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Wang F, Kim SH, Zhao Y, Raghuram A, Veeraraghavan A, Robinson J, Hielscher AH. High-Speed Time-Domain Diffuse Optical Tomography with a Sensitivity Equation-based Neural Network. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2023; 9:459-474. [PMID: 37456517 PMCID: PMC10348778 DOI: 10.1109/tci.2023.3273423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Steady progress in time-domain diffuse optical tomography (TD-DOT) technology is allowing for the first time the design of low-cost, compact, and high-performance systems, thus promising more widespread clinical TD-DOT use, such as for recording brain tissue hemodynamics. TD-DOT is known to provide more accurate values of optical properties and physiological parameters compared to its frequency-domain or steady-state counterparts. However, achieving high temporal resolution is still difficult, as solving the inverse problem is computationally demanding, leading to relatively long reconstruction times. The runtime is further compromised by processes that involve 'nontrivial' empirical tuning of reconstruction parameters, which increases complexity and inefficiency. To address these challenges, we present a new reconstruction algorithm that combines a deep-learning approach with our previously introduced sensitivity-equation-based, non-iterative sparse optical reconstruction (SENSOR) code. The new algorithm (called SENSOR-NET) unfolds the iterations of SENSOR into a deep neural network. In this way, we achieve high-resolution sparse reconstruction using only learned parameters, thus eliminating the need to tune parameters prior to reconstruction empirically. Furthermore, once trained, the reconstruction time is not dependent on the number of sources or wavelengths used. We validate our method with numerical and experimental data and show that accurate reconstructions with 1 mm spatial resolution can be obtained in under 20 milliseconds regardless of the number of sources used in the setup. This opens the door for real-time brain monitoring and other high-speed DOT applications.
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Affiliation(s)
- Fay Wang
- Department of Biomedical Engineering, Columbia University, New York, NY 10027
| | - Stephen H Kim
- Department of Biomedical Engineering, New York University - Tandon School of Engineering, New York, NY 10001
| | - Yongyi Zhao
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005
| | - Ankit Raghuram
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005
| | - Ashok Veeraraghavan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005
| | - Jacob Robinson
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005
| | - Andreas H Hielscher
- Department of Biomedical Engineering, New York University - Tandon School of Engineering, New York, NY 10001
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Lanka P, Yang L, Orive-Miguel D, Veesa JD, Tagliabue S, Sudakou A, Samaei S, Forcione M, Kovacsova Z, Behera A, Gladytz T, Grosenick D, Hervé L, Durduran T, Bejm K, Morawiec M, Kacprzak M, Sawosz P, Gerega A, Liebert A, Belli A, Tachtsidis I, Lange F, Bale G, Baratelli L, Gioux S, Alexander K, Wolf M, Sekar SKV, Zanoletti M, Pirovano I, Lacerenza M, Qiu L, Ferocino E, Maffeis G, Amendola C, Colombo L, Frabasile L, Levoni P, Buttafava M, Renna M, Di Sieno L, Re R, Farina A, Spinelli L, Dalla Mora A, Contini D, Taroni P, Tosi A, Torricelli A, Dehghani H, Wabnitz H, Pifferi A. Multi-laboratory performance assessment of diffuse optics instruments: the BitMap exercise. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210373SSR. [PMID: 35701869 PMCID: PMC9199954 DOI: 10.1117/1.jbo.27.7.074716] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 05/05/2022] [Indexed: 05/06/2023]
Abstract
SIGNIFICANCE Multi-laboratory initiatives are essential in performance assessment and standardization-crucial for bringing biophotonics to mature clinical use-to establish protocols and develop reference tissue phantoms that all will allow universal instrument comparison. AIM The largest multi-laboratory comparison of performance assessment in near-infrared diffuse optics is presented, involving 28 instruments and 12 institutions on a total of eight experiments based on three consolidated protocols (BIP, MEDPHOT, and NEUROPT) as implemented on three kits of tissue phantoms. A total of 20 synthetic indicators were extracted from the dataset, some of them defined here anew. APPROACH The exercise stems from the Innovative Training Network BitMap funded by the European Commission and expanded to include other European laboratories. A large variety of diffuse optics instruments were considered, based on different approaches (time domain/frequency domain/continuous wave), at various stages of maturity and designed for different applications (e.g., oximetry, spectroscopy, and imaging). RESULTS This study highlights a substantial difference in hardware performances (e.g., nine decades in responsivity, four decades in dark count rate, and one decade in temporal resolution). Agreement in the estimates of homogeneous optical properties was within 12% of the median value for half of the systems, with a temporal stability of <5 % over 1 h, and day-to-day reproducibility of <3 % . Other tests encompassed linearity, crosstalk, uncertainty, and detection of optical inhomogeneities. CONCLUSIONS This extensive multi-laboratory exercise provides a detailed assessment of near-infrared Diffuse optical instruments and can be used for reference grading. The dataset-available soon in an open data repository-can be evaluated in multiple ways, for instance, to compare different analysis tools or study the impact of hardware implementations.
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Affiliation(s)
- Pranav Lanka
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
- Address all correspondence to Pranav Lanka, ; Heidrun Wabnitz,
| | - Lin Yang
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | | | - Joshua Deepak Veesa
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | | | - Aleh Sudakou
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Saeed Samaei
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Mario Forcione
- University Hospitals Birmingham, National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham, United Kingdom
| | - Zuzana Kovacsova
- UCL, Department of Medical Physics & Biomedical Engineering, London, United Kingdom
| | - Anurag Behera
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | - Thomas Gladytz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Dirk Grosenick
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Lionel Hervé
- Université Grenoble Alpes, CEA, LETI, DTBS, Grenoble, France
| | - Turgut Durduran
- The Institute of Photonic Sciences (ICFO), Castelldefels, Spain
| | - Karolina Bejm
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Magdalena Morawiec
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Michał Kacprzak
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Piotr Sawosz
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Anna Gerega
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Antonio Belli
- University Hospitals Birmingham, National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham, United Kingdom
| | - Ilias Tachtsidis
- UCL, Department of Medical Physics & Biomedical Engineering, London, United Kingdom
| | - Frédéric Lange
- UCL, Department of Medical Physics & Biomedical Engineering, London, United Kingdom
| | - Gemma Bale
- University of Cambridge, Department of Engineering and Department of Physics, Cambridge, United Kingdom
| | - Luca Baratelli
- University of Strasbourg, ICube Laboratory, Strasbourg, France
| | - Sylvain Gioux
- University of Strasbourg, ICube Laboratory, Strasbourg, France
| | - Kalyanov Alexander
- University Hospital Zurich, Biomedical Optics Research Laboratory, Department of Neonatology, Zurich, Switzerland
| | - Martin Wolf
- University Hospital Zurich, Biomedical Optics Research Laboratory, Department of Neonatology, Zurich, Switzerland
| | | | - Marta Zanoletti
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | - Ileana Pirovano
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | | | - Lina Qiu
- South China Normal University, School of Software, Guangzhou, China
| | | | - Giulia Maffeis
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | | | - Lorenzo Colombo
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | | | - Pietro Levoni
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | | | - Marco Renna
- Istituto di Fotonica e Nanotecnologie, Milano, Italy
| | - Laura Di Sieno
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | - Rebecca Re
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
- Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Milano, Italy
| | - Andrea Farina
- Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Milano, Italy
| | - Lorenzo Spinelli
- Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Milano, Italy
| | | | - Davide Contini
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | - Paola Taroni
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
| | - Alberto Tosi
- Istituto di Fotonica e Nanotecnologie, Milano, Italy
| | | | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
- Address all correspondence to Pranav Lanka, ; Heidrun Wabnitz,
| | - Antonio Pifferi
- Politecnico di Milano, Dipartimento di Fisica, Milano, Italy
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Di Sieno L, Behera A, Rohilla S, Ferocino E, Contini D, Torricelli A, Krämer B, Koberling F, Pifferi A, Mora AD. Probe-hosted large area silicon photomultiplier and high-throughput timing electronics for enhanced performance time-domain functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2020; 11:6389-6412. [PMID: 33282497 PMCID: PMC7687960 DOI: 10.1364/boe.400868] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 09/21/2020] [Accepted: 10/07/2020] [Indexed: 05/06/2023]
Abstract
Two main bottlenecks prevent time-domain diffuse optics instruments to reach their maximum performances, namely the limited light harvesting capability of the detection chain and the bounded data throughput of the timing electronics. In this work, for the first time to our knowledge, we overcome both those limitations using a probe-hosted large area silicon photomultiplier detector coupled to high-throughput timing electronics. The system performances were assessed based on international protocols for diffuse optical imagers showing better figures with respect to a state-of-the-art device. As a first step towards applications, proof-of-principle in-vivo brain activation measurements demonstrated superior signal-to-noise ratio as compared to current technologies.
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Affiliation(s)
- L. Di Sieno
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - A. Behera
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - S. Rohilla
- PicoQuant Innovation GmbH, Rudower Chaussee 29, 12489 Berlin, Germany
- Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu and Berlin Institute of Health, Department of Internal Medicine/Infectious Diseases and Respiratory Medicine, Charitéplatz 1, 10117 Berlin, Germany
| | - E. Ferocino
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - D. Contini
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - A. Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - B. Krämer
- PicoQuant GmbH, Rudower Chaussee 29, 12489 Berlin, Germany
| | - F. Koberling
- PicoQuant GmbH, Rudower Chaussee 29, 12489 Berlin, Germany
| | - A. Pifferi
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
- Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
| | - A. Dalla Mora
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
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