Abstract

We developed a ratiometric method capable of estimating total hemoglobin concentration from optically measured diffuse reflectance spectra. The three isosbestic wavelength ratio pairs that best correlated to total hemoglobin concentration independent of saturation and scattering were 545/390, 452/390, and 529/390 nm. These wavelength pairs were selected using forward Monte Carlo simulations which were used to extract hemoglobin concentration from experimental phantom measurements. Linear regression coefficients from the simulated data were directly applied to the phantom data, by calibrating for instrument throughput using a single phantom. Phantoms with variable scattering and hemoglobin saturation were tested with two different instruments, and the average percent errors between the expected and ratiometrically-extracted hemoglobin concentration were as low as 6.3%. A correlation of r = 0.88 between hemoglobin concentration extracted using the 529/390 nm isosbestic ratio and a scalable inverse Monte Carlo model was achieved for in vivo dysplastic cervical measurements (hemoglobin concentrations have been shown to be diagnostic for the detection of cervical pre-cancer by our group). These results indicate that use of such a simple ratiometric method has the potential to be used in clinical applications where tissue hemoglobin concentrations need to be rapidly quantified in vivo.

© 2010 OSA

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  1. W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
    [CrossRef] [PubMed]
  2. J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
    [PubMed]
  3. N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
    [PubMed]
  4. J. F. Jansen, J. A. Koutcher, and A. Shukla-Dave, “Non-invasive imaging of angiogenesis in head and neck squamous cell carcinoma,” Angiogenesis (2010).
  5. K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
    [PubMed]
  6. S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
    [CrossRef] [PubMed]
  7. 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]
  8. G. M. Palmer and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms,” Appl. Opt. 45(5), 1062–1071 (2006).
    [CrossRef] [PubMed]
  9. G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
    [CrossRef] [PubMed]
  10. 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]
  11. M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
    [PubMed]
  12. R. N. Pittman and B. R. Duling, “A new method for the measurement of percent oxyhemoglobin,” J. Appl. Physiol. 38(2), 315–320 (1975).
    [PubMed]
  13. Q. Liu and T. Vo-Dinh, “Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms,” Med. Phys. 36(10), 4819–4829 (2009).
    [CrossRef] [PubMed]
  14. J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
    [CrossRef] [PubMed]
  15. G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
    [CrossRef] [PubMed]
  16. S. Prahl, “Optical Properties Spectra,” (Oregon Medical Laser Center, 2003).
  17. S. Prahl, “Mie Scattering Program,” (Oregon Medical Laser Center, 2005).
  18. J. E. Bender, A. B. Shang, E. W. Moretti, B. Yu, L. M. Richards, and N. Ramanujam, “Noninvasive monitoring of tissue hemoglobin using UV-VIS diffuse reflectance spectroscopy: a pilot study,” Opt. Express 17(26), 23396–23409 (2009).
    [CrossRef]
  19. T. M. Bydlon, S. A. Kennedy, L. M. Richards, J. Q. Brown, B. Yu, M. K. Junker, J. Gallagher, J. Geradts, L. G. Wilke, and N. Ramanujam, “Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins,” Opt. Express 18(8), 8058–8076 (2010).
    [CrossRef] [PubMed]
  20. 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]
  21. R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
    [CrossRef] [PubMed]
  22. V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
    [PubMed]

2010 (1)

2009 (4)

Q. Liu and T. Vo-Dinh, “Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms,” Med. Phys. 36(10), 4819–4829 (2009).
[CrossRef] [PubMed]

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

J. E. Bender, A. B. Shang, E. W. Moretti, B. Yu, L. M. Richards, and N. Ramanujam, “Noninvasive monitoring of tissue hemoglobin using UV-VIS diffuse reflectance spectroscopy: a pilot study,” Opt. Express 17(26), 23396–23409 (2009).
[CrossRef]

2008 (1)

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

2006 (2)

2004 (1)

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

2003 (1)

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

2002 (1)

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

1998 (1)

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

1997 (1)

1995 (2)

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

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]

1993 (1)

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

1992 (1)

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]

1987 (1)

M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
[PubMed]

1975 (1)

R. N. Pittman and B. R. Duling, “A new method for the measurement of percent oxyhemoglobin,” J. Appl. Physiol. 38(2), 315–320 (1975).
[PubMed]

A’Amar, O.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

Albertyn, G.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Amorosino, M. S.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

Aparecida Pinto, G.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Arimoto, Y.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Bean, S. M.

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

Bender, J. E.

J. E. Bender, A. B. Shang, E. W. Moretti, B. Yu, L. M. Richards, and N. Ramanujam, “Noninvasive monitoring of tissue hemoglobin using UV-VIS diffuse reflectance spectroscopy: a pilot study,” Opt. Express 17(26), 23396–23409 (2009).
[CrossRef]

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

Bentley, R. C.

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

Bigio, I. J.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

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]

Blumenfeld, W.

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Boyer, J.

Breslin, T. M.

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Brown, J. Q.

T. M. Bydlon, S. A. Kennedy, L. M. Richards, J. Q. Brown, B. Yu, M. K. Junker, J. Gallagher, J. Geradts, L. G. Wilke, and N. Ramanujam, “Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins,” Opt. Express 18(8), 8058–8076 (2010).
[CrossRef] [PubMed]

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

Bydlon, T. M.

Calabro, K. W.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

Carasan, G. A.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Carroll, P. R.

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Cartwright, P. S.

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

Chang, V.

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

Chang, V. T.

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

Chung, Y. S.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Da Silva, B. B.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

De Moraes, N. G.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Dirix, L.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Duling, B. R.

R. N. Pittman and B. R. Duling, “A new method for the measurement of percent oxyhemoglobin,” J. Appl. Physiol. 38(2), 315–320 (1975).
[PubMed]

Ellis, C. G.

M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
[PubMed]

Ellsworth, M. L.

M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
[PubMed]

Farrell, T. J.

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]

Flax, J.

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Folkman, J.

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Fuselier, T.

Gallagher, J.

Geradts, J.

Gilchrist, K. W.

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Goovaerts, G.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Jacques, S. L.

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]

Johnson, T. M.

Jung, J. J.

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Junker, M. K.

Kato, Y.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Kennedy, S. A.

Kim, H. S.

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Kondo, Y.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Lee, J. S.

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Lee, M. C.

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Liu, Q.

Q. Liu and T. Vo-Dinh, “Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms,” Med. Phys. 36(10), 4819–4829 (2009).
[CrossRef] [PubMed]

Maeda, K.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Moore, L. K.

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

Moretti, E. W.

Mourant, J. R.

Nitta, A.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Ogawa, Y.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Onoda, N.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Palmer, G. M.

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms,” Appl. Opt. 45(5), 1062–1071 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Park, C. S.

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Patterson, M. S.

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]

Pittman, R. N.

M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
[PubMed]

R. N. Pittman and B. R. Duling, “A new method for the measurement of percent oxyhemoglobin,” J. Appl. Physiol. 38(2), 315–320 (1975).
[PubMed]

Ramanujam, N.

T. M. Bydlon, S. A. Kennedy, L. M. Richards, J. Q. Brown, B. Yu, M. K. Junker, J. Gallagher, J. Geradts, L. G. Wilke, and N. Ramanujam, “Performance metrics of an optical spectral imaging system for intra-operative assessment of breast tumor margins,” Opt. Express 18(8), 8058–8076 (2010).
[CrossRef] [PubMed]

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

J. E. Bender, A. B. Shang, E. W. Moretti, B. Yu, L. M. Richards, and N. Ramanujam, “Noninvasive monitoring of tissue hemoglobin using UV-VIS diffuse reflectance spectroscopy: a pilot study,” Opt. Express 17(26), 23396–23409 (2009).
[CrossRef]

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

G. M. Palmer and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms,” Appl. Opt. 45(5), 1062–1071 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Reif, R.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

Richards, L. M.

Sawada, T.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Shang, A. B.

Singh, S. K.

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

Sowa, M.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Takatsuka, S.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Tjalma, W.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Van Daele, A.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

van Dam, P.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Van Marck, E.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Vassallo, J.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Vieira, S. C.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Vishwanath, K.

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

Vo-Dinh, T.

Q. Liu and T. Vo-Dinh, “Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms,” Med. Phys. 36(10), 4819–4829 (2009).
[CrossRef] [PubMed]

Wang, L.

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]

Weidner, N.

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Weyler, J.

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Wilke, L. G.

Wilson, B.

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]

Xu, F.

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Yamashita, Y.

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Yu, B.

Zeferino, L. C.

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

Zheng, L.

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]

Zhu, C.

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part II: Application to breast cancer diagnosis,” Appl. Opt. 45(5), 1072–1078 (2006).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

Am. J. Pathol. (1)

N. Weidner, P. R. Carroll, J. Flax, W. Blumenfeld, and J. Folkman, “Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma,” Am. J. Pathol. 143(2), 401–409 (1993).
[PubMed]

Am. J. Physiol. (1)

M. L. Ellsworth, R. N. Pittman, and C. G. Ellis, “Measurement of hemoglobin oxygen saturation in capillaries,” Am. J. Physiol. 252(5 Pt 2), H1031–H1040 (1987).
[PubMed]

Anal. Quant. Cytol. Histol. (1)

J. S. Lee, H. S. Kim, J. J. Jung, M. C. Lee, and C. S. Park, “Angiogenesis, cell proliferation and apoptosis in progression of cervical neoplasia,” Anal. Quant. Cytol. Histol. 24(2), 103–113 (2002).
[PubMed]

Appl. Opt. (3)

Br. J. Cancer (1)

W. Tjalma, E. Van Marck, J. Weyler, L. Dirix, A. Van Daele, G. Goovaerts, G. Albertyn, and P. van Dam, “Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer,” Br. J. Cancer 78(2), 170–174 (1998).
[CrossRef] [PubMed]

Comput. Methods Programs Biomed. (1)

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]

Gynecol. Oncol. (1)

S. C. Vieira, L. C. Zeferino, B. B. Da Silva, G. Aparecida Pinto, J. Vassallo, G. A. Carasan, and N. G. De Moraes, “Quantification of angiogenesis in cervical cancer: a comparison among three endothelial cell markers,” Gynecol. Oncol. 93(1), 121–124 (2004).
[CrossRef] [PubMed]

IEEE Trans. Biomed. Eng. (2)

J. E. Bender, K. Vishwanath, L. K. Moore, J. Q. Brown, V. Chang, G. M. Palmer, and N. Ramanujam, “A robust Monte Carlo model for the extraction of biological absorption and scattering in vivo,” IEEE Trans. Biomed. Eng. 56(4), 960–968 (2009).
[CrossRef] [PubMed]

G. M. Palmer, C. Zhu, T. M. Breslin, F. Xu, K. W. Gilchrist, and N. Ramanujam, “Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003),” IEEE Trans. Biomed. Eng. 50(11), 1233–1242 (2003).
[CrossRef] [PubMed]

J. Appl. Physiol. (1)

R. N. Pittman and B. R. Duling, “A new method for the measurement of percent oxyhemoglobin,” J. Appl. Physiol. 38(2), 315–320 (1975).
[PubMed]

J. Biomed. Opt. (1)

R. Reif, M. S. Amorosino, K. W. Calabro, O. A’Amar, S. K. Singh, and I. J. Bigio, “Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures,” J. Biomed. Opt. 13(1), 010502 (2008).
[CrossRef] [PubMed]

J. Clin. Oncol. (1)

K. Maeda, Y. S. Chung, S. Takatsuka, Y. Ogawa, T. Sawada, Y. Yamashita, N. Onoda, Y. Kato, A. Nitta, Y. Arimoto, Y. Kondo, and M. Sowa, “Tumor angiogenesis as a predictor of recurrence in gastric carcinoma,” J. Clin. Oncol. 13(2), 477–481 (1995).
[PubMed]

Med. Phys. (2)

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]

Q. Liu and T. Vo-Dinh, “Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms,” Med. Phys. 36(10), 4819–4829 (2009).
[CrossRef] [PubMed]

Neoplasia (1)

V. T. Chang, P. S. Cartwright, S. M. Bean, G. M. Palmer, R. C. Bentley, and N. Ramanujam, “Quantitative physiology of the precancerous cervix in vivo through optical spectroscopy,” Neoplasia 11(4), 325–332 (2009).
[PubMed]

Opt. Express (2)

Other (3)

S. Prahl, “Optical Properties Spectra,” (Oregon Medical Laser Center, 2003).

S. Prahl, “Mie Scattering Program,” (Oregon Medical Laser Center, 2005).

J. F. Jansen, J. A. Koutcher, and A. Shukla-Dave, “Non-invasive imaging of angiogenesis in head and neck squamous cell carcinoma,” Angiogenesis (2010).

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Figures (7)

Fig. 1
Fig. 1

Flow chart illustrating the processes for selecting the best ratios which were tested in three sets of phantoms.

Fig. 2
Fig. 2

Flow chart illustrating the processes for selecting the best ratios based on the phantom experiments.

Fig. 3
Fig. 3

Histogram of average percent errors from the simulations. The ratios within each bin of the histogram are labeled on the figure in order of increasing %error.

Fig. 4
Fig. 4

Average percent error for Set 1for each of the 25 best ratios determined from the simulations. The black line shows the cut-off of 20% average error.

Fig. 5
Fig. 5

Average percent error for Set 2 (top) and Set 3 (bottom) measured with Instrument 1 for each of the 12 best ratios determined from the Hb saturation phantoms. The black line shows the cut-off of 20% average error.

Fig. 6
Fig. 6

Average percent error for Set 2 (top) and Set 3 (bottom) measured with Instrument 2 for each of the six best ratios determined from phantoms measured with Instrument 1. The black line shows the cut-off of 20% average error.

Fig. 7
Fig. 7

Monte Carlo-extracted Hb versus Hb extracted with 545/390 (top left), 452/390 (top right), and 529/390 nm (bottom) reflectance ratios for in vivo cervical measurements. The solid line is the line of perfect agreement for the Monte Carlo-extracted Hb concentration.

Tables (6)

Tables Icon

Table 1 Total Hb concentration and Hb saturation used in the simulations

Tables Icon

Table 2 μs’ for each of the five scattering levels as a function of isosbestic wavelength

Tables Icon

Table 3 Ranges of Hb concentrations and mean μs’ (averaged over 350-600 nm) for Phantom Sets 2 and 3. Set 2 had two µs’ levels, each of which had the same range of Hb

Tables Icon

Table 4 Average percent error for the simulations (“Sims”) and three testing phantom sets. Set 1 had variable Hb saturation, Set 2 had variations in Hb concentration for two scattering levels, and Set 3 had large variations in Hb concentration for one scattering level. Sets 2 and 3 were measured with both instruments. The errors are shown for the six best ratios and the inverse Monte Carlo model

Tables Icon

Table 5 Ranges of scattering slope, b, for which the six best ratios were still considered best ratios. To still be considered a best ratio, these values of b had to result in ≤ 20% error for simulations and Sets 1-3 measured with Instrument 1

Tables Icon

Table 6 Average percent error when g = 0.7, 0.9, and 0.95 were used for Sets 1-3 measured with Instrument 1. The average percent error for 545/390 and 570/390 nm with Set 2 and g = 0.7 slightly exceeded the 20% limit

Equations (1)

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% e r r o r = 100 | fit H b H b | n

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