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Nogueira MS, Gunther JE, Komolibus K, Ryan SM, Murray BS, Jezzini MA, Kennedy D, Andersson-Engels S. Teaching and learning in biophotonics: Crossing the bridge between educators and students. JOURNAL OF BIOPHOTONICS 2024; 17:e202300491. [PMID: 38664987 DOI: 10.1002/jbio.202300491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 07/13/2024]
Abstract
As a rapidly growing field, biophotonics demonstrates an increasingly higher demand for interdisciplinary professionals and requires the implementation of a structured approach to educational and outreach activities focused on appropriate curriculum, and teaching and learning for audiences with diverse technical backgrounds and learning styles. Our study shows the main findings upon applying this approach to biophotonics workshops delivered 2 consecutive years while updating and improving learning outcomes, teaching strategies, workshop content based on student and teacher feedback. We provided resources for a variety of lecture-based, experimental, computer simulation activities. Quality of subject matter, teaching, and overall learning was rated as "Very good" or "Good" by 88%, 76%, and 82% of students in average, respectively. Application of our teaching strategies and materials during short- and long-term workshops/courses could potentially increase the interest in pursuing careers in the biophotonics field and related areas, leading to standardized approaches in designing education and outreach events across centers.
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Affiliation(s)
- Marcelo S Nogueira
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
| | - Jacqueline E Gunther
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
| | - Katarzyna Komolibus
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
| | - Sinéad M Ryan
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
| | - Brian S Murray
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
| | - Moises A Jezzini
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
| | - Declan Kennedy
- Department of Education, University College Cork, Cork, Ireland
| | - Stefan Andersson-Engels
- Biophotonics@Tyndall, Tyndall National Institute, University College Cork, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
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Stergar J, Hren R, Milanič M. Design and Validation of a Custom-Made Hyperspectral Microscope Imaging System for Biomedical Applications. SENSORS (BASEL, SWITZERLAND) 2023; 23:2374. [PMID: 36904578 PMCID: PMC10007032 DOI: 10.3390/s23052374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/10/2023] [Accepted: 02/19/2023] [Indexed: 06/18/2023]
Abstract
Hyperspectral microscope imaging (HMI) is an emerging modality that integrates spatial information collected by standard laboratory microscopy and the spectral-based contrast obtained by hyperspectral imaging and may be instrumental in establishing novel quantitative diagnostic methodologies, particularly in histopathology. Further expansion of HMI capabilities hinges upon the modularity and versatility of systems and their proper standardization. In this report, we describe the design, calibration, characterization, and validation of the custom-made laboratory HMI system based on a Zeiss Axiotron fully motorized microscope and a custom-developed Czerny-Turner-type monochromator. For these important steps, we rely on a previously designed calibration protocol. Validation of the system demonstrates a performance comparable to classic spectrometry laboratory systems. We further demonstrate validation against a laboratory hyperspectral imaging system for macroscopic samples, enabling future comparison of spectral imaging results across length scales. An example of the utility of our custom-made HMI system on a standard hematoxylin and eosin-stained histology slide is also shown.
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Affiliation(s)
- Jošt Stergar
- Jožef Stefan Institute, Jamova Cesta 39, SI-1000 Ljubljana, Slovenia
- Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, SI-1000 Ljubljana, Slovenia
| | - Rok Hren
- Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, SI-1000 Ljubljana, Slovenia
| | - Matija Milanič
- Jožef Stefan Institute, Jamova Cesta 39, SI-1000 Ljubljana, Slovenia
- Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, SI-1000 Ljubljana, Slovenia
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Olaetxea I, Lafuente H, Lopez E, Izeta A, Jaunarena I, Seifert A. Photonic Technology for In Vivo Monitoring of Hypoxia-Ischemia. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 10:e2204834. [PMID: 36377426 PMCID: PMC9811478 DOI: 10.1002/advs.202204834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Surveillance of physiological parameters of newborns during delivery triggers medical decision-making, can rescue life and health, and helps avoid unnecessary cesareans. Here, the development of a photonic technology for monitoring perinatal asphyxia is presented and validated in vivo in a preclinical stage. Contrary to state of the art, the technology provides continuous data in real-time in a non-invasive manner. Moreover, the technology does not rely on a single parameter as pH or lactate, instead monitors changes of the entirety of physiological parameters accessible by Raman spectroscopy. By a fiber-coupled Raman probe that is in controlled contact with the skin of the subject, near-infrared Raman spectra are measured and analyzed by machine learning algorithms to develop classification models. As a performance benchmarking, various hybrid and non-hybrid classifiers are tested. In an asphyxia model in newborn pigs, more than 1000 Raman spectra are acquired at three different clinical phases-basal condition, hypoxia-ischemia, and post-hypoxia-ischemia stage. In this preclinical proof-of-concept study, figures of merit reach 90% levels for classifying the clinical phases and demonstrate the power of the technology as an innovative medical tool for diagnosing a perinatal adverse outcome.
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Affiliation(s)
- Ion Olaetxea
- CIC nanoGUNE BRTASan Sebastián20018Spain
- Department of Communications EngineeringUniversity of the Basque CountryBilbao48013Spain
| | - Hector Lafuente
- Biodonostia Health Research InstituteSan Sebastián20014Spain
| | | | - Ander Izeta
- Biodonostia Health Research InstituteSan Sebastián20014Spain
- Tecnun School of Engineering ‐ University of NavarraSan Sebastián20018Spain
| | - Ibon Jaunarena
- Biodonostia Health Research InstituteSan Sebastián20014Spain
| | - Andreas Seifert
- CIC nanoGUNE BRTASan Sebastián20018Spain
- IKERBASQUEBasque Foundation for ScienceBilbao48009Spain
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Hilzenrat G, Gill ET, McArthur SL. Imaging approaches for monitoring three-dimensional cell and tissue culture systems. JOURNAL OF BIOPHOTONICS 2022; 15:e202100380. [PMID: 35357086 DOI: 10.1002/jbio.202100380] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/27/2022] [Accepted: 03/28/2022] [Indexed: 06/14/2023]
Abstract
The past decade has seen an increasing demand for more complex, reproducible and physiologically relevant tissue cultures that can mimic the structural and biological features of living tissues. Monitoring the viability, development and responses of such tissues in real-time are challenging due to the complexities of cell culture physical characteristics and the environments in which these cultures need to be maintained in. Significant developments in optics, such as optical manipulation, improved detection and data analysis, have made optical imaging a preferred choice for many three-dimensional (3D) cell culture monitoring applications. The aim of this review is to discuss the challenges associated with imaging and monitoring 3D tissues and cell culture, and highlight topical label-free imaging tools that enable bioengineers and biophysicists to non-invasively characterise engineered living tissues.
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Affiliation(s)
- Geva Hilzenrat
- Bioengineering Engineering Group, School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, Victoria, Australia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton, Victoria, Australia
| | - Emma T Gill
- Bioengineering Engineering Group, School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, Victoria, Australia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton, Victoria, Australia
| | - Sally L McArthur
- Bioengineering Engineering Group, School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, Victoria, Australia
- Biomedical Manufacturing, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Clayton, Victoria, Australia
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Pacheco A, Grygoryev K, Messina W, Andersson-Engels S. Lung tissue phantom mimicking pulmonary optical properties, relative humidity, and temperature: a tool to analyze the changes in oxygen gas absorption for different inflated volumes. JOURNAL OF BIOMEDICAL OPTICS 2021; 27:JBO-210214SSR. [PMID: 34725995 PMCID: PMC8558837 DOI: 10.1117/1.jbo.27.7.074707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/15/2021] [Indexed: 06/07/2023]
Abstract
SIGNIFICANCE Gas in scattering media absorption spectroscopy (GASMAS) enables noninvasive gas sensing in the body. It is developing as a tool for diagnosis and monitoring of respiratory conditions in neonates. Phantom models with relevant features to the clinical translation of GASMAS technology are necessary to understand technical challenges and potential applications of this technique. State-of-the-art phantoms designed for this purpose have focused on the optical properties and anthropomorphic geometry of the thorax, contributing to the source-detector placement, design, and optimization. Lung phantom mimicking the alveolar anatomy has not been included in the existent models due to the inherent complexity of the tissue. We present a simplified model that recreates inflated alveoli embedded in lung phantom. AIM The goal of this study was to build a lung model with air-filled structures mimicking inflated alveoli surrounded by optical phantom with accurate optical properties (μa = 0.50 cm - 1 and μs'=5.4 cm-1) and physiological parameters [37°C and 100% relative humidity (RH)], and to control the air volume within the phantom to demonstrate the feasibility of GASMAS in sensing changes in pulmonary air volume. APPROACH The lung model was built using a capillary structure with analogous size to alveolar units. Part of the capillaries were filled with liquid lung optical phantom to recreate scattering and absorption, whereas empty capillaries mimicked air filled alveoli. The capillary array was placed inside a custom-made chamber that maintained pulmonary temperature and RH. The geometry of the chamber permitted the placement of the laser head and detector of a GASMAS bench top system (MicroLab Dual O2 / H2O), to test the changes in volume of the lung model in transmittance geometry. RESULTS The lung tissue model with air volume range from 6.89 × 10 - 7 m3 to 1.80 × 10 - 3 m3 was built. Two measurement sets, with 10 different capillary configurations each, were arranged to increase or decrease progressively (in steps of 3.93 × 10 - 8 m3) the air volume in the lung model. The respective GASMAS data acquisition was performed for both data sets. The maximum absorption signal was obtained for configurations with the highest number of air-filled capillaries and decreased progressively when the air spaces were replaced by capillaries filled with liquid optical phantom. Further studies are necessary to define the minimum and maximum volume of air that can be measured with GASMAS-based devices for different source-detector geometries. CONCLUSIONS The optical properties and the structure of tissue from the respiratory zone have been modeled using a simplified capillary array immersed in a controlled environment chamber at pulmonary temperature and RH. The feasibility of measuring volume changes with GASMAS technique has been proven, stating a new possible application of GASMAS technology in respiratory treatment and diagnostics.
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Affiliation(s)
- Andrea Pacheco
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland
- University College Cork, Department of Physics, Cork, Ireland
| | - Konstantin Grygoryev
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland
| | - Walter Messina
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland
| | - Stefan Andersson-Engels
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland
- University College Cork, Department of Physics, Cork, Ireland
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Tadesse LF, Safir F, Ho CS, Hasbach X, Khuri-Yakub BP, Jeffrey SS, Saleh AAE, Dionne J. Toward rapid infectious disease diagnosis with advances in surface-enhanced Raman spectroscopy. J Chem Phys 2021; 152:240902. [PMID: 32610995 DOI: 10.1063/1.5142767] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
In a pandemic era, rapid infectious disease diagnosis is essential. Surface-enhanced Raman spectroscopy (SERS) promises sensitive and specific diagnosis including rapid point-of-care detection and drug susceptibility testing. SERS utilizes inelastic light scattering arising from the interaction of incident photons with molecular vibrations, enhanced by orders of magnitude with resonant metallic or dielectric nanostructures. While SERS provides a spectral fingerprint of the sample, clinical translation is lagged due to challenges in consistency of spectral enhancement, complexity in spectral interpretation, insufficient specificity and sensitivity, and inefficient workflow from patient sample collection to spectral acquisition. Here, we highlight the recent, complementary advances that address these shortcomings, including (1) design of label-free SERS substrates and data processing algorithms that improve spectral signal and interpretability, essential for broad pathogen screening assays; (2) development of new capture and affinity agents, such as aptamers and polymers, critical for determining the presence or absence of particular pathogens; and (3) microfluidic and bioprinting platforms for efficient clinical sample processing. We also describe the development of low-cost, point-of-care, optical SERS hardware. Our paper focuses on SERS for viral and bacterial detection, in hopes of accelerating infectious disease diagnosis, monitoring, and vaccine development. With advances in SERS substrates, machine learning, and microfluidics and bioprinting, the specificity, sensitivity, and speed of SERS can be readily translated from laboratory bench to patient bedside, accelerating point-of-care diagnosis, personalized medicine, and precision health.
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Affiliation(s)
- Loza F Tadesse
- Department of Bioengineering, Stanford University School of Medicine and School of Engineering, Stanford, California 94305, USA
| | - Fareeha Safir
- Department of Mechanical Engineering, Stanford University School of Engineering, Stanford, California 94305, USA
| | - Chi-Sing Ho
- Department of Applied Physics, Stanford University School of Humanities and Sciences, Stanford, California 94305, USA
| | - Ximena Hasbach
- Department of Materials Science and Engineering, Stanford University School of Engineering, Stanford, California 94305, USA
| | - Butrus Pierre Khuri-Yakub
- Department of Electrical Engineering, Stanford University School of Engineering, Stanford, California 94305, USA
| | - Stefanie S Jeffrey
- Department of Surgery, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Amr A E Saleh
- Department of Materials Science and Engineering, Stanford University School of Engineering, Stanford, California 94305, USA
| | - Jennifer Dionne
- Department of Materials Science and Engineering, Stanford University School of Engineering, Stanford, California 94305, USA
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7
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Olaetxea I, Valero A, Lopez E, Lafuente H, Izeta A, Jaunarena I, Seifert A. Machine Learning-Assisted Raman Spectroscopy for pH and Lactate Sensing in Body Fluids. Anal Chem 2020; 92:13888-13895. [PMID: 32985871 DOI: 10.1021/acs.analchem.0c02625] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
This study presents the combination of Raman spectroscopy with machine learning algorithms as a prospective diagnostic tool capable of detecting and monitoring relevant variations of pH and lactate as recognized biomarkers of several pathologies. The applicability of the method proposed here is tested both in vitro and ex vivo. In a first step, Raman spectra of aqueous solutions are evaluated for the identification of characteristic patterns resulting from changes in pH or in the concentration of lactate. The method is further validated with blood and plasma samples. Principal component analysis is used to highlight the relevant features that differentiate the Raman spectra regarding their pH and concentration of lactate. Partial least squares regression models are developed to capture and model the spectral variability of the Raman spectra. The performance of these predictive regression models is demonstrated by clinically accurate predictions of pH and lactate from unknown samples in the physiologically relevant range. These results prove the potential of our method to develop a noninvasive technology, based on Raman spectroscopy, for continuous monitoring of pH and lactate in vivo.
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Affiliation(s)
- Ion Olaetxea
- Nanoengineering Group, CIC nanoGUNE BRTA, Tolosa Hiribidea 76, 20018 San Sebastián, Spain.,PhD Student, Department of Communications Engineering, University of the Basque Country (UPV/EHU), Torres Quevedo Ingeniaria Plaza 1, 48013 Bilbao, Spain
| | - Ana Valero
- Nanoengineering Group, CIC nanoGUNE BRTA, Tolosa Hiribidea 76, 20018 San Sebastián, Spain
| | - Eneko Lopez
- Nanoengineering Group, CIC nanoGUNE BRTA, Tolosa Hiribidea 76, 20018 San Sebastián, Spain
| | - Héctor Lafuente
- Tissue Engineering, Biodonostia Health Research Institute, Begiristain Doktorea Pasealekua, 20014 San Sebastián, Spain
| | - Ander Izeta
- Tissue Engineering, Biodonostia Health Research Institute, Begiristain Doktorea Pasealekua, 20014 San Sebastián, Spain
| | - Ibon Jaunarena
- Obstetrics and Gynaecology, Biodonostia Health Research Institute, Begiristain Doktorea Pasealekua, 20014 San Sebastián, Spain.,Donostia University Hospital, Begiristain Doktorea Pasealekua, 20014 San Sebastián, Spain
| | - Andreas Seifert
- Nanoengineering Group, CIC nanoGUNE BRTA, Tolosa Hiribidea 76, 20018 San Sebastián, Spain.,IKERBASQUE, Basque Foundation for Science, Euskadi Plaza 5, 48009 Bilbao, Spain
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8
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Hutchinson MR. Science convergence applied to psychoneuroimmunology: The future of measurement and imaging. Brain Behav Immun 2020; 88:262-269. [PMID: 32289367 DOI: 10.1016/j.bbi.2020.04.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 03/06/2020] [Accepted: 04/10/2020] [Indexed: 11/29/2022] Open
Abstract
The future of psychoneuroimmunology requires breakthrough technology discoveries. These next generation technologies need to address the unique challenges that are raised by imaging and measuring the activity of the neuroimmune interface in health and disease. The complexity of this challenge is centred around the multidimensionality of the neuroimmune system. These include novel challenges of capturing potent and rare biological signals over long times and vast anatomical distances. Here is a summary of the outcomes of the investments made by the Australian Research Council Centre of Excellence for Nanoscale BioPhotonics which was presented as part of the PNIRSAsia-Pacific symposium at the 2019 International Brain Research Organization.
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Affiliation(s)
- Mark R Hutchinson
- Adelaide Medical School, Faculty of Health Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia; Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, Adelaide, South Australia 5005, Australia; Institute for Photonics and Advanced Sensing, University of Adelaide, Adelaide, South Australia 5005, Australia; Robinson Research Institute, University of Adelaide, Adelaide, South Australia 5005, Australia
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9
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Davis KD, Aghaeepour N, Ahn AH, Angst MS, Borsook D, Brenton A, Burczynski ME, Crean C, Edwards R, Gaudilliere B, Hergenroeder GW, Iadarola MJ, Iyengar S, Jiang Y, Kong JT, Mackey S, Saab CY, Sang CN, Scholz J, Segerdahl M, Tracey I, Veasley C, Wang J, Wager TD, Wasan AD, Pelleymounter MA. Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities. Nat Rev Neurol 2020; 16:381-400. [PMID: 32541893 PMCID: PMC7326705 DOI: 10.1038/s41582-020-0362-2] [Citation(s) in RCA: 201] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2020] [Indexed: 02/06/2023]
Abstract
Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.
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Affiliation(s)
- Karen D Davis
- Department of Surgery and Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - David Borsook
- Center for Pain and the Brain, Harvard Medical School, Boston, MA, USA
| | | | | | | | - Robert Edwards
- Pain Management Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Georgene W Hergenroeder
- The Vivian L. Smith Department of Neurosurgery, The University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA
| | - Michael J Iadarola
- Department of Perioperative Medicine, Clinical Center, NIH, Rockville, MD, USA
| | - Smriti Iyengar
- Division of Translational Research, National Institute of Neurological Disorders and Stroke, NIH, Rockville, MD, USA
| | - Yunyun Jiang
- The Biostatistics Center, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Jiang-Ti Kong
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Sean Mackey
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Carl Y Saab
- Department of Neuroscience and Department of Neurosurgery, Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Christine N Sang
- Department of Anesthesiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Joachim Scholz
- Neurocognitive Disorders, Pain and New Indications, Biogen, Cambridge, MA, USA
| | | | - Irene Tracey
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Jing Wang
- Department of Anesthesiology, Perioperative Care and Pain Medicine, NYU School of Medicine, New York, NY, USA
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Ajay D Wasan
- Anesthesiology and Perioperative Medicine and Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary Ann Pelleymounter
- Division of Translational Research, National Institute of Neurological Disorders and Stroke, NIH, Rockville, MD, USA
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Pradhan P, Guo S, Ryabchykov O, Popp J, Bocklitz TW. Deep learning a boon for biophotonics? JOURNAL OF BIOPHOTONICS 2020; 13:e201960186. [PMID: 32167235 DOI: 10.1002/jbio.201960186] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 02/22/2020] [Accepted: 03/10/2020] [Indexed: 06/10/2023]
Abstract
This review covers original articles using deep learning in the biophotonic field published in the last years. In these years deep learning, which is a subset of machine learning mostly based on artificial neural network geometries, was applied to a number of biophotonic tasks and has achieved state-of-the-art performances. Therefore, deep learning in the biophotonic field is rapidly growing and it will be utilized in the next years to obtain real-time biophotonic decision-making systems and to analyze biophotonic data in general. In this contribution, we discuss the possibilities of deep learning in the biophotonic field including image classification, segmentation, registration, pseudostaining and resolution enhancement. Additionally, we discuss the potential use of deep learning for spectroscopic data including spectral data preprocessing and spectral classification. We conclude this review by addressing the potential applications and challenges of using deep learning for biophotonic data.
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Affiliation(s)
- Pranita Pradhan
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), Member of Leibniz Research Alliance 'Health Technologies', Jena, Germany
| | - Shuxia Guo
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), Member of Leibniz Research Alliance 'Health Technologies', Jena, Germany
| | - Oleg Ryabchykov
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), Member of Leibniz Research Alliance 'Health Technologies', Jena, Germany
| | - Juergen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), Member of Leibniz Research Alliance 'Health Technologies', Jena, Germany
| | - Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology (Leibniz-IPHT), Member of Leibniz Research Alliance 'Health Technologies', Jena, Germany
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11
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Olaetxea I, Lopez E, Valero A, Seifert A. Determination of physiological lactate and pH by Raman spectroscopy. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:475-481. [PMID: 31945941 DOI: 10.1109/embc.2019.8856471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Lactate and pH values in human blood are important physiological parameters that can reflect serious pathological states as sepsis or hypoxia. In this study we demonstrate that we can determine lactate and pH values from blood samples by Raman spectroscopy combined with multivariate analysis at medically relevant resolution and reliability. The method prepares the base for new real-time in vivo analytics for a number of pathological cases and physiological control in competitive sports. We demonstrate the capability to resolve pH variations of 0.04 and lactate concentrations of 0.20 mM ex vivo.
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12
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Krafft C, Popp J. Medical needs for translational biophotonics with the focus on Raman‐based methods. TRANSLATIONAL BIOPHOTONICS 2019. [DOI: 10.1002/tbio.201900018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena Germany
- Institute of Physical Chemistry and Abbe Center of PhotonicsFriedrich Schiller University Jena Jena Germany
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Non-ionizing, laser radiation in Theranostics: The need for dosimetry and the role of Medical Physics. Phys Med 2019; 63:7-18. [DOI: 10.1016/j.ejmp.2019.05.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2019] [Revised: 05/10/2019] [Accepted: 05/20/2019] [Indexed: 01/30/2023] Open
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14
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Waterhouse DJ, Fitzpatrick CRM, Pogue BW, O'Connor JPB, Bohndiek SE. A roadmap for the clinical implementation of optical-imaging biomarkers. Nat Biomed Eng 2019; 3:339-353. [PMID: 31036890 DOI: 10.1038/s41551-019-0392-5] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Accepted: 03/17/2019] [Indexed: 02/07/2023]
Abstract
Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett's oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical-imaging technologies.
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Affiliation(s)
- Dale J Waterhouse
- Department of Physics, University of Cambridge, Cambridge, UK
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Catherine R M Fitzpatrick
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Department of Engineering, University of Cambridge, Cambridge, UK
| | | | | | - Sarah E Bohndiek
- Department of Physics, University of Cambridge, Cambridge, UK.
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
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Hernandez-Quintanar L, Rodriguez-Salvador M. Discovering new 3D bioprinting applications: Analyzing the case of optical tissue phantoms. Int J Bioprint 2018; 5:178. [PMID: 32596533 PMCID: PMC7294689 DOI: 10.18063/ijb.v5i1.178] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 12/18/2018] [Indexed: 11/25/2022] Open
Abstract
Optical tissue phantoms enable to mimic the optical properties of biological tissues for biomedical device calibration, new equipment validation, and clinical training for the detection, and treatment of diseases. Unfortunately, current methods for their development present some problems, such as a lack of repeatability in their optical properties. Where the use of three-dimensional (3D) printing or 3D bioprinting could address these issues. This paper aims to evaluate the use of this technology in the development of optical tissue phantoms. A competitive technology intelligence methodology was applied by analyzing Scopus, Web of Science, and patents from January 1, 2000, to July 31, 2018. The main trends regarding methods, materials, and uses, as well as predominant countries, institutions, and journals, were determined. The results revealed that, while 3D printing is already employed (in total, 108 scientific papers and 18 patent families were identified), 3D bioprinting is not yet applied for optical tissue phantoms. Nevertheless, it is expected to have significant growth. This research gives biomedical scientists a new window of opportunity for exploring the use of 3D bioprinting in a new area that may support testing of new equipment and development of techniques for the diagnosis and treatment of diseases.
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Wilson BC, Jermyn M, Leblond F. Challenges and opportunities in clinical translation of biomedical optical spectroscopy and imaging. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-13. [PMID: 29512358 PMCID: PMC5838403 DOI: 10.1117/1.jbo.23.3.030901] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 01/24/2018] [Indexed: 05/03/2023]
Abstract
Medical devices face many hurdles before they enter routine clinical practice to address unmet clinical needs. This is also the case for biomedical optical spectroscopy and imaging systems that are used here to illustrate the opportunities and challenges involved. Following initial concept, stages in clinical translation include instrument development, preclinical testing, clinical prototyping, clinical trials, prototype-to-product conversion, regulatory approval, commercialization, and finally clinical adoption and dissemination, all in the face of potentially competing technologies. Optical technologies face additional challenges from their being extremely diverse, often targeting entirely different diseases and having orders-of-magnitude differences in resolution and tissue penetration. However, these technologies can potentially address a wide variety of unmet clinical needs since they provide rich intrinsic biochemical and structural information, have high sensitivity and specificity for disease detection and localization, and are practical, safe (minimally invasive, nonionizing), and relatively affordable.
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Affiliation(s)
- Brian C. Wilson
- University of Toronto and Princess Margaret Cancer Centre/University Health Network, Department of Medical Biophysics, Toronto, Ontario, Canada
| | - Michael Jermyn
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States
| | - Frederic Leblond
- Polytechnique Montreal, Department of Engineering Physics, Montreal, Québec, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montreal, Québec, Canada
- Address all correspondence to: Frederic Leblond, E-mail:
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