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Hayes G, Sparks S, Pinto J, Bulte DP. Ramp protocol for non-linear cerebrovascular reactivity with transcranial doppler ultrasound. J Neurosci Methods 2025; 416:110381. [PMID: 39884440 DOI: 10.1016/j.jneumeth.2025.110381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2024] [Revised: 01/10/2025] [Accepted: 01/28/2025] [Indexed: 02/01/2025]
Abstract
BACKGROUND Cerebrovascular reactivity (CVR) reflects the ability of cerebral blood vessels to adjust their diameter in response to vasoactive stimuli, which is crucial for maintaining brain health. Traditional CVR assessments commonly use a two-point measurement, assuming a linear relationship between cerebral blood flow (CBF) and arterial CO2. However, this approach fails to capture non-linear characteristics, particularly the plateaus at extreme CO2 levels. NEW METHOD This study introduces a cost-effective, ramp-based end-tidal CO2 (PETCO2) protocol to assess non-linear aspects of CVR. Using transcranial Doppler ultrasound, we monitored blood velocity responses to progressive increases in arterial CO2 levels in eleven healthy adults, covering a spectrum from hypocapnia to hypercapnia. RESULTS All eleven participants successfully completed the protocol, with an average PETCO2 range of 26 ± 4 mmHg and blood velocity changes from -29 % to + 50 % relative to baseline. Non-linear CVR characteristics were observed in all subjects. Sigmoid models provided significantly better fits to the CVR data than linear models, while Bayesian approaches followed expected physiological ranges more accurately than least squares regression methods. COMPARISON WITH EXISTING METHODS Unlike traditional CVR methods, this ramp protocol captures the full, non-linear CVR profile. The sigmoid modeling approach offers a more accurate representation of cerebrovascular dynamics, particularly at CO2 extremes. CONCLUSIONS The PETCO2 ramp protocol with non-linear CVR modeling shows promise as an accessible and reliable tool for assessing CBF dynamics. With high completion rates, straightforward implementation, and low equipment cost, this approach holds significant potential for clinical applications in cerebrovascular health evaluation.
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Affiliation(s)
- Genevieve Hayes
- IBME, Department of Engineering Science, University of Oxford, Oxford UK.
| | - Sierra Sparks
- IBME, Department of Engineering Science, University of Oxford, Oxford UK
| | - Joana Pinto
- IBME, Department of Engineering Science, University of Oxford, Oxford UK
| | - Daniel P Bulte
- IBME, Department of Engineering Science, University of Oxford, Oxford UK
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2
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Zvolanek KM, Moore JE, Jarvis K, Moum SJ, Bright MG. Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence. J Cereb Blood Flow Metab 2025; 45:746-764. [PMID: 39534950 PMCID: PMC11563552 DOI: 10.1177/0271678x241298588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 09/09/2024] [Accepted: 10/17/2024] [Indexed: 11/16/2024]
Abstract
Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n = 12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity (CVR) in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.
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Affiliation(s)
- Kristina M Zvolanek
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA
| | - Jackson E Moore
- Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA
- Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Kelly Jarvis
- Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Sarah J Moum
- Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Medical Imaging, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA
| | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA
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Chan RW, Hamilton-Fletcher G, Edelman BJ, Faiq MA, Sajitha TA, Moeller S, Chan KC. NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:1-18. [PMID: 39463889 PMCID: PMC11506209 DOI: 10.1162/imag_a_00325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 10/29/2024]
Abstract
NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations. In this study, we evaluated the effects of NORDIC PCA compared with "Standard" processing in various rodent fMRI contexts that range from task-evoked optogenetic fMRI to resting-state fMRI. We also evaluated the effects of NORDIC PCA on human resting-state and retinotopic mapping fMRI via population receptive field (pRF) modeling. In rodent optogenetic fMRI, apart from doubling the tSNR, NORDIC PCA resulted in a larger number of activated voxels and a significant decrease in the variance of evoked brain responses without altering brain morphology. In rodent resting-state fMRI, we found that NORDIC PCA induced a nearly threefold increase in tSNR and preserved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. NORDIC PCA further improved the detection of TGN020-induced aquaporin-4 inhibition on rCVR compared with Standard processing without NORDIC PCA. NORDIC PCA also increased the tSNR for both human resting-state and pRF fMRI, and for the latter also increased activation cluster sizes while retaining retinotopic organization. This suggests that NORDIC PCA preserves the spatiotemporal precision of fMRI signals needed for pRF analysis, and effectively captures small activity changes with high sensitivity. Taken together, these results broadly demonstrate the value of NORDIC PCA for the enhanced detection of neural dynamics across various rodent and human fMRI contexts. This can in turn play an important role in improving fMRI image quality and sensitivity for translational and preclinical neuroimaging research.
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Affiliation(s)
- Russell W. Chan
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
- E-SENSE Innovation & Technology, Hong Kong, China
- Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Giles Hamilton-Fletcher
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Bradley J. Edelman
- Brain-Wide Circuits for Behavior Research Group, Max Planck Institute of Biological Intelligence, Planegg, Germany
- Emotion Research Department, Max Planck Institute of Psychiatry, Munich, Germany
| | - Muneeb A. Faiq
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Thajunnisa A. Sajitha
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
| | - Kevin C. Chan
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, Tandon School of Engineering, New York University, New York, NY, United States
- Department of Ophthalmology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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Sparks S, Hayes G, Pinto J, Bulte D. Characterising cerebrovascular reactivity and the pupillary light response-a comparative study. Front Physiol 2024; 15:1384113. [PMID: 39175613 PMCID: PMC11338921 DOI: 10.3389/fphys.2024.1384113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 07/29/2024] [Indexed: 08/24/2024] Open
Abstract
Introduction Smooth muscle is integral to multiple autonomic systems, including cerebrovascular dynamics through vascular smooth muscle cells and in ocular muscle dynamics, by regulating pupil size. In the brain, smooth muscle function plays a role in cerebrovascular reactivity (CVR) that describes changes in blood vessel calibre in response to vasoactive stimuli. Similarly, pupil size regulation can be measured using the pupillary light response (PLR), the pupil's reaction to changes in light levels. The primary aim of this study was to explore the interplay between cerebral blood flow and pupil dynamics, evaluated using CVR and PLR, respectively. Methods A total of 20 healthy adults took part in a CVR gas stimulus protocol and a light and dark flash PLR protocol. CVR was calculated as the blood flow velocity change in the middle cerebral artery, measured using transcranial Doppler ultrasound in response to a 5% increase in CO2. Multiple PLR metrics were evaluated with a clinical pupillometer. Results CVR and PLR metrics were all within the expected physiological ranges for healthy adults. Nine different PLR metrics, assessed through the light and dark flash protocols, were compared against CVR. A significant negative relationship was observed between the latency of the PLR in the dark flash protocol and CVR. No statistically significant relationships were found between CVR and other PLR metrics. Conclusion This is the first study to investigate the relationship between cerebral blood flow and pupil dynamics. A significant relationship between dark flash latency and CVR was observed. Future work includes evaluating these relationships using more robust CVR and PLR measurement techniques in a larger, more diverse cohort. Notably, more research is warranted into the PLR using a dark flash protocol and its connection to cerebrovascular function.
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Affiliation(s)
| | | | | | - Daniel Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
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Rajagopalan V, Truong V, Wang S, Lopez J, Rosas V, Borzage M, Votava-Smith JK, Ponrartana S, Panigrahy A, Detterich J, Wood J. Non-invasive in-utero quantification of vascular reactivity in human placenta. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 63:481-488. [PMID: 37820067 DOI: 10.1002/uog.27512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 09/26/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVE Placental vascular reactivity (PlVR) indicates the ability of the placental vasculature to match blood supply to fetal demand. Many pregnancy disorders alter the characteristics of PlVR, resulting in suboptimal oxygen delivery, although current understanding is limited by the lack of non-invasive, repeatable methods to measure PlVR in utero. Our objective was to quantify PlVR by measuring the placental response to transient changes in maternal carbon dioxide (CO2) using blood-oxygen-level-dependent (BOLD) magnetic resonance imaging (MRI). We hypothesized that PlVR will increase with gestational age to meet the changing demands of a growing fetus, and that PlVR will be driven by a maternal response to changes in CO2 concentration. METHODS This was a cross-sectional study of 35 women with a healthy singleton pregnancy, of whom 31 were included in the analysis. The median gestational age was 32.6 (range, 22.6-38.4) weeks. Pregnant women were instructed to follow audiovisual breathing cues during a MRI scan. Maternal end-tidal CO2 (EtCO2) was measured concurrently with resting placental BOLD MRI for a total of 7-8 min. Preprocessing of magnetic resonance images consisted of manual delineation of placental anatomy and motion correction. In each placental voxel, vascular reactivity was computed using a coherence-weighted general linear model between MRI signal and EtCO2 stimulus. Global PlVR was computed as the mean of voxel-wise PlVR values across the placenta. RESULTS PlVR, quantified by the placental response to induced, transient changes in maternal CO2, was consistently measured in utero using BOLD MRI. PlVR increased non-linearly with advancing gestational age (P < 0.001) and was higher on the fetal side of the placenta. PlVR was associated positively with fetal brain volume after accounting for gestational age. PlVR did not show any significant associations with maternal characteristics. CONCLUSIONS We present, for the first time, a non-invasive paradigm to quantify PlVR in ongoing human pregnancies without the use of exogenous gases or contrast agents. Our findings suggest that PlVR is driven by a fetal response to changes in maternal CO2. Ease of translation to the clinical setting makes PlVR a promising biomarker for the identification and management of high-risk pregnancies. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- V Rajagopalan
- Department of Radiology, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - V Truong
- University of Southern California, Los Angeles, CA, USA
| | - S Wang
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J Lopez
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - V Rosas
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - M Borzage
- Division of Neonatology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J K Votava-Smith
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - S Ponrartana
- University of Southern California, Los Angeles, CA, USA
| | - A Panigrahy
- Pediatric Imaging Research Lab, Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - J Detterich
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J Wood
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
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Xu B, Vu C, Borzage M, González-Zacarías C, Shen J, Wood J. Improved cerebrovascular reactivity mapping using coherence weighted general linear model in the frequency domain. Neuroimage 2023; 284:120448. [PMID: 37952392 PMCID: PMC10822713 DOI: 10.1016/j.neuroimage.2023.120448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 10/25/2023] [Accepted: 11/06/2023] [Indexed: 11/14/2023] Open
Abstract
Cerebrovascular reactivity (CVR) is a prognostic indicator of cerebrovascular health. Estimating CVR from endogenous end-tidal carbon dioxide (CO2) fluctuation and MRI signal recorded under resting state can be difficult due to the poor signal-to-noise ratio (SNR) of signals. Thus, we aimed to improve the method of estimating CVR from end-tidal CO2 and MRI signals. We proposed a coherence weighted general linear model (CW-GLM) to estimate CVR from the Fourier coefficients weighted by the signal coherence in frequency domain, which confers two advantages. First, it requires no signal alignment in time domain, which simplifies experimental methods. Second, it limits the GLM analysis within the frequency band where CO2 and MRI signals are highly correlated, which automatically suppresses noise and nuisance signals. We compared the performance of our method with time-domain GLM (TD-GLM) and frequency-domain GLM (FD-GLM) in both synthetic and in-vivo data; wherein we calculated CVR from signals recorded under both resting state and sinusoidal stimulus. In synthetic data, CW-GLM has a remarkable performance on CVR estimation from narrow band signals with a mean-absolute error of 0.7 % (gray matter) and 1.2 % (white matter), which was lower than all the other methods. Meanwhile, CW-GLM maintains a comparable performance on CVR estimation from resting signals, with a mean-absolute error of 4.1 % (gray matter) and 8 % (white matter). The superior performance was maintained across the 36 in-vivo measurements, with CW-GLM exhibiting limits of agreement of -16.7 % - 9.5 % between CVR calculated from the resting and sinusoidal CO2 paradigms which was 12 % - 209 % better than current time-domain methods. Evaluating of the cross-coherence spectrum revealed highest signal coherence within the frequency band from 0.01 Hz to 0.05 Hz, which overlaps with previously recommended frequency band (0.02 Hz to 0.04 Hz) for CVR analysis. Our data demonstrates that CW-GLM can work as a self-adaptive band-pass filter to improve CVR robustness, while also avoiding the need for signal temporal alignment.
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Affiliation(s)
- Botian Xu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States; Department of Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Chau Vu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States; Department of Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Matthew Borzage
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States; Division of Neonatology, Department of Pediatrics, Fetal and Neonatal Institute, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Clio González-Zacarías
- Department of Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States; Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, United States
| | - Jian Shen
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States; Department of Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - John Wood
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States; Department of Pediatrics and Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States.
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Mahler S, Huang YX, Liang M, Avalos A, Tyszka JM, Mertz J, Yang C. Assessing depth sensitivity in laser interferometry speckle visibility spectroscopy (iSVS) through source-to-detector distance variation and cerebral blood flow monitoring in humans and rabbits. BIOMEDICAL OPTICS EXPRESS 2023; 14:4964-4978. [PMID: 37791277 PMCID: PMC10545208 DOI: 10.1364/boe.498815] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 10/05/2023]
Abstract
Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to monitor cerebral blood flow. The technique, using a multi-pixel detecting device (e.g., camera), allows the detection of a larger number of speckles, increasing the proportion of light that is detected. Due to this increase, it is possible to collect light that has propagated deeper through the brain. As a direct consequence, cerebral blood flow can be monitored. However, isolating the cerebral blood flow from the other layers, such as the scalp or skull components, remains challenging. In this paper, we report our investigations on the depth-sensitivity of laser interferometry speckle visibility spectroscopy (iSVS). Specifically, we varied the depth of penetration of the laser light into the head by tuning the source-to-detector distance, and identified the transition point at which cerebral blood flow in humans and rabbits starts to be detected.
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Affiliation(s)
- Simon Mahler
- Department of Electrical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Yu Xi Huang
- Department of Electrical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Mingshu Liang
- Department of Electrical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Alan Avalos
- Office of Laboratory Animal Resources (OLAR), California Institute of Technology, Pasadena, California 91125, USA
| | - Julian M. Tyszka
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California 91125, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
- Neurophotonics Center, Boston University, Boston, Massachusetts 02215, USA
| | - Changhuei Yang
- Department of Electrical Engineering, California Institute of Technology, Pasadena, California 91125, USA
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Cowdrick KR, Urner T, Sathialingam E, Fang Z, Quadri A, Turrentine K, Yup Lee S, Buckley EM. Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression. NEUROPHOTONICS 2023; 10:025002. [PMID: 37034012 PMCID: PMC10079775 DOI: 10.1117/1.nph.10.2.025002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/07/2023] [Indexed: 06/19/2023]
Abstract
Significance Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed. Aim We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms. Approach Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions. Results Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ). Conclusions More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.
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Affiliation(s)
- Kyle R. Cowdrick
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Tara Urner
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Eashani Sathialingam
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Zhou Fang
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Ayesha Quadri
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Morehouse School of Medicine, Atlanta, Georgia, United States
| | - Katherine Turrentine
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Seung Yup Lee
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Kennesaw State University, Department of Electrical and Computer Engineering, Marietta, Georgia, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta, Children’s Research Scholar, Atlanta, Georgia, United States
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Zvolanek KM, Moia S, Dean JN, Stickland RC, Caballero-Gaudes C, Bright MG. Comparing end-tidal CO 2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI. Neuroimage 2023; 272:120038. [PMID: 36958618 DOI: 10.1016/j.neuroimage.2023.120038] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/27/2023] [Accepted: 03/14/2023] [Indexed: 03/25/2023] Open
Abstract
Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented method to map CVR involves using a breath-hold task during a BOLD fMRI scan. Recording end-tidal CO2 (PETCO2) changes during the breath-hold task is recommended to be used as a reference signal for modeling CVR amplitude in standard units (%BOLD/mmHg) and CVR delay in seconds. However, obtaining reliable PETCO2 recordings requires equipment and task compliance that may not be achievable in all settings. To address this challenge, we investigated two alternative reference signals to map CVR amplitude and delay in a lagged general linear model (lagged-GLM) framework: respiration volume per time (RVT) and average gray matter BOLD response (GM-BOLD). In 8 healthy adults with multiple scan sessions, we compare spatial agreement of CVR maps from RVT and GM-BOLD to those generated with PETCO2. We define a threshold to determine whether a PETCO2 recording has "sufficient" quality for CVR mapping and perform these comparisons in 16 datasets with sufficient PETCO2 and 6 datasets with insufficient PETCO2. When PETCO2 quality is sufficient, both RVT and GM-BOLD produce CVR amplitude maps that are nearly identical to those from PETCO2 (after accounting for differences in scale), with the caveat they are not in standard units to facilitate between-group comparisons. CVR delays are comparable to PETCO2 with an RVT regressor but may be underestimated with the average GM-BOLD regressor. Importantly, when PETCO2 quality is insufficient, RVT and GM-BOLD CVR recover reasonable CVR amplitude and delay maps, provided the participant attempted the breath-hold task. Therefore, our framework offers a solution for achieving high quality CVR maps in both retrospective and prospective studies where sufficient PETCO2 recordings are not available and especially in populations where obtaining reliable measurements is a known challenge (e.g., children). Our results have the potential to improve the accessibility of CVR mapping and to increase the prevalence of this promising metric of vascular health.
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Affiliation(s)
- Kristina M Zvolanek
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA.
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain; Medical Imaging Processing Lab (MIP:Lab), Neuro-X institute, EPFL, Geneva, Switzerland
| | - Joshua N Dean
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA
| | - Rachael C Stickland
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Molly G Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA
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Wei Z, Li Y, Hou X, Han Z, Xu J, McMahon MT, Duan W, Liu G, Lu H. Quantitative cerebrovascular reactivity MRI in mice using acetazolamide challenge. Magn Reson Med 2022; 88:2233-2241. [PMID: 35713368 PMCID: PMC9574885 DOI: 10.1002/mrm.29353] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/24/2022] [Accepted: 05/23/2022] [Indexed: 01/29/2023]
Abstract
PURPOSE To develop a quantitative MRI method to estimate cerebrovascular reactivity (CVR) in mice. METHODS We described an MRI procedure to measure cerebral vasodilatory response to acetazolamide (ACZ), a vasoactive agent previously used in human clinical imaging. Vascular response was determined by cerebral blood flow (CBF) measured with phase-contrast or pseudo-continuous arterial spin labeling MRI. Vasodilatory input intensity was determined by plasma ACZ level using high-performance liquid chromatography. We verified the source of the CVR MRI signal by comparing ACZ injection to phosphate-buffered saline injection and noninjection experiments. Dose dependence and feasibility of regional CVR measurement were also investigated. RESULTS Cerebral blood flow revealed an exponential increase following intravenous ACZ injection, with a time constant of 1.62 min. In contrast, phosphate-buffered saline or noninjection exhibited a slow linear CBF increase, consistent with a gradual accumulation of anesthetic agent, isoflurane, used in this study. When comparing different ACZ doses, injections of 30, 60, 120, and 180 mg/kg yielded a linear increase in plasma ACZ concentration (p < 0.0001). On the other hand, CBF changes under these doses were not different from each other (p = 0.50). The pseudo-continuous arterial spin labeling MRI with multiple postlabeling delays revealed similar vascular responses at different postlabeling delay values. There was a regional difference in CVR (p = 0.005), with isocortex (0.81 ± 0.17%/[μg/ml]) showing higher CVR than deep-brain regions. Mice receiving multiple ACZ injections lived for a minimum of 6 months after the study without noticeable aberrant behavior or appearance. CONCLUSIONS We demonstrated the proof-of-principle of a new quantitative CVR mapping technique in mice.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Yuguo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Zheng Han
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Michael T. McMahon
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Wenzhen Duan
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of medicine, Baltimore, Maryland, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of medicine, Baltimore, Maryland, USA
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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11
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Ciumas C, Rheims S, Ryvlin P. fMRI studies evaluating central respiratory control in humans. Front Neural Circuits 2022; 16:982963. [PMID: 36213203 PMCID: PMC9537466 DOI: 10.3389/fncir.2022.982963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
Abstract
A plethora of neural centers in the central nervous system control the fundamental respiratory pattern. This control is ensured by neurons that act as pacemakers, modulating activity through chemical control driven by changes in the O2/CO2 balance. Most of the respiratory neural centers are located in the brainstem, but difficult to localize on magnetic resonance imaging (MRI) due to their small size, lack of visually-detectable borders with neighboring areas, and significant physiological noise hampering detection of its activity with functional MRI (fMRI). Yet, several approaches make it possible to study the normal response to different abnormal stimuli or conditions such as CO2 inhalation, induced hypercapnia, volitional apnea, induced hypoxia etc. This review provides a comprehensive overview of the majority of available studies on central respiratory control in humans.
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Affiliation(s)
- Carolina Ciumas
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Lyon Neuroscience Research Center, Institut National de la Santé et de la Recherche Médicale U1028/CNRS UMR 5292 Lyon 1 University, Bron, France
- IDEE Epilepsy Institute, Lyon, France
| | - Sylvain Rheims
- Lyon Neuroscience Research Center, Institut National de la Santé et de la Recherche Médicale U1028/CNRS UMR 5292 Lyon 1 University, Bron, France
- IDEE Epilepsy Institute, Lyon, France
- Department of Functional Neurology and Epileptology, Hospices Civils de Lyon, Lyon, France
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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12
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science, and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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13
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Chan RW, Lee RP, Wu SY, Tse EL, Xue Y, Moeller S, Chan KC. NOise Reduction with DIstribution Corrected (NORDIC) PCA improves signal-to-noise in rodent resting-state and optogenetic functional MRI. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1847-1850. [PMID: 36086476 PMCID: PMC10259819 DOI: 10.1109/embc48229.2022.9871459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve rodent fMRI using NORDIC PCA has not been explored. In this study, we developed a rodent fMRI preprocessing pipeline by incorporating NORDIC and evaluated its performance in a range of rodent fMRI applications from resting-state fMRI to task-evoked fMRI using optogenetics. In resting-state fMRI, we demonstrated a significant increase in tSNR by more than 3 times after NORDIC correction with reduced variance and improved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. In optogenetic fMRI, apart from tSNR increase, more activated voxels and a significant decrease in the variance of activated brain signals were observed after NORDIC correction without apparent change in brain morphology. Taken together, our results signified the values of NORDIC correction for better detection of brain activities in rodent fMRI. Clinical Relevance: NORDIC PCA increases temporal signalto- noise ratio in rodent resting-state and task-evoked functional MRI, which can play an important role in improving the image quality for translational medicine and preclinical research, and for guiding future clinical neuroimaging.
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14
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Yew B, Jang JY, Dutt S, Li Y, Sible IJ, Gaubert A, Ho JK, Blanken AE, Marshall A, Shao X, Wang DJJ, Nation DA. Cerebrovascular reactivity deficits in cognitively unimpaired older adults: vasodilatory versus vasoconstrictive responses. Neurobiol Aging 2022; 113:55-62. [PMID: 35325813 PMCID: PMC10958374 DOI: 10.1016/j.neurobiolaging.2022.02.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 01/27/2022] [Accepted: 02/16/2022] [Indexed: 01/16/2023]
Abstract
Cerebrovascular reactivity (CVR) deficits may index vulnerability to vascular brain injury and cognitive impairment, but findings on age-related changes in CVR have been mixed, and no studies to date have directly compared age-related changes in CVR to hypercapnia versus hypocapnia. The present study compared CVR in 31 cognitively unimpaired older adults (ages 55-87) and 30 healthy younger adults (ages 18-28). Breath control tasks induced CVR to hypocapnia (0.1 Hz paced breathing) and hypercapnia (15s breath holds) during pseudo-continuous arterial spin labeling MRI. Relative to younger adults, cognitively unimpaired older adults displayed lower levels of global CVR under both hypocapnia and hypercapnia. In region-of-interest analyses, older adults exhibited attenuated CVR to hypocapnia in select frontal and temporal regions, and lower CVR to hypercapnia in all cortical, limbic, and subcortical regions examined, relative to younger adults. Results indicate age-related deficits in CVR are detectible even in cognitively unimpaired older adults and are disproportionately related to vasodilatory (hypercapnia) responses relative to vasoconstrictive (hypocapnia) responses. Findings may offer means for early detection of cerebrovascular dysfunction.
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Affiliation(s)
- Belinda Yew
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Jung Yun Jang
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Shubir Dutt
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Yanrong Li
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Isabel J Sible
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Aimée Gaubert
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Jean K Ho
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA
| | - Anna E Blanken
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Anisa Marshall
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Xingfeng Shao
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Daniel A Nation
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA; Department of Psychological Science, University of California, Irvine, Irvine, CA, USA.
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15
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Stickland RC, Zvolanek KM, Moia S, Ayyagari A, Caballero-Gaudes C, Bright MG. A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function. Neuroimage 2021; 239:118306. [PMID: 34175427 PMCID: PMC8552969 DOI: 10.1016/j.neuroimage.2021.118306] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/18/2021] [Accepted: 06/23/2021] [Indexed: 12/22/2022] Open
Abstract
Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO2 pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO2 pressure: a breath-hold task to induce hypercapnia (CO2 increase) and a cued deep breathing task to induce hypocapnia (CO2 decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO2 by systematically shifting the CO2 regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO2 and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.
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Affiliation(s)
- Rachael C Stickland
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
| | - Kristina M Zvolanek
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain; University of the Basque Country EHU/UPV, Donostia, Gipuzkoa, Spain
| | - Apoorva Ayyagari
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | | | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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16
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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: 1.8] [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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17
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Liu P, Liu G, Pinho MC, Lin Z, Thomas BP, Rundle M, Park DC, Huang J, Welch BG, Lu H. Cerebrovascular Reactivity Mapping Using Resting-State BOLD Functional MRI in Healthy Adults and Patients with Moyamoya Disease. Radiology 2021; 299:419-425. [PMID: 33687287 DOI: 10.1148/radiol.2021203568] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Cerebrovascular reserve, the potential capacity of brain tissue to receive more blood flow when needed, is a desirable marker in evaluating ischemic risk. However, current measurement methods require acetazolamide injection or hypercapnia challenge, prompting a clinical need for resting-state (RS) blood oxygen level-dependent (BOLD) functional MRI data to measure cerebrovascular reactivity (CVR). Purpose To optimize and evaluate an RS CVR MRI technique and demonstrate its relationship to neurosurgical treatment. Materials and Methods In this HIPAA-compliant study, RS BOLD functional MRI data collected in 170 healthy controls between December 2008 and September 2010 were retrospectively evaluated to identify the optimal frequency range of temporal filtering on the basis of spatial correlation with the reference standard CVR map obtained with CO2 inhalation. Next, the optimized RS method was applied in a new, prospective cohort of 50 participants with Moyamoya disease who underwent imaging between June 2014 and August 2019. Finally, CVR values were compared between brain hemispheres with and brain hemispheres without revascularization surgery by using Mann-Whitney U test. Results A total of 170 healthy controls (mean age ± standard deviation, 51 years ± 20; 105 women) and 100 brain hemispheres of 50 participants with Moyamoya disease (mean age, 41 years ± 12; 43 women) were evaluated. RS CVR maps based on a temporal filtering frequency of [0, 0.1164 Hz] yielded the highest spatial correlation (r = 0.74) with the CO2 inhalation CVR results. In patients with Moyamoya disease, 77 middle cerebral arteries (MCAs) had stenosis. RS CVR in the MCA territory was lower in the group that did not undergo surgery (n = 30) than in the group that underwent surgery (n = 47) (mean, 0.407 relative units [ru] ± 0.208 vs 0.532 ru ± 0.182, respectively; P = .006), which is corroborated with the CO2 inhalation CVR data (mean, 0.242 ru ± 0.273 vs 0.437 ru ± 0.200; P = .003). Conclusion Cerebrovascular reactivity mapping performed by using resting-state blood oxygen level-dependent functional MRI provided a task-free method to measure cerebrovascular reserve and depicted treatment effect of revascularization surgery in patients with Moyamoya disease comparable to that with the reference standard of CO2 inhalation MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wolf and Ware in this issue.
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Affiliation(s)
- Peiying Liu
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Gongkai Liu
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Marco C Pinho
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Zixuan Lin
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Binu P Thomas
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Melissa Rundle
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Denise C Park
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Judy Huang
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Babu G Welch
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
| | - Hanzhang Lu
- From the Departments of Radiology (P.L., G.L., Z.L., H.L.) and Neurosurgery (J.H.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Park 324, Baltimore, MD 21287; Department of Radiology (M.C.P., B.G.W.), Advanced Imaging Research Center (M.C.P., B.P.T.), and Department of Neurologic Surgery (B.G.W.), UT Southwestern Medical Center, Dallas, Tex; and Center for Vital Longevity, University of Texas at Dallas, Dallas, Tex (M.R., D.C.P.)
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Moia S, Termenon M, Uruñuela E, Chen G, Stickland RC, Bright MG, Caballero-Gaudes C. ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI. Neuroimage 2021; 233:117914. [PMID: 33684602 PMCID: PMC8351526 DOI: 10.1016/j.neuroimage.2021.117914] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/25/2021] [Accepted: 02/22/2021] [Indexed: 12/19/2022] Open
Abstract
Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.
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Affiliation(s)
- Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Spain; University of the Basque Country UPV/EHU, Donostia, Spain.
| | - Maite Termenon
- Basque Center on Cognition, Brain and Language, Donostia, Spain
| | - Eneko Uruñuela
- Basque Center on Cognition, Brain and Language, Donostia, Spain; University of the Basque Country UPV/EHU, Donostia, Spain
| | - Gang Chen
- Scientific and Statistical Computing Core, NIMH/NIH/HHS, Bethesda, MD, United States
| | - Rachael C Stickland
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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Pinto J, Bright MG, Bulte DP, Figueiredo P. Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide. Front Physiol 2021; 11:608475. [PMID: 33536935 PMCID: PMC7848198 DOI: 10.3389/fphys.2020.608475] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/02/2020] [Indexed: 01/08/2023] Open
Abstract
Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.
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Affiliation(s)
- Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Molly G. Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Daniel P. Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Patrícia Figueiredo
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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