Comparison of Frequency-and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia

Rathinaswamy B. Govindan; Kenneth Martin Brady; An N. Massaro; Jamie Perin; Jacky M. Jennings; Adre J. Duplessis; Raymond C. Koehler; Jennifer K. Lee

doi:10.1159/000499425

Comparison of Frequency-and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia

Rathinaswamy B. Govindan, Kenneth Martin Brady, An N. Massaro, Jamie Perin, Jacky M. Jennings, Adre J. Duplessis, Raymond C. Koehler, Jennifer K. Lee^*

^*Corresponding author for this work

Pediatrics

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Introduction: The optimal method to detect impairments in cerebrovascular pressure autoregulation in neonates with hypoxic-ischemic encephalopathy (HIE) is unclear. Improving autoregulation monitoring methods would significantly advance neonatal neurocritical care. Methods: We tested several mathematical algorithms from the frequency and time domains in a piglet model of HIE, hypothermia, and hypotension. We used laser Doppler flowmetry and induced hypotension to delineate the gold standard lower limit of autoregulation (LLA). Receiver operating characteristics curve analyses were used to determine which indices could distinguish blood pressure above the LLA from that below the LLA in each piglet. Results: Phase calculation in the frequency band with maximum coherence, as well as the correlation between mean arterial pressure (MAP) and near-infrared spectroscopy relative total tissue hemoglobin (HbT) or regional oxygen saturation (rSO), accurately discriminated functional from dysfunctional autoregulation. Neither hypoxia-ischemia nor hypothermia affected the accuracy of these indices. Coherence alone and gain had low diagnostic value relative to phase and correlation. Conclusion: Our findings indicate that phase shift is the most accurate component of autoregulation monitoring in the developing brain, and it can be measured using correlation or by calculating phase when coherence is maximal. Phase and correlation autoregulation indices from MAP and rSO2 and vasoreactivity indices from MAP and HbT are accurate metrics that are suitable for clinical HIE studies.

Original language	English (US)
Pages (from-to)	547-559
Number of pages	13
Journal	Developmental Neuroscience
Volume	40
Issue number	5-6
DOIs	https://doi.org/10.1159/000499425
State	Published - Jul 1 2019

Funding

National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK) This work was supported by the National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK), an American Heart Association grant-in-aid (to A.N.M., R.B.G., and J.K.L.), and an American Heart Association Transformational Project Award (to J.K.L.). Some methods used to measure and monitor autoregulation as described in this manuscript were patented by The Johns Hopkins University, listing K.B. as a coinventor. These patents are exclusively licensed to Medtronic Inc. and K.B. received a portion of the licensing fee. J.K.L. received research support from Medtronic for a separate study. J.K.L. was also a paid Advisory Board member for Medtronic. This arrangement was reviewed and approved by the Johns Hopkins University in accordance with its conflict of inter- est policies. Medtronic had no role in the study design, data collection and analysis, interpretation of results, writing, or decision to submit our manuscript for publication.

Keywords

Brain hypoxia
Cerebrovascular circulation
Hypothermia
Ischemia
Newborn

ASJC Scopus subject areas

Neurology
Developmental Neuroscience

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10.1159/000499425

Cite this

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title = "Comparison of Frequency-and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia",

abstract = "Introduction: The optimal method to detect impairments in cerebrovascular pressure autoregulation in neonates with hypoxic-ischemic encephalopathy (HIE) is unclear. Improving autoregulation monitoring methods would significantly advance neonatal neurocritical care. Methods: We tested several mathematical algorithms from the frequency and time domains in a piglet model of HIE, hypothermia, and hypotension. We used laser Doppler flowmetry and induced hypotension to delineate the gold standard lower limit of autoregulation (LLA). Receiver operating characteristics curve analyses were used to determine which indices could distinguish blood pressure above the LLA from that below the LLA in each piglet. Results: Phase calculation in the frequency band with maximum coherence, as well as the correlation between mean arterial pressure (MAP) and near-infrared spectroscopy relative total tissue hemoglobin (HbT) or regional oxygen saturation (rSO), accurately discriminated functional from dysfunctional autoregulation. Neither hypoxia-ischemia nor hypothermia affected the accuracy of these indices. Coherence alone and gain had low diagnostic value relative to phase and correlation. Conclusion: Our findings indicate that phase shift is the most accurate component of autoregulation monitoring in the developing brain, and it can be measured using correlation or by calculating phase when coherence is maximal. Phase and correlation autoregulation indices from MAP and rSO2 and vasoreactivity indices from MAP and HbT are accurate metrics that are suitable for clinical HIE studies.",

keywords = "Brain hypoxia, Cerebrovascular circulation, Hypothermia, Ischemia, Newborn",

author = "Govindan, {Rathinaswamy B.} and Brady, {Kenneth Martin} and Massaro, {An N.} and Jamie Perin and Jennings, {Jacky M.} and Duplessis, {Adre J.} and Koehler, {Raymond C.} and Lee, {Jennifer K.}",

note = "Funding Information: National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK) Funding Information: This work was supported by the National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK), an American Heart Association grant-in-aid (to A.N.M., R.B.G., and J.K.L.), and an American Heart Association Transformational Project Award (to J.K.L.). Funding Information: Some methods used to measure and monitor autoregulation as described in this manuscript were patented by The Johns Hopkins University, listing K.B. as a coinventor. These patents are exclusively licensed to Medtronic Inc. and K.B. received a portion of the licensing fee. J.K.L. received research support from Medtronic for a separate study. J.K.L. was also a paid Advisory Board member for Medtronic. This arrangement was reviewed and approved by the Johns Hopkins University in accordance with its conflict of inter- est policies. Medtronic had no role in the study design, data collection and analysis, interpretation of results, writing, or decision to submit our manuscript for publication. Publisher Copyright: {\textcopyright} 2019 S. Karger AG, Basel. Copyright: All rights reserved.",

year = "2019",

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doi = "10.1159/000499425",

language = "English (US)",

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T1 - Comparison of Frequency-and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia

AU - Govindan, Rathinaswamy B.

AU - Brady, Kenneth Martin

AU - Massaro, An N.

AU - Perin, Jamie

AU - Jennings, Jacky M.

AU - Duplessis, Adre J.

AU - Koehler, Raymond C.

AU - Lee, Jennifer K.

N1 - Funding Information: National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK) Funding Information: This work was supported by the National Institutes of Health, Bethesda, MD, USA (grant Nos. K08NS080984 and R01NS107417 to J.K.L., and R01NS060703 to RCK), an American Heart Association grant-in-aid (to A.N.M., R.B.G., and J.K.L.), and an American Heart Association Transformational Project Award (to J.K.L.). Funding Information: Some methods used to measure and monitor autoregulation as described in this manuscript were patented by The Johns Hopkins University, listing K.B. as a coinventor. These patents are exclusively licensed to Medtronic Inc. and K.B. received a portion of the licensing fee. J.K.L. received research support from Medtronic for a separate study. J.K.L. was also a paid Advisory Board member for Medtronic. This arrangement was reviewed and approved by the Johns Hopkins University in accordance with its conflict of inter- est policies. Medtronic had no role in the study design, data collection and analysis, interpretation of results, writing, or decision to submit our manuscript for publication. Publisher Copyright: © 2019 S. Karger AG, Basel. Copyright: All rights reserved.

PY - 2019/7/1

Y1 - 2019/7/1

N2 - Introduction: The optimal method to detect impairments in cerebrovascular pressure autoregulation in neonates with hypoxic-ischemic encephalopathy (HIE) is unclear. Improving autoregulation monitoring methods would significantly advance neonatal neurocritical care. Methods: We tested several mathematical algorithms from the frequency and time domains in a piglet model of HIE, hypothermia, and hypotension. We used laser Doppler flowmetry and induced hypotension to delineate the gold standard lower limit of autoregulation (LLA). Receiver operating characteristics curve analyses were used to determine which indices could distinguish blood pressure above the LLA from that below the LLA in each piglet. Results: Phase calculation in the frequency band with maximum coherence, as well as the correlation between mean arterial pressure (MAP) and near-infrared spectroscopy relative total tissue hemoglobin (HbT) or regional oxygen saturation (rSO), accurately discriminated functional from dysfunctional autoregulation. Neither hypoxia-ischemia nor hypothermia affected the accuracy of these indices. Coherence alone and gain had low diagnostic value relative to phase and correlation. Conclusion: Our findings indicate that phase shift is the most accurate component of autoregulation monitoring in the developing brain, and it can be measured using correlation or by calculating phase when coherence is maximal. Phase and correlation autoregulation indices from MAP and rSO2 and vasoreactivity indices from MAP and HbT are accurate metrics that are suitable for clinical HIE studies.

AB - Introduction: The optimal method to detect impairments in cerebrovascular pressure autoregulation in neonates with hypoxic-ischemic encephalopathy (HIE) is unclear. Improving autoregulation monitoring methods would significantly advance neonatal neurocritical care. Methods: We tested several mathematical algorithms from the frequency and time domains in a piglet model of HIE, hypothermia, and hypotension. We used laser Doppler flowmetry and induced hypotension to delineate the gold standard lower limit of autoregulation (LLA). Receiver operating characteristics curve analyses were used to determine which indices could distinguish blood pressure above the LLA from that below the LLA in each piglet. Results: Phase calculation in the frequency band with maximum coherence, as well as the correlation between mean arterial pressure (MAP) and near-infrared spectroscopy relative total tissue hemoglobin (HbT) or regional oxygen saturation (rSO), accurately discriminated functional from dysfunctional autoregulation. Neither hypoxia-ischemia nor hypothermia affected the accuracy of these indices. Coherence alone and gain had low diagnostic value relative to phase and correlation. Conclusion: Our findings indicate that phase shift is the most accurate component of autoregulation monitoring in the developing brain, and it can be measured using correlation or by calculating phase when coherence is maximal. Phase and correlation autoregulation indices from MAP and rSO2 and vasoreactivity indices from MAP and HbT are accurate metrics that are suitable for clinical HIE studies.

KW - Brain hypoxia

KW - Cerebrovascular circulation

KW - Hypothermia

KW - Ischemia

KW - Newborn

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Comparison of Frequency-and Time-Domain Autoregulation and Vasoreactivity Indices in a Piglet Model of Hypoxia-Ischemia and Hypothermia

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