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Kostoglou K, Bello-Robles F, Brassard P, Chacon M, Claassen JA, Czosnyka M, Elting JW, Hu K, Labrecque L, Liu J, Marmarelis VZ, Payne SJ, Shin DC, Simpson D, Smirl J, Panerai RB, Mitsis GD. Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet). J Cereb Blood Flow Metab 2024:271678X241249276. [PMID: 38688529 DOI: 10.1177/0271678x241249276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.
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Affiliation(s)
- Kyriaki Kostoglou
- Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria
| | - Felipe Bello-Robles
- Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile
| | - Patrice Brassard
- Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC, Canada
- Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec, Quebec, QC, Canada
| | - Max Chacon
- Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile
| | - Jurgen Ahr Claassen
- Department of Geriatrics, Radboud University Medical Center, Research Institute for Medical Innovation and Donders Institute, Nijmegen, The Netherlands
- Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM), Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Marek Czosnyka
- Department of Clinical Neurosciences, Neurosurgery Department, University of Cambridge, Cambridge, UK
| | - Jan-Willem Elting
- Department of Neurology and Clinical Neurophysiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Kun Hu
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Lawrence Labrecque
- Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC, Canada
- Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec, Quebec, QC, Canada
| | - Jia Liu
- Laboratory for Engineering and Scientific Computing, Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Vasilis Z Marmarelis
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Stephen J Payne
- Institute of Applied Mechanics, National Taiwan University, Taipei, Taiwan
| | - Dae Cheol Shin
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - David Simpson
- Institute of Sound and Vibration Research, University of Southampton, Southampton, UK
| | - Jonathan Smirl
- Cerebrovascular Concussion Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
- Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ronney B Panerai
- Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM), Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, British Heart Foundation, Glenfield Hospital, Leicester, UK
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, QC, Canada
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Marmarelis VZ, Shin DC, Zhang R. The Dynamic Relationship Between Cortical Oxygenation and End-Tidal CO 2 Transient Changes Is Impaired in Mild Cognitive Impairment Patients. Front Physiol 2021; 12:772456. [PMID: 34955886 PMCID: PMC8695976 DOI: 10.3389/fphys.2021.772456] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/19/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Recent studies have utilized data-based dynamic modeling to establish strong association between dysregulation of cerebral perfusion and Mild Cognitive Impairment (MCI), expressed in terms of impaired CO2 dynamic vasomotor reactivity in the cerebral vasculature. This raises the question of whether this is due to dysregulation of central mechanisms (baroreflex and chemoreflex) or mechanisms of cortical tissue oxygenation (CTO) in MCI patients. We seek to answer this question using data-based input-output predictive dynamic models. Objective: To use subject-specific data-based multivariate input-output dynamic models to quantify the effects of systemic hemodynamic and blood CO2 changes upon CTO and to examine possible differences in CTO regulation in MCI patients versus age-matched controls, after the dynamic effects of central regulatory mechanisms have been accounted for by using cerebral flow measurements as another input. Methods: The employed model-based approach utilized the general dynamic modeling methodology of Laguerre expansions of kernels to analyze spontaneous time-series data in order to quantify the dynamic effects upon CTO (an index of relative capillary hemoglobin saturation distribution measured via near-infrared spectroscopy) of contemporaneous changes in end-tidal CO2 (proxy for arterial CO2), arterial blood pressure and cerebral blood flow velocity in the middle cerebral arteries (measured via transcranial Doppler). Model-based indices (physio-markers) were computed for these distinct dynamic relationships. Results: The obtained model-based indices revealed significant statistical differences of CO2 dynamic vasomotor reactivity in cortical tissue, combined with "perfusivity" that quantifies the dynamic relationship between flow velocity in cerebral arteries and CTO in MCI patients versus age-matched controls (p = 0.006). Significant difference between MCI patients and age-matched controls was also found in the respective model-prediction accuracy (p = 0.0001). Combination of these model-based indices via the Fisher Discriminant achieved even smaller p-value (p = 5 × 10-5) when comparing MCI patients with controls. The differences in dynamics of CTO in MCI patients are in lower frequencies (<0.05 Hz), suggesting impairment in endocrine/metabolic (rather than neural) mechanisms. Conclusion: The presented model-based approach elucidates the multivariate dynamic connectivity in the regulation of cerebral perfusion and yields model-based indices that may serve as physio-markers of possible dysregulation of CTO during transient CO2 changes in MCI patients.
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Affiliation(s)
- Vasilis Z. Marmarelis
- Biomedical Engineering Department, University of Southern California, Los Angeles, CA, United States
| | - Dae C. Shin
- Biomedical Engineering Department, University of Southern California, Los Angeles, CA, United States
| | - Rong Zhang
- Institute for Exercise and Environmental Medicine, UT Southwestern Medical Center, Dallas, TX, United States
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Marmarelis V, Shin D, Zhang R. Closed-Loop Dynamic Modeling of the Heart-Rate Reflex to Concurrent Spontaneous Changes of Arterial Blood Pressure and CO2 Tension: Quantification of the Effects of Mild Cognitive Impairment. IEEE Trans Biomed Eng 2021; 68:3347-3355. [PMID: 33819147 DOI: 10.1109/tbme.2021.3070900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To extend closed-loop modeling of the heart-rate reflex (HRR) by including the dynamic effects of concurrent changes in blood CO2 tension. This extended dynamic model can be used to generate physio-markers of "baroreflex gain" (BRG) and "chemoreflex gain" (CRG) that allow quantitative assessment of the possible impact of pathologies upon HRR. Mild Cognitive Impairment (MCI) is used as an example. METHODS The proposed data-based closed-loop modeling methodology estimates the forward and reverse dynamic components of the model via Laguerre kernel expansions of two open-loop models using spontaneous time-series data collected in 45 MCI patients and 15 controls. The BRG and CRG physio-markers are subsequently computed for each subject via simulation of the obtained closed-loop model for unit-step change of arterial pressure or blood CO2 tension, respectively. RESULTS Both open-loop and closed-loop HRR modeling revealed that MCI patients exhibit significantly smaller CRG relative to controls (p<0.001), but not significantly different BRG. Furthermore, the closed-loop model captured the dynamic effect of sympathetic activity as resonant peak around 0.1 Hz (Mayer wave) in the chemoreflex and baroreflex transfer functions (not captured via open-loop modeling). This may prove valuable in advancing our understanding of how sympathetic activity impacts HRR in various pathologies. CONCLUSION The extended HRR model, incorporating the dynamic effects of concurrent changes of blood CO2 tension, revealed significantly reduced chemoreflex gain (but not baroreflex gain) in MCI patients. Furthermore, the closed-loop model captured the sympathetic influence around 0.1 Hz. SIGNIFICANCE Multivariate closed-loop dynamic modeling is valuable for understanding physiological autoregulation.
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Krishnamurthy V, Sprick JD, Krishnamurthy LC, Barter JD, Turabi A, Hajjar IM, Nocera JR. The Utility of Cerebrovascular Reactivity MRI in Brain Rehabilitation: A Mechanistic Perspective. Front Physiol 2021; 12:642850. [PMID: 33815146 PMCID: PMC8009989 DOI: 10.3389/fphys.2021.642850] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/22/2021] [Indexed: 01/06/2023] Open
Abstract
Cerebrovascular control and its integration with other physiological systems play a key role in the effective maintenance of homeostasis in brain functioning. Maintenance, restoration, and promotion of such a balance are one of the paramount goals of brain rehabilitation and intervention programs. Cerebrovascular reactivity (CVR), an index of cerebrovascular reserve, plays an important role in chemo-regulation of cerebral blood flow. Improved vascular reactivity and cerebral blood flow are important factors in brain rehabilitation to facilitate desired cognitive and functional outcomes. It is widely accepted that CVR is impaired in aging, hypertension, and cerebrovascular diseases and possibly in neurodegenerative syndromes. However, a multitude of physiological factors influence CVR, and thus a comprehensive understanding of underlying mechanisms are needed. We are currently underinformed on which rehabilitation method will improve CVR, and how this information can inform on a patient's prognosis and diagnosis. Implementation of targeted rehabilitation regimes would be the first step to elucidate whether such regimes can modulate CVR and in the process may assist in improving our understanding for the underlying vascular pathophysiology. As such, the high spatial resolution along with whole brain coverage offered by MRI has opened the door to exciting recent developments in CVR MRI. Yet, several challenges currently preclude its potential as an effective diagnostic and prognostic tool in treatment planning and guidance. Understanding these knowledge gaps will ultimately facilitate a deeper understanding for cerebrovascular physiology and its role in brain function and rehabilitation. Based on the lessons learned from our group's past and ongoing neurorehabilitation studies, we present a systematic review of physiological mechanisms that lead to impaired CVR in aging and disease, and how CVR imaging and its further development in the context of brain rehabilitation can add value to the clinical settings.
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Affiliation(s)
- Venkatagiri Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VAMC, Decatur, GA, United States
- Division of Geriatrics and Gerontology, Department of Medicine, Emory University, Atlanta, GA, United States
- Department of Neurology, Emory University, Atlanta, GA, United States
| | - Justin D. Sprick
- Division of Renal Medicine, Department of Medicine, Emory University, Atlanta, GA, United States
| | - Lisa C. Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VAMC, Decatur, GA, United States
- Department of Physics & Astronomy, Georgia State University, Atlanta, GA, United States
| | - Jolie D. Barter
- Division of Geriatrics and Gerontology, Department of Medicine, Emory University, Atlanta, GA, United States
| | - Aaminah Turabi
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VAMC, Decatur, GA, United States
- Department of Biology, Georgia State University, Atlanta, GA, United States
| | - Ihab M. Hajjar
- Department of Neurology, Emory University, Atlanta, GA, United States
| | - Joe R. Nocera
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VAMC, Decatur, GA, United States
- Department of Neurology, Emory University, Atlanta, GA, United States
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University, Atlanta, GA, United States
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Marmarelis VZ, Shin DC, Oesterreich M, Mueller M. Quantification of dynamic cerebral autoregulation and CO 2 dynamic vasomotor reactivity impairment in essential hypertension. J Appl Physiol (1985) 2020; 128:397-409. [PMID: 31917625 DOI: 10.1152/japplphysiol.00620.2019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The study of dynamic cerebral autoregulation (DCA) in essential hypertension has received considerable attention because of its clinical importance. Several studies have examined the dynamic relationship between spontaneous beat-to-beat arterial blood pressure data and contemporaneous cerebral blood flow velocity measurements (obtained via transcranial Doppler at the middle cerebral arteries) in the form of a linear input-output model using transfer function analysis. This analysis is more reliable when the contemporaneous effects of changes in blood CO2 tension are also taken into account, because of the significant effects of CO2 dynamic vasomotor reactivity (DVR) upon cerebral flow. In this article, we extract such input-output predictive models from spontaneous time series hemodynamic data of 24 patients with essential hypertension and 20 normotensive control subjects under resting conditions, using the novel methodology of principal dynamic modes (PDMs) that achieves improved estimation accuracy over previous methods for relatively short and noisy data. The obtained data-based models are subsequently used to compute indexes and markers that quantify DCA and DVR in each subject or patient and therefore can be used to assess the effects of essential hypertension. These model-based DCA and DVR indexes were properly defined to capture the observed effects of DCA and VR and found to be significantly different (P < 0.05) in the hypertensive patients. We also found significant differences between patients and control subjects in the relative contribution of three PDMs to the model output prediction, a finding that offers the prospect of identifying the physiological mechanisms affected by essential hypertension when the PDMs are interpreted in terms of specific physiological mechanisms.NEW & NOTEWORTHY This article presents novel model-based methodology for obtaining diagnostic indexes of dynamic cerebral autoregulation and dynamic vasomotor reactivity in hypertension.
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Affiliation(s)
- Vasilis Z Marmarelis
- Biomedical Simulations Resource Center, University of Southern California, Los Angeles, California
| | - Dae C Shin
- Biomedical Simulations Resource Center, University of Southern California, Los Angeles, California
| | | | - Martin Mueller
- Neurocenter, Luzerner Kantonsspital, Lucerne, Switzerland
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Müller M, Österreich M. Cerebral Microcirculatory Blood Flow Dynamics During Rest and a Continuous Motor Task. Front Physiol 2019; 10:1355. [PMID: 31708802 PMCID: PMC6821676 DOI: 10.3389/fphys.2019.01355] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 10/11/2019] [Indexed: 12/13/2022] Open
Abstract
Objectives: To examine the brain’s microcirculatory response over the course of a continuous 5-min elbow movement task in order to estimate its potential role in grading vaso-neural coupling compared to the macrocirculatory response. Methods: We simultaneously recorded cerebral blood flow velocity (CBFV), changes in oxygenated/deoxygenated hemoglobin concentrations ([oxHb], [deoxHb]), blood pressure (BP), and end-tidal CO2 over 5-min periods of rest and left elbow movements in 24 healthy persons (13 women and 11 men of mean age ± SD, 38 ± 11 years). A low frequency range (0.07–0.15 Hz) was used for analysis by transfer function estimates of phase and gain. Results: Elbow movement led to a small BP increase (mean BP at rest 83 mm Hg, at movement 87; p < 0.01) and a small ETCO2 decrease (at rest 44.6 mm Hg, at movement 41.7 mm Hg; p < 0.01). Further, it increased BP-[oxHb] phase from 55° (both sides) to 74° (right; p < 0.05)/69° (left; p < 0.05), and BP-[deoxHb] phase from 264° (right)/270° (left) to 288° (right; p < 0.05)/297° (left; p = 0.09). The cerebral mean transit time at 0.1 Hz of 5.6 s of rest remained unchanged by movement. Elbow movement significantly decreased BP-CBFV gain on both sides, and BP-CBFV phase only on the right side (p = 0.05). Conclusion: Elbow movement leads to an increased time delay between BP and [oxHb]/[deoxHb] while leaving the cerebral mean transit time unchanged. Phase shifting is usually the more robust parameter when using a transfer function to estimate dynamic cerebral autoregulation; phase shifting at the microcirculatory level seems to be a better marker of VNC-induced changes than phase shifting between BP and CBFV.
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Affiliation(s)
- Martin Müller
- Neurovascular Laboratory, Neurocenter, Lucerne Kantonsspital, Lucerne, Switzerland
| | - Mareike Österreich
- Neurovascular Laboratory, Neurocenter, Lucerne Kantonsspital, Lucerne, Switzerland
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Marmarelis VZ, Shin DC, Tarumi T, Zhang R. Comparing model-based cerebrovascular physiomarkers with DTI biomarkers in MCI patients. Brain Behav 2019; 9:e01356. [PMID: 31286695 PMCID: PMC6710205 DOI: 10.1002/brb3.1356] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 06/14/2019] [Accepted: 06/14/2019] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE To compare the novel model-based hemodynamic physiomarker of Dynamic Vasomotor Reactivity (DVR) with biomarkers based on Diffusion Tensor Imaging (DTI) and some widely used neurocognitive scores in terms of their ability to delineate patients with amnestic Mild Cognitive Impairment (MCI) from age-matched cognitively normal controls. MATERIALS & METHODS The model-based DVR and MRI-based DTI markers were obtained from 36 patients with amnestic MCI and 16 age-matched controls without cognitive impairment, for whom widely used neurocognitive scores were available. These markers and scores were subsequently compared in terms of statistical delineation between patients and controls. RESULTS It was found that statistically significant delineation between MCI patients and controls was comparable for DVR or DTI markers (p < 0.01). The performance of both types of markers was consistent with the scores of some (but not all) widely used neurocognitive tests. CONCLUSION Since DTI offers a measure of cerebral white matter integrity, the results suggest that the model-based hemodynamic marker of DVR may correlate with cognitive impairment due to white matter lesions. This finding is consistent with the hypothesis that dysregulation of cerebral microcirculation may be an early cause of cognitive impairment, which has been recently corroborated by several studies.
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Affiliation(s)
- Vasilis Z. Marmarelis
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCalifornia
| | - Dae C. Shin
- Biomedical Simulations Resource CenterUniversity of Southern CaliforniaLos AngelesCalifornia
| | - Takashi Tarumi
- Neurology and NeurotherapeuticsUT Southwestern Medical CenterDallasTexas
- Institute for Exercise and Environmental MedicineTexas Health Presbyterian HospitalDallasTexas
- Present address:
Human Informatics Research InstituteNational Institute of Advanced Industrial Science and TechnologyTsukubaJapan
| | - Rong Zhang
- Neurology and NeurotherapeuticsUT Southwestern Medical CenterDallasTexas
- Institute for Exercise and Environmental MedicineTexas Health Presbyterian HospitalDallasTexas
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Sanders ML, Elting JWJ, Panerai RB, Aries M, Bor-Seng-Shu E, Caicedo A, Chacon M, Gommer ED, Van Huffel S, Jara JL, Kostoglou K, Mahdi A, Marmarelis VZ, Mitsis GD, Müller M, Nikolic D, Nogueira RC, Payne SJ, Puppo C, Shin DC, Simpson DM, Tarumi T, Yelicich B, Zhang R, Claassen JAHR. Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability. Front Physiol 2019; 10:865. [PMID: 31354518 PMCID: PMC6634255 DOI: 10.3389/fphys.2019.00865] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 06/20/2019] [Indexed: 11/24/2022] Open
Abstract
Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.
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Affiliation(s)
- Marit L Sanders
- Department of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Jan Willem J Elting
- Department of Neurology, University Medical Center Groningen, Groningen, Netherlands
| | - Ronney B Panerai
- Department of Cardiovascular Sciences, NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Marcel Aries
- Department of Intensive Care, University of Maastricht, Maastricht University Medical Center, Maastricht, Netherlands
| | - Edson Bor-Seng-Shu
- Department of Neurology, Faculty of Medicine, Hospital das Clinicas University of São Paulo, São Paulo, Brazil
| | - Alexander Caicedo
- Department of Applied Mathematics and Computer Science, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Bogotá, Colombia
| | - Max Chacon
- Department of Engineering Informatics, Institute of Biomedical Engineering, University of Santiago, Santiago, Chile
| | - Erik D Gommer
- Department of Clinical Neurophysiology, Maastricht University Medical Centre, Maastricht, Netherlands
| | - Sabine Van Huffel
- Department of Electronic Engineering (ESAT), Stadius Center for Dynamical Systems, Signal Processing and Data Analytics, Katholieke Universiteit Leuven, Leuven, Belgium.,Interuniversity Microelectronics Centre, Leuven, Belgium
| | - José L Jara
- Department of Engineering Informatics, Institute of Biomedical Engineering, University of Santiago, Santiago, Chile
| | - Kyriaki Kostoglou
- Department of Electrical, Computer and Software Engineering, McGill University, Montreal, QC, Canada
| | - Adam Mahdi
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Vasilis Z Marmarelis
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, QC, Canada
| | - Martin Müller
- Department of Neurology, Luzerner Kantonsspital, Luzern, Switzerland
| | - Dragana Nikolic
- Faculty of Engineering and the Environment, Institute of Sound and Vibration Research, University of Southampton, Southampton, United Kingdom
| | - Ricardo C Nogueira
- Department of Neurology, Faculty of Medicine, Hospital das Clinicas University of São Paulo, São Paulo, Brazil
| | - Stephen J Payne
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Corina Puppo
- Departamento de Emergencia, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay
| | - Dae C Shin
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - David M Simpson
- Faculty of Engineering and the Environment, Institute of Sound and Vibration Research, University of Southampton, Southampton, United Kingdom
| | - Takashi Tarumi
- Institute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Bernardo Yelicich
- Departamento de Emergencia, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay
| | - Rong Zhang
- Institute for Exercise and Environmental Medicine, Presbyterian Hospital of Dallas, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Jurgen A H R Claassen
- Department of Geriatric Medicine, Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
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Sanders ML, Claassen JAHR, Aries M, Bor-Seng-Shu E, Caicedo A, Chacon M, Gommer ED, Van Huffel S, Jara JL, Kostoglou K, Mahdi A, Marmarelis VZ, Mitsis GD, Müller M, Nikolic D, Nogueira RC, Payne SJ, Puppo C, Shin DC, Simpson DM, Tarumi T, Yelicich B, Zhang R, Panerai RB, Elting JWJ. Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study. Physiol Meas 2018; 39:125002. [PMID: 30523976 DOI: 10.1088/1361-6579/aae9fd] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
OBJECTIVE Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings have all led to a lack of standardisation and comparability between studies. We evaluated reproducibility of dCA parameters by assessing systematic errors in surrogate data resulting from different modelling techniques. APPROACH Fourteen centres analysed 22 datasets consisting of two repeated physiological blood pressure measurements with surrogate cerebral blood flow velocity signals, generated using Tiecks curves (autoregulation index, ARI 0-9) and added noise. For reproducibility, dCA methods were grouped in three broad categories: 1. Transfer function analysis (TFA)-like output; 2. ARI-like output; 3. Correlation coefficient-like output. For all methods, reproducibility was determined by one-way intraclass correlation coefficient analysis (ICC). MAIN RESULTS For TFA-like methods the mean (SD; [range]) ICC gain was 0.71 (0.10; [0.49-0.86]) and 0.80 (0.17; [0.36-0.94]) for VLF and LF (p = 0.003) respectively. For phase, ICC values were 0.53 (0.21; [0.09-0.80]) for VLF, and 0.92 (0.13; [0.44-1.00]) for LF (p < 0.001). Finally, ICC for ARI-like methods was equal to 0.84 (0.19; [0.41-0.94]), and for correlation-like methods, ICC was 0.21 (0.21; [0.056-0.35]). SIGNIFICANCE When applied to realistic surrogate data, free from the additional exogenous influences of physiological variability on cerebral blood flow, most methods of dCA modelling showed ICC values considerably higher than what has been reported for physiological data. This finding suggests that the poor reproducibility reported by previous studies may be mainly due to the inherent physiological variability of cerebral blood flow regulatory mechanisms rather than related to (stationary) random noise and the signal analysis methods.
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Affiliation(s)
- Marit L Sanders
- Department of Geriatric Medicine, Radboudumc Alzheimer Centre and Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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Shahzad T, Saleem S, Usman S, Mirza J, Islam QU, Ouahada K, Marwala T. System dynamics of active and passive postural changes: Insights from principal dynamic modes analysis of baroreflex loop. Comput Biol Med 2018; 100:27-35. [PMID: 29975851 DOI: 10.1016/j.compbiomed.2018.06.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Revised: 06/21/2018] [Accepted: 06/22/2018] [Indexed: 10/28/2022]
Abstract
The baroreflex being a key modulator of cardiovascular control ensures adequate blood pressure regulation under orthostatic stress which otherwise may cause severe hypotension. Contrary to conventional baroreflex sensitivity indices derived across a-priori traditional frequency bands, the present study is aimed at proposing new indices for the assessment of baroreflex drive which follows active (supine to stand-up) and passive (supine to head-up tilt) postural changes. To achieve this, a novel system identification approach of principal dynamic modes (PDM) was utilized to extract data-adaptive frequency components of closed-loop interactions between beat-to-beat interval and systolic blood pressure recorded from 10 healthy humans. We observed that the gain of low-pass global PDM of cardiac arm (:feedback reflex loop, mediated by pressure sensors to adjust heart rate in response to arterial blood pressure), and 0.2 Hz global PDM of mechanical arm (:feed-forward pathways, originating changes in arterial blood pressure in response to heart rate variations) may function as potential markers to distinguish active and passive orthostatic tests in healthy subjects.
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Affiliation(s)
- Tariq Shahzad
- Department of Electrical and Electronic Engineering Science, University of Johannesburg, South Africa.
| | - Saqib Saleem
- Department of Electrical Engineering, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, Pakistan.
| | - Saeeda Usman
- Department of Electrical Engineering, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, Pakistan.
| | - Jawad Mirza
- Department of Electrical Engineering, COMSATS University Islamabad, Islamabad, Pakistan.
| | - Qamar-Ul Islam
- Department of Space Science, Institute of Space Technology, Islamabad, Pakistan.
| | - Khmaies Ouahada
- Department of Electrical and Electronic Engineering Science, University of Johannesburg, South Africa.
| | - Tshilidzi Marwala
- Department of Electrical and Electronic Engineering Science, University of Johannesburg, South Africa.
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11
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Saleem S, Teal PD, Howe CA, Tymko MM, Ainslie PN, Tzeng YC. Is the Cushing mechanism a dynamic blood pressure-stabilizing system? Insights from Granger causality analysis of spontaneous blood pressure and cerebral blood flow. Am J Physiol Regul Integr Comp Physiol 2018; 315:R484-R495. [PMID: 29668325 DOI: 10.1152/ajpregu.00032.2018] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Blood pressure (BP) regulation is widely recognized as being integral to the control of end-organ perfusion, but it remains unclear whether end-organ perfusion also plays a role in driving changes in BP. A randomized and placebo-controlled study design was followed to examine feedback relationships between very-low-frequency fluctuations in BP and cerebral blood flow (CBF) in humans under placebo treatment and α1-adrenergic blockade. To determine the causal relations among hemodynamic variables, BP, middle cerebral artery blood velocity (MCAv), and end-tidal CO 2 time-series were decimated, low-pass filtered (<0.07 Hz), fitted to vector autoregressive models, and tested for Granger causality in the time domain. Results showed that 1) at baseline, changes in BP and MCAv often interact in a closed-loop; and 2) α1-adrenergic blockade results in the dominant causal direction from BP to MCAv. These results suggest that, between subjects, cerebral pressure-flow interactions at time scales < 0.07 Hz are frequently bidirectional, and that in the presence of an intact autonomic nervous system BP may be regulated by reflex pathways sensitive to changes in CBF.
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Affiliation(s)
- Saqib Saleem
- Department of Electrical Engineering, COMSATS Institute of Information Technology , Sahiwal , Pakistan.,Wellington Medical Technology Group, Centre for Translational Physiology, University of Otago , Wellington , New Zealand
| | - Paul D Teal
- School of Engineering and Computer Science, Victoria University of Wellington , Wellington , New Zealand
| | - Connor A Howe
- Centre for Heart, Lung and Vascular Health, School of Health and Exercise Science, University of British Columbia , Kelowna, British Columbia , Canada
| | - Michael M Tymko
- Centre for Heart, Lung and Vascular Health, School of Health and Exercise Science, University of British Columbia , Kelowna, British Columbia , Canada
| | - Philip N Ainslie
- Centre for Heart, Lung and Vascular Health, School of Health and Exercise Science, University of British Columbia , Kelowna, British Columbia , Canada
| | - Yu-Chieh Tzeng
- Wellington Medical Technology Group, Centre for Translational Physiology, University of Otago , Wellington , New Zealand
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12
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Lytton WW, Arle J, Bobashev G, Ji S, Klassen TL, Marmarelis VZ, Schwaber J, Sherif MA, Sanger TD. Multiscale modeling in the clinic: diseases of the brain and nervous system. Brain Inform 2017; 4:219-230. [PMID: 28488252 PMCID: PMC5709279 DOI: 10.1007/s40708-017-0067-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 04/27/2017] [Indexed: 12/26/2022] Open
Abstract
Computational neuroscience is a field that traces its origins to the efforts of Hodgkin and Huxley, who pioneered quantitative analysis of electrical activity in the nervous system. While also continuing as an independent field, computational neuroscience has combined with computational systems biology, and neural multiscale modeling arose as one offshoot. This consolidation has added electrical, graphical, dynamical system, learning theory, artificial intelligence and neural network viewpoints with the microscale of cellular biology (neuronal and glial), mesoscales of vascular, immunological and neuronal networks, on up to macroscales of cognition and behavior. The complexity of linkages that produces pathophysiology in neurological, neurosurgical and psychiatric disease will require multiscale modeling to provide understanding that exceeds what is possible with statistical analysis or highly simplified models: how to bring together pharmacotherapeutics with neurostimulation, how to personalize therapies, how to combine novel therapies with neurorehabilitation, how to interlace periodic diagnostic updates with frequent reevaluation of therapy, how to understand a physical disease that manifests as a disease of the mind. Multiscale modeling will also help to extend the usefulness of animal models of human diseases in neuroscience, where the disconnects between clinical and animal phenomenology are particularly pronounced. Here we cover areas of particular interest for clinical application of these new modeling neurotechnologies, including epilepsy, traumatic brain injury, ischemic disease, neurorehabilitation, drug addiction, schizophrenia and neurostimulation.
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Affiliation(s)
- William W. Lytton
- Department of Physiology and Pharmacology and Neurology, SUNY Downstate, Kings County Hospital, Brooklyn, NY 11203 USA
| | | | | | - Songbai Ji
- Thayer School of Engineering, Department of Surgery and of Orthopaedic Surgery, Geisel School of Medicine, Dartmouth College, Hanover, NH 3755 USA
| | | | | | | | - Mohamed A. Sherif
- Yale U, New Haven, CT USA
- VA Connecticut Healthcare System, West Haven, CT USA
- Ain Shams U Institute of Psychiatry, Cairo, Egypt
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13
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Saleem S, Tzeng YC, Kleijn WB, Teal PD. Detection of Impaired Sympathetic Cerebrovascular Control Using Functional Biomarkers Based on Principal Dynamic Mode Analysis. Front Physiol 2017; 7:685. [PMID: 28119628 PMCID: PMC5220091 DOI: 10.3389/fphys.2016.00685] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2016] [Accepted: 12/23/2016] [Indexed: 11/13/2022] Open
Abstract
This study sought to determine whether models of cerebrovascular function based on Laguerre-Volterra kernels that account for nonlinear cerebral blood flow (CBF) dynamics can detect the effects of functional cerebral sympathetic blockade. We retrospectively analyzed continuous beat-to-beat blood pressure, middle cerebral blood velocity, and partial-pressure of end-tidal CO2 (PETCO2) recordings from eighteen healthy individuals who were treated with either an oral dose of the α1-adrenergic receptor blocker Prazosin or a placebo treatment. The global principal dynamic modes (PDMs) were analyzed using Laguerre-Volterra kernels to examine the nonlinear system dynamics. Our principal findings were: (1) very low frequency (<0.03 Hz) linear components of first-order kernels for BP and PETCO2 are mutually coupled to CBF dynamics with the ability to separate individuals between control and blockade conditions, and (2) the gains of the nonlinear functions associated with low-pass and ≈0.03 Hz global PDMs for the BP are sensitive to sympathetic blockade. Collectively these results suggest that very low frequency global PDMs for BP may have potential utility as functional biomarkers of sympathetic neurovascular dysfunction which can occur in conditions like autonomic failure, stroke and traumatic brain injury.
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Affiliation(s)
- Saqib Saleem
- Department of Electrical Engineering, COMSATS Institute of Information Technology Sahiwal, Pakistan
| | - Yu-Chieh Tzeng
- Wellington Medical Technology Group, Centre for Translational Physiology, University of Otago Wellington, New Zealand
| | - W Bastiaan Kleijn
- School of Engineering and Computer Science, Victoria University of Wellington Wellington, New Zealand
| | - Paul D Teal
- School of Engineering and Computer Science, Victoria University of Wellington Wellington, New Zealand
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14
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Marmarelis VZ, Shin DC, Tarumi T, Zhang R. Comparison of Model-Based Indices of Cerebral Autoregulation and Vasomotor Reactivity Using Transcranial Doppler versus Near-Infrared Spectroscopy in Patients with Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2017; 56:89-105. [PMID: 27911329 PMCID: PMC5240580 DOI: 10.3233/jad-161004] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2016] [Indexed: 01/24/2023]
Abstract
We recently introduced model-based "physiomarkers" of dynamic cerebral autoregulation and CO2 vasomotor reactivity as an aid for diagnosis of early-stage Alzheimer's disease (AD) [1], where significant impairment of dynamic vasomotor reactivity (DVR) was observed in early-stage AD patients relative to age-matched controls. Milder impairment of DVR was shown in patients with amnestic mild cognitive impairment (MCI) using the same approach in a subsequent study [2]. The advocated approach utilizes subject-specific data-based models of cerebral hemodynamics to quantify the dynamic effects of resting-state changes in arterial blood pressure and end-tidal CO2 (the putative inputs) upon cerebral blood flow velocity (the putative output) measured at the middle cerebral artery via transcranial Doppler (TCD). The obtained input-output models are then used to compute model-based indices of DCA and DVR from model-predicted responses to an input pressure pulse or an input CO2 pulse, respectively. In this paper, we compare these model-based indices of DVR and DCA in 46 amnestic MCI patients, relative to 20 age-matched controls, using TCD measurements with their counterparts using Near-Infrared Spectroscopy (NIRS) measurements of blood oxygenation at the lateral prefrontal cortex in 43 patients and 22 age-matched controls. The goal of the study is to assess whether NIRS measurements can be used instead of TCD measurements to obtain model-based physiomarkers with comparable diagnostic utility. The results corroborate this view in terms of the ability of either output to yield model-based physiomarkers that can differentiate the group of aMCI patients from age-matched healthy controls.
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Affiliation(s)
- Vasilis Z. Marmarelis
- Biomedical Simulations Resource Center, University of Southern California, Los Angeles, CA, USA
| | - Dae C. Shin
- Biomedical Simulations Resource Center, University of Southern California, Los Angeles, CA, USA
| | - Takashi Tarumi
- Exercise Physiology & Rehabilitation Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Rong Zhang
- Exercise Physiology & Rehabilitation Center, UT Southwestern Medical Center, Dallas, TX, USA
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15
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Saleem S, Teal PD, Kleijn WB, Ainslie PN, Tzeng YC. Identification of human sympathetic neurovascular control using multivariate wavelet decomposition analysis. Am J Physiol Heart Circ Physiol 2016; 311:H837-48. [DOI: 10.1152/ajpheart.00254.2016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 06/16/2016] [Indexed: 02/07/2023]
Abstract
The dynamic regulation of cerebral blood flow (CBF) is thought to involve myogenic and chemoreflex mechanisms, but the extent to which the sympathetic nervous system also plays a role remains debated. Here we sought to identify the role of human sympathetic neurovascular control by examining cerebral pressure-flow relations using linear transfer function analysis and multivariate wavelet decomposition analysis that explicitly accounts for the confounding effects of dynamic end-tidal Pco2 (PetCO2) fluctuations. In 18 healthy participants randomly assigned to the α1-adrenergic blockade group ( n = 9; oral Prazosin, 0.05 mg/kg) or the placebo group ( n = 9), we recorded blood pressure, middle cerebral blood flow velocity, and breath-to-breath PetCO2. Analyses showed that the placebo administration did not alter wavelet phase synchronization index (PSI) values, whereas sympathetic blockade increased PSI for frequency components ≤0.03 Hz. Additionally, three-way interaction effects were found for PSI change scores, indicating that the treatment response varied as a function of frequency and whether PSI values were PetCO2 corrected. In contrast, sympathetic blockade did not affect any linear transfer function parameters. These data show that very-low-frequency CBF dynamics have a composite origin involving, not only nonlinear and nonstationary interactions between BP and PetCO2, but also frequency-dependent interplay with the sympathetic nervous system.
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Affiliation(s)
- Saqib Saleem
- School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand
- Interdisciplinary Neuroprotection Research Group, Centre for Translational Physiology, University of Otago, Wellington, New Zealand
| | - Paul D. Teal
- School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand
| | - W. Bastiaan Kleijn
- School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand
| | - Philip N. Ainslie
- Centre for Heart Lung and Vascular Health, School of Health and Exercise Science, University of British Columbia Okanagan, Kelowna, British Columbia, Canada
| | - Yu-Chieh Tzeng
- Interdisciplinary Neuroprotection Research Group, Centre for Translational Physiology, University of Otago, Wellington, New Zealand
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16
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Marmarelis VZ, Mitsis GD, Shin DC, Zhang R. Multiple-input nonlinear modelling of cerebral haemodynamics using spontaneous arterial blood pressure, end-tidal CO2 and heart rate measurements. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2016; 374:rsta.2015.0180. [PMID: 27044989 PMCID: PMC4822442 DOI: 10.1098/rsta.2015.0180] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/11/2016] [Indexed: 05/24/2023]
Abstract
In order to examine the effect of changes in heart rate (HR) upon cerebral perfusion and autoregulation, we include the HR signal recorded from 18 control subjects as a third input in a two-input model of cerebral haemodynamics that has been used previously to quantify the dynamic effects of changes in arterial blood pressure and end-tidal CO2upon cerebral blood flow velocity (CBFV) measured at the middle cerebral arteries via transcranial Doppler ultrasound. It is shown that the inclusion of HR as a third input reduces the output prediction error in a statistically significant manner, which implies that there is a functional connection between HR changes and CBFV. The inclusion of nonlinearities in the model causes further statistically significant reduction of the output prediction error. To achieve this task, we employ the concept of principal dynamic modes (PDMs) that yields dynamic nonlinear models of multi-input systems using relatively short data records. The obtained PDMs suggest model-driven quantitative hypotheses for the role of sympathetic and parasympathetic activity (corresponding to distinct PDMs) in the underlying physiological mechanisms by virtue of their relative contributions to the model output. These relative PDM contributions are subject-specific and, therefore, may be used to assess personalized characteristics for diagnostic purposes.
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Affiliation(s)
- V Z Marmarelis
- Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - G D Mitsis
- Bioengineering, McGill University, Montreal, Quebec, Canada
| | - D C Shin
- Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - R Zhang
- Institute for Exercise and Environmental Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
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17
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Li H, Guo Q, Inoue T, Polito VA, Tabuchi K, Hammer RE, Pautler RG, Taffet GE, Zheng H. Vascular and parenchymal amyloid pathology in an Alzheimer disease knock-in mouse model: interplay with cerebral blood flow. Mol Neurodegener 2014; 9:28. [PMID: 25108425 PMCID: PMC4132280 DOI: 10.1186/1750-1326-9-28] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Accepted: 08/05/2014] [Indexed: 12/31/2022] Open
Abstract
Background Accumulation and deposition of β-amyloid peptides (Aβ) in the brain is a central event in the pathogenesis of Alzheimer’s disease (AD). Besides the parenchymal pathology, Aβ is known to undergo active transport across the blood–brain barrier and cerebral amyloid angiopathy (CAA) is a prominent feature in the majority of AD. Although impaired cerebral blood flow (CBF) has been implicated in faulty Aβ transport and clearance, and cerebral hypoperfusion can exist in the pre-clinical phase of Alzheimer’s disease (AD), it is still unclear whether it is one of the causal factors for AD pathogenesis, or an early consequence of a multi-factor condition that would lead to AD at late stage. To study the potential interaction between faulty CBF and amyloid accumulation in clinical-relevant situation, we generated a new amyloid precursor protein (APP) knock-in allele that expresses humanized Aβ and a Dutch mutation in addition to Swedish/London mutations and compared this line with an equivalent knock-in line but in the absence of the Dutch mutation, both crossed onto the PS1M146V knock-in background. Results Introduction of the Dutch mutation results in robust CAA and parenchymal Aβ pathology, age-dependent reduction of spatial learning and memory deficits, and CBF reduction as detected by fMRI. Direct manipulation of CBF by transverse aortic constriction surgery on the left common carotid artery caused differential changes in CBF in the anterior and middle region of the cortex, where it is reduced on the left side and increased on the right side. However these perturbations in CBF resulted in the same effect: both significantly exacerbate CAA and amyloid pathology. Conclusions Our study reveals a direct and positive link between vascular and parenchymal Aβ; both can be modulated by CBF. The new APP knock-in mouse model recapitulates many symptoms of AD including progressive vascular and parenchymal Aβ pathology and behavioral deficits in the absence of APP overexpression.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Hui Zheng
- Huffington Center on Aging, Baylor College of Medicine, Houston, Texas 77030, USA.
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