A review of electrical impedance tomography in lung applications: Theory and algorithms for absolute images
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Citações na Scopus
63
Tipo de produção
article
Data de publicação
2019
Título da Revista
ISSN da Revista
Título do Volume
Editora
PERGAMON-ELSEVIER SCIENCE LTD
Autores
MARTINS, Thiago de Castro
SATO, Andre Kubagawa
MOURA, Fernando Silva de
CAMARGO, Erick Dario Leon Bueno de
SILVA, Olavo Luppi
SANTOS, Talles Batista Rattis
ZHAO, Zhanqi
MOELLER, Knut
MUELLER, Jennifer L.
Citação
ANNUAL REVIEWS IN CONTROL, v.48, p.442-471, 2019
Resumo
Electrical Impedance Tomography (EIT) is under fast development. The present paper is a review of some procedures that have contributed to improve spatial resolution and material properties accuracy, admitivity or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve clinical acceptance of EIT. The Control Theory, State Observers more specifically, have a developed theory that can be used for designing and operating EIT devices. Electrode placement, current injection strategy and electrode electric potential measurements strategy should maximize the number of observable and controllable directions of the state vector space. A non-linear stochastic state observer, the Unscented Kalman Filter, is used directly for reconstructing absolute EIT images. Historically, difference images were explored first since they are more stable in the presence of modelling errors. Absolute images require more detailed models of contact impedance, stray capacitance and properly refined finite element mesh, where the electric potential gradient is high. Parallelization of the forward program computation is necessary since the solution of the inverse problem often requires frequent solutions of the forward problem. Several reconstruction algorithms benefit from the Bayesian inverse problem approach and the concept of prior information. Anatomic and physiological information are used to form the prior information. An already tested methodology is presented to build the prior probability density function using an ensemble of CT scans and in vivo impedance measurements. Eight absolute EIT image algorithms are presented.
Palavras-chave
Electrical impedance tomography, Anatomical atlas, Bayesian inference, Massive parallel computing, Approximation error, ARDS, Lung diseases
Referências
- Adams R., 1975, SOBOLEV SPACES
- Adler A, 1996, IEEE T MED IMAGING, V15, P170, DOI 10.1109/42.491418
- Adler A, 2012, PHYSIOL MEAS, V33, P679, DOI 10.1088/0967-3334/33/5/679
- Allen GB, 2005, J APPL PHYSIOL, V99, P723, DOI 10.1152/japplphysiol.01339.2004
- Alquier P, 2016, STAT COMPUT, V26, P29, DOI 10.1007/s11222-014-9521-x
- Alsaker M., 2018, J COMPUTATIONAL APPL
- Alsaker M., 2017, INVERSE PROBLEMS IMA
- Alsaker M, 2018, INVERSE PROBL IMAG, V12, P883, DOI 10.3934/ipi.2018037
- Alsaker M, 2016, SIAM J IMAGING SCI, V9, P1619, DOI 10.1137/15M1020137
- Bachmann MC, 2018, CRIT CARE, V22, DOI 10.1186/s13054-018-2195-6
- Bates JHT, 2009, LUNG MECHANICS: AN INVERSE MODELING APPROACH, P1
- Bates JHT, 2002, J APPL PHYSIOL, V93, P705, DOI 10.1152/japplphysiol.01274.2001
- Bera TK, 2012, MECHATRONIC & INNOVATIVE APPLICATIONS, P3
- Bikowski J, 2008, INVERSE PROBL IMAG, V2, P43
- Bikowski J, 2011, INVERSE PROBL, V27, DOI 10.1088/0266-5611/27/1/015002
- Bjorck A., 1996, NUMERICAL METHODS LE
- Bockris J. O. M., 1998, MODERN ELECTROCHEM A, V2A
- Borges JB, 2012, J APPL PHYSIOL, V112, P225, DOI 10.1152/japplphysiol.01090.2010
- Borsic A, 2010, IEEE T MED IMAGING, V29, P44, DOI 10.1109/TMI.2009.2022540
- Brovman EY, 2018, J LAPAROENDOSC ADV S, V28, P1463, DOI 10.1089/lap.2018.0297
- Brower RG, 2004, NEW ENGL J MED, V351, P327
- Brown B. H., 2003, Journal of Medical Engineering & Technology, V27, P97, DOI 10.1080/0309190021000059687
- Brown B H, 1987, Clin Phys Physiol Meas, V8 Suppl A, P91, DOI 10.1088/0143-0815/8/4A/012
- Brown RM, 1997, COMMUN PART DIFF EQ, V22, P1009, DOI 10.1080/03605309708821292
- CALDERON AP, 1980, SEM NUM AN ITS APPL
- Calvetti D, 2015, INVERSE PROBL IMAG, V9, P749, DOI 10.3934/ipi.2015.9.749
- Calvetti D, 2015, INVERSE PROBL IMAG, V9, P767, DOI 10.3934/ipi.2015.9.767
- Camargo E. D. L B., 2013, THESIS
- Carver B., 2012, MED IMAGING TECHNIQU
- Cheney M, 1999, SIAM REV, V41, P85, DOI 10.1137/S0036144598333613
- CHENG KS, 1989, IEEE T BIO-MED ENG, V36, P918, DOI 10.1109/10.35300
- Cinnella G, 2015, ANESTHESIOLOGY, V123, P1113, DOI 10.1097/ALN.0000000000000862
- Clay MT, 2002, IEEE T MED IMAGING, V21, P629, DOI 10.1109/TMI.2002.800572
- Cornean H., 2006, Journal of Inverse and ILL-Posed Problems, V14, P111, DOI 10.1163/156939406777571102
- Darde J, 2016, ESAIM-MATH MODEL NUM, V50, P415, DOI 10.1051/m2an/2015049
- Darde J, 2013, INVERSE PROBL, V29, DOI 10.1088/0266-5611/29/8/085004
- Lima CR, 2007, MEAS SCI TECHNOL, V18, P2847, DOI 10.1088/0957-0233/18/9/014
- DeAngelo M, 2010, PHYSIOL MEAS, V31, P221, DOI 10.1088/0967-3334/31/2/008
- Delbary F., APPL ANAL, P1
- Delbary F., INVERSE PROBLEMS IMA
- Delbary F, 2011, J PHYS CONF SER, V290, DOI 10.1088/1742-6596/290/1/012003
- Demidenko E, 2005, IEEE T BIO-MED ENG, V52, P238, DOI 10.1109/TBME.2004.840506
- Denai MA, 2010, IEEE T INF TECHNOL B, V14, P641, DOI 10.1109/TITB.2009.2036010
- Dodd M, 2014, INVERSE PROBL IMAG, V8, P1013, DOI 10.3934/ipi.2014.8.1013
- Eichler L, 2018, OBES SURG, V28, P122, DOI 10.1007/s11695-017-2794-3
- Engrand P., 1997, 5 INT C NUCL ENG NIC, P1
- Eronia N, 2017, ANN INTENSIVE CARE, V7, DOI 10.1186/s13613-017-0299-9
- EYUBOGLU BM, 1995, PHYSIOL MEAS, V16, pA191, DOI 10.1088/0967-3334/16/3A/018
- EYUBOGLU BM, 1989, IEEE ENG MED BIOL, V8, P39, DOI 10.1109/51.32404
- Faddeev L. D., 1966, SOV PHYS DOKL, V10, P1033
- Ferguson ND, 2012, INTENS CARE MED, V38, P1573, DOI 10.1007/s00134-012-2682-1
- Franchineau G, 2017, AM J RESP CRIT CARE, V196, P447, DOI 10.1164/rccm.201605-1055OC
- Francini E, 2000, INVERSE PROBL, V16, P107, DOI 10.1088/0266-5611/16/1/309
- Frerichs I, 1998, ACTA ANAESTH SCAND, V42, P721, DOI 10.1111/j.1399-6576.1998.tb05308.x
- Frerichs I, 2016, PHYSIOL MEAS, V37, P698, DOI 10.1088/0967-3334/37/6/698
- Frerichs I, 2002, IEEE T MED IMAGING, V21, P646, DOI 10.1109/TMI.2002.800585
- Frerichs I, 2017, THORAX, V72, P83, DOI 10.1136/thoraxjnl-2016-208357
- Frerichs I, 2012, J CRIT CARE, V27, P172, DOI 10.1016/j.jcrc.2011.04.008
- Gabriel S, 1996, PHYS MED BIOL, V41, P2251, DOI 10.1088/0031-9155/41/11/002
- GEDDES LA, 1971, MED BIOL ENG, V9, P511, DOI 10.1007/BF02474708
- Golub GH, 2010, PRINC SER APPL MATH, P1
- Gong B, 2015, EXPERT REV RESP MED, V9, P721, DOI 10.1586/17476348.2015.1103650
- Gow C-H., 2018, IFAC PAPERSONLINE, V51, P52
- Grychtol B, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0103045
- Hamilton SJ, 2018, PHYSIOL MEAS, V39, DOI 10.1088/1361-6579/aac8b1
- Hamilton SJ, 2017, PHYSIOL MEAS, V38, P1176, DOI 10.1088/1361-6579/aa63d7
- Hamilton SJ, 2012, INVERSE PROBL, V28, DOI 10.1088/0266-5611/28/9/095005
- Hamilton SJ, 2017, IEEE T MED IMAGING, V36, P457, DOI 10.1109/TMI.2016.2613511
- Hanke M, 2003, INVERSE PROBL, V19, pS65, DOI 10.1088/0266-5611/19/6/055
- Hanke M, 2011, MATH MOD METH APPL S, V21, P1395, DOI 10.1142/S0218202511005362
- Heines S. J. H., 2018, J CLIN MONITORING CO
- Herrera C. N. L, 2012, THESIS
- Herrera CNL, 2015, IEEE T MED IMAGING, V34, P267, DOI 10.1109/TMI.2014.2354333
- HOLDER DS, 2005, ELECT IMPEDANCE TOMO
- Hsu YL, 2017, PHYSIOL MEAS, V38, P1193, DOI 10.1088/1361-6579/aa66fd
- HUA P, 1993, IEEE T BIO-MED ENG, V40, P335, DOI 10.1109/10.222326
- Hua P, 1988, Clin Phys Physiol Meas, V9 Suppl A, P137, DOI 10.1088/0143-0815/9/4A/023
- Hyvonen N, 2017, SIAM J APPL MATH, V77, P2250, DOI 10.1137/17M1124292
- Isaacson D, 2006, PHYSIOL MEAS, V27, pS43, DOI 10.1088/0967-3334/27/5/S04
- Isaacson D, 2004, IEEE T MED IMAGING, V23, P821, DOI 10.1109/TMI.2004.827482
- Jang J, 2015, PHYSIOL MEAS, V36, P1179, DOI 10.1088/0967-3334/36/6/1179
- Jones DF, 2002, EUR J OPER RES, V137, P1, DOI 10.1016/S0377-2217(01)00123-0
- Kaipio J. P, 2004, STAT COMPUTATIONAL I, P160
- Kaipio J, 2007, J COMPUT APPL MATH, V198, P493, DOI 10.1016/j.cam.2005.09.027
- Kaipio JP, 1999, ANN NY ACAD SCI, V873, P430, DOI 10.1111/j.1749-6632.1999.tb09492.x
- Kaipio JP, 1998, P ANN INT IEEE EMBS, V20, P1032, DOI 10.1109/IEMBS.1998.745626
- Kaminsky DA, 2004, J APPL PHYSIOL, V97, P1849, DOI 10.1152/japplphysiol.00300.2004
- Kao TJ, 2006, PHYSIOL MEAS, V27, pS1, DOI 10.1088/0967-3334/27/5/S01
- Karagiannidis C, 2018, CRIT CARE, V22, DOI 10.1186/s13054-018-2137-3
- Karsten J, 2015, ACTA ANAESTH SCAND, V59, P723, DOI 10.1111/aas.12518
- Karsten J, 2016, CRIT CARE, V20, DOI 10.1186/s13054-015-1161-9
- Kim BS, 2004, MEAS SCI TECHNOL, V15, P2113, DOI 10.1088/0957-0233/15/10/022
- Kim KY, 2002, IEEE T MAGN, V38, P1301, DOI 10.1109/20.996332
- Kim KY, 2001, MEAS SCI TECHNOL, V12, P1032, DOI 10.1088/0957-0233/12/8/307
- Knudsen K., 2011, DISCRET CONTIN DYN S, P884
- Knudsen K, 2007, SIAM J APPL MATH, V67, P893, DOI 10.1137/060656930
- Knudsen K, 2009, INVERSE PROBL IMAG, V3, P599, DOI 10.3934/ipi.2009.3.599
- Kolehmainen V, 2001, INVERSE PROBL, V17, P1937, DOI 10.1088/0266-5611/17/6/324
- Kreutzer M, 2012, IEEE SYM PARA DISTR, P1696, DOI 10.1109/IPDPSW.2012.211
- Krueger-Ziolek S, 2017, PHYSIOL MEAS, V38, P1214, DOI 10.1088/1361-6579/aa69d5
- Krueger-Ziolek S, 2016, RESP PHYSIOL NEUROBI, V233, P25, DOI 10.1016/j.resp.2016.07.010
- Krueger-Ziolek S, 2015, PHYSIOL MEAS, V36, P1109, DOI 10.1088/0967-3334/36/6/1109
- Li CM, 2005, PROC CVPR IEEE, P430
- Lionheart W, 2005, SER MED PHY BIOMED E, P3
- Lionheart WRB, 2001, PHYSIOL MEAS, V22, P85, DOI 10.1088/0967-3334/22/1/311
- Lipponen A, 2011, MEAS SCI TECHNOL, V22, DOI 10.1088/0957-0233/22/10/104013
- Liu CH, 1998, J APPL PHYSIOL, V84, P1447
- Long Y, 2015, CHINESE MED J-PEKING, V128, P1421, DOI 10.4103/0366-6999.157626
- Lowhagen K, 2011, ACTA ANAESTH SCAND, V55, P165, DOI 10.1111/j.1399-6576.2010.02331.x
- Lowhagen K, 2010, MINERVA ANESTESIOL, V76, P1024
- Martins T.C., 2011, P 18 IFAC WORLD C MI, V18, P4989
- Martins T. C., 2018, IFAC PAPERS ONLINE, V51, P47
- Martins TC, 2017, IFAC PAPERSONLINE, V50, P9961, DOI 10.1016/j.ifacol.2017.08.1574
- Martins TC, 2015, IEEE ENG MED BIO, P4069, DOI 10.1109/EMBC.2015.7319288
- Martins TD, 2016, COMPUT MATH APPL, V72, P1230, DOI 10.1016/j.camwa.2016.06.021
- Martins TD, 2014, I S BIOMED IMAGING, P185, DOI 10.1109/ISBI.2014.6867840
- Martins TD, 2013, IEEE ENG MED BIO, P6425, DOI 10.1109/EMBC.2013.6611025
- Martins TD, 2012, IEEE ENG MED BIO, P1518, DOI 10.1109/EMBC.2012.6346230
- Martins TD, 2012, IEEE T BIO-MED ENG, V59, P1861, DOI 10.1109/TBME.2012.2188398
- Martins TD, 2011, IEEE ENG MED BIO, P7033, DOI 10.1109/IEMBS.2011.6091778
- Mauri T, 2013, AM J RESP CRIT CARE, V188, P1466, DOI 10.1164/rccm.201303-0463IM
- Meade MO, 2008, JAMA-J AM MED ASSOC, V299, P637, DOI 10.1001/jama.299.6.637
- Mellenthin M. M., 2018, IEEE T INSTRUMENTATI
- METROPOLIS N, 1953, J CHEM PHYS, V21, P1087, DOI 10.1063/1.1699114
- Meurant G, 2005, NUMER ALGORITHMS, V40, P157, DOI 10.1007/S11075-005-1528-0
- Meurant G, 2006, LANCZOS CONJUGATE GR
- Morais CCA, 2017, AM J RESP CRIT CARE, V195, P1070, DOI 10.1164/rccm.201609-1780LE
- Moura F. S., 2013, THESIS
- Moura FS, 2010, IEEE T BIO-MED ENG, V57, P422, DOI 10.1109/TBME.2009.2032529
- Mueller JL, 2018, PHYSIOL MEAS, V39, DOI 10.1088/1361-6579/aac295
- Mueller JL, 2012, COMPUT SCI ENG SER, V10, P3, DOI 10.1137/1.9781611972344
- Mueller JL, 2003, SIAM J SCI COMPUT, V24, P1232, DOI 10.1137/S1064827501394568
- Muller P. A., 2014, THESIS
- Muller PA, 2018, PHYSIOL MEAS, V39, DOI 10.1088/1361-6579/aab8c4
- Muller PA, 2017, IEEE T MED IMAGING, V36, P1868, DOI 10.1109/TMI.2017.2695893
- Murphy EK, 2009, IEEE T MED IMAGING, V28, P1576, DOI 10.1109/TMI.2009.2021611
- Nachman AI, 1996, ANN MATH, V143, P71, DOI 10.2307/2118653
- NACHMAN AI, 1988, ANN MATH, V128, P531, DOI 10.2307/1971435
- NELSON LW, 1976, IEEE T AUTOMAT CONTR, V21, P94, DOI 10.1109/TAC.1976.1101148
- Nestler C, 2017, BRIT J ANAESTH, V119, P1194, DOI 10.1093/bja/aex192
- Ngatchou P., 2005, P 13 INT C INT SYST, P84, DOI 10.1109/ISAP.2005.1599245
- Nissinen A, 2011, INT J UNCERTAIN QUAN, V1, P203, DOI 10.1615/Int.J.UncertaintyQuantification.v1.i3.20
- Nopp P, 1997, MED BIOL ENG COMPUT, V35, P695, DOI 10.1007/BF02510980
- NOVIKOV RG, 1988, FUNCT ANAL APPL+, V22, P263
- Ogata K, 1987, DISCRETE TIME CONTRO
- PAULSON K, 1992, SIAM J APPL MATH, V52, P1012, DOI 10.1137/0152059
- Pillow JJ, 2006, PEDIATR PULM, V41, P105, DOI 10.1002/ppul.20319
- POLLAK V, 1974, MED BIOL ENG, V12, P460, DOI 10.1007/BF02478602
- Pulletz S, 2012, MULTIDISCIP RESP MED, V7, DOI 10.1186/2049-6958-7-44
- Radke O. C., 2015, ANESTH PAIN MED, V5
- Santos SA, 2018, RESP PHYSIOL NEUROBI, V254, P1, DOI 10.1016/j.resp.2018.03.016
- Sato A. K., 2018, IFAC PAPERSONLINE, V51, P41
- Schibler A, 2013, PHYSIOL MEAS, V34, P1319, DOI 10.1088/0967-3334/34/10/1319
- Siltanen S, 2000, INVERSE PROBL, V16, P681, DOI 10.1088/0266-5611/16/3/310
- Siltanen Samuli, 1999, ANN ACAD SCI FENN-M, V121, P56
- Silva O. L, 2012, THESIS
- Silva O. L., 2018, IFAC PAPERSONLINE, V51, P30
- Silva OL, 2017, CONTROL ENG PRACT, V58, P276, DOI 10.1016/j.conengprac.2016.03.003
- SOMERSALO E, 1992, SIAM J APPL MATH, V52, P1023, DOI 10.1137/0152060
- SOMERSALO E, 1991, INVERSE PROBL, V7, P899, DOI 10.1088/0266-5611/7/6/011
- Sousa T., 2011, P COB 2011 21 INT C, P24
- Spadaro S, 2018, CRIT CARE, V22, DOI 10.1186/s13054-017-1931-7
- Sun Q, 2017, CRIT CARE, V21, DOI 10.1186/s13054-017-1714-1
- Suppapitnarm A, 2000, ENG OPTIMIZ, V33, P59, DOI 10.1080/03052150008940911
- Pham T, 2017, AM J RESP CRIT CARE, V195, P860, DOI 10.1164/rccm.201609-1773CP
- Tavares RS, 2012, J PHYS CONF SER, V407, DOI 10.1088/1742-6596/407/1/012015
- Tavares RS, 2019, BIOMED SIGNAL PROCES, V52, P445, DOI 10.1016/j.bspc.2017.02.007
- TAVARES RS, 2014, IFAC P VOLUMES IFACP, V19, P7535
- Terragni PP, 2007, AM J RESP CRIT CARE, V175, P160, DOI 10.1164/rccm.200607-915OC
- Trigo F. C., 2005, THESIS
- Trigo FC, 2004, IEEE T BIO-MED ENG, V51, P72, DOI 10.1109/TBME.2003.820389
- Vauhkonen M, 1998, IEEE T BIO-MED ENG, V45, P486, DOI 10.1109/10.664204
- Vauhkonen P. J., 2004, THESIS
- Vauhkonen PJ, 1999, IEEE T BIO-MED ENG, V46, P1150, DOI 10.1109/10.784147
- Vauhkonen PJ, 2000, PHYSIOL MEAS, V21, P125, DOI 10.1088/0967-3334/21/1/316
- Vazquez F, 2011, CONCURR COMP-PRACT E, V23, P815, DOI 10.1002/cpe.1658
- Venegas JG, 1998, J APPL PHYSIOL, V84, P389
- Vilhunen T, 2002, MEAS SCI TECHNOL, V13, P1848, DOI 10.1088/0957-0233/13/12/307
- Vogt B, 2018, PEDIATR PULM, V53, P293, DOI 10.1002/ppul.23912
- Vogt B, 2016, AM J PHYSIOL-LUNG C, V311, pL8, DOI 10.1152/ajplung.00463.2015
- Vogt B, 2012, J APPL PHYSIOL, V113, P1154, DOI 10.1152/japplphysiol.01630.2011
- Wang W, 2018, KAOHSIUNG J MED SCI, V34, P420, DOI 10.1016/j.kjms.2017.12.012
- Wettstein M, 2014, PLOS ONE, V9, DOI 10.1371/journal.pone.0106591
- Wrigge H, 2016, J THORAC DIS, V8, pE1661, DOI 10.21037/jtd.2016.12.101
- YANG CD, 1990, J GUID CONTROL DYNAM, V13, P1051, DOI 10.2514/3.20578
- Yun L, 2016, MEDICINE, V95, DOI 10.1097/MD.0000000000003820
- Zhang J, 2010, PHYSIOL MEAS, V31, pS45, DOI 10.1088/0967-3334/31/8/S04
- Zhang W, 2014, PHYSIOL MEAS, V35, P2001, DOI 10.1088/0967-3334/35/10/2001
- Zhao Z, 2017, ACTA ANAESTH SCAND, V61, P1166, DOI 10.1111/aas.12959
- Zhao Z., 2012, VENTILATION INHOMOGE
- Zhao ZQ, 2018, PHYSIOL MEAS, V39, DOI 10.1088/1361-6579/aaaeb2
- Zhao ZQ, 2018, PHYSIOL MEAS, V39, DOI 10.1088/1361-6579/aa9eb4
- Zhao ZQ, 2013, PHYSIOL MEAS, V34, pN107, DOI 10.1088/0967-3334/34/11/N107