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Gallagher A, Wallois F, Obrig H. Functional near-infrared spectroscopy in pediatric clinical research: Different pathophysiologies and promising clinical applications. NEUROPHOTONICS 2023; 10:023517. [PMID: 36873247 PMCID: PMC9982436 DOI: 10.1117/1.nph.10.2.023517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
Over its 30 years of existence, functional near-infrared spectroscopy (fNIRS) has matured into a highly versatile tool to study brain function in infants and young children. Its advantages, amongst others, include its ease of application and portability, the option to combine it with electrophysiology, and its relatively good tolerance to movement. As shown by the impressive body of fNIRS literature in the field of cognitive developmental neuroscience, the method's strengths become even more relevant for (very) young individuals who suffer from neurological, behavioral, and/or cognitive impairment. Although a number of studies have been conducted with a clinical perspective, fNIRS cannot yet be considered as a truly clinical tool. The first step has been taken in this direction by studies exploring options in populations with well-defined clinical profiles. To foster further progress, here, we review several of these clinical approaches to identify the challenges and perspectives of fNIRS in the field of developmental disorders. We first outline the contributions of fNIRS in selected areas of pediatric clinical research: epilepsy, communicative and language disorders, and attention-deficit/hyperactivity disorder. We provide a scoping review as a framework to allow the highlighting of specific and general challenges of using fNIRS in pediatric research. We also discuss potential solutions and perspectives on the broader use of fNIRS in the clinical setting. This may be of use to future research, targeting clinical applications of fNIRS in children and adolescents.
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Affiliation(s)
- Anne Gallagher
- CHU Sainte-Justine University Hospital, Université de Montréal, LIONLab, Cerebrum, Department of Psychology, Montréal, Quebec, Canada
| | - Fabrice Wallois
- Université de Picardie Jules Verne, Inserm U1105, GRAMFC, Amiens, France
| | - Hellmuth Obrig
- University Hospital and Faculty of Medicine Leipzig/Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, Clinic for Cognitive Neurology, Leipzig, Germany
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Zhang H, Xu L, Yu J, Li J, Wang J. Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network. Front Neurosci 2023; 17:1132231. [PMID: 36968494 PMCID: PMC10038196 DOI: 10.3389/fnins.2023.1132231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 02/23/2023] [Indexed: 03/12/2023] Open
Abstract
The accurate diagnosis of autism spectrum disorder (ASD) is of great practical significance in clinical practice. The spontaneous hemodynamic fluctuations were collected by functional near-infrared spectroscopy (fNIRS) from the bilateral frontal and temporal cortices of typically developing (TD) children and children with ASD. Since traditional machine learning and deep learning methods cannot make full use of the potential spatial dependence between variable pairs, and require a long time series to diagnose ASD. Therefore, we use adaptive spatiotemporal graph convolution network (ASGCN) and short time series to classify ASD and TD. To capture spatial and temporal features of fNIRS multivariable time series without the pre-defined graph, we combined the improved adaptive graph convolution network (GCN) and gated recurrent units (GRU). We conducted a series of experiments on the fNIRS dataset, and found that only using 2.1 s short time series could achieve high precision classification, with an accuracy of 95.4%. This suggests that our approach may have the potential to detect pathological signals in autism patients within 2.1 s. In different brain regions, the left frontal lobe has the best classification effect, and the abnormalities occur more frequently in left hemisphere and frontal lobe region. Moreover, we also found that there were correlations between multiple channels, which had different degrees of influence on the classification of ASD. From this, we can also generalize to a wider range, there may be potential correlations between different brain regions. This may help to better understand the cortical mechanism of ASD.
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Affiliation(s)
- Haoran Zhang
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Lingyu Xu
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China
- *Correspondence: Lingyu Xu
| | - Jie Yu
- School of Computer Engineering and Science, Shanghai University, Shanghai, China
- Jie Yu
| | - Jun Li
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, China
- Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
| | - Jinhong Wang
- Department of Medical Imaging Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Akila V, Johnvictor AC. Functional near infrared spectroscopy for brain functional connectivity analysis: A graph theoretic approach. Heliyon 2023; 9:e15002. [PMID: 37082646 PMCID: PMC10112026 DOI: 10.1016/j.heliyon.2023.e15002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 03/13/2023] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
Background Functional Near-Infrared Spectroscopy is an optical brain monitoring technique which uses NIRS to perform functional neuroimaging. It uses near-infrared light for measuring brain activity and to estimate the cortical hemodynamic activity in the brain due to motor activity. Functional NIRS measures the changes in oxygen levels in oxygenated and deoxygenated hemoglobin by optical absorption. One of the main challenges in the analysis of fNIRS signals is the signal degradation due to the interference from noise and artifacts from multiple sources. Methods In this context, this research aims to analyze the connectivity between different regions of the brain using graph theory and hence the geometrical association of brain networks in terms of functional parameters. In this study, the impact of two noise removal processes (CBSI and TDDR), along with two types of correlation fNIRS such as Pearson's Correlation (PC), and Cross Correlation (CC) and various whole-brain network architectures on the reproducibility of graph measurements for individual participants has been carefully examined for different densities ranging from 5% to 50%.The graph measures' repeatability at the individual level was studied using the test-retest variability (TRT). Results The test-retest variability for global measurements in binary networks was substantially large at low densities, regardless of the noise removal method or the kind of correlation. Very low test -reset values are observed for weighted networks and great reproducibility for measures of the entire graph. When comparing the test-retest values for various methods, the kind of correlation, the absolute value of the correlation, and the weight calculation method on the raw correlation value all had significant major effects. Conclusion Based on a weighted network with the absolute cross correlation functioning as the weight, this study revealed that normalized global graph measurements were reliable. The node definition techniques that were utilized to remove noise were not essential for the normalized graph measures to be reproducible.
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Bonilauri A, Sangiuliano Intra F, Baglio F, Baselli G. Impact of Anatomical Variability on Sensitivity Profile in fNIRS-MRI Integration. SENSORS (BASEL, SWITZERLAND) 2023; 23:2089. [PMID: 36850685 PMCID: PMC9962997 DOI: 10.3390/s23042089] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is an important non-invasive technique used to monitor cortical activity. However, a varying sensitivity of surface channels vs. cortical structures may suggest integrating the fNIRS with the subject-specific anatomy (SSA) obtained from routine MRI. Actual processing tools permit the computation of the SSA forward problem (i.e., cortex to channel sensitivity) and next, a regularized solution of the inverse problem to map the fNIRS signals onto the cortex. The focus of this study is on the analysis of the forward problem to quantify the effect of inter-subject variability. Thirteen young adults (six males, seven females, age 29.3 ± 4.3) underwent both an MRI scan and a motor grasping task with a continuous wave fNIRS system of 102 measurement channels with optodes placed according to a 10/5 system. The fNIRS sensitivity profile was estimated using Monte Carlo simulations on each SSA and on three major atlases (i.e., Colin27, ICBM152 and FSAverage) for comparison. In each SSA, the average sensitivity curves were obtained by aligning the 102 channels and segmenting them by depth quartiles. The first quartile (depth < 11.8 (0.7) mm, median (IQR)) covered 0.391 (0.087)% of the total sensitivity profile, while the second one (depth < 13.6 (0.7) mm) covered 0.292 (0.009)%, hence indicating that about 70% of the signal was from the gyri. The sensitivity bell-shape was broad in the source-detector direction (20.953 (5.379) mm FWHM, first depth quartile) and steeper in the transversal one (6.082 (2.086) mm). The sensitivity of channels vs. different cortical areas based on SSA were analyzed finding high dispersions among subjects and large differences with atlas-based evaluations. Moreover, the inverse cortical mapping for the grasping task showed differences between SSA and atlas based solutions. In conclusion, integration with MRI SSA can significantly improve fNIRS interpretation.
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Affiliation(s)
- Augusto Bonilauri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | | | - Francesca Baglio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
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Li R, Yang D, Fang F, Hong KS, Reiss AL, Zhang Y. Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155865. [PMID: 35957421 PMCID: PMC9371171 DOI: 10.3390/s22155865] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/27/2022] [Accepted: 07/30/2022] [Indexed: 05/29/2023]
Abstract
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research.
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Affiliation(s)
- Rihui Li
- Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
| | - Dalin Yang
- School of Mechanical Engineering, Pusan National University, Pusan 43241, Korea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, 4515 McKinley Avenue, St. Louis, MO 63110, USA
| | - Feng Fang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Pusan 43241, Korea
| | - Allan L. Reiss
- Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
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Tung H, Lin WH, Lan TH, Hsieh PF, Chiang MC, Lin YY, Peng SJ. Network reorganization during verbal fluency task in fronto-temporal epilepsy: A functional near-infrared spectroscopy study. J Psychiatr Res 2021; 138:541-549. [PMID: 33990025 DOI: 10.1016/j.jpsychires.2021.05.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 04/25/2021] [Accepted: 05/01/2021] [Indexed: 10/21/2022]
Abstract
This is the first study to use functional near-infrared spectroscopy (fNIRS) to investigate how the lateralization of the epileptogenic zone affects the reconfiguration of task-related network patterns. Eleven left fronto-temporal epilepsy (L-FTE) and 11 right fronto-temporal epilepsy (R-FTE), as well as 22 age- and gender-matched controls, were enrolled. Signals from 52-channel fNIRS were recorded while the subject was undertaking verbal fluency tasks (VFTs), which included categorical (CFT) and letter (LFT) fluency tasks. Three analytic methods were used to study the network topology: network-based analysis, hub identification, and proportional threshold to select the top 20% strongest connections for both graph theory parameters and clinical correlation. Performance of CFT is accomplished primarily using the ventral pathway, and bilateral ventral pathways are augmented in fronto-temporal epilepsy patients by strengthening the inter-hemispheric connections, especially for R-FTE. LFT mainly employed the dorsal pathway, and further prioritized the left dorsal pathway in strengthening intra-hemispheric connections in fronto-temporal epilepsy, especially L-FTE. The top 20% of the strongest connections only present differences in CFT network compared with the controls. R-FTE increased inter-hemispheric network density, while L-FTE decreased inter-hemispheric average characteristic path length. Accumulative seizure burden only affects L-FTE network. Better LFT performance and longer educational years seem to promote left fronto-temporal networks, and decreased the demand from RR intra-hemispheric connectivity in L-FTE. LFT scores in R-FTE are maintained by preserved RR intra-hemispheric networks. However, CFT scores and educational years seem to have no effect on the CFT network topology in both FTE.
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Affiliation(s)
- Hsin Tung
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taiwan; Center of Faculty Development, Taichung Veterans General Hospital, Taiwan; Division of Epilepsy, Neurological Institute, Taichung Veterans General Hospital, Taiwan
| | - Wei-Hao Lin
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan; Department of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tsuo-Hung Lan
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan; Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Peiyuan F Hsieh
- Division of Epilepsy, Neurological Institute, Taichung Veterans General Hospital, Taiwan
| | - Ming-Chang Chiang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yung-Yang Lin
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taiwan; Department of Critical Care Medicine, Taipei Veterans General Hospital, Taiwan; Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Syu-Jyun Peng
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
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Abstract
SUMMARY Long-term video-EEG monitoring has been the gold standard for diagnosis of epileptic and nonepileptic events. Medication changes, safety, and a lack of recording EEG in one's habitual environment may interfere with diagnostic representation and subsequently affect management. Some spells defy standard EEG because of ultradian and circadian times of occurrence, manifest nocturnal expression of epileptiform activity, and require classification for clarifying diagnostic input to identify optimal treatment. Some patients may be unaware of seizures, have frequent events, or subclinical seizures that require quantification before optimal management. The influence on antiseizure drug management and clinical drug research can be enlightened by long-term outpatient ambulatory EEG monitoring. With recent governmental shifts to focus on mobile health, ambulatory EEG monitoring has grown beyond diagnostic capabilities to target the dynamic effects of medical and nonmedical treatment for patients with epilepsy in their natural environment. Furthermore, newer applications in ambulatory monitoring include additional physiologic parameters (e.g., sleep, detection of myogenic signals, etc.) and extend treatment relevance to patients beyond seizure reduction alone addressing comorbid conditions. It is with this focus in mind that we direct our discussion on the present and future aspects of using ambulatory EEG monitoring in the treatment of patients with epilepsy.
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Hernandez-Martin E, Gonzalez-Mora JL. Diffuse optical tomography in the human brain: A briefly review from the neurophysiology to its applications. BRAIN SCIENCE ADVANCES 2021. [DOI: 10.26599/bsa.2020.9050014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The present work describes the use of noninvasive diffuse optical tomography (DOT) technology to measure hemodynamic changes, providing relevant information which helps to understand the basis of neurophysiology in the human brain. Advantages such as portability, direct measurements of hemoglobin state, temporal resolution, non‐restricted movements as occurs in magnetic resonance imaging (MRI) devices mean that DOT technology can be used in research and clinical fields. In this review we covered the neurophysiology, physical principles underlying optical imaging during tissue‐light interactions, and technology commonly used during the construction of a DOT device including the source‐detector requirements to improve the image quality. DOT provides 3D cerebral activation images due to complex mathematical models which describe the light propagation inside the tissue head. Moreover, we describe briefly the use of Bayesian methods for raw DOT data filtering as an alternative to linear filters widely used in signal processing, avoiding common problems such as the filter selection or a false interpretation of the results which is sometimes due to the interference of background physiological noise with neural activity.
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Affiliation(s)
- Estefania Hernandez-Martin
- Department of Basic Medical Science, Faculty of Health Science, Medicine Section, Universidad de La Laguna, 38071, Spain
| | - José Luis Gonzalez-Mora
- Department of Basic Medical Science, Faculty of Health Science, Medicine Section, Universidad de La Laguna, 38071, Spain
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Yücel MA, Lühmann AV, Scholkmann F, Gervain J, Dan I, Ayaz H, Boas D, Cooper RJ, Culver J, Elwell CE, Eggebrecht A, Franceschini MA, Grova C, Homae F, Lesage F, Obrig H, Tachtsidis I, Tak S, Tong Y, Torricelli A, Wabnitz H, Wolf M. Best practices for fNIRS publications. NEUROPHOTONICS 2021; 8:012101. [PMID: 33442557 PMCID: PMC7793571 DOI: 10.1117/1.nph.8.1.012101] [Citation(s) in RCA: 142] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 12/02/2020] [Indexed: 05/09/2023]
Abstract
The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years. Today, it is addressing a wide range of applications within different populations and utilizes a great variety of experimental paradigms. With the rapid growth and the diversification of research methods, some inconsistencies are appearing in the way in which methods are presented, which can make the interpretation and replication of studies unnecessarily challenging. The Society for Functional Near-Infrared Spectroscopy has thus been motivated to organize a representative (but not exhaustive) group of leaders in the field to build a consensus on the best practices for describing the methods utilized in fNIRS studies. Our paper has been designed to provide guidelines to help enhance the reliability, repeatability, and traceability of reported fNIRS studies and encourage best practices throughout the community. A checklist is provided to guide authors in the preparation of their manuscripts and to assist reviewers when evaluating fNIRS papers.
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Affiliation(s)
- Meryem A. Yücel
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Alexander v. Lühmann
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Felix Scholkmann
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Neonatology Research, Zurich, Switzerland
- University of Bern, Institute for Complementary and Integrative Medicine, Bern, Switzerland
| | - Judit Gervain
- Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
- Università di Padova, Department of Social and Developmental Psychology, Padua, Italy
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Applied Cognitive Neuroscience Laboratory, Tokyo, Japan
| | - 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 Psychology, Philadelphia, Pennsylvania, United States
- Drexel University, Drexel Solutions Institute, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, Department of Family and Community Health, Philadelphia, Pennsylvania, United States
- Children’s Hospital of Philadelphia, Center for Injury Research and Prevention, Philadelphia, Pennsylvania, United States
| | - David Boas
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
| | - Robert J. Cooper
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Joseph Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Clare E. Elwell
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Adam Eggebrecht
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Maria A. Franceschini
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Christophe Grova
- Concordia University, Department of Physics and PERFORM Centre, Multimodal Functional Imaging Lab, Montreal, Québec, Canada
- McGill University, Biomedical Engineering Department, Multimodal Functional Imaging Lab, Montreal, Québec, Canada
| | - Fumitaka Homae
- Tokyo Metropolitan University, Department of Language Sciences, Tokyo, Japan
| | - Frédéric Lesage
- Polytechnique Montréal, Department Electrical Engineering, Montreal, Canada
| | - Hellmuth Obrig
- University Hospital Leipzig, Max-Planck-Institute for Human Cognitive and Brain Sciences and Clinic for Cognitive Neurology, Leipzig, Germany
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Sungho Tak
- Korea Basic Science Institute, Research Center for Bioconvergence Analysis, Ochang, Cheongju, Republic of Korea
| | - Yunjie Tong
- Weldon School of Biomedical Engineering Purdue University, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, Milan, Italy
| | | | - Martin Wolf
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Neonatology Research, Zurich, Switzerland
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HU XINHUA, XIAO GANG, ZHU KEXIN, HU SHUYI, CHEN JIU, YU YUN. APPLICATION OF FUNCTIONAL NEAR-INFRARED SPECTROSCOPY IN NEUROLOGICAL DISEASES: EPILEPSY, STROKE AND PARKINSON. J MECH MED BIOL 2020. [DOI: 10.1142/s0219519420400230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The functional near-infrared spectroscopy (fNIRS) technology is an optical imaging technology that applies near-infrared light to measure the oxygenated and deoxygenated hemoglobin concentration alteration in cortical brain structures. It has the ability to directly measure changes in the blood oxygen level of the high temporal resolution associated with neural activation. Thus, it has been utilized in different neurological diseases, such as epilepsy, stroke, and Parkinson. The work of this paper will focus on the application of the fNIRS in the three neurological diseases and the principle of fNIRS. Moreover, the difficulties and challenges that the technology is currently experiencing have been discussed.
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Affiliation(s)
- XINHUA HU
- Department of Neurosurgery, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - GANG XIAO
- The Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences and Department of Endocrinology, Fudan University, Shanghai, 200032, P. R. China
| | - KEXIN ZHU
- The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - SHUYI HU
- The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - JIU CHEN
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - YUN YU
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
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Hemispheric Cerebral Oximetry Monitoring During Pediatric Seizure Activity in a Pediatric Emergency Department. Pediatr Emerg Care 2020; 36:e513-e526. [PMID: 29140931 PMCID: PMC7469875 DOI: 10.1097/pec.0000000000001354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Sustained neuronal activity during seizures causes cellular perturbations, alterations in cerebral physiology, and potentially neurological injury, a neurological emergency. With variable clinical manifestations of seizures, frequent failure of seizure recognition by providers in pediatric and developmentally challenged patients can increase seizure complications. Neuroresuscitation should include rapid cerebral physiology assessment for increased seizure recognition and optimal neurological outcomes. In neurological emergencies, cerebral oximetry has demonstrated its utility in altered cerebral physiology and a standard combat neurological assessment tool. During adult seizures, cerebral oximetry (regional cerebral oxygen saturation [rcSO2]) has been shown as a useful neurological assessment tool, but research is lacking in pediatric emergency department (PED) seizure patients. OBJECTIVE The aim of this study was to identify trends in rcSO2 readings for patients presenting to the PED with seizure activity and in the postseizure state in order to evaluate usefulness of rcSO2 as a neurological assessment tool in pediatric seizure patients. METHODS This was a PED observational case series comparing hemispheric rcSO2 readings in first-time clinically evident generalized and focal seizure patients to first-time postseizure patients with no PED seizures. RESULTS Generalized or focal seizure (n = 185) hemispheric rcSO2 revealed significant differences compared with nonseizure and controls' rcSO2 readings (n = 115) (P < 0.0001). Generalized and focal seizure rcSO2's were either less than 60% or greater than 80% compared with nonseizure rcSO2 (P < 0.0001). Ipsilateral focal seizure rcSO2 correlated to seizure side (P < 0.0001) and was less than the contralateral rcSO2 (P < 0.0001), with interhemispheric rcSO2 discordance greater than 16 (P < 0.0001). Seizure to preseizure rcSO2 discordance was as follows: generalized 15.2, focal: left 19.8, right 20.3 (P < 0.0001). CONCLUSIONS Hemispheric during-seizure rcSO2 readings significantly correlated with generalized and focal seizures and reflected altered cerebral physiology. Ipsilateral focal seizure rcSO2 readings correlated to the focal side with wide interhemispheric rcSO2 discordance. All postseizure rcSO2 readings returned to preseizure readings, showing altered cerebral physiology resolution. Overall, in generalized or focal seizure, rcSO2 readings were less than 60% or greater than 80%, and in focal seizure, interhemispheric rcSO2 discordance was greater than 10. During seizures, hemispheric rcSO2 readings demonstrated its potential pediatric seizure utility. Utilizing rcSO2 readings related to seizure activity could expedite pediatric and developmentally challenged patients' seizure recognition, cerebral assessment, and interventions especially in pharmacoresistant seizures.
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Xu L, Guo Y, Li J, Yu J, Xu H. Classification of autism spectrum disorder based on fluctuation entropy of spontaneous hemodynamic fluctuations. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.101958] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Abstract
Numerous technologies have been introduced for the diagnosis, treatment, and management of patients with neurologic disorders, offering the promise of early diagnosis, tailored and individualized interventions, improvement in quality of life, and restoration of neurologic function. Many of these technologies have become available commercially without having been evaluated by rigorous clinical trials and regulatory reviews, or at the least by peer review of results submitted for publication. A subset is intended to assess, assist, and monitor cognitive functions, motor skills, and autonomic functions and as such may be applicable to persons with developmental disabilities. Barriers that have previously limited the use of technologies by persons with neurodevelopmental disabilities are disappearing as new technologies that have the potential to substantially augment diagnosis and interventions to enhance the daily lives of persons with these disorders are emerging. While recent and future advances in technology have the potential to transform their lives, cautious and thoughtful evaluation is needed to ensure the technologies provide maximal value. As such, further work is needed to demonstrate feasibility, efficacy, and cost-effectiveness, and technologies should be designed to be optimized for individual use.
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Affiliation(s)
- Steven C Schachter
- Department of Neurology, Harvard Medical School, Boston, MA, United States.
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Almajidy RK, Mankodiya K, Abtahi M, Hofmann UG. A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments. IEEE Rev Biomed Eng 2019; 13:292-308. [PMID: 31634142 DOI: 10.1109/rbme.2019.2944351] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.
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15
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A Mini-Review on Functional Near-Infrared Spectroscopy (fNIRS): Where Do We Stand, and Where Should We Go? PHOTONICS 2019. [DOI: 10.3390/photonics6030087] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
This mini-review is aimed at briefly summarizing the present status of functional near-infrared spectroscopy (fNIRS) and predicting where the technique should go in the next decade. This mini-review quotes 33 articles on the different fNIRS basics and technical developments and 44 reviews on the fNIRS applications published in the last eight years. The huge number of review articles about a wide spectrum of topics in the field of cognitive and social sciences, functional neuroimaging research, and medicine testifies to the maturity achieved by this non-invasive optical vascular-based functional neuroimaging technique. Today, fNIRS has started to be utilized on healthy subjects while moving freely in different naturalistic settings. Further instrumental developments are expected to be done in the near future to fully satisfy this latter important aspect. In addition, fNIRS procedures, including correction methods for the strong extracranial interferences, need to be standardized before using fNIRS as a clinical tool in individual patients. New research avenues such as interactive neurosciences, cortical activation modulated by different type of sport performance, and cortical activation during neurofeedback training are highlighted.
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16
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Teleanu DM, Chircov C, Grumezescu AM, Volceanov A, Teleanu RI. Contrast Agents Delivery: An Up-to-Date Review of Nanodiagnostics in Neuroimaging. NANOMATERIALS (BASEL, SWITZERLAND) 2019; 9:E542. [PMID: 30987211 PMCID: PMC6523665 DOI: 10.3390/nano9040542] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 03/28/2019] [Accepted: 03/29/2019] [Indexed: 12/14/2022]
Abstract
Neuroimaging is a highly important field of neuroscience, with direct implications for the early diagnosis and progression monitoring of brain-associated diseases. Neuroimaging techniques are categorized into structural, functional and molecular neuroimaging, each possessing advantages and disadvantages in terms of resolution, invasiveness, toxicity of contrast agents and costs. Nanotechnology-based approaches for neuroimaging mostly involve the development of nanocarriers for incorporating contrast agents or the use of nanomaterials as imaging agents. Inorganic and organic nanoparticles, liposomes, micelles, nanobodies and quantum dots are some of the most studied candidates for the delivery of contrast agents for neuroimaging. This paper focuses on describing the conventional modalities used for imaging and the applications of nanotechnology for developing novel strategies for neuroimaging. The aim is to highlight the roles of nanocarriers for enhancing and/or overcome the limitations associated with the most commonly utilized neuroimaging modalities. For future directions, several techniques that could benefit from the increased contrast induced by using imaging probes are presented.
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Affiliation(s)
- Daniel Mihai Teleanu
- Emergency University Hospital, "Carol Davila" University of Medicine and Pharmacy, 050474 Bucharest, Romania.
| | - Cristina Chircov
- Faculty of Engineering in Foreign Languages, Politehnica University of Bucharest, 060042 Bucharest, Romania.
- Faculty of Applied Chemistry and Materials Science, Politehnica University of Bucharest, 011061 Bucharest, Romania.
| | - Alexandru Mihai Grumezescu
- Faculty of Applied Chemistry and Materials Science, Politehnica University of Bucharest, 011061 Bucharest, Romania.
- ICUB - Research Institute of University of Bucharest, University of Bucharest, 36-46 M. Kogalniceanu Blvd., Bucharest 050107, Romania.
| | - Adrian Volceanov
- Faculty of Applied Chemistry and Materials Science, Politehnica University of Bucharest, 011061 Bucharest, Romania.
| | - Raluca Ioana Teleanu
- "Victor Gomoiu" Clinical Children's Hospital, "Carol Davila" University of Medicine and Pharmacy, 050474 Bucharest, Romania.
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17
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Quantitatively detecting postictal hypoperfusion in patients with focal epilepsy using CT perfusion: Determining cross-modality comparisons and electrode artifacts. J Neurosci Methods 2019; 314:13-20. [PMID: 30658125 DOI: 10.1016/j.jneumeth.2019.01.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 12/20/2018] [Accepted: 01/12/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND We previously showed that CT perfusion (CTP) and arterial spin labelled (ASL) MRI can localize the seizure onset zone in humans via postictal perfusion patterns. As a step towards improving the feasibility/ease of collecting postictal CBF data, we determined whether EEG electrodes need to be removed for CTP data collection and whether a cross-modality comparison between baseline ASL and postictal CTP data is possible. NEW METHOD Five patients with epilepsy underwent postictal CTP scanning. Three patients had an interictal ASL scan; one patient had both an ASL and CTP interictal scan. Postictal CTP maps were quantitatively compared to 1) ASL maps averaged from 100 healthy controls, 2) each patient's baseline ASL map and 3) each patient's baseline CTP map. To assess for electrode artifacts, a phantom and one patient underwent CTP scanning with EEG electrodes in place. The acquired scans were assessed for artifacts and for postictal hypoperfusion. RESULTS Focal postictal hypoperfusion was observable only in intra-modality comparisons (CTP to CTP) and not in cross-modality comparisons (CTP to ASL). EEG electrodes produced streaking artifact that decreased image quality and precluded quantitative analysis. COMPARISON WITH EXISTING METHODS(S) An intra-modality comparison of baseline CTP to postictal CTP was the only comparison method that showed localized hypoperfusion. CONCLUSIONS Quantitative comparison between postictal CTP and baseline ASL scans is not feasible. Postictal hypoperfusion can be detected by CTP only when two CTP scans are collected and when metallic EEG electrodes are removed.
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18
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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: 63] [Impact Index Per Article: 9.0] [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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19
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Pichette J, Laurence A, Angulo L, Lesage F, Bouthillier A, Nguyen DK, Leblond F. Intraoperative video-rate hemodynamic response assessment in human cortex using snapshot hyperspectral optical imaging. NEUROPHOTONICS 2016; 3:045003. [PMID: 27752519 PMCID: PMC5061108 DOI: 10.1117/1.nph.3.4.045003] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 09/19/2016] [Indexed: 05/21/2023]
Abstract
Using light, we are able to visualize the hemodynamic behavior of the brain to better understand neurovascular coupling and cerebral metabolism. In vivo optical imaging of tissue using endogenous chromophores necessitates spectroscopic detection to ensure molecular specificity as well as sufficiently high imaging speed and signal-to-noise ratio, to allow dynamic physiological changes to be captured, isolated, and used as surrogate of pathophysiological processes. An optical imaging system is introduced using a 16-bands on-chip hyperspectral camera. Using this system, we show that up to three dyes can be imaged and quantified in a tissue phantom at video-rate through the optics of a surgical microscope. In vivo human patient data are presented demonstrating brain hemodynamic response can be measured intraoperatively with molecular specificity at high speed.
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Affiliation(s)
- Julien Pichette
- Polytechnique Montreal, Department of Engineering Physics, C.P. 6079, Succ. Centre-Ville, Montréal H3C3A7, Canada
| | - Audrey Laurence
- Polytechnique Montreal, Department of Engineering Physics, C.P. 6079, Succ. Centre-Ville, Montréal H3C3A7, Canada
| | - Leticia Angulo
- Polytechnique Montreal, Department of Engineering Physics, C.P. 6079, Succ. Centre-Ville, Montréal H3C3A7, Canada
| | - Frederic Lesage
- Polytechnique Montreal, Department of Electrical Engineering, C.P. 6079, Succ. Centre-Ville, Montréal H3C3A7, Canada
| | - Alain Bouthillier
- Centre Hospitalier de l’Université de Montréal, Notre-Dame Hospital, Division of Neurosurgery, 1560 Sherbrooke Street East, Montréal H2L4M1, Canada
| | - Dang Khoa Nguyen
- Centre Hospitalier de l’Université de Montréal, Notre-Dame Hospital, Division of Neurology, 1560 Sherbrooke Street East, Montréal H2L4M1, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, 900 Saint-Denis, Montréal H2X0A9, Canada
| | - Frederic Leblond
- Polytechnique Montreal, Department of Engineering Physics, C.P. 6079, Succ. Centre-Ville, Montréal H3C3A7, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, 900 Saint-Denis, Montréal H2X0A9, Canada
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