative fractions of collagen, water, and fat that are detected.

Wilson et al. have recently reported that the absorption peaks of lipids occur at 920, 1040, 1210, 1730, and 1760 nm.9 Our study shows that the total attenuation length (lt) from all tissue samples were significantly longer in the three SWIR windows compared to the conventional first NIR window, despite increased collagen or lipid content. Scattering losses due to the solid angle were the same for all specimens. A single scattering event is likely when lt is greater than the sample thickness. Total attenuation measurements were evaluated based on the relative absorption measurements from the first NIR window and the SWIR windows for each tissue. Attenuation lengths obtained from studying lipid rich tissues were longer in the SWIR optical windows (specifically NIR windows II and III) compared to the first NIR window. It is possible that the second and third NIR optical windows are most valuable in studies of tissues with decreased collagen and increased lipid content, whereas windows III and IV might be particularly useful for diagnosis and evaluation of bone diseases or cancer (Table 4).

Table 4

Select chromophores at the first and SWIR optical windows.

WindowWavelength range (nm)ChromophoresAbsorption peak (nm)
I650 to 950Deoxyhemoglobin (Hb)780
Oxyhemoglobin (HbO2)830
II1100 to 1350Lipids1200
Collagen1200
III1600 to 1870Lipids1730, 1750
Collagen1725
IV2100 to 2350Collagen2300

Attenuation lengths obtained from studying bone tissues were greatest at the longest wavelength range in the SWIR (namely at third and fourth windows). The composition of bone is approximately one-third collagen, and, importantly, bone has very little fat content.38,39 Collagen has an absorption peak at 2300 nm. It may be that minimal absorption at the fourth window and negligible scattering provides the ideal combination for deep tissue imaging of bone and other collagen-rich tissues. Window IV may also be most valuable for evaluation of other tissues, including cartilage, teeth, blood vessels, intervertebral discs, and skin.

6.

Conclusion

Total attenuation lengths (lt) from cancers, bone, chicken fat, and solutions of intralipid were calculated at the first NIR and SWIR optical windows. lt results from all tissue samples reveal significantly greater lengths in the three SWIR windows compared to the conventional first NIR window, despite increased collagen or lipid content. Moreover, we note that NIR windows II and III appear to be the optimal SWIR range for studying tissues with a higher fat content, for example, normal breast, brain, and normal prostate. Because of their increased collagen content, cancer and diseases of bone may be best studied at windows III and IV. Among potential medical uses of the fourth window are the evaluation of skin cancers, studies of brain, atherosclerosis and vulnerable plaque, aneurysms, and evaluation of disorders of bone, including Paget’s disease and osteogenesis imperfecta. Imaging using the SWIR windows with a compact supercontinuum laser light system (with advantages including high power, broadband spectrum, and the ability to span from the ultraviolet to the infrared) may be utilized in combination with many optical applications including label-free microscopy, fluorescence lifetime imaging, and may also be useful during endoscopy to reveal early and in situ cancers.

Disclosures

We have a patent pending, “Second, third, and fourth near-infrared spectral windows for deep optical imaging of tissue with less scattering.”

Acknowledgments

This research was supported in part by ARO and Corning.

References

1. 

C. H. Liu et al., “NIR Raman and fluorescence spectroscopies diagnose cancer,” Proc. SPIE, 1887 188 (1993). http://dx.doi.org/10.1117/12.151201 PSISDG 0277-786X Google Scholar

2. 

G. Yu et al., “Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring,” J. Biomed. Opt., 17 (1), 010901 (2012). http://dx.doi.org/10.1117/1.JBO.17.1.010901 JBOPFO 1083-3668 Google Scholar

3. 

B. Shadgan et al., “Wireless near-infrared spectroscopy of skeletal muscle oxygenation and hemodynamics during exercise and ischemia,” Spectroscopy, 23 (5–6), 233 –241 (2009). http://dx.doi.org/10.1155/2009/719604 Google Scholar

4. 

M. Wolf et al., “Progress of near-infrared spectroscopy and topography for brain and muscle clinical applications,” J. Biomed. Opt., 12 (6), 062104 (2007). http://dx.doi.org/10.1117/1.2804899 JBOPFO 1083-3668 Google Scholar

5. 

E. Keller et al., “Noninvasive measurement of regional cerebral blood flow and regional cerebral blood volume by near-infrared spectroscopy and indocyanine green dye dilution,” Neuroimage, 20 (2), 828 –839 (2003). http://dx.doi.org/10.1016/S1053-8119(03)00315-X NEIMEF 1053-8119 Google Scholar

6. 

L. A. Sordillo et al., “Time-resolved fluorescence for breast cancer detection using an octreotate-indocyanine green derivative dye conjugate,” Proc. SPIE, 8577 857708 (2013). http://dx.doi.org/10.1117/12.2003102 PSISDG 0277-786X Google Scholar

7. 

D. C. Sordillo et al., “A novel approach to Paget’s disease diagnosis and monitoring using near-infrared absorption spectroscopy,” Proc. SPIE, 8565 856566 (2013). http://dx.doi.org/10.1117/12.981747 PSISDG 0277-786X Google Scholar

8. 

H. J. Van Staveren et al., “Light scattering in lntralipid-10% in the wavelength range of 400-1100 nm,” Appl. Opt., 30 (31), 4507 –4514 (1991). http://dx.doi.org/10.1364/AO.30.004507 APOPAI 0003-6935 Google Scholar

9. 

R. H. Wilson et al., “Review of short-wave infrared spectroscopy and imaging methods for biological tissue characterization,” J. Biomed. Opt., 20 (3), 030901 (2015). http://dx.doi.org/10.1117/1.JBO.20.3.030901 JBOPFO 1083-3668 Google Scholar

10. 

A. M. Smith, M. C. Mancini and S. Nie, “Bioimaging: second window for in vivo imaging,” Nat. Nanotechnol., 4 (11), 710 –711 (2009). http://dx.doi.org/10.1038/nnano.2009.326 NNAABX 1748-3387 Google Scholar

11. 

L. A. Sordillo et al., “Deep optical imaging of tissue using the second and third near-infrared spectral windows,” J. Biomed. Opt., 19 (5), 056004 (2014). http://dx.doi.org/10.1117/1.JBO.19.5.056004 JBOPFO 1083-3668 Google Scholar

12. 

L. Shi et al., “Transmission in near-infrared optical windows for deep brain imaging,” J. Biophotonics, 9 (1–2), 38 –43 (2016). http://dx.doi.org/10.1002/jbio.201500192 Google Scholar

13. 

R. Nachabe et al., “Estimation of biological chromophores using diffuse optical spectroscopy: benefit of extending the UV-VIS wavelength range to include 1000 to 1600 nm,” Biomed. Opt. Express, 1 (5), 1432 –1442 (2010). http://dx.doi.org/10.1364/BOE.1.001432 BOEICL 2156-7085 Google Scholar

14. 

K. M. Yoo, F. Liu and R. R. Alfano, “Imaging through a scattering wall using absorption,” Opt. Lett., 16 (13), 1068 –1070 (1991). http://dx.doi.org/10.1364/OL.16.001068 OPLEDP 0146-9592 Google Scholar

15. 

R. R. Alfano, The Supercontinuum Laser Source, 3rd ed.Springer, New York (2016). Google Scholar

16. 

I. T. Sorokina and E. Sorokin, “Femtosecond Cr2+-based lasers,” IEEE J. Sel. Top. Quantum Electron., 21 (1), 273 –291 (2015). http://dx.doi.org/10.1109/JSTQE.2014.2341589 IJSQEN 1077-260X Google Scholar

17. 

D. C. Sordillo et al., “Fourth near-infrared optical window for assessment of bone and other tissues,” Proc. SPIE, 9689 96894J (2016). http://dx.doi.org/10.1117/12.2214320 PSISDG 0277-786X Google Scholar

18. 

L. A. Sordillo et al., “Third therapeutic spectral window for deep tissue imaging,” Proc. SPIE, 8940 89400V (2014). http://dx.doi.org/10.1117/12.2040604 PSISDG 0277-786X Google Scholar

19. 

L. Wang et al., “Ballistic 2D imaging through scattering walls using an ultrafast optical Kerr gate,” Science, 253 (5021), 769 –771 (1991). http://dx.doi.org/10.1126/science.253.5021.769 SCIEAS 0036-8075 Google Scholar

20. 

Z. Glasser et al., “The effect of measurement on the ballistic-diffusive transition in turbid media,” J. Biomed. Opt., 18 (10), 106006 (2013). http://dx.doi.org/10.1117/1.JBO.18.10.106006 JBOPFO 1083-3668 Google Scholar

21. 

R. R. Alfano et al., “Light propagation in highly scattering turbid media: concepts, techniques, and biomedical applications,” Photonics: Scientific Foundations, Technology and Applications, 367 –412 Wiley and Sons, Hoboken, New Jersey (2015). Google Scholar

22. 

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol., 58 (11), R37 –R61 (2013). http://dx.doi.org/10.1088/0031-9155/58/11/R37 PHMBA7 0031-9155 Google Scholar

23. 

A. Yaroshevsky et al., “The transition from the ballistic to the diffusive regime in a turbid medium,” Opt. Lett., 36 (8), 1395 –1397 (2011). http://dx.doi.org/10.1364/OL.36.001395 OPLEDP 0146-9592 Google Scholar

24. 

K. M. Yoo, F. Liu and R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett., 64 (22), 2647 –2650 (1990). http://dx.doi.org/10.1103/PhysRevLett.64.2647 PRLTAO 0031-9007 Google Scholar

25. 

Z. Q. Zhang et al., “Wave transport in random media: the ballistic to diffusive regime,” Phys. Rev. E., 60 (4), 4843 –4850 (1999). http://dx.doi.org/10.1103/PhysRevE.60.4843 Google Scholar

26. 

T. L. Troy and S. N. Thennadil, “Optical properties of human skin in the near infrared wavelength range 1000 to 2200 nm,” J. Biomed. Opt., 6 (2), 167 –176 (2001). http://dx.doi.org/10.1117/1.1344191 JBOPFO 1083-3668 Google Scholar

27. 

E. Zamoras-Rojas et al., “Optical properties of pig skin epidermis and dermis estimated with double integrating sphere measurements,” Innov. Food Sci. Emerg. Technol., 20 343 –349 (2013). http://dx.doi.org/10.1016/j.ifset.2013.06.008 Google Scholar

28. 

J. Wang et al., “Near-infrared spectroscopic characterization of human advanced atherosclerotic plaques,” J. Am. Coll. Cardio., 39 (8), 1305 –1313 (2002). http://dx.doi.org/10.1016/S0735-1097(02)01767-9 Google Scholar

29. 

S. Tauber et al., “Light dosimetric quantitative analysis of the human petrous bone: experimental study for laser irradiation of the cochlea,” Lasers Surg. Med., 28 (1), 18 –26 (2001). http://dx.doi.org/10.1002/(ISSN)1096-9101 LSMEDI 0196-8092 Google Scholar

30. 

M. Firbank et al., “Measurement of the optical properties of the skull in the wavelength range 650-950 nm,” Phys. Med. Biol., 38 (4), 503 –510 (1993). http://dx.doi.org/10.1088/0031-9155/38/4/002 PHMBA7 0031-9155 Google Scholar

31. 

N. Ugryumova, S. J. Matcher and D. P. Attenburrow, “Measurement of bone mineral density via light scattering,” Phys. Med. Biol., 49 (3), 469 –483 (2004). http://dx.doi.org/10.1088/0031-9155/49/3/009 PHMBA7 0031-9155 Google Scholar

32. 

A. Pifferi et al., “Optical biopsy of bone tissue: a step toward the diagnosis of bone pathologies,” J. Biomed. Opt., 9 (3), 474 –480 (2004). http://dx.doi.org/10.1117/1.1691029 JBOPFO 1083-3668 Google Scholar

33. 

A. N. Bashkatov et al., “Optical properties of human cranial bone in the spectral range from 800 to 2000 nm,” Proc. SPIE, 6163 616310 (2005). http://dx.doi.org/10.1117/12.697305 PSISDG 0277-786X Google Scholar

34. 

P. Taroni et al., “Absorption of collagen: effects on the estimate of breast composition and related diagnostic implications,” J. Biomed. Opt., 12 (1), 014021 (2007). http://dx.doi.org/10.1117/1.2699170 JBOPFO 1083-3668 Google Scholar

35. 

R. Nachabe et al., “Diagnosis of breast cancer using diffuse optical spectroscopy from 500 to 1600 nm: comparison and classification methods,” J. Biomed. Opt., 16 (8), 087010 (2011). http://dx.doi.org/10.1117/1.3611010 JBOPFO 1083-3668 Google Scholar

36. 

L. A. Sordillo et al., “Optical spectral fingerprints of tissues from patients with different breast cancer histologies using a novel fluorescence spectroscopic device,” Technol. Cancer Res. Treat., 12 (5), 455 –461 (2013). http://dx.doi.org/10.7785/tcrt.2012.500330 Google Scholar

37. 

L. A. Sordillo et al., “Differences in fluorescence profiles from breast cancer tissues due to changes in relative tryptophan content via energy transfer: tryptophan content correlates with histologic grade and tumor size but not with lymph node metastases,” J. Biomed. Opt., 19 (5), 125002 (2014). http://dx.doi.org/10.1117/1.JBO.19.12.125002 JBOPFO 1083-3668 Google Scholar

38. 

S. Teitelbaum, “Bone resorption by osteoclasts,” Science, 289 (5484), 1504 –1508 (2000). http://dx.doi.org/10.1126/science.289.5484.1504 SCIEAS 0036-8075 Google Scholar

39. 

B. Clarke, “Normal bone anatomy and physiology,” Clin. J. Am. Soc. Nephrol., 3 S131 –S139 (2008). http://dx.doi.org/10.2215/CJN.04151206 Google Scholar

Biography

Diana C. Sordillo is a PhD student in mathematics at Vanderbilt University and a researcher at the Institute for Ultrafast Spectroscopy and Lasers in the physics department at the City College of CUNY. She received her MS degree in mathematics from New York University.

Laura A. Sordillo received her MS degree in physics at CCNY. She is a PhD student in the Department of Electrical Engineering at CCNY. She has developed with others a portable device for assessment of high grade cancers, found there exist four NIR optical windows that can be utilized to image breast, brain and bone, and investigated the key role of tryptophan in cancers and neurological diseases. She is a recipient of the CCNY-MSKCC Graduate Award.

Peter P. Sordillo is an attending physician at Lenox Hill Hospital, where his specialty is the treatment of patients with extremely rare cancers. He also holds graduate degrees in philosophy (causality) and in physics. He is a research consultant at the Institute for Ultrafast Spectroscopy and Lasers in the physics department at the City College of CUNY.

Lingyan Shi is a research scientist at Columbia University. Her current research focuses on metabolic imaging with nonlinear biomedical optics such as stimulated Raman scattering (SRS). Before coming to Columbia University, she was a research associate studying deep brain imaging and drug delivery in brain at the Institute for Ultrafast Spectroscopy and Lasers and biology department, CCNY, where she received her PhD in biomedical engineering.

Robert R. Alfano is a distinguished professor of science and engineering at the City College of CUNY. He has pioneered many applications of light and photonics technologies to the study of biological, biomedical, and condensed matter systems, invented and used in his research supercontinuum and tunable solid state lasers. He has received his PhD in physics from New York University and is a fellow of American Physical Society, Optical Society of America, and IEEE.

© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2017/$25.00 © 2017 SPIE
Diana C. Sordillo, Laura A. Sordillo, Peter P. Sordillo, Lingyan Shi, and Robert R. Alfano "Short wavelength infrared optical windows for evaluation of benign and malignant tissues," Journal of Biomedical Optics 22(4), 045002 (3 April 2017). https://doi.org/10.1117/1.JBO.22.4.045002
Received: 18 October 2016; Accepted: 3 March 2017; Published: 3 April 2017
Lens.org Logo
CITATIONS
Cited by 56 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Tissues

Short wave infrared radiation

Near infrared

Absorption

Collagen

Signal attenuation

Bone

Back to Top