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Yu Y, Feng T, Qiu H, Gu Y, Chen Q, Zuo C, Ma H. Simultaneous photoacoustic and ultrasound imaging: A review. ULTRASONICS 2024; 139:107277. [PMID: 38460216 DOI: 10.1016/j.ultras.2024.107277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/09/2024] [Accepted: 02/26/2024] [Indexed: 03/11/2024]
Abstract
Photoacoustic imaging (PAI) is an emerging biomedical imaging technique that combines the advantages of optical and ultrasound imaging, enabling the generation of images with both optical resolution and acoustic penetration depth. By leveraging similar signal acquisition and processing methods, the integration of photoacoustic and ultrasound imaging has introduced a novel hybrid imaging modality suitable for clinical applications. Photoacoustic-ultrasound imaging allows for non-invasive, high-resolution, and deep-penetrating imaging, providing a wealth of image information. In recent years, with the deepening research and the expanding biomedical application scenarios of photoacoustic-ultrasound bimodal systems, the immense potential of photoacoustic-ultrasound bimodal imaging in basic research and clinical applications has been demonstrated, with some research achievements already commercialized. In this review, we introduce the principles, technical advantages, and biomedical applications of photoacoustic-ultrasound bimodal imaging techniques, specifically focusing on tomographic, microscopic, and endoscopic imaging modalities. Furthermore, we discuss the future directions of photoacoustic-ultrasound bimodal imaging technology.
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Affiliation(s)
- Yinshi Yu
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Ting Feng
- Academy for Engineering & Technology, Fudan University, Shanghai 200433,China.
| | - Haixia Qiu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Ying Gu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Qian Chen
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Chao Zuo
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
| | - Haigang Ma
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
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Srinivasan S, Acharya D, Butters E, Collins-Jones L, Mancini F, Bale G. Subject-specific information enhances spatial accuracy of high-density diffuse optical tomography. FRONTIERS IN NEUROERGONOMICS 2024; 5:1283290. [PMID: 38444841 PMCID: PMC10910052 DOI: 10.3389/fnrgo.2024.1283290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a widely used imaging method for mapping brain activation based on cerebral hemodynamics. The accurate quantification of cortical activation using fNIRS data is highly dependent on the ability to correctly localize the positions of light sources and photodetectors on the scalp surface. Variations in head size and shape across participants greatly impact the precise locations of these optodes and consequently, the regions of the cortical surface being reached. Such variations can therefore influence the conclusions drawn in NIRS studies that attempt to explore specific cortical regions. In order to preserve the spatial identity of each NIRS channel, subject-specific differences in NIRS array registration must be considered. Using high-density diffuse optical tomography (HD-DOT), we have demonstrated the inter-subject variability of the same HD-DOT array applied to ten participants recorded in the resting state. We have also compared three-dimensional image reconstruction results obtained using subject-specific positioning information to those obtained using generic optode locations. To mitigate the error introduced by using generic information for all participants, photogrammetry was used to identify specific optode locations per-participant. The present work demonstrates the large variation between subjects in terms of which cortical parcels are sampled by equivalent channels in the HD-DOT array. In particular, motor cortex recordings suffered from the largest optode localization errors, with a median localization error of 27.4 mm between generic and subject-specific optodes, leading to large differences in parcel sensitivity. These results illustrate the importance of collecting subject-specific optode locations for all wearable NIRS experiments, in order to perform accurate group-level analysis using cortical parcellation.
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Affiliation(s)
- Sruthi Srinivasan
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Deepshikha Acharya
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Emilia Butters
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Liam Collins-Jones
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Flavia Mancini
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Gemma Bale
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
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Hirvi P, Kuutela T, Fang Q, Hannukainen A, Hyvönen N, Nissilä I. Effects of atlas-based anatomy on modelled light transport in the neonatal head. Phys Med Biol 2023; 68:135019. [PMID: 37167982 PMCID: PMC10460200 DOI: 10.1088/1361-6560/acd48c] [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: 11/08/2022] [Revised: 04/21/2023] [Accepted: 05/11/2023] [Indexed: 05/13/2023]
Abstract
Objective.Diffuse optical tomography (DOT) provides a relatively convenient method for imaging haemodynamic changes related to neuronal activity on the cerebral cortex. Due to practical challenges in obtaining anatomical images of neonates, an anatomical framework is often created from an age-appropriate atlas model, which is individualized to the subject based on measurements of the head geometry. This work studies the approximation error arising from using an atlas instead of the neonate's own anatomical model.Approach.We consider numerical simulations of frequency-domain (FD) DOT using two approaches, Monte Carlo simulations and diffusion approximation via finite element method, and observe the variation in (1) the logarithm of amplitude and phase shift measurements, and (2) the corresponding inner head sensitivities (Jacobians), due to varying segmented anatomy. Varying segmentations are sampled by registering 165 atlas models from a neonatal database to the head geometry of one individual selected as the reference model. Prior to the registration, we refine the segmentation of the cerebrospinal fluid (CSF) by separating the CSF into two physiologically plausible layers.Main results.In absolute measurements, a considerable change in the grey matter or extracerebral tissue absorption coefficient was found detectable over the anatomical variation. In difference measurements, a small local 10%-increase in brain absorption was clearly detectable in the simulated measurements over the approximation error in the Jacobians, despite the wide range of brain maturation among the registered models.Significance.Individual-level atlas models could potentially be selected within several weeks in gestational age in DOT difference imaging, if an exactly age-appropriate atlas is not available. The approximation error method could potentially be implemented to improve the accuracy of atlas-based imaging. The presented CSF segmentation algorithm could be useful also in other model-based imaging modalities. The computation of FD Jacobians is now available in the widely-used Monte Carlo eXtreme software.
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Affiliation(s)
- Pauliina Hirvi
- Aalto University, Department of
Mathematics and Systems Analysis, PO Box 11100, FI-00076 AALTO,
Finland
| | - Topi Kuutela
- Aalto University, Department of
Mathematics and Systems Analysis, PO Box 11100, FI-00076 AALTO,
Finland
| | - Qianqian Fang
- Northeastern University, Department of
Bioengineering, 360 Huntington Ave, Boston, MA 02115, United States of
America
| | - Antti Hannukainen
- Aalto University, Department of
Mathematics and Systems Analysis, PO Box 11100, FI-00076 AALTO,
Finland
| | - Nuutti Hyvönen
- Aalto University, Department of
Mathematics and Systems Analysis, PO Box 11100, FI-00076 AALTO,
Finland
| | - Ilkka Nissilä
- Aalto University, Department of
Neuroscience and Biomedical Engineering, PO Box 12200, FI-00076 AALTO,
Finland
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Anaya D, Batra G, Bracewell P, Catoen R, Chakraborty D, Chevillet M, Damodara P, Dominguez A, Emms L, Jiang Z, Kim E, Klumb K, Lau F, Le R, Li J, Mateo B, Matloff L, Mehta A, Mugler EM, Murthy A, Nakagome S, Orendorff R, Saung EF, Schwarz R, Sethi R, Sevile R, Srivastava A, Sundberg J, Yang Y, Yin A. Scalable, modular continuous wave functional near-infrared spectroscopy system (Spotlight). JOURNAL OF BIOMEDICAL OPTICS 2023; 28:065003. [PMID: 37325190 PMCID: PMC10261976 DOI: 10.1117/1.jbo.28.6.065003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/26/2023] [Accepted: 05/01/2023] [Indexed: 06/17/2023]
Abstract
Significance We present a fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy system, Spotlight, consisting of multiple palm-sized modules-each containing high-density light-emitting diode and silicon photomultiplier detector arrays embedded in a flexible membrane that facilitates optode coupling to scalp curvature. Aim Spotlight's goal is to be a more portable, accessible, and powerful functional near-infrared spectroscopy (fNIRS) device for neuroscience and brain-computer interface (BCI) applications. We hope that the Spotlight designs we share here can spur more advances in fNIRS technology and better enable future non-invasive neuroscience and BCI research. Approach We report sensor characteristics in system validation on phantoms and motor cortical hemodynamic responses in a human finger-tapping experiment, where subjects wore custom 3D-printed caps with two sensor modules. Results The task conditions can be decoded offline with a median accuracy of 69.6%, reaching 94.7% for the best subject, and at a comparable accuracy in real time for a subset of subjects. We quantified how well the custom caps fitted to each subject and observed that better fit leads to more observed task-dependent hemodynamic response and better decoding accuracy. Conclusions The advances presented here should serve to make fNIRS more accessible for BCI applications.
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Affiliation(s)
- Daniel Anaya
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Gautam Batra
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Ryan Catoen
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Mark Chevillet
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | | | - Laurence Emms
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Zifan Jiang
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ealgoo Kim
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Keith Klumb
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Frances Lau
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Rosemary Le
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Jamie Li
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Brett Mateo
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Laura Matloff
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Asha Mehta
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Akansh Murthy
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Sho Nakagome
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ryan Orendorff
- Meta Platforms, Inc., Menlo Park, California, United States
| | - E-Fann Saung
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Roland Schwarz
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ruben Sethi
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Rudy Sevile
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - John Sundberg
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ying Yang
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Allen Yin
- Meta Platforms, Inc., Menlo Park, California, United States
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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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Lotter LD, Kohl SH, Gerloff C, Bell L, Niephaus A, Kruppa JA, Dukart J, Schulte-Rüther M, Reindl V, Konrad K. Revealing the neurobiology underlying interpersonal neural synchronization with multimodal data fusion. Neurosci Biobehav Rev 2023; 146:105042. [PMID: 36641012 DOI: 10.1016/j.neubiorev.2023.105042] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/13/2023]
Abstract
Humans synchronize with one another to foster successful interactions. Here, we use a multimodal data fusion approach with the aim of elucidating the neurobiological mechanisms by which interpersonal neural synchronization (INS) occurs. Our meta-analysis of 22 functional magnetic resonance imaging and 69 near-infrared spectroscopy hyperscanning experiments (740 and 3721 subjects) revealed robust brain regional correlates of INS in the right temporoparietal junction and left ventral prefrontal cortex. Integrating this meta-analytic information with public databases, biobehavioral and brain-functional association analyses suggested that INS involves sensory-integrative hubs with functional connections to mentalizing and attention networks. On the molecular and genetic levels, we found INS to be associated with GABAergic neurotransmission and layer IV/V neuronal circuits, protracted developmental gene expression patterns, and disorders of neurodevelopment. Although limited by the indirect nature of phenotypic-molecular association analyses, our findings generate new testable hypotheses on the neurobiological basis of INS.
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Affiliation(s)
- Leon D Lotter
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine - Brain & Behaviour (INM-7), Jülich Research Centre, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Max Planck School of Cognition, Stephanstrasse 1A, 04103 Leipzig, Germany.
| | - Simon H Kohl
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
| | - Christian Gerloff
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Chair II of Mathematics, Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, Aachen, Germany
| | - Laura Bell
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; Audiovisual Media Center, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Alexandra Niephaus
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany
| | - Jana A Kruppa
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine - Brain & Behaviour (INM-7), Jülich Research Centre, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Martin Schulte-Rüther
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Vanessa Reindl
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Psychology, School of Social Sciences, Nanyang Technological University, S639818, Singapore
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
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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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Bonilauri A, Sangiuliano Intra F, Rossetto F, Borgnis F, Baselli G, Baglio F. Whole-Head Functional Near-Infrared Spectroscopy as an Ecological Monitoring Tool for Assessing Cortical Activity in Parkinson's Disease Patients at Different Stages. Int J Mol Sci 2022; 23:ijms232314897. [PMID: 36499223 PMCID: PMC9736501 DOI: 10.3390/ijms232314897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/18/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is increasingly employed as an ecological neuroimaging technique in assessing age-related chronic neurological disorders, such as Parkinson's disease (PD), mainly providing a cross-sectional characterization of clinical phenotypes in ecological settings. Current fNIRS studies in PD have investigated the effects of motor and non-motor impairment on cortical activity during gait and postural stability tasks, but no study has employed fNIRS as an ecological neuroimaging tool to assess PD at different stages. Therefore, in this work, we sought to investigate the cortical activity of PD patients during a motor grasping task and its relationship with both the staging of the pathology and its clinical variables. This study considered 39 PD patients (age 69.0 ± 7.64, 38 right-handed), subdivided into two groups at different stages by the Hoehn and Yahr (HY) scale: early PD (ePD; N = 13, HY = [1; 1.5]) and moderate PD (mPD; N = 26, HY = [2; 2.5; 3]). We employed a whole-head fNIRS system with 102 measurement channels to monitor brain activity. Group-level activation maps and region of interest (ROI) analysis were computed for ePD, mPD, and ePD vs. mPD contrasts. A ROI-based correlation analysis was also performed with respect to contrasted subject-level fNIRS data, focusing on age, a Cognitive Reserve Index questionnaire (CRIQ), disease duration, the Unified Parkinson's Disease Rating Scale (UPDRS), and performances in the Stroop Color and Word (SCW) test. We observed group differences in age, disease duration, and the UPDRS, while no significant differences were found for CRIQ or SCW scores. Group-level activation maps revealed that the ePD group presented higher activation in motor and occipital areas than the mPD group, while the inverse trend was found in frontal areas. Significant correlations with CRIQ, disease duration, the UPDRS, and the SCW were mostly found in non-motor areas. The results are in line with current fNIRS and functional and anatomical MRI scientific literature suggesting that non-motor areas-primarily the prefrontal cortex area-provide a compensation mechanism for PD motor impairment. fNIRS may serve as a viable support for the longitudinal assessment of therapeutic and rehabilitation procedures, and define new prodromal, low-cost, and ecological biomarkers of disease progression.
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Affiliation(s)
- Augusto Bonilauri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Francesca Sangiuliano Intra
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
- Faculty of Education, Free University of Bolzano-Bozen, 39042 Brixen, Italy
- Correspondence:
| | - Federica Rossetto
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Francesca Borgnis
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Francesca Baglio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
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Efficient computation of the steady-state and time-domain solutions of the photon diffusion equation in layered turbid media. Sci Rep 2022; 12:18979. [PMID: 36347893 PMCID: PMC9643457 DOI: 10.1038/s41598-022-22649-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 10/18/2022] [Indexed: 11/09/2022] Open
Abstract
Accurate and efficient forward models of photon migration in heterogeneous geometries are important for many applications of light in medicine because many biological tissues exhibit a layered structure of independent optical properties and thickness. However, closed form analytical solutions are not readily available for layered tissue-models, and often are modeled using computationally expensive numerical techniques or theoretical approximations that limit accuracy and real-time analysis. Here, we develop an open-source accurate, efficient, and stable numerical routine to solve the diffusion equation in the steady-state and time-domain for a layered cylinder tissue model with an arbitrary number of layers and specified thickness and optical coefficients. We show that the steady-state ([Formula: see text] ms) and time-domain ([Formula: see text] ms) fluence (for an 8-layer medium) can be calculated with absolute numerical errors approaching machine precision. The numerical implementation increased computation speed by 3 to 4 orders of magnitude compared to previously reported theoretical solutions in layered media. We verify our solutions asymptotically to homogeneous tissue geometries using closed form analytical solutions to assess convergence and numerical accuracy. Approximate solutions to compute the reflected intensity are presented which can decrease the computation time by an additional 2-3 orders of magnitude. We also compare our solutions for 2, 3, and 5 layered media to gold-standard Monte Carlo simulations in layered tissue models of high interest in biomedical optics (e.g. skin/fat/muscle and brain). The presented routine could enable more robust real-time data analysis tools in heterogeneous tissues that are important in many clinical applications such as functional brain imaging and diffuse optical spectroscopy.
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Fu X, Richards JE. Age-related changes in diffuse optical tomography sensitivity profiles from childhood to adulthood. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:083004. [PMID: 35810323 PMCID: PMC9270691 DOI: 10.1117/1.jbo.27.8.083004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
SIGNIFICANCE Diffuse optical tomography (DOT) uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the brain location that generates the hemodynamic signal require accurate descriptions of the DOT sensitivity to the underlying cortex. DOT sensitivity profiles are different in infants compared with adults. However, the descriptions of DOT sensitivity profiles from early childhood to adulthood are lacking despite the continuous head and brain development. AIM We aim to investigate age-related differences in DOT sensitivity profiles in individuals aged from 2 to 34 years with narrow age ranges of 0.5 or 1 year. APPROACH We implemented existing photon migration simulation methods and computed source-detector channel DOT sensitivity using age-appropriate, realistic head models. RESULTS DOT sensitivity profiles change systematically as a function of source-detector separation distance for all age groups. Children displayed distinctive DOT sensitivity profiles compared to older individuals, and the differences were enhanced at larger separation distances. CONCLUSIONS The findings have important implications for the design of source-detector placement and image reconstruction. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone DOT data. Using age-inappropriate head models will have more negative impacts on estimation accuracy in younger children.
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Affiliation(s)
- Xiaoxue Fu
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
| | - John E. Richards
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
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11
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Smartphone-based photogrammetry provides improved localization and registration of scalp-mounted neuroimaging sensors. Sci Rep 2022; 12:10862. [PMID: 35760834 PMCID: PMC9237074 DOI: 10.1038/s41598-022-14458-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 06/07/2022] [Indexed: 11/11/2022] Open
Abstract
Functional near infrared spectroscopy and electroencephalography are non-invasive techniques that rely on sensors placed over the scalp. The spatial localization of the measured brain activity requires the precise individuation of sensor positions and, when individual anatomical information is not available, the accurate registration of these sensor positions to a head atlas. Both these issues could be successfully addressed using a photogrammetry-based method. In this study we demonstrate that sensor positions can be accurately detected from a video recorded with a smartphone, with a median localization error of 0.7 mm, comparable if not lower, to that of conventional approaches. Furthermore, we demonstrate that the additional information of the shape of the participant’s head can be further exploited to improve the registration of the sensor’s positions to a head atlas, reducing the median sensor localization error of 31% compared to the standard registration approach.
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12
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Paul R, Murali K, Chetia S, Varma HM. A simple algorithm for diffuse optical tomography without Jacobian inversion. Biomed Phys Eng Express 2022; 8. [PMID: 35447616 DOI: 10.1088/2057-1976/ac6909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 04/21/2022] [Indexed: 11/11/2022]
Abstract
A computationally simpler algorithm to reconstruct the optical property distribution of turbid media using diffuse optical tomographic principles is presented. The proposed algorithm eliminates the requirement of large Jacobian matrix inversion which otherwise is essential for tomographic imaging. The most significant Jacobians are identified based on proper thresholding of the measurement and the intersection of these Jacobians gives the approximate spatial location of the inhomogeneity. The algorithm is tested and optimized using simulations and further validated using tissue-mimicking phantom-based experiments andin-vivosmall-animal experiments.
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Affiliation(s)
- Ria Paul
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - K Murali
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - Sumana Chetia
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
| | - Hari M Varma
- Indian Institute of Technology Bombay (IITB), Mumbai-400076, India
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13
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Jafari CZ, Mihelic SA, Engelmann S, Dunn AK. High-resolution three-dimensional blood flow tomography in the subdiffuse regime using laser speckle contrast imaging. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210364SSR. [PMID: 35362273 PMCID: PMC8968074 DOI: 10.1117/1.jbo.27.8.083011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 03/04/2022] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE Visualizing high-resolution hemodynamics in cerebral tissue over a large field of view (FOV), provides important information in studying disease states affecting the brain. Current state-of-the-art optical blood flow imaging techniques either lack spatial resolution or are too slow to provide high temporal resolution reconstruction of flow map over a large FOV. AIM We present a high spatial resolution computational optical imaging technique based on principles of laser speckle contrast imaging (LSCI) for reconstructing the blood flow maps in complex tissue over a large FOV provided that the three-dimensional (3D) vascular structure is known or assumed. APPROACH Our proposed method uses a perturbation Monte Carlo simulation of the high-resolution 3D geometry for both accurately deriving the speckle contrast forward model and calculating the Jacobian matrix used in our reconstruction algorithm to achieve high resolution. Given the convex nature of our highly nonlinear problem, we implemented a mini-batch gradient descent with an adaptive learning rate optimization method to iteratively reconstruct the blood flow map. Specifically, we implemented advanced optimization techniques combined with efficient parallelization and vectorization of the forward and derivative calculations to make reconstruction of the blood flow map feasible with reconstruction times on the order of tens of minutes. RESULTS We tested our reconstruction algorithm through simulation of both a flow phantom model as well as an anatomically correct murine cerebral tissue and vasculature captured via two-photon microscopy. Additionally, we performed a noise study, examining the robustness of our inverse model in presence of 0.1% and 1% additive noise. In all cases, the blood flow reconstruction error was <2 % for most of the vasculature, except for the peripheral vasculature which suffered from insufficient photon sampling. Descending vasculature and deeper structures showed slightly higher sensitivity to noise compared with vasculature with a horizontal orientation at the more superficial layers. Our results show high-resolution reconstruction of the blood flow map in tissue down to 500 μm and beyond. CONCLUSIONS We have demonstrated a high-resolution computational imaging technique for visualizing blood flow map in complex tissue over a large FOV. Once a high-resolution structural image is captured, our reconstruction algorithm only requires a few LSCI images captured through a camera to reconstruct the blood flow map computationally at a high resolution. We note that the combination of high temporal and spatial resolution of our reconstruction algorithm makes the solution well-suited for applications involving fast monitoring of flow dynamics over a large FOV, such as in functional neural imaging.
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Affiliation(s)
- Chakameh Z. Jafari
- The University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, Texas, United States
| | - Samuel A. Mihelic
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States
| | - Shaun Engelmann
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States
| | - Andrew K. Dunn
- The University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, Texas, United States
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States
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Fu X, Richards JE. Investigating developmental changes in scalp-to-cortex correspondence using diffuse optical tomography sensitivity in infancy. NEUROPHOTONICS 2021; 8:035003. [PMID: 34322572 PMCID: PMC8305752 DOI: 10.1117/1.nph.8.3.035003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 07/09/2021] [Indexed: 05/25/2023]
Abstract
Significance: Diffuse optical tomography (DOT) uses near-infrared light spectroscopy (NIRS) to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of NIRS data require accurate descriptions of the cranio-cerebral relations and DOT sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. Aim: We aim to investigate age-related differences in scalp-to-cortex distance and mapping between scalp locations and cortical regions of interest (ROIs) among infants (2 weeks to 24 months with narrow age bins), children (4 and 12 years), and adults (20 to 24 years). Approach: We used spatial scalp projection and photon propagation simulation methods with age-matched realistic head models based on MRIs. Results: There were age-group differences in the scalp-to-cortex distances in infancy. The developmental increase was magnified in children and adults. There were systematic age-related differences in the probabilistic mappings between scalp locations and cortical ROIs. Conclusions: Our findings have important implications in the design of sensor placement and making anatomical interpretations in NIRS and fNIRS research. Age-appropriate, realistic head models should be used to provide anatomical guidance for standalone DOT data in infants.
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Affiliation(s)
- Xiaoxue Fu
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
| | - John E. Richards
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
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15
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Fu X, Richards JE. Age-related changes in diffuse optical tomography sensitivity profiles in infancy. PLoS One 2021; 16:e0252036. [PMID: 34101747 PMCID: PMC8186805 DOI: 10.1371/journal.pone.0252036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 05/08/2021] [Indexed: 02/06/2023] Open
Abstract
Diffuse optical tomography uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the location that generates the hemodynamic signal requires accurate descriptions of diffuse optical tomography sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. The present study used photon propagation simulation methods to examine diffuse optical tomography sensitivity profiles in realistic head models among infants ranging from 2 weeks to 24 months with narrow age bins, children (4 and 12 years) and adults (20 to 24 years). The sensitivity profiles changed systematically with the source-detector separation distance. The peak of the sensitivity function in the head was largest at the smallest separation distance and decreased as separation distance increased. The fluence value dissipated more quickly with sampling depth at the shorter source-detector separations than the longer separation distances. There were age-related differences in the shape and variance of sensitivity profiles across a wide range of source-detector separation distances. Our findings have important implications in the design of sensor placement and diffuse optical tomography image reconstruction in (functional) near-infrared light spectroscopy research. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone near-infrared light spectroscopy data in infants.
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Affiliation(s)
- Xiaoxue Fu
- Department of Psychology, University of South Carolina, Columbia, United States of America
| | - John E. Richards
- Department of Psychology, University of South Carolina, Columbia, United States of America
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16
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Cai L, Okada E, Minagawa Y, Kawaguchi H. Correlating functional near-infrared spectroscopy with underlying cortical regions of 0-, 1-, and 2-year-olds using theoretical light propagation analysis. NEUROPHOTONICS 2021; 8:025009. [PMID: 34079846 PMCID: PMC8166262 DOI: 10.1117/1.nph.8.2.025009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 05/18/2021] [Indexed: 05/03/2023]
Abstract
Significance: The establishment of a light propagation analysis-based scalp-cortex correlation (SCC) between the scalp location of the source-detector (SD) pair and brain regions is essential for measuring functional brain development in the first 2 years of life using functional near-infrared spectroscopy (fNIRS). Aim: We aimed to reveal the optics-based SCC of 0-, 1-, and 2-year-olds (yo) and the suitable SD distance for this age period. Approach: Light propagation analyses using age-appropriate head models were conducted on SD pairs at 10-10 fiducial points on the scalp to obtain optics-based SCC and its metrics: the number of corresponding brain regions ( N C B R ), selectivity and sensitivity of the most likely corresponding brain region (MLCBR), and consistency of the MLCBR across developmental ages. Moreover, we assessed the suitable SD distances for 0-, 1-, and 2-yo by simultaneously considering the selectivity and sensitivity of the MLCBR. Results: Age-related changes in the SCC metrics were observed. For instance, the N C B R of 0-yo was larger than that of 1- and 2-yo. Conversely, the selectivity of 0-yo was lower than that of 1- and 2-yo. The sensitivity of 1-yo was higher than that of 0-yo at 15- to 30-mm SD distances and higher than that of 2-yo at 10-mm SD distance. Notably, the MLCBR of the fiducial points around the longitudinal fissure was inconsistent across age groups. An SD distance between 15 and 25 mm was found to be appropriate for satisfying both sensitivity and selectivity requirements. In addition, this work provides reference tables of optics-based SCC for 0-, 1-, and 2-yo. Conclusions: Optics-based SCC will be informative in designing and explaining child developmental studies using fNIRS. The suitable SD distances were between 15 and 25 mm for the first 2 years of life.
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Affiliation(s)
- Lin Cai
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
| | - Eiji Okada
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
| | | | - Hiroshi Kawaguchi
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
- National Institute of Advanced Industrial Science and Technology, Human Informatics and Interaction Research Institute, Tsukuba, Japan
- Address all correspondence to Hiroshi Kawaguchi,
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17
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Forbes SH, Wijeakumar S, Eggebrecht AT, Magnotta VA, Spencer JP. Processing pipeline for image reconstructed fNIRS analysis using both MRI templates and individual anatomy. NEUROPHOTONICS 2021; 8:025010. [PMID: 35106319 PMCID: PMC8786393 DOI: 10.1117/1.nph.8.2.025010] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 05/18/2021] [Indexed: 05/29/2023]
Abstract
Significance: Image reconstruction of fNIRS data is a useful technique for transforming channel-based fNIRS into a volumetric representation and managing spatial variance based on optode location. We present an innovative integrated pipeline for image reconstruction of fNIRS data using either MRI templates or individual anatomy. Aim: We demonstrate a pipeline with accompanying code to allow users to clean and prepare optode location information, prepare and standardize individual anatomical images, create the light model, run the 3D image reconstruction, and analyze data in group space. Approach: We synthesize a combination of new and existing software packages to create a complete pipeline, from raw data to analysis. Results: This pipeline has been tested using both templates and individual anatomy, and on data from different fNIRS data collection systems. We show high temporal correlations between channel-based and image-based fNIRS data. In addition, we demonstrate the reliability of this pipeline with a sample dataset that included 74 children as part of a longitudinal study taking place in Scotland. We demonstrate good correspondence between data in channel space and image reconstructed data. Conclusions: The pipeline presented here makes a unique contribution by integrating multiple tools to assemble a complete pipeline for image reconstruction in fNIRS. We highlight further issues that may be of interest to future software developers in the field.
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Affiliation(s)
- Samuel H. Forbes
- University of East Anglia, School of Psychology, Lawrence Stenhouse Building, Norwich, United Kingdom
| | | | - Adam T. Eggebrecht
- Washington University, Mallinckrodt Institute of Radiology, St Louis, Missouri, United States
| | | | - John P. Spencer
- University of East Anglia, School of Psychology, Lawrence Stenhouse Building, Norwich, United Kingdom
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18
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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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19
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Padawer-Curry JA, Jahnavi J, Breimann JS, Licht DJ, Yodh AG, Cohen AS, White BR. Variability in atlas registration of optical intrinsic signal imaging and its effect on functional connectivity analysis. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2021; 38:245-252. [PMID: 33690536 PMCID: PMC7993363 DOI: 10.1364/josaa.410447] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 12/22/2020] [Indexed: 05/25/2023]
Abstract
To compare neuroimaging data between subjects, images from individual sessions need to be aligned to a common reference or "atlas." Atlas registration of optical intrinsic signal imaging of mice, for example, is commonly performed using affine transforms with parameters determined by manual selection of canonical skull landmarks. Errors introduced by such procedures have not previously been investigated. We quantify the variability that arises from this process and consequent errors from misalignment that affect interpretation of functional neuroimaging data. We propose an improved method, using separately acquired high-resolution images and demonstrate improvements in variability and alignment using this method.
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Affiliation(s)
- Jonah A. Padawer-Curry
- Department of Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Jharna Jahnavi
- Department of Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Jake S. Breimann
- Department of Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Daniel J. Licht
- Department of Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Arjun G. Yodh
- Department of Physics and Astronomy, University of Pennsylvania. 3231 Walnut St., Philadelphia, PA 19104, USA
| | - Akiva S. Cohen
- Department of Anesthesiology and Critical Care Medicine, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3615 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Brian R. White
- Department of Pediatrics, The Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. 3401 Civic Center Blvd., Philadelphia, PA 19104 USA
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20
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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: 126] [Impact Index Per Article: 42.0] [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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21
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Wu MM, Chan ST, Mazumder D, Tamborini D, Stephens KA, Deng B, Farzam P, Chu JY, Franceschini MA, Qu JZ, Carp SA. Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling. NEUROPHOTONICS 2021; 8:015001. [PMID: 33437846 PMCID: PMC7779997 DOI: 10.1117/1.nph.8.1.015001] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Accepted: 12/09/2020] [Indexed: 05/08/2023]
Abstract
Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index ( CBF i ) estimates. Aim: We explore the effectiveness of MC DCS models in recovering accurate CBF i changes in the presence of strong systemic physiology variations during a hypercapnia maneuver. Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBF i timecourses. The results of the MC CBF i values from a set of human subject hypercapnia sessions were compared with CBF i values estimated using a semi-infinite analytical model, as commonly used in the field. Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBF i changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses. Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.
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Affiliation(s)
- Melissa M. Wu
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Suk-Tak Chan
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Dibbyan Mazumder
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Davide Tamborini
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Kimberly A. Stephens
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Bin Deng
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Parya Farzam
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Joyce Yawei Chu
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Jason Zhensheng Qu
- Massachusetts General Hospital, Harvard Medical School, Department of Anesthesia, Critical Care and Pain Medicine, Boston, Massachusetts, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Address all correspondence to Stefan A. Carp,
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22
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Collins-Jones LH, Arichi T, Poppe T, Billing A, Xiao J, Fabrizi L, Brigadoi S, Hebden JC, Elwell CE, Cooper RJ. Construction and validation of a database of head models for functional imaging of the neonatal brain. Hum Brain Mapp 2020; 42:567-586. [PMID: 33068482 PMCID: PMC7814762 DOI: 10.1002/hbm.25242] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 07/01/2020] [Accepted: 09/24/2020] [Indexed: 12/17/2022] Open
Abstract
The neonatal brain undergoes dramatic structural and functional changes over the last trimester of gestation. The accuracy of source localisation of brain activity recorded from the scalp therefore relies on accurate age-specific head models. Although an age-appropriate population-level atlas could be used, detail is lost in the construction of such atlases, in particular with regard to the smoothing of the cortical surface, and so such a model is not representative of anatomy at an individual level. In this work, we describe the construction of a database of individual structural priors of the neonatal head using 215 individual-level datasets at ages 29-44 weeks postmenstrual age from the Developing Human Connectome Project. We have validated a method to segment the extra-cerebral tissue against manual segmentation. We have also conducted a leave-one-out analysis to quantify the expected spatial error incurred with regard to localising functional activation when using a best-matching individual from the database in place of a subject-specific model; the median error was calculated to be 8.3 mm (median absolute deviation 3.8 mm). The database can be applied for any functional neuroimaging modality which requires structural data whereby the physical parameters associated with that modality vary with tissue type and is freely available at www.ucl.ac.uk/dot-hub.
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Affiliation(s)
- Liam H Collins-Jones
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Biomedical Optics Research Laboratory, Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK.,Department of Bioengineering, Imperial College of Science, Technology, and Medicine, London, UK
| | - Tanya Poppe
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK
| | - Addison Billing
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Institute for Cognitive Neuroscience, University College London, London, UK
| | - Jiaxin Xiao
- Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, UK
| | - Lorenzo Fabrizi
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Sabrina Brigadoi
- Department of Information Engineering, University of Padova, Padova, Italy.,Department of Developmental Psychology and Socialisation, University of Padova, Padova, Italy
| | - Jeremy C Hebden
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Biomedical Optics Research Laboratory, Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Clare E Elwell
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Robert J Cooper
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Biomedical Optics Research Laboratory, Medical Physics and Biomedical Engineering, University College London, London, UK
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23
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Hu XS, Wagley N, Rioboo AT, DaSilva AF, Kovelman I. Photogrammetry-based stereoscopic optode registration method for functional near-infrared spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200049R. [PMID: 32880124 PMCID: PMC7463164 DOI: 10.1117/1.jbo.25.9.095001] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 08/11/2020] [Indexed: 05/24/2023]
Abstract
SIGNIFICANCE Functional near-infrared spectroscopy (fNIRS) is an emerging brain imaging technique due to its small size, low cost, minimum scanning sonic noise, and portability. Unfortunately, because this technique does not provide neuroanatomical information to accompany the functional data, its data interpretation remains a persistent challenge in fNIRS brain imaging applications. The two most popular approaches for fNIRS anatomical registration are magnetic resonance imaging (MRI) and three-dimensional (3-D) digitization. MRI scanning yields high-precision registration but reduces the cost-effectiveness and accessibility of fNIRS imaging. Alternatively, the low cost and portable 3-D digitizers are affected by magnetic properties of ambient metal objects, including participant clothing, testing equipment, medical implants, and so forth. AIM To overcome these obstacles and provide accessible and reliable neuroanatomical registration for fNIRS imaging, we developed and explored a photogrammetry optode registration (POR) method. APPROACH The POR method uses a consumer-grade camera to reconstruct a 3-D image of the fNIRS optode-set, including light emitters and detectors, on a participant's head. This reconstruction process uses a linear-time incremental structure from motion (LTI-SfM) algorithm, based on 100 to 150 digital photos. The POR method then aligns the reconstructed image with an anatomical template of the brain. RESULTS To validate this method, we tested 22 adult and 19 child participants using the POR method and MRI imaging. The results comparisons suggest on average 55% and 46% overlap across all data channel measurements registered by the two methods in adult and children, respectively. Importantly, this overlap reached 65% and 60% in only the frontal channels. CONCLUSIONS These results suggested that the mismatch in registration was partially due to higher variation in backward optode placement rather than the registration efficacy. Therefore, the photo-based registration method can offer an accessible and reliable approach to neuroanatomical registration of fNIRS as well as other surface-based neuroimaging and neuromodulation methods.
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Affiliation(s)
- Xiao-Su Hu
- University of Michigan, School of Dentistry, Department of Biologic and Materials Sciences and Prosthodontics, Headache & Orofacial Pain Effort (H.O.P.E.) Lab, Ann Arbor, Michigan, United States
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Neelima Wagley
- University of Michigan, Department of Psychology, Ann Arbor, Michigan, United States
| | - Akemi Tsutsumi Rioboo
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Alexandre F. DaSilva
- University of Michigan, School of Dentistry, Department of Biologic and Materials Sciences and Prosthodontics, Headache & Orofacial Pain Effort (H.O.P.E.) Lab, Ann Arbor, Michigan, United States
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Ioulia Kovelman
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
- University of Michigan, Department of Psychology, Ann Arbor, Michigan, United States
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24
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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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25
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Mahmoodkalayeh S, Zarei M, Ansari MA, Kratkiewicz K, Ranjbaran M, Manwar R, Avanaki K. Improving vascular imaging with co-planar mutually guided photoacoustic and diffuse optical tomography: a simulation study. BIOMEDICAL OPTICS EXPRESS 2020; 11:4333-4347. [PMID: 32923047 PMCID: PMC7449743 DOI: 10.1364/boe.385017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 07/01/2020] [Accepted: 07/01/2020] [Indexed: 05/04/2023]
Abstract
Diffuse optical tomography (DOT) and photoacoustic tomography (PAT) are functional imaging modalities that provide absorption coefficient maps of the tissue. Spatial resolution of DOT is relatively low due to light scattering characteristics of the tissue. On the other hand, although PAT can resolve regions of different absorptions with a high spatial resolution, measuring the absolute value of optical absorptions using PAT is challenging due to unknown light fluence distribution in the tissue. Development of image guidance techniques using a priori information of imaging target structure has been shown to increase the accuracy of DOT. PAT is one such method that can be used as a complementary modality to serve as a guide for DOT image reconstruction. On the other hand, estimated fluence map provided by DOT can be used to quantitatively correct PAT images. In this study we introduce a mutually-guided imaging system for fast and simultaneous optical and photoacoustic measurements of tissue absorption map, where DOT is guided by the PAT image and vice versa. Using the obtained absorption map of the tissue, we then estimate the tissue scattering map. We conducted this study using a series of simulations on digital phantoms and demonstrated the effectiveness of the proposed method.
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Affiliation(s)
| | - Mehrdad Zarei
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran 19839 69411, Iran
| | - Mohammad Ali Ansari
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran 19839 69411, Iran
| | - Karl Kratkiewicz
- Wayne State University, Bioengineering Department, Detroit, Michigan 48201, USA
| | - Mohsen Ranjbaran
- Department of Physics, University of Isfahan, Isfahan 81746-73441, Iran
| | - Rayyan Manwar
- Wayne State University, Bioengineering Department, Detroit, Michigan 48201, USA
| | - Kamran Avanaki
- Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60607, USA
- Department of Dermatology, University of Illinois at Chicago, Chicago, Illinois 60607, USA
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26
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Zhao H, Brigadoi S, Chitnis D, Vita ED, Castellaro M, Powell S, Everdell NL, Cooper RJ. A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging. BIOMEDICAL OPTICS EXPRESS 2020; 11:4110-4129. [PMID: 32923032 PMCID: PMC7449732 DOI: 10.1364/boe.394914] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 06/03/2020] [Accepted: 06/09/2020] [Indexed: 05/09/2023]
Abstract
The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience.
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Affiliation(s)
- Hubin Zhao
- DOT-HUB, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Sabrina Brigadoi
- Department of Developmental and Social Psychology, University of Padova, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Danial Chitnis
- School of Engineering, Institute for Integrated Micro and Nano Systems, University of Edinburgh, Edinburgh, EH9 3FF, UK
| | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, SE1 7EH, UK
| | - Marco Castellaro
- Department of Information Engineering, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Samuel Powell
- Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Nicholas L. Everdell
- DOT-HUB, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Robert J. Cooper
- DOT-HUB, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
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27
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Brain correlates of motor complexity during observed and executed actions. Sci Rep 2020; 10:10965. [PMID: 32620887 PMCID: PMC7335074 DOI: 10.1038/s41598-020-67327-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 05/18/2020] [Accepted: 06/05/2020] [Indexed: 12/29/2022] Open
Abstract
Recently, cortical areas with motor properties have attracted attention widely to their involvement in both action generation and perception. Inferior frontal gyrus (IFG), ventral premotor cortex (PMv) and inferior parietal lobule (IPL), presumably consisting of motor-related areas, are of particular interest, given that they respond to motor behaviors both when they are performed and observed. Converging neuroimaging evidence has shown the functional roles of IFG, PMv and IPL in action understanding. Most studies have focused on the effects of modulations in goals and kinematics of observed actions on the brain response, but little research has explored the effects of manipulations in motor complexity. To address this, we used fNIRS to examine the brain activity in the frontal, motor, parietal and occipital regions, aiming to better understand the brain correlates involved in encoding motor complexity. Twenty-one healthy adults executed and observed two hand actions that differed in motor complexity. We found that motor complexity sensitive brain regions were present in the pars opercularis IFG/PMv, primary motor cortex (M1), IPL/supramarginal gyrus and middle occipital gyrus (MOG) during action execution, and in pars opercularis IFG/PMv and M1 during action observation. Our findings suggest that the processing of motor complexity involves not only M1 but also pars opercularis IFG, PMv and IPL, each of which plays a critical role in action perception and execution.
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28
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Tran AP, Yan S, Fang Q. Improving model-based functional near-infrared spectroscopy analysis using mesh-based anatomical and light-transport models. NEUROPHOTONICS 2020; 7:015008. [PMID: 32118085 PMCID: PMC7035879 DOI: 10.1117/1.nph.7.1.015008] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 02/05/2020] [Indexed: 05/04/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. Aim: We aim to highlight the importance of accurate anatomical modeling in the context of fNIRS and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. Approach: We have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models, compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multilayered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element-based photon simulations for fNIRS studies. Results: A variety of high-quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare three brain anatomical models-the voxel-based brain segmentation, tetrahedral brain mesh, and layered-slab brain model-and demonstrate noticeable discrepancies in brain partial pathlengths when using approximated brain anatomies, ranging between - 1.5 % to 23% with the voxelated brain and 36% to 166% with the layered-slab brain. Conclusion: The generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes "Brain2Mesh" and "Iso2Mesh" are freely available at http://mcx.space/brain2mesh.
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Affiliation(s)
- Anh Phong Tran
- Northeastern University, Department of Chemical Engineering, Boston, Massachusetts, United States
| | - Shijie Yan
- Northeastern University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
| | - Qianqian Fang
- Northeastern University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
- Address all correspondence to Qianqian Fang, E-mail:
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29
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Abdalmalak A, Milej D, Cohen DJ, Anazodo U, Ssali T, Diop M, Owen AM, St Lawrence K. Using fMRI to investigate the potential cause of inverse oxygenation reported in fNIRS studies of motor imagery. Neurosci Lett 2019; 714:134607. [PMID: 31693928 DOI: 10.1016/j.neulet.2019.134607] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/28/2019] [Accepted: 10/30/2019] [Indexed: 12/31/2022]
Abstract
Motor imagery (MI) is a commonly used cognitive task in brain-computer interface (BCI) applications because it produces reliable activity in motor-planning regions. However, a number of functional near-infrared spectroscopy (fNIRS) studies have reported the unexpected finding of inverse oxygenation: increased deoxyhemoglobin and decreased oxyhemoglobin during task periods. This finding questions the reliability of fNIRS for BCI applications given that MI activation should result in a focal increase in blood oxygenation. In an attempt to elucidate this phenomenon, fMRI and fNIRS data were acquired on 15 healthy participants performing a MI task. The fMRI data provided global coverage of brain activity, thus allowing visualization of all potential brain regions activated and deactivated during task periods. Indeed, fMRI results from seven subjects included activation in the primary motor cortex and/or the pre-supplementary motor area during the rest periods in addition to the expected activation in the supplementary motor and premotor areas. Of these seven subjects, two showed inverse oxygenation with fNIRS. The proximity of the regions showing inverse oxygenation to the motor planning regions suggests that inverse activation detected by fNIRS may likely be a consequence of partial volume errors due to the sensitivity of the optodes to both primary motor and motor planning regions.
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Affiliation(s)
- Androu Abdalmalak
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada.
| | - Daniel Milej
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
| | - David J Cohen
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
| | - Udunna Anazodo
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
| | - Tracy Ssali
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
| | - Mamadou Diop
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
| | - Adrian M Owen
- The Brain and Mind Institute, Western University, London, Ontario, N6A 5B7, Canada
| | - Keith St Lawrence
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada; Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1 Canada
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30
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Mahmoodkalayeh S, Ansari MA, Tuchin VV. Head model based on the shape of the subject's head for optical brain imaging. BIOMEDICAL OPTICS EXPRESS 2019; 10:2795-2808. [PMID: 31259052 PMCID: PMC6583357 DOI: 10.1364/boe.10.002795] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 04/24/2019] [Accepted: 05/09/2019] [Indexed: 05/05/2023]
Abstract
Optical imaging methods such as near-infrared spectroscopy and diffuse optical tomography rely on models to solve the inverse problem. Imaging an adult human head also requires a head model. Using a model, which makes describing the structure of the head better, leads to acquiring a more accurate absorption map. Here, by combining the key features of layered slab models and head atlases, we introduce a new two-layered head model that is based on the surface geometry of the subject's head with variable thickness of the superficial layer. Using the Monte Carlo approach, we assess the performance of our model for fitting the optical properties from simulated time-resolved data of the adult head in a null distance source-detector configuration. Using our model, we observed improved results at 70 percent of the locations on the head and an overall 20 percent reduction in relative error compared to layered slab model.
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Affiliation(s)
- Sadreddin Mahmoodkalayeh
- Department of Physics, Shahid Beheshti University, Velenjak, Tehran, Iran
- Laser and Plasma Research Institute, Shahid Beheshti University, 1983969411, Tehran, Iran
| | - Mohammad Ali Ansari
- Laser and Plasma Research Institute, Shahid Beheshti University, 1983969411, Tehran, Iran
| | - Valery V. Tuchin
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Interdisciplinary Laboratory of Biophotonics, Tomsk State University, Tomsk, Russia
- Laboratory of Laser Diagnostics of Technical and Living Systems, Institute of Precision Mechanics and Control of the Russian Academy of Sciences, Saratov, Russia
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31
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Wheelock MD, Culver JP, Eggebrecht AT. High-density diffuse optical tomography for imaging human brain function. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2019; 90:051101. [PMID: 31153254 PMCID: PMC6533110 DOI: 10.1063/1.5086809] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Accepted: 04/14/2019] [Indexed: 05/08/2023]
Abstract
This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.
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Affiliation(s)
- Muriah D. Wheelock
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | | | - Adam T. Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
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32
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Wang C, Zhang T, Shan Z, Liu J, Yuan D, Li X. Dynamic interpersonal neural synchronization underlying pain-induced cooperation in females. Hum Brain Mapp 2019; 40:3222-3232. [PMID: 30950151 DOI: 10.1002/hbm.24592] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 03/18/2019] [Accepted: 03/25/2019] [Indexed: 01/13/2023] Open
Abstract
Individuals in pain are motivated to be cooperative in social interaction. Yet, there has been little research on how pain dynamically affects cooperation at a neural level. The present study investigated the cooperative behavior under acute physical pain by asking dyads to complete three blocks of button-press cooperative task, while neural activities were recorded simultaneously on each subject by the fNIRS-based hyperscanning. Results showed that individuals in pain improved their cooperation rate across task blocks. Accordingly, increased interpersonal neural synchronization (INS) was found at the left prefrontal cortex in second block, whereas increased INS was found at the right prefrontal cortex and the right parietal cortex in third block compared to the first block. Moreover, the change of INS in right parietal cortex was positively correlated with subjective pain rating in the pain treatment group. In addition, dynamic interpersonal neural networks were identified in painful condition with increasing frontoparietal networks across time. By uncovering dissociative neural processes involved in how pain affects cooperation in social interaction, the present work provides the first interbrain evidence to highlight the sociality of pain on social interaction in perspective of motivational aspect of pain.
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Affiliation(s)
- Chenbo Wang
- Laboratory of Brain Functional Genomics (MOE&STCSM), Shanghai Changning-ECNU Mental Health Center, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Tingyu Zhang
- School of Psychology and Cognitive Science, Shanghai Changning-ECNU Mental Health Center, East China Normal University, Shanghai, China
| | - Zhoukuidong Shan
- Laboratory of Brain Functional Genomics (MOE&STCSM), Shanghai Changning-ECNU Mental Health Center, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Jieqiong Liu
- School of Psychology and Cognitive Science, Shanghai Changning-ECNU Mental Health Center, East China Normal University, Shanghai, China
| | - Di Yuan
- School of Psychology and Cognitive Science, Shanghai Changning-ECNU Mental Health Center, East China Normal University, Shanghai, China
| | - Xianchun Li
- Laboratory of Brain Functional Genomics (MOE&STCSM), Shanghai Changning-ECNU Mental Health Center, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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Perrey S, Besson P. Studying brain activity in sports performance: Contributions and issues. PROGRESS IN BRAIN RESEARCH 2018; 240:247-267. [PMID: 30390834 DOI: 10.1016/bs.pbr.2018.07.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Understanding the interactions between brain activity and behavior comprehensively in achieving optimal exercise performance in sports is still lacking. The existent research in this area has been limited by the constraints of sports environments and the robustness of the most suitable non-invasive functional neuroimaging methods (electroencephalography, EEG and functional near-infrared spectroscopy, fNIRS) to motion artifacts and noise. However, recent advances in brain mapping technology should improve the capabilities of the future brain imaging devices to assess and monitor the level of adaptive cognitive-motor performance during exercise in sports environments. The purpose of this position manuscript is to discuss the contributions and issues in behavioral neuroscience related to brain activity measured during exercise and in various sports. A first part aims to give an overview of EEG and fNIRS neuroimaging methods assessing electrophysiological activity and hemodynamic responses of the acute and chronic relation of physical exercise on the human brain. Then, methodological issues, such as the reliability of brain data during physical exertion, key limitations and possible prospects of fNIRS and EEG methods are provided. While the use of such methods in sports environments remains scarce and limited to controlled cycling task, new generation of wearable, whole-scalp EEG and fNIRS technologies could open up a range of new applications in sports sciences for providing neuroimaging-based biomarkers (hemodynamic and/or neural electrical signals) to various types of exercise and innovative training.
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Affiliation(s)
| | - Pierre Besson
- Euromov-University of Montpellier, Montpellier, France
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Relationship between sensorimotor cortical activation as assessed by functional near infrared spectroscopy and lower extremity motor coordination in bilateral cerebral palsy. NEUROIMAGE-CLINICAL 2018; 20:275-285. [PMID: 30101059 PMCID: PMC6083901 DOI: 10.1016/j.nicl.2018.07.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 06/28/2018] [Accepted: 07/25/2018] [Indexed: 12/31/2022]
Abstract
Background Evaluation of task-evoked cortical responses during movement has been limited in individuals with bilateral cerebral palsy (CP), despite documented alterations in brain structure/function and deficits in motor control. Objective To systematically evaluate cortical activity associated with lower extremity tasks, and relate activation parameters to clinical measures in CP. Methods 28 ambulatory participants (14 with bilateral CP and 14 with typical development) completed five motor tasks (non-dominant ankle dorsiflexion, hip flexion and leg cycling as well as bilateral dorsiflexion and cycling) in a block design while their sensorimotor cortex was monitored using functional near infrared spectroscopy (fNIRS), in addition to laboratory and clinical measures of performance. Results Main effects for group and task were found for extent of fNIRS activation (number of active channels; p < 0.001 and p = 0.010, respectively), magnitude of activation (sum of beta values; p < 0.001 for both), and number of active muscles (p = 0.001 and p < 0.001, respectively), but no group by task interactions. Collectively, subgroups with CP and especially those with greater impairments, showed higher extent and magnitude of cortical sensorimotor activation as well as higher amounts of concurrent activity in muscles not required for task performance. Magnitude of fNIRS activation during non-dominant dorsiflexion correlated with validated measures of selective control (r = −0.60, p = 0.03), as well as mobility and daily activity (r = −0.55, p = 0.04 and r = −0.52, p = 0.05, respectively) and self-reported gait function (r = −0.68, p = 0.01) in those with CP. Conclusions The association between higher activity in the sensorimotor cortex and decreased selectivity in cortical organization suggests a potential neural mechanism of motor deficits and target for intervention. First fNIRS comparison of a range of lower extremity tasks in children with and without bilateral CP. FNIRS showed a greater amount and extent of activation of sensorimotor cortices in CP. Greater activation correlated with a greater number of muscles involved in the task. fNIRS results correlated to clinical measures of motor control and function.
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Machado A, Cai Z, Pellegrino G, Marcotte O, Vincent T, Lina JM, Kobayashi E, Grova C. Optimal positioning of optodes on the scalp for personalized functional near-infrared spectroscopy investigations. J Neurosci Methods 2018; 309:91-108. [PMID: 30107210 DOI: 10.1016/j.jneumeth.2018.08.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 08/07/2018] [Accepted: 08/08/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND Application of functional Near InfraRed Spectroscopy (fNIRS) in neurology is still limited as a good optical coupling and optimized optode coverage of specific brain regions remains challenging, notably for prolonged monitoring. METHODS We propose to evaluate a new procedure allowing accurate investigation of specific brain regions. The procedure consists in: (i) A priori maximization of spatial sensitivity of fNIRS measurements targeting specific brain regions, while reducing the number of applied optodes in order to decrease installation time and improve subject comfort. (ii) Utilization of a 3D neuronavigation device and usage of collodion to glue optodes on the scalp, ensuring good optical contact for prolonged investigations. (iii) Local reconstruction of the hemodynamic activity along the cortical surface using inverse modelling. RESULTS Using realistic simulations, we demonstrated that maps derived from optimal montage acquisitions showed, after reconstruction, spatial resolution only slightly lower to that of ultra high density montages while significantly reducing the number of optodes. The optimal montages provided overall good quantitative accuracy especially at the peak of the spatially reconstructed map. We also evaluated real motor responses in two healthy subjects and obtained reproducible motor responses over different sessions. COMPARISON WITH EXISTING METHODS We are among the first to propose a mathematical optimization strategy, allowing high sensitivity measurements. CONCLUSIONS Our results support that using personalized optimal montages should allow to conduct accurate fNIRS studies in clinical settings and realistic lifestyle conditions.
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Affiliation(s)
- A Machado
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada.
| | - Z Cai
- Physics Department and PERFORM center, Concordia University, Montreal, Canada
| | - G Pellegrino
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada; IRCCS Fondazione Ospedale San Camillo Via Alberoni, Venice, Italy
| | - O Marcotte
- GERAD, École des HEC, Montréal, Canada; Département d'informatique, Université du Québec à Montréal, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
| | - T Vincent
- Physics Department and PERFORM center, Concordia University, Montreal, Canada
| | - J-M Lina
- École de technologie supérieure de l'Université du Québec, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
| | - E Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Canada
| | - C Grova
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada; Physics Department and PERFORM center, Concordia University, Montreal, Canada; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
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Tremblay J, Martínez-Montes E, Vannasing P, Nguyen DK, Sawan M, Lepore F, Gallagher A. Comparison of source localization techniques in diffuse optical tomography for fNIRS application using a realistic head model. BIOMEDICAL OPTICS EXPRESS 2018; 9:2994-3016. [PMID: 30619642 PMCID: PMC6033567 DOI: 10.1364/boe.9.002994] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 05/18/2018] [Accepted: 05/26/2018] [Indexed: 05/24/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique that elicits growing interest for research and clinical applications. In the last decade, efforts have been made to develop a mathematical framework in order to image the effective sources of hemoglobin variations in brain tissues. Different approaches can be used to impose additional information or constraints when reconstructing the cerebral images of an ill-posed problem. The goal of this study is to compare the performance and limitations of several source localization techniques in the context of fNIRS tomography using individual anatomical magnetic resonance imaging (MRI) to model light propagation. The forward problem is solved using a Monte Carlo simulation of light propagation in the tissues. The inverse problem has been linearized using the Rytov approximation. Then, Tikhonov regularization applied to least squares, truncated singular value decomposition, back-projection, L1-norm regularization, minimum norm estimates, low resolution electromagnetic tomography and Bayesian model averaging techniques are compared using a receiver operating characteristic analysis, blurring and localization error measures. Using realistic simulations (n = 450) and data acquired from a human participant, this study depicts how these source localization techniques behave in a human head fNIRS tomography. When compared to other methods, Bayesian model averaging is proposed as a promising method in DOT and shows great potential to improve specificity, accuracy, as well as to reduce blurring and localization error even in presence of noise and deep sources. Classical reconstruction methods, such as regularized least squares, offer better sensitivity but higher blurring; while more novel L1-based method provides sparse solutions with small blurring and high specificity but lower sensitivity. The application of these methods is also demonstrated experimentally using visual fNIRS experiment with adult participant.
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Affiliation(s)
- Julie Tremblay
- LIONLAB, Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Canada
| | | | - Phetsamone Vannasing
- LIONLAB, Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Canada
| | - Dang K Nguyen
- Neurology Division, Centre hospitalier de l'Université de Montréal (CHUM), Hôpital Notre-Dame, Montréal, Canada
| | - Mohamad Sawan
- Polystim Neurotech Lab, Polytechnique Montréal, Montréal, Canada
| | - Franco Lepore
- Centre de recherche en neuropsychologie et cognition (CERNEC), Département de psychologie, Université de Montréal, Montréal, Canada
| | - Anne Gallagher
- LIONLAB, Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Canada
- Centre de recherche en neuropsychologie et cognition (CERNEC), Département de psychologie, Université de Montréal, Montréal, Canada
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Zhao H, Cooper RJ. Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system. NEUROPHOTONICS 2018; 5:011012. [PMID: 28983490 PMCID: PMC5613216 DOI: 10.1117/1.nph.5.1.011012] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 08/28/2017] [Indexed: 05/23/2023]
Abstract
The development of a whole-scalp, high sampling-density diffuse optical tomography (DOT) system is a critical next step in the evolution of the field of diffuse optics. To achieve this with optical fiber bundles is extremely challenging, simply because of the sheer number of bundles required, and the associated challenges of weight and ergonomics. Dispensing with optical fiber bundles and moving to head-mounted optoelectronics can potentially facilitate the advent of a new generation of wearable, whole-scalp technologies that will open up a range of new experimental and clinical applications for diffuse optical measurements. Here, we present a concise review of the significant progress that has been made toward achieving a wearable, fiberless, high-density, whole-scalp DOT system. We identify the key limitations of current technologies and discuss the possible opportunities for future development.
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Affiliation(s)
- Hubin Zhao
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Robert J. Cooper
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
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38
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Lee CW, Cooper RJ, Austin T. Diffuse optical tomography to investigate the newborn brain. Pediatr Res 2017; 82:376-386. [PMID: 28419082 DOI: 10.1038/pr.2017.107] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Accepted: 02/06/2017] [Indexed: 11/09/2022]
Abstract
Over the past 15 years, functional near-infrared spectroscopy (fNIRS) has emerged as a powerful technology for studying the developing brain. Diffuse optical tomography (DOT) is an extension of fNIRS that combines hemodynamic information from dense optical sensor arrays over a wide field of view. Using image reconstruction techniques, DOT can provide images of the hemodynamic correlates to neural function that are comparable to those produced by functional magnetic resonance imaging. This review article explains the principles of DOT, and highlights the growing literature on the use of DOT in the study of healthy development of the infant brain, and the study of novel pathophysiology in infants with brain injury. Current challenges, particularly around instrumentation and image reconstruction, will be discussed, as will the future of this growing field, with particular focus on whole-brain, time-resolved DOT.
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Affiliation(s)
- Chuen Wai Lee
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Neonatology, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Robert J Cooper
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Topun Austin
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Neonatology, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Brigadoi S, Phan P, Highton D, Powell S, Cooper RJ, Hebden J, Smith M, Tachtsidis I, Elwell CE, Gibson AP. Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data. NEUROPHOTONICS 2017; 4:021105. [PMID: 28560239 PMCID: PMC5443419 DOI: 10.1117/1.nph.4.2.021105] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 05/01/2017] [Indexed: 05/23/2023]
Abstract
In diffuse optical tomography (DOT), overlapping and multidistance measurements are required to reconstruct depth-resolved images of oxy- ([Formula: see text]) and deoxy- (HHb) hemoglobin concentration changes occurring in the brain. These can be considered an indirect measure of brain activity, under the assumption of intact neurovascular coupling. Broadband systems also allow changes in the redox state of cytochrome c oxidase (oxCCO) to be measured, which can be an important biomarker when neurovascular coupling is impaired. We used DOT to reconstruct images of [Formula: see text], [Formula: see text], and [Formula: see text] from data acquired with a broadband system. Four healthy volunteers were measured while performing a visual stimulation task (4-Hz inverting checkerboard). The broadband system was configured to allow multidistance and overlapping measurements of the participants' visual cortex with 32 channels. A multispectral approach was employed to reconstruct changes in concentration of the three chromophores during the visual stimulation. A clear and focused activation was reconstructed in the left occipital cortex of all participants. The difference between the residuals of the three-chromophore model and of the two-chromophore model (recovering only [Formula: see text] and [Formula: see text]) exhibits a spectrum similar to that of oxCCO. These results form a basis for further studies aimed to further optimize image reconstruction of [Formula: see text].
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Affiliation(s)
- Sabrina Brigadoi
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
- University of Padova, Department of Developmental and Social Psychology, Padova, Italy
| | - Phong Phan
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - David Highton
- National Hospital for Neurology and Neurosurgery, Neurocritical Care, London, United Kingdom
| | - Samuel Powell
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
- University College London, Department of Computer Science, London, United Kingdom
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Jeremy Hebden
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Martin Smith
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
- National Hospital for Neurology and Neurosurgery, Neurocritical Care, London, United Kingdom
- NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Clare E. Elwell
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Adam P. Gibson
- University College London, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
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40
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Wijeakumar S, Huppert TJ, Magnotta VA, Buss AT, Spencer JP. Validating an image-based fNIRS approach with fMRI and a working memory task. Neuroimage 2017; 147:204-218. [DOI: 10.1016/j.neuroimage.2016.12.007] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2015] [Revised: 11/15/2016] [Accepted: 12/03/2016] [Indexed: 10/20/2022] Open
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41
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Hernández-Martin E, Marcano F, Casanova O, Modroño C, Plata-Bello J, González-Mora JL. Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study. NEUROPHOTONICS 2017; 4:015003. [PMID: 28386575 PMCID: PMC5350545 DOI: 10.1117/1.nph.4.1.015003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 02/28/2017] [Indexed: 05/07/2023]
Abstract
Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp-brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity.
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Affiliation(s)
- Estefania Hernández-Martin
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
- Address all correspondence to: Estefania Hernández-Martin, E-mail:
| | - Francisco Marcano
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
| | - Oscar Casanova
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
| | - Cristian Modroño
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
| | - Julio Plata-Bello
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
| | - Jose Luis González-Mora
- Universidad de La Laguna, Faculty of Health Sciences (Medicine Section), Department of Basic Medical Science (Physiology Section), Spain
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42
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Davies DJ, Clancy M, Lighter D, Balanos GM, Lucas SJE, Dehghani H, Su Z, Forcione M, Belli A. Frequency-domain vs continuous-wave near-infrared spectroscopy devices: a comparison of clinically viable monitors in controlled hypoxia. J Clin Monit Comput 2016; 31:967-974. [PMID: 27778208 PMCID: PMC5599440 DOI: 10.1007/s10877-016-9942-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Accepted: 10/07/2016] [Indexed: 11/13/2022]
Abstract
The Near-infrared spectroscopy (NIRS) has not been adopted as a mainstream monitoring modality in acute neurosurgical care due to concerns about its reliability and consistency. However, improvements in NIRS parameter recovery techniques are now available that may improve the quantitative accuracy of NIRS for this clinical context. Therefore, the aim of this study was to compare the abilities of a continuous-wave (CW) NIRS device with a similarly clinically viable NIRS device utilising a frequency-domain (FD) parameter recovery technique in detecting changes in cerebral tissue saturation during stepwise increases of experimentally induced hypoxia. Nine healthy individuals (6M/3F) underwent a dynamic end-tidal forced manipulation of their expiratory gases to induce a stepwise induced hypoxia. The minimum end-tidal oxygen partial pressure (EtO2) achieved was 40 mm Hg. Simultaneous neurological and extra-cranial tissue NIRS reading were obtained during this protocol by both tested devices. Both devices detected significant changes in cerebral tissue saturation during the induction of hypoxia (CW 9.8 ± 2.3 %; FD 7.0 ± 3.4 %; Wilcoxon signed rank test P < 0.01 for both devices). No significant difference was observed between the saturation changes observed by either device (P = 0.625). An observably greater degree of noise was noticed in parameters recovered by the FD device, and both demonstrated equally variable baseline readings (Coefficient of variance 8.4 and 9.7 % for the CW and FD devices, respectively) between individuals tested. No advantageous difference was observed in parameters recovered from the FD device compared with those detected by CW.
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Affiliation(s)
- David James Davies
- National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre (NIHR SRMRC), University Hospitals Birmingham NHS Foundation Trust, Heritage Building (Old Queen Elizabeth Hospital), Edgbaston, Birmingham, B15 2TH, UK. .,Department of Neurosurgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
| | - Michael Clancy
- PSIBS Doctoral Training Centre, University of Birmingham, Birmingham, UK
| | - Daniel Lighter
- School of Chemistry, University of Birmingham, Birmingham, UK
| | - George M Balanos
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK
| | - Samuel John Edwin Lucas
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK
| | - Hamid Dehghani
- PSIBS Doctoral Training Centre, University of Birmingham, Birmingham, UK
| | - Zhangjie Su
- National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre (NIHR SRMRC), University Hospitals Birmingham NHS Foundation Trust, Heritage Building (Old Queen Elizabeth Hospital), Edgbaston, Birmingham, B15 2TH, UK.,School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - Mario Forcione
- Department of Neurosurgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Antonio Belli
- National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre (NIHR SRMRC), University Hospitals Birmingham NHS Foundation Trust, Heritage Building (Old Queen Elizabeth Hospital), Edgbaston, Birmingham, B15 2TH, UK.,Department of Neurosurgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.,School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
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43
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Li L, Cazzell M, Babawale O, Liu H. Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults. NEUROPHOTONICS 2016; 3:045002. [PMID: 27752518 PMCID: PMC5052324 DOI: 10.1117/1.nph.3.4.045002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 09/12/2016] [Indexed: 05/12/2023]
Abstract
Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.
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Affiliation(s)
- Lin Li
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas 76019, United States
- University of California, Department of Neurology, David Geffen School of Medicine, Los Angeles, California 90095, United States
| | - Mary Cazzell
- Cook Children’s Medical Center, 801 Seventh Avenue, Fort Worth, Texas 76104, United States
| | - Olajide Babawale
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas 76019, United States
| | - Hanli Liu
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas 76019, United States
- Address all correspondence to: Hanli Liu, E-mail:
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Clancy M, Belli A, Davies D, Lucas SJE, Su Z, Dehghani H. Improving the quantitative accuracy of cerebral oxygen saturation in monitoring the injured brain using atlas based Near Infrared Spectroscopy models. JOURNAL OF BIOPHOTONICS 2016; 9:812-826. [PMID: 27003677 DOI: 10.1002/jbio.201500302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 02/18/2016] [Accepted: 02/18/2016] [Indexed: 06/05/2023]
Abstract
The application of Near Infrared Spectroscopy (NIRS) for the monitoring of the cerebral oxygen saturation within the brain is well established, albeit using temporal data that can only measure relative changes of oxygenation state of the brain from a baseline. The focus of this investigation is to demonstrate that hybridisation of existing near infrared probe designs and reconstruction techniques can pave the way to produce a system and methods that can be used to monitor the absolute oxygen saturation in the injured brain. Using registered Atlas models in simulation, a novel method is outlined by which the quantitative accuracy and practicality of NIRS for specific use in monitoring the injured brain, can be improved, with cerebral saturation being recovered to within 10.1 ± 1.8% of the expected values.
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Affiliation(s)
- Michael Clancy
- PSIBS Doctoral Training Centre, University of Birmingham, United Kingdom.
| | - Antonio Belli
- NIHR Surgical Reconstruction and Microbiology Research Centre, Queen Elizabeth Hospital Birmingham, United Kingdom
| | - David Davies
- NIHR Surgical Reconstruction and Microbiology Research Centre, Queen Elizabeth Hospital Birmingham, United Kingdom
| | - Samuel J E Lucas
- School of Sport, Exercise and Rehabilitation Science, University of Birmingham, United Kingdom
| | - Zhangjie Su
- NIHR Surgical Reconstruction and Microbiology Research Centre, Queen Elizabeth Hospital Birmingham, United Kingdom
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, United Kingdom
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45
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Noninvasive Brain Physiology Monitoring for Extreme Environments: A Critical Review. J Neurosurg Anesthesiol 2016; 27:318-28. [PMID: 25811362 DOI: 10.1097/ana.0000000000000175] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Our ability to monitor the brain physiology is advancing; however, most of the technology is bulky, expensive, and designed for traditional clinical settings. With long-duration space exploration, there is a need for developing medical technologies that are reliable, low energy, portable, and semiautonomous. Our aim was to review the state of the art for noninvasive technologies capable of monitoring brain physiology in diverse settings. A literature review of PubMed and the Texas Medical Center library sites was performed using prespecified search criteria to identify portable technologies for monitoring physiological aspects of the brain physiology. Most brain-monitoring technologies require a moderate to high degree of operator skill. Some are low energy, but many require a constant external power supply. Most of the technologies lack the accuracy seen in gold standard measures, due to the need for calibration, but may be useful for screening or monitoring relative changes in a parameter. Most of the technologies use ultrasound or electromagnetic radiation as energy sources. There is an important need for further development of portable technologies that can be operated in a variety of extreme environments to monitor brain health.
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MinR 10/20 system: Quantitative and reproducible cranial landmark setting method for MRI based on minimum initial reference points. J Neurosci Methods 2016; 264:86-93. [DOI: 10.1016/j.jneumeth.2016.02.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Revised: 02/27/2016] [Accepted: 02/29/2016] [Indexed: 11/20/2022]
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Brigadoi S, Powell S, Cooper RJ, Dempsey LA, Arridge S, Everdell N, Hebden J, Gibson AP. Evaluating real-time image reconstruction in diffuse optical tomography using physiologically realistic test data. BIOMEDICAL OPTICS EXPRESS 2015; 6:4719-4737. [PMID: 26713189 PMCID: PMC4679249 DOI: 10.1364/boe.6.004719] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Revised: 11/01/2015] [Accepted: 11/03/2015] [Indexed: 05/30/2023]
Abstract
In diffuse optical tomography (DOT), real-time image reconstruction of oxy- and deoxy-haemoglobin changes occurring in the brain could give valuable information in clinical care settings. Although non-linear reconstruction techniques could provide more accurate results, their computational burden makes them unsuitable for real-time applications. Linear techniques can be employed under the assumption that the expected change in absorption is small. Several approaches exist, differing primarily in their handling of regularization and the noise statistics. In real experiments, it is impossible to compute the true noise statistics, because of the presence of physiological oscillations in the measured data. This is even more critical in real-time applications, where no off-line filtering and averaging can be performed to reduce the noise level. Therefore, many studies substitute the noise covariance matrix with the identity matrix. In this paper, we examined two questions: does using the noise model with realistic, imperfect data yield an improvement in image quality compared to using the identity matrix; and what is the difference in quality between online and offline reconstructions. Bespoke test data were created using a novel process through which simulated changes in absorption were added to real resting-state DOT data. A realistic multi-layer head model was used as the geometry for the reconstruction. Results validated our assumptions, highlighting the validity of computing the noise statistics from the measured data for online image reconstruction, which was performed at 2 Hz. Our results can be directly extended to a real application where real-time imaging is required.
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Affiliation(s)
- Sabrina Brigadoi
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
| | - Samuel Powell
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
- Department of Computer Science, University College London, London WC1E 6BT,
UK
| | - Robert J. Cooper
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
| | - Laura A. Dempsey
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
| | - Simon Arridge
- Department of Computer Science, University College London, London WC1E 6BT,
UK
| | - Nick Everdell
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
| | - Jeremy Hebden
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
| | - Adam P. Gibson
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT,
UK
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Bowman LC, Kovelman I, Hu X, Wellman HM. Children's belief- and desire-reasoning in the temporoparietal junction: evidence for specialization from functional near-infrared spectroscopy. Front Hum Neurosci 2015; 9:560. [PMID: 26500527 PMCID: PMC4595792 DOI: 10.3389/fnhum.2015.00560] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 09/22/2015] [Indexed: 11/13/2022] Open
Abstract
Behaviorally, children's explicit theory of mind (ToM) proceeds in a progression of mental-state understandings: developmentally, children demonstrate accurate explicit desire-reasoning before accurate explicit belief-reasoning. Given its robust and cross-cultural nature, we hypothesize this progression may be paced in part by maturation/specialization of the brain. Neuroimaging research demonstrates that the right temporoparietal junction (TPJ) becomes increasingly selective for ToM reasoning as children age, and as their ToM improves. But this research has narrowly focused on beliefs or on undifferentiated mental-states. A recent ERP study in children included a critical contrast to desire-reasoning, and demonstrated that right posterior potentials differentiated belief-reasoning from desire-reasoning. Taken together, the literature suggests that children's desire-belief progression may be paced by specialization of the right TPJ for belief-reasoning specifically, beyond desire-reasoning. In the present study, we tested this hypothesis directly by examining children's belief- and desire-reasoning using functional near-infrared spectroscopy in conjunction with structural magnetic resonance imaging to pinpoint brain activation in the right TPJ. Results showed greatest activation in the right TPJ for belief-reasoning, beyond desire-reasoning, and beyond non-mental reasoning (control). Findings replicate and critically extend prior ERP results, and provide clear evidence for a specific neural mechanism underlying children's progression from understanding desires to understanding beliefs.
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Affiliation(s)
- Lindsay C Bowman
- Department of Pediatrics, Harvard Medical School, Boston, MA USA ; Division of Developmental Medicine, Laboratories of Cognitive Neuroscience, Boston Children's Hospital, Boston, MA USA
| | - Ioulia Kovelman
- Department of Psychology, University of Michigan, Ann Arbor, MI USA ; Center for Human Growth and Development, University of Michigan, Ann Arbor, MI USA
| | - Xiaosu Hu
- Center for Human Growth and Development, University of Michigan, Ann Arbor, MI USA
| | - Henry M Wellman
- Department of Psychology, University of Michigan, Ann Arbor, MI USA ; Center for Human Growth and Development, University of Michigan, Ann Arbor, MI USA
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Hyde DC, Aparicio Betancourt M, Simon CE. Human temporal-parietal junction spontaneously tracks others' beliefs: A functional near-infrared spectroscopy study. Hum Brain Mapp 2015; 36:4831-46. [PMID: 26368326 DOI: 10.1002/hbm.22953] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 08/12/2015] [Accepted: 08/13/2015] [Indexed: 11/11/2022] Open
Abstract
Humans have the unique capacity to actively reflect on the thoughts, beliefs, and knowledge of others, but do we also track mental states spontaneously when observing other people? We asked this question by monitoring brain activity in belief-sensitive cortex using functional near-infrared spectroscopy (fNIRS) during free-viewing of social videos. More specifically, we identified a portion of the right temporal-parietal junction (rTPJ) selective for mental state processing using an established, explicit theory of mind task, and then analyzed the brain response in that region of interest (ROI) during free-viewing of video clips involving people producing goal-directed actions. We found a significant increase in oxygenated hemoglobin concentration in our rTPJ ROI during free-viewing for all of our test videos. Activity in this region was further modulated by the extent to which the knowledge state, or beliefs, of the protagonist regarding the location of an object contrasted with the reality of where the object was hidden. Open-ended questioning suggested our participants were not explicitly focusing on belief states of the characters during free-viewing. Further analyses ruled out lower-level details of the video clips or general attentional differences between conditions as likely explanations for the results. As such, these results call into question the traditional characterization of theory of mind as a resource intensive, deliberate process, and, instead, support an emerging view of theory of mind as a foundation for, rather than the pinnacle of, human social cognition.
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Affiliation(s)
- Daniel C Hyde
- Department of Psychology, University of Illinois Urbana-Champaign, Champaign, Illinois
| | | | - Charline E Simon
- Department of Psychology, University of Illinois Urbana-Champaign, Champaign, Illinois
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Wijeakumar S, Spencer JP, Bohache K, Boas DA, Magnotta VA. Validating a new methodology for optical probe design and image registration in fNIRS studies. Neuroimage 2015; 106:86-100. [PMID: 25705757 DOI: 10.1016/j.neuroimage.2014.11.022] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing.
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