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Gao Y, Rogers D, von Lühmann A, Ortega-Martinez A, Boas DA, Yücel MA. Short-separation regression incorporated diffuse optical tomography image reconstruction modeling for high-density functional near-infrared spectroscopy. NEUROPHOTONICS 2023; 10:025007. [PMID: 37228904 PMCID: PMC10203730 DOI: 10.1117/1.nph.10.2.025007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 04/08/2023] [Accepted: 05/03/2023] [Indexed: 05/27/2023]
Abstract
Significance Short-separation (SS) regression and diffuse optical tomography (DOT) image reconstruction, two widely adopted methods in functional near-infrared spectroscopy (fNIRS), were demonstrated to individually facilitate the separation of brain activation and physiological signals, with further improvement using both sequentially. We hypothesized that doing both simultaneously would further improve the performance. Aim Motivated by the success of these two approaches, we propose a method, SS-DOT, which applies SS and DOT simultaneously. Approach The method, which employs spatial and temporal basis functions to represent the hemoglobin concentration changes, enables us to incorporate SS regressors into the time series DOT model. To benchmark the performance of the SS-DOT model against conventional sequential models, we use fNIRS resting state data augmented with synthetic brain response as well as data acquired during a ball squeezing task. The conventional sequential models comprise performing SS regression and DOT. Results The results show that the SS-DOT model improves the image quality by increasing the contrast-to-background ratio by a threefold improvement. The benefits are marginal at small brain activation. Conclusions The SS-DOT model improves the fNIRS image reconstruction quality.
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Affiliation(s)
- Yuanyuan Gao
- Boston University, Neurophotonics Center, Boston, Massachusetts, United States
| | - De’Ja Rogers
- Boston University, Neurophotonics Center, Boston, Massachusetts, United States
| | | | | | - David A. Boas
- Boston University, Neurophotonics Center, Boston, Massachusetts, United States
| | - Meryem Ayşe Yücel
- Boston University, Neurophotonics Center, Boston, Massachusetts, United States
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Ortega-Martinez A, Rogers D, Anderson J, Farzam P, Gao Y, Zimmermann B, Yücel MA, Boas DA. How much do time-domain functional near-infrared spectroscopy (fNIRS) moments improve estimation of brain activity over traditional fNIRS? NEUROPHOTONICS 2023; 10:013504. [PMID: 36284602 PMCID: PMC9587749 DOI: 10.1117/1.nph.10.1.013504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
SIGNIFICANCE Advances in electronics have allowed the recent development of compact, high channel count time domain functional near-infrared spectroscopy (TD-fNIRS) systems. Temporal moment analysis has been proposed for increased brain sensitivity due to the depth selectivity of higher order temporal moments. We propose a general linear model (GLM) incorporating TD moment data and auxiliary physiological measurements, such as short separation channels, to improve the recovery of the HRF. AIMS We compare the performance of previously reported multi-distance TD moment techniques to commonly used techniques for continuous wave (CW) fNIRS hemodynamic response function (HRF) recovery, namely block averaging and CW GLM. Additionally, we compare the multi-distance TD moment technique to TD moment GLM. APPROACH We augmented resting TD-fNIRS moment data (six subjects) with known synthetic HRFs. We then employed block averaging and GLM techniques with "short-separation regression" designed both for CW and TD to recover the HRFs. We calculated the root mean square error (RMSE) and the correlation of the recovered HRF to the ground truth. We compared the performance of equivalent CW and TD techniques with paired t-tests. RESULTS We found that, on average, TD moment HRF recovery improves correlations by 98% and 48% for HbO and HbR respectively, over CW GLM. The improvement on the correlation for TD GLM over TD moment is 12% (HbO) and 27% (HbR). RMSE decreases 56% and 52% (HbO and HbR) for TD moment compared to CW GLM. We found no statistically significant improvement in the RMSE for TD GLM compared to TD moment. CONCLUSIONS Properly covariance-scaled TD moment techniques outperform their CW equivalents in both RMSE and correlation in the recovery of the synthetic HRFs. Furthermore, our proposed TD GLM based on moments outperforms regular TD moment analysis, while allowing the incorporation of auxiliary measurements of the confounding physiological signals from the scalp.
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Affiliation(s)
| | - De’Ja Rogers
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - Jessica Anderson
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - Parya Farzam
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - Yuanyuan Gao
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - Bernhard Zimmermann
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
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Chen Y, Cao Z, Mao M, Sun W, Song Q, Mao D. Increased cortical activation and enhanced functional connectivity in the prefrontal cortex ensure dynamic postural balance during dual-task obstacle negotiation in the older adults: A fNIRS study. Brain Cogn 2022; 163:105904. [PMID: 36063567 DOI: 10.1016/j.bandc.2022.105904] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 08/15/2022] [Accepted: 08/22/2022] [Indexed: 01/12/2023]
Abstract
OBJECTIVE By analyzing the cortical activation and functional connectivity of the prefrontal cortex (PFC) during dual-task obstacle negotiation in the older adults, cognitive resources allocation and neural regulatory mechanisms of aging brain were shed light on in complex walking conditions. METHODS Twenty-eight healthy right-handed subjects participated in the study, including 15 men and 13 women (age: 68.6 ± 4.1 years, height: 162.96 ± 6.05 cm, weight: 63.63 ± 9.64 kg). There were four tasks: Normal Walk (NW), Obstacle Negotiation during Normal Walk (NW + ON), Walk while performing Cognitive Task (WCT), and Obstacle Negotiation during Walk while performing Cognitive Task (WCT + ON). Participants wore functional near-infrared spectroscopy (fNIRS) to collect hemodynamic signals from various regions of interest (ROIs) in the PFC, while the three-dimensional motion capture system was used to test the gait velocity. Cognitive task data was recorded. RESULTS In WCT + ON, the HbO2 concentration change value (△HbO2) of the left dorsolateral prefrontal cortex was significantly greater than that in the other three tasks (p < 0.05), and the△HbO2 of the right dorsolateral prefrontal cortex was significantly greater than that in NW + ON (p < 0.05). The gait velocities in the four tasks were significantly different (p < 0.05) (NW > WCT > NW + ON > WCT + ON). There was no significant difference in cognitive performance between in the WCT and WCT + ON (p > 0.05). In WCT + ON, the left and right dorsolateral prefrontal areas had strong functional connectivity and the left frontal pole was most widely connected to the other ROIs. Compared to that in NW, the functional connectivity of the left prefrontal lobe was significantly enhanced in WCT + ON (p < 0.05). CONCLUSIONS As walking difficulty increased, the PFC activation in the older adults changed from right-sided to bilateral activation, indicating that the left PFC cognitive resources compensated for the right PFC in dual-task obstacle negotiation. The cognitive resources recruitment in dual-task obstacle negotiation might be achieved by synchronization and coordination of associated brain areas in the PFC, primarily to maintain dynamic postural balance when walking.
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Affiliation(s)
- Yan Chen
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China; College of Sport and Health, Shandong Sport University, Jinan, Shandong 250102, China.
| | - Zhenjing Cao
- College of Sport and Health, Shandong Sport University, Jinan, Shandong 250102, China
| | - Min Mao
- School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China
| | - Wei Sun
- College of Sport and Health, Shandong Sport University, Jinan, Shandong 250102, China
| | - Qipeng Song
- College of Sport and Health, Shandong Sport University, Jinan, Shandong 250102, China
| | - Dewei Mao
- School of Kinesiology, Shanghai University of Sport, Shanghai 200438, China; College of Sport and Health, Shandong Sport University, Jinan, Shandong 250102, China.
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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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Wyser D, Mattille M, Wolf M, Lambercy O, Scholkmann F, Gassert R. Short-channel regression in functional near-infrared spectroscopy is more effective when considering heterogeneous scalp hemodynamics. NEUROPHOTONICS 2020; 7:035011. [PMID: 33029548 PMCID: PMC7523733 DOI: 10.1117/1.nph.7.3.035011] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 09/04/2020] [Indexed: 05/20/2023]
Abstract
Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing systemic "noise" by subtracting the signal measured at a short source-detector separation (mainly scalp hemodynamics) from the one of a long separation (brain and scalp hemodynamics). In literature, incongruent approaches on the selection of the optimal regressor signal are reported based on different assumptions on scalp hemodynamics properties. Aim: We investigated the spatial and temporal distribution of scalp hemodynamics over the sensorimotor cortex and evaluated its influence on the effectiveness of short-channel regressions. Approach: We performed hand-grasping and resting-state experiments with five subjects, measuring with 16 optodes over sensorimotor areas, including eight 8-mm channels. We performed detailed correlation analyses of scalp hemodynamics and evaluated 180 hand-grasping and 270 simulated (overlaid on resting-state measurements) trials. Five short-channel regressor combinations were implemented with general linear models. Three were chosen according to literature, and two were proposed based on additional physiological assumptions [considering multiple short channels and their Mayer wave (MW) oscillations]. Results: We found heterogeneous hemodynamics in the scalp, coming on top of a global close-to-homogeneous behavior (correlation 0.69 to 0.92). The results further demonstrate that short-channel regression always improves brain activity estimates but that better results are obtained when heterogeneity is assumed. In particular, we highlight that short-channel regression is more effective when combining multiple scalp regressors and when MWs are additionally included. Conclusion: We shed light on the selection of optimal regressor signals for improving the removal of systemic physiological artifacts in fNIRS. We conclude that short-channel regression is most effective when assuming heterogeneous hemodynamics, in particular when combining spatial- and frequency-specific information. A better understanding of scalp hemodynamics and more effective short-channel regression will promote more accurate assessments of functional brain activity in clinical and research settings.
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Affiliation(s)
- Dominik Wyser
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Michelle Mattille
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
| | - Martin Wolf
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Olivier Lambercy
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
| | - Felix Scholkmann
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Roger Gassert
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
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6
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Nguyen T, Kim M, Gwak J, Lee JJ, Choi KY, Lee KH, Kim JG. Investigation of brain functional connectivity in patients with mild cognitive impairment: A functional near-infrared spectroscopy (fNIRS) study. JOURNAL OF BIOPHOTONICS 2019; 12:e201800298. [PMID: 30963713 DOI: 10.1002/jbio.201800298] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 03/17/2019] [Accepted: 04/04/2019] [Indexed: 06/09/2023]
Abstract
This study examines brain functional connectivity in both cognitively normal seniors and patients with mild cognitive impairment (MCI) to elucidate prospective markers of MCI. A homemade four-channel functional near-infrared spectroscopy (fNIRS) system was employed to measure hemodynamic responses in the subjects' prefrontal cortex during a resting state, an oddball task, a 1-back task, and a verbal fluency task. Brain functional connectivity was calculated as the Pearson correlation coefficients between fNIRS channels. The results show that during the verbal fluency task, while the healthy control (HC) group presents a significantly stronger inter-hemispheric connectivity compared to intra-hemispheric connectivity, there is no difference between the inter- and intra-hemispheric connectivity in the MCI group. In addition, a comparison between the MCI and HC connectivity reveals that the MCI group has a statistically higher right and inter-hemispheric connectivity during the resting state, but a significantly lower left and inter-hemispheric connectivity during the verbal fluency test. These findings demonstrate the potential of fNIRS to study brain functional connectivity in neurodegenerative diseases.
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Affiliation(s)
- Thien Nguyen
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Minhee Kim
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Jeonghwan Gwak
- Department of Software, Korea National University of Transportation, Chungju, Republic of Korea
| | - Jang J Lee
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Kyu Y Choi
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Kun H Lee
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
- National Research Center for Dementia, Chosun University, Gwangju, Republic of Korea
| | - Jae G Kim
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
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7
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Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650-900 nm) to measure changes in cerebral blood volume and oxygenation. Over the last several decades, this technique has been utilized in a growing number of functional and resting-state brain studies. The lower operation cost, portability, and versatility of this method make it an alternative to methods such as functional magnetic resonance imaging for studies in pediatric and special populations and for studies without the confining limitations of a supine and motionless acquisition setup. However, the analysis of fNIRS data poses several challenges stemming from the unique physics of the technique, the unique statistical properties of data, and the growing diversity of non-traditional experimental designs being utilized in studies due to the flexibility of this technology. For these reasons, specific analysis methods for this technology must be developed. In this paper, we introduce the NIRS Brain AnalyzIR toolbox as an open-source Matlab-based analysis package for fNIRS data management, pre-processing, and first- and second-level (i.e., single subject and group-level) statistical analysis. Here, we describe the basic architectural format of this toolbox, which is based on the object-oriented programming paradigm. We also detail the algorithms for several of the major components of the toolbox including statistical analysis, probe registration, image reconstruction, and region-of-interest based statistics.
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Affiliation(s)
- Hendrik Santosa
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA
| | - Xuetong Zhai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA
| | - Frank Fishburn
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA
| | - Theodore Huppert
- Departments of Radiology and Bioengineering, University of Pittsburgh, Clinical Science Translational Institute, and Center for the Neural Basis of Cognition, Pittsburgh, PA 15213-2536, USA
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Kontos AP, Huppert TJ, Beluk NH, Elbin RJ, Henry LC, French J, Dakan SM, Collins MW. Brain activation during neurocognitive testing using functional near-infrared spectroscopy in patients following concussion compared to healthy controls. Brain Imaging Behav 2015; 8:621-34. [PMID: 24477579 DOI: 10.1007/s11682-014-9289-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
There is no accepted clinical imaging modality for concussion, and current imaging modalities including fMRI, DTI, and PET are expensive and inaccessible to most clinics/patients. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, portable, and low-cost imaging modality that can measure brain activity. The purpose of this study was to compare brain activity as measured by fNIRS in concussed and age-matched controls during the performance of cognitive tasks from a computerized neurocognitive test battery. Participants included nine currently symptomatic patients aged 18-45 years with a recent (15-45 days) sport-related concussion and five age-matched healthy controls. The participants completed a computerized neurocognitive test battery while wearing the fNIRS unit. Our results demonstrated reduced brain activation in the concussed subject group during word memory, (spatial) design memory, digit-symbol substitution (symbol match), and working memory (X's and O's) tasks. Behavioral performance (percent-correct and reaction time respectively) was lower for concussed participants on the word memory, design memory, and symbol match tasks than controls. The results of this preliminary study suggest that fNIRS could be a useful, portable assessment tool to assess reduced brain activation and augment current approaches to assessment and management of patients following concussion.
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Affiliation(s)
- A P Kontos
- UPMC Sports Medicine Concussion Program/Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA,
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Validation of the hypercapnic calibrated fMRI method using DOT-fMRI fusion imaging. Neuroimage 2014; 102 Pt 2:729-35. [PMID: 25196509 DOI: 10.1016/j.neuroimage.2014.08.052] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Revised: 08/26/2014] [Accepted: 08/29/2014] [Indexed: 11/22/2022] Open
Abstract
Calibrated functional magnetic resonance imaging (fMRI) is a widely used method to investigate brain function in terms of physiological quantities such as the cerebral metabolic rate of oxygen (CMRO2). The first and one of the most common methods of fMRI calibration is hypercapnic calibration. This is achieved via simultaneous measures of the blood-oxygenation-level dependent (BOLD) and the arterial spin labeling (ASL) signals during a functional task that evokes regional changes in CMRO2. A subsequent acquisition is then required during which the subject inhales carbon dioxide for short periods of time. A calibration constant, typically labeled M, is then estimated from the hypercapnic data and is subsequently used together with the BOLD-ASL recordings to compute evoked changes in CMRO2 during the functional task. The computation of M assumes a constant CMRO2 during the CO2 inhalation, an assumption that has been questioned since the origin of calibrated fMRI. In this study we used diffuse optical tomography (DOT) together with BOLD and ASL--an alternative calibration method that does not require any gas manipulation and therefore no constant CMRO2 assumption--to cross-validate the estimation of M obtained from a traditional hypercapnic calibration. We found a high correlation between the M values (R=0.87, p<0.01) estimated using these two approaches. The findings serve to validate the hypercapnic fMRI calibration technique and suggest that the inter-subject variability routinely obtained for M is reproducible with an alternative method and might therefore reflect inter-subject physiological variability.
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Karmiloff-Smith A, Casey BJ, Massand E, Tomalski P, Thomas MSC. Environmental and Genetic Influences on Neurocognitive Development: The Importance of Multiple Methodologies and Time-Dependent Intervention. Clin Psychol Sci 2014; 2:628-637. [PMID: 26682092 DOI: 10.1177/2167702614521188] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Genetic mutations and environmental factors dynamically influence gene expression and developmental trajectories at the neural, cognitive, and behavioral levels. The examples in this article cover different periods of neurocognitive development-early childhood, adolescence, and adulthood-and focus on studies in which researchers have used a variety of methodologies to illustrate the early effects of socioeconomic status and stress on brain function, as well as how allelic differences explain why some individuals respond to intervention and others do not. These studies highlight how similar behaviors can be driven by different underlying neural processes and show how a neurocomputational model of early development can account for neurodevelopmental syndromes, such as autism spectrum disorders, with novel implications for intervention. Finally, these studies illustrate the importance of the timing of environmental and genetic factors on development, consistent with our view that phenotypes are emergent, not predetermined.
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Affiliation(s)
| | - B J Casey
- Sackler Institute, Weill Cornell Medical College
| | - Esha Massand
- Centre for Brain and Cognitive Development, Birkbeck, University of London
| | | | - Michael S C Thomas
- Centre for Brain and Cognitive Development, Birkbeck, University of London
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11
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Yücel MA, Huppert TJ, Boas DA, Gagnon L. Calibrating the BOLD signal during a motor task using an extended fusion model incorporating DOT, BOLD and ASL data. Neuroimage 2012; 61:1268-76. [PMID: 22546318 PMCID: PMC3376222 DOI: 10.1016/j.neuroimage.2012.04.036] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2011] [Revised: 04/12/2012] [Accepted: 04/16/2012] [Indexed: 12/01/2022] Open
Abstract
Multimodal imaging improves the accuracy of the localization and the quantification of brain activation when measuring different manifestations of the hemodynamic response associated with cerebral activity. In this study, we incorporated cerebral blood flow (CBF) changes measured with arterial spin labeling (ASL), Diffuse Optical Tomography (DOT) and blood oxygen level-dependent (BOLD) recordings to reconstruct changes in oxy- (ΔHbO(2)) and deoxyhemoglobin (ΔHbR). Using the Grubb relation between relative changes in CBF and cerebral blood volume (CBV), we incorporated the ASL measurement as a prior to the total hemoglobin concentration change (ΔHbT). We applied this ASL fusion model to both synthetic data and experimental multimodal recordings during a 2-s finger-tapping task. Our results show that the new approach is very powerful in estimating ΔHbO(2) and ΔHbR with high spatial and quantitative accuracy. Moreover, our approach allows the computation of baseline total hemoglobin concentration (HbT(0)) as well as of the BOLD calibration factor M on a single subject basis. We obtained an average HbT(0) of 71 μM, an average M value of 0.18 and an average increase of 13% in cerebral metabolic rate of oxygen (CMRO(2)), all of which are in agreement with values previously reported in the literature. Our method yields an independent measurement of M, which provides an alternative measurement to validate the hypercapnic calibration of the BOLD signal.
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Affiliation(s)
- Meryem A Yücel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
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12
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Price JC. Molecular brain imaging in the multimodality era. J Cereb Blood Flow Metab 2012; 32:1377-92. [PMID: 22434068 PMCID: PMC3390805 DOI: 10.1038/jcbfm.2012.29] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Revised: 02/06/2012] [Accepted: 02/07/2012] [Indexed: 11/08/2022]
Abstract
Multimodality molecular brain imaging encompasses in vivo visualization, evaluation, and measurement of cellular/molecular processes. Instrumentation and software developments over the past 30 years have fueled advancements in multimodality imaging platforms that enable acquisition of multiple complementary imaging outcomes by either combined sequential or simultaneous acquisition. This article provides a general overview of multimodality neuroimaging in the context of positron emission tomography as a molecular imaging tool and magnetic resonance imaging as a structural and functional imaging tool. Several image examples are provided and general challenges are discussed to exemplify complementary features of the modalities, as well as important strengths and weaknesses of combined assessments. Alzheimer's disease is highlighted, as this clinical area has been strongly impacted by multimodality neuroimaging findings that have improved understanding of the natural history of disease progression, early disease detection, and informed therapy evaluation.
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Affiliation(s)
- Julie C Price
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
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13
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Beauchamp MS, Beurlot MR, Fava E, Nath AR, Parikh NA, Saad ZS, Bortfeld H, Oghalai JS. The developmental trajectory of brain-scalp distance from birth through childhood: implications for functional neuroimaging. PLoS One 2011; 6:e24981. [PMID: 21957470 PMCID: PMC3177859 DOI: 10.1371/journal.pone.0024981] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2011] [Accepted: 08/23/2011] [Indexed: 01/27/2023] Open
Abstract
Measurements of human brain function in children are of increasing interest in cognitive neuroscience. Many techniques for brain mapping used in children, including functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS), use probes placed on or near the scalp. The distance between the scalp and the brain is a key variable for these techniques because optical, electrical and magnetic signals are attenuated by distance. However, little is known about how scalp-brain distance differs between different cortical regions in children or how it changes with development. We investigated scalp-brain distance in 71 children, from newborn to age 12 years, using structural T1-weighted MRI scans of the whole head. Three-dimensional reconstructions were created from the scalp surface to allow for accurate calculation of brain-scalp distance. Nine brain landmarks in different cortical regions were manually selected in each subject based on the published fNIRS literature. Significant effects were found for age, cortical region and hemisphere. Brain-scalp distances were lowest in young children, and increased with age to up to double the newborn distance. There were also dramatic differences between brain regions, with up to 50% differences between landmarks. In frontal and temporal regions, scalp-brain distances were significantly greater in the right hemisphere than in the left hemisphere. The largest contributors to developmental changes in brain-scalp distance were increases in the corticospinal fluid (CSF) and inner table of the cranium. These results have important implications for functional imaging studies of children: age and brain-region related differences in fNIRS signals could be due to the confounding factor of brain-scalp distance and not true differences in brain activity.
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Affiliation(s)
- Michael S Beauchamp
- Department of Neurobiology and Anatomy, University of Texas Health Science Center, Houston, Texas, United States of America.
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14
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Fluorescence molecular tomography: principles and potential for pharmaceutical research. Pharmaceutics 2011; 3:229-74. [PMID: 24310495 PMCID: PMC3864234 DOI: 10.3390/pharmaceutics3020229] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2011] [Revised: 04/07/2011] [Accepted: 04/15/2011] [Indexed: 11/17/2022] Open
Abstract
Fluorescence microscopic imaging is widely used in biomedical research to study molecular and cellular processes in cell culture or tissue samples. This is motivated by the high inherent sensitivity of fluorescence techniques, the spatial resolution that compares favorably with cellular dimensions, the stability of the fluorescent labels used and the sophisticated labeling strategies that have been developed for selectively labeling target molecules. More recently, two and three-dimensional optical imaging methods have also been applied to monitor biological processes in intact biological organisms such as animals or even humans. These whole body optical imaging approaches have to cope with the fact that biological tissue is a highly scattering and absorbing medium. As a consequence, light propagation in tissue is well described by a diffusion approximation and accurate reconstruction of spatial information is demanding. While in vivo optical imaging is a highly sensitive method, the signal is strongly surface weighted, i.e., the signal detected from the same light source will become weaker the deeper it is embedded in tissue, and strongly depends on the optical properties of the surrounding tissue. Derivation of quantitative information, therefore, requires tomographic techniques such as fluorescence molecular tomography (FMT), which maps the three-dimensional distribution of a fluorescent probe or protein concentration. The combination of FMT with a structural imaging method such as X-ray computed tomography (CT) or Magnetic Resonance Imaging (MRI) will allow mapping molecular information on a high definition anatomical reference and enable the use of prior information on tissue's optical properties to enhance both resolution and sensitivity. Today many of the fluorescent assays originally developed for studies in cellular systems have been successfully translated for experimental studies in animals. The opportunity of monitoring molecular processes non-invasively in the intact organism is highly attractive from a diagnostic point of view but even more so for the drug developer, who can use the techniques for proof-of-mechanism and proof-of-efficacy studies. This review shall elucidate the current status and potential of fluorescence tomography including recent advances in multimodality imaging approaches for preclinical and clinical drug development.
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15
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Gagnon L, Perdue K, Greve DN, Goldenholz D, Kaskhedikar G, Boas DA. Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling. Neuroimage 2011; 56:1362-71. [PMID: 21385616 DOI: 10.1016/j.neuroimage.2011.03.001] [Citation(s) in RCA: 183] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2010] [Revised: 02/19/2011] [Accepted: 03/01/2011] [Indexed: 11/28/2022] Open
Abstract
Diffuse optical imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R(2) coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p<0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique.
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Affiliation(s)
- Louis Gagnon
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
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16
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Abstract
Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp.
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Affiliation(s)
- Xu Cui
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA 94305, USA.
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17
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Abdelnour F, Huppert T. A random-effects model for group-level analysis of diffuse optical brain imaging. BIOMEDICAL OPTICS EXPRESS 2010; 2:1-25. [PMID: 21326631 PMCID: PMC3028484 DOI: 10.1364/boe.2.000001] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2010] [Revised: 11/01/2010] [Accepted: 11/02/2010] [Indexed: 05/14/2023]
Abstract
Diffuse optical imaging is a non-invasive technique for measuring changes in blood oxygenation in the brain. This technique is based on the temporally and spatially resolved recording of optical absorption in tissue within the near-infrared range of light. Optical imaging can be used to study functional brain activity similar to functional MRI. However, group level comparisons of brain activity from diffuse optical data are difficult due to registration of optical sensors between subjects. In addition, optical signals are sensitive to inter-subject differences in cranial anatomy and the specific arrangement of optical sensors relative to the underlying functional region. These factors can give rise to partial volume errors and loss of sensitivity and therefore must be accounted for in combining data from multiple subjects. In this work, we describe an image reconstruction approach using a parametric Bayesian model that simultaneously reconstructs group-level images of brain activity in the context of a random-effects analysis. Using this model, we demonstrate that localization accuracy and the statistical effects size of group-level reconstructions can be improved when compared to individualized reconstructions. In this model, we use the Restricted Maximum Likelihood (ReML) method to optimize a Bayesian random-effects model.
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Affiliation(s)
- Farras Abdelnour
- Department of Radiology, University of Pittsburgh, 200 Lothrop St. Pittsburgh PA 15213, USA
| | - Theodore Huppert
- Department of Radiology, University of Pittsburgh, 200 Lothrop St. Pittsburgh PA 15213, USA
- Department of Bioengineering University of Pittsburgh, 300 Technology Dr. Pittsburgh PA 15219, USA
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18
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Cui X, Bray S, Bryant DM, Glover GH, Reiss AL. A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. Neuroimage 2010; 54:2808-21. [PMID: 21047559 DOI: 10.1016/j.neuroimage.2010.10.069] [Citation(s) in RCA: 549] [Impact Index Per Article: 39.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2010] [Revised: 10/21/2010] [Accepted: 10/23/2010] [Indexed: 11/18/2022] Open
Abstract
Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp.
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Affiliation(s)
- Xu Cui
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA 94305, USA.
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19
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Klose CD, Klose AD, Netz UJ, Scheel AK, Beuthan J, Hielscher AH. Computer-aided interpretation approach for optical tomographic images. JOURNAL OF BIOMEDICAL OPTICS 2010; 15:066020. [PMID: 21198194 PMCID: PMC3017575 DOI: 10.1117/1.3516705] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
A computer-aided interpretation approach is proposed to detect rheumatic arthritis (RA) in human finger joints using optical tomographic images. The image interpretation method employs a classification algorithm that makes use of a so-called self-organizing mapping scheme to classify fingers as either affected or unaffected by RA. Unlike in previous studies, this allows for combining multiple image features, such as minimum and maximum values of the absorption coefficient for identifying affected and not affected joints. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index, and mutual information. Different methods (i.e., clinical diagnostics, ultrasound imaging, magnet resonance imaging, and inspection of optical tomographic images), were used to produce ground truth benchmarks to determine the performance of image interpretations. Using data from 100 finger joints, findings suggest that some parameter combinations lead to higher sensitivities, while others to higher specificities when compared to single parameter classifications employed in previous studies. Maximum performances are reached when combining the minimum/maximum ratio of the absorption coefficient and image variance. In this case, sensitivities and specificities over 0.9 can be achieved. These values are much higher than values obtained when only single parameter classifications were used, where sensitivities and specificities remained well below 0.8.
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Affiliation(s)
- Christian D Klose
- Columbia University, Department of Biomedical Engineering, New York, NY 10027, USA
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20
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Abdelnour F, Genovese C, Huppert T. Hierarchical Bayesian regularization of reconstructions for diffuse optical tomography using multiple priors. BIOMEDICAL OPTICS EXPRESS 2010; 1:1084-1103. [PMID: 21258532 PMCID: PMC3018091 DOI: 10.1364/boe.1.001084] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2010] [Revised: 10/02/2010] [Accepted: 10/02/2010] [Indexed: 05/03/2023]
Abstract
Diffuse optical tomography (DOT) is a non-invasive brain imaging technique that uses low-levels of near-infrared light to measure optical absorption changes due to regional blood flow and blood oxygen saturation in the brain. By arranging light sources and detectors in a grid over the surface of the scalp, DOT studies attempt to spatially localize changes in oxy- and deoxy-hemoglobin in the brain that result from evoked brain activity during functional experiments. However, the reconstruction of accurate spatial images of hemoglobin changes from DOT data is an ill-posed linearized inverse problem, which requires model regularization to yield appropriate solutions. In this work, we describe and demonstrate the application of a parametric restricted maximum likelihood method (ReML) to incorporate multiple statistical priors into the recovery of optical images. This work is based on similar methods that have been applied to the inverse problem for magnetoencephalography (MEG). Herein, we discuss the adaptation of this model to DOT and demonstrate that this approach provides a means to objectively incorporate reconstruction constraints and demonstrate this approach through a series of simulated numerical examples.
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Affiliation(s)
- Farras Abdelnour
- Department of Radiology, University of Pittsburgh, 200 Lothrop St. Pittsburgh PA 15213, USA
| | - Christopher Genovese
- Department of Statistics, Carnegie Mellon University, 5000 Forbes Ave. Pittsburgh PA 15213, USA
| | - Theodore Huppert
- Department of Radiology, University of Pittsburgh, 200 Lothrop St. Pittsburgh PA 15213, USA
- Department of Bioengineering University of Pittsburgh, 300 Technology Dr. Pittsburgh PA 15219, USA
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21
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Mesquita RC, Franceschini MA, Boas DA. Resting state functional connectivity of the whole head with near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2010; 1:324-336. [PMID: 21258470 PMCID: PMC3005169 DOI: 10.1364/boe.1.000324] [Citation(s) in RCA: 94] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2010] [Revised: 06/24/2010] [Accepted: 07/27/2010] [Indexed: 05/18/2023]
Abstract
Resting state connectivity aims to identify spontaneous cerebral hemodynamic fluctuations that reflect neuronal activity at rest. In this study, we investigated the spatial-temporal correlation of hemoglobin concentration signals over the whole head during the resting state. By choosing a source-detector pair as a seed, we calculated the correlation value between its time course and the time course of all other source-detector combinations, and projected them onto a topographic map. In all subjects, we found robust spatial interactions in agreement with previous fMRI and NIRS findings. Strong correlations between the two opposite hemispheres were seen for both sensorimotor and visual cortices. Correlations in the prefrontal cortex were more heterogeneous and dependent on the hemodynamic contrast. HbT provided robust, well defined maps, suggesting that this contrast may be used to better localize functional connectivity. The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results. These results confirm the feasibility of using functional connectivity with optical methods during the resting state, and validate its use to investigate cortical interactions across the whole head.
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Affiliation(s)
- Rickson C. Mesquita
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital,
Charlestown, MA 02129, USA
- Department of Physics & Astronomy, University of Pennsylvania, 209 South 33rd St., Philadelphia, PA 19104, USA
| | - Maria A. Franceschini
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital,
Charlestown, MA 02129, USA
| | - David A. Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital,
Charlestown, MA 02129, USA
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22
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Karmiloff-Smith A. Neuroimaging of the developing brain: taking "developing" seriously. Hum Brain Mapp 2010; 31:934-41. [PMID: 20496384 PMCID: PMC6870631 DOI: 10.1002/hbm.21074] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2010] [Accepted: 03/16/2010] [Indexed: 11/06/2022] Open
Abstract
With a few notable exceptions, many studies, be they behavioral, neuroimaging, or genetic, are snapshots that compare one child group to one adult group, which capture only two points in time and tell the scientist nothing about the mechanisms underlying neural trajectories over developmental time. Thus, a distinction needs to be drawn between child neuroimaging and developmental neuroimaging, the latter approach being relevant not just to children, but to adults and the ageing brain.
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Affiliation(s)
- Annette Karmiloff-Smith
- Birkbeck Centre for Brain and Cognitive Development, University of London, London, United Kingdom.
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23
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White BR, Culver JP. Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance. JOURNAL OF BIOMEDICAL OPTICS 2010; 15:026006. [PMID: 20459251 PMCID: PMC2874047 DOI: 10.1117/1.3368999] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2009] [Revised: 01/15/2010] [Accepted: 01/20/2010] [Indexed: 05/18/2023]
Abstract
Despite the unique brain imaging capabilities and advantages of functional near-infrared spectroscopy (fNIRS), including portability and comprehensive hemodynamic measurement, widespread acceptance in the neuroimaging community has been hampered by low spatial resolution and image localization errors. While recent technical developments such as high-density diffuse optical tomography (HD-DOT) have, in principle, been shown to have superior in silico image quality, the majority of optical imaging studies are still conducted with sparse fNIRS arrays, perhaps partially because the performance increases of HD-DOT appear incremental. Without a quantitative comparative analysis between HD-DOT and fNIRS, using both simulation and in vivo neuroimaging, the implications of the new HD-DOT technology have been difficult to judge. We present a quantitative comparison of HD-DOT and two commonly used fNIRS geometries using (1) standard metrics of image quality, (2) simulated brain mapping tasks, and (3) in vivo visual cortex mapping results in adult humans. The results show that better resolution and lower positional errors are achieved with HD-DOT and that these improvements provide a substantial advancement in neuroimaging capability. In particular, we demonstrate that HD-DOT enables detailed phase-encoded retinotopic mapping, while sparse arrays are limited to imaging individual block-design visual stimuli.
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Affiliation(s)
- Brian R White
- Washington University School of Medicine, Department of Radiology and Department of Physics, St. Louis, Missouri 63110, USA
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24
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Lloyd-Fox S, Blasi A, Elwell C. Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy. Neurosci Biobehav Rev 2010; 34:269-84. [DOI: 10.1016/j.neubiorev.2009.07.008] [Citation(s) in RCA: 586] [Impact Index Per Article: 41.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2009] [Revised: 07/15/2009] [Accepted: 07/16/2009] [Indexed: 11/24/2022]
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25
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Abdelnour F, Schmidt B, Huppert TJ. Topographic localization of brain activation in diffuse optical imaging using spherical wavelets. Phys Med Biol 2009; 54:6383-413. [PMID: 19809125 PMCID: PMC2806654 DOI: 10.1088/0031-9155/54/20/023] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Diffuse optical imaging is a non-invasive technique that uses near-infrared light to measure changes in brain activity through an array of sensors placed on the surface of the head. Compared to functional MRI, optical imaging has the advantage of being portable while offering the ability to record functional changes in both oxy- and deoxy-hemoglobin within the brain at a high temporal resolution. However, the reconstruction of accurate spatial images of brain activity from optical measurements represents an ill-posed and underdetermined problem that requires regularization. These reconstructions benefit from incorporating prior information about the underlying spatial structure and function of the brain. In this work, we describe a novel image reconstruction approach which uses surface-based wavelets derived from structural MRI to incorporate high-resolution anatomical and structural prior information about the brain. This surface-based approach is used to approximate brain activation patterns through the reconstruction and presentation of topographical (two-dimensional) maps of brain activation directly onto the folded surface of the cortex. The set of wavelet coefficients is directly estimated by a truncated singular-value decomposition based pseudo-inversion of the wavelet projection of the optical forward model. We use a reconstruction metric based on Shannon entropy which quantifies the sparse loading of the wavelet coefficients and is used to determine the optimal truncation and regularization of this inverse model. In this work, examples of the performance of this model are illustrated for several cases of numerical simulation and experimental data with comparison to functional magnetic resonance imaging.
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Affiliation(s)
- F Abdelnour
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
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26
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Huppert TJ, Diamond SG, Franceschini MA, Boas DA. HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain. APPLIED OPTICS 2009; 48:D280-98. [PMID: 19340120 PMCID: PMC2761652 DOI: 10.1364/ao.48.00d280] [Citation(s) in RCA: 914] [Impact Index Per Article: 60.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data.
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Affiliation(s)
- Theodore J Huppert
- Departments of Radiology and Bioengineering, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania 15213, USA.
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