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Al-Salihi M, Chen Z, Samanta S, Elazab A, Yi R, Wang S, Lin F, Qu J, Liu L. Improving the performance of rapid lifetime determination for wide-field time-gated imaging in live cells. OPTICS EXPRESS 2022; 30:30760-30778. [PMID: 36242174 DOI: 10.1364/oe.454958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/08/2022] [Indexed: 06/16/2023]
Abstract
In biological research, rapid wide-field fluorescence lifetime imaging has become an important imaging tool. However, the biological samples with weak fluorescence signals and lower sensitivity often suffer from very low precision in lifetime determinations which restricts its widespread utilization in many bioimaging applications. To address this issue, a method is presented in this paper to substantially enhance the precision of rapid lifetime determination (RLD). It expedites the discrimination of fluorescence lifetimes, even for the weak signals coming from the cells, stained with long-lived biocompatible AIS/ZnS QDs. The proposed method works in two phases. The first phase deals with the systematic noise analysis based on the signal and contrast of the images in a time-gated imaging system, wherein acquiring the high-quality imaging data through optimization of hardware parameters improves the overall system performance. In the second phase, the chosen images are treated using total variation denoising method combined with the Max/Min filtering method for extracting the region of interest to reconstruct the intensity images for RLD. We performed several experiments on live cells to demonstrate the improvements in imaging performance by the systematic optimizations and data treatment. Obtained results demonstrated a great enhancement in signal-to-noise and contrast-to-noise ratios beside witnessing an obvious improvement in RLD for weak signals. This approach can be used not only to improve the quality of time-gated imaging data but also for efficient fluorescence lifetime imaging of live biological samples without compromising imaging speed and light exposure.
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Yang F, Gong X, Faulkner D, Gao S, Yao R, Zhang Y, Intes X. Accelerating vasculature imaging in tumor using mesoscopic fluorescence molecular tomography via a hybrid reconstruction strategy. Biochem Biophys Res Commun 2021; 562:29-35. [PMID: 34030042 DOI: 10.1016/j.bbrc.2021.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 05/09/2021] [Indexed: 10/21/2022]
Abstract
Mesoscopic fluorescent molecular tomography (MFMT) enables to image fluorescent molecular probes beyond the typical depth limits of microscopic imaging and with enhanced resolution compared to macroscopic imaging. However, MFMT is a scattering-based inverse problem that is an ill-posed inverse problem and hence, requires relative complex iterative solvers coupled with regularization strategies. Inspired by the potential of deep learning in performing image formation tasks from raw measurements, this work proposes a hybrid approach to solve the MFMT inverse problem. This methodology combines a convolutional symmetric network and a conventional iterative algorithm to accelerate the reconstruction procedure. By the proposed deep neural network, the principal components of the sensitivity matrix are extracted and the accompanying noise in measurements is suppressed, which helps to accelerate the reconstruction and improve the accuracy of results. We apply the proposed method to reconstruct in silico and vascular tree models. The results demonstrate that reconstruction accuracy and speed are highly improved due to the reduction of redundant entries of the sensitivity matrix and noise suppression.
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Affiliation(s)
- Fugang Yang
- School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai, 264005, China
| | - Xue Gong
- School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai, 264005, China.
| | - Denzel Faulkner
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA
| | - Shan Gao
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA
| | - Ruoyang Yao
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA
| | - Yanli Zhang
- School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai, 264005, China
| | - Xavier Intes
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA
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Intravital mesoscopic fluorescence molecular tomography allows non-invasive in vivo monitoring and quantification of breast cancer growth dynamics. Commun Biol 2021; 4:556. [PMID: 33976362 PMCID: PMC8113483 DOI: 10.1038/s42003-021-02063-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 03/31/2021] [Indexed: 02/03/2023] Open
Abstract
Preclinical breast tumor models are an invaluable tool to systematically study tumor progression and treatment response, yet methods to non-invasively monitor the involved molecular and mechanistic properties under physiologically relevant conditions are limited. Here we present an intravital mesoscopic fluorescence molecular tomography (henceforth IFT) approach that is capable of tracking fluorescently labeled tumor cells in a quantitative manner inside the mammary gland of living mice. Our mesoscopic approach is entirely non-invasive and thus permits prolonged observational periods of several months. The relatively high sensitivity and spatial resolution further enable inferring the overall number of oncogene-expressing tumor cells as well as their tumor volume over the entire cycle from early tumor growth to residual disease following the treatment phase. Our IFT approach is a promising method for studying tumor growth dynamics in a quantitative and longitudinal fashion in-vivo.
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Ozturk MS, Lee VK, Zou H, Friedel RH, Intes X, Dai G. High-resolution tomographic analysis of in vitro 3D glioblastoma tumor model under long-term drug treatment. SCIENCE ADVANCES 2020; 6:eaay7513. [PMID: 32181351 PMCID: PMC7060061 DOI: 10.1126/sciadv.aay7513] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 12/11/2019] [Indexed: 05/21/2023]
Abstract
Glioblastoma multiforme (GBM) is a lethal type of brain tumor that often develop therapeutic resistance over months of chemotherapy cycles. Recently, 3D GBM models were developed to facilitate evaluation of drug treatment before undergoing expensive animal studies. However, for long-term evaluation of therapeutic efficacy, novel approaches for GBM tissue construction are still needed. Moreover, there is still a need to develop fast and sensitive imaging methods for the noninvasive assessment of this 3D constructs and their response to drug treatment. Here, we report on the development of an integrated platform that enable generating (i) an in vitro 3D GBM model with perfused vascular channels that allows long-term culture and drug delivery and (ii) a 3D imaging modality that enables researchers to noninvasively assess longitudinal fluorescent signals over the whole in vitro model.
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Affiliation(s)
- Mehmet S. Ozturk
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Vivian K. Lee
- Department of Bioengineering, Northeastern University, Boston, MA, USA
| | - Hongyan Zou
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Roland H. Friedel
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xavier Intes
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
- Corresponding author. (X.I.); (G.D.)
| | - Guohao Dai
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Corresponding author. (X.I.); (G.D.)
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Yang F, Faulkner D, Yao R, Ozturk MS, Qu Q, Intes X. System configuration optimization for mesoscopic fluorescence molecular tomography. BIOMEDICAL OPTICS EXPRESS 2019; 10:5660-5674. [PMID: 31799038 PMCID: PMC6865091 DOI: 10.1364/boe.10.005660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 10/05/2019] [Accepted: 10/05/2019] [Indexed: 05/04/2023]
Abstract
Tissue engineering applications demand 3D, non-invasive, and longitudinal assessment of bioprinted constructs. Current emphasis is on developing tissue constructs mimicking in vivo conditions; however, these are increasingly challenging to image as they are typically a few millimeters thick and turbid, limiting the usefulness of classical fluorescence microscopic techniques. For such applications, we developed a Mesoscopic Fluorescence Molecular Tomography methodology that collects high information content data to enable high-resolution tomographic reconstruction of fluorescence biomarkers at millimeters depths. This imaging approach is based on an inverse problem; hence, its imaging performances are dependent on critical technical considerations including optode sampling, forward model design and inverse solver parameters. Herein, we investigate the impact of the optical system configuration parameters, including detector layout, number of detectors, combination of detector and source numbers, and scanning mode with uncoupled or coupled source and detector array, on the 3D imaging performances. Our results establish that an MFMT system with a 2D detection chain implemented in a de-scanned mode provides the optimal imaging reconstruction performances.
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Affiliation(s)
- Fugang Yang
- School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai 264005, China
| | - Denzel Faulkner
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Ruoyang Yao
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Mehmet S Ozturk
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Qinglan Qu
- Department of Reproductive Medicine, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, 264000, China
| | - Xavier Intes
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
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Sinha L, Massanes F, Torres VC, Li C, Tichauer KM, Brankov JG. Comparison of time- and angular-domain scatter rejection in mesoscopic optical projection tomography: a simulation study. BIOMEDICAL OPTICS EXPRESS 2019; 10:747-760. [PMID: 30800512 PMCID: PMC6377887 DOI: 10.1364/boe.10.000747] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 12/12/2018] [Accepted: 01/10/2019] [Indexed: 06/09/2023]
Abstract
Optical imaging offers exquisite sensitivity and resolution for assessing biological tissue in microscopy applications; however, for samples that are greater than a few hundred microns in thickness (such as whole tissue biopsies), spatial resolution is substantially limited by the effects of light scattering. To improve resolution, time- and angular-domain methods have been developed to reject detection of highly scattered light. This work utilizes a modified version of a commonly used Monte Carlo light propagation software package (MCML) to present the first comparison of time- and angular-domain improvements in spatial resolution with respect to varying sample thickness and optical properties (absorption and scattering). Specific comparisons were made at various tissue thicknesses (1-6 mm) assuming either typical (average) soft tissue scattering properties, μs ' = 10 cm-1, or low scattering properties, μs ' = 3.4 cm-1, as measured in lymph nodes.
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Affiliation(s)
- L. Sinha
- Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn Street, Chicago, IL 60616, USA
| | - F. Massanes
- Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USA
| | - V. C. Torres
- Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn Street, Chicago, IL 60616, USA
| | - C. Li
- Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn Street, Chicago, IL 60616, USA
| | - K. M. Tichauer
- Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn Street, Chicago, IL 60616, USA
| | - J. G. Brankov
- Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn Street, Chicago, IL 60616, USA
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An Y, Wang K, Tian J. Recent methodology advances in fluorescence molecular tomography. Vis Comput Ind Biomed Art 2018; 1:1. [PMID: 32240398 PMCID: PMC7098398 DOI: 10.1186/s42492-018-0001-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 06/30/2018] [Indexed: 12/26/2022] Open
Abstract
Molecular imaging (MI) is a novel imaging discipline that has been continuously developed in recent years. It combines biochemistry, multimodal imaging, biomathematics, bioinformatics, cell & molecular physiology, biophysics, and pharmacology, and it provides a new technology platform for the early diagnosis and quantitative analysis of diseases, treatment monitoring and evaluation, and the development of comprehensive physiology. Fluorescence Molecular Tomography (FMT) is a type of optical imaging modality in MI that captures the three-dimensional distribution of fluorescence within a biological tissue generated by a specific molecule of fluorescent material within a biological tissue. Compared with other optical molecular imaging methods, FMT has the characteristics of high sensitivity, low cost, and safety and reliability. It has become the research frontier and research hotspot of optical molecular imaging technology. This paper took an overview of the recent methodology advances in FMT, mainly focused on the photon propagation model of FMT based on the radiative transfer equation (RTE), and the reconstruction problem solution consist of forward problem and inverse problem. We introduce the detailed technologies utilized in reconstruction of FMT. Finally, the challenges in FMT were discussed. This survey aims at summarizing current research hotspots in methodology of FMT, from which future research may benefit.
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Affiliation(s)
- Yu An
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Kun Wang
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
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Yang F, Yao R, Ozturk M, Faulkner D, Qu Q, Intes X. Improving mesoscopic fluorescence molecular tomography via preconditioning and regularization. BIOMEDICAL OPTICS EXPRESS 2018; 9:2765-2778. [PMID: 30258689 PMCID: PMC6154183 DOI: 10.1364/boe.9.002765] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 05/11/2018] [Accepted: 05/15/2018] [Indexed: 05/21/2023]
Abstract
Mesoscopic fluorescence molecular tomography (MFMT) is a novel imaging technique capable of obtaining 3-D distribution of molecular probes inside biological tissues at depths of a few millimeters with a resolution up to ~100 μm. However, the ill-conditioned nature of the MFMT inverse problem severely deteriorates its reconstruction performances. Furthermore, dense spatial sampling and fine discretization of the imaging volume required for high resolution reconstructions make the sensitivity matrix (Jacobian) highly correlated, which prevents even advanced algorithms from achieving optimal solutions. In this work, we propose two computational methods to respectively increase the incoherence of the sensitivity matrix and improve the convergence rate of the inverse solver. We first apply a compressed sensing (CS) based preconditioner on either the whole sensitivity matrix or sub sensitivity matrices to reduce the coherence between columns of the sensitivity matrix. Then we employed a regularization method based on the weight iterative improvement method (WIIM) to mitigate the ill-condition of the sensitivity matrix and to drive the iterative optimization process towards convergence at a faster rate. We performed numerical simulations and phantom experiments to validate the effectiveness of the proposed strategies. In both in silico and in vitro cases, we were able to improve the quality of MFMT reconstructions significantly.
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Affiliation(s)
- Fugang Yang
- School of Information and Electronic Engineering, Shandong Institute of Business and Technology, Yantai 264005, China
| | - Ruoyang Yao
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Mehmet Ozturk
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Denzel Faulkner
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
| | - Qinglan Qu
- Department of Reproductive Medicine, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai 264000, China
| | - Xavier Intes
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
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