Abstract

The quantification of visceral organ oxygenation after trauma-related systemic hypovolemia and shock is critical to enable effective resuscitation. In this work, a photoplethysmography-based (PPG) sensor was specifically designed for probing the perfusion and oxygenation condition of intestinal tissue with the ultimate goal to monitor patients post trauma to guide resuscitation. Through Monte Carlo modeling, suitable optofluidic phantoms were determined, the wavelength and separation distance for the sensor was optimized, and sensor performance for the quantification of tissue perfusion and oxygenation was tested on the in-vitro phantom. In particular, the Monte Carlo simulated both a standard block three-layer model and a more realistic model including villi. Measurements were collected on the designed three layer optofluidic phantom and the results taken with the small form factor PPG device showed a marked improvement when using shorter visible wavelengths over the more conventional longer visible wavelengths. Overall, in this work a Monte Carlo model was developed, an optofluidic phantom was built, and a small form factor PPG sensor was developed and characterized using the phantom for perfusion and oxygenation over the visible wavelength range. The results show promise that this small form factor PPG sensor could be used as a future guide to shock-related resuscitation.

© 2017 Optical Society of America

Full Article  |  PDF Article
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References

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2016 (2)

C. L. Campbell, K. Wood, C. T. Brown, and H. Moseley, “Monte Carlo modelling of photodynamic therapy treatments comparing clustered three dimensional tumour structures with homogeneous tissue structures,” Phys. Med. Biol. 61(13), 4840–4854 (2016).
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S. Chatterjee, J. Phillips, and P. Kyriacou, “Monte Carlo investigation of the effect of blood volume and oxygen saturation on optical path in reflectance pulse oximetry,” Biomed. Phys. Eng. Express 2(6), 065018 (2016).
[Crossref]

2015 (4)

T. Y. Abay and P. A. Kyriacou, “Reflectance photoplethysmography as noninvasive monitoring of tissue blood perfusion,” IEEE Trans. Biomed. Eng. 62(9), 2187–2195 (2015).
[Crossref] [PubMed]

D. Neil Granger, L. Holm, and P. Kvietys, “The gastrointestinal circulation: physiology and pathophysiology,” Compr. Physiol. 5, 1541–1583 (2015).
[Crossref]

L. Zheng, C. J. Kelly, and S. P. Colgan, “Physiologic hypoxia and oxygen homeostasis in the healthy intestine. A Review in the Theme: Cellular Responses to Hypoxia,” Am. J. Physiol. Cell Physiol. 309(6), C350–C360 (2015).
[Crossref] [PubMed]

T. Kurata, Z. Li, S. Oda, H. Kawahira, and H. Haneishi, “Impact of vessel diameter and bandwidth of illumination in sidestream dark-field oximetry,” Biomed. Opt. Express 6(5), 1616–1631 (2015).
[Crossref] [PubMed]

2014 (1)

T. Tamura, Y. Maeda, M. Sekine, and M. Yoshida, “Wearable photoplethysmographic sensors—past and present,” Electronics (Basel) 3(2), 282–302 (2014).
[Crossref]

2013 (3)

F. Mustafa and M. Jaafar, “Comparison of wavelength-dependent penetration depths of lasers in different types of skin in photodynamic therapy,” Indian J. Phys. 87(3), 203–209 (2013).
[Crossref]

T. J. Akl, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Intestinal perfusion monitoring using photoplethysmography,” J. Biomed. Opt. 18(8), 087005 (2013).
[Crossref] [PubMed]

P. Di Donato, D. Penninck, M. Pietra, M. Cipone, and A. Diana, “Ultrasonographic measurement of the relative thickness of intestinal wall layers in clinically healthly cats,” J. Feline Med. Surg. 16, 333–339 (2013).

2012 (2)

C.-C. Chuang, Y.-T. Lee, C.-M. Chen, Y.-S. Hsieh, T.-C. Liu, and C.-W. Sun, “Patient-oriented simulation based on Monte Carlo algorithm by using MRI data,” Biomed. Eng. Online 11(1), 21 (2012).
[Crossref] [PubMed]

T. W. Scheeren, P. Schober, and L. A. Schwarte, “Monitoring tissue oxygenation by near infrared spectroscopy (NIRS): background and current applications,” J. Clin. Monit. Comput. 26(4), 279–287 (2012).
[Crossref] [PubMed]

2011 (5)

A. Yaroshevsky, Z. Glasser, E. Granot, and S. Sternklar, “Transition from the ballistic to the diffusive regime in a turbid medium,” Opt. Lett. 36(8), 1395–1397 (2011).
[Crossref] [PubMed]

R. Long, T. King, T. Akl, M. N. Ericson, M. Wilson, G. L. Coté, and M. J. McShane, “Optofluidic phantom mimicking optical properties of porcine livers,” Biomed. Opt. Express 2(7), 1877–1892 (2011).
[Crossref] [PubMed]

S. Kumari and A. Nirala, “Study of light propagation in human, rabbit and rat liver tissue by Monte Carlo simulation,” Optik-International Journal for Light and Electron Optics 122(9), 807–810 (2011).
[Crossref]

T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
[Crossref] [PubMed]

A. Plüddemann, M. Thompson, C. Heneghan, and C. Price, “Pulse oximetry in primary care: primary care diagnostic technology update,” Br. J. Gen. Pract. 61(586), 358–359 (2011).
[Crossref] [PubMed]

2010 (2)

C. Fries and M. J. Midwinter, “Trauma resuscitation and damage control surgery,” Surgery 28(11), 563–567 (2010).
[Crossref]

C. G. Cronin, E. Delappe, D. G. Lohan, C. Roche, and J. M. Murphy, “Normal small bowel wall characteristics on MR enterography,” Eur. J. Radiol. 75(2), 207–211 (2010).
[Crossref] [PubMed]

2007 (3)

G. Themelis, H. D’Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, and M. A. Franceschini, “Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations,” J. Biomed. Opt. 12(1), 014033 (2007).
[Crossref] [PubMed]

S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
[Crossref]

P. D. Mannheimer, “The light-tissue interaction of pulse oximetry,” Anesth. Analg. 105(6Suppl), S10–S17 (2007).
[Crossref] [PubMed]

2006 (1)

2005 (1)

D. Hidović-Rowe and E. Claridge, “Modelling and validation of spectral reflectance for the colon,” Phys. Med. Biol. 50(6), 1071–1093 (2005).
[Crossref] [PubMed]

2004 (1)

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
[Crossref] [PubMed]

2002 (1)

A. P. Lima, P. Beelen, and J. Bakker, “Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion,” Crit. Care Med. 30(6), 1210–1213 (2002).
[Crossref] [PubMed]

2000 (2)

P. J. Matheson, M. A. Wilson, and R. N. Garrison, “Regulation of Intestinal Blood Flow,” J. Surg. Res. 93(1), 182–196 (2000).
[Crossref] [PubMed]

L. N. Diebel, J. G. Tyburski, and S. A. Dulchavsky, “Effect of acute hemodilution on intestinal perfusion and intramucosal pH after shock,” J. Trauma 49(5), 800–805 (2000).
[Crossref] [PubMed]

1999 (1)

S. R. Zacharias, P. Offner, E. E. Moore, and J. Burch, “Damage control surgery,” AACN Clin. Issues 10(1), 95–103 (1999).
[Crossref] [PubMed]

1996 (2)

S. A. Skinner and P. E. O’Brien, “The microvascular structure of the normal colon in rats and humans,” J. Surg. Res. 61(2), 482–490 (1996).
[Crossref] [PubMed]

M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
[Crossref] [PubMed]

1995 (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]

1992 (1)

E. A. Deitch, “Multiple organ failure. Pathophysiology and potential future therapy,” Ann. Surg. 216(2), 117–134 (1992).
[Crossref] [PubMed]

1991 (1)

Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
[Crossref] [PubMed]

1989 (2)

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” Dosimetry of laser radiation in medicine and biology 5, 102–111 (1989).

G. H. Weiss, R. Nossal, and R. F. Bonner, “Statistics of penetration depth of photons re-emitted from irradiated tissue,” J. Mod. Opt. 36(3), 349–359 (1989).
[Crossref]

1979 (1)

J. W. Severinghaus, “Simple, accurate equations for human blood O2 dissociation computations,” J. Appl. Physiol. 46(3), 599–602 (1979).
[PubMed]

1977 (1)

J. Weinmann, A. Hayat, and G. Raviv, “Reflection photoplethysmography of arterial-blood-volume pulses,” Med. Biol. Eng. Comput. 15(1), 22–31 (1977).
[Crossref] [PubMed]

Abay, T. Y.

T. Y. Abay and P. A. Kyriacou, “Reflectance photoplethysmography as noninvasive monitoring of tissue blood perfusion,” IEEE Trans. Biomed. Eng. 62(9), 2187–2195 (2015).
[Crossref] [PubMed]

Akl, T.

Akl, T. J.

T. J. Akl, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Intestinal perfusion monitoring using photoplethysmography,” J. Biomed. Opt. 18(8), 087005 (2013).
[Crossref] [PubMed]

Bakker, J.

A. P. Lima, P. Beelen, and J. Bakker, “Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion,” Crit. Care Med. 30(6), 1210–1213 (2002).
[Crossref] [PubMed]

Barie, P.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
[Crossref] [PubMed]

Beelen, P.

A. P. Lima, P. Beelen, and J. Bakker, “Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion,” Crit. Care Med. 30(6), 1210–1213 (2002).
[Crossref] [PubMed]

Beilman, G.

S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
[Crossref]

Boas, D. A.

G. Themelis, H. D’Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, and M. A. Franceschini, “Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations,” J. Biomed. Opt. 12(1), 014033 (2007).
[Crossref] [PubMed]

Bokhari, F.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
[Crossref] [PubMed]

Bonadies, J.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
[Crossref] [PubMed]

Bonner, R. F.

G. H. Weiss, R. Nossal, and R. F. Bonner, “Statistics of penetration depth of photons re-emitted from irradiated tissue,” J. Mod. Opt. 36(3), 349–359 (1989).
[Crossref]

Brown, C. T.

C. L. Campbell, K. Wood, C. T. Brown, and H. Moseley, “Monte Carlo modelling of photodynamic therapy treatments comparing clustered three dimensional tumour structures with homogeneous tissue structures,” Phys. Med. Biol. 61(13), 4840–4854 (2016).
[Crossref] [PubMed]

Burch, J.

S. R. Zacharias, P. Offner, E. E. Moore, and J. Burch, “Damage control surgery,” AACN Clin. Issues 10(1), 95–103 (1999).
[Crossref] [PubMed]

Campbell, C. L.

C. L. Campbell, K. Wood, C. T. Brown, and H. Moseley, “Monte Carlo modelling of photodynamic therapy treatments comparing clustered three dimensional tumour structures with homogeneous tissue structures,” Phys. Med. Biol. 61(13), 4840–4854 (2016).
[Crossref] [PubMed]

Carlos Puyana, J.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
[Crossref] [PubMed]

Chatterjee, S.

S. Chatterjee, J. Phillips, and P. Kyriacou, “Monte Carlo investigation of the effect of blood volume and oxygen saturation on optical path in reflectance pulse oximetry,” Biomed. Phys. Eng. Express 2(6), 065018 (2016).
[Crossref]

Chen, C.-M.

C.-C. Chuang, Y.-T. Lee, C.-M. Chen, Y.-S. Hsieh, T.-C. Liu, and C.-W. Sun, “Patient-oriented simulation based on Monte Carlo algorithm by using MRI data,” Biomed. Eng. Online 11(1), 21 (2012).
[Crossref] [PubMed]

Chuang, C.-C.

C.-C. Chuang, Y.-T. Lee, C.-M. Chen, Y.-S. Hsieh, T.-C. Liu, and C.-W. Sun, “Patient-oriented simulation based on Monte Carlo algorithm by using MRI data,” Biomed. Eng. Online 11(1), 21 (2012).
[Crossref] [PubMed]

Cipone, M.

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L. Zheng, C. J. Kelly, and S. P. Colgan, “Physiologic hypoxia and oxygen homeostasis in the healthy intestine. A Review in the Theme: Cellular Responses to Hypoxia,” Am. J. Physiol. Cell Physiol. 309(6), C350–C360 (2015).
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T. J. Akl, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Intestinal perfusion monitoring using photoplethysmography,” J. Biomed. Opt. 18(8), 087005 (2013).
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C. G. Cronin, E. Delappe, D. G. Lohan, C. Roche, and J. M. Murphy, “Normal small bowel wall characteristics on MR enterography,” Eur. J. Radiol. 75(2), 207–211 (2010).
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P. Di Donato, D. Penninck, M. Pietra, M. Cipone, and A. Diana, “Ultrasonographic measurement of the relative thickness of intestinal wall layers in clinically healthly cats,” J. Feline Med. Surg. 16, 333–339 (2013).

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G. Themelis, H. D’Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, and M. A. Franceschini, “Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations,” J. Biomed. Opt. 12(1), 014033 (2007).
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P. Di Donato, D. Penninck, M. Pietra, M. Cipone, and A. Diana, “Ultrasonographic measurement of the relative thickness of intestinal wall layers in clinically healthly cats,” J. Feline Med. Surg. 16, 333–339 (2013).

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S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
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Dulchavsky, S. A.

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S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
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T. J. Akl, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Intestinal perfusion monitoring using photoplethysmography,” J. Biomed. Opt. 18(8), 087005 (2013).
[Crossref] [PubMed]

R. Long, T. King, T. Akl, M. N. Ericson, M. Wilson, G. L. Coté, and M. J. McShane, “Optofluidic phantom mimicking optical properties of porcine livers,” Biomed. Opt. Express 2(7), 1877–1892 (2011).
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G. Themelis, H. D’Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, and M. A. Franceschini, “Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations,” J. Biomed. Opt. 12(1), 014033 (2007).
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C. Fries and M. J. Midwinter, “Trauma resuscitation and damage control surgery,” Surgery 28(11), 563–567 (2010).
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Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
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Haneishi, H.

Hayat, A.

J. Weinmann, A. Hayat, and G. Raviv, “Reflection photoplethysmography of arterial-blood-volume pulses,” Med. Biol. Eng. Comput. 15(1), 22–31 (1977).
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A. Plüddemann, M. Thompson, C. Heneghan, and C. Price, “Pulse oximetry in primary care: primary care diagnostic technology update,” Br. J. Gen. Pract. 61(586), 358–359 (2011).
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D. Hidović-Rowe and E. Claridge, “Modelling and validation of spectral reflectance for the colon,” Phys. Med. Biol. 50(6), 1071–1093 (2005).
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C.-C. Chuang, Y.-T. Lee, C.-M. Chen, Y.-S. Hsieh, T.-C. Liu, and C.-W. Sun, “Patient-oriented simulation based on Monte Carlo algorithm by using MRI data,” Biomed. Eng. Online 11(1), 21 (2012).
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G. Themelis, H. D’Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, and M. A. Franceschini, “Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations,” J. Biomed. Opt. 12(1), 014033 (2007).
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M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
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Kawanishi, M.

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L. Zheng, C. J. Kelly, and S. P. Colgan, “Physiologic hypoxia and oxygen homeostasis in the healthy intestine. A Review in the Theme: Cellular Responses to Hypoxia,” Am. J. Physiol. Cell Physiol. 309(6), C350–C360 (2015).
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T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
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D. Neil Granger, L. Holm, and P. Kvietys, “The gastrointestinal circulation: physiology and pathophysiology,” Compr. Physiol. 5, 1541–1583 (2015).
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S. Chatterjee, J. Phillips, and P. Kyriacou, “Monte Carlo investigation of the effect of blood volume and oxygen saturation on optical path in reflectance pulse oximetry,” Biomed. Phys. Eng. Express 2(6), 065018 (2016).
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C. G. Cronin, E. Delappe, D. G. Lohan, C. Roche, and J. M. Murphy, “Normal small bowel wall characteristics on MR enterography,” Eur. J. Radiol. 75(2), 207–211 (2010).
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Luchette, F.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
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T. Tamura, Y. Maeda, M. Sekine, and M. Yoshida, “Wearable photoplethysmographic sensors—past and present,” Electronics (Basel) 3(2), 282–302 (2014).
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T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
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P. J. Matheson, M. A. Wilson, and R. N. Garrison, “Regulation of Intestinal Blood Flow,” J. Surg. Res. 93(1), 182–196 (2000).
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Midwinter, M. J.

C. Fries and M. J. Midwinter, “Trauma resuscitation and damage control surgery,” Surgery 28(11), 563–567 (2010).
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S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
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S. R. Zacharias, P. Offner, E. E. Moore, and J. Burch, “Damage control surgery,” AACN Clin. Issues 10(1), 95–103 (1999).
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S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
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C. L. Campbell, K. Wood, C. T. Brown, and H. Moseley, “Monte Carlo modelling of photodynamic therapy treatments comparing clustered three dimensional tumour structures with homogeneous tissue structures,” Phys. Med. Biol. 61(13), 4840–4854 (2016).
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C. G. Cronin, E. Delappe, D. G. Lohan, C. Roche, and J. M. Murphy, “Normal small bowel wall characteristics on MR enterography,” Eur. J. Radiol. 75(2), 207–211 (2010).
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F. Mustafa and M. Jaafar, “Comparison of wavelength-dependent penetration depths of lasers in different types of skin in photodynamic therapy,” Indian J. Phys. 87(3), 203–209 (2013).
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Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
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S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
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Neil Granger, D.

D. Neil Granger, L. Holm, and P. Kvietys, “The gastrointestinal circulation: physiology and pathophysiology,” Compr. Physiol. 5, 1541–1583 (2015).
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Nirala, A.

S. Kumari and A. Nirala, “Study of light propagation in human, rabbit and rat liver tissue by Monte Carlo simulation,” Optik-International Journal for Light and Electron Optics 122(9), 807–810 (2011).
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Offner, P.

S. R. Zacharias, P. Offner, E. E. Moore, and J. Burch, “Damage control surgery,” AACN Clin. Issues 10(1), 95–103 (1999).
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T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
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T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
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P. Di Donato, D. Penninck, M. Pietra, M. Cipone, and A. Diana, “Ultrasonographic measurement of the relative thickness of intestinal wall layers in clinically healthly cats,” J. Feline Med. Surg. 16, 333–339 (2013).

Perko, G.

M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
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M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
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Phillips, J.

S. Chatterjee, J. Phillips, and P. Kyriacou, “Monte Carlo investigation of the effect of blood volume and oxygen saturation on optical path in reflectance pulse oximetry,” Biomed. Phys. Eng. Express 2(6), 065018 (2016).
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Pietra, M.

P. Di Donato, D. Penninck, M. Pietra, M. Cipone, and A. Diana, “Ultrasonographic measurement of the relative thickness of intestinal wall layers in clinically healthly cats,” J. Feline Med. Surg. 16, 333–339 (2013).

Pliakos, I.

T. S. Papavramidis, A. D. Marinis, I. Pliakos, I. Kesisoglou, and N. Papavramidou, “Abdominal compartment syndrome - Intra-abdominal hypertension: Defining, diagnosing, and managing,” J. Emerg. Trauma Shock 4(2), 279–291 (2011).
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A. Plüddemann, M. Thompson, C. Heneghan, and C. Price, “Pulse oximetry in primary care: primary care diagnostic technology update,” Br. J. Gen. Pract. 61(586), 358–359 (2011).
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S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” Dosimetry of laser radiation in medicine and biology 5, 102–111 (1989).

Price, C.

A. Plüddemann, M. Thompson, C. Heneghan, and C. Price, “Pulse oximetry in primary care: primary care diagnostic technology update,” Br. J. Gen. Pract. 61(586), 358–359 (2011).
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Puyana, J.

S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
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J. Weinmann, A. Hayat, and G. Raviv, “Reflection photoplethysmography of arterial-blood-volume pulses,” Med. Biol. Eng. Comput. 15(1), 22–31 (1977).
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Rhee, P.

S. Cohn, A. Nathens, F. Moore, P. Rhee, J. Puyana, E. Moore, and G. Beilman, “Tissue Oxygen Saturation Predicts the Development of Organ Dysfunction During Traumatic Shock Resuscitation,” J. Trauma Inj. Infect. Crit. Care 62(1), 44–55 (2007).
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Roche, C.

C. G. Cronin, E. Delappe, D. G. Lohan, C. Roche, and J. M. Murphy, “Normal small bowel wall characteristics on MR enterography,” Eur. J. Radiol. 75(2), 207–211 (2010).
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S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
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M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
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T. W. Scheeren, P. Schober, and L. A. Schwarte, “Monitoring tissue oxygenation by near infrared spectroscopy (NIRS): background and current applications,” J. Clin. Monit. Comput. 26(4), 279–287 (2012).
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M. J. Perko, G. Perko, S. Just, N. H. Secher, and T. V. Schroeder, “Changes in superior mesenteric artery Doppler waveform during reduction of cardiac stroke volume and hypotension,” Ultrasound Med. Biol. 22(1), 11–18 (1996).
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Sekine, M.

T. Tamura, Y. Maeda, M. Sekine, and M. Yoshida, “Wearable photoplethysmographic sensors—past and present,” Electronics (Basel) 3(2), 282–302 (2014).
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Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
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Simon, R.

S. A. Tisherman, P. Barie, F. Bokhari, J. Bonadies, B. Daley, L. Diebel, S. R. Eachempati, S. Kurek, F. Luchette, J. Carlos Puyana, M. Schreiber, and R. Simon, “Clinical practice guideline: endpoints of resuscitation,” J. Trauma 57(4), 898–912 (2004).
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S. A. Skinner and P. E. O’Brien, “The microvascular structure of the normal colon in rats and humans,” J. Surg. Res. 61(2), 482–490 (1996).
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Sun, C.-W.

C.-C. Chuang, Y.-T. Lee, C.-M. Chen, Y.-S. Hsieh, T.-C. Liu, and C.-W. Sun, “Patient-oriented simulation based on Monte Carlo algorithm by using MRI data,” Biomed. Eng. Online 11(1), 21 (2012).
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Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
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Y. Shimada, K. Nakashima, Y. Fujiwara, T. Komatsu, M. Kawanishi, J. Takezawa, and S. Takatani, “Evaluation of a new reflectance pulse oximeter for clinical applications,” Med. Biol. Eng. Comput. 29(5), 557–561 (1991).
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Figures (14)

Fig. 1
Fig. 1

The “slab” and villi models explored by the simulations. Dimensions of the layers are shown below in Table 1: the muscularis is shown at the bottom of the tissue in the figure, and the mucosa and villi are shown at the top of the tissue in the figure.

Fig. 2
Fig. 2

a) CAD drawing of the grid pattern used to represent the submucosal vasculature, b) Zoomed in image of green rectangle in a) showing the details of the grid pattern.

Fig. 3
Fig. 3

Comparison of the two models while probing the same tissue domain. Individual percent differences between the two models are seen to not exceed 1.5% for any case explored in this set. From this surface plot it can be seen that more differences arise from changes in the optical properties of the mucosal layer as a function of the tissue perfusion.

Fig. 4
Fig. 4

Percent difference of diffuse reflectance between the villi and slab models for all cases of perfusion and oxygenation examined.

Fig. 5
Fig. 5

Optical properties of optofluidic intestinal tissue phantom.

Fig. 6
Fig. 6

a) Fabricated intestinal tissue phantom, b) Clear phantom to show details of channels.

Fig. 7
Fig. 7

Normalized reflectance intensity for each of the wavelengths of interest.

Fig. 8
Fig. 8

Modified sensor boards: a) Sensor Board variety A with green and blue LEDs, and b) Sensor Board variety B with red and blue LEDs, and c) proposed orientation of sensor on the tissue. By aligning the LEDs longitudinally geometrical consideration imposed by the cylindrical intestine are reduced. The back surface of the sensor has been made transparent here to show how the LEDs are aligned.

Fig. 9
Fig. 9

Probability distribution of fluence depth through the tissue. Estimating an intestinal wall thickness of ~2mm, most of the light incident on the tissue (>99%) will not pass through to the lumen of the intestine for these visible wavelengths. A comparison to 800 nm has been added to show the differences in the depth penetration of light between visible and NIR wavelengths.

Fig. 10
Fig. 10

Samples of time domain and frequency domain signals for each of the wavelengths used, SBR470 = 32.33 dB, SBR560 = 27.25 dB, and SBR630 = 14.57 dB.

Fig. 11
Fig. 11

Peak-to-peak amplitude measurements collected from in-vitro phantom experiments, the blue and green wavelengths show discernable differences between different perfusion conditions, while the red wavelength has only small differences with higher relative noise.

Fig. 12
Fig. 12

Changes in mean signal intensity as a function of oxygenation across the three wavelengths of interest, with each plot normalized individually.

Fig. 13
Fig. 13

Perfusion indices for each of the wavelengths used. Stronger trends are present in the blue and green signals where only a weak trend is present in the red signal, with the dependence upon oxygenation seen to be minimal.

Fig. 14
Fig. 14

The modulation ratio between the 470 nm and 560 nm signals and between the 470 nm and 630 nm signals, changes in the ratio can be seen to be more of a function of oxygenation than of perfusion.

Tables (4)

Tables Icon

Table 1 Optical properties and dimensions of the layers used for the simulations

Tables Icon

Table 2 Optical properties of tissue phantoms

Tables Icon

Table 3 Optical properties of blood phantoms compared to optical properties used in simulation

Tables Icon

Table 4 Ratio of absorbance between oxygenated and deoxygenated blood for different wavelengths

Equations (10)

Equations on this page are rendered with MathJax. Learn more.

d=0.0033(1+ P Arterial 100 )
x λ =0.12 P Tissue 100 ( S O 2 100 x Hb O 2 ,λ +(1 S O 2 100 ) x Hb,λ )+(10.12 P Tissue 100 ) x Mucosa
P O 2 ¯ = 1 z v s d i d i + z v s P O 2 Artery (10.25( z l ))dz
P O 2 ¯ =P O 2 Artery (1 d i 4l s z v 8l )
s= log(N(0,1)) μ t
S O 2 ¯ = P O 2 ¯ 3 +150 P O 2 ¯ P O 2 ¯ 3 +150 P O 2 ¯ +23400 100
P I λ = A C λ D C λ
R= P I λ 1 P I λ 2
Z r,λ = 0.476 r 0.5 ( μ a μ s ' ) 0.25
P z,r =8 (3 μ a μ s ' ) 0.5 z r e (48 μ a μ s ' ) 0.5 z 2 r

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