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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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Intraoperative Optical and Fluorescence Imaging of Blood Flow Distributions in Mastectomy Skin Flaps for Identifying Ischemic Tissues. Plast Reconstr Surg 2022; 150:282-287. [PMID: 35653513 PMCID: PMC9334221 DOI: 10.1097/prs.0000000000009333] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
SUMMARY Insufficient blood flow causes mastectomy skin flap necrosis in 5 to 30 percent of cases. Fluorescence angiography with the injection of indocyanine green dye has shown high sensitivities (90 to 100 percent) but moderate specificities (72 to 50 percent) in predicting mastectomy skin flap necrosis. However, a number of challenging issues limit its wide acceptance in clinical settings, including allergic reaction, short time-window for observation, and high cost for equipment and supplies. An emerging inexpensive speckle contrast diffuse correlation tomography technology enables noninvasive, noncontact, and continuous three-dimensional imaging of blood flow distributions in deep tissues. This preliminary study tested the hypothesis that speckle contrast diffuse correlation tomography and indocyanine green-fluorescence angiography measurements of blood flow distributions in mastectomy skin flaps are consistent. Eleven female patients undergoing skin-sparing or nipple-sparing mastectomies were imaged sequentially by the dye-free speckle contrast diffuse correlation tomography and dye-based commercial fluorescence angiography (SPY-PHI). Resulting images from these two imaging modalities were co-registered based on the ischemic areas with the lowest blood flow values. Because the ischemic areas have irregular shapes, a novel contour-based algorithm was used to compare three-dimensional images of blood flow distribution and two-dimensional maps of indocyanine green perfusion. Significant correlations were observed between the two measurements in all contours from a selected area of 10 × 10 mm 2 with the lowest blood flow ( r ≥ 0.78; p < 0.004), suggesting that speckle contrast diffuse correlation tomography provides the information for identifying ischemic tissues in mastectomy skin flaps. With further optimization and validation in large populations, speckle contrast diffuse correlation tomography may ultimately be used as a noninvasive and inexpensive imaging tool for intraoperative assessment of skin flap viability to predict mastectomy skin flap necrosis. CLINICAL QUESTION/LEVEL OF EVIDENCE Diagnostic, II.
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3
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science, and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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4
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Maria A, Hirvi P, Kotilahti K, Heiskala J, Tuulari JJ, Karlsson L, Karlsson H, Nissilä I. Imaging affective and non-affective touch processing in two-year-old children. Neuroimage 2022; 251:118983. [PMID: 35149231 DOI: 10.1016/j.neuroimage.2022.118983] [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: 06/07/2021] [Revised: 12/22/2021] [Accepted: 02/07/2022] [Indexed: 10/19/2022] Open
Abstract
Touch is an important component of early parent-child interaction and plays a critical role in the socio-emotional development of children. However, there are limited studies on touch processing amongst children in the age range from one to three years. The present study used frequency-domain diffuse optical tomography (DOT) to investigate the processing of affective and non-affective touch over left frontotemporal brain areas contralateral to the stimulated forearm in two-year-old children. Affective touch was administered by a single stroke with a soft brush over the child's right dorsal forearm at 3 cm/s, while non-affective touch was provided by multiple brush strokes at 30 cm/s. We found that in the insula, the total haemoglobin (HbT) response to slow brushing was significantly greater than the response to fast brushing (slow > fast). Additionally, a region in the postcentral gyrus, Rolandic operculum and superior temporal gyrus exhibited greater response to fast brushing than slow brushing (fast > slow). These findings confirm that an adult-like pattern of haemodynamic responses to affective and non-affective touch can be recorded in two-year-old subjects using DOT. To improve the accuracy of modelling light transport in the two-year-old subjects, we used a published age-appropriate atlas and deformed it to match the exterior shape of each subject's head. We estimated the combined scalp and skull, and grey matter (GM) optical properties by fitting simulated data to calibrated and coupling error corrected phase and amplitude measurements. By utilizing a two-compartment cerebrospinal fluid (CSF) model, the accuracy of estimation of GM optical properties and the localization of activation in the insula was improved. The techniques presented in this paper can be used to study neural development of children at different ages and illustrate that the technology is well-tolerated by most two-year-old children and not excessively sensitive to subject movement. The study points the way towards exciting possibilities in functional imaging of deeper functional areas near sulci in small children.
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Affiliation(s)
- Ambika Maria
- University of Turku, Department of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study, Finland; University of Turku and Turku University Hospital, Department of Psychiatry, Finland
| | - Pauliina Hirvi
- Aalto University, Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, AALTO FI-00076, Finland; Aalto University, Department of Mathematics and Systems Analysis, Finland
| | - Kalle Kotilahti
- Aalto University, Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, AALTO FI-00076, Finland; University of Turku, Department of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study, Finland
| | - Juha Heiskala
- HUS Medical Imaging Center, Clinical Neurophysiology; Clinical Neurosciences, Helsinki, University Hospital and University of Helsinki, Helsinki, Finland
| | - Jetro J Tuulari
- University of Turku, Department of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study, Finland; University of Turku and Turku University Hospital, Department of Psychiatry, Finland; Turku Collegium for Science, Medicine and Technology, TCSMT, University of Turku, Finland
| | - Linnea Karlsson
- University of Turku, Department of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study, Finland; University of Turku and Turku University Hospital, Department of Psychiatry, Finland; University of Turku and Turku University Hospital, Department of Paediatrics and Adolescent Medicine, Finland; Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Hasse Karlsson
- University of Turku, Department of Clinical Medicine, Turku Brain and Mind Center, FinnBrain Birth Cohort Study, Finland; University of Turku and Turku University Hospital, Department of Psychiatry, Finland
| | - Ilkka Nissilä
- Aalto University, Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, AALTO FI-00076, Finland.
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5
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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: 2] [Impact Index Per Article: 0.7] [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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6
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Sherafati A, Snyder AZ, Eggebrecht AT, Bergonzi KM, Burns-Yocum TM, Lugar HM, Ferradal SL, Robichaux-Viehoever A, Smyser CD, Palanca BJ, Hershey T, Culver JP. Global motion detection and censoring in high-density diffuse optical tomography. Hum Brain Mapp 2020; 41:4093-4112. [PMID: 32648643 PMCID: PMC8022277 DOI: 10.1002/hbm.25111] [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: 02/17/2020] [Revised: 06/05/2020] [Accepted: 06/10/2020] [Indexed: 12/30/2022] Open
Abstract
Motion‐induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high‐density diffuse optical tomography (HD‐DOT) with hundreds to thousands of source‐detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near‐infrared spectroscopy (fNIRS). This limitation restricts the application of HD‐DOT in many challenging imaging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluated a new motion detection method for multi‐channel optical imaging systems that leverages spatial patterns across measurement channels. Specifically, we introduced a global variance of temporal derivatives (GVTD) metric as a motion detection index. We showed that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion—with an area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we showed that applying GVTD‐based motion censoring on both hearing words task and resting state HD‐DOT data with natural head motion results in an improved spatial similarity to fMRI mapping. We then compared the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation‐based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring on HD‐DOT data outperforms other methods and results in spatial maps more similar to those of matched fMRI data.
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Affiliation(s)
- Arefeh Sherafati
- Department of Physics, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Adam T Eggebrecht
- Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.,Department of Biomedical Engineering, Washington University School in St. Louis, St. Louis, Missouri, USA.,Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | | | - Tracy M Burns-Yocum
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Heather M Lugar
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Silvina L Ferradal
- Department Of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, USA
| | | | - Christopher D Smyser
- Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ben J Palanca
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Tamara Hershey
- Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.,Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Joseph P Culver
- Department of Physics, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Radiology, Washington University School of Medicine in St, St. Louis, Missouri, USA.,Department of Biomedical Engineering, Washington University School in St. Louis, St. Louis, Missouri, USA.,Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
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7
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White BR, Padawer-Curry JA, Cohen AS, Licht DJ, Yodh AG. Brain segmentation, spatial censoring, and averaging techniques for optical functional connectivity imaging in mice. BIOMEDICAL OPTICS EXPRESS 2019; 10:5952-5973. [PMID: 31799057 PMCID: PMC6865125 DOI: 10.1364/boe.10.005952] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 09/05/2019] [Accepted: 09/13/2019] [Indexed: 05/25/2023]
Abstract
Resting-state functional connectivity analysis using optical neuroimaging holds the potential to be a powerful bridge between mouse models of disease and clinical neurologic monitoring. However, analysis techniques specific to optical methods are rudimentary, and algorithms from magnetic resonance imaging are not always applicable to optics. We have developed visual processing tools to increase data quality, improve brain segmentation, and average across sessions with better field-of-view. We demonstrate improved performance using resting-state optical intrinsic signal from normal mice. The proposed methods increase the amount of usable data from neuroimaging studies, improve image fidelity, and should be translatable to human optical neuroimaging systems.
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Affiliation(s)
- Brian R. White
- Division of Pediatric Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia. 3401 Civic Center Blvd., Pediatric Cardiology - 8NW, Philadelphia, PA 19104, USA
| | - Jonah A. Padawer-Curry
- Division of Neurology, Department of Pediatrics, The Children’s Hospital of Philadelphia. 3501 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Akiva S. Cohen
- Department of Anesthesiology and Critical Care Medicine, The Children’s Hospital of Philadelphia. 3615 Civic Center Blvd., Abramson Research Center, Room 816-H, Philadelphia, PA 19104, USA
| | - Daniel J. Licht
- Division of Neurology, Department of Pediatrics, The Children’s Hospital of Philadelphia. 3501 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
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8
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Lu W, Duan J, Orive-Miguel D, Herve L, Styles IB. Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2019; 10:2684-2707. [PMID: 31259044 PMCID: PMC6583327 DOI: 10.1364/boe.10.002684] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 03/29/2019] [Accepted: 04/17/2019] [Indexed: 05/18/2023]
Abstract
Total variation (TV) is a powerful regularization method that has been widely applied in different imaging applications, but is difficult to apply to diffuse optical tomography (DOT) image reconstruction (inverse problem) due to unstructured discretization of complex geometries, non-linearity of the data fitting and regularization terms, and non-differentiability of the regularization term. We develop several approaches to overcome these difficulties by: i) defining discrete differential operators for TV regularization using both finite element and graph representations; ii) developing an optimization algorithm based on the alternating direction method of multipliers (ADMM) for the non-differentiable and non-linear minimization problem; iii) investigating isotropic and anisotropic variants of TV regularization, and comparing their finite element (FEM)- and graph-based implementations. These approaches are evaluated on experiments on simulated data and real data acquired from a tissue phantom. Our results show that both FEM and graph-based TV regularization is able to accurately reconstruct both sparse and non-sparse distributions without the over-smoothing effect of Tikhonov regularization and the over-sparsifying effect of L1 regularization. The graph representation was found to out-perform the FEM method for low-resolution meshes, and the FEM method was found to be more accurate for high-resolution meshes.
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Affiliation(s)
- Wenqi Lu
- School of Computer Science, University of Birmingham,
UK
| | - Jinming Duan
- School of Computer Science, University of Birmingham,
UK
| | - David Orive-Miguel
- CEA, LETI, MINATEC Campus, F-38054 Grenoble,
France
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble,
France
| | - Lionel Herve
- CEA, LETI, MINATEC Campus, F-38054 Grenoble,
France
| | - Iain B. Styles
- School of Computer Science, University of Birmingham,
UK
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9
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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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10
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Wang B, Pan T, Zhang Y, Liu D, Jiang J, Zhao H, Gao F. A Kalman-based tomographic scheme for directly reconstructing activation levels of brain function. OPTICS EXPRESS 2019; 27:3229-3246. [PMID: 30732347 DOI: 10.1364/oe.27.003229] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
In functional near-infrared spectroscopy (fNIRS), the conventional indirect approaches first separately recover the spatial distribution of the changes in the optical properties at every time point, and then extract the activation levels by a time-course analysis process at every site. In the tomographic implementation of fNIRS, i.e., diffuse optical tomography (DOT), these approaches not only suffer from the ill-posedness of the optical inversions and error propagation between the two successive steps, but also fail to achieve satisfactory temporal resolution due to the requirement for a complete data set. To cope with the above adversities of the indirect approaches, we propose herein a direct approach to tomographically reconstructing the activation levels by incorporating a Kalman scheme. Dynamic simulative and phantom experiments were conducted for the performance validation of the proposed approach, demonstrating its potentials to improve the calculated images and to relax the speed limitation of the instruments.
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11
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Bergonzi KM, Burns-Yocum TM, Bumstead JR, Buckley EM, Mannion PC, Tracy CH, Mennerick E, Ferradal SL, Dehghani H, Eggebrecht AT, Culver JP. Lightweight sCMOS-based high-density diffuse optical tomography. NEUROPHOTONICS 2018; 5:035006. [PMID: 30137925 PMCID: PMC6096280 DOI: 10.1117/1.nph.5.3.035006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2018] [Accepted: 07/25/2018] [Indexed: 05/23/2023]
Abstract
Though optical imaging of human brain function is gaining momentum, widespread adoption is restricted in part by a tradeoff among cap wearability, field of view, and resolution. To increase coverage while maintaining functional magnetic resonance imaging (fMRI)-comparable image quality, optical systems require more fibers. However, these modifications drastically reduce the wearability of the imaging cap. The primary obstacle to optimizing wearability is cap weight, which is largely determined by fiber diameter. Smaller fibers collect less light and lead to challenges in obtaining adequate signal-to-noise ratio. Here, we report on a design that leverages the exquisite sensitivity of scientific CMOS cameras to use fibers with ∼30× smaller cross-sectional area than current high-density diffuse optical tomography (HD-DOT) systems. This superpixel sCMOS DOT (SP-DOT) system uses 200-μm -diameter fibers that facilitate a lightweight, wearable cap. We developed a superpixel algorithm with pixel binning and electronic noise subtraction to provide high dynamic range ( >105 ), high frame rate ( >6 Hz ), and a low effective detectivity threshold ( ∼200 fW/Hz1/2-mm2 ), each comparable with previous HD-DOT systems. To assess system performance, we present retinotopic mapping of the visual cortex ( n=5 subjects). SP-DOT offers a practical solution to providing a wearable, large field-of-view, and high-resolution optical neuroimaging system.
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Affiliation(s)
- Karla M. Bergonzi
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
| | - Tracy M. Burns-Yocum
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Jonathan R. Bumstead
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Elise M. Buckley
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Patrick C. Mannion
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Christopher H. Tracy
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Eli Mennerick
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Silvina L. Ferradal
- Boston Children’s Hospital, Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston, Massachusetts, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Joseph P. Culver
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri, United States
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12
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Lu W, Lighter D, Styles IB. L 1-norm based nonlinear reconstruction improves quantitative accuracy of spectral diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2018; 9:1423-1444. [PMID: 29675293 PMCID: PMC5905897 DOI: 10.1364/boe.9.001423] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 12/22/2017] [Accepted: 12/22/2017] [Indexed: 05/21/2023]
Abstract
Spectrally constrained diffuse optical tomography (SCDOT) is known to improve reconstruction in diffuse optical imaging; constraining the reconstruction by coupling the optical properties across multiple wavelengths suppresses artefacts in the resulting reconstructed images. In other work, L1-norm regularization has been shown to improve certain types of image reconstruction problems as its sparsity-promoting properties render it robust against noise and enable the preservation of edges in images, but because the L1-norm is non-differentiable, it is not always simple to implement. In this work, we show how to incorporate L1 regularization into SCDOT. Three popular algorithms for L1 regularization are assessed for application in SCDOT: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM), and fast iterative shrinkage-thresholding algorithm (FISTA). We introduce an objective procedure for determining the regularization parameter in these algorithms and compare their performance in simulated experiments, and in real data acquired from a tissue phantom. Our results show that L1 regularization consistently outperforms Tikhonov regularization in this application, particularly in the presence of noise.
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Affiliation(s)
- Wenqi Lu
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
| | - Daniel Lighter
- Physical Sciences for Health Centre for Doctoral Training, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
| | - Iain B. Styles
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
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13
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Doulgerakis M, Eggebrecht AT, Wojtkiewicz S, Culver JP, Dehghani H. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-11. [PMID: 29197176 PMCID: PMC5709934 DOI: 10.1117/1.jbo.22.12.125001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 11/06/2017] [Indexed: 05/18/2023]
Abstract
Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25 s/excitation source.
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Affiliation(s)
- Matthaios Doulgerakis
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
- Address all correspondence to: Matthaios Doulgerakis, E-mail:
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | | | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
- Washington University School of Medicine, Division of Biology and Biomedical Sciences, St. Louis, Missouri, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
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14
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Dura E, Domingo J, Ayala G, Marti-Bonmati L, Goceri E. Probabilistic liver atlas construction. Biomed Eng Online 2017; 16:15. [PMID: 28086965 PMCID: PMC5237330 DOI: 10.1186/s12938-016-0305-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 12/19/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. RESULTS A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. CONCLUSION We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.
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Affiliation(s)
- Esther Dura
- Department of Informatics, School of Engineering, University of Valencia, Avda. de la Universidad, 46100, Burjasot, Spain
| | - Juan Domingo
- Department of Informatics, School of Engineering, University of Valencia, Avda. de la Universidad, 46100, Burjasot, Spain
| | - Guillermo Ayala
- Department of Statistics and Operations Research, University of Valencia, Avda. Vicent Andrés Estellés, 1, 46100, Burjasot, Spain.
| | | | - E Goceri
- Department of Computer Engineering, Akdeniz University, Antalya, Turkey
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15
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Wan W, Wang Y, Qi J, Liu L, Ma W, Li J, Zhang L, Zhou Z, Zhao H, Gao F. Region-based diffuse optical tomography with registered atlas: in vivo acquisition of mouse optical properties. BIOMEDICAL OPTICS EXPRESS 2016; 7:5066-5080. [PMID: 28018725 PMCID: PMC5175552 DOI: 10.1364/boe.7.005066] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 10/20/2016] [Accepted: 11/09/2016] [Indexed: 05/14/2023]
Abstract
The reconstruction quality in the model-based optical tomography modalities can greatly benefit from a priori information of accurate tissue optical properties, which are difficult to be obtained in vivo with a conventional diffuse optical tomography (DOT) system alone. One of the solutions is to apply a priori anatomical structures obtained with anatomical imaging systems such as X-ray computed tomography (XCT) to constrain the reconstruction process of DOT. However, since X-ray offers low soft-tissue contrast, segmentation of abdominal organs from sole XCT images can be problematic. In order to overcome the challenges, the current study proposes a novel method of recovering a priori organ-oriented tissue optical properties, where anatomical structures of an in vivo mouse are approximately obtained by registering a standard anatomical atlas, i.e., the Digimouse, to the target XCT volume with the non-rigid image registration, and, in turn, employed to guide DOT for extracting the optical properties of inner organs. Simulative investigations have validated the methodological availability of such atlas-registration-based DOT strategy in revealing both a priori anatomical structures and optical properties. Further experiments have demonstrated the feasibility of the proposed method for acquiring the organ-oriented tissue optical properties of in vivo mice, making it as an efficient way of the reconstruction enhancement.
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Affiliation(s)
- Wenbo Wan
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Yihan Wang
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Jin Qi
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Lingling Liu
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Wenjuan Ma
- Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Jiao Li
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Limin Zhang
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Zhongxing Zhou
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Huijuan Zhao
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Feng Gao
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
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16
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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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17
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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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18
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Bentz BZ, Chavan AV, Lin D, Tsai EHR, Webb KJ. Fabrication and application of heterogeneous printed mouse phantoms for whole animal optical imaging. APPLIED OPTICS 2016; 55:280-7. [PMID: 26835763 PMCID: PMC5652317 DOI: 10.1364/ao.55.000280] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
This work demonstrates the usefulness of 3D printing for optical imaging applications. Progress in developing optical imaging for biomedical applications requires customizable and often complex objects for testing and evaluation. There is therefore high demand for what have become known as tissue-simulating "phantoms." We present a new optical phantom fabricated using inexpensive 3D printing methods with multiple materials, allowing for the placement of complex inhomogeneities in complex or anatomically realistic geometries, as opposed to previous phantoms, which were limited to simple shapes formed by molds or machining. We use diffuse optical imaging to reconstruct optical parameters in 3D space within a printed mouse to show the applicability of the phantoms for developing whole animal optical imaging methods. This phantom fabrication approach is versatile, can be applied to optical imaging methods besides diffusive imaging, and can be used in the calibration of live animal imaging data.
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19
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Nouizi F, Luk A, Thayer D, Lin Y, Ha S, Gulsen G. Experimental validation of a high-resolution diffuse optical imaging modality: photomagnetic imaging. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:16009. [PMID: 26790644 PMCID: PMC4719037 DOI: 10.1117/1.jbo.21.1.016009] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 12/11/2015] [Indexed: 05/25/2023]
Abstract
We present experimental results that validate our imaging technique termed photomagnetic imaging (PMI). PMI illuminates the medium under investigation with a near-infrared light and measures the induced temperature increase using magnetic resonance imaging. A multiphysics solver combining light and heat propagation is used to model spatiotemporal distribution of temperature increase. Furthermore, a dedicated PMI reconstruction algorithm has been developed to reveal high-resolution optical absorption maps from temperature measurements. Being able to perform measurements at any point within the medium, PMI overcomes the limitations of conventional diffuse optical imaging. We present experimental results obtained on agarose phantoms mimicking biological tissue with inclusions having either different sizes or absorption contrasts, located at various depths. The reconstructed images show that PMI can successfully resolve these inclusions with high resolution and recover their absorption coefficient with high-quantitative accuracy. Even a 1-mm inclusion located 6-mm deep is recovered successfully and its absorption coefficient is underestimated by only 32%. The improved PMI system presented here successfully operates under the maximum skin exposure limits defined by the American National Standards Institute, which opens up the exciting possibility of its future clinical use for diagnostic purposes.
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Affiliation(s)
- Farouk Nouizi
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
| | - Alex Luk
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
| | - Dave Thayer
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, 510 South Kingshighway Boulevard, St. Louis, Missouri 63110, United States
| | - Yuting Lin
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, 55 Fruit Street, Boston, Massachusetts 02144, United States
| | - Seunghoon Ha
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Philips Healthcare, N27 West 23676 Paul Road, Pewaukee, Wisconsin 53072, United States
| | - Gultekin Gulsen
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
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20
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Wu X, Eggebrecht AT, Ferradal SL, Culver JP, Dehghani H. Fast and efficient image reconstruction for high density diffuse optical imaging of the human brain. BIOMEDICAL OPTICS EXPRESS 2015; 6:4567-84. [PMID: 26601019 PMCID: PMC4646563 DOI: 10.1364/boe.6.004567] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 10/14/2015] [Accepted: 10/16/2015] [Indexed: 05/18/2023]
Abstract
Real-time imaging of human brain has become an important technique within neuroimaging. In this study, a fast and efficient sensitivity map generation based on Finite Element Models (FEM) is developed which utilises a reduced sensitivitys matrix taking advantage of sparsity and parallelisation processes. Time and memory efficiency of these processes are evaluated and compared with conventional method showing that for a range of mesh densities from 50000 to 320000 nodes, the required memory is reduced over tenfold and computational time fourfold allowing for near real-time image recovery.
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Affiliation(s)
- Xue Wu
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Adam T. Eggebrecht
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St. Louis, MO, 63110, USA
| | - Silvina L. Ferradal
- Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Joseph P. Culver
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St. Louis, MO, 63110, USA
- Department of Biomedical Engineering, Washington University, One Brookings Drive, St. Louis, MO, 63130, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
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Mozumder M, Tarvainen T, Seppänen A, Nissilä I, Arridge SR, Kolehmainen V. Nonlinear approach to difference imaging in diffuse optical tomography. JOURNAL OF BIOMEDICAL OPTICS 2015; 20:105001. [PMID: 26440615 DOI: 10.1117/1.jbo.20.10.105001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 09/02/2015] [Indexed: 06/05/2023]
Abstract
Difference imaging aims at recovery of the change in the optical properties of a body based on measurements before and after the change. Conventionally, the image reconstruction is based on using difference of the measurements and a linear approximation of the observation model. One of the main benefits of the linearized difference reconstruction is that the approach has a good tolerance to modeling errors, which cancel out partially in the subtraction of the measurements. However, a drawback of the approach is that the difference images are usually only qualitative in nature and their spatial resolution can be weak because they rely on the global linearization of the nonlinear observation model. To overcome the limitations of the linear approach, we investigate a nonlinear approach for difference imaging where the images of the optical parameters before and after the change are reconstructed simultaneously based on the two datasets. We tested the feasibility of the method with simulations and experimental data from a phantom and studied how the approach tolerates modeling errors like domain truncation, optode coupling errors, and domain shape errors.
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Affiliation(s)
- Meghdoot Mozumder
- University of Eastern Finland, Department of Applied Physics, P.O. Box 1627, Kuopio 70211, Finland
| | - Tanja Tarvainen
- University of Eastern Finland, Department of Applied Physics, P.O. Box 1627, Kuopio 70211, FinlandbUniversity College London, Department of Computer Science, Gower Street, London WC1E 6BT, United Kingdom
| | - Aku Seppänen
- University of Eastern Finland, Department of Applied Physics, P.O. Box 1627, Kuopio 70211, Finland
| | - Ilkka Nissilä
- Aalto University School of Science, Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, Aalto 00076, FinlanddHelsinki University Central Hospital, HUS Medical Imaging Center, BioMag Laboratory, P.O. Box 340, HUS 00029, Finland
| | - Simon R Arridge
- University College London, Department of Computer Science, Gower Street, London WC1E 6BT, United Kingdom
| | - Ville Kolehmainen
- University of Eastern Finland, Department of Applied Physics, P.O. Box 1627, Kuopio 70211, Finland
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Wu X, Eggebrecht AT, Ferradal SL, Culver JP, Dehghani H. Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography. NEUROPHOTONICS 2015; 2:035002. [PMID: 26217675 PMCID: PMC4509792 DOI: 10.1117/1.nph.2.3.035002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2015] [Accepted: 06/18/2015] [Indexed: 05/22/2023]
Abstract
Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the "nearest point to point" registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex.
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Affiliation(s)
- Xue Wu
- University of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Department of Radiology, 4525 Scott Avenue, St. Louis, Missouri 63110, United States
| | - Silvina L. Ferradal
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, 4525 Scott Avenue, St. Louis, Missouri 63110, United States
- Washington University, Department of Biomedical Engineering, One Brookings Drive, St. Louis, Missouri 63130, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom
- Address all correspondence to: Hamid Dehghani, E-mail:
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