Abstract

To simulate the hemodynamic effects in the feet in response to a thigh cuff occlusion, we have developed a multi-compartmental model in which the circulatory system for the leg is represented by its electrical equivalents. Dynamic vascular optical tomographic imaging data previously obtained from 20 patients with peripheral artery disease (PAD) and 20 healthy subjects is used to test the model. Analyzing the clinical data with the support of the model yields diagnostic specificity and sensitivity in the 90-95% range, significantly higher than previously reported.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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    [Crossref] [PubMed]
  6. Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
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    [Crossref] [PubMed]
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  23. N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
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    [Crossref] [PubMed]
  26. T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
    [Crossref] [PubMed]
  27. J. M. Masciotti, J. M. Lasker, and A. H. Hielscher, “Digital lock-in algorithm for biomedical spectroscopy and imaging instruments with multiple modulated sources,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2006).
    [Crossref]
  28. H. K. Kim, M. Flexman, D. J. Yamashiro, J. J. Kandel, and A. H. Hielscher, “PDE-constrained multispectral imaging of tissue chromophores with the equation of radiative transfer,” Biomed. Opt. Express 1(3), 812–824 (2010).
    [Crossref] [PubMed]
  29. D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
    [Crossref] [PubMed]

2015 (1)

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

2014 (1)

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

2012 (2)

M. A. Khalil, H. K. Kim, I. K. Kim, M. Flexman, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Dynamic diffuse optical tomography imaging of peripheral arterial disease,” Biomed. Opt. Express 3(9), 2288–2298 (2012).
[Crossref] [PubMed]

A. W. Pollak, P. T. Norton, and C. M. Kramer, “Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions,” Circ Cardiovasc Imaging 5(6), 797–807 (2012).
[Crossref] [PubMed]

2011 (1)

Y. Shi, P. Lawford, and R. Hose, “Review of zero-D and 1-D models of blood flow in the cardiovascular system,” Biomed. Eng. Online 10(33), 33 (2011).
[Crossref] [PubMed]

2010 (2)

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

H. K. Kim, M. Flexman, D. J. Yamashiro, J. J. Kandel, and A. H. Hielscher, “PDE-constrained multispectral imaging of tissue chromophores with the equation of radiative transfer,” Biomed. Opt. Express 1(3), 812–824 (2010).
[Crossref] [PubMed]

2009 (3)

D. M. N. M. Al-Qaisi, D. H. King, S. Kaddoura, and M. Hamady, “Imaging of peripheral vascular disease,” Reports in Medical Imaging 2, 25–34 (2009).
[Crossref]

N. Westerhof, J. W. Lankhaar, and B. E. Westerhof, “The arterial Windkessel,” Med. Biol. Eng. Comput. 47(2), 131–141 (2009).
[Crossref] [PubMed]

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

2007 (1)

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

2006 (1)

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

2005 (2)

American Diabetes Association, “Peripheral Arterial Disease in People with Diabetes,” J. Am. Podiatr. Med. Assoc. 95(3), 309–319 (2005).
[Crossref]

H. L. Gornik and J. A. Beckman, “Cardiology patient page. Peripheral arterial disease,” Circulation 111(13), e169–e172 (2005).
[Crossref] [PubMed]

2004 (2)

A. Stoyioglou and M. R. Jaff, “Medical treatment of peripheral arterial disease: a comprehensive review,” J. Vasc. Interv. Radiol. 15(11), 1197–1207 (2004).
[Crossref] [PubMed]

M. S. Olufsen and A. Nadim, “On deriving lumped models for blood flow and pressure in the systemic arteries,” Math. Biosci. Eng. 1(1), 61–80 (2004).
[Crossref] [PubMed]

2003 (1)

American Diabetes Association, “Peripheral arterial disease in people with diabetes,” Diabetes Care 26(12), 3333–3341 (2003).
[Crossref] [PubMed]

2002 (2)

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
[Crossref] [PubMed]

2001 (1)

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

1999 (1)

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

1996 (1)

N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
[PubMed]

1992 (1)

N. Stergiopulos, D. F. Young, and T. R. Rogge, “Computer simulation of arterial flow with applications to arterial and aortic stenoses,” J. Biomech. 25(12), 1477–1488 (1992).
[Crossref] [PubMed]

1991 (1)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

1974 (1)

J. K. Raines, M. Y. Jaffrin, and A. H. Shapiro, “A computer simulation of arterial dynamics in the human leg,” J. Biomech. 7(1), 77–91 (1974).
[Crossref] [PubMed]

Al-Qaisi, D. M. N. M.

D. M. N. M. Al-Qaisi, D. H. King, S. Kaddoura, and M. Hamady, “Imaging of peripheral vascular disease,” Reports in Medical Imaging 2, 25–34 (2009).
[Crossref]

Amato, F.

G. Fragomeni, A. Merola, S. De Franciscis, and F. Amato, “A Haemodynamic Model of the Venous Network of the Lower Limbs,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2007), pp. 1002–1005.
[Crossref]

Andreisek, G.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Beckman, J. A.

H. L. Gornik and J. A. Beckman, “Cardiology patient page. Peripheral arterial disease,” Circulation 111(13), e169–e172 (2005).
[Crossref] [PubMed]

Chang, W.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Clement, D. L.

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

Cohn, J. N.

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

Dachun Xu,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Dayal, R.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

M. A. Khalil, H. K. Kim, I. K. Kim, M. Flexman, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Dynamic diffuse optical tomography imaging of peripheral arterial disease,” Biomed. Opt. Express 3(9), 2288–2298 (2012).
[Crossref] [PubMed]

Dayi Hu, S. L.

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

De Bruyne, L.

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

De Buyzere, M. M.

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

De Franciscis, S.

G. Fragomeni, A. Merola, S. De Franciscis, and F. Amato, “A Haemodynamic Model of the Venous Network of the Lower Limbs,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2007), pp. 1002–1005.
[Crossref]

Duprez, D.

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Duprez, D. A.

D. A. Duprez, M. M. De Buyzere, L. De Bruyne, D. L. Clement, and J. N. Cohn, “Small and large artery elasticity indices in peripheral arterial occlusive disease (PAOD),” Vasc. Med. 6(4), 211–214 (2001).
[Crossref] [PubMed]

Egawa, K.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Fedosov, I. V.

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

Fisher, A. C.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Flexman, M.

Flotte, T.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Fragomeni, G.

G. Fragomeni, A. Merola, S. De Franciscis, and F. Amato, “A Haemodynamic Model of the Venous Network of the Lower Limbs,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2007), pp. 1002–1005.
[Crossref]

Fujimoto, J. G.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Fujimoto, K.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Giudiceandrea, A.

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Goepfert, K.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Gornik, H. L.

H. L. Gornik and J. A. Beckman, “Cardiology patient page. Peripheral arterial disease,” Circulation 111(13), e169–e172 (2005).
[Crossref] [PubMed]

Goulermas, J. Y.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Gregory, K.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Hamady, M.

D. M. N. M. Al-Qaisi, D. H. King, S. Kaddoura, and M. Hamady, “Imaging of peripheral vascular disease,” Reports in Medical Imaging 2, 25–34 (2009).
[Crossref]

Hamilton, G.

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Hee, M. R.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Hervo, P.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Hielscher, A. H.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

M. A. Khalil, H. K. Kim, I. K. Kim, M. Flexman, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Dynamic diffuse optical tomography imaging of peripheral arterial disease,” Biomed. Opt. Express 3(9), 2288–2298 (2012).
[Crossref] [PubMed]

H. K. Kim, M. Flexman, D. J. Yamashiro, J. J. Kandel, and A. H. Hielscher, “PDE-constrained multispectral imaging of tissue chromophores with the equation of radiative transfer,” Biomed. Opt. Express 1(3), 812–824 (2010).
[Crossref] [PubMed]

J. M. Masciotti, J. M. Lasker, and A. H. Hielscher, “Digital lock-in algorithm for biomedical spectroscopy and imaging instruments with multiple modulated sources,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2006).
[Crossref]

Hisatomi, A.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Hoi, J. W.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

Hose, R.

Y. Shi, P. Lawford, and R. Hose, “Review of zero-D and 1-D models of blood flow in the cardiovascular system,” Biomed. Eng. Online 10(33), 33 (2011).
[Crossref] [PubMed]

Huang, D.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Inubushi, T.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Izzo, J. L.

T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
[Crossref] [PubMed]

Jaff, M. R.

A. Stoyioglou and M. R. Jaff, “Medical treatment of peripheral arterial disease: a comprehensive review,” J. Vasc. Interv. Radiol. 15(11), 1197–1207 (2004).
[Crossref] [PubMed]

Jaffrin, M. Y.

J. K. Raines, M. Y. Jaffrin, and A. H. Shapiro, “A computer simulation of arterial dynamics in the human leg,” J. Biomech. 7(1), 77–91 (1974).
[Crossref] [PubMed]

Jue Li,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Kaddoura, S.

D. M. N. M. Al-Qaisi, D. H. King, S. Kaddoura, and M. Hamady, “Imaging of peripheral vascular disease,” Reports in Medical Imaging 2, 25–34 (2009).
[Crossref]

Kandel, J. J.

Kashiwagi, A.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Khalil, M. A.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

M. A. Khalil, H. K. Kim, I. K. Kim, M. Flexman, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Dynamic diffuse optical tomography imaging of peripheral arterial disease,” Biomed. Opt. Express 3(9), 2288–2298 (2012).
[Crossref] [PubMed]

Kim, H. K.

Kim, I.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

Kim, I. K.

King, D. H.

D. M. N. M. Al-Qaisi, D. H. King, S. Kaddoura, and M. Hamady, “Imaging of peripheral vascular disease,” Reports in Medical Imaging 2, 25–34 (2009).
[Crossref]

Klochkov, V. A.

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

Koppensteiner, R.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Kramer, C. M.

A. W. Pollak, P. T. Norton, and C. M. Kramer, “Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions,” Circ Cardiovasc Imaging 5(6), 797–807 (2012).
[Crossref] [PubMed]

Kurochkin, M. A.

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

Lankhaar, J. W.

N. Westerhof, J. W. Lankhaar, and B. E. Westerhof, “The arterial Windkessel,” Med. Biol. Eng. Comput. 47(2), 131–141 (2009).
[Crossref] [PubMed]

Lasker, J. M.

J. M. Masciotti, J. M. Lasker, and A. H. Hielscher, “Digital lock-in algorithm for biomedical spectroscopy and imaging instruments with multiple modulated sources,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2006).
[Crossref]

Lawford, P.

Y. Shi, P. Lawford, and R. Hose, “Review of zero-D and 1-D models of blood flow in the cardiovascular system,” Biomed. Eng. Online 10(33), 33 (2011).
[Crossref] [PubMed]

Liling Zou,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Lin, C. P.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Maegawa, H.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Manning, T. S.

T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
[Crossref] [PubMed]

Masciotti, J. M.

J. M. Masciotti, J. M. Lasker, and A. H. Hielscher, “Digital lock-in algorithm for biomedical spectroscopy and imaging instruments with multiple modulated sources,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2006).
[Crossref]

Meister, J. J.

N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
[PubMed]

Merola, A.

G. Fragomeni, A. Merola, S. De Franciscis, and F. Amato, “A Haemodynamic Model of the Venous Network of the Lower Limbs,” in Proceedings of IEEE Conference on Engineering in Medicine and Biology Society (IEEE, 2007), pp. 1002–1005.
[Crossref]

Morikawa, S.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Nadim, A.

M. S. Olufsen and A. Nadim, “On deriving lumped models for blood flow and pressure in the systemic arteries,” Math. Biosci. Eng. 1(1), 61–80 (2004).
[Crossref] [PubMed]

Nanz, D.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Nishio, Y.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Norton, P. T.

A. W. Pollak, P. T. Norton, and C. M. Kramer, “Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions,” Circ Cardiovasc Imaging 5(6), 797–807 (2012).
[Crossref] [PubMed]

O’Rourke, M. F.

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Olufsen, M. S.

M. S. Olufsen and A. Nadim, “On deriving lumped models for blood flow and pressure in the systemic arteries,” Math. Biosci. Eng. 1(1), 61–80 (2004).
[Crossref] [PubMed]

Pagoto,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Pfammatter, T.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Plante, G. E.

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Pollak, A. W.

A. W. Pollak, P. T. Norton, and C. M. Kramer, “Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions,” Circ Cardiovasc Imaging 5(6), 797–807 (2012).
[Crossref] [PubMed]

Postnov, D. E.

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

Puliafito, C. A.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Raines, J. K.

J. K. Raines, M. Y. Jaffrin, and A. H. Shapiro, “A computer simulation of arterial dynamics in the human leg,” J. Biomech. 7(1), 77–91 (1974).
[Crossref] [PubMed]

Rogge, T. R.

N. Stergiopulos, D. F. Young, and T. R. Rogge, “Computer simulation of arterial flow with applications to arterial and aortic stenoses,” J. Biomech. 25(12), 1477–1488 (1992).
[Crossref] [PubMed]

Salacinski, H. J.

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Schuman, J. S.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Seifalian, A. M.

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Sfirakis, P.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Shapiro, A. H.

J. K. Raines, M. Y. Jaffrin, and A. H. Shapiro, “A computer simulation of arterial dynamics in the human leg,” J. Biomech. 7(1), 77–91 (1974).
[Crossref] [PubMed]

Shi, Y.

Y. Shi, P. Lawford, and R. Hose, “Review of zero-D and 1-D models of blood flow in the cardiovascular system,” Biomed. Eng. Online 10(33), 33 (2011).
[Crossref] [PubMed]

Shrikhande, G.

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

M. A. Khalil, H. K. Kim, I. K. Kim, M. Flexman, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Dynamic diffuse optical tomography imaging of peripheral arterial disease,” Biomed. Opt. Express 3(9), 2288–2298 (2012).
[Crossref] [PubMed]

Shykoff, B. E.

T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
[Crossref] [PubMed]

Staessen, J. A.

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Stergiopulos, N.

N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
[PubMed]

N. Stergiopulos, D. F. Young, and T. R. Rogge, “Computer simulation of arterial flow with applications to arterial and aortic stenoses,” J. Biomech. 25(12), 1477–1488 (1992).
[Crossref] [PubMed]

Stinson, W. G.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Stiukhina, E. S.

E. S. Stiukhina, M. A. Kurochkin, V. A. Klochkov, I. V. Fedosov, and D. E. Postnov, “Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model,” Proc. SPIE 9448, 94481K (2014).

Stoyioglou, A.

A. Stoyioglou and M. R. Jaff, “Medical treatment of peripheral arterial disease: a comprehensive review,” J. Vasc. Interv. Radiol. 15(11), 1197–1207 (2004).
[Crossref] [PubMed]

Suzuki, E.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Swanson, E. A.

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

Tai, N. R. M.

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Theodorakis, G.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Tsanas, A.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Tsiapras, D.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Vartela, V.

A. Tsanas, J. Y. Goulermas, V. Vartela, D. Tsiapras, G. Theodorakis, A. C. Fisher, and P. Sfirakis, “The Windkessel model revisited: a qualitative analysis of the circulatory system,” Med. Eng. Phys. 31(5), 581–588 (2009).
[Crossref] [PubMed]

Vlachopoulos, C.

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Weishaupt, D.

G. Andreisek, T. Pfammatter, K. Goepfert, D. Nanz, P. Hervo, R. Koppensteiner, and D. Weishaupt, “Peripheral arteries in diabetic patients: standard bolus-chase and time-resolved MR angiography,” Radiology 242(2), 610–620 (2007).
[Crossref] [PubMed]

Westerhof, B. E.

N. Westerhof, J. W. Lankhaar, and B. E. Westerhof, “The arterial Windkessel,” Med. Biol. Eng. Comput. 47(2), 131–141 (2009).
[Crossref] [PubMed]

Westerhof, N.

N. Westerhof, J. W. Lankhaar, and B. E. Westerhof, “The arterial Windkessel,” Med. Biol. Eng. Comput. 47(2), 131–141 (2009).
[Crossref] [PubMed]

N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
[PubMed]

Yamashiro, D. J.

Yawei Xu,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Yoshimura, T.

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Young, D. F.

N. Stergiopulos, D. F. Young, and T. R. Rogge, “Computer simulation of arterial flow with applications to arterial and aortic stenoses,” J. Biomech. 25(12), 1477–1488 (1992).
[Crossref] [PubMed]

Yunsheng Ma,

Dachun Xu, Jue Li, Liling Zou, Yawei Xu, S. L. Dayi Hu, Pagoto, and Yunsheng Ma, “Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review,” Vasc. Med. 15(5), 361–369 (2010).
[Crossref] [PubMed]

Am. J. Hypertens. (1)

M. F. O’Rourke, J. A. Staessen, C. Vlachopoulos, D. Duprez, and G. E. Plante, “Clinical applications of arterial stiffness; definitions and reference values,” Am. J. Hypertens. 15(5), 426–444 (2002).
[Crossref] [PubMed]

Am. J. Physiol. (1)

N. Stergiopulos, J. J. Meister, and N. Westerhof, “Determinants of stroke volume and systolic and diastolic aortic pressure,” Am. J. Physiol. 270(6 Pt 2), H2050–H2059 (1996).
[PubMed]

Biomed. Eng. Online (1)

Y. Shi, P. Lawford, and R. Hose, “Review of zero-D and 1-D models of blood flow in the cardiovascular system,” Biomed. Eng. Online 10(33), 33 (2011).
[Crossref] [PubMed]

Biomed. Opt. Express (2)

Circ Cardiovasc Imaging (1)

A. W. Pollak, P. T. Norton, and C. M. Kramer, “Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions,” Circ Cardiovasc Imaging 5(6), 797–807 (2012).
[Crossref] [PubMed]

Circulation (1)

H. L. Gornik and J. A. Beckman, “Cardiology patient page. Peripheral arterial disease,” Circulation 111(13), e169–e172 (2005).
[Crossref] [PubMed]

Diabetes Care (2)

American Diabetes Association, “Peripheral arterial disease in people with diabetes,” Diabetes Care 26(12), 3333–3341 (2003).
[Crossref] [PubMed]

T. Yoshimura, E. Suzuki, K. Egawa, Y. Nishio, H. Maegawa, S. Morikawa, T. Inubushi, A. Hisatomi, K. Fujimoto, and A. Kashiwagi, “Low blood flow estimates in lower-leg arteries predict cardiovascular events in Japanese patients with type 2 diabetes with normal ankle-brachial indexes,” Diabetes Care 29(8), 1884–1890 (2006).
[Crossref] [PubMed]

Eur. J. Vasc. Endovasc. Surg. (1)

M. A. Khalil, H. K. Kim, J. W. Hoi, I. Kim, R. Dayal, G. Shrikhande, and A. H. Hielscher, “Detection of Peripheral Arterial Disease Within the Foot Using Vascular Optical Tomographic Imaging: A Clinical Pilot Study,” Eur. J. Vasc. Endovasc. Surg. 49(1), 83–89 (2015).
[Crossref] [PubMed]

Hypertension (1)

T. S. Manning, B. E. Shykoff, and J. L. Izzo, “Validity and reliability of diastolic pulse contour analysis (windkessel model) in humans,” Hypertension 39(5), 963–968 (2002).
[Crossref] [PubMed]

J. Am. Podiatr. Med. Assoc. (1)

American Diabetes Association, “Peripheral Arterial Disease in People with Diabetes,” J. Am. Podiatr. Med. Assoc. 95(3), 309–319 (2005).
[Crossref]

J. Biomech. (2)

J. K. Raines, M. Y. Jaffrin, and A. H. Shapiro, “A computer simulation of arterial dynamics in the human leg,” J. Biomech. 7(1), 77–91 (1974).
[Crossref] [PubMed]

N. Stergiopulos, D. F. Young, and T. R. Rogge, “Computer simulation of arterial flow with applications to arterial and aortic stenoses,” J. Biomech. 25(12), 1477–1488 (1992).
[Crossref] [PubMed]

J. Vasc. Interv. Radiol. (1)

A. Stoyioglou and M. R. Jaff, “Medical treatment of peripheral arterial disease: a comprehensive review,” J. Vasc. Interv. Radiol. 15(11), 1197–1207 (2004).
[Crossref] [PubMed]

J. Vasc. Surg. (1)

N. R. M. Tai, A. Giudiceandrea, H. J. Salacinski, A. M. Seifalian, and G. Hamilton, “In vivo femoropopliteal arterial wall compliance in subjects with and without lower limb vascular disease,” J. Vasc. Surg. 30(5), 936–945 (1999).
[Crossref] [PubMed]

Math. Biosci. Eng. (1)

M. S. Olufsen and A. Nadim, “On deriving lumped models for blood flow and pressure in the systemic arteries,” Math. Biosci. Eng. 1(1), 61–80 (2004).
[Crossref] [PubMed]

Med. Biol. Eng. Comput. (1)

N. Westerhof, J. W. Lankhaar, and B. E. Westerhof, “The arterial Windkessel,” Med. Biol. Eng. Comput. 47(2), 131–141 (2009).
[Crossref] [PubMed]

Med. Eng. Phys. (1)

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Radiology (1)

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[Crossref]

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Figures (8)

Fig. 1
Fig. 1 Schematic of the model implemented.
Fig. 2
Fig. 2 Example of the time-dependent functions RV(t) (blue) and RA(t) (red) for a specific combination of the simulation parameters for a cuff inflation/deflation cycle.
Fig. 3
Fig. 3 A - The estimated cross-correlation coefficients ρ(h,W) in the cross sectional image of the foot calculated for [HbT] = [HbO2] + [Hb]. B - The temporal map showing the percentage change of total hemoglobin distribution considering the entire cross-sectional area (red dotted line) and only the regions in which ρ≥0.7 (blue line).
Fig. 4
Fig. 4 Example of a typical hemodynamic response to a cuff inflation/ deflation (120 mmHg) recorded with our VOTI system (black curve). Also shown are 10 “best” fittings (green dotted lines) obtained automatically by the program. The cuff inflation starts at 10 seconds and lasts for 60 seconds.
Fig. 5
Fig. 5 Examples of the effects of X, RCUFF_Vm, RV and RA on the curves while keeping constant the other parameters. A- The effect of the cuff on the arteries (X) is the main cause in the creation of the experimentally observed plateau; B- Increasing the effect of the cuff (RCUFF_Vm) creates a deeper plateau; C- The vein resistance (RV) affects the curve only after the cuff starts to deflate; D- The main arteries resistance (RA) effect is limited to a slight change in the slope when the other parameters are kept to their minimum values.
Fig. 6
Fig. 6 Mean and Standard Deviations of the average total system resistance during a cuff inflation estimated in Healthy and PAD patients. The mean values and standard deviations are respectively 27.1 ± 3.9 [mmHg s/mL] in Healthy and 33.9 ± 2.1 [mmHg s/mL] in PAD patients.
Fig. 7
Fig. 7 ROC curve to distinguish between healthy and PAD patients obtained considering the total system resistance when the cuff is inflated.
Fig. 8
Fig. 8 Train and Test results for both the model resistance (M) and the percentage change in total hemoglobin (PC) considering 500 different combinations of patients for each bar graph. The bar graphs are zoomed in the 60%-100% range to better visualize the changes in the mean values. Between 20 and 32 patients were used for the training (numbers on the left of the slash) and the remaining patients (from 20 to 8) were used for the test (numbers on the right of the slash). In black is shown the standard deviation obtained.

Tables (1)

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Table 1 Variables Range

Equations (7)

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{ d V C A dt =-( 1 C A × R A ( t ) + 1 C A × R AO )× V C A + 1 C A × R AO × V C AO + V Heart ( t ) C A × R A ( t ) d V C AO dt = 1 C AO × R AO × V C A -( 1 C AO × R AO + 1 C AO × R C )× V C AO + 1 C AO × R C × V C C d V C C dt = 1 C C × R C × V C AO -( 1 C C × R C + 1 C C × R VN )× V C C + 1 C C × R VN × V C V d V C V dt = 1 C V × R VN × V C C -( 1 C V × R V ( t ) + 1 C V × R VN )× V C V
R V ( t )= R V ( 0 )+ R CUFFV ( t )
R CUFFV ( t )={ 0 R CUFFVm ×( exp( t )exp( t start_i ) )/( exp( t end_i )exp( t start_i ) ) R CUFFVm R CUFFVm ×( exp( t end_d ( t t start_d ) )exp( t start_d ) )/( exp( t end_d )exp( t start_d ) ) 0 for { t>0t t start_i t> t start_i t t end_i t> t end_i t t start_d t> t start_d t t end_d t> t end_d
R A ( t )= R A ( 0 )+ R CUFFA ( t )
R CUFFA ( t )={ 0 X× R CUFFVm ×( exp( t )exp( t start_i +Δt ) )/( exp( t end_i )exp( t start_i +Δt ) ) X× R CUFFVm X× R CUFFVm ×( exp( t end_d ( t t start_d ) )exp( t start_d ) )/( exp( t end_d )exp( t start_d ) ) 0 for { t>0t t start_i +Δt t> t start_i +Δtt t end_i t> t end_i t t start_d t> t start_d t t end_d t> t end_d
ρ( h,W )= i=1 N ( h i μ h )( W i μ W ) i=1 N ( h i μ h ) 2 j=1 N ( W j μ W ) 2
R T = R A (0)+X R CUFFVm + R AO + R C + R VN + R V (0)+ R CUFFVm

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