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Hong J, Zhu W, He K, Chen X, Lu J, Li P. Ergodic speckle contrast optical coherence tomography velocimetry of rapid blood flow. OPTICS LETTERS 2024; 49:3600-3603. [PMID: 38950219 DOI: 10.1364/ol.523063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 05/27/2024] [Indexed: 07/03/2024]
Abstract
Visualizing a 3D blood flow velocity field through noninvasive imaging is crucial for analyzing hemodynamic mechanisms in areas prone to disorders. However, traditional correlation-based optical coherence tomography (OCT) velocimetry techniques have a maximum measurable flow velocity depending on the A-line rate. We presented the ergodic speckle contrast OCT (ESCOCT) to break the bottleneck in measuring the rapid blood flow velocity. It achieved a measurement of blood flow velocity ranging from 9.5 to 280 mm/s using a 100 kHz swept-source (SS) OCT based on 100 A-repeats scanning mode. Addressing the non-ergodic problem of temporal OCT signals by integrating more consecutive A-scans, ESCOCT can enable the estimation for lower velocity flows by increasing A-repeats. ESCOCT provided a wide dynamic range with no upper limit on measuring blood flow velocity with an adequate signal-to-noise ratio and improved the sensitivity and accuracy of the hemodynamic assessment.
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Benson EJ, Aronowitz DI, Forti RM, Lafontant A, Ranieri NR, Starr JP, Melchior RW, Lewis A, Jahnavi J, Breimann J, Yun B, Laurent GH, Lynch JM, White BR, Gaynor JW, Licht DJ, Yodh AG, Kilbaugh TJ, Mavroudis CD, Baker WB, Ko TS. Diffuse Optical Monitoring of Cerebral Hemodynamics and Oxygen Metabolism during and after Cardiopulmonary Bypass: Hematocrit Correction and Neurological Vulnerability. Metabolites 2023; 13:1153. [PMID: 37999249 PMCID: PMC10672802 DOI: 10.3390/metabo13111153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/07/2023] [Accepted: 11/07/2023] [Indexed: 11/25/2023] Open
Abstract
Cardiopulmonary bypass (CPB) provides cerebral oxygenation and blood flow (CBF) during neonatal congenital heart surgery, but the impacts of CPB on brain oxygen supply and metabolic demands are generally unknown. To elucidate this physiology, we used diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy to continuously measure CBF, oxygen extraction fraction (OEF), and oxygen metabolism (CMRO2) in 27 neonatal swine before, during, and up to 24 h after CPB. Concurrently, we sampled cerebral microdialysis biomarkers of metabolic distress (lactate-pyruvate ratio) and injury (glycerol). We applied a novel theoretical approach to correct for hematocrit variation during optical quantification of CBF in vivo. Without correction, a mean (95% CI) +53% (42, 63) increase in hematocrit resulted in a physiologically improbable +58% (27, 90) increase in CMRO2 relative to baseline at CPB initiation; following correction, CMRO2 did not differ from baseline at this timepoint. After CPB initiation, OEF increased but CBF and CMRO2 decreased with CPB time; these temporal trends persisted for 0-8 h following CPB and coincided with a 48% (7, 90) elevation of glycerol. The temporal trends and glycerol elevation resolved by 8-24 h. The hematocrit correction improved quantification of cerebral physiologic trends that precede and coincide with neurological injury following CPB.
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Affiliation(s)
- Emilie J. Benson
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA; (E.J.B.); (A.G.Y.)
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Danielle I. Aronowitz
- Division of Cardiothoracic Surgery, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (D.I.A.); (J.W.G.); (C.D.M.)
| | - Rodrigo M. Forti
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Alec Lafontant
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Nicolina R. Ranieri
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Jonathan P. Starr
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (J.P.S.); (T.J.K.)
| | - Richard W. Melchior
- Department of Perfusion Services, Cardiac Center, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA;
| | - Alistair Lewis
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jharna Jahnavi
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Jake Breimann
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Bohyun Yun
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Gerard H. Laurent
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Jennifer M. Lynch
- Division of Cardiothoracic Anesthesiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA;
| | - Brian R. White
- Division of Cardiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - J. William Gaynor
- Division of Cardiothoracic Surgery, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (D.I.A.); (J.W.G.); (C.D.M.)
| | - Daniel J. Licht
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Arjun G. Yodh
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA; (E.J.B.); (A.G.Y.)
| | - Todd J. Kilbaugh
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (J.P.S.); (T.J.K.)
| | - Constantine D. Mavroudis
- Division of Cardiothoracic Surgery, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (D.I.A.); (J.W.G.); (C.D.M.)
| | - Wesley B. Baker
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (R.M.F.); (A.L.); (N.R.R.); (J.J.); (J.B.); (B.Y.); (G.H.L.); (D.J.L.); (W.B.B.)
| | - Tiffany S. Ko
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA; (J.P.S.); (T.J.K.)
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Maity AK, Sharma MK, Veeraraghavan A, Sabharwal A. SpeckleCam: high-resolution computational speckle contrast tomography for deep blood flow imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:5316-5337. [PMID: 37854569 PMCID: PMC10581815 DOI: 10.1364/boe.498900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 10/20/2023]
Abstract
Laser speckle contrast imaging is widely used in clinical studies to monitor blood flow distribution. Speckle contrast tomography, similar to diffuse optical tomography, extends speckle contrast imaging to provide deep tissue blood flow information. However, the current speckle contrast tomography techniques suffer from poor spatial resolution and involve both computation and memory intensive reconstruction algorithms. In this work, we present SpeckleCam, a camera-based system to reconstruct high resolution 3D blood flow distribution deep inside the skin. Our approach replaces the traditional forward model using diffuse approximations with Monte-Carlo simulations-based convolutional forward model, which enables us to develop an improved deep tissue blood flow reconstruction algorithm. We show that our proposed approach can recover complex structures up to 6 mm deep inside a tissue-like scattering medium in the reflection geometry. We also conduct human experiments to demonstrate that our approach can detect reduced flow in major blood vessels during vascular occlusion.
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Affiliation(s)
- Akash Kumar Maity
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Manoj Kumar Sharma
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Ashok Veeraraghavan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Ashutosh Sabharwal
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
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Pian Q, Alfadhel M, Tang J, Lee GV, Li B, Fu B, Ayata Y, Yaseen MA, Boas DA, Secomb TW, Sakadzic S. Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:076003. [PMID: 37484973 PMCID: PMC10362155 DOI: 10.1117/1.jbo.28.7.076003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 05/30/2023] [Accepted: 06/05/2023] [Indexed: 07/25/2023]
Abstract
Significance The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms. Aim We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM). Approach We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram. Results We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments. Conclusions The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.
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Affiliation(s)
- Qi Pian
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Mohammed Alfadhel
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Jianbo Tang
- Southern University of Science and Technology, Department of Biomedical Engineering, Shenzhen, China
| | - Grace V. Lee
- University of Arizona, Program in Applied Mathematics, Tucson, Arizona, United States
| | - Baoqiang Li
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, Brain Cognition and Brain Disease Institute; Shenzhen Fundamental Research Institutions, Shenzhen–Hong Kong Institute of Brain Science, Shenzhen, Guangdong, China
| | - Buyin Fu
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Yagmur Ayata
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Mohammad Abbas Yaseen
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Timothy W. Secomb
- University of Arizona, Program in Applied Mathematics, Tucson, Arizona, United States
- University of Arizona, Department of Mathematics, Tucson, Arizona, United States
- University of Arizona, Department of Physiology, Tucson, Arizona, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
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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: 48] [Impact Index Per Article: 24.0] [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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Non-Invasive Blood Flow Speed Measurement Using Optics. SENSORS 2022; 22:s22030897. [PMID: 35161643 PMCID: PMC8838687 DOI: 10.3390/s22030897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 01/19/2022] [Accepted: 01/20/2022] [Indexed: 11/17/2022]
Abstract
Non-invasive measurement of the arterial blood speed gives important health information such as cardio output and blood supplies to vital organs. The magnitude and change in arterial blood speed are key indicators of the health conditions and development and progression of diseases. We demonstrated a simple technique to directly measure the blood flow speed in main arteries based on the diffused light model. The concept is demonstrated with a phantom that uses intralipid hydrogel to model the biological tissue and an embedded glass tube with flowing human blood to model the blood vessel. The correlation function of the measured photocurrent was used to find the electrical field correlation function via the Siegert relation. We have shown that the characteristic decorrelation rate (i.e., the inverse of the decoherent time) is linearly proportional to the blood speed and independent of the tube diameter. This striking property can be explained by an approximate analytic solution for the diffused light equation in the regime where the convective flow is the dominating factor for decorrelation. As a result, we have demonstrated a non-invasive method of measuring arterial blood speed without any prior knowledge or assumption about the geometric or mechanic properties of the blood vessels.
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Cheng X, Sie EJ, Naufel S, Boas DA, Marsili F. Measuring neuronal activity with diffuse correlation spectroscopy: a theoretical investigation. NEUROPHOTONICS 2021; 8:035004. [PMID: 34368390 PMCID: PMC8339443 DOI: 10.1117/1.nph.8.3.035004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/16/2021] [Indexed: 05/18/2023]
Abstract
Significance: Diffuse correlation spectroscopy (DCS) measures cerebral blood flow non-invasively. Variations in blood flow can be used to detect neuronal activities, but its peak has a latency of a few seconds, which is slow for real-time monitoring. Neuronal cells also deform during activation, which, in principle, can be utilized to detect neuronal activity on fast timescales (within 100 ms) using DCS. Aims: We aim to characterize DCS signal variation quantified as the change of the decay time of the speckle intensity autocorrelation function during neuronal activation on both fast (within 100 ms) and slow (100 ms to seconds) timescales. Approach: We extensively modeled the variations in the DCS signal that are expected to arise from neuronal activation using Monte Carlo simulations, including the impacts of neuronal cell motion, vessel wall dilation, and blood flow changes. Results: We found that neuronal cell motion induces a DCS signal variation of ∼ 10 - 5 . We also estimated the contrast and number of channels required to detect hemodynamic signals at different time delays. Conclusions: From this extensive analysis, we do not expect to detect neuronal cell motion using DCS in the near future based on current technology trends. However, multi-channel DCS will be able to detect hemodynamic response with sub-second latency, which is interesting for brain-computer interfaces.
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Affiliation(s)
- Xiaojun Cheng
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Massachusetts, United States
- Address all correspondence to Xiaojun Cheng,
| | - Edbert J. Sie
- Facebook Reality Labs Research, Menlo Park, California, United States
| | - Stephanie Naufel
- Facebook Reality Labs Research, Menlo Park, California, United States
| | - David A. Boas
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Massachusetts, United States
| | - Francesco Marsili
- Facebook Reality Labs Research, Menlo Park, California, United States
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8
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Rognon P, Macaulay M. Shear-induced diffusion in dense granular fluids. SOFT MATTER 2021; 17:5271-5277. [PMID: 34008690 DOI: 10.1039/d1sm00422k] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Granular materials are comprised of solid, athermal grains. Whilst immune to thermal motion, these grains move and diffuse when they undergo shear deformation. Here we introduce this process of shear-induced diffusion with a focus on dense flows. The goal is to present the established scaling laws for continuum diffusivity and to relate them to the micro-mechanisms of a granular random walk. We then suggest how this knowledge may help advance our understanding of granular rheology and diffusion in other soft-materials.
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Affiliation(s)
- Pierre Rognon
- Particles and Grains Laboratory, School of Civil Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
| | - Matthew Macaulay
- Particles and Grains Laboratory, School of Civil Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
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9
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Liu C, Kılıç K, Erdener SE, Boas DA, Postnov DD. Choosing a model for laser speckle contrast imaging. BIOMEDICAL OPTICS EXPRESS 2021; 12:3571-3583. [PMID: 34221679 PMCID: PMC8221943 DOI: 10.1364/boe.426521] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 05/08/2021] [Accepted: 05/18/2021] [Indexed: 05/02/2023]
Abstract
Laser speckle contrast imaging (LSCI) is a real-time full-field non-invasive technique, which is broadly applied to visualize blood flow in biomedical applications. In its foundation is the link between the speckle contrast and dynamics of light scattering particles-erythrocytes. The mathematical form describing this relationship, which is critical for accurate blood flow estimation, depends on the sample's light-scattering properties. However, in biological applications, these properties are often unknown, thus requiring assumptions to be made to perform LSCI analysis. Here, we review the most critical assumptions in the LSCI theory and simulate how they affect blood flow estimation accuracy. We show that the most commonly applied model can severely underestimate the flow change, particularly when imaging brain parenchyma or other capillary perfused tissue (e.g. skin) under ischemic conditions. Based on these observations and guided by the recent experimental results, we propose an alternative model that allows measuring blood flow changes with higher accuracy.
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Affiliation(s)
- Chang Liu
- Department of Biomedical Engineering, Boston University, Massachusetts 02215, USA
- Department of Bioengineering, Northeastern University, Massachusetts 02115, USA
| | - Kıvılcım Kılıç
- Neurophotonics Center, Boston University, Massachusetts 02215, USA
| | - Sefik Evren Erdener
- Neurophotonics Center, Boston University, Massachusetts 02215, USA
- Institute of Neurological Sciences and Psychiatry, Hacettepe University, Ankara, Turkey
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, Massachusetts 02215, USA
- Neurophotonics Center, Boston University, Massachusetts 02215, USA
| | - Dmitry D. Postnov
- Neurophotonics Center, Boston University, Massachusetts 02215, USA
- Department of Biomedical Sciences, Copenhagen University, Copenhagen, Denmark
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10
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Sunil S, Evren Erdener S, Cheng X, Kura S, Tang J, Jiang J, Karrobi K, Kılıç K, Roblyer D, Boas DA. Stroke core revealed by tissue scattering using spatial frequency domain imaging. NEUROIMAGE-CLINICAL 2020; 29:102539. [PMID: 33385882 PMCID: PMC7779322 DOI: 10.1016/j.nicl.2020.102539] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 12/14/2020] [Accepted: 12/15/2020] [Indexed: 12/26/2022]
Abstract
We present OCT and SFDI as methods to measure the spatial extent of stroke in mice. OCT was a reliable predictor of the stroke core in a photothrombosis stroke model. SFDI scattering coefficient spatially overlaps with OCT attenuation after stroke. Scattering increases following stroke reliably predict ischemic injury. SFDI provides a wide-field optical approach to map the stroke core.
Ischemic stroke leads to a reduction or complete loss of blood supply causing injury to brain tissue, which ultimately leads to behavioral impairment. Optical techniques are widely used to study the structural and functional changes that result as a consequence of ischemic stroke both in the acute and chronic phases of stroke recovery. It is currently a challenge to accurately estimate the spatial extent of the infarct without the use of histological parameters however, and in order to follow recovery mechanisms longitudinally at the mesoscopic scale it is essential to know the spatial extent of the stroke core. In this paper we first establish optical coherence tomography (OCT) as a reliable indicator of the stroke core by analyzing signal attenuation and spatially correlating it with the infarct, determined by staining with triphenyl-tetrazolium chloride (TTC). We then introduce spatial frequency domain imaging (SFDI) as a mesoscopic optical technique that can be used to accurately measure the infarct spatial extent by exploiting changes in optical scattering that occur as a consequence of ischemic stroke. Additionally, we follow the progression of ischemia through the acute and sub-acute phases of stroke recovery using both OCT and SFDI and show a consistently high spatial overlap in estimating infarct location. The use of SFDI in assessing infarct location will allow longitudinal studies targeted at following functional recovery mechanisms on a mesoscopic level without having to sacrifice the mouse acutely.
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Affiliation(s)
- Smrithi Sunil
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
| | - Sefik Evren Erdener
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Institute of Neurological Sciences and Psychiatry, Hacettepe University, Ankara, Turkey
| | - Xiaojun Cheng
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Sreekanth Kura
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Jianbo Tang
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - John Jiang
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Kavon Karrobi
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Kıvılcım Kılıç
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Darren Roblyer
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
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11
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Postnov DD, Tang J, Erdener SE, Kılıç K, Boas DA. Dynamic light scattering imaging. SCIENCE ADVANCES 2020; 6:6/45/eabc4628. [PMID: 33158865 PMCID: PMC7673709 DOI: 10.1126/sciadv.abc4628] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 09/17/2020] [Indexed: 05/18/2023]
Abstract
We introduce dynamic light scattering imaging (DLSI) to enable the wide-field measurement of the speckle temporal intensity autocorrelation function. DLSI uses the full temporal sampling of speckle fluctuations and a comprehensive model to identify the dynamic scattering regime and obtain a quantitative image of the scatterer dynamics. It reveals errors in the traditional theory of laser Doppler flowmetry and laser speckle contrast imaging and provides guidance on the best model to use in cerebral blood flow imaging.
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Affiliation(s)
- Dmitry D Postnov
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
- Biomedical Sciences Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen 2200, Denmark
| | - Jianbo Tang
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
| | | | - Kıvılcım Kılıç
- Neurophotonics Center, Boston University, Boston, MA 02215, USA
| | - David A Boas
- Neurophotonics Center, Boston University, Boston, MA 02215, USA.
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12
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Tang JC, Vankayala R, Mac JT, Anvari B. RBC-Derived Optical Nanoparticles Remain Stable After a Freeze-Thaw Cycle. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2020; 36:10003-10011. [PMID: 32787036 PMCID: PMC9844156 DOI: 10.1021/acs.langmuir.0c00637] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Nanosized carriers engineered from red blood cells (RBCs) provide a means for delivering various cargos, including drugs, biologics, and imaging agents. We have engineered nanosized particles from RBCs, doped with the near-infrared (NIR) fluorochrome, indocyanine green (ICG). An important issue related to clinical translation of RBC-derived nanocarriers, including these NIR nanoparticles, is their stability postfabrication. Freezing may provide a method for long-term storage of these and other RBC-derived nanoparticles. Herein, we have investigated the physical and optical stability of these particles in response to a single freeze-thaw cycle. Nanoparticles were frozen to -20 °C, stored frozen for up to 8 weeks, and then thawed at room temperature. Our results show that the hydrodynamic diameter, zeta potential, optical density, and NIR fluorescence emission of these nanoparticles are retained following the freeze-thaw cycle. The ability of these nanoparticles in NIR fluorescence imaging of ovarian cancer cells, as well as their biodistribution in reticuloendothelial organs of healthy Swiss Webster mice after the freeze-thaw cycle is similar to that for freshly prepared nanoparticles. These results indicate that a single cycle of freezing the RBC-derived nanoparticles to -20 °C followed by thawing at room temperature is an effective method to retain the physical and optical characteristics of the nanoparticles, and their interactions with biological systems without the need for use of cryoprotectants.
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Affiliation(s)
- Jack C Tang
- Department of Bioengineering, University of California, Riverside, California 92521, United States
| | - Raviraj Vankayala
- Department of Bioengineering, University of California, Riverside, California 92521, United States
| | - Jenny T Mac
- Department of Biochemistry, University of California, Riverside, California 92521, United States
| | - Bahman Anvari
- Department of Bioengineering, University of California, Riverside, California 92521, United States
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13
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Sathialingam E, Williams EK, Lee SY, McCracken CE, Lam WA, Buckley EM. Hematocrit significantly confounds diffuse correlation spectroscopy measurements of blood flow. BIOMEDICAL OPTICS EXPRESS 2020; 11:4786-4799. [PMID: 32923078 PMCID: PMC7449719 DOI: 10.1364/boe.397613] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 05/11/2023]
Abstract
Diffuse correlation spectroscopy (DCS) is an optical modality used to measure an index of blood flow in biological tissue. This blood flow index depends on both the red blood cell flow rate and density (i.e., hematocrit), although the functional form of hematocrit dependence is not well delineated. Herein, we develop and validate a novel tissue-simulating phantom containing hundreds of microchannels to investigate the influence of hematocrit on blood flow index. For a fixed flow rate, we demonstrate a significant inverse relationship between hematocrit and blood flow index that must be accounted for to accurately estimate blood flow under anemic conditions.
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Affiliation(s)
- Eashani Sathialingam
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr, NE, Atlanta, GA 30322, USA
| | - Evelyn Kendall Williams
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr, NE, Atlanta, GA 30322, USA
| | - Seung Yup Lee
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr, NE, Atlanta, GA 30322, USA
| | - Courtney E. McCracken
- Department of Pediatrics, School of Medicine, Emory University, 2015 Uppergate Dr., Atlanta, GA 30322, USA
| | - Wilbur A. Lam
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr, NE, Atlanta, GA 30322, USA
- Department of Pediatrics, School of Medicine, Emory University, 2015 Uppergate Dr., Atlanta, GA 30322, USA
| | - Erin M. Buckley
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr, NE, Atlanta, GA 30322, USA
- Department of Pediatrics, School of Medicine, Emory University, 2015 Uppergate Dr., Atlanta, GA 30322, USA
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14
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Ferris NG, Cannon TM, Villiger M, Bouma BE, Uribe-Patarroyo N. Forward multiple scattering dominates speckle decorrelation in whole-blood flowmetry using optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2020; 11:1947-1966. [PMID: 32341859 PMCID: PMC7173878 DOI: 10.1364/boe.384539] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 03/06/2020] [Accepted: 03/06/2020] [Indexed: 05/22/2023]
Abstract
Quantitative blood flow measurements using optical coherence tomography (OCT) have a wide potential range of medical research and clinical applications. Flowmetry based on the temporal dynamics of the OCT signal may have the ability to measure three-dimensional flow profiles regardless of the flow direction. State-of-the-art models describing the OCT signal temporal statistics are based on dynamic light scattering (DLS), a model which is inherently limited to single scattering regimes. DLS methods continue to be applied to OCT despite the knowledge that red blood cells produce strong forward multiple scattering. Here, we postulate that forward multiple scattering is the primary mechanism causing the rate of speckle-decorrelation derived from data acquired in vivo to deviate from the rate of decorrelation determined in phantom experiments. We also postulate that multiple scattering contributions to decorrelation are only present when the sample exhibits velocity field inhomogeneities larger than the scale of a resolution volume and are thus absent in rigid bulk motion. To test these hypotheses, we performed a systematic study of the effects of forward multiple scattering on OCT signal decorrelation with phantom experiments under physiologically relevant flow conditions and relative bulk motion. Our experimental results confirm that the amount of forward multiple scattering affects the proportionality between lateral flow and decorrelation. We propose that multiply scattered light carries information from different locations in the sample and each location imprints scattering dynamics on the scattered light causing increased decorrelation rates. Our analysis confirms that the detection of forward scattered light inside the vessel lumen causes an increase in the rate of decorrelation which results in an overestimation of blood flow velocities at depths as shallow as 40 µm into whole blood for OCT systems with typical numerical apertures used in retinal imaging.
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Affiliation(s)
- Natalie G. Ferris
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, 40 Blossom Street, Boston, Massachusetts 02114, USA
- Harvard-MIT Program in Health Sciences and Technology, Cambridge, Massachusetts 02139, USA
- Harvard Graduate Program in Biophysics, Harvard University Cambridge, Massachusetts 02139, USA
| | - Taylor M. Cannon
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, 40 Blossom Street, Boston, Massachusetts 02114, USA
- Harvard-MIT Program in Health Sciences and Technology, Cambridge, Massachusetts 02139, USA
| | - Martin Villiger
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, 40 Blossom Street, Boston, Massachusetts 02114, USA
| | - Brett E. Bouma
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, 40 Blossom Street, Boston, Massachusetts 02114, USA
- Harvard-MIT Program in Health Sciences and Technology, Cambridge, Massachusetts 02139, USA
- Institute for Medical Engineering and Science, MIT, Massachusetts 02139, USA
| | - Néstor Uribe-Patarroyo
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, 40 Blossom Street, Boston, Massachusetts 02114, USA
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15
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Kholiqov O, Zhou W, Zhang T, Du Le VN, Srinivasan VJ. Time-of-flight resolved light field fluctuations reveal deep human tissue physiology. Nat Commun 2020; 11:391. [PMID: 31959896 PMCID: PMC6971031 DOI: 10.1038/s41467-019-14228-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 12/17/2019] [Indexed: 12/16/2022] Open
Abstract
Red blood cells (RBCs) transport oxygen to tissues and remove carbon dioxide. Diffuse optical flowmetry (DOF) assesses deep tissue RBC dynamics by measuring coherent fluctuations of multiply scattered near-infrared light intensity. While classical DOF measurements empirically correlate with blood flow, they remain far-removed from light scattering physics and difficult to interpret in layered media. To advance DOF measurements closer to the physics, here we introduce an interferometric technique, surmounting challenges of bulk motion to apply it in awake humans. We reveal two measurement dimensions: optical phase, and time-of-flight (TOF), the latter with 22 picosecond resolution. With this multidimensional data, we directly confirm the unordered, or Brownian, nature of optically probed RBC dynamics typically assumed in classical DOF. We illustrate how incorrect absorption assumptions, anisotropic RBC scattering, and layered tissues may confound classical DOF. By comparison, our direct method enables accurate and comprehensive assessment of blood flow dynamics in humans.
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Affiliation(s)
- Oybek Kholiqov
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA
| | - Wenjun Zhou
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA
| | - Tingwei Zhang
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA
| | - V N Du Le
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA
| | - Vivek J Srinivasan
- Department of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
- Department of Ophthalmology and Vision Science, University of California Davis, Davis School of Medicine, Sacramento, CA, 96817, USA.
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16
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Gräfe MGO, Nadiarnykh O, De Boer JF. Optical coherence tomography velocimetry based on decorrelation estimation of phasor pair ratios (DEPPAIR). BIOMEDICAL OPTICS EXPRESS 2019; 10:5470-5485. [PMID: 31799025 PMCID: PMC6865093 DOI: 10.1364/boe.10.005470] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 09/17/2019] [Accepted: 09/20/2019] [Indexed: 05/13/2023]
Abstract
Quantitative velocity estimations in optical coherence tomography requires the estimation of the axial and lateral flow components. Optical coherence tomography measures the depth resolved complex field reflected from a sample. While the axial velocity component can be determined from the Doppler shift or phase shift between a pair of consecutive measurements at the same location, the estimation of the lateral component for in vivo applications is still challenging. One approach to determine lateral velocity is multiple simultaneous measurements at different angles. In another approach the lateral component can be retrieved through repeated measurements at (nearly) the same location by an analysis of the decorrelation over time. In this paper we follow the latter approach. We describe a model for the complex field changes between consecutive measurements and use it to predict the uncertainties for amplitude-based, phase-based and complex algorithms. The uncertainty of the flow estimations follows from a statistical analysis and is determined by the number of available measurements and the applied analysis method. The model is verified in phantom measurements and the dynamic range of velocity estimations is investigated. We demonstrate that phase-based and complex (phasor) based lateral flow estimation methods are superior to amplitude-based algorithms.
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17
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Wei W, Tang P, Xie Z, Li Y, Wang RK. Dynamic imaging and quantification of subcellular motion with eigen-decomposition optical coherence tomography-based variance analysis. JOURNAL OF BIOPHOTONICS 2019; 12:e201900076. [PMID: 31033200 PMCID: PMC6774886 DOI: 10.1002/jbio.201900076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 04/21/2019] [Accepted: 04/26/2019] [Indexed: 06/01/2023]
Abstract
The dynamic properties of subcellular organism are important biomarkers of the health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motion by using eigen decomposition (ED)-based variance analysis of time-dependent complex optical coherence tomography signals. This method reveals a superior advantage of contrast to noise ratio when compared with the approach that employs intensity decorrelation. Furthermore, the eigen values derived from ED processing are calculated and applied to assess the power ratios of complex signal invariance that decreases exponentially along time dimension. The validation experiments are performed on the patterned samples of yeast powder mixed with gelatin/TiO2 water solution. Additionally, the proposed method is used to image mouse cerebral cortex in normal and pathological conditions, suggesting the practicality of variance power mapping in analyzing cortical neural activities. The technique promises efficient measurement of subcellular motions with high sensitivity and high throughput for in vivo and in situ applications.
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Affiliation(s)
- Wei Wei
- Department of Bioengineering, University of Washington, Seattle, Washington
| | - Peijun Tang
- Department of Bioengineering, University of Washington, Seattle, Washington
| | - Zhiying Xie
- Department of Biology, University of Washington, Seattle, Washington
| | - Yuandong Li
- Department of Bioengineering, University of Washington, Seattle, Washington
| | - Ruikang K Wang
- Department of Bioengineering, University of Washington, Seattle, Washington
- Department of Ophthalmology, University of Washington, Seattle, Washington
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18
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Popov I, Weatherbee A, Vitkin A. Impact of velocity gradient in Poiseuille flow on the statistics of coherent radiation scattered by flowing Brownian particles in optical coherence tomography. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-7. [PMID: 31562708 PMCID: PMC6997670 DOI: 10.1117/1.jbo.24.9.097001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 08/23/2019] [Indexed: 05/22/2023]
Abstract
A closed-form expression is obtained for the temporal correlation function of the scattered radiation detected in optical coherence tomography (OCT), taking into account the flow velocity gradient across the OCT detection volume in the suspension of flowing Brownian particles. The analytical approach we use includes both the laser beam and wavefront curvature radii changing over the depth. Also, we compare our results with a previously obtained theoretical model, partially an empirical approach. Our findings suggest the importance of the flow velocity gradient for accurate measurements of flow velocity vector, particle diffusivity, shear-induced diffusion, and potentially other OCT applications.
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Affiliation(s)
- Ivan Popov
- University of Toronto, Department of Medical Biophysics, Toronto Medical Discovery Tower, Toronto, Ontario, Canada
- Address all correspondence to Ivan Popov, E-mail:
| | - Andrew Weatherbee
- University of Toronto, Department of Medical Biophysics, Toronto Medical Discovery Tower, Toronto, Ontario, Canada
| | - Alex Vitkin
- University of Toronto, Department of Medical Biophysics, Toronto Medical Discovery Tower, Toronto, Ontario, Canada
- University of Toronto, Department of Radiation Oncology, Toronto, Ontario, Canada
- Ontario Cancer Institute/University Health Network, Division of Biophysics and Bioimaging, Toronto, Ontario, Canada
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19
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Erdener ŞE, Dalkara T. Small Vessels Are a Big Problem in Neurodegeneration and Neuroprotection. Front Neurol 2019; 10:889. [PMID: 31474933 PMCID: PMC6707104 DOI: 10.3389/fneur.2019.00889] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Accepted: 08/01/2019] [Indexed: 12/11/2022] Open
Abstract
The cerebral microcirculation holds a critical position to match the high metabolic demand by neuronal activity. Functionally, microcirculation is virtually inseparable from other nervous system cells under both physiological and pathological conditions. For successful bench-to-bedside translation of neuroprotection research, the role of microcirculation in acute and chronic neurodegenerative disorders appears to be under-recognized, which may have contributed to clinical trial failures with some neuroprotectants. Increasing data over the last decade suggest that microcirculatory impairments such as endothelial or pericyte dysfunction, morphological irregularities in capillaries or frequent dynamic stalls in blood cell flux resulting in excessive heterogeneity in capillary transit may significantly compromise tissue oxygen availability. We now know that ischemia-induced persistent abnormalities in capillary flow negatively impact restoration of reperfusion after recanalization of occluded cerebral arteries. Similarly, microcirculatory impairments can accompany or even precede neural loss in animal models of several neurodegenerative disorders including Alzheimer's disease. Macrovessels are relatively easy to evaluate with radiological or experimental imaging methods but they cannot faithfully reflect the downstream microcirculatory disturbances, which may be quite heterogeneous across the tissue at microscopic scale and/or happen fast and transiently. The complexity and size of the elements of microcirculation, therefore, require utilization of cutting-edge imaging techniques with high spatiotemporal resolution as well as multidisciplinary team effort to disclose microvascular-neurodegenerative connection and to test treatment approaches to advance the field. Developments in two photon microscopy, ultrafast ultrasound, and optical coherence tomography provide valuable experimental tools to reveal those microscopic events with high resolution. Here, we review the up-to-date advances in understanding of the primary microcirculatory abnormalities that can result in neurodegenerative processes and the combined neurovascular protection approaches that can prevent acute as well as chronic neurodegeneration.
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Affiliation(s)
- Şefik Evren Erdener
- Institute of Neurological Sciences and Psychiatry, Hacettepe University, Ankara, Turkey
| | - Turgay Dalkara
- Institute of Neurological Sciences and Psychiatry, Hacettepe University, Ankara, Turkey.,Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
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20
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Mireles M, Morales-Dalmau J, Johansson JD, Vidal-Rosas EE, Vilches C, Martínez-Lozano M, Sanz V, de Miguel I, Casanovas O, Quidant R, Durduran T. Non-invasive and quantitative in vivo monitoring of gold nanoparticle concentration and tissue hemodynamics by hybrid optical spectroscopies. NANOSCALE 2019; 11:5595-5606. [PMID: 30860518 DOI: 10.1039/c8nr08790c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Owing to their unique combination of chemical and physical properties, inorganic nanoparticles show a great deal of potential as suitable agents for early diagnostics and less invasive therapies. Yet, their translation to the clinic has been hindered, in part, by the lack of non-invasive methods to quantify their concentration in vivo while also assessing their effect on the tissue physiology. In this work, we demonstrate that diffuse optical techniques, employing near-infrared light, have the potential to address this need in the case of gold nanoparticles which support localized surface plasmons. An orthoxenograft mouse model of clear cell renal cell carcinoma was non-invasively assessed by diffuse reflectance and correlation spectroscopies before and over several days following a single intravenous tail vein injection of polyethylene glycol-coated gold nanorods (AuNRs-PEG). Our platform enables to resolve the kinetics of the AuNR-PEG uptake by the tumor in quantitative agreement with ex vivo inductively coupled plasma mass spectroscopy. Furthermore, it allows for the simultaneous monitoring of local tissue hemodynamics, enabling us to conclude that AuNRs-PEG do not significantly alter the animal physiology. We note that the penetration depth of this current probe was a few millimeters but can readily be extended to centimeters, hence gaining clinical relevance. This study and the methodology presented here complement the nanomedicine toolbox by providing a flexible platform, extendable to other absorbing agents that can potentially be translated to human trials.
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Affiliation(s)
- Miguel Mireles
- ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels, Barcelona, Spain.
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21
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Tang J, Erdener SE, Sunil S, Boas DA. Normalized field autocorrelation function-based optical coherence tomography three-dimensional angiography. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-8. [PMID: 30868803 PMCID: PMC6414735 DOI: 10.1117/1.jbo.24.3.036005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 02/06/2019] [Indexed: 05/02/2023]
Abstract
Optical coherence tomography angiography (OCTA) has been widely used for en face visualization of the microvasculature, but is challenged for real three-dimensional (3-D) topologic imaging due to the "tail" artifacts that appear below large vessels. Further, OCTA is generally incapable of differentiating descending arterioles from ascending venules. We introduce a normalized field autocorrelation function-based OCTA (g1-OCTA), which minimizes the tail artifacts and is capable of distinguishing penetrating arterioles from venules in the 3-D image. g1 ( τ ) is calculated from repeated optical coherence tomography (OCT) acquisitions for each spatial location. The decay amplitude of g1 ( τ ) is retrieved to represent the dynamics for each voxel. To account for the small g1 ( τ ) decay in capillaries where red blood cells are flowing slowly and discontinuously, Intralipid is injected to enhance the OCT signal. We demonstrate that the proposed technique realizes 3-D OCTA with negligible tail projections and the penetrating arteries are readily identified. In addition, compared to regular OCTA, the proposed g1-OCTA largely increased the depth-of-field. This technique provides a more accurate rendering of the vascular 3-D anatomy and has the potential for more quantitative characterization of vascular networks.
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Affiliation(s)
- Jianbo Tang
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
- Address all correspondence to Jianbo Tang, E-mail:
| | - Sefik Evren Erdener
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Smrithi Sunil
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - David A. Boas
- Boston University, Neurophotonics Center, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
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22
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Zirak P, Gregori-Pla C, Blanco I, Fortuna A, Cotta G, Bramon P, Serra I, Mola A, Solà-Soler J, Giraldo-Giraldo BF, Durduran T, Mayos M. Characterization of the microvascular cerebral blood flow response to obstructive apneic events during night sleep. NEUROPHOTONICS 2018; 5:045003. [PMID: 30681667 PMCID: PMC6215085 DOI: 10.1117/1.nph.5.4.045003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Accepted: 10/10/2018] [Indexed: 05/09/2023]
Abstract
Obstructive apnea causes periodic changes in cerebral and systemic hemodynamics, which may contribute to the increased risk of cerebrovascular disease of patients with obstructive sleep apnea (OSA) syndrome. The improved understanding of the consequences of an apneic event on the brain perfusion may improve our knowledge of these consequences and then allow for the development of preventive strategies. Our aim was to characterize the typical microvascular, cortical cerebral blood flow (CBF) changes in an OSA population during an apneic event. Sixteen patients (age 58 ± 8 years , 75% male) with a high risk of severe OSA were measured with a polysomnography device and with diffuse correlation spectroscopy (DCS) during one night of sleep with 1365 obstructive apneic events detected. All patients were later confirmed to suffer from severe OSA syndrome with a mean of 83 ± 15 apneas and hypopneas per hour. DCS has been shown to be able to characterize the microvascular CBF response to each event with a sufficient contrast-to-noise ratio to reveal its dynamics. It has also revealed that an apnea causes a peak increase of microvascular CBF ( 30 ± 17 % ) at the end of the event followed by a drop ( - 20 ± 12 % ) similar to what was observed in macrovascular CBF velocity of the middle cerebral artery. This study paves the way for the utilization of DCS for further studies on these populations.
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Affiliation(s)
- Peyman Zirak
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Clara Gregori-Pla
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
- Address all correspondence to: Clara Gregori-Pla, E-mail:
| | - Igor Blanco
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Ana Fortuna
- Hospital de la Santa Creu i Sant Pau, Department of Respiratory Medicine, Sleep Unit, Barcelona, Spain
| | - Gianluca Cotta
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Pau Bramon
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Isabel Serra
- Centre de Recerca Matemàtica (CRM), Bellaterra, Spain
| | - Anna Mola
- Hospital de la Santa Creu i Sant Pau, Department of Respiratory Medicine, Sleep Unit, Barcelona, Spain
| | - Jordi Solà-Soler
- Universitat Politècnica de Catalunya (UPC)-Barcelona Tech, Department of Automatic Control (ESAII), Barcelona, Spain
- The Barcelona Institute of Science and Technology, Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
| | - Beatriz F. Giraldo-Giraldo
- Universitat Politècnica de Catalunya (UPC)-Barcelona Tech, Department of Automatic Control (ESAII), Barcelona, Spain
- The Barcelona Institute of Science and Technology, Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
| | - Turgut Durduran
- ICFO-Institut de Ciències Fotòniques, Barcelona Institute of Science and Technology, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Mercedes Mayos
- Hospital de la Santa Creu i Sant Pau, Department of Respiratory Medicine, Sleep Unit, Barcelona, Spain
- CIBER Enfermedades Respiratorias (CibeRes) (CB06/06), Madrid, Spain
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23
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Liu J, Wang H, Wang P, Jin Z, Li W, Zhang H, Shen Z, Xiong D. Establishing the quantitative relationship between diffuse speckle contrast analysis signals with absolute blood flow. BIOMEDICAL OPTICS EXPRESS 2018; 9:4792-4806. [PMID: 30319903 PMCID: PMC6179414 DOI: 10.1364/boe.9.004792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 08/15/2018] [Accepted: 09/06/2018] [Indexed: 06/08/2023]
Abstract
Diffuse speckle contrast analysis (DSCA) measures blood flow in deep tissues by taking advantage of the sensitivity of the speckle contrast signal to red blood cells (RBCs) motions. However, there has yet to be presented a clearly defined relationship between the absolute blood flow BFabs and the measured speckle contrast signal. Here, we derive an expression of linear approximation function for speckle contrast, taking into account both shear-induced diffusive and correlated advective RBCs motions in the vessels. We provide a linear relationship between the slope k slope of this linear function and BFabs. The feasibility of this relationship is validated by Monte Carlo simulations of heterogeneous tissue with varying vessel radii. Furthermore, based on this quantitative relationship, we can determine the relative contributions of diffusive RBCs motion on the reduction of speckle contrast, considering different vascular morphology and flow profiles.
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Affiliation(s)
- Jialin Liu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
| | - Haiyang Wang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
| | - Peipei Wang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
| | - Zhiliang Jin
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
| | - Weimin Li
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
| | - Hongchao Zhang
- School of Science, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, Nanjing 210094, China
| | - Zhonghua Shen
- School of Science, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, Nanjing 210094, China
| | - Daxi Xiong
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, No. 88 Keling Street, Suzhou 215163, China
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24
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Tang J, Erdener SE, Fu B, Boas DA. Capillary red blood cell velocimetry by phase-resolved optical coherence tomography. OPTICS LETTERS 2017; 42:3976-3979. [PMID: 28957175 PMCID: PMC5972360 DOI: 10.1364/ol.42.003976] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 09/05/2017] [Indexed: 05/05/2023]
Abstract
We present a phase-resolved optical coherence tomography (OCT) method to extend Doppler OCT for the accurate measurement of the red blood cell (RBC) velocity in cerebral capillaries. OCT data were acquired with an M-mode scanning strategy (repeated A-scans) to account for the single-file passage of RBCs in a capillary, which were then high-pass filtered to remove the stationary component of the signal to ensure an accurate measurement of phase shift of flowing RBCs. The angular frequency of the signal from flowing RBCs was then quantified from the dynamic component of the signal and used to calculate the axial speed of flowing RBCs in capillaries. We validated our measurement by RBC passage velocimetry using the signal magnitude of the same OCT time series data.
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Affiliation(s)
- Jianbo Tang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - Sefik Evren Erdener
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - Buyin Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - David A. Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA
- Neurophotonics Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
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