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Intraoperative Cerebral Autoregulation Assessment Using Ultrasound-Tagged Near-Infrared-Based Cerebral Blood Flow in Comparison to Transcranial Doppler Cerebral Flow Velocity: A Pilot Study
Author's Accepted Manuscript
Intraoperative Cerebral Autoregulation Assessment Using Ultrasound Tagged Near Infrared-Based Cerebral Blood Flow in Comparison to Transcranial Doppler Cerebral Flow Velocity: A Pilot Study John M. Murkin MD, FRCPC, Moshe Kamar MD, Zmira Silman, Michal Balberg PhD, Sandra J. Adams RN www.elsevier.com/locate/buildenv
PII: DOI: Reference:
S1053-0770(15)00512-1 http://dx.doi.org/10.1053/j.jvca.2015.05.201 YJCAN3315
To appear in:
Journal of Cardiothoracic and Vascular Anesthesia
Cite this article as: John M. Murkin MD, FRCPC, Moshe Kamar MD, Zmira Silman, Michal Balberg PhD, Sandra J. Adams RN, Intraoperative Cerebral Autoregulation Assessment Using Ultrasound Tagged Near Infrared-Based Cerebral Blood Flow in Comparison to Transcranial Doppler Cerebral Flow Velocity: A Pilot Study, Journal of Cardiothoracic and Vascular Anesthesia, http://dx.doi.org/10.1053/j.jvca.2015.05.201 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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This was a feasibility study investigating the efficacy of a new UT-NIR device (Ornim medical LTD, Kefar Saba Israel) for monitoring CFI and determination of CA and LLA in the operating room environment, and as such, faced several challenges. As TCD is the only other continuous and non-invasive technique for assessment of CA, we sought to employ it for cross-validation of UT-NIR detection of CA. However, TCD is limited by the need to find and maintain an acoustic window, is highly operator dependent, and is very susceptible to interference from electrocautery and other noise transients. This was demonstrated in the current study where insufficient TCD data was obtainable during electrocautery-free intervals to permit calculation of Mx during preand post-CPB intervals and in which a stable and continuous TCD signal could not be maintained in a further 8 of 20 patients during CPB. Of note, while a 40% failure rate for TCD monitoring may appear excessive it is not inconsistent with other such clinical studies. In a study of 239 patients it was reported that TCD was unsuccessful in 46% of female patients even at highest ultrasound intensity, while another study of 176 carotid endarterectomies reported an inability to monitor TCD hemodynamics in over 40% of patients.[13,14]
Since agreement was demonstrated between Mx and CFIx in determining presence or absence of CA during CPB, and given the high correlation (r2 = 0.828; p = 0.003) between LLA determined independently by each device as show in Figure 2, a further analysis of CA employing only CFIx data during pre- and post-CPB study periods was undertaken. The agreement in determination of CA between the two modalities of Mx and CFIx in patients monitored during CPB demonstrates that the UT-NIR device can detect CA and provides continuous monitoring of CBF intraoperatively independent of electrocautery usage. The resulting observation that 15% of patients demonstrated impairment of CA during CPB as represented in Figure 3b, is similar to the 20% incidence found in the study of Ono et al.[1] The further observation that 1 patient in whom intact CA was present prior to CPB, but who subsequently demonstrated impaired CA during and after CPB, and 5 patients in whom CA was impaired pre-CPB, of whom all demonstrated CA during CPB as shown in Figure 3a, and 4 of whom showed intact CA post-CPB, while very preliminary, is provocative and suggests that non-pulsatile perfusion or other unknown factors during CPB may be etiologic in altering cerebrovascular vasoreactivity in the perioperative period. Also, while the mean LLA detected during CPB was 48 mmHg and compatible with generally accepted perfusion parameters of MAP > 50 mmHg during CPB, it should be borne in mind that 2 of 10 patients had LLA 60 mmHg and at least 2 further patients had non-intact CA consistent with other reports,[1] and is thus further evidence that monitoring and individualization of cerebral perfusion parameters is a requisite for maintenance of optimal perioperative cerebral perfusion. It must be borne in mind however, that these are preliminary observations and will need further validation as this investigation was undertaken as a feasibility study rather than as a primary assessment of cerebral physiology. Also, the cutoff threshold of 0.35 for presence/absence of
intact CA, while consistent with similar such studies,[11] remains arbitrary and may predispose towards a determination of non-intact CA, and that even the dichotomous categorization of CA as intact or non-intact may be a simplification as there is increasing evidence of even more subtle alterations in CA that reflect degrees of vasoreactivity more optimally characterized in head injury patients as ‘better or worse’ cerebral autoregulation rather than representing an ‘all or none’ phenomenon.[8] ,# # # # 9 #% # 9 @ $# # 9% ## #% #%$# F/4 /3G'5.!, #% # "$ &E/ #=F/3 /:G5 #@ # 9 #% & "# # &O# "# # # # $9# # <#$ ##=F/7 /2G 5 % # ##&$# .# # "# #'5.!, & @ #"$#."# " $$# $ # $ # , #" #%$# # " %$@=F/:G 5# % #"% $$#$ 6 # ## A# O#B@"# ##@ ## @& # =* M# & % ## # # "" $#$ ###@ A# B " $ # &= # !, # # %## %& # $# "" $# # "####& @ @ # "" $## &## # $?%=5 $#$$##"@"#$## #### $?% # $# & $@=
While primarily a measure of cerebral microcirculatory flow, UT-NIR has been shown to correlate with changes in global CBF as shown by Schytz et al comparing UT-NIR to 133Xe
single photon emission computed tomography (SPECT) in healthy volunteers in response to acetazolamide administration.[12] Transcranial Doppler assesses large vessel (eg. MCA) flow velocities, therefore, as in this study, it was anticipated that both UT-NIR and TCD modalities will trend similarly but not necessarily correlate. Increasingly, real time detection of cerebral CA is demonstrating a significant role in patient outcomes in various settings. In a series of 234 cardiac surgical patients Ono et al. reported impaired CA during CPB in 20%.[1] Of these patients multivariate analysis demonstrated a significant correlation between impaired CA during CPB and perioperative stroke with an occurrence in 6 of 47 (12.8%) patients with impaired CA compared with 5 of 187 (2.7%) in whom CA was intact.[3] Whether detection of CA will have similar prognostic importance in other high risk clinical settings is yet to be determined. In severe traumatic brain injury use of invasive intracranial pressure (ICP) monitoring and MAP to calculate PRx and a low-frequency autoregulation index as comprehensive indices of cerebrovascular autoregulatory capacity are being increasingly advocated for clinical management guidelines with a goal of optimizing cerebral perfusion without increasing and potentially lowering ICP.[20] The associations that have been made to date between impairment of CA and duration of hypotension below LLA and various adverse cerebral and renal outcomes makes optimal MAP and cerebral perfusion pressure management a dynamic and potentially titratable process in a variety of high risk patients.[3,4,15] The concept that cerebrovascular autoregulatory capacity is a dynamic physiologic phenomenon sensitive to perturbations in brain milieu and as reflected in the temporally/procedurally variable results shown by several patients within the current study is provocative. Whether the dynamic status of CA we observed in some patients is related to alterations in autonomic tonus,[21]
alterations in plasma volume,[22] or systemic inflammation and endotoxin release,[23] all of which can accompany CPB, or rather reflects other unknown mechanisms is currently unclear, but the demonstrated ability of CFIx to function as a non-invasive index of cerebral autoregulatory homeostasisis becoming increasingly clinically attractive.[24] The current feasibility study has demonstrated excellent concordance of CFIx with TCD-derived Mx for detection of CA and LLA and it is anticipated it will be followed by a larger study based on data and experience gained from the current investigation. *
1] Ono M, Brady K, Easley RB, Brown C, Kraut M, Gottesman RF, Hogue CW Jr. Duration and magnitude of blood pressure below cerebral autoregulation threshold during cardiopulmonary bypass is associated with major morbidity and operative mortality. J Thorac Cardiovasc Surg. 2014;147(1):483-9. 2] Murkin JM, Farrar JK, Tweed WA, McKenzie FN, Guiraudon G. Cerebral autoregulation and flow/metabolism coupling during cardiopulmonary bypass: the influence of PaCO2. Anesth Analg 66:825-832, 1987 3] Ono M, Joshi B, Brady K, Easley RB, Zheng Y, Brown C, Baumgartner W, Hogue CW. Risks for impaired cerebral autoregulation during cardiopulmonary bypass and postoperative stroke. Br J Anaesth. 2012;109(3):391-8 4] Ono M, Arnaoutakis GJ, Fine DM, Brady K, Easley RB, Zheng Y, Brown C, Katz NM, Grams ME, Hogue CW. Blood pressure excursions below the cerebral autoregulation threshold during cardiac surgery are associated with acute kidney injury. Crit Care Med. 2013;41(2):46471
4G Q * #=#$ $ $@& #%@ # %"&# # # = #0CCC+8:A0B6/04.-C 3G = "" ! # "& !#= #H # 0CC4+2A0B6/-2./80= :G! + !+R . 1+ ,+=! & &#$ $@ " # ## "% = , ./0/10..!02.
8] Zweifel C, Dias C, Smielewski P, Czosnyka M. Continuous time-domain monitoring of cerebral autoregulation in neurocritical care. Med Eng Phys. 2014;36(5):638-45 9] Zweifel C, Czosnyka M, Lavinio A, Castellani G, Kim DJ, Carrera E, Pickard JD, Kirkpatrick PJ, Smielewski P. A comparison study of cerebral autoregulation assessed with transcranial Doppler and cortical laser Doppler flowmetry. Neurol Res. 2010;32(4):425-8. 10] Ono M, Zheng Y, Joshi B, Sigl JC, Hogue CW. Validation of a stand-alone near-infrared spectroscopy system for monitoring cerebral autoregulation during cardiac surgery. Anesth Analg. 2013;116(1):198-204. 11] Brady KM, Lee JK, Kibler KK, et al. Continuous time-domain analysis of cerebrovascular autoregulation using near-infrared spectroscopy. Stroke 2007; 38:2818 12] Schytz HW, Guo S, Jensen LT, Kamar M, Nini A, Gress DR, Ashina M. A new technology for detecting cerebral blood flow: a comparative study of ultrasound tagged NIRS and 133XeSPECT. Neurocrit Care. 2012;17(1):139-45
13] Itoh T, Matsumoto M, Handa N, Maeda H, Hougaku H, Hashimoto H, Etani H, Tsukamoto Y, Kamada T. Effect of transcranial Doppler intensity on successful recording in Japanese patients. Ultrasound Med Biol. 1996;22(6):701-5. 14] Dinkel M, Langer H, Loerler H, Rügheimer E, Schweiger H. [Neuromonitoring in carotid surgery: possibilities and limits of transcranial Doppler ultrasound.] Vasa 1994;23(4) 337-44. German 15] Murkin JM, Arango M. Near-infrared spectroscopy as an index of brain and tissue oxygenation. Br J Anaesth. 2009;103Suppl 1:i3-13 /3G ##* V H= " # ? ## $ $ "#"%= ""% =0CC8+02A8B683-.7:=
17] Racheli N, Ron A, Metzger C, Breskin I, Balberg M, Shechter R. Non-invasive blood flow measurements using ultrasound modulated diffused light. Photons Plus Ultrasound: Imaging and Sensing 2012. Oraevsky AA, Wang LV (Eds); Proc of SPIE, Vol 8223; 82232A 18] Davie SN, Grocott HP. Impact of extracranial contamination on regional cerebral oxygen saturation: a comparison of three cerebral oximetry technologies. Anesthesiology 2012;116(4):834-40 19] Ogoh S, Sato K, Okazaki K, Miyamoto T, Secher F, Sørensen H, Rasmussen P, Secher NH. A decrease in spatially resolved near-infrared spectroscopy-determined frontal lobe tissue oxygenation by phenylephrine reflects reduced skin blood flow. Anesth Analg. 2014;118(4):8239 20] Depreitere B, Güiza F, Van den Berghe G, Schuhmann MU, Maier G, Piper I, Meyfroidt G. Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in
patients with severe traumatic brain injury based on minute-by-minute monitoring data. J Neurosurg. 2014;120(6):1451-7 21] Zhang R, Zuckerman JH, Iwasaki K, Wilson TE, Crandall CG, Levine BD. Autonomic neural control of dynamic cerebral autoregulation in humans. Circulation. 2002;106(14):181420. 22] Jeong SM, Hwang GS, Kim SO, Levine BD, Zhang R. Dynamic cerebral autoregulation after bed rest: effects of volume loading and exercise countermeasures. J Appl Physiol (1985).2014;116(1):24-31. 23] Berg RM, Plovsing RR, Ronit A, Bailey DM, Holstein-Rathlou NH, Møller K. Disassociation of static and dynamic cerebral autoregulatory performance in healthy volunteers after lipopolysaccharide infusion and in patients with sepsis. Am J Physiol Regul Integr Comp Physiol. 2012;303(11):R1127-35 24] Murkin JM.Is it better to shine a light, or rather to curse the darkness? Cerebral near-infrared spectroscopy and cardiac surgery. Eur J Cardiothorac Surg. 2013;43(6):1081-3
Figure Legends Figure 1 Flow chart of patient enrollment (CA is cerebral autoregulation, MAP is mean arterial pressure, CFI is cerebral flow index, TCD is transcranial Doppler)
., 33 *
The figure demonstrates the correlation between LLA values as detected by both methods, where LLA is lower limit of cerebral autoregulation (mmHg), UT-NIR is ultrasound tagged near infrared device, TCD is transcranial Doppler, CFIx is cerebral flow index correlation index and Mx is TCD flow velocity correlation index. (r2 = 0.828; p = 0.003)
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Table 1
Table 1. Demographic and procedural variables of all patients consented
Monitoring (n) Male N (%)
CFI, TCD, MAP
CFI, MAP
No MAP
Total
12
8
6
26
10 (83%)
4 (50%)
4(67%)
18 (69%)
P-value
0.283
Age (years- Mean ± SD)
63.5 ± 11.3
65.5 ± 13.4
64.2 ±14.3
64.9 ± 12.2
Current Smoking (N=22)
6 (67%)
4 (50%)
2 (40%)
12 (55%)
0.573*
0.603
Diabetes (N=25)
6 (55%)
4 (50%)
3 (50%)
13 (52%) 0.977
Hypertension (N=24)
8(73%)
6(86%)
4(67%)
18(82%) 0.711
CAD (N=24)
8 (73%)
5 (71%)
4 (67%)
17 (71%) 0.965
CABG
4 (33%)
4 (50%)
3 (50%)
11 (42%)
AVR
3 (25%)
3 (38%)
2 (33%)
8 (31%)
CABG+AVR
3 (25%)
1 (13%)
0 (0%)
4 (15%)
MVR
2 (17%)
0 (0%)
1 (17%)
3 (12%)
99.1 ± 17.6
119.1 ± 25.1
149.2 ± 41.3
116.8 ± 74.1
0.547*
195.7 ± 17.5
260.5 ± 26.5
298.5 ± 63.5
239 .3± 99.6
0.041*
Procedure
Duration CPB (min) Mean ± SD Duration surgery (min) Mean ± SD
(CFI is cerebral flow index; TCD is transcranial Doppler; MAP is mean arterial pressure; CAD is coronary artery disease; CABG is coronary artery bypass graft; AVR is aortic valve replacement; MVR is mitral valve repair or replacement; CPB is cardiopulmonary bypass). For categorical data, p values by chi square test; for continuous measurements *p values by Kruskal Wallis test.
Table 3
Table 3. Presence or absence of cerebral autoregulation (CA) in individual patients Measure Monitor Type Study Interval Subject ID #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20
CA status CFIx
Mx
Pre
CPB Post
CPB
CA CA CA CA CA CA CA CA
CA CA CA CA CA CA CA CA CA CA CA CA CA CA nCA nCA nCA nCA nCA nCA
nCA nCA nCA nCA nCA nCA nCA nCA nCA CA
CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA nCA nCA nCA nCA
CA CA CA CA CA CA CA
CA CA CA
LLA (mmHg) CFIx Mx CPB
40 60 70 40 40 30 50 55 60 50 50 35 50 50 40
70 40 50 30 50 45 60
40 50 50
nCA 40 nCA 45
CFI is NIRS-derived cerebral flow index, TCD is transcranial Doppler, LLA is lower limit of cerebral autoregulation, nCA is non-detectable cerebral autoregulation, CPB is cardiopulmonary bypass period, Pre is before CPB period, Post is after CPB period, # indicates individual study patients.
Figure 1
Figure 2
Figure 2. Correlation of LLA between TCD and UT-NIR
Figure 3
Figure 3. Example of patients with intact and non-intact cerebral autoregulation
Figure 4
Figure 4 Schematic of US-tagged NIR device
Light SKIN BONE DURA/CSF BRAIN
Source
Ultrasound Sensor
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Intraoperative Cerebral Autoregulation Assessment Using Ultrasound Tagged Near Infrared-Based Cerebral Blood Flow in Comparison to Transcranial Doppler Cerebral Flow Velocity: A Pilot Study John M. Murkin MD, FRCPC, Moshe Kamar MD, Zmira Silman, Michal Balberg PhD, Sandra J. Adams RN www.elsevier.com/locate/buildenv
PII: DOI: Reference:
S1053-0770(15)00512-1 http://dx.doi.org/10.1053/j.jvca.2015.05.201 YJCAN3315
To appear in:
Journal of Cardiothoracic and Vascular Anesthesia
Cite this article as: John M. Murkin MD, FRCPC, Moshe Kamar MD, Zmira Silman, Michal Balberg PhD, Sandra J. Adams RN, Intraoperative Cerebral Autoregulation Assessment Using Ultrasound Tagged Near Infrared-Based Cerebral Blood Flow in Comparison to Transcranial Doppler Cerebral Flow Velocity: A Pilot Study, Journal of Cardiothoracic and Vascular Anesthesia, http://dx.doi.org/10.1053/j.jvca.2015.05.201 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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This was a feasibility study investigating the efficacy of a new UT-NIR device (Ornim medical LTD, Kefar Saba Israel) for monitoring CFI and determination of CA and LLA in the operating room environment, and as such, faced several challenges. As TCD is the only other continuous and non-invasive technique for assessment of CA, we sought to employ it for cross-validation of UT-NIR detection of CA. However, TCD is limited by the need to find and maintain an acoustic window, is highly operator dependent, and is very susceptible to interference from electrocautery and other noise transients. This was demonstrated in the current study where insufficient TCD data was obtainable during electrocautery-free intervals to permit calculation of Mx during preand post-CPB intervals and in which a stable and continuous TCD signal could not be maintained in a further 8 of 20 patients during CPB. Of note, while a 40% failure rate for TCD monitoring may appear excessive it is not inconsistent with other such clinical studies. In a study of 239 patients it was reported that TCD was unsuccessful in 46% of female patients even at highest ultrasound intensity, while another study of 176 carotid endarterectomies reported an inability to monitor TCD hemodynamics in over 40% of patients.[13,14]
Since agreement was demonstrated between Mx and CFIx in determining presence or absence of CA during CPB, and given the high correlation (r2 = 0.828; p = 0.003) between LLA determined independently by each device as show in Figure 2, a further analysis of CA employing only CFIx data during pre- and post-CPB study periods was undertaken. The agreement in determination of CA between the two modalities of Mx and CFIx in patients monitored during CPB demonstrates that the UT-NIR device can detect CA and provides continuous monitoring of CBF intraoperatively independent of electrocautery usage. The resulting observation that 15% of patients demonstrated impairment of CA during CPB as represented in Figure 3b, is similar to the 20% incidence found in the study of Ono et al.[1] The further observation that 1 patient in whom intact CA was present prior to CPB, but who subsequently demonstrated impaired CA during and after CPB, and 5 patients in whom CA was impaired pre-CPB, of whom all demonstrated CA during CPB as shown in Figure 3a, and 4 of whom showed intact CA post-CPB, while very preliminary, is provocative and suggests that non-pulsatile perfusion or other unknown factors during CPB may be etiologic in altering cerebrovascular vasoreactivity in the perioperative period. Also, while the mean LLA detected during CPB was 48 mmHg and compatible with generally accepted perfusion parameters of MAP > 50 mmHg during CPB, it should be borne in mind that 2 of 10 patients had LLA 60 mmHg and at least 2 further patients had non-intact CA consistent with other reports,[1] and is thus further evidence that monitoring and individualization of cerebral perfusion parameters is a requisite for maintenance of optimal perioperative cerebral perfusion. It must be borne in mind however, that these are preliminary observations and will need further validation as this investigation was undertaken as a feasibility study rather than as a primary assessment of cerebral physiology. Also, the cutoff threshold of 0.35 for presence/absence of
intact CA, while consistent with similar such studies,[11] remains arbitrary and may predispose towards a determination of non-intact CA, and that even the dichotomous categorization of CA as intact or non-intact may be a simplification as there is increasing evidence of even more subtle alterations in CA that reflect degrees of vasoreactivity more optimally characterized in head injury patients as ‘better or worse’ cerebral autoregulation rather than representing an ‘all or none’ phenomenon.[8] ,# # # # 9 #% # 9 @ $# # 9% ## #% #%$# F/4 /3G'5.!, #% # "$ &E/ #=F/3 /:G5 #@ # 9 #% & "# # &O# "# # # # $9# # <#$ ##=F/7 /2G 5 % # ##&$# .# # "# #'5.!, & @ #"$#."# " $$# $ # $ # , #" #%$# # " %$@=F/:G 5# % #"% $$#$ 6 # ## A# O#B@"# ##@ ## @& # =* M# & % ## # # "" $#$ ###@ A# B " $ # &= # !, # # %## %& # $# "" $# # "####& @ @ # "" $## &## # $?%=5 $#$$##"@"#$## #### $?% # $# & $@=
While primarily a measure of cerebral microcirculatory flow, UT-NIR has been shown to correlate with changes in global CBF as shown by Schytz et al comparing UT-NIR to 133Xe
single photon emission computed tomography (SPECT) in healthy volunteers in response to acetazolamide administration.[12] Transcranial Doppler assesses large vessel (eg. MCA) flow velocities, therefore, as in this study, it was anticipated that both UT-NIR and TCD modalities will trend similarly but not necessarily correlate. Increasingly, real time detection of cerebral CA is demonstrating a significant role in patient outcomes in various settings. In a series of 234 cardiac surgical patients Ono et al. reported impaired CA during CPB in 20%.[1] Of these patients multivariate analysis demonstrated a significant correlation between impaired CA during CPB and perioperative stroke with an occurrence in 6 of 47 (12.8%) patients with impaired CA compared with 5 of 187 (2.7%) in whom CA was intact.[3] Whether detection of CA will have similar prognostic importance in other high risk clinical settings is yet to be determined. In severe traumatic brain injury use of invasive intracranial pressure (ICP) monitoring and MAP to calculate PRx and a low-frequency autoregulation index as comprehensive indices of cerebrovascular autoregulatory capacity are being increasingly advocated for clinical management guidelines with a goal of optimizing cerebral perfusion without increasing and potentially lowering ICP.[20] The associations that have been made to date between impairment of CA and duration of hypotension below LLA and various adverse cerebral and renal outcomes makes optimal MAP and cerebral perfusion pressure management a dynamic and potentially titratable process in a variety of high risk patients.[3,4,15] The concept that cerebrovascular autoregulatory capacity is a dynamic physiologic phenomenon sensitive to perturbations in brain milieu and as reflected in the temporally/procedurally variable results shown by several patients within the current study is provocative. Whether the dynamic status of CA we observed in some patients is related to alterations in autonomic tonus,[21]
alterations in plasma volume,[22] or systemic inflammation and endotoxin release,[23] all of which can accompany CPB, or rather reflects other unknown mechanisms is currently unclear, but the demonstrated ability of CFIx to function as a non-invasive index of cerebral autoregulatory homeostasisis becoming increasingly clinically attractive.[24] The current feasibility study has demonstrated excellent concordance of CFIx with TCD-derived Mx for detection of CA and LLA and it is anticipated it will be followed by a larger study based on data and experience gained from the current investigation. *
1] Ono M, Brady K, Easley RB, Brown C, Kraut M, Gottesman RF, Hogue CW Jr. Duration and magnitude of blood pressure below cerebral autoregulation threshold during cardiopulmonary bypass is associated with major morbidity and operative mortality. J Thorac Cardiovasc Surg. 2014;147(1):483-9. 2] Murkin JM, Farrar JK, Tweed WA, McKenzie FN, Guiraudon G. Cerebral autoregulation and flow/metabolism coupling during cardiopulmonary bypass: the influence of PaCO2. Anesth Analg 66:825-832, 1987 3] Ono M, Joshi B, Brady K, Easley RB, Zheng Y, Brown C, Baumgartner W, Hogue CW. Risks for impaired cerebral autoregulation during cardiopulmonary bypass and postoperative stroke. Br J Anaesth. 2012;109(3):391-8 4] Ono M, Arnaoutakis GJ, Fine DM, Brady K, Easley RB, Zheng Y, Brown C, Katz NM, Grams ME, Hogue CW. Blood pressure excursions below the cerebral autoregulation threshold during cardiac surgery are associated with acute kidney injury. Crit Care Med. 2013;41(2):46471
4G Q * #=#$ $ $@& #%@ # %"&# # # = #0CCC+8:A0B6/04.-C 3G = "" ! # "& !#= #H # 0CC4+2A0B6/-2./80= :G! + !+R . 1+ ,+=! & &#$ $@ " # ## "% = , ./0/10..!02.
8] Zweifel C, Dias C, Smielewski P, Czosnyka M. Continuous time-domain monitoring of cerebral autoregulation in neurocritical care. Med Eng Phys. 2014;36(5):638-45 9] Zweifel C, Czosnyka M, Lavinio A, Castellani G, Kim DJ, Carrera E, Pickard JD, Kirkpatrick PJ, Smielewski P. A comparison study of cerebral autoregulation assessed with transcranial Doppler and cortical laser Doppler flowmetry. Neurol Res. 2010;32(4):425-8. 10] Ono M, Zheng Y, Joshi B, Sigl JC, Hogue CW. Validation of a stand-alone near-infrared spectroscopy system for monitoring cerebral autoregulation during cardiac surgery. Anesth Analg. 2013;116(1):198-204. 11] Brady KM, Lee JK, Kibler KK, et al. Continuous time-domain analysis of cerebrovascular autoregulation using near-infrared spectroscopy. Stroke 2007; 38:2818 12] Schytz HW, Guo S, Jensen LT, Kamar M, Nini A, Gress DR, Ashina M. A new technology for detecting cerebral blood flow: a comparative study of ultrasound tagged NIRS and 133XeSPECT. Neurocrit Care. 2012;17(1):139-45
13] Itoh T, Matsumoto M, Handa N, Maeda H, Hougaku H, Hashimoto H, Etani H, Tsukamoto Y, Kamada T. Effect of transcranial Doppler intensity on successful recording in Japanese patients. Ultrasound Med Biol. 1996;22(6):701-5. 14] Dinkel M, Langer H, Loerler H, Rügheimer E, Schweiger H. [Neuromonitoring in carotid surgery: possibilities and limits of transcranial Doppler ultrasound.] Vasa 1994;23(4) 337-44. German 15] Murkin JM, Arango M. Near-infrared spectroscopy as an index of brain and tissue oxygenation. Br J Anaesth. 2009;103Suppl 1:i3-13 /3G ##* V H= " # ? ## $ $ "#"%= ""% =0CC8+02A8B683-.7:=
17] Racheli N, Ron A, Metzger C, Breskin I, Balberg M, Shechter R. Non-invasive blood flow measurements using ultrasound modulated diffused light. Photons Plus Ultrasound: Imaging and Sensing 2012. Oraevsky AA, Wang LV (Eds); Proc of SPIE, Vol 8223; 82232A 18] Davie SN, Grocott HP. Impact of extracranial contamination on regional cerebral oxygen saturation: a comparison of three cerebral oximetry technologies. Anesthesiology 2012;116(4):834-40 19] Ogoh S, Sato K, Okazaki K, Miyamoto T, Secher F, Sørensen H, Rasmussen P, Secher NH. A decrease in spatially resolved near-infrared spectroscopy-determined frontal lobe tissue oxygenation by phenylephrine reflects reduced skin blood flow. Anesth Analg. 2014;118(4):8239 20] Depreitere B, Güiza F, Van den Berghe G, Schuhmann MU, Maier G, Piper I, Meyfroidt G. Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in
patients with severe traumatic brain injury based on minute-by-minute monitoring data. J Neurosurg. 2014;120(6):1451-7 21] Zhang R, Zuckerman JH, Iwasaki K, Wilson TE, Crandall CG, Levine BD. Autonomic neural control of dynamic cerebral autoregulation in humans. Circulation. 2002;106(14):181420. 22] Jeong SM, Hwang GS, Kim SO, Levine BD, Zhang R. Dynamic cerebral autoregulation after bed rest: effects of volume loading and exercise countermeasures. J Appl Physiol (1985).2014;116(1):24-31. 23] Berg RM, Plovsing RR, Ronit A, Bailey DM, Holstein-Rathlou NH, Møller K. Disassociation of static and dynamic cerebral autoregulatory performance in healthy volunteers after lipopolysaccharide infusion and in patients with sepsis. Am J Physiol Regul Integr Comp Physiol. 2012;303(11):R1127-35 24] Murkin JM.Is it better to shine a light, or rather to curse the darkness? Cerebral near-infrared spectroscopy and cardiac surgery. Eur J Cardiothorac Surg. 2013;43(6):1081-3
Figure Legends Figure 1 Flow chart of patient enrollment (CA is cerebral autoregulation, MAP is mean arterial pressure, CFI is cerebral flow index, TCD is transcranial Doppler)
., 33 *
The figure demonstrates the correlation between LLA values as detected by both methods, where LLA is lower limit of cerebral autoregulation (mmHg), UT-NIR is ultrasound tagged near infrared device, TCD is transcranial Doppler, CFIx is cerebral flow index correlation index and Mx is TCD flow velocity correlation index. (r2 = 0.828; p = 0.003)
4, 5- + ( # # # # # "% %" 9 & #% 9 ,9 $@ 9# 9=** @ #$ @ %&# @@ -=$ 9O ,9PC=-4 # $ @ - = 6, # + # * ( # #!, # # # # %# "# # & "# "" $##!, # "# "#$'5* #I
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Table 1
Table 1. Demographic and procedural variables of all patients consented
Monitoring (n) Male N (%)
CFI, TCD, MAP
CFI, MAP
No MAP
Total
12
8
6
26
10 (83%)
4 (50%)
4(67%)
18 (69%)
P-value
0.283
Age (years- Mean ± SD)
63.5 ± 11.3
65.5 ± 13.4
64.2 ±14.3
64.9 ± 12.2
Current Smoking (N=22)
6 (67%)
4 (50%)
2 (40%)
12 (55%)
0.573*
0.603
Diabetes (N=25)
6 (55%)
4 (50%)
3 (50%)
13 (52%) 0.977
Hypertension (N=24)
8(73%)
6(86%)
4(67%)
18(82%) 0.711
CAD (N=24)
8 (73%)
5 (71%)
4 (67%)
17 (71%) 0.965
CABG
4 (33%)
4 (50%)
3 (50%)
11 (42%)
AVR
3 (25%)
3 (38%)
2 (33%)
8 (31%)
CABG+AVR
3 (25%)
1 (13%)
0 (0%)
4 (15%)
MVR
2 (17%)
0 (0%)
1 (17%)
3 (12%)
99.1 ± 17.6
119.1 ± 25.1
149.2 ± 41.3
116.8 ± 74.1
0.547*
195.7 ± 17.5
260.5 ± 26.5
298.5 ± 63.5
239 .3± 99.6
0.041*
Procedure
Duration CPB (min) Mean ± SD Duration surgery (min) Mean ± SD
(CFI is cerebral flow index; TCD is transcranial Doppler; MAP is mean arterial pressure; CAD is coronary artery disease; CABG is coronary artery bypass graft; AVR is aortic valve replacement; MVR is mitral valve repair or replacement; CPB is cardiopulmonary bypass). For categorical data, p values by chi square test; for continuous measurements *p values by Kruskal Wallis test.
Table 3
Table 3. Presence or absence of cerebral autoregulation (CA) in individual patients Measure Monitor Type Study Interval Subject ID #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20
CA status CFIx
Mx
Pre
CPB Post
CPB
CA CA CA CA CA CA CA CA
CA CA CA CA CA CA CA CA CA CA CA CA CA CA nCA nCA nCA nCA nCA nCA
nCA nCA nCA nCA nCA nCA nCA nCA nCA CA
CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA nCA nCA nCA nCA
CA CA CA CA CA CA CA
CA CA CA
LLA (mmHg) CFIx Mx CPB
40 60 70 40 40 30 50 55 60 50 50 35 50 50 40
70 40 50 30 50 45 60
40 50 50
nCA 40 nCA 45
CFI is NIRS-derived cerebral flow index, TCD is transcranial Doppler, LLA is lower limit of cerebral autoregulation, nCA is non-detectable cerebral autoregulation, CPB is cardiopulmonary bypass period, Pre is before CPB period, Post is after CPB period, # indicates individual study patients.
Figure 1
Figure 2
Figure 2. Correlation of LLA between TCD and UT-NIR
Figure 3
Figure 3. Example of patients with intact and non-intact cerebral autoregulation
Figure 4
Figure 4 Schematic of US-tagged NIR device
Light SKIN BONE DURA/CSF BRAIN
Source
Ultrasound Sensor
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