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Khan AF, Zhang F, Shou G, Yuan H, Ding L. Transient brain-wide coactivations and structured transitions revealed in hemodynamic imaging data. Neuroimage 2022; 260:119460. [PMID: 35868615 PMCID: PMC9472706 DOI: 10.1016/j.neuroimage.2022.119460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 11/17/2022] Open
Abstract
Brain-wide patterns in resting human brains, as either structured functional connectivity (FC) or recurring brain states, have been widely studied in the neuroimaging literature. In particular, resting-state FCs estimated over windowed timeframe neuroimaging data from sub-minutes to minutes using correlation or blind source separation techniques have reported many brain-wide patterns of significant behavioral and disease correlates. The present pilot study utilized a novel whole-head cap-based high-density diffuse optical tomography (DOT) technology, together with data-driven analysis methods, to investigate recurring transient brain-wide patterns in spontaneous fluctuations of hemodynamic signals at the resolution of single timeframes from thirteen healthy adults in resting conditions. Our results report that a small number, i.e., six, of brain-wide coactivation patterns (CAPs) describe major spatiotemporal dynamics of spontaneous hemodynamic signals recorded by DOT. These CAPs represent recurring brain states, showing spatial topographies of hemispheric symmetry, and exhibit highly anticorrelated pairs. Moreover, a structured transition pattern among the six brain states is identified, where two CAPs with anterior-posterior spatial patterns are significantly involved in transitions among all brain states. Our results further elucidate two brain states of global positive and negative patterns, indicating transient neuronal coactivations and co-deactivations, respectively, over the entire cortex. We demonstrate that these two brain states are responsible for the generation of a subset of peaks and troughs in global signals (GS), supporting the recent reports on neuronal relevance of hemodynamic GS. Collectively, our results suggest that transient neuronal events (i.e., CAPs), global brain activity, and brain-wide structured transitions co-exist in humans and these phenomena are closely related, which extend the observations of similar neuronal events recently reported in animal hemodynamic data. Future studies on the quantitative relationship among these transient events and their relationships to windowed FCs along with larger sample size are needed to understand their changes with behaviors and diseased conditions.
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Affiliation(s)
- Ali Fahim Khan
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Fan Zhang
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Guofa Shou
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, 110 W. Boyd St. DEH room 150, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, USA.
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Dooley M, Paterson T, Dexter L, Matousek P, Dehghani H, Notingher I. Model-Based Optimization of Laser Excitation and Detection Improves Spectral Contrast in Noninvasive Diffuse Raman Spectroscopy. APPLIED SPECTROSCOPY 2022; 76:801-811. [PMID: 35081779 DOI: 10.1177/00037028211072900] [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] [Indexed: 05/04/2023]
Abstract
Spatially offset Raman spectroscopy (SORS) is a powerful technique for subsurface molecular analysis of optically turbid samples. Numerical modeling of light propagation has been used to investigate opportunities for improving spectral contrast and signal to noise ratio when imaging regions of interest located 0-4.5 mm below the surface in polymer bulk material. Two- and three-dimensional modeling results demonstrate that when analyzing a certain region of interest (ROI) of finite lateral dimensions below the sample surface, offsetting both the laser source and detector in opposite directions from the central point of the ROI can increase the spectral contrast as compared to conventional SORS approach where the detector or the laser source is maintained at the central point (centered SORS). The outlined modeling results have been validated experimentally using a bulk polymer sample with a trans-stilbene ROI (cylinder) below the sample surface. The results show that modeling of the spatial configurations of laser excitation and detection points can be used to optimize the instrument configuration to achieve significant improvements (up to 2.25-fold) in performance over the conventional centered SORS. Such optimal solutions can then be implemented, for example, using robust fiber optic probes, moveable optics, or flexible spatial light modulator instruments for specific applications.
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Affiliation(s)
- Max Dooley
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Thomas Paterson
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Louise Dexter
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
| | - Pavel Matousek
- Central Laser Facility, UK Research and Innovation (UKRI), STFC Rutherford Appleton Laboratory, Harwell Oxford, UK
| | - Hamid Dehghani
- School of Computer Sciences, 1724University of Birmingham, Birmingham, UK
| | - Ioan Notingher
- School of Physics and Astronomy, 6123University of Nottingham, Nottingham, UK
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Pacheco A, Jayet B, Svanberg EK, Dehghani H, Dempsey E, Andersson-Engels S. Numerical investigation of the influence of the source and detector position for optical measurement of lung volume and oxygen content in preterm infants. JOURNAL OF BIOPHOTONICS 2022; 15:e202200041. [PMID: 35340113 DOI: 10.1002/jbio.202200041] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
There is an urgent need for improved respiratory surveillance of preterm infants. Gas in scattering media absorption spectroscopy (GASMAS) is emerging as a potential clinical cutaneous monitoring tool of lung functions in neonates. A challenge in the clinical translation of GASMAS is to obtain sufficiently high signal-to-noise ratios in the measurements, since the light attenuation is high in human tissue. Previous GASMAS studies on piglets have shown higher signal quality with an internal source, as more light propagates through the lung and the loss due to scattering and absorption is less. In this article we simulated light propagation with an intratracheal and a dermal source, and investigated the signal quality and lung volume probed. The results suggest that GASMAS has the potential to measure respiratory volumes; and the sensitivity is higher for an intratracheal source which also enables to probe most of the lung.
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Affiliation(s)
- Andrea Pacheco
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
| | - Baptiste Jayet
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Emilie Krite Svanberg
- Department of Clinical Sciences, Paediatric Anaesthesiology and Intensive Care Medicine, Skåne University Hospital, Lund University, Lund, Sweden
| | - Hamid Dehghani
- School of Computer Science, the University of Birmingham, Birmingham
| | - Eugene Dempsey
- INFANT Centre, Cork University Maternity Hospital, University College Cork, Ireland
| | - Stefan Andersson-Engels
- Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
- Department of Physics, University College Cork, Cork, Ireland
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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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Zhu Y, Ni L, Hu G, Johnson LA, Eaton KA, Wang X, Higgins PDR, Xu G. Prototype endoscopic photoacoustic-ultrasound balloon catheter for characterizing intestinal obstruction. BIOMEDICAL OPTICS EXPRESS 2022; 13:3355-3365. [PMID: 35781972 PMCID: PMC9208587 DOI: 10.1364/boe.456672] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/03/2022] [Accepted: 04/05/2022] [Indexed: 06/14/2023]
Abstract
In our previous studies, we have demonstrated the feasibility of characterizing intestinal inflammation and fibrosis using endoscopic photoacoustic imaging. Purposed at te clinical translation of the imaging technology, we developed a photoacoustic/ultrasound imaging probe by integrating a miniaturized ultrasound array and an angle-tipped optical fiber in a hydrostatic balloon catheter. When collapsed, the catheter probe may potentially be compatible with a clinical ileo-colonoscope. In addition, the flexible surface of the hydrostatic balloon allows for acoustic coupling at the uneven surfaces of the gas-filled intestine. Tissue phantom studies show that the catheter probe possesses an imaging penetration of at least 12 mm. Experiments with a rabbit model in vivo validated the probe in differentiating normal, acute and chronic conditions in intestinal obstruction.
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Affiliation(s)
- Yunhao Zhu
- Department of Biomedical Engineering, University of Michigan, USA
| | - Linyu Ni
- Department of Biomedical Engineering, University of Michigan, USA
| | - Guorong Hu
- Department of Biomedical Engineering, University of Michigan, USA
| | | | - Kathryn A. Eaton
- Department of Microbiology and Immunology, University of Michigan, USA
| | - Xueding Wang
- Department of Biomedical Engineering, University of Michigan, USA
| | | | - Guan Xu
- Department of Biomedical Engineering, University of Michigan, USA
- Department of Ophthalmology and Visual Sciences, University of Michigan, USA
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56
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Bentley A, Xu X, Deng Z, Rowe JE, Kang-Hsin Wang K, Dehghani H. Quantitative molecular bioluminescence tomography. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-220026GRR. [PMID: 35726130 PMCID: PMC9207518 DOI: 10.1117/1.jbo.27.6.066004] [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: 02/08/2022] [Accepted: 05/27/2022] [Indexed: 06/15/2023]
Abstract
SIGNIFICANCE Bioluminescence imaging and tomography (BLT) are used to study biologically relevant activity, typically within a mouse model. A major limitation is that the underlying optical properties of the volume are unknown, leading to the use of a "best" estimate approach often compromising quantitative accuracy. AIM An optimization algorithm is presented that localizes the spatial distribution of bioluminescence by simultaneously recovering the optical properties and location of bioluminescence source from the same set of surface measurements. APPROACH Measured data, using implanted self-illuminating sources as well as an orthotopic glioblastoma mouse model, are employed to recover three-dimensional spatial distribution of the bioluminescence source using a multi-parameter optimization algorithm. RESULTS The proposed algorithm is able to recover the size and location of the bioluminescence source while accounting for tissue attenuation. Localization accuracies of <1 mm are obtained in all cases, which is similar if not better than current "gold standard" methods that predict optical properties using a different imaging modality. CONCLUSIONS Application of this approach, using in-vivo experimental data has shown that quantitative BLT is possible without the need for any prior knowledge about optical parameters, paving the way toward quantitative molecular imaging of exogenous and indigenous biological tumor functionality.
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Affiliation(s)
- Alexander Bentley
- University of Birmingham, School of Computer Science, College of Engineering and Physical Sciences, Birmingham, United Kingdom
- University of Birmingham, College of Engineering and Physical Sciences, Physical Sciences for Health Doctoral Training Centre, Birmingham, United Kingdom
| | - Xiangkun Xu
- University of Texas Southwestern Medical Center, Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, Dallas, Texas, United States
- Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, Maryland, United States
| | - Zijian Deng
- University of Texas Southwestern Medical Center, Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, Dallas, Texas, United States
- Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, Maryland, United States
| | - Jonathan E. Rowe
- University of Birmingham, School of Computer Science, College of Engineering and Physical Sciences, Birmingham, United Kingdom
| | - Ken Kang-Hsin Wang
- University of Texas Southwestern Medical Center, Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, Dallas, Texas, United States
- Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, Maryland, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, College of Engineering and Physical Sciences, Birmingham, United Kingdom
- University of Birmingham, College of Engineering and Physical Sciences, Physical Sciences for Health Doctoral Training Centre, Birmingham, United Kingdom
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Bürmen M, Pernuš F, Naglič P. MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python package. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210365SSRRR. [PMID: 35437973 PMCID: PMC9016074 DOI: 10.1117/1.jbo.27.8.083012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 03/18/2022] [Indexed: 05/16/2023]
Abstract
SIGNIFICANCE Current open-source Monte Carlo (MC) method implementations for light propagation modeling are many times tedious to build and require third-party licensed software that can often discourage prospective researchers in the biomedical optics community from fully utilizing the light propagation tools. Furthermore, the same drawback also limits rigorous cross-validation of physical quantities estimated by various MC codes. AIM Proposal of an open-source tool for light propagation modeling and an easily accessible dataset to encourage fruitful communications amongst researchers and pave the way to a more consistent comparison between the available implementations of the MC method. APPROACH The PyXOpto implementation of the MC method for multilayered and voxelated tissues based on the Python programming language and PyOpenCL extension enables massively parallel computation on numerous OpenCL-enabled devices. The proposed implementation is used to compute a large dataset of reflectance, transmittance, energy deposition, and sampling volume for various source, detector, and tissue configurations. RESULTS The proposed PyXOpto agrees well with the original MC implementation. However, further validation reveals a noticeable bias introduced by the random number generator used in the original MC implementation. CONCLUSIONS Establishing a common dataset is highly important for the validation of existing and development of MC codes for light propagation in turbid media.
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Affiliation(s)
- Miran Bürmen
- University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia
| | - Franjo Pernuš
- University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia
- Sensum d.o.o., Ljubljana, Slovenia
| | - Peter Naglič
- University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia
- Address all correspondence to Peter Naglič,
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Wojtkiewicz S, Bejm K, Liebert A. Lock-in functional near-infrared spectroscopy for measurement of the haemodynamic brain response. BIOMEDICAL OPTICS EXPRESS 2022; 13:1869-1887. [PMID: 35519260 PMCID: PMC9045899 DOI: 10.1364/boe.448038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/13/2022] [Accepted: 02/15/2022] [Indexed: 06/14/2023]
Abstract
Here we show a method of the lock-in amplifying near-infrared signals originating within a human brain. It implies using two 90-degree rotated source-detector pairs fixed on a head surface. Both pairs have a joint sensitivity region located towards the brain. A direct application of the lock-in technique on both signals results in amplifying common frequency components, e.g. related to brain cortex stimulation and attenuating the rest, including all components not related to the stimulation: e.g. pulse, instrumental and biological noise or movement artefacts. This is a self-driven method as no prior assumptions are needed and the noise model is provided by the interfering signals themselves. We show the theory (classical modified Beer-Lambert law and diffuse optical tomography approaches), the algorithm implementation and tests on a finite element mathematical model and in-vivo on healthy volunteers during visual cortex stimulation. The proposed hardware and algorithm complexity suit the entire spectrum of (continuous wave, frequency domain, time-resolved) near-infrared spectroscopy systems featuring real-time, direct, robust and low-noise brain activity registration tool. As such, this can be of special interest in optical brain computer interfaces and high reliability/stability monitors of tissue oxygenation.
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Affiliation(s)
- Stanislaw Wojtkiewicz
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Trojdena 4, 02-109, Poland
| | - Karolina Bejm
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Trojdena 4, 02-109, Poland
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Trojdena 4, 02-109, Poland
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Balasubramaniam GM, Arnon S. Regression-based neural network for improving image reconstruction in diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2022; 13:2006-2017. [PMID: 35519246 PMCID: PMC9045936 DOI: 10.1364/boe.449448] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 05/02/2023]
Abstract
Diffuse optical tomography (DOT) is a non-invasive imaging technique utilizing multi-scattered light at visible and infrared wavelengths to detect anomalies in tissues. However, the DOT image reconstruction is based on solving the inverse problem, which requires massive calculations and time. In this article, for the first time, to the best of our knowledge, a simple, regression-based cascaded feed-forward deep learning neural network is derived to solve the inverse problem of DOT in compressed breast geometry. The predicted data is subsequently utilized to visualize the breast tissues and their anomalies. The dataset in this study is created using a Monte-Carlo algorithm, which simulates the light propagation in the compressed breast placed inside a parallel plate source-detector geometry (forward process). The simulated DL-DOT system's performance is evaluated using the Pearson correlation coefficient (R) and the Mean squared error (MSE) metrics. Although a comparatively smaller dataset (50 nos.) is used, our simulation results show that the developed feed-forward network algorithm to solve the inverse problem delivers an increment of ∼30% over the analytical solution approach, in terms of R. Furthermore, the proposed network's MSE outperforms that of the analytical solution's MSE by a large margin revealing the robustness of the network and the adaptability of the system for potential applications in medical settings.
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Zhang Y, Fang Q. BlenderPhotonics: an integrated open-source software environment for three-dimensional meshing and photon simulations in complex tissues. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:083014. [PMID: 35429155 PMCID: PMC9010662 DOI: 10.1117/1.jbo.27.8.083014] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 03/23/2022] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE Rapid advances in biophotonics techniques require quantitative, model-based computational approaches to obtain functional and structural information from increasingly complex and multiscaled anatomies. The lack of efficient tools to accurately model tissue structures and subsequently perform quantitative multiphysics modeling greatly impedes the clinical translation of these modalities. AIM Although the mesh-based Monte Carlo (MMC) method expands our capabilities in simulating complex tissues using tetrahedral meshes, the generation of such domains often requires specialized meshing tools, such as Iso2Mesh. Creating a simplified and intuitive interface for tissue anatomical modeling and optical simulations is essential toward making these advanced modeling techniques broadly accessible to the user community. APPROACH We responded to the above challenge by combining the powerful, open-source three-dimensional (3D) modeling software, Blender, with state-of-the-art 3D mesh generation and MC simulation tools, utilizing the interactive graphical user interface in Blender as the front-end to allow users to create complex tissue mesh models and subsequently launch MMC light simulations. RESULTS Here, we present a tutorial to our Python-based Blender add-on-BlenderPhotonics-to interface with Iso2Mesh and MMC, which allows users to create, configure and refine complex simulation domains and run hardware-accelerated 3D light simulations with only a few clicks. We provide a comprehensive introduction to this tool and walk readers through five examples, ranging from simple shapes to sophisticated realistic tissue models. CONCLUSIONS BlenderPhotonics is user friendly and open source, and it leverages the vastly rich ecosystem of Blender. It wraps advanced modeling capabilities within an easy-to-use and interactive interface. The latest software can be downloaded at http://mcx.space/bp.
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Affiliation(s)
- Yuxuan Zhang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
- Northeastern University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
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Wang H, Feng T, Dong X, Zhao Z, Han G, Wang J, Ma W, Wang R, Liu M, Miao J. Method for improving the accuracy of fluorescence molecular tomography based on multi-wavelength concurrent reconstruction. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:044102. [PMID: 35489912 DOI: 10.1063/5.0056883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
A Concurrent-wavelength Reconstruction Algorithm (CRA) based on multi-wavelength information fusion is proposed in this paper that aims to further improve the accuracy of Fluorescence Molecular Tomography (FMT) reconstruction. Combining multi-spectral data with FMT technology, the information of 650 and 750 nm wavelengths near-infrared was used to increase the feature information of the dominant 850 nm wavelength near-infrared effectively. Principal component analysis, which can remove redundant information and achieve data dimensionality reduction, was then utilized to extract the feature information. Finally, tomographic reconstruction of the anomalies was performed based on the stacked auto-encoder neural network model. The comparison results of numerical experiments showed that the reconstruction effect of CRA was superior to the performance of the single wavelength model. The correlation coefficient between CRA reconstructed anomalies' fluorescence yield values and the real fluorescence yield values remained at 0.95 or more under the noise of different levels of signal-to-noise ratios. Therefore, the CRA proposed in this paper could effectively improve on the ill-posedness of the inverse problem, which could further enhance the accuracy of FMT reconstruction.
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Affiliation(s)
- Huiquan Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Tianzi Feng
- School of Electronic and Information Engineering, Tiangong University, Tianjin 300387, China
| | - Xinming Dong
- The Center of Tianjin Rehabilitation and Sanatorium, Tianjin 300387, China
| | - Zhe Zhao
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Guang Han
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Jinhai Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Wenjuan Ma
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China
| | - Rong Wang
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Minghu Liu
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Jinghong Miao
- School of Life Sciences, Tiangong University, Tianjin 300387, China
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Gröhl J, Dreher KK, Schellenberg M, Rix T, Holzwarth N, Vieten P, Ayala L, Bohndiek SE, Seitel A, Maier-Hein L. SIMPA: an open-source toolkit for simulation and image processing for photonics and acoustics. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210395SSR. [PMID: 35380031 PMCID: PMC8978263 DOI: 10.1117/1.jbo.27.8.083010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/28/2022] [Indexed: 05/09/2023]
Abstract
SIGNIFICANCE Optical and acoustic imaging techniques enable noninvasive visualisation of structural and functional properties of tissue. The quantification of measurements, however, remains challenging due to the inverse problems that must be solved. Emerging data-driven approaches are promising, but they rely heavily on the presence of high-quality simulations across a range of wavelengths due to the lack of ground truth knowledge of tissue acoustical and optical properties in realistic settings. AIM To facilitate this process, we present the open-source simulation and image processing for photonics and acoustics (SIMPA) Python toolkit. SIMPA is being developed according to modern software design standards. APPROACH SIMPA enables the use of computational forward models, data processing algorithms, and digital device twins to simulate realistic images within a single pipeline. SIMPA's module implementations can be seamlessly exchanged as SIMPA abstracts from the concrete implementation of each forward model and builds the simulation pipeline in a modular fashion. Furthermore, SIMPA provides comprehensive libraries of biological structures, such as vessels, as well as optical and acoustic properties and other functionalities for the generation of realistic tissue models. RESULTS To showcase the capabilities of SIMPA, we show examples in the context of photoacoustic imaging: the diversity of creatable tissue models, the customisability of a simulation pipeline, and the degree of realism of the simulations. CONCLUSIONS SIMPA is an open-source toolkit that can be used to simulate optical and acoustic imaging modalities. The code is available at: https://github.com/IMSY-DKFZ/simpa, and all of the examples and experiments in this paper can be reproduced using the code available at: https://github.com/IMSY-DKFZ/simpa_paper_experiments.
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Affiliation(s)
- Janek Gröhl
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Kris K. Dreher
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Physics and Astronomy, Heidelberg, Germany
| | - Melanie Schellenberg
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
- HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg, Germany
| | - Tom Rix
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
| | - Niklas Holzwarth
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Patricia Vieten
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Physics and Astronomy, Heidelberg, Germany
| | - Leonardo Ayala
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Medical Faculty, Heidelberg, Germany
| | - Sarah E. Bohndiek
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, United Kingdom
- University of Cambridge, Department of Physics, Cambridge, United Kingdom
| | - Alexander Seitel
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Lena Maier-Hein
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Heidelberg University, Faculty of Mathematics and Computer Science, Heidelberg, Germany
- Heidelberg University, Medical Faculty, Heidelberg, Germany
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Feng J, Zhang W, Li Z, Jia K, Jiang S, Dehghani H, Pogue BW, Paulsen KD. Deep-learning based image reconstruction for MRI-guided near-infrared spectral tomography. OPTICA 2022; 9:264-267. [PMID: 35340570 PMCID: PMC8952193 DOI: 10.1364/optica.446576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/12/2022] [Indexed: 05/02/2023]
Abstract
Non-invasive near-infrared spectral tomography (NIRST) can incorporate the structural information provided by simultaneous magnetic resonance imaging (MRI), and this has significantly improved the images obtained of tissue function. However, the process of MRI guidance in NIRST has been time consuming because of the needs for tissue-type segmentation and forward diffuse modeling of light propagation. To overcome these problems, a reconstruction algorithm for MRI-guided NIRST based on deep learning is proposed and validated by simulation and real patient imaging data for breast cancer characterization. In this approach, diffused optical signals and MRI images were both used as the input to the neural network, and simultaneously recovered the concentrations of oxy-hemoglobin, deoxy-hemoglobin, and water via end-to-end training by using 20,000 sets of computer-generated simulation phantoms. The simulation phantom studies showed that the quality of the reconstructed images was improved, compared to that obtained by other existing reconstruction methods. Reconstructed patient images show that the well-trained neural network with only simulation data sets can be directly used for differentiating malignant from benign breast tumors.
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Affiliation(s)
- Jinchao Feng
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Wanlong Zhang
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Zhe Li
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Kebin Jia
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
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64
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Yin W, Li X, Cao Q, Wang H, Zhang B. Bioluminescence tomography reconstruction in conjunction with an organ probability map as an anatomical reference. BIOMEDICAL OPTICS EXPRESS 2022; 13:1275-1291. [PMID: 35414991 PMCID: PMC8973175 DOI: 10.1364/boe.448862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/15/2022] [Accepted: 01/23/2022] [Indexed: 06/14/2023]
Abstract
To alleviate the ill-posedness of bioluminescence tomography (BLT) reconstruction, anatomical information from computed tomography (CT) or magnetic resonance imaging (MRI) is usually adopted to improve the reconstruction quality. With the anatomical information, different organs could be segmented and assigned with appropriate optical parameters, and the reconstruction could be confined into certain organs. However, image segmentation is a time-consuming and challenging work, especially for the low-contrast organs. In this paper, we present a BLT reconstruction method in conjunction with an organ probability map to effectively incorporate the anatomical information. Instead of using a segmentation with a fixed organ map, an organ probability map is established by registering the CT image of the mouse to the statistical mouse atlas with the constraints of the mouse surface and high-contrast organs (bone and lung). Then the organ probability map of the low-contrast organs, such as the liver and kidney, is determined automatically. After discretization of the mouse torso, a heterogeneous model is established as the input for reconstruction, in which the optical parameter of each node is calculated according to the organ probability map. To take the advantage of the sparse Bayesian Learning (SBL) method in recovering block sparse signals in inverse problems, which is common in BLT applications where the target distribution has the characteristic of sparsity and block structure, a two-step method in conjunction with the organ probability map is presented. In the first step, a fast sparse algorithm, L1-LS, is used to reveal the source distribution on the organ level. In the second step, the bioluminescent source is reconstructed on the pixel level based on the SBL method. Both simulation and in vivo experiments are conducted, and the results demonstrate that the organ probability map in conjunction with the proposed two-step BLT reconstruction method is feasible to accurately reconstruct the localization of the bioluminescent light source.
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Affiliation(s)
- Wanzhou Yin
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
- Contributed equally
| | - Xiang Li
- Department of Radiology, the Second Hospital of Dalian Medial University, Dalian, Liaoning 116023, China
- Contributed equally
| | - Qian Cao
- Department of Radiology, the Second Hospital of Dalian Medial University, Dalian, Liaoning 116023, China
- Contributed equally
| | - Hongkai Wang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Bin Zhang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
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Ben Yedder H, Cardoen B, Shokoufi M, Golnaraghi F, Hamarneh G. Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:515-530. [PMID: 34606449 DOI: 10.1109/tmi.2021.3117276] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to assess its optical properties and identify abnormalities. DOT image reconstruction is an ill-posed problem due to the highly scattered photons in the medium and the smaller number of measurements compared to the number of unknowns. Limited-angle DOT reduces probe complexity at the cost of increased reconstruction complexity. Reconstructions are thus commonly marred by artifacts and, as a result, it is difficult to obtain an accurate reconstruction of target objects, e.g., malignant lesions. Reconstruction does not always ensure good localization of small lesions. Furthermore, conventional optimization-based reconstruction methods are computationally expensive, rendering them too slow for real-time imaging applications. Our goal is to develop a fast and accurate image reconstruction method using deep learning, where multitask learning ensures accurate lesion localization in addition to improved reconstruction. We apply spatial-wise attention and a distance transform based loss function in a novel multitask learning formulation to improve localization and reconstruction compared to single-task optimized methods. Given the scarcity of real-world sensor-image pairs required for training supervised deep learning models, we leverage physics-based simulation to generate synthetic datasets and use a transfer learning module to align the sensor domain distribution between in silico and real-world data, while taking advantage of cross-domain learning. Applying our method, we find that we can reconstruct and localize lesions faithfully while allowing real-time reconstruction. We also demonstrate that the present algorithm can reconstruct multiple cancer lesions. The results demonstrate that multitask learning provides sharper and more accurate reconstruction.
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66
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Wang Y, Li S, Wang Y, Yan Q, Wang X, Shen Y, Li Z, Kang F, Cao X, Zhu S. Compact fiber-free parallel-plane multi-wavelength diffuse optical tomography system for breast imaging. OPTICS EXPRESS 2022; 30:6469-6486. [PMID: 35299431 DOI: 10.1364/oe.448874] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/05/2022] [Indexed: 06/14/2023]
Abstract
To facilitate the clinical applicability of the diffuse optical inspection device, a compact multi-wavelength diffuse optical tomography system for breast imaging (compact-DOTB) with a fiber-free parallel-plane structure was designed and fabricated for acquiring three-dimensional optical properties of the breast in continuous-wave mode. The source array consists of 56 surface-mounted micro light-emitting diodes (LEDs), each integrating three wavelengths (660, 750, and 840 nm). The detector array is arranged with 56 miniaturized surface-mounted optical sensors, each encapsulating a high-sensitivity photodiode (PD) and a low-noise current amplifier with a gain of 24×. The system provides 3,136 pairs of source-detector measurements at each wavelength, and the fiber-free design largely ensures consistency between source/detection channels while effectively reducing the complexity of system operation and maintenance. We have evaluated the compact-DOTB system's characteristics and demonstrated its performance in terms of reconstruction positioning accuracy and recovery contrast with breast-sized phantom experiments. Furthermore, the breast cancer patient studies have been carried out, and the quantitative results indicate that the compact-DOTB system is able to observe the changes in the functional tissue components of the breast after receiving the neoadjuvant chemotherapy (NAC), demonstrating the great potential of the proposed compact system for clinical applications, while its cost and ease of operation are competitive with the existing breast-DOT devices.
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67
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Smith JT, Ochoa M, Faulkner D, Haskins G, Intes X. Deep learning in macroscopic diffuse optical imaging. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210288VRR. [PMID: 35218169 PMCID: PMC8881080 DOI: 10.1117/1.jbo.27.2.020901] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 02/09/2022] [Indexed: 05/02/2023]
Abstract
SIGNIFICANCE Biomedical optics system design, image formation, and image analysis have primarily been guided by classical physical modeling and signal processing methodologies. Recently, however, deep learning (DL) has become a major paradigm in computational modeling and has demonstrated utility in numerous scientific domains and various forms of data analysis. AIM We aim to comprehensively review the use of DL applied to macroscopic diffuse optical imaging (DOI). APPROACH First, we provide a layman introduction to DL. Then, the review summarizes current DL work in some of the most active areas of this field, including optical properties retrieval, fluorescence lifetime imaging, and diffuse optical tomography. RESULTS The advantages of using DL for DOI versus conventional inverse solvers cited in the literature reviewed herein are numerous. These include, among others, a decrease in analysis time (often by many orders of magnitude), increased quantitative reconstruction quality, robustness to noise, and the unique capability to learn complex end-to-end relationships. CONCLUSIONS The heavily validated capability of DL's use across a wide range of complex inverse solving methodologies has enormous potential to bring novel DOI modalities, otherwise deemed impractical for clinical translation, to the patient's bedside.
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Affiliation(s)
- Jason T. Smith
- Rensselaer Polytechnic Institute, Department of Biomedical Engineering, Troy, New York, United States
| | - Marien Ochoa
- Rensselaer Polytechnic Institute, Department of Biomedical Engineering, Troy, New York, United States
| | - Denzel Faulkner
- Rensselaer Polytechnic Institute, Department of Biomedical Engineering, Troy, New York, United States
| | - Grant Haskins
- Rensselaer Polytechnic Institute, Department of Biomedical Engineering, Troy, New York, United States
| | - Xavier Intes
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation and Imaging for Medicine, Troy, New York, United States
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68
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Li CL, Fisher CJ, Wilson BC, Weersink RA. Preclinical evaluation of a clinical prototype transrectal diffuse optical tomography system for monitoring photothermal therapy of focal prostate cancer. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210262RR. [PMID: 35106981 PMCID: PMC8806493 DOI: 10.1117/1.jbo.27.2.026001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 01/05/2022] [Indexed: 05/20/2023]
Abstract
SIGNIFICANCE Our work demonstrates in preclinical models that continuous-wave transrectal diffuse optical tomography (TRDOT) can be used to accurately monitor photothermal therapy (PTT) and, in particular, the progression of the photocoagulation boundary toward the rectum. When used in patients, this should prevent rectal damage during PTT, thereby achieving maximum treatment efficacy while ensuring safety, using a technology platform suitable for wide dissemination. AIM We aim to validate that TRDOT measurements analyzed using a shape-based image-reconstruction algorithm (SBDOT) allow localization of the photocoagulation boundary during PTT within ±1 mm toward the rectum in the transverse plane. APPROACH TRDOT measurements were performed in tissue-simulating phantoms, ex vivo tissues, and an in vivo canine prostate model. The accuracy and sensitivity of reconstructing the size and location of the coagulation zone were determined, based on changes in the tissue absorption and reduced scattering coefficients upon photocoagulation. The reconstruction also yields the native and coagulated tissue optical properties. RESULTS The TRDOT measurements and SBDOT reconstruction algorithm were confirmed to perform sufficiently well for clinical translation in PTT monitoring, recovering the location of the coagulation boundary within ±1 mm compared to the true value as determined by direct visualization postexcision and/or MRI. CONCLUSIONS Implementing previously described TRDOT instrumentation and SBDOT image reconstruction in different tissue models confirms the potential for clinincal translation, including required refinements of the system and reconstruction algorithm.
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Affiliation(s)
- Celina L. Li
- University of Toronto, Department of Medical Biophysics, Toronto, Canada
| | - Carl J. Fisher
- University Health Network, Princess Margaret Cancer Centre, Toronto, Canada
| | - Brian C. Wilson
- University of Toronto, Department of Medical Biophysics, Toronto, Canada
- University Health Network, Princess Margaret Cancer Centre, Toronto, Canada
| | - Robert A. Weersink
- University of Toronto, Department of Medical Biophysics, Toronto, Canada
- University Health Network, Princess Margaret Cancer Centre, Toronto, Canada
- University of Toronto, Department of Radiation Oncology, Toronto, Canada
- University of Toronto, Institute of Biomedical Engineering, Toronto, Canada
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69
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70
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Abstract
Diffuse optical tomography using deep learning is an emerging technology that has found impressive medical diagnostic applications. However, creating an optical imaging system that uses visible and near-infrared (NIR) light is not straightforward due to photon absorption and multi-scattering by tissues. The high distortion levels caused due to these effects make the image reconstruction incredibly challenging. To overcome these challenges, various techniques have been proposed in the past, with varying success. One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. This article attempts to provide researchers with the necessary background and tools to implement deep learning methods to solve diffuse optical tomography.
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71
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Ruesch A, McKnight JC, Fahlman A, Shinn-Cunningham BG, Kainerstorfer JM. Near-Infrared Spectroscopy as a Tool for Marine Mammal Research and Care. Front Physiol 2022; 12:816701. [PMID: 35111080 PMCID: PMC8801602 DOI: 10.3389/fphys.2021.816701] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Developments in wearable human medical and sports health trackers has offered new solutions to challenges encountered by eco-physiologists attempting to measure physiological attributes in freely moving animals. Near-infrared spectroscopy (NIRS) is one such solution that has potential as a powerful physio-logging tool to assess physiology in freely moving animals. NIRS is a non-invasive optics-based technology, that uses non-ionizing radiation to illuminate biological tissue and measures changes in oxygenated and deoxygenated hemoglobin concentrations inside tissues such as skin, muscle, and the brain. The overall footprint of the device is small enough to be deployed in wearable physio-logging devices. We show that changes in hemoglobin concentration can be recorded from bottlenose dolphins and gray seals with signal quality comparable to that achieved in human recordings. We further discuss functionality, benefits, and limitations of NIRS as a standard tool for animal care and wildlife tracking for the marine mammal research community.
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Affiliation(s)
- Alexander Ruesch
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
| | - J. Chris McKnight
- Sea Mammal Research Unit, University of St Andrews, St Andrews, United Kingdom
| | - Andreas Fahlman
- Fundación Oceanogràfic de la Comunitat Valenciana, Valencia, Spain
- Kolmården Wildlife Park, Kolmården, Sweden
| | - Barbara G. Shinn-Cunningham
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Jana M. Kainerstorfer
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
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72
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Lohrengel S, Mahmoudzadeh M, Oumri F, Salmon S, Wallois F. A homogenized cerebrospinal fluid model for diffuse optical tomography in the neonatal head. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2022; 38:e3538. [PMID: 34617416 DOI: 10.1002/cnm.3538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
Diffuse optical tomography is a non-invasive and non-irradiating medical imaging technique that is particularly suitable for cerebral monitoring of newborns since it can be used at the bedside of the patient. Here, a new model for optical tomography in the neonatal brain is presented that takes into account the presence of arachnoid trabeculae in the cerebrospinal fluid (CSF). It is known that the classical diffusion approximation (DA) for light propagation is at the limit of validity in the CSF layer due to the low values of the absorption and scattering coefficients. The new model is obtained by the DA of the homogenized radiative transfer equation and is rigorously justified. Numerical results in two and three dimensions attest for the improved sensitivity of the new model to the presence of perturbations in the brain layer.
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Affiliation(s)
- Stephanie Lohrengel
- Laboratoire de Mathématiques LMR CNRS UMR 9008, Université de Reims-Champagne Ardenne, Moulin de la Housse, Reims, France
| | - Mahdi Mahmoudzadeh
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, Amiens, France
| | - Farah Oumri
- Laboratoire de Mathématiques LMR CNRS UMR 9008, Université de Reims-Champagne Ardenne, Moulin de la Housse, Reims, France
| | - Stéphanie Salmon
- Laboratoire de Mathématiques LMR CNRS UMR 9008, Université de Reims-Champagne Ardenne, Moulin de la Housse, Reims, France
| | - Fabrice Wallois
- INSERM UMR-S 1105, GRAMFC, Université de Picardie-Jules Verne, CHU Sud, Amiens, France
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73
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Deng Z, Xu X, Dehghani H, Sforza DM, Iordachita I, Lim M, Wong JW, Wang KKH. Quantitative Bioluminescence Tomography for In Vivo Volumetric-Guided Radiotherapy. Methods Mol Biol 2022; 2393:701-731. [PMID: 34837208 PMCID: PMC9098109 DOI: 10.1007/978-1-0716-1803-5_38] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Several groups, including ours, have initiated efforts to develop small-animal irradiators that mimic radiation therapy (RT) for human treatment. The major image modality used to guide irradiation is cone-beam computed tomography (CBCT). While CBCT provides excellent guidance capability, it is less adept at localizing soft tissue targets growing in a low image contrast environment. In contrast, bioluminescence imaging (BLI) provides strong image contrast and thus is an attractive solution for soft tissue targeting. However, commonly used 2D BLI on an animal surface is inadequate to guide irradiation, because optical transport from an internal bioluminescent tumor is highly susceptible to the effects of optical path length and tissue absorption and scattering. Recognition of these limitations led us to integrate 3D bioluminescence tomography (BLT) with the small animal radiation research platform (SARRP). In this chapter, we introduce quantitative BLT (QBLT) with the advanced capabilities of quantifying tumor volume for irradiation guidance. The detail of system components, calibration protocol, and step-by-step procedure to conduct the QBLT-guided irradiation are described.
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Affiliation(s)
- Zijian Deng
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiangkun Xu
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - Daniel M Sforza
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Iulian Iordachita
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - John W Wong
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Ken Kang-Hsin Wang
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA.
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
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Numerical Optimisation of a NIRS Device for Monitoring Tissue Oxygen Saturation. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1395:411-416. [PMID: 36527671 DOI: 10.1007/978-3-031-14190-4_67] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The present work aims to develop a wearable, textile-integrated NIRS-based tissue oxygen saturation (StO2) monitor for alerting mobility-restricted individuals - such as paraplegics - of critical tissue oxygen de-saturation in the regions such as the sacrum and the ischial tuberosity; these regions are proven to be extremely susceptible to the development of pressure injuries (PI).Using a combination of numerical methods including finite element analysis, image reconstruction, stochastic gradient descent with momentum (SGDm) and genetic algorithms, a methodology was developed to define the optimal combination of wavelengths and source-detector geometry needed for measuring the StO2 in tissue up to depths of 3 cm. The sensor design was optimised to account for physiologically relevant adipose tissue thicknesses (ATT) between 1 mm and 5 mm. The approach assumes only a priori knowledge of the optical properties of each of the three tissue layers used in the model (skin, fat, muscle) based on the absorption and scattering coefficients of four chromophores (O2Hb, HHb, H2O and lipid).The results show that the selected wavelengths as well as the source-detector geometries and number of sources and detectors depend on ATT and the degree and volume of the hypoxic regions. As a result of a genetic algorithm used to combine the various optimised designs into a single sensor layout, a group of four wavelengths was chosen, coinciding with the four chromophores and agreeing very well with literature. The optimised number of source points and detector points and their geometry resulted in good reconstruction of the StO2 across a wide range of layer geometries.
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Hybrid Convolutional Neural Network (hCNN) for Image Reconstruction in Near-Infrared Optical Tomography. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1395:165-170. [PMID: 36527632 DOI: 10.1007/978-3-031-14190-4_28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Near-infrared optical tomography (NIROT), a promising imaging modality for early detection of oxygenation in the brain of preterm infants, requires data acquisition at the tissue surface and thus an image reconstruction adaptable to cephalometric variations and surface topologies. Widely used model-based reconstruction methods come with the drawback of huge computational cost. Neural networks move this computational load to an offline training phase, allowing much faster reconstruction. Our aim is a data-driven volumetric image reconstruction that generalises well to different surfaces, increases reconstruction speed, localisation accuracy and image quality. We propose a hybrid convolutional neural network (hCNN) based on the well-known V-net architecture to learn inclusion localisation and absorption coefficients of heterogenous arbitrary shapes via a joint cost function. We achieved an average reconstruction time of 30.45 s, a time reduction of 89% and inclusion detection with an average Dice score of 0.61. The CNN is flexible to surface topologies and compares well in quantitative metrics with the traditional model-based (MB) approach and state-of-the-art neuronal networks for NIROT. The proposed hCNN was successfully trained, validated and tested on in-silico data, excels MB methods in localisation accuracy and provides a remarkable increase in reconstruction speed.
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Jiang J, Costanzo Mata AD, Lindner S, Charbon E, Wolf M, Kalyanov A. 2.5 Hz sample rate time-domain near-infrared optical tomography based on SPAD-camera image tissue hemodynamics. BIOMEDICAL OPTICS EXPRESS 2022; 13:133-146. [PMID: 35154859 PMCID: PMC8803024 DOI: 10.1364/boe.441061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 11/12/2021] [Accepted: 11/15/2021] [Indexed: 05/31/2023]
Abstract
Time-domain near-infrared optical tomography (TD NIROT) techniques based on diffuse light were gaining performance over the last years. They are capable of imaging tissue at several centimeters depth and reveal clinically relevant information, such as tissue oxygen saturation. In this work, we present the very first in vivo results of our SPAD camera-based TD NIROT reflectance system with a temporal resolution of ∼116 ps. It provides 2800 time of flight source-detector pairs in a compact probe of only 6 cm in diameter. Additionally, we describe a 3-step reconstruction procedure that enables accurate recovery of structural information and of the optical properties. We demonstrate the system's performance firstly in reconstructing the 3D-structure of a heterogeneous tissue phantom with tissue-like scattering and absorption properties within a volume of 9 cm diameter and 5 cm thickness. Furthermore, we performed in vivo tomography of an index finger located within a homogeneous scattering medium. We employed a fast sampling rate of 2.5 Hz to detect changes in tissue oxygenation. Tomographic reconstructions were performed in true 3D, and without prior structural information, demonstrating the powerful capabilities of the system. This shows its potential for clinical applications.
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Affiliation(s)
- Jingjing Jiang
- Biomedical Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich / University Hospital Zurich, Switzerland
| | - Aldo Di Costanzo Mata
- Biomedical Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich / University Hospital Zurich, Switzerland
| | - Scott Lindner
- Biomedical Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich / University Hospital Zurich, Switzerland
- Advanced Quantum Architecture (AQUA) laboratory, School of Engineering, EPFL Lausanne, Switzerland
- now with ams OSRAM, Rüschlikon, Zurich, Switzerland
| | - Edoardo Charbon
- Advanced Quantum Architecture (AQUA) laboratory, School of Engineering, EPFL Lausanne, Switzerland
| | - Martin Wolf
- Biomedical Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich / University Hospital Zurich, Switzerland
| | - Alexander Kalyanov
- Biomedical Optics Research Laboratory (BORL), Dept. of Neonatology, University of Zurich / University Hospital Zurich, Switzerland
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Wang X, Hu R, Wang Y, Yan Q, Wang Y, Kang F, Zhu S. A Data Self-Calibration Method Based on High-Density Parallel Plate Diffuse Optical Tomography for Breast Cancer Imaging. Front Oncol 2021; 11:786289. [PMID: 34993144 PMCID: PMC8724432 DOI: 10.3389/fonc.2021.786289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/03/2021] [Indexed: 11/13/2022] Open
Abstract
When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruction. However, it is complicated to customize corresponding reference phantoms based on the breast shape and background optical parameters of different subjects in clinical trials. Furthermore, although high-density (HD) DOT configuration has been proven to improve imaging quality, a large number of source-detector (SD) pairs also increase the difficulty of multi-channel correction. To enhance the applicability of the breast DOT, a data self-calibration method based on an HD parallel-plate DOT system is proposed in this paper to replace the conventional relative measurement on a reference phantom. The reference predicted data can be constructed directly from the measurement data with the support of the HD-DOT system, which has nearly a hundred sets of measurements at each SD distance. The proposed scheme has been validated by Monte Carlo (MC) simulation, breast-size phantom experiments, and clinical trials, exhibiting the feasibility in ensuring the quality of the DOT reconstruction while effectively reducing the complexity associated with relative measurements on reference phantoms.
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Affiliation(s)
- Xin Wang
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Rui Hu
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Yirong Wang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Qiang Yan
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
| | - Yihan Wang
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
- *Correspondence: Yihan Wang, ; Shouping Zhu,
| | - Fei Kang
- Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Shouping Zhu
- School of Life Science and Technology, Xidian University, Xi’an, China
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xi’an, China
- *Correspondence: Yihan Wang, ; Shouping Zhu,
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78
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Nouizi F, Algarawi M, Erkol H, Luk A, Gulsen G. Multiwavelength photo-magnetic imaging algorithm improved for direct chromophore concentration recovery using spectral constraints. APPLIED OPTICS 2021; 60:10855-10861. [PMID: 35200850 DOI: 10.1364/ao.439250] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 11/12/2021] [Indexed: 06/14/2023]
Abstract
Multiwavelength photo-magnetic imaging (PMI) is a novel combination of diffuse optics and magnetic resonance imaging, to the best of our knowledge, that yields tissue chromophore concentration maps with high resolution and quantitative accuracy. Here, we present the first experimental results, to the best of our knowledge, obtained using a spectrally constrained PMI image reconstruction method, where chromophore concentration maps are directly recovered, unlike the conventional two-step approach that requires an intermediate step of reconstructing wavelength-dependent absorption coefficient maps. The imposition of the prior spectral information into the PMI inverse problem improves the reconstructed image quality and allows recovery of highly quantitative concentration maps, which are crucial for effective cancer detection and characterization. The obtained results demonstrate the higher performance of the direct reconstruction method. Indeed, the reconstructed concentration maps are not only of higher quality but also obtained approximately 2 times faster than the conventional method.
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79
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Agrawal S, Suresh T, Garikipati A, Dangi A, Kothapalli SR. Modeling combined ultrasound and photoacoustic imaging: Simulations aiding device development and artificial intelligence. PHOTOACOUSTICS 2021; 24:100304. [PMID: 34584840 PMCID: PMC8452892 DOI: 10.1016/j.pacs.2021.100304] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 09/01/2021] [Accepted: 09/08/2021] [Indexed: 05/07/2023]
Abstract
Combined ultrasound and photoacoustic (USPA) imaging has attracted several pre-clinical and clinical applications due to its ability to simultaneously display structural, functional, and molecular information of deep biological tissue in real time. However, the depth and wavelength dependent optical attenuation and the unknown optical and acoustic heterogeneities limit the USPA imaging performance in deep tissue regions. Novel instrumentation, image reconstruction, and artificial intelligence (AI) methods are currently being investigated to overcome these limitations and improve the USPA image quality. Effective implementation of these approaches requires a reliable USPA simulation tool capable of generating US based anatomical and PA based molecular contrasts of deep biological tissue. Here, we developed a hybrid USPA simulation platform by integrating finite element models of light (NIRFast) and ultrasound (k-Wave) propagations for co-simulation of B-mode US and PA images. The platform allows optimization of different design parameters for USPA devices, such as the aperture size and frequency of both light and ultrasound detector arrays. For designing tissue-realistic digital phantoms, a dictionary-based function has been added to k-Wave to generate various levels of ultrasound speckle contrast. The feasibility of modeling US imaging combined with optical fluence dependent multispectral PA imaging is demonstrated using homogeneous as well as heterogeneous tissue phantoms mimicking human organs (e.g., prostate and finger). In addition, we also demonstrate the potential of the simulation platform to generate large scale application-specific training and test datasets for AI enhanced USPA imaging. The complete USPA simulation codes together with the supplementary user guides have been posted to an open-source repository (https://github.com/KothapalliLabPSU/US-PA_simulation_codes).
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Affiliation(s)
- Sumit Agrawal
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
| | - Thaarakh Suresh
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Ankit Garikipati
- Department of Electrical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
| | - Ajay Dangi
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
- Penn State Cancer Institute, Pennsylvania State University, Hershey, PA, 17033, USA
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80
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Feng J, Jiang S, Pogue BW, Paulsen KD. Performance assessment of MRI guided continuous wave near-infrared spectral tomography for breast imaging. BIOMEDICAL OPTICS EXPRESS 2021; 12:7657-7672. [PMID: 35003858 PMCID: PMC8713687 DOI: 10.1364/boe.444131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 06/14/2023]
Abstract
Integration of magnetic resonance imaging (MRI) and near-infrared spectral tomography (NIRST) has yielded promising diagnostic performance for breast imaging in the past. This study focused on whether MRI-guided NIRST can quantify hemoglobin concentration using only continuous wave (CW) measurements. Patients were classified into four breast density groups based on their MRIs. Optical scattering properties were assigned based on average values obtained from these density groups, and MRI-guided NIRST images were reconstructed from calibrated CW data. Total hemoglobin (HbT) contrast between suspected lesions and surrounding normal tissue was used as an indicator of the malignancy. Results obtained from simulations and twenty-four patient cases indicate that the diagnostic power when using only CW data to differentiate malignant from benign abnormalities is similar to that obtained from combined frequency domain (FD) and CW data. These findings suggest that eliminating FD detection to reduce the cost and complexity of MRI-guided NIRST is possible.
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Affiliation(s)
- Jinchao Feng
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
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81
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Khan AF, Zhang F, Yuan H, Ding L. Brain-Wide Diffuse Optical Tomography Based on Cap-Based, Whole-Head fNIRS Recording. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:3609-3612. [PMID: 34892019 DOI: 10.1109/embc46164.2021.9630249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Diffuse optical tomography (DOT), based on functional near-infrared spectroscopy, is a portable, low-cost, noninvasive functional neuroimaging technology for studying the human brain in normal and diseased conditions. The goal of the present study was to evaluate the performance of a cap-based brain-wide DOT (BW-DOT) framework in mapping brain-wide networked activities. We first analyzed point-spread-function (PSF)-based metrics on a realistic head geometry. Our simulation results indicated that these metrics of the optode cap varied across the brain and were of lower quality in brain areas deep or away from the optodes. We further reconstructed brain-wide resting-state networks using experimental data from healthy participants, which resembled the template networks established in the fMRI literature. The preliminary results of the present study highlight the importance of evaluating PSF-based metrics on realistic head geometries for DOT and suggest that BW-DOT technology is a promising functional neuroimaging tool for studying brain-wide neural activities and large-scale neural networks, which was not available by patch-based DOT. A full-scope evaluation and validation in more realistic head models and more participants are needed in the future to establish the findings of the present study further.Clinical relevance- Via simulations and experimental evaluation, this work establishes a novel framework to image large-scale brain networks, which benefits the patient population, such as bedridden patients, infants, etc., who otherwise cannot undergo conventional brain monitoring modalities like fMRI and PET.
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82
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Biswas A, Moka S, Muller A, Parthasarathy AB. Fast diffuse correlation spectroscopy with a low-cost, fiber-less embedded diode laser. BIOMEDICAL OPTICS EXPRESS 2021; 12:6686-6700. [PMID: 34858674 PMCID: PMC8606156 DOI: 10.1364/boe.435136] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/20/2021] [Accepted: 09/21/2021] [Indexed: 06/02/2023]
Abstract
Diffuse correlation spectroscopy (DCS), a popular optical technique for fast noninvasive measurement of blood flow, is commonly implemented using expensive fiber-coupled long coherence length laser systems. Here, we report the development of a portable and fiber-less approach that can be used as a low-cost alternative to illuminate tissue in DCS instruments. We validate the accuracy and noise characteristics of the fiber-less DCS laser source, by comparisons against traditional DCS light sources, with experiments on controlled tissue-simulating phantoms and in humans.
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Affiliation(s)
- Arindam Biswas
- Department of Electrical Engineering, University of South Florida, 4202 E. Fowler Avenue, ENG030, Tampa, FL 33620, USA
| | - Sadhu Moka
- Department of Electrical Engineering, University of South Florida, 4202 E. Fowler Avenue, ENG030, Tampa, FL 33620, USA
| | - Andreas Muller
- Department of Physics, University of South Florida, 4202 E. Fowler Avenue, ISA2019, Tampa, FL 33620, USA
| | - Ashwin B. Parthasarathy
- Department of Electrical Engineering, University of South Florida, 4202 E. Fowler Avenue, ENG030, Tampa, FL 33620, USA
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Diagnostic validity of early proximal caries detection using near-infrared imaging technology on 3D range data of posterior teeth. Clin Oral Investig 2021; 26:543-553. [PMID: 34636940 PMCID: PMC8791888 DOI: 10.1007/s00784-021-04032-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/09/2021] [Indexed: 11/04/2022]
Abstract
Objectives This in vitro study analysed potential of early proximal caries detection using 3D range data of teeth consisting of near-infrared reflection images at 850 nm (NIRR). Materials and methods Two hundred fifty healthy and carious permanent human teeth were arranged pairwise, examined with bitewing radiography (BWR) and NIRR and validated with micro-computed tomography. NIRR findings were evaluated from buccal, lingual and occlusal (trilateral) views according to yes/no decisions about presence of caries. Reliability assessments included kappa statistics and revealed high agreement for both methods. Statistical analysis included cross tabulation and calculation of sensitivity, specificity and AUC. Results Underestimation of caries was 24.8% for NIRR and 26.4% for BWR. Overestimation was 10.4% for occlusal NIRR and 0% for BWR. Trilateral NIRR had overall accuracy of 64.8%, overestimation of 15.6% and underestimation of 19.6%. NIRR and BWR showed high specificity and low sensitivity for proximal caries detection. Conclusions NIRR achieved diagnostic results comparable to BWR. Trilateral NIRR assessments overestimated presence of proximal caries, revealing stronger sensitivity for initial caries detection than BWR. Clinical relevance NIRR provided valid complement to BWR as diagnostic instrument. Investigation from multiple angles did not substantially improve proximal caries detection with NIRR.
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84
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A scalable open-source MATLAB toolbox for reconstruction and analysis of multispectral optoacoustic tomography data. Sci Rep 2021; 11:19872. [PMID: 34615891 PMCID: PMC8494751 DOI: 10.1038/s41598-021-97726-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 08/17/2021] [Indexed: 12/03/2022] Open
Abstract
Multispectral photoacoustic tomography enables the resolution of spectral components of a tissue or sample at high spatiotemporal resolution. With the availability of commercial instruments, the acquisition of data using this modality has become consistent and standardized. However, the analysis of such data is often hampered by opaque processing algorithms, which are challenging to verify and validate from a user perspective. Furthermore, such tools are inflexible, often locking users into a restricted set of processing motifs, which may not be able to accommodate the demands of diverse experiments. To address these needs, we have developed a Reconstruction, Analysis, and Filtering Toolbox to support the analysis of photoacoustic imaging data. The toolbox includes several algorithms to improve the overall quantification of photoacoustic imaging, including non-negative constraints and multispectral filters. We demonstrate various use cases, including dynamic imaging challenges and quantification of drug effect, and describe the ability of the toolbox to be parallelized on a high performance computing cluster.
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85
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Ioussoufovitch S, Cohen DJF, Milej D, Diop M. Compressed sensing time-resolved spectrometer for quantification of light absorbers in turbid media. BIOMEDICAL OPTICS EXPRESS 2021; 12:6442-6460. [PMID: 34745748 PMCID: PMC8547999 DOI: 10.1364/boe.433427] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/20/2021] [Accepted: 09/10/2021] [Indexed: 06/13/2023]
Abstract
Time-resolved (TR) spectroscopy is well-suited to address the challenges of quantifying light absorbers in highly scattering media such as living tissue; however, current TR spectrometers are either based on expensive array detectors or rely on wavelength scanning. Here, we introduce a TR spectrometer architecture based on compressed sensing (CS) and time-correlated single-photon counting. Using both CS and basis scanning, we demonstrate that-in homogeneous and two-layer tissue-mimicking phantoms made of Intralipid and Indocyanine Green-the CS method agrees with or outperforms uncompressed approaches. Further, we illustrate the superior depth sensitivity of TR spectroscopy and highlight the potential of the device to quantify absorption changes in deeper (>1 cm) tissue layers.
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Affiliation(s)
- Seva Ioussoufovitch
- Western University, Faculty of Engineering, School of Biomedical Engineering, Collaborative Training Program in Musculoskeletal Health Research, Bone & Joint Institute, 1151 Richmond St., London, N6A 5C1, Canada
| | - David Jonathan Fulop Cohen
- Western University, Schulich School of Medicine & Dentistry, Department of Medical Biophysics, 1151 Richmond St., London, N6A 5C1, Canada
| | - Daniel Milej
- Western University, Schulich School of Medicine & Dentistry, Department of Medical Biophysics, 1151 Richmond St., London, N6A 5C1, Canada
- Lawson Health Research Institute, Imaging Program, 268 Grosvenor St., London, N6A 4V2, Canada
| | - Mamadou Diop
- Western University, Faculty of Engineering, School of Biomedical Engineering, Collaborative Training Program in Musculoskeletal Health Research, Bone & Joint Institute, 1151 Richmond St., London, N6A 5C1, Canada
- Western University, Schulich School of Medicine & Dentistry, Department of Medical Biophysics, 1151 Richmond St., London, N6A 5C1, Canada
- Lawson Health Research Institute, Imaging Program, 268 Grosvenor St., London, N6A 4V2, Canada
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86
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Wojtkiewicz S, Liebert A. Parallel, multi-purpose Monte Carlo code for simulation of light propagation in segmented tissues. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2021.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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87
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Fan W, Dehghani H, Eggebrecht AT. Investigation of effect of modulation frequency on high-density diffuse optical tomography image quality. NEUROPHOTONICS 2021; 8:045002. [PMID: 34849379 PMCID: PMC8612746 DOI: 10.1117/1.nph.8.4.045002] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 11/04/2021] [Indexed: 05/16/2023]
Abstract
Significance: By incorporating multiple overlapping functional near-infrared spectroscopy (fNIRS) measurements, high-density diffuse optical tomography (HD-DOT) images human brain function with fidelity comparable to functional magnetic resonance imaging (fMRI). Previous work has shown that frequency domain high-density diffuse optical tomography (FD-HD-DOT) may further improve image quality over more traditional continuous wave (CW) HD-DOT. Aim: The effects of modulation frequency on image quality as obtainable with FD-HD-DOT is investigated through simulations with a realistic noise model of functional activations in human head models, arising from 11 source modulation frequencies between CW and 1000 MHz. Approach: Simulations were performed using five representative head models with an HD regular grid of 158 light sources and 166 detectors and an empirically derived noise model. Functional reconstructions were quantitatively assessed with multiple image quality metrics including the localization error (LE), success rate, full width at half maximum, and full volume at half maximum (FVHM). All metrics were evaluated against CW-based models. Results: Compared to CW, localization accuracy is improved by >40% throughout brain depths of 13 to 25 mm below the surface with 300 to 500 MHz modulation frequencies. Additionally, the reliable field of view in brain tissue is enlarged by 35% to 48% within an optimal frequency of 300 MHz after considering realistic noise, depending on the dynamic range of the system. Conclusions: These results point to the tremendous opportunities in further development of high bandwidth FD-HD-DOT system hardware for applications in human brain mapping.
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Affiliation(s)
- Weihao Fan
- Washington University, Department of Physics, St. Louis, Missouri, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
- Washington University, Department of Biomedical Engineering, St. Louis, Missouri, United States
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88
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Smith AG, Perez R, Thomas A, Stewart S, Samiei A, Bangalore A, Gomer H, Darr MB, Schweitzer RC, Vasudevan S, Cohen J, Post JC, Murali S, Treado PJ. Objective determination of peripheral edema in heart failure patients using short-wave infrared molecular chemical imaging. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-210090RR. [PMID: 34689443 PMCID: PMC8541742 DOI: 10.1117/1.jbo.26.10.105002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 09/16/2021] [Indexed: 05/04/2023]
Abstract
SIGNIFICANCE Peripheral pitting edema is a clinician-administered measure for grading edema. Peripheral edema is graded 0, 1 + , 2 + , 3 + , or 4 + , but subjectivity is a major limitation of this technique. A pilot clinical study for short-wave infrared (SWIR) molecular chemical imaging (MCI) effectiveness as an objective, non-contact quantitative peripheral edema measure is underway. AIM We explore if SWIR MCI can differentiate populations with and without peripheral edema. Further, we evaluate the technology for correctly stratifying subjects with peripheral edema. APPROACH SWIR MCI of shins from healthy subjects and heart failure (HF) patients was performed. Partial least squares discriminant analysis (PLS-DA) was used to discriminate the two populations. PLS regression (PLSR) was applied to assess the ability of MCI to grade edema. RESULTS Average spectra from edema exhibited higher water absorption than non-edema spectra. SWIR MCI differentiated healthy volunteers from a population representing all pitting edema grades with 97.1% accuracy (N = 103 shins). Additionally, SWIR MCI correctly classified shin pitting edema levels in patients with 81.6% accuracy. CONCLUSIONS Our study successfully achieved the two primary endpoints. Application of SWIR MCI to monitor patients while actively receiving HF treatment is necessary to validate SWIR MCI as an HF monitoring technology.
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Affiliation(s)
- Aaron G. Smith
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
| | - Reina Perez
- Allegheny General Hospital, Pittsburgh, Pennsylvania, United States
| | - Aaron Thomas
- Allegheny General Hospital, Pittsburgh, Pennsylvania, United States
| | - Shona Stewart
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
- Address all correspondence to Shona Stewart,
| | - Arash Samiei
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
| | - Arjun Bangalore
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
| | - Heather Gomer
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
| | - Marlena B. Darr
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
| | | | | | - Jeffrey Cohen
- ChemImage Corporation, Pittsburgh, Pennsylvania, United States
- Allegheny General Hospital, Pittsburgh, Pennsylvania, United States
| | | | - Srinivas Murali
- Allegheny General Hospital, Pittsburgh, Pennsylvania, United States
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Mohammad PPS, Isarangura S, Eddins A, Parthasarathy AB. Comparison of functional activation responses from the auditory cortex derived using multi-distance frequency domain and continuous wave near-infrared spectroscopy. NEUROPHOTONICS 2021; 8:045004. [PMID: 34926716 PMCID: PMC8673635 DOI: 10.1117/1.nph.8.4.045004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 11/29/2021] [Indexed: 05/08/2023]
Abstract
Significance: Quantitative measurements of cerebral hemodynamic changes due to functional activation are widely accomplished with commercial continuous wave (CW-NIRS) instruments despite the availability of the more rigorous multi-distance frequency domain (FD-NIRS) approach. A direct comparison of the two approaches to functional near-infrared spectroscopy can help in the interpretation of optical data and guide implementations of diffuse optical instruments for measuring functional activation. Aim: We explore the differences between CW-NIRS and multi-distance FD-NIRS by comparing measurements of functional activation in the human auditory cortex. Approach: Functional activation of the human auditory cortex was measured using a commercial frequency domain near-infrared spectroscopy instrument for 70 dB sound pressure level broadband noise and pure tone (1000 Hz) stimuli. Changes in tissue oxygenation were calculated using the modified Beer-Lambert law (CW-NIRS approach) and the photon diffusion equation (FD-NIRS approach). Results: Changes in oxygenated hemoglobin measured with the multi-distance FD-NIRS approach were about twice as large as those measured with the CW-NIRS approach. A finite-element simulation of the functional activation problem was performed to demonstrate that tissue oxygenation changes measured with the CW-NIRS approach is more accurate than that with multi-distance FD-NIRS. Conclusions: Multi-distance FD-NIRS approaches tend to overestimate functional activation effects, in part due to partial volume effects.
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Affiliation(s)
| | - Sittiprapa Isarangura
- University of South Florida, Department of Communication Sciences and Disorders, Tampa, Florida, United States
| | - Ann Eddins
- University of South Florida, Department of Communication Sciences and Disorders, Tampa, Florida, United States
| | - Ashwin B. Parthasarathy
- University of South Florida, Department of Electrical Engineering, Tampa, Florida, United States
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90
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Sudakou A, Lange F, Isler H, Lanka P, Wojtkiewicz S, Sawosz P, Ostojic D, Wolf M, Pifferi A, Tachtsidis I, Liebert A, Gerega A. Time-domain NIRS system based on supercontinuum light source and multi-wavelength detection: validation for tissue oxygenation studies. BIOMEDICAL OPTICS EXPRESS 2021; 12:6629-6650. [PMID: 34745761 PMCID: PMC8548017 DOI: 10.1364/boe.431301] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/06/2021] [Accepted: 09/07/2021] [Indexed: 05/15/2023]
Abstract
We present and validate a multi-wavelength time-domain near-infrared spectroscopy (TD-NIRS) system that avoids switching wavelengths and instead exploits the full capability of a supercontinuum light source by emitting and acquiring signals for the whole chosen range of wavelengths. The system was designed for muscle and brain oxygenation monitoring in a clinical environment. A pulsed supercontinuum laser emits broadband light and each of two detection modules acquires the distributions of times of flight of photons (DTOFs) for 16 spectral channels (used width 12.5 nm / channel), providing a total of 32 DTOFs at up to 3 Hz. Two emitting fibers and two detection fiber bundles allow simultaneous measurements at two positions on the tissue or at two source-detector separations. Three established protocols (BIP, MEDPHOT, and nEUROPt) were used to quantitatively assess the system's performance, including linearity, coupling, accuracy, and depth sensitivity. Measurements were performed on 32 homogeneous phantoms and two inhomogeneous phantoms (solid and liquid). Furthermore, measurements on two blood-lipid phantoms with a varied amount of blood and Intralipid provide the strongest validation for accurate tissue oximetry. The retrieved hemoglobin concentrations and oxygen saturation match well with the reference values that were obtained using a commercially available NIRS system (OxiplexTS) and a blood gas analyzer (ABL90 FLEX), except a discrepancy occurs for the lowest amount of Intralipid. In-vivo measurements on the forearm of three healthy volunteers during arterial (250 mmHg) and venous (60 mmHg) cuff occlusions provide an example of tissue monitoring during the expected hemodynamic changes that follow previously well-described physiologies. All results, including quantitative parameters, can be compared to other systems that report similar tests. Overall, the presented TD-NIRS system has an exemplary performance evaluated with state-of-the-art performance assessment methods.
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Affiliation(s)
- Aleh Sudakou
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Frédéric Lange
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Helene Isler
- Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Pranav Lanka
- Dipartimento di Fisica, Politecnico di Milano, Milano, Italy
| | | | - Piotr Sawosz
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Daniel Ostojic
- Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Martin Wolf
- Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Antonio Pifferi
- Dipartimento di Fisica, Politecnico di Milano, Milano, Italy
| | - Ilias Tachtsidis
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Anna Gerega
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
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91
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Clinically translatable quantitative molecular photoacoustic imaging with liposome-encapsulated ICG J-aggregates. Nat Commun 2021; 12:5410. [PMID: 34518530 PMCID: PMC8438038 DOI: 10.1038/s41467-021-25452-3] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 08/11/2021] [Indexed: 02/08/2023] Open
Abstract
Photoacoustic (PA) imaging is a functional and molecular imaging technique capable of high sensitivity and spatiotemporal resolution at depth. Widespread use of PA imaging, however, is limited by currently available contrast agents, which either lack PA-signal-generation ability for deep imaging or their absorbance spectra overlap with hemoglobin, reducing sensitivity. Here we report on a PA contrast agent based on targeted liposomes loaded with J-aggregated indocyanine green (ICG) dye (i.e., PAtrace) that we synthesized, bioconjugated, and characterized to addresses these limitations. We then validated PAtrace in phantom, in vitro, and in vivo PA imaging environments for both spectral unmixing accuracy and targeting efficacy in a folate receptor alpha-positive ovarian cancer model. These study results show that PAtrace concurrently provides significantly improved contrast-agent quantification/sensitivity and SO2 estimation accuracy compared to monomeric ICG. PAtrace's performance attributes and composition of FDA-approved components make it a promising agent for future clinical molecular PA imaging.
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92
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Feng T, Zhu Y, Morris R, kozloff KM, Wang X. The feasibility study of the transmission mode photoacoustic measurement of human calcaneus bone in vivo. PHOTOACOUSTICS 2021; 23:100273. [PMID: 34745881 PMCID: PMC8552339 DOI: 10.1016/j.pacs.2021.100273] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/04/2021] [Accepted: 05/12/2021] [Indexed: 05/26/2023]
Abstract
The photoacoustic (PA) technique is uniquely positioned for biomedical applications primarily due to its ability to visualize optical absorption contrast in deep tissue at ultrasound resolution. In this work, via both three-dimensional (3D) numerical simulations and in vivo experiments on human subjects, we investigated the possibility of PA measurement of human calcaneus bones in vivo in a non-invasive manner, as well as its feasibility to differentiate osteoporosis patients from normal subjects. The results from the simulations and the experiments both demonstrated that, when one side of the heel is illuminated by laser with light fluence under the ANSI safety limit, the PA signal generated in the human calcaneus bone can be detected by an ultrasonic transducer at the other side of the heel (i.e. transmission mode). Quantitative power spectral analyses of the calcaneus bone PA signals were also conducted, demonstrating that the microarchitectural changes in calcaneus bone due to osteoporosis can be detected, as reflected by enhanced high frequency components in detected PA bone signal. Further statistical analysis of the experimental results from 10 osteoporosis patients and 10 healthy volunteers showed that the weighted frequency as a quantified PA spectral parameter can differentiate the two subject groups with statistical significance.
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Affiliation(s)
- Ting Feng
- Department of Biomedical Engineering, University of Michigan Medical School, MI 48109, USA
| | - Yunhao Zhu
- Department of Biomedical Engineering, University of Michigan Medical School, MI 48109, USA
| | | | - Kenneth M. kozloff
- Department of Biomedical Engineering, University of Michigan Medical School, MI 48109, USA
- Department of Orthopaedic Surgery, University of Michigan Medical School, MI 48109, USA
| | - Xueding Wang
- Department of Biomedical Engineering, University of Michigan Medical School, MI 48109, USA
- Department of Radiology, University of Michigan Medical School, MI 48109, USA
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93
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Yazdani A, Agrawal S, Johnstonbaugh K, Kothapalli SR, Monga V. Simultaneous Denoising and Localization Network for Photoacoustic Target Localization. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2367-2379. [PMID: 33939612 PMCID: PMC8526152 DOI: 10.1109/tmi.2021.3077187] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
A significant research problem of recent interest is the localization of targets like vessels, surgical needles, and tumors in photoacoustic (PA) images.To achieve accurate localization, a high photoacoustic signal-to-noise ratio (SNR) is required. However, this is not guaranteed for deep targets, as optical scattering causes an exponential decay in optical fluence with respect to tissue depth. To address this, we develop a novel deep learning method designed to explicitly exhibit robustness to noise present in photoacoustic radio-frequency (RF) data. More precisely, we describe and evaluate a deep neural network architecture consisting of a shared encoder and two parallel decoders. One decoder extracts the target coordinates from the input RF data while the other boosts the SNR and estimates clean RF data. The joint optimization of the shared encoder and dual decoders lends significant noise robustness to the features extracted by the encoder, which in turn enables the network to contain detailed information about deep targets that may be obscured by noise. Additional custom layers and newly proposed regularizers in the training loss function (designed based on observed RF data signal and noise behavior) serve to increase the SNR in the cleaned RF output and improve model performance. To account for depth-dependent strong optical scattering, our network was trained with simulated photoacoustic datasets of targets embedded at different depths inside tissue media of different scattering levels. The network trained on this novel dataset accurately locates targets in experimental PA data that is clinically relevant with respect to the localization of vessels, needles, or brachytherapy seeds. We verify the merits of the proposed architecture by outperforming the state of the art on both simulated and experimental datasets.
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94
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田 文, 杨 丹, 魏 竹, 王 骄. [Study on the inverse problem of diffuse optical tomography based on improved stacked auto-encoder]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2021; 38:774-782. [PMID: 34459178 PMCID: PMC9927525 DOI: 10.7507/1001-5515.202010041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 02/23/2021] [Indexed: 11/03/2022]
Abstract
The inverse problem of diffuse optical tomography (DOT) is ill-posed. Traditional method cannot achieve high imaging accuracy and the calculation process is time-consuming, which restricts the clinical application of DOT. Therefore, a method based on stacked auto-encoder (SAE) was proposed and used for the DOT inverse problem. Firstly, a traditional SAE method is used to solved the inverse problem. Then, the output structure of SAE neural network is improved to a single output SAE, which reduce the burden on the neural network. Finally, the improved SAE method is used to compare with traditional SAE method and traditional levenberg-marquardt (LM) iterative method. The result shows that the average time to solve the inverse problem of the method proposed in this paper is only 1.67% of the LM method. The mean square error (MSE) value is 46.21% lower than the traditional iterative method, 61.53% lower than the traditional SAE method, and the image correlation coefficient(ICC) value is 4.03% higher than the traditional iterative method, 18.7% higher than the traditional SAE method and has good noise immunity under 3% noise conditions. The research results in this article prove that the improved SAE method has higher image quality and noise resistance than the traditional SAE method, and at the same time has a faster calculation speed than the traditional iterative method, which is conducive to the application of neural networks in DOT inverse problem calculation.
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Affiliation(s)
- 文旭 田
- 东北大学 信息科学与工程学院(沈阳 110819)School of Information Science & Engineering, Northeastern University, Shenyang 110819, P.R.China
- 东北大学 辽宁省红外光电材料及微纳器件重点实验室(沈阳 110819)Key Laboratory of Infrared Optoelectric Materials and Micro-Nano Devices, Shenyang 110819, P.R.China
| | - 丹 杨
- 东北大学 信息科学与工程学院(沈阳 110819)School of Information Science & Engineering, Northeastern University, Shenyang 110819, P.R.China
- 东北大学 辽宁省红外光电材料及微纳器件重点实验室(沈阳 110819)Key Laboratory of Infrared Optoelectric Materials and Micro-Nano Devices, Shenyang 110819, P.R.China
- 东北大学 智能工业数据解析与优化教育部重点实验室(沈阳 110819)Key Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang 110819, P.R.China
| | - 竹林 魏
- 东北大学 信息科学与工程学院(沈阳 110819)School of Information Science & Engineering, Northeastern University, Shenyang 110819, P.R.China
- 东北大学 辽宁省红外光电材料及微纳器件重点实验室(沈阳 110819)Key Laboratory of Infrared Optoelectric Materials and Micro-Nano Devices, Shenyang 110819, P.R.China
| | - 骄 王
- 东北大学 信息科学与工程学院(沈阳 110819)School of Information Science & Engineering, Northeastern University, Shenyang 110819, P.R.China
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95
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Peter J. Musiré: multimodal simulation and reconstruction framework for the radiological imaging sciences. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200190. [PMID: 34218676 DOI: 10.1098/rsta.2020.0190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/11/2021] [Indexed: 06/13/2023]
Abstract
A software-based workflow is proposed for managing the execution of simulation and image reconstruction for SPECT, PET, CBCT, MRI, BLI and FMI packages in single and multimodal biomedical imaging applications. The workflow is composed of a Bash script, the purpose of which is to provide an interface to the user, and to organize data flow between dedicated programs for simulation and reconstruction. The currently incorporated simulation programs comprise GATE for Monte Carlo simulation of SPECT, PET and CBCT, SpinScenario for simulating MRI, and Lipros for Monte Carlo simulation of BLI and FMI. Currently incorporated image reconstruction programs include CASToR for SPECT and PET as well as RTK for CBCT. MetaImage (mhd) standard is used for voxelized phantom and image data format. Meshlab project (mlp) containers incorporating polygon meshes and point clouds defined by the Stanford triangle format (ply) are employed to represent anatomical structures for optical simulation, and to represent tumour cell inserts. A number of auxiliary programs have been developed for data transformation and adaptive parameter assignment. The software workflow uses fully automatic distribution to, and consolidation from, any number of Linux workstations and CPU cores. Example data are presented for clinical SPECT, PET and MRI systems using the Mida head phantom and for preclinical X-ray, PET and BLI systems employing the Digimouse phantom. The presented method unifies and simplifies multimodal simulation setup and image reconstruction management and might be of value for synergistic image research. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.
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Affiliation(s)
- Jörg Peter
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Im Neuenheimer Feld, 280, 69120 Heidelberg, Germany
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96
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Rubtsova NI, Hart MC, Arroyo AD, Osharovich SA, Liebov BK, Miller J, Yuan M, Cochran JM, Chong S, Yodh AG, Busch TM, Delikatny EJ, Anikeeva N, Popov AV. NIR Fluorescent Imaging and Photodynamic Therapy with a Novel Theranostic Phospholipid Probe for Triple-Negative Breast Cancer Cells. Bioconjug Chem 2021; 32:1852-1863. [PMID: 34139845 DOI: 10.1021/acs.bioconjchem.1c00295] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
New exogenous probes are needed for both imaging diagnostics and therapeutics. Here, we introduce a novel nanocomposite near-infrared (NIR) fluorescent imaging probe and test its potency as a photosensitizing agent for photodynamic therapy (PDT) against triple-negative breast cancer cells. The active component in the nanocomposite is a small molecule, pyropheophorbide a-phosphatidylethanolamine-QSY21 (Pyro-PtdEtn-QSY), which is imbedded into lipid nanoparticles for transport in the body. The probe targets abnormal choline metabolism in cancer cells; specifically, the overexpression of phosphatidylcholine-specific phospholipase C (PC-PLC) in breast, prostate, and ovarian cancers. Pyro-PtdEtn-QSY consists of a NIR fluorophore and a quencher, attached to a PtdEtn moiety. It is selectively activated by PC-PLC resulting in enhanced fluorescence in cancer cells compared to normal cells. In our in vitro investigation, four breast cancer cell lines showed higher probe activation levels than noncancerous control cells, immortalized human mammary gland cells, and normal human T cells. Moreover, the ability of this nanocomposite to function as a sensitizer in PDT experiments on MDA-MB-231 cells suggests that the probe is promising as a theranostic agent.
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Affiliation(s)
- Natalia I Rubtsova
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Michael C Hart
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Alejandro D Arroyo
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Sofya A Osharovich
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Benjamin K Liebov
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Joann Miller
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Bldg 421, Philadelphia, Pennsylvania 19104, United States
| | - Min Yuan
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Bldg 421, Philadelphia, Pennsylvania 19104, United States
| | - Jeffrey M Cochran
- Department of Physics and Astronomy, University of Pennsylvania, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States
| | - Sanghoon Chong
- Department of Physics and Astronomy, University of Pennsylvania, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States
| | - Arjun G Yodh
- Department of Physics and Astronomy, University of Pennsylvania, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States
| | - Theresa M Busch
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Bldg 421, Philadelphia, Pennsylvania 19104, United States
| | - E James Delikatny
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
| | - Nadia Anikeeva
- Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, United States
| | - Anatoliy V Popov
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, Pennsylvania 19104, United States
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97
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Xu X, Deng Z, Dehghani H, Iordachita I, Lim M, Wong JW, Wang KKH. Quantitative Bioluminescence Tomography-guided Conformal Irradiation for Preclinical Radiation Research. Int J Radiat Oncol Biol Phys 2021; 111:1310-1321. [PMID: 34411639 PMCID: PMC8602741 DOI: 10.1016/j.ijrobp.2021.08.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 07/16/2021] [Accepted: 08/05/2021] [Indexed: 10/31/2022]
Abstract
PURPOSE Widely used cone beam computed tomography (CBCT)-guided irradiators in preclinical radiation research are limited to localize soft tissue target because of low imaging contrast. Knowledge of target volume is a fundamental need for radiation therapy (RT). Without such information to guide radiation, normal tissue can be overirradiated, introducing experimental uncertainties. This led us to develop high-contrast quantitative bioluminescence tomography (QBLT) for guidance. The use of a 3-dimensional bioluminescence signal, related to cell viability, for preclinical radiation research is one step toward biology-guided RT. METHODS AND MATERIALS Our QBLT system enables multiprojection and multispectral bioluminescence imaging to maximize input data for the tomographic reconstruction. Accurate quantification of spectrum and dynamic change of in vivo signal were also accounted for the QBLT. A spectral-derivative method was implemented to eliminate the modeling of the light propagation from animal surface to detector. We demonstrated the QBLT capability of guiding conformal RT using a bioluminescent glioblastoma (GBM) model in vivo. A threshold was determined to delineate QBLT reconstructed gross target volume (GTVQBLT), which provides the best overlap between the GTVQBLT and CBCT contrast labeled GBM (GTV), used as the ground truth for GBM volume. To account for the uncertainty of GTVQBLT in target positioning and volume delineation, a margin was determined and added to the GTVQBLT to form a QBLT planning target volume (PTVQBLT) for guidance. RESULTS The QBLT can reconstruct in vivo GBM with localization accuracy within 1 mm. A 0.5-mm margin was determined and added to GTVQBLT to form PTVQBLT, largely improving tumor coverage from 75.0% (0 mm margin) to 97.9% in average, while minimizing normal tissue toxicity. With the goal of prescribed dose 5 Gy covering 95% of PTVQBLT, QBLT-guided 7-field conformal RT can effectively irradiate 99.4 ± 1.0% of GTV. CONCLUSIONS The QBLT provides a unique opportunity for investigators to use biologic information for target delineation, guiding conformal irradiation, and reducing normal tissue involvement, which is expected to increase reproducibility of scientific discovery.
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Affiliation(s)
- Xiangkun Xu
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland; Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Zijian Deng
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland; Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, West Midlands, United Kingdom
| | - Iulian Iordachita
- Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, Maryland
| | - Michael Lim
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland; Department of Neurosurgery, Stanford University, Stanford, California
| | - John W Wong
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Ken Kang-Hsin Wang
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland; Biomedical Imaging and Radiation Technology Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas.
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98
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Yun S, Kim Y, Kim H, Lee S, Jeong U, Lee H, Choi YW, Cho S. Three-compartment-breast (3CB) prior-guided diffuse optical tomography based on dual-energy digital breast tomosynthesis (DBT). BIOMEDICAL OPTICS EXPRESS 2021; 12:4837-4851. [PMID: 34513228 PMCID: PMC8407844 DOI: 10.1364/boe.431244] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/01/2021] [Accepted: 07/03/2021] [Indexed: 05/18/2023]
Abstract
Diffuse optical tomography (DOT) is a non-invasive functional imaging modality that uses near-infrared (NIR) light to measure the oxygenation state and the concentration of hemoglobin. By complementarily using DOT with other anatomical imaging modalities, physicians can diagnose more accurately through additional functional image information. In breast imaging, diagnosis of dense breasts is often challenging because the bulky fibrous tissues may hinder the correct tumor characterization. In this work, we proposed a three-compartment-breast (3CB) decomposition-based prior-guided optical tomography for enhancing DOT image quality. We conjectured that the 3CB prior would lead to improvement of the spatial resolution and also of the contrast of the reconstructed tumor image, particularly for the dense breasts. We conducted a Monte-Carlo simulation to acquire dual-energy X-ray projections of a realistic 3D numerical breast phantom and performed digital breast tomosynthesis (DBT) for setting up a 3CB model. The 3CB prior was then used as a structural guide in DOT image reconstruction. The proposed method resulted in the higher spatial resolution of the recovered tumor even when the tumor is surrounded by the fibroglandular tissues compared with the typical two-composition-prior method or the standard Tikhonov regularization method.
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Affiliation(s)
- Sungho Yun
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - Yejin Kim
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - Hyeongseok Kim
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
- KAIST Institute for Artificial Intelligence, KAIST, Daejeon 34141, Republic of Korea
| | - Seoyoung Lee
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - Uijin Jeong
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - Hoyeon Lee
- Department of Radiation and Oncology, MGH, Boston 02114, USA
| | - Young-wook Choi
- Korea Electrotechnology Research Institute, Ansan 15588, Republic of Korea
| | - Seungryong Cho
- Department of Nuclear and Quantum Engineering, KAIST, Daejeon 34141, Republic of Korea
- KAIST Institute for Artificial Intelligence, KAIST, Daejeon 34141, Republic of Korea
- KAIST Institutes for ITC and HST, KAIST, Daejeon 34141, Republic of Korea
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99
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Fu X, Richards JE. Age-related changes in diffuse optical tomography sensitivity profiles in infancy. PLoS One 2021; 16:e0252036. [PMID: 34101747 PMCID: PMC8186805 DOI: 10.1371/journal.pone.0252036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 05/08/2021] [Indexed: 02/06/2023] Open
Abstract
Diffuse optical tomography uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the location that generates the hemodynamic signal requires accurate descriptions of diffuse optical tomography sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. The present study used photon propagation simulation methods to examine diffuse optical tomography sensitivity profiles in realistic head models among infants ranging from 2 weeks to 24 months with narrow age bins, children (4 and 12 years) and adults (20 to 24 years). The sensitivity profiles changed systematically with the source-detector separation distance. The peak of the sensitivity function in the head was largest at the smallest separation distance and decreased as separation distance increased. The fluence value dissipated more quickly with sampling depth at the shorter source-detector separations than the longer separation distances. There were age-related differences in the shape and variance of sensitivity profiles across a wide range of source-detector separation distances. Our findings have important implications in the design of sensor placement and diffuse optical tomography image reconstruction in (functional) near-infrared light spectroscopy research. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone near-infrared light spectroscopy data in infants.
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Affiliation(s)
- Xiaoxue Fu
- Department of Psychology, University of South Carolina, Columbia, United States of America
| | - John E. Richards
- Department of Psychology, University of South Carolina, Columbia, United States of America
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Spink SS, Teng F, Pera V, Peterson HM, Cormier T, Sauer-Budge A, Chargin D, Brookfield S, Eggebrecht AT, Ko N, Roblyer D. High optode-density wearable diffuse optical probe for monitoring paced breathing hemodynamics in breast tissue. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-200339SSR. [PMID: 34080400 PMCID: PMC8170390 DOI: 10.1117/1.jbo.26.6.062708] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 05/16/2021] [Indexed: 06/12/2023]
Abstract
SIGNIFICANCE Diffuse optical imaging (DOI) provides in vivo quantification of tissue chromophores such as oxy- and deoxyhemoglobin (HbO2 and HHb, respectively). These parameters have been shown to be useful for predicting neoadjuvant treatment response in breast cancer patients. However, most DOI devices designed for the breast are nonportable, making frequent longitudinal monitoring during treatment a challenge. Furthermore, hemodynamics related to the respiratory cycle are currently unexplored in the breast and may have prognostic value. AIM To design, fabricate, and validate a high optode-density wearable continuous wave diffuse optical probe for the monitoring of breathing hemodynamics in breast tissue. APPROACH The probe has a rigid-flex design with 16 dual-wavelength sources and 16 detectors. Performance was characterized on tissue-simulating phantoms, and validation was performed through flow phantom and cuff occlusion measurements. The breasts of N = 4 healthy volunteers were measured while performing a breathing protocol. RESULTS The probe has 512 unique source-detector (S-D) pairs that span S-D separations of 10 to 54 mm. It exhibited good performance characteristics: μa drift of 0.34%/h, μa precision of 0.063%, and mean SNR ≥ 24 dB up to 41 mm S-D separation. Absorption contrast was detected in flow phantoms at depths exceeding 28 mm. A cuff occlusion measurement confirmed the ability of the probe to track expected hemodynamics in vivo. Breast measurements on healthy volunteers during paced breathing revealed median signal-to-motion artifact ratios ranging from 8.1 to 8.7 dB. Median ΔHbO2 and ΔHHb amplitudes ranged from 0.39 to 0.67 μM and 0.08 to 0.12 μM, respectively. Median oxygen saturations at the respiratory rate ranged from 82% to 87%. CONCLUSIONS A wearable diffuse optical probe has been designed and fabricated for the measurement of breast tissue hemodynamics. This device is capable of quantifying breathing-related hemodynamics in healthy breast tissue.
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Affiliation(s)
- Samuel S. Spink
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Fei Teng
- Boston University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States
| | - Vivian Pera
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Hannah M. Peterson
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Tim Cormier
- Boston University, Fraunhofer Center for Manufacturing Innovation, Boston, Massachusetts, United States
| | - Alexis Sauer-Budge
- Boston University, Fraunhofer Center for Manufacturing Innovation, Boston, Massachusetts, United States
| | - David Chargin
- Boston University, Fraunhofer Center for Manufacturing Innovation, Boston, Massachusetts, United States
| | - Sam Brookfield
- Boston University, Fraunhofer Center for Manufacturing Innovation, Boston, Massachusetts, United States
| | - Adam T. Eggebrecht
- Washington University, Department of Radiology, St. Louis, Missouri, United States
| | - Naomi Ko
- Boston Medical Center, Section of Hematology and Oncology, Women’s Health Unit, Boston, Massachusetts, United States
| | - Darren Roblyer
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
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