Abstract

Skin breakdown is a prevalent and costly medical condition worldwide, with the etiologic and healing processes being complex and multifactorial. Quantitative assessment of wound healing is challenging due to the subjective measurement of wound size and related characteristics. We propose that in vivo spectral reflectance measurements can serve as valuable clinical monitoring tool/device in the study of wound healing. We have designed a multi spectral camera able to acquire 18 wavelength sensitive images in a single snapshot. A lenslets array in front of a digital camera is combined with narrowband filters (bandwidth 10 nm) ranging from 460 to 886nm. Images taken with the spectroscopic camera are composed of 18 identical sub-images, each carrying different spectral information, that can be used in the assessment of skin chromophores. A clinical trial based on a repeated measures design was conducted at the National Rehabilitation Hospital on 15 individuals to assess whether Poly Carboxy Methyl Glucose Sulfate (PCMGS, CACIPLIQ20), a bio-engineered component of the extracellular matrix of the skin, is effective at promoting healing of a variety of wounds. Multi spectral images collected at different wavelengths combined with optical skin models were used to quantify skin oxygen saturation and its relation to the traditional measures of wound healing.

© 2010 OSA

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  1. A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).
  2. G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
    [CrossRef]
  3. H. J. Noordmans, R. De Roode, M. Staring, and R. Verdaasdonk, “Registration and analysis of in-vivo multi-spectral images for correction of motion and comparison in time,” Proc. SPIE, 7. 608106.1-.9 (2006).
  4. R. De Roode, H. J. Noordmans, R. Verdaasdonk, and V. Sigurdsson, “MULTISPECTRAL DETECTORS: Multispectral system evaluates treatments in dermatology,” Laser Focus World. 42 (Apr 2006) www.laserfocusworld.com .
  5. T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
    [CrossRef] [PubMed]
  6. I. V. Meglinski and S. J. Matcher, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23(4), 741–753 (2002).
    [CrossRef] [PubMed]
  7. I. V. Meglinski and S. J. Matcher, “Computer simulation of the sin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 44–50 (2003).
    [CrossRef]
  8. J. Ramella-Roman and S. Mathews, “Spectroscopic Measurement of Oxygen Saturation in the Retina,” IEEE J. Sel. Top. Quantum Electron. 13(6), 1697–1703 (2007).
    [CrossRef]
  9. S. A. Mathews, “Design and fabrication of a low-cost, multispectral imaging system,” Appl. Opt. 47(28), F71–F76 (2008).
    [CrossRef] [PubMed]
  10. J. Ramella - Roman, S. Mathews, H. Kandiamalla, A. Nabili, D. Duncan, S. A. D'Anna, S. M. Shah, and Q. D. Nguyen, “Measurement of oxygen saturation in the retina with a spectroscopic sesitive multi aperture camera,” Opt. Express 16(9), 6170–6182 (2008) (i).
    [CrossRef] [PubMed]
  11. T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).
  12. L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML--Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).
    [CrossRef] [PubMed]
  13. G. N. Stamatas and N. Kollias, “In vivo documentation of cutaneous inflammation using spectral imaging,” J. Biomed. Opt. 12(5), 051603 (2007).
    [CrossRef] [PubMed]
  14. S. Iyad, Saidi, 1992 Transcutaneous optical measurement of hyperbilirubinemia in neonates. Ph.D. dissertation, Rice University, Houston, TX, USA.
  15. S. Takatani and M. D. Graham, “Theoretical analysis of diffuse reflectance from a two-layer tissue model,” IEEE Trans. Biomed. Eng. BME-26(12), 656–664 (1979).
    [CrossRef]
  16. Center for Wound Healing,and Hyperbaric Medicine, “Smoking and woundhealing,” Wound Healing Center., Trinitas Hospital. (2001). http://www.woundhealingcenter.org/SmokingandWound Healing.pdf .C. Ueno, T. Hunt, H. Hopf, “Using Physiology to improve surgical wound outcomes,” Plast. Reconstr. Surg. 117, 59S–71S (2006)
  17. Some portions of this paper have appeared in M. Nabili, J. C. Ramella-Roman, Assessment of skin wound healing with a multi-aperture camera, Photonics in Dermatology and Plastic Surgery, Proceedings of SPIE Vol. 7161A, 2009.

2008 (3)

2007 (2)

J. Ramella-Roman and S. Mathews, “Spectroscopic Measurement of Oxygen Saturation in the Retina,” IEEE J. Sel. Top. Quantum Electron. 13(6), 1697–1703 (2007).
[CrossRef]

G. N. Stamatas and N. Kollias, “In vivo documentation of cutaneous inflammation using spectral imaging,” J. Biomed. Opt. 12(5), 051603 (2007).
[CrossRef] [PubMed]

2006 (2)

T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).

G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
[CrossRef]

2004 (1)

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

2003 (1)

I. V. Meglinski and S. J. Matcher, “Computer simulation of the sin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 44–50 (2003).
[CrossRef]

2002 (1)

I. V. Meglinski and S. J. Matcher, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23(4), 741–753 (2002).
[CrossRef] [PubMed]

1995 (1)

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

1979 (1)

S. Takatani and M. D. Graham, “Theoretical analysis of diffuse reflectance from a two-layer tissue model,” IEEE Trans. Biomed. Eng. BME-26(12), 656–664 (1979).
[CrossRef]

Amyot, F.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Binzoni, T.

T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
[CrossRef] [PubMed]

Chen, Y.

T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).

Chernomordik, V. V.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

D'Anna, S. A.

Dasgeb, B.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Demos, S. G.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Duncan, D.

Gandjbakhche, A. H.

T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
[CrossRef] [PubMed]

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Graham, M. D.

S. Takatani and M. D. Graham, “Theoretical analysis of diffuse reflectance from a two-layer tissue model,” IEEE Trans. Biomed. Eng. BME-26(12), 656–664 (1979).
[CrossRef]

Hassan, M.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Jacques, S. L.

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

Kandiamalla, H.

Kollias, N.

G. N. Stamatas and N. Kollias, “In vivo documentation of cutaneous inflammation using spectral imaging,” J. Biomed. Opt. 12(5), 051603 (2007).
[CrossRef] [PubMed]

G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
[CrossRef]

Little, R. F.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Marchesini, R.

T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
[CrossRef] [PubMed]

Matcher, S. J.

I. V. Meglinski and S. J. Matcher, “Computer simulation of the sin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 44–50 (2003).
[CrossRef]

I. V. Meglinski and S. J. Matcher, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23(4), 741–753 (2002).
[CrossRef] [PubMed]

Mathews, S.

Mathews, S. A.

Meglinski, I. V.

I. V. Meglinski and S. J. Matcher, “Computer simulation of the sin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 44–50 (2003).
[CrossRef]

I. V. Meglinski and S. J. Matcher, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23(4), 741–753 (2002).
[CrossRef] [PubMed]

Moffitt, T.

T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).

Nabili, A.

Nguyen, Q. D.

Prahl, S.A.

T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).

Pursley, R.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Ramella - Roman, J.

Ramella-Roman, J.

J. Ramella-Roman and S. Mathews, “Spectroscopic Measurement of Oxygen Saturation in the Retina,” IEEE J. Sel. Top. Quantum Electron. 13(6), 1697–1703 (2007).
[CrossRef]

Riley, J. D.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Shah, S. M.

Southall, M.

G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
[CrossRef]

Stamatas, G. N.

G. N. Stamatas and N. Kollias, “In vivo documentation of cutaneous inflammation using spectral imaging,” J. Biomed. Opt. 12(5), 051603 (2007).
[CrossRef] [PubMed]

G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
[CrossRef]

Takatani, S.

S. Takatani and M. D. Graham, “Theoretical analysis of diffuse reflectance from a two-layer tissue model,” IEEE Trans. Biomed. Eng. BME-26(12), 656–664 (1979).
[CrossRef]

Tao, Y.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Vogel, A.

T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
[CrossRef] [PubMed]

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Wang, L. H.

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

Yarchoan, R.

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Zheng, L. Q.

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

Appl. Opt. (1)

Comput. Methods Programs Biomed. (2)

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

I. V. Meglinski and S. J. Matcher, “Computer simulation of the sin reflectance spectra,” Comput. Methods Programs Biomed. 70(2), 44–50 (2003).
[CrossRef]

IEEE J. Sel. Top. Quantum Electron. (1)

J. Ramella-Roman and S. Mathews, “Spectroscopic Measurement of Oxygen Saturation in the Retina,” IEEE J. Sel. Top. Quantum Electron. 13(6), 1697–1703 (2007).
[CrossRef]

IEEE Trans. Biomed. Eng. (1)

S. Takatani and M. D. Graham, “Theoretical analysis of diffuse reflectance from a two-layer tissue model,” IEEE Trans. Biomed. Eng. BME-26(12), 656–664 (1979).
[CrossRef]

J. Biomed. Opt. (2)

G. N. Stamatas and N. Kollias, “In vivo documentation of cutaneous inflammation using spectral imaging,” J. Biomed. Opt. 12(5), 051603 (2007).
[CrossRef] [PubMed]

A. Vogel, V. V. Chernomordik, J. D. Riley, M. Hassan, F. Amyot, B. Dasgeb, S. G. Demos, R. Pursley, R. F. Little, R. Yarchoan, Y. Tao, and A. H. Gandjbakhche, “Using noninvasive multispectral imaging to quantitatively assess tissue vasculature,” J. Biomed. Opt. 12, 051604.1–12 (2004).

Opt. Express (1)

Phys. Med. Biol. (1)

T. Binzoni, A. Vogel, A. H. Gandjbakhche, and R. Marchesini, “Detection limits of multi-spectral optical imaging under the skin surface,” Phys. Med. Biol. 53(3), 617–636 (2008).
[CrossRef] [PubMed]

Physiol. Meas. (1)

I. V. Meglinski and S. J. Matcher, “Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions,” Physiol. Meas. 23(4), 741–753 (2002).
[CrossRef] [PubMed]

The society for investigative dermatology (1)

G. N. Stamatas, M. Southall, and N. Kollias, “In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared,” The society for investigative dermatology 126(8), 1753–1760 (2006).
[CrossRef]

Other (6)

H. J. Noordmans, R. De Roode, M. Staring, and R. Verdaasdonk, “Registration and analysis of in-vivo multi-spectral images for correction of motion and comparison in time,” Proc. SPIE, 7. 608106.1-.9 (2006).

R. De Roode, H. J. Noordmans, R. Verdaasdonk, and V. Sigurdsson, “MULTISPECTRAL DETECTORS: Multispectral system evaluates treatments in dermatology,” Laser Focus World. 42 (Apr 2006) www.laserfocusworld.com .

T. Moffitt, Y. Chen, and S.A. Prahl. “Preparation and characterization of polyurethane optical phantoms,” J. Biomed. Opt. 11 041103.1–10 (2006).

S. Iyad, Saidi, 1992 Transcutaneous optical measurement of hyperbilirubinemia in neonates. Ph.D. dissertation, Rice University, Houston, TX, USA.

Center for Wound Healing,and Hyperbaric Medicine, “Smoking and woundhealing,” Wound Healing Center., Trinitas Hospital. (2001). http://www.woundhealingcenter.org/SmokingandWound Healing.pdf .C. Ueno, T. Hunt, H. Hopf, “Using Physiology to improve surgical wound outcomes,” Plast. Reconstr. Surg. 117, 59S–71S (2006)

Some portions of this paper have appeared in M. Nabili, J. C. Ramella-Roman, Assessment of skin wound healing with a multi-aperture camera, Photonics in Dermatology and Plastic Surgery, Proceedings of SPIE Vol. 7161A, 2009.

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Figures (10)

Fig. 1
Fig. 1

An image of the clinical system apparatus

Fig. 2
Fig. 2

Comparison between the experiment result and Monte Carlo simulation for 3 epoxy phantoms. The solid black lines represent the Monte Carlo results, the void symbols are the corresponding experimental results. The factor A was kept constant in all experimental results. Top phantom µa = 0.0671 mm-1, µs’ = 0.3464 mm-1,bottom line µa = 0.846 mm-1, µs’ = 1.3175 mm-1 in wavelength 660 nm.

Fig. 3
Fig. 3

Reflectance of Spectralon color (green, red, yellow) standard collected by camera compared with calibrated NIST values. Calibtated data is not available above 800 nm, hence the last image of the spectral camera is omitted from this graph.

Fig. 4
Fig. 4

The thick black line is the standard image used to correct for distortion artifacts. The thickness of each line is 0.6 cm. the vertical line is 14.2 cm and the horizontal line is 21.6cm. The light lines represent a possible distortion observed with the multi-spectral camera. The dashed lines represent the area calculated to assess the level of distortion.

Fig. 5
Fig. 5

Images acquired at different target to camera distances (D) for upper left lens in multispectral camera.

Fig. 6
Fig. 6

Calculated distortion at different target to camera distances. The distortion is minimum between 8.5 cm to 11.5 cm for all 7 lenses.

Fig. 7
Fig. 7

Blue dots shows the distortion for 18 different lenses at 9.5 cm, and the black dots shows the same distortion after registration.

Fig. 8
Fig. 8

Oxygen saturation maps (SO2) during the inflation and deflation of a pressure cuff. The false color map relates to oxygen saturation (values are between 0 and 1). The line in the first figure on the left corresponds to 0.5 cm.

Fig. 9
Fig. 9

Typical image acquired with the spectral camera.

Fig. 10
Fig. 10

A typical raw image of the wound at 540 nm, (left) and corresponding oxygen saturation map (right).

Equations (2)

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R ( x , y , λ ) = A × R p h a n t o m ( x , y , λ ) D a r k ( x , y , λ ) R w h i t e S T D ( x , y , λ ) D a r k ( x , y , λ )
D i s t o r t i o n = R 1 + R 2 + R 3 + R 4 M = [ p i x e l ] . [ p i x e l ] [ p i x e l ] / [ c m ] = [ p i x e l . c m ]

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