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Butters E, Srinivasan S, O'Brien JT, Su L, Bale G. A promising tool to explore functional impairment in neurodegeneration: A systematic review of near-infrared spectroscopy in dementia. Ageing Res Rev 2023; 90:101992. [PMID: 37356550 DOI: 10.1016/j.arr.2023.101992] [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: 04/07/2023] [Revised: 06/15/2023] [Accepted: 06/22/2023] [Indexed: 06/27/2023]
Abstract
This systematic review aimed to evaluate previous studies which used near-infrared spectroscopy (NIRS) in dementia given its suitability as a diagnostic and investigative tool in this population. From 800 identified records which used NIRS in dementia and prodromal stages, 88 studies were evaluated which employed a range of tasks testing memory (29), word retrieval (24), motor (8) and visuo-spatial function (4), and which explored the resting state (32). Across these domains, dementia exhibited blunted haemodynamic responses, often localised to frontal regions of interest, and a lack of task-appropriate frontal lateralisation. Prodromal stages, such as mild cognitive impairment, revealed mixed results. Reduced cognitive performance accompanied by either diminished functional responses or hyperactivity was identified, the latter suggesting a compensatory response not present at the dementia stage. Despite clear evidence of alterations in brain oxygenation in dementia and prodromal stages, a consensus as to the nature of these changes is difficult to reach. This is likely partially due to the lack of standardisation in optical techniques and processing methods for the application of NIRS to dementia. Further studies are required exploring more naturalistic settings and a wider range of dementia subtypes.
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Affiliation(s)
- Emilia Butters
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK; Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Sruthi Srinivasan
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Neuroscience, University of Sheffield, 385a Glossop Rd, Broomhall, Sheffield S10 2HQ, UK
| | - Gemma Bale
- Department of Physics, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0FA, UK
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2
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Wei W, Li X, Feng L, Jiao J, Li W, Cai Y, Fang R, Han Y. The effect of intraoperative transnasal humidified rapid-insufflation ventilatory exchange on emergence from general anesthesia in patients undergoing microlaryngeal surgery: a randomized controlled trial. BMC Anesthesiol 2023; 23:202. [PMID: 37312020 DOI: 10.1186/s12871-023-02169-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 06/08/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND Transnasal humidified rapid-insufflation ventilatory exchange (THRIVE) has received extensive attention for its utility in tubeless anesthesia. Still, the effects of its carbon dioxide accumulation on emergence from anesthesia have not been reported. This randomized controlled trial aimed at exploring the impact of THRIVE combined with laryngeal mask (LM) on the quality of emergence in patients undergoing microlaryngeal surgery. METHODS After research ethics board approval, 40 eligible patients receiving elective microlaryngeal vocal cord polypectomy were randomly allocated 1:1 to two groups, THRIVE + LM group: intraoperative apneic oxygenation using THRIVE followed by mechanical ventilation through a laryngeal mask in the post-anesthesia care unit (PACU), or MV + ETT group: mechanically ventilated through an endotracheal tube for both intraoperative and post-anesthesia periods. The primary outcome was duration of PACU stay. Other parameters reflecting quality of emergence and carbon dioxide accumulation were also recorded. RESULTS Duration of PACU stay (22.4 ± 6.4 vs. 28.9 ± 8.8 min, p = 0.011) was shorter in the THRIVE + LM group. The incidence of cough (2/20, 10% vs. 19/20, 95%, P < 0.001) was significantly lower in the THRIVE + LM group. Peripheral arterial oxygen saturation and mean arterial pressure during intraoperative and PACU stay, Quality of Recovery Item 40 total score at one day after surgery and Voice Handicap Index-10 score at seven days after surgery were of no difference between two groups. CONCLUSIONS The THRIVE + LM strategy could accelerate emergence from anesthesia and reduce the incidence of cough without compromising oxygenation. However, these benefits did not convert to the QoR-40 and VHI-10 scores improvement. TRIAL REGISTRATION ChiCTR2000038652.
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Affiliation(s)
- Wei Wei
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China
| | - Xiang Li
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China
| | - Lili Feng
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China
| | - Jiali Jiao
- Institute of Translational Medicine, Shanghai Jiao Tong University, Minhang District, Shanghai, China
| | - Wenxian Li
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China
| | - Yirong Cai
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China
| | - Rui Fang
- Department of Otolaryngology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, China
| | - Yuan Han
- Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Xuhui District, Shanghai, 200031, China.
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Keles HO, Karakulak EZ, Hanoglu L, Omurtag A. Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy. Front Hum Neurosci 2022; 16:1061668. [PMID: 36518566 PMCID: PMC9742284 DOI: 10.3389/fnhum.2022.1061668] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/01/2022] [Indexed: 08/10/2023] Open
Abstract
INTRODUCTION Alzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million new cases every year. There is a need for relatively less costly and more objective methods of screening and early diagnosis. METHODS Functional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD. For a practical clinically relevant system, a smaller number of optimally placed channels are clearly preferable. In this study, we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations. Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study. RESULTS We have shown that resting-state fNIRS recordings from a small number of prefrontal locations provide a promising methodology for detecting AD and monitoring its progression. A high-density continuous-wave fNIRS system was first used to verify the relatively lower hemodynamic activity in the prefrontal cortical areas observed in patients with AD. By using the episode averaged standard deviation of the oxyhemoglobin concentration changes as features that were fed into a Support Vector Machine; we then showed that the accuracy of subsets of optical channels in predicting the presence and severity of AD was significantly above chance. The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score with ≤5 channels. DISCUSSION These scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression.
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Affiliation(s)
- Hasan Onur Keles
- Department of Biomedical Engineering, Ankara University, Ankara, Turkey
| | | | - Lutfu Hanoglu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Ahmet Omurtag
- Department of Engineering, Nottingham Trent University, Nottingham, United Kingdom
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4
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Trambaiolli LR, Cassani R, Biazoli CE, Cravo AM, Sato JR, Falk TH. Multimodal resting-state connectivity predicts affective neurofeedback performance. Front Hum Neurosci 2022; 16:977776. [PMID: 36158618 PMCID: PMC9493361 DOI: 10.3389/fnhum.2022.977776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.
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Affiliation(s)
- Lucas R. Trambaiolli
- Basic Neuroscience Division, McLean Hospital–Harvard Medical School, Belmont, MA, United States
| | - Raymundo Cassani
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Claudinei E. Biazoli
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom
| | - André M. Cravo
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - João R. Sato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- Big Data, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Tiago H. Falk
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC, Canada
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Yang D, Hong KS. Quantitative Assessment of Resting-State for Mild Cognitive Impairment Detection: A Functional Near-Infrared Spectroscopy and Deep Learning Approach. J Alzheimers Dis 2021; 80:647-663. [PMID: 33579839 DOI: 10.3233/jad-201163] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
BACKGROUND Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease. Early diagnosis of MCI can allow for treatment to improve cognitive function and reduce modifiable risk factors. OBJECTIVE This study aims to investigate the feasibility of individual MCI detection from healthy control (HC) using a minimum duration of resting-state functional near-infrared spectroscopy (fNIRS) signals. METHODS In this study, nine different measurement durations (i.e., 30, 60, 90, 120, 150, 180, 210, 240, and 270 s) were evaluated for MCI detection via the graph theory analysis and traditional machine learning approach, such as linear discriminant analysis, support vector machine, and K-nearest neighbor algorithms. Moreover, feature representation- and classification-based transfer learning (TL) methods were applied to identify MCI from HC through the input of connectivity maps with 30 and 90 s duration. RESULTS There was no significant difference among the nine various time windows in the machine learning and graph theory analysis. The feature representation-based TL showed improved accuracy in both 30 and 90 s cases (i.e., 30 s: 81.27% and 90 s: 76.73%). Notably, the classification-based TL method achieved the highest accuracy of 95.81% using the pre-trained convolutional neural network (CNN) model with the 30 s interval functional connectivity map input. CONCLUSION The results indicate that a 30 s measurement of the resting-state with fNIRS could be used to detect MCI. Moreover, the combination of neuroimaging (e.g., functional connectivity maps) and deep learning methods (e.g., CNN and TL) can be considered as novel biomarkers for clinical computer-assisted MCI diagnosis.
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Affiliation(s)
- Dalin Yang
- School of Mechanical Engineering, Pusan National University, Guemjeong-gu, Busan, Republic of Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Guemjeong-gu, Busan, Republic of Korea.,Department of Cogno-Mechatronics Engineering, Pusan National University, Guemjeong-gu, Busan, Republic of Korea
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Bonilauri A, Sangiuliano Intra F, Pugnetti L, Baselli G, Baglio F. A Systematic Review of Cerebral Functional Near-Infrared Spectroscopy in Chronic Neurological Diseases-Actual Applications and Future Perspectives. Diagnostics (Basel) 2020; 10:E581. [PMID: 32806516 PMCID: PMC7459924 DOI: 10.3390/diagnostics10080581] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 08/06/2020] [Accepted: 08/07/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The management of people affected by age-related neurological disorders requires the adoption of targeted and cost-effective interventions to cope with chronicity. Therapy adaptation and rehabilitation represent major targets requiring long-term follow-up of neurodegeneration or, conversely, the promotion of neuroplasticity mechanisms. However, affordable and reliable neurophysiological correlates of cerebral activity to be used throughout treatment stages are often lacking. The aim of this systematic review is to highlight actual applications of functional Near-Infrared Spectroscopy (fNIRS) as a versatile optical neuroimaging technology for investigating cortical hemodynamic activity in the most common chronic neurological conditions. METHODS We reviewed studies investigating fNIRS applications in Parkinson's Disease (PD), Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) as those focusing on motor and cognitive impairment in ageing and Multiple Sclerosis (MS) as the most common chronic neurological disease in young adults. The literature search was conducted on NCBI PubMed and Web of Science databases by PRISMA guidelines. RESULTS We identified a total of 63 peer-reviewed articles. The AD spectrum is the most investigated pathology with 40 articles ranging from the traditional monitoring of tissue oxygenation to the analysis of functional resting-state conditions or cognitive functions by means of memory and verbal fluency tasks. Conversely, applications in PD (12 articles) and MS (11 articles) are mainly focused on the characterization of motor functions and their association with dual-task conditions. The most investigated cortical area is the prefrontal cortex, since reported to play an important role in age-related compensatory mechanism and neurofunctional changes associated to these chronic neurological conditions. Interestingly, only 9 articles applied a longitudinal approach. CONCLUSION The results indicate that fNIRS is mainly employed for the cross-sectional characterization of the clinical phenotypes of these pathologies, whereas data on its utility for longitudinal monitoring as surrogate biomarkers of disease progression and rehabilitation effects are promising but still lacking.
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Affiliation(s)
- Augusto Bonilauri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy; (A.B.); (G.B.)
| | - Francesca Sangiuliano Intra
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy; (L.P.); (F.B.)
- Faculty of Education, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
| | - Luigi Pugnetti
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy; (L.P.); (F.B.)
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy; (A.B.); (G.B.)
| | - Francesca Baglio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy; (L.P.); (F.B.)
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Yang D, Huang R, Yoo SH, Shin MJ, Yoon JA, Shin YI, Hong KS. Detection of Mild Cognitive Impairment Using Convolutional Neural Network: Temporal-Feature Maps of Functional Near-Infrared Spectroscopy. Front Aging Neurosci 2020; 12:141. [PMID: 32508627 PMCID: PMC7253632 DOI: 10.3389/fnagi.2020.00141] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 04/27/2020] [Indexed: 12/16/2022] Open
Abstract
Mild cognitive impairment (MCI) is the clinical precursor of Alzheimer's disease (AD), which is considered the most common neurodegenerative disease in the elderly. Some MCI patients tend to remain stable over time and do not evolve to AD. It is essential to diagnose MCI in its early stages and provide timely treatment to the patient. In this study, we propose a neuroimaging approach to identify MCI using a deep learning method and functional near-infrared spectroscopy (fNIRS). For this purpose, fifteen MCI subjects and nine healthy controls (HCs) were asked to perform three mental tasks: N-back, Stroop, and verbal fluency (VF) tasks. Besides examining the oxygenated hemoglobin changes (ΔHbO) in the region of interest, ΔHbO maps at 13 specific time points (i.e., 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, and 65 s) during the tasks and seven temporal feature maps (i.e., two types of mean, three types of slope, kurtosis, and skewness) in the prefrontal cortex were investigated. A four-layer convolutional neural network (CNN) was applied to identify the subjects into either MCI or HC, individually, after training the CNN model with ΔHbO maps and temporal feature maps above. Finally, we used the 5-fold cross-validation approach to evaluate the performance of the CNN. The results of temporal feature maps exhibited high classification accuracies: The average accuracies for the N-back task, Stroop task, and VFT, respectively, were 89.46, 87.80, and 90.37%. Notably, the highest accuracy of 98.61% was achieved from the ΔHbO slope map during 20-60 s interval of N-back tasks. Our results indicate that the fNIRS imaging approach based on temporal feature maps is a promising diagnostic method for early detection of MCI and can be used as a tool for clinical doctors to identify MCI from their patients.
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Affiliation(s)
- Dalin Yang
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
| | - Ruisen Huang
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
| | - So-Hyeon Yoo
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
| | - Myung-Jun Shin
- Department of Rehabilitation Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, South Korea
| | - Jin A Yoon
- Department of Rehabilitation Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, South Korea
| | - Yong-Il Shin
- Department of Rehabilitation Medicine, Pusan National University School of Medicine, Pusan National University Yangsan Hospital, Yangsan-si, South Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
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Yeung MK, Chan AS. Functional near-infrared spectroscopy reveals decreased resting oxygenation levels and task-related oxygenation changes in mild cognitive impairment and dementia: A systematic review. J Psychiatr Res 2020; 124:58-76. [PMID: 32120065 DOI: 10.1016/j.jpsychires.2020.02.017] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/17/2020] [Accepted: 02/19/2020] [Indexed: 02/06/2023]
Abstract
Nuclear medicine and functional magnetic resonance imaging studies have shown that mild cognitive impairment (MCI) and dementia, including Alzheimer's disease (AD), are characterized by changes in cerebral blood flow. This article reviews the application of an alternative method, functional near-infrared spectroscopy (fNIRS), to the study of cerebral oxygenation changes in MCI and dementia. We synthesized 36 fNIRS studies that examined hemodynamic changes during both the resting state and the execution of tasks of word retrieval, memory, motor control, and visuospatial perception in MCI and dementia. This qualitative review reveals that (amnestic) MCI and AD patients have disrupted frontal and long-range connectivity in the resting state compared to individuals with normal cognition (NC). These patients also exhibit reduced frontal oxygenation changes in various cognitive domains. The review also shows that disrupted connectivity and decreased frontal oxygenation levels/changes are more severe in AD than in (amnestic) MCI, confirming that MCI is an intermediate stage between NC and dementia. Thus, there is reduced resting frontal perfusion, which is greater than expected for age, and a lack of frontal compensatory responses to functional decline across cognitive operations (i.e., word retrieval and memory functioning) in MCI and AD. These indices might potentially serve as perfusion- or oxygenation-based biomarkers for MCI/dementia. To expand the utility of fNIRS for MCI and dementia, further studies that measure tissue oxygenation in a wider range of brain regions and cognitive domains, compare different MCI and dementia types, and correlate changes in cerebral oxygenation over time with disease progression are needed.
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Affiliation(s)
- Michael K Yeung
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Agnes S Chan
- Neuropsychology Laboratory, Department of Psychology, The Chinese University of Hong Kong, Hong Kong SAR, China; Chanwuyi Research Center for Neuropsychological Well-being, The Chinese University of Hong Kong, Hong Kong SAR, China.
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9
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Lemaire G, Courcelle R, Navarra E, Momeni M. Abrupt Suppression of Electroencephalographic Activity Due to Acute Hypercapnic Event Under Cardiopulmonary Bypass Detected by the NeuroSENSE Depth-of-Anesthesia Monitor. J Cardiothorac Vasc Anesth 2019; 34:179-183. [PMID: 31378651 DOI: 10.1053/j.jvca.2019.07.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/23/2019] [Accepted: 07/09/2019] [Indexed: 11/11/2022]
Affiliation(s)
- Guillaume Lemaire
- Department of Anesthesiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium.
| | - Romain Courcelle
- Department of Anesthesiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Emiliano Navarra
- Department of Cardiothoracic and Vascular Surgery, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Mona Momeni
- Department of Anesthesiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
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10
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Beishon L, Haunton VJ, Panerai RB, Robinson TG. Cerebral Hemodynamics in Mild Cognitive Impairment: A Systematic Review. J Alzheimers Dis 2018; 59:369-385. [PMID: 28671118 DOI: 10.3233/jad-170181] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The incidence of dementia is projected to rise over the coming decades, but with no sensitive diagnostic tests available. Vascular pathology precedes the deposition of amyloid and is an attractive early target. OBJECTIVE The aim of this review was to investigate the use of cerebral hemodynamics and oxygenation as a novel biomarker for mild cognitive impairment (MCI), focusing on transcranial Doppler ultrasonography (TCD) and near-infrared spectroscopy (NIRS). METHODS 2,698 articles were identified from Medline, Embase, PsychINFO, and Web of Science databases. 306 articles were screened and quality assessed independently by two reviewers; 26 met the inclusion criteria. Meta-analyses were performed for each marker with two or more studies and limited heterogeneity. RESULTS Eleven studies were TCD, 8 NIRS, 5 magnetic resonance imaging, and 2 positron/single photon emission tomography. Meta-analyses showed reduced tissue oxygenation index, cerebral blood flow and velocity, with higher pulsatility index, phase and cerebrovascular resistance in MCI compared to controls. The majority of studies found reduced CO2 reactivity in MCI, with mixed findings in neuroactivation studies. CONCLUSION Despite small sample sizes and heterogeneity, meta-analyses demonstrate clear abnormalities in cerebral hemodynamic and oxygenation parameters, even at an early stage of cognitive decline. Further work is required to investigate the use of cerebral hemodynamic and oxygenation parameters as a sensitive biomarker for dementia.
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Affiliation(s)
- Lucy Beishon
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Victoria J Haunton
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.,NIHR Biomedical Research Unit in Cardiovascular Disease, British Heart Foundation Cardiovascular Research Centre, Glenfield Hospital, Leicester, UK
| | - Ronney B Panerai
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.,NIHR Biomedical Research Unit in Cardiovascular Disease, British Heart Foundation Cardiovascular Research Centre, Glenfield Hospital, Leicester, UK
| | - Thompson G Robinson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.,NIHR Biomedical Research Unit in Cardiovascular Disease, British Heart Foundation Cardiovascular Research Centre, Glenfield Hospital, Leicester, UK
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11
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Beishon LC, Williams CAL, Panerai RB, Robinson TG, Haunton VJ. The assessment of neurovascular coupling with the Addenbrooke’s Cognitive Examination: a functional transcranial Doppler ultrasonographic study. J Neurophysiol 2018; 119:1084-1094. [DOI: 10.1152/jn.00698.2017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Cerebrovascular dysfunction occurs early in dementia and can be identified by transcranial Doppler ultrasonography (TCD). Few studies have examined cerebral blood flow velocity (CBFv) responses to a detailed cognitive battery. This study aimed to characterize all CBFv responses, and the effect of hemispheric dominance, to the Addenbrooke’s Cognitive Examination (ACE-III) in healthy volunteers. Forty volunteers underwent continuous bilateral TCD, beat-to-beat blood pressure (MAP; Finapres), heart rate (HR; electrocardiogram), and end-tidal CO2 (ETCO2; capnography) monitoring. After a 5-min baseline period, all tasks from the ACE-III were performed in 3 sections (A: attention, fluency, memory; B: language; C: visuospatial, memory). Data are population mean normalized percentage (PM%) change from a 20-s baseline period before task initiation. Forty bilateral data sets were obtained (27 women, 37 right-hand dominant). All paradigms produced a sharp increase in CBFv in both dominant (PM% range: 3.29 to 9.70%) and nondominant (PM% range: 4.34 to 11.63%) hemispheres at task initiation, with associated increases in MAP (PM% range: 3.06 to 16.04%). ETCO2 did not differ significantly at task initiation (PM% range: −1.1 to 2.4%, P > 0.05). HR differed significantly across A and C tasks at initiation (PM% range: −1.1 to 2.4%, P < 0.05), but not B tasks. In conclusion, all tasks resulted in increases in CBFv, differing significantly between paradigms. These results require further investigation in a cognitively impaired population. NEW & NOTEWORTHY This study is the first to provide a normative data set of cerebral blood flow velocity (CBFv) responses to a complete cognitive assessment (Addenbrooke’s Cognitive Examination, ACE-III) in a large sample ( n = 40) of healthy volunteers. All tasks produced peak and sustained increases in CBFv to different extents. The ACE-III is a feasible tool to assess neurovascular coupling with transcranial Doppler ultrasonography. These data can be used to inform the most appropriate cognitive task to elicit CBFv responses for future studies.
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Affiliation(s)
- Lucy C. Beishon
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | - Claire A. L. Williams
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | - Ronney B. Panerai
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom
| | - Thompson G. Robinson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom
| | - Victoria J. Haunton
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom
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12
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Chiarelli AM, Zappasodi F, Di Pompeo F, Merla A. Simultaneous functional near-infrared spectroscopy and electroencephalography for monitoring of human brain activity and oxygenation: a review. NEUROPHOTONICS 2017; 4:041411. [PMID: 28840162 PMCID: PMC5566595 DOI: 10.1117/1.nph.4.4.041411] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 07/24/2017] [Indexed: 05/24/2023]
Abstract
Multimodal monitoring has become particularly common in the study of human brain function. In this context, combined, synchronous measurements of functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) are getting increased interest. Because of the absence of electro-optical interference, it is quite simple to integrate these two noninvasive recording procedures of brain activity. fNIRS and EEG are both scalp-located procedures. fNIRS estimates brain hemodynamic fluctuations relying on spectroscopic measurements, whereas EEG captures the macroscopic temporal dynamics of brain electrical activity through passive voltages evaluations. The "orthogonal" neurophysiological information provided by the two technologies and the increasing interest in the neurovascular coupling phenomenon further encourage their integration. This review provides, together with an introduction regarding the principles and future directions of the two technologies, an evaluation of major clinical and nonclinical applications of this flexible, low-cost combination of neuroimaging modalities. fNIRS-EEG systems exploit the ability of the two technologies to be conducted in an environment or experimental setting and/or on subjects that are generally not suited for other neuroimaging modalities, such as functional magnetic resonance imaging, positron emission tomography, and magnetoencephalography. fNIRS-EEG brain monitoring settles itself as a useful multimodal tool for brain electrical and hemodynamic activity investigation.
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Affiliation(s)
- Antonio M. Chiarelli
- University of Illinois at Urbana Champaign, Beckman Institute, Urbana, Illinois, United States
| | - Filippo Zappasodi
- Università G. d’Annunzio, Department of Neuroscience, Imaging and Clinical Science, Chieti, Italy
- Università G. d’Annunzio, Institute for Advanced Biomedical Technologies, Chieti, Italy
| | - Francesco Di Pompeo
- Università G. d’Annunzio, Department of Neuroscience, Imaging and Clinical Science, Chieti, Italy
- Università G. d’Annunzio, Institute for Advanced Biomedical Technologies, Chieti, Italy
| | - Arcangelo Merla
- Università G. d’Annunzio, Department of Neuroscience, Imaging and Clinical Science, Chieti, Italy
- Università G. d’Annunzio, Institute for Advanced Biomedical Technologies, Chieti, Italy
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Effects of transcranial direct current stimulation on the functional coupling of the sensorimotor cortical network. Neuroimage 2016; 140:50-6. [DOI: 10.1016/j.neuroimage.2016.01.051] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 01/18/2016] [Accepted: 01/22/2016] [Indexed: 11/21/2022] Open
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Memory Assessment in the Clinical Context Using Functional Magnetic Resonance Imaging. Neuroimaging Clin N Am 2014; 24:585-97. [DOI: 10.1016/j.nic.2014.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Castellazzi G, Palesi F, Casali S, Vitali P, Sinforiani E, Wheeler-Kingshott CAM, D'Angelo E. A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia. Front Neurosci 2014; 8:223. [PMID: 25126054 PMCID: PMC4115623 DOI: 10.3389/fnins.2014.00223] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Accepted: 07/07/2014] [Indexed: 01/26/2023] Open
Abstract
In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70 ± 6 years), 12 MCI (74 ± 6 years), and 16 HC (69 ± 5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p < 0.001) with psychological scores, in particular Mini-Mental State Examination (MMSE) and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.
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Affiliation(s)
- Gloria Castellazzi
- Department of Industrial and Information Engineering, University of PaviaPavia, Italy
- Brain Connectivity Center, C. Mondino National Neurological InstitutePavia, Italy
| | - Fulvia Palesi
- Brain Connectivity Center, C. Mondino National Neurological InstitutePavia, Italy
- Department of Physics, University of PaviaPavia, Italy
| | - Stefano Casali
- Brain Connectivity Center, C. Mondino National Neurological InstitutePavia, Italy
- Department of Brain and Behavioral Sciences, University of PaviaPavia, Italy
| | - Paolo Vitali
- Brain MRI 3T Mondino Research Center, C. Mondino National Neurological InstitutePavia, Italy
| | - Elena Sinforiani
- Neurology Unit, C. Mondino National Neurological InstitutePavia, Italy
| | | | - Egidio D'Angelo
- Brain Connectivity Center, C. Mondino National Neurological InstitutePavia, Italy
- Department of Brain and Behavioral Sciences, University of PaviaPavia, Italy
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