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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 3, Iss. 5 — May. 1, 2012
  • pp: 878–898

Improving optical contact for functional near‑infrared brain spectroscopy and imaging with brush optodes

Bilal Khan, Chester Wildey, Robert Francis, Fenghua Tian, Mauricio R. Delgado, Hanli Liu, Duncan MacFarlane, and George Alexandrakis  »View Author Affiliations


Biomedical Optics Express, Vol. 3, Issue 5, pp. 878-898 (2012)
http://dx.doi.org/10.1364/BOE.3.000878


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Video Abstract

Improving optical contact for functional infrared brain spectroscopy and imaging with brush optodes

Abstract

A novel brush optode was designed and demonstrated to overcome poor optical contact with the scalp that can occur during functional near infrared spectroscopy (fNIRS) and imaging due to light obstruction by hair. The brush optodes were implemented as an attachment to existing commercial flat-faced (conventional) fiber bundle optodes. The goal was that the brush optodes would thread through hair and improve optical contact on subjects with dense hair. Simulations and experiments were performed to assess the magnitude of these improvements. FNIRS measurements on 17 subjects with varying hair colors (blonde, brown, and black) and hair densities (0–2.96 hairs/mm2) were performed during a finger tapping protocol for both flat and brush optodes. In addition to reaching a study success rate of almost 100% when using the brush optode extensions, the measurement setup times were reduced by a factor of three. Furthermore, the brush optodes enabled improvements in the activation signal-to-noise ratio (SNR) by up to a factor of ten as well as significant (p < 0.05) increases in the detected area of activation (dAoA). The measured improvements in SNR were matched by Monte Carlo (MC) simulations of photon propagation through scalp and hair. In addition, an analytical model was derived to mathematically estimate the observed light power losses due to different hair colors and hair densities. Interestingly, the derived analytical formula produced excellent estimates of the experimental data and MC simulation results despite several simplifying assumptions. The analytical model enables researchers to readily estimate the light power losses due to obstruction by hair for both flat-faced fiber bundles and individual fibers for a given subject.

© 2012 OSA

OCIS Codes
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(300.6340) Spectroscopy : Spectroscopy, infrared
(170.2655) Medical optics and biotechnology : Functional monitoring and imaging

ToC Category:
Neuroscience and Brain Imaging

History
Original Manuscript: February 1, 2012
Revised Manuscript: April 1, 2012
Manuscript Accepted: April 2, 2012
Published: April 6, 2012

Citation
Bilal Khan, Chester Wildey, Robert Francis, Fenghua Tian, Mauricio R. Delgado, Hanli Liu, Duncan MacFarlane, and George Alexandrakis, "Improving optical contact for functional near‑infrared brain spectroscopy and imaging with brush optodes," Biomed. Opt. Express 3, 878-898 (2012)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-3-5-878


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References

  1. X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009). [CrossRef] [PubMed]
  2. K. Li, L. Guo, J. Nie, G. Li, and T. Liu, “Review of methods for functional brain connectivity detection using fMRI,” Comput. Med. Imaging Graph.33(2), 131–139 (2009). [CrossRef] [PubMed]
  3. G. Muehllehner and J. S. Karp, “Positron emission tomography,” Phys. Med. Biol.51(13), R117–R137 (2006). [CrossRef] [PubMed]
  4. B. Dilharreguy, R. A. Jones, and C. T. Moonen, “Influence of fMRI data sampling on the temporal characterization of the hemodynamic response,” Neuroimage19(4), 1820–1828 (2003). [CrossRef] [PubMed]
  5. T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage29(2), 368–382 (2006). [CrossRef] [PubMed]
  6. F. Abdelnour, B. Schmidt, and T. J. Huppert, “Topographic localization of brain activation in diffuse optical imaging using spherical wavelets,” Phys. Med. Biol.54(20), 6383–6413 (2009). [CrossRef] [PubMed]
  7. S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010). [PubMed]
  8. M. Izzetoglu, A. Devaraj, S. Bunce, and B. Onaral, “Motion artifact cancellation in NIR spectroscopy using Wiener filtering,” IEEE Trans. Biomed. Eng.52(5), 934–938 (2005). [CrossRef] [PubMed]
  9. C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009). [CrossRef] [PubMed]
  10. T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004). [CrossRef] [PubMed]
  11. B. Khan, F. Tian, K. Behbehani, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, D. Reid, H. Liu, and G. Alexandrakis, “Identification of abnormal motor cortex activation patterns in children with cerebral palsy by functional near-infrared spectroscopy,” J. Biomed. Opt.15(3), 036008 (2010). [CrossRef] [PubMed]
  12. F. Tian, M. R. Delgado, S. C. Dhamne, B. Khan, G. Alexandrakis, M. I. Romero, L. Smith, D. Reid, N. J. Clegg, and H. Liu, “Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy,” Opt. Express18(25), 25973–25986 (2010). [CrossRef] [PubMed]
  13. D. H. Burns, S. Rosendahl, D. Bandilla, O. C. Maes, H. M. Chertkow, and H. M. Schipper, “Near-infrared spectroscopy of blood plasma for diagnosis of sporadic Alzheimer’s disease,” J. Alzheimers Dis.17(2), 391–397 (2009). [PubMed]
  14. A. Gibson and H. Dehghani, “Diffuse optical imaging,” Philos. Transact. A Math. Phys. Eng. Sci.367(1900), 3055–3072 (2009). [CrossRef] [PubMed]
  15. M. Kubota, M. Inouchi, I. Dan, D. Tsuzuki, A. Ishikawa, and T. Scovel, “Fast (100-175 ms) components elicited bilaterally by language production as measured by three-wavelength optical imaging,” Brain Res.1226, 124–133 (2008). [CrossRef] [PubMed]
  16. Q. Zhang, X. Yan, and G. E. Strangman, “Development of motion resistant instrumentation for ambulatory near-infrared spectroscopy,” J. Biomed. Opt.16(8), 087008 (2011). [CrossRef] [PubMed]
  17. H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010). [PubMed]
  18. F. Orihuela-Espina, D. R. Leff, D. R. James, A. W. Darzi, and G. Z. Yang, “Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation,” Phys. Med. Biol.55(13), 3701–3724 (2010). [CrossRef] [PubMed]
  19. A. V. Medvedev, J. M. Kainerstorfer, S. V. Borisov, A. H. Gandjbakhche, and J. Vanmeter, ““Seeing” electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal,” J. Biomed. Opt.15(6), 061702 (2010). [CrossRef] [PubMed]
  20. T. Funane, M. Kiguchi, H. Atsumori, H. Sato, K. Kubota, and H. Koizumi, “Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy,” J. Biomed. Opt.16(7), 077011 (2011). [CrossRef] [PubMed]
  21. S. M. Liao, N. M. Gregg, B. R. White, B. W. Zeff, K. A. Bjerkaas, T. E. Inder, and J. P. Culver, “Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study,” J. Biomed. Opt.15(2), 026010 (2010). [CrossRef] [PubMed]
  22. B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011). [CrossRef]
  23. J. M. Barman, I. Astore, and V. Pecoraro, “The normal trichogram of the adult,” J. Invest. Dermatol.44, 233–236 (1965). [PubMed]
  24. M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt.11(5), 054007 (2006). [CrossRef] [PubMed]
  25. C. Julien, “The enigma of Mayer waves: Facts and models,” Cardiovasc. Res.70(1), 12–21 (2006). [CrossRef] [PubMed]
  26. J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, “Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation,” J. Biomed. Opt.10(1), 011013 (2005). [CrossRef] [PubMed]
  27. N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics2, 0000–9999 (2010). [PubMed]
  28. G. Morren, U. Wolf, P. Lemmerling, M. Wolf, J. H. Choi, E. Gratton, L. De Lathauwer, and S. Van Huffel, “Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis,” Med. Biol. Eng. Comput.42(1), 92–99 (2004). [CrossRef] [PubMed]
  29. Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering for global interference cancellation and real-time recovery of evoked brain activity: a Monte Carlo simulation study,” J. Biomed. Opt.12(4), 044014 (2007). [CrossRef] [PubMed]
  30. B. Khan, P. Chand, and G. Alexandrakis, “Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging,” Biomed. Opt. Express2(12), 3367–3386 (2011). [CrossRef] [PubMed]
  31. T. J. Huppert, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain,” Appl. Opt.48(10), D280–D298 (2009). [CrossRef] [PubMed]
  32. B. Brooksby, S. Srinivasan, S. Jiang, H. Dehghani, B. W. Pogue, K. D. Paulsen, J. Weaver, C. Kogel, and S. P. Poplack, “Spectral priors improve near-infrared diffuse tomography more than spatial priors,” Opt. Lett.30(15), 1968–1970 (2005). [CrossRef] [PubMed]
  33. A. Li, Q. Zhang, J. P. Culver, E. L. Miller, and D. A. Boas, “Reconstructing chromosphere concentration images directly by continuous-wave diffuse optical tomography,” Opt. Lett.29(3), 256–258 (2004). [CrossRef] [PubMed]
  34. C. F. Beckmann, M. Jenkinson, and S. M. Smith, “General multilevel linear modeling for group analysis in FMRI,” Neuroimage20(2), 1052–1063 (2003). [CrossRef] [PubMed]
  35. A. F. Abdelnour and T. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage46(1), 133–143 (2009). [CrossRef] [PubMed]
  36. A. K. Singh and I. Dan, “Exploring the false discovery rate in multichannel NIRS,” Neuroimage33(2), 542–549 (2006). [CrossRef] [PubMed]
  37. S. H. Tseng, P. Bargo, A. Durkin, and N. Kollias, “Chromophore concentrations, absorption and scattering properties of human skin in-vivo,” Opt. Express17(17), 14599–14617 (2009). [CrossRef] [PubMed]
  38. F. Jimenez, A. Izeta, and E. Poblet, “Morphometric analysis of the human scalp hair follicle: practical implications for the hair transplant surgeon and hair regeneration studies,” Dermatol. Surg.37(1), 58–64 (2011). [CrossRef] [PubMed]
  39. A. Kharin, B. Varghese, R. Verhagen, and N. Uzunbajakava, “Optical properties of the medulla and the cortex of human scalp hair,” J. Biomed. Opt.14(2), 024035 (2009). [CrossRef] [PubMed]
  40. D. J. Cuccia, F. Bevilacqua, A. J. Durkin, F. R. Ayers, and B. J. Tromberg, “Quantitation and mapping of tissue optical properties using modulated imaging,” J. Biomed. Opt.14(2), 024012 (2009). [CrossRef] [PubMed]
  41. R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. A11(10), 2727–2741 (1994). [CrossRef] [PubMed]
  42. F. K. Knoll, Radiation Detection and Measurement (Wiley, New York, 1988).
  43. 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]
  44. D. Yudovsky and L. Pilon, “Modeling the local excitation fluence rate and fluorescence emission in absorbing and strongly scattering multilayered media,” Appl. Opt.49(31), 6072–6084 (2010). [CrossRef]

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