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Balasubramanian H, Hobson CM, Chew TL, Aaron JS. Imagining the future of optical microscopy: everything, everywhere, all at once. Commun Biol 2023; 6:1096. [PMID: 37898673 PMCID: PMC10613274 DOI: 10.1038/s42003-023-05468-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/16/2023] [Indexed: 10/30/2023] Open
Abstract
The optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.
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Affiliation(s)
| | - Chad M Hobson
- Advanced Imaging Center; Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA, 20147, USA
| | - Teng-Leong Chew
- Advanced Imaging Center; Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA, 20147, USA
| | - Jesse S Aaron
- Advanced Imaging Center; Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA, 20147, USA.
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Vega JD, Hara D, Schmidt RM, Abuhaija MB, Tao W, Dogan N, Pollack A, Ford JC, Shi J. In vivo active-targeting fluorescence molecular imaging with adaptive background fluorescence subtraction. Front Oncol 2023; 13:1130155. [PMID: 36998445 PMCID: PMC10043309 DOI: 10.3389/fonc.2023.1130155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/28/2023] [Indexed: 03/18/2023] Open
Abstract
Using active tumor-targeting nanoparticles, fluorescence imaging can provide highly sensitive and specific tumor detection, and precisely guide radiation in translational radiotherapy study. However, the inevitable presence of non-specific nanoparticle uptake throughout the body can result in high levels of heterogeneous background fluorescence, which limits the detection sensitivity of fluorescence imaging and further complicates the early detection of small cancers. In this study, background fluorescence emanating from the baseline fluorophores was estimated from the distribution of excitation light transmitting through tissues, by using linear mean square error estimation. An adaptive masked-based background subtraction strategy was then implemented to selectively refine the background fluorescence subtraction. First, an in vivo experiment was performed on a mouse intratumorally injected with passively targeted fluorescent nanoparticles, to validate the reliability and robustness of the proposed method in a stringent situation wherein the target fluorescence was overlapped with the strong background. Then, we conducted in vivo studies on 10 mice which were inoculated with orthotopic breast tumors and intravenously injected with actively targeted fluorescent nanoparticles. Results demonstrated that active targeting combined with the proposed background subtraction method synergistically increased the accuracy of fluorescence molecular imaging, affording sensitive tumor detection.
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Affiliation(s)
- Jorge D. Vega
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Daiki Hara
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Ryder M. Schmidt
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Marwan B. Abuhaija
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Wensi Tao
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Nesrin Dogan
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Alan Pollack
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - John C. Ford
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
- *Correspondence: John C. Ford, ; Junwei Shi,
| | - Junwei Shi
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, FL, United States
- *Correspondence: John C. Ford, ; Junwei Shi,
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Gao S, Li M, Smith JT, Intes X. Design and characterization of a time-domain optical tomography platform for mesoscopic lifetime imaging. BIOMEDICAL OPTICS EXPRESS 2022; 13:4637-4651. [PMID: 36187247 PMCID: PMC9484415 DOI: 10.1364/boe.460216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/17/2022] [Accepted: 07/12/2022] [Indexed: 06/16/2023]
Abstract
We report on the system design and instrumental characteristics of a novel time-domain mesoscopic fluorescence molecular tomography (TD-MFMT) system for multiplexed molecular imaging in turbid media. The system is equipped with a supercontinuum pulsed laser for broad spectral excitation, based on a high-density descanned raster scanning intensity-based acquisition for 2D and 3D imaging and augmented with a high-dynamical range linear time-resolved single-photon avalanche diode (SPAD) array for lifetime quantification. We report on the system's spatio-temporal and spectral characteristics and its sensitivity and specificity in controlled experimental settings. Also, a phantom study is undertaken to test the performance of the system to image deeply-seated fluorescence inclusions in tissue-like media. In addition, ex vivo tumor xenograft imaging is performed to validate the system's applicability to the biological sample. The characterization results manifest the capability to sense small fluorescence concentrations (on the order of nanomolar) while quantifying fluorescence lifetimes and lifetime-based parameters at high resolution. The phantom results demonstrate the system's potential to perform 3D multiplexed imaging thanks to spectral and lifetime contrast in the mesoscopic range (at millimeters depth). The ex vivo imaging exhibits the prospect of TD-MFMT to resolve intra-tumoral heterogeneity in a depth-dependent manner.
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Affiliation(s)
- Shan Gao
- Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Mengzhou Li
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Jason T. Smith
- Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Xavier Intes
- Center for Modeling, Simulation and Imaging in Medicine (CeMSIM), Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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Nizam NI, Ochoa M, Smith JT, Intes X. 3D k-space reflectance fluorescence tomography via deep learning. OPTICS LETTERS 2022; 47:1533-1536. [PMID: 35290357 PMCID: PMC9335514 DOI: 10.1364/ol.450935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
We report on the potential to perform image reconstruction in 3D k-space reflectance fluorescence tomography (FT) using deep learning (DL). Herein, we adopt a modified AUTOMAP architecture and develop a training methodology that leverages an open-source Monte-Carlo-based simulator to generate a large dataset. Using an enhanced EMNIST (EEMNIST) dataset as an embedded contrast function allows us to train the network efficiently. The optical strategy utilizes k-space illumination in a reflectance configuration to probe tissue in the mesoscopic regime with high sensitivity and resolution. The proposed DL model training and validation is performed with both in silico data and a phantom experiment. Overall, our results indicate that the approach can correctly reconstruct both single and multiple fluorescent embedding(s) in a 3D volume. Furthermore, the presented technique is shown to outperform the traditional approaches [least-squares (LSQ) and total-variation minimization (TVAL)], especially at higher depths. We, therefore, expect the proposed computational technique to have future implications in preclinical studies.
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Affiliation(s)
- Navid Ibtehaj Nizam
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Marien Ochoa
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Jason T. Smith
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Xavier Intes
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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