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Rocha MB, Pratavieira S, Vieira RS, Geller JD, Stein ALM, de Oliveira FSS, Canuto TRP, de Paula Vieira L, Rossoni R, Santos MCS, Frasson PHL, Krohling RA. Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks. Photodiagnosis Photodyn Ther 2025; 52:104462. [PMID: 39736369 DOI: 10.1016/j.pdpdt.2024.104462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2024] [Revised: 12/19/2024] [Accepted: 12/26/2024] [Indexed: 01/01/2025]
Abstract
In recent years, interest in applying deep learning (DL) to medical diagnosis has rapidly increased, driven primarily by the development of Convolutional Neural Networks and Transformers. Despite advancements in DL, the automated diagnosis of skin cancer remains a significant challenge. Emulating dermatologists, deep learning approaches using clinical images acquired from smartphones and considering patient lesion information have achieved performance levels close to those of specialists. While including clinical information, such as whether the lesion bleeds, hurts, or itches, improves diagnostic metrics, it is insufficient for correctly differentiating some major skin cancer lesions. An alternate technology for diagnosing skin cancer is fluorescence widefield imaging, where the skin lesion is illuminated with excitation light, causing it to emit fluorescence. Since there is no public dataset of fluorescence images for skin lesions, to the best of our knowledge, an effort has been made and resulted in 1,563 fluorescence images of major skin lesions taken by smartphones using the handheld LED wieldfield fluorescence device. The collected images were annotated and analyzed, creating a new dataset named FLUO-SC. Convolutional neural networks were then applied to classify skin lesions using these fluorescence images. Experimental results indicate that fluorescence images are competitive with clinical images (baseline) for classifying major skin lesions and show promising potential for discrimination.
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Affiliation(s)
- Matheus B Rocha
- Labcin - Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil; Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil.
| | | | - Renan Souza Vieira
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
| | - Juliana Duarte Geller
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
| | - Amanda Lima Mutz Stein
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
| | | | - Tania R P Canuto
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Secretary of Health of the Espírito Santo State, Governor of Espírito Santo state, Vitória, Brazil
| | - Luciana de Paula Vieira
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil; Secretary of Health of the Espírito Santo State, Governor of Espírito Santo state, Vitória, Brazil
| | - Renan Rossoni
- Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
| | - Maria C S Santos
- Pathological Anatomy Unit of the University Hospital Cassiano Antônio Moraes (HUCAM), Federal University of Espírito Santo, Vitória, Brazil
| | - Patricia H L Frasson
- Department of Specialized Medicine, Federal University of Espírito Santo, Vitória, Brazil; Dermatological Assistance Program (PAD), Federal University of Espírito Santo, Vitória, Brazil
| | - Renato A Krohling
- Labcin - Nature Inspired Computing Laboratory, Federal University of Espírito Santo, Vitória, Brazil; Graduate Program in Computer Science, Federal University of Espírito Santo, Vitória, Brazil.
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Kumar P, Rathod S. Integration of the fluorescence based portable device with the AI tools for the real-time monitoring of oral mucosal lesions. Sci Rep 2025; 15:10222. [PMID: 40133572 PMCID: PMC11937504 DOI: 10.1038/s41598-025-94676-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Accepted: 03/17/2025] [Indexed: 03/27/2025] Open
Abstract
There is a need for non-invasive, sensitive, real-time, and user-friendly optical devices integrated with artificial intelligence (AI) based tools for the detection of oral mucosal lesions at early stage. Research on the development of optical devices has been executed by several research groups for the cancer detection and it is still being continued. We have also contributed towards it by developing a steady- state fluorescence-based portable device. The in-house developed device is equipped with 405 nm laser diode, UV visible spectrometer, optical components, and other accessories. Laser light irradiated on the oral cavity of diseased (cancerous) and non-diseased (normal) groups, excites the two endogenous fluorophores namely FAD and porphyrin. We observed an enhancement in the porphyrin fluorescence of cancerous patients (OSCC and Dysplasia) than the normal group. Data analysis carried out by AI tools i.e., Naïve Bayes, LDA, and QDA showed slightly higher accuracy for QDA. QDA was able to discriminate among Normal to OSCC, Normal to Dysplasia, and Dysplasia to OSCC with accuracies of 95.34%, 100%, and 97.43% respectively.
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Affiliation(s)
- Pavan Kumar
- Faculty of Engineering and Technology (FEAT), Datta Meghe Institute of Higher Education and Research (DMIHER), Wardha, 442001, India.
- Department of Physics, Indian Institute of Technology Kanpur (IITK), Kanpur, 208016, India.
| | - Shashikant Rathod
- Department of Instrumentation and Control Engineering, COEP Technological University, Pune, 411005, India
- Program Launch Management Analytics, FORDS Motors Pvt. Ltd, Chennai, 600119, India
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Khazaei K, Roshandel P, Parastar H. Visible-short wavelength near infrared hyperspectral imaging coupled with multivariate curve resolution-alternating least squares for diagnosis of breast cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2025; 324:124966. [PMID: 39153346 DOI: 10.1016/j.saa.2024.124966] [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: 05/14/2024] [Revised: 07/26/2024] [Accepted: 08/10/2024] [Indexed: 08/19/2024]
Abstract
This study investigates the application of visible-short wavelength near-infrared hyperspectral imaging (Vis-SWNIR HSI) in the wavelength range of 400-950 nm and advanced chemometric techniques for diagnosing breast cancer (BC). The research involved 56 ex-vivo samples encompassing both cancerous and non-cancerous breast tissue from females. First, HSI images were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to exploit pure spatial and spectral profiles of active components. Then, the MCR-ALS resolved spatial profiles were arranged in a new data matrix for exploration and discrimination between benign and cancerous tissue samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA classification accuracy of 82.1 % showed the potential of HSI and chemometrics for non-invasive detection of BC. Additionally, the resolved spectral profiles by MCR-ALS can be used to track the changes in the breast tissue during cancer and treatment. It is concluded that the proposed strategy in this work can effectively differentiate between cancerous and non-cancerous breast tissue and pave the way for further studies and potential clinical implementation of this innovative approach, offering a promising avenue for improving early detection and treatment outcomes in BC patients.
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Affiliation(s)
- Kazhal Khazaei
- Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran
| | - Pegah Roshandel
- Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran
| | - Hadi Parastar
- Department of Chemistry, Sharif University of Technology, P.O. Box 11155-9516, Tehran, Iran.
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Mann P, Thapa P, Nayyar V, Surya V, Mishra D, Mehta DS. Multispectral polarization microscopy of different stages of human oral tissue: A polarization study. JOURNAL OF BIOPHOTONICS 2024; 17:e202300236. [PMID: 37789505 DOI: 10.1002/jbio.202300236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/05/2023]
Abstract
Many optical techniques have been used in various diagnostics and biomedical applications since a decade and polarization imaging is one of the non-invasive and label free optical technique to investigate biological samples making it an important tool in diagnostics, biomedical applications. We report a multispectral polarization-based imaging of oral tissue by utilizing a polarization microscope system with a broadband-light source. Experiments were performed on oral tissue samples and multispectral Stokes mapping was done by recording a set of intensity images. Polarization-based parameters like degree of polarization, angle of fast axis, retardation and linear birefringence have been retrieved. The statistical moments of these polarization components have also been reported at multiples wavelengths. The polarimetric properties of oral tissue at different stages of cancer have been analyzed and significant changes from normal to pre-cancerous lesions to the cancerous are observed in linear birefringence quantification as (1.7 ± 0.1) × 10-3 , (2.5 ± 0.2) × 10-3 and (3.3 ± 0.2) × 10-3 respectively.
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Affiliation(s)
- Priyanka Mann
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India
| | - Pramila Thapa
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India
| | - Vivek Nayyar
- Department of Oral Pathology and Microbiology, Centre for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Delhi, India
| | - Varun Surya
- Department of Oral Pathology and Microbiology, Centre for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Delhi, India
| | - Deepika Mishra
- Department of Oral Pathology and Microbiology, Centre for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), Delhi, India
| | - Dalip Singh Mehta
- Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India
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Zhou X, Ma L, Mubarak HK, Palsgrove D, Sumer BD, Chen AY, Fei B. Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:016005. [PMID: 38239390 PMCID: PMC10795499 DOI: 10.1117/1.jbo.29.1.016005] [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: 05/01/2023] [Revised: 12/04/2023] [Accepted: 12/20/2023] [Indexed: 01/22/2024]
Abstract
Significance Polarized hyperspectral microscopes with the capability of full Stokes vector imaging have potential for many biological and medical applications. Aim The aim of this study is to investigate polarized hyperspectral imaging (PHSI) for improving the visualization of collagen fibers, which is an important biomarker related to tumor development, and improving the differentiation of normal and tumor cells on pathologic slides. Approach We customized a polarized hyperspectral microscopic imaging system comprising an upright microscope with a motorized stage, two linear polarizers, two liquid crystal variable retarders (LCVRs), and a compact SnapScan hyperspectral camera. The polarizers and LCVRs worked in tandem with the hyperspectral camera to acquire polarized hyperspectral images, which were further used to calculate four Stokes vectors: S 0 , S 1 , S 2 , and S 3 . Synthetic RGB images of the Stokes vectors were generated for the visualization of cellular components in PHSI images. Regions of interest of collagen, normal cells, and tumor cells in the synthetic RGB images were selected, and spectral signatures of the selected components were extracted for comparison. Specifically, we qualitatively and quantitatively investigated the enhanced visualization and spectral characteristics of dense fibers and sparse fibers in normal stroma tissue, fibers accumulated within tumors, and fibers accumulated around tumors. Results By employing our customized polarized hyperspectral microscope, we extract the spectral signatures of Stokes vector parameters of collagen as well as of tumor and normal cells. The measurement of Stokes vector parameters increased the image contrast of collagen fibers and cells in the slides. Conclusions With the spatial and spectral information from the Stokes vector data cubes (S 0 , S 1 , S 2 , and S 3 ), our PHSI microscope system enhances the visualization of tumor cells and tumor microenvironment components, thus being beneficial for pathology and oncology.
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Affiliation(s)
- Ximing Zhou
- The University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- The University of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States
| | - Ling Ma
- The University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- The University of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States
| | - Hasan K. Mubarak
- The University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- The University of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States
| | - Doreen Palsgrove
- The University of Texas Southwestern Medical Center, Department of Pathology, Dallas, Texas, United States
| | - Baran D. Sumer
- The University of Texas Southwestern Medical Center, Department of Otolaryngology, Dallas, Texas, United States
| | - Amy Y. Chen
- Emory University, Department of Otolaryngology, Atlanta, Georgia, United States
| | - Baowei Fei
- The University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- The University of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States
- The University of Texas Southwestern Medical Center, Department of Radiology, Dallas, Texas, United States
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Liao J, Zhang T, Li C, Huang Z. U-shaped fusion convolutional transformer based workflow for fast optical coherence tomography angiography generation in lips. BIOMEDICAL OPTICS EXPRESS 2023; 14:5583-5601. [PMID: 38021117 PMCID: PMC10659781 DOI: 10.1364/boe.502085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/15/2023] [Accepted: 09/23/2023] [Indexed: 12/01/2023]
Abstract
Oral disorders, including oral cancer, pose substantial diagnostic challenges due to late-stage diagnosis, invasive biopsy procedures, and the limitations of existing non-invasive imaging techniques. Optical coherence tomography angiography (OCTA) shows potential in delivering non-invasive, real-time, high-resolution vasculature images. However, the quality of OCTA images are often compromised due to motion artifacts and noise, necessitating more robust and reliable image reconstruction approaches. To address these issues, we propose a novel model, a U-shaped fusion convolutional transformer (UFCT), for the reconstruction of high-quality, low-noise OCTA images from two-repeated OCT scans. UFCT integrates the strengths of convolutional neural networks (CNNs) and transformers, proficiently capturing both local and global image features. According to the qualitative and quantitative analysis in normal and pathological conditions, the performance of the proposed pipeline outperforms that of the traditional OCTA generation methods when only two repeated B-scans are performed. We further provide a comparative study with various CNN and transformer models and conduct ablation studies to validate the effectiveness of our proposed strategies. Based on the results, the UFCT model holds the potential to significantly enhance clinical workflow in oral medicine by facilitating early detection, reducing the need for invasive procedures, and improving overall patient outcomes.
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Affiliation(s)
- Jinpeng Liao
- School of Science and Engineering, University of Dundee, DD1 4HN, Scotland, United Kingdom
| | - Tianyu Zhang
- School of Science and Engineering, University of Dundee, DD1 4HN, Scotland, United Kingdom
| | - Chunhui Li
- School of Science and Engineering, University of Dundee, DD1 4HN, Scotland, United Kingdom
| | - Zhihong Huang
- School of Science and Engineering, University of Dundee, DD1 4HN, Scotland, United Kingdom
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Tran MH, Fei B. Compact and ultracompact spectral imagers: technology and applications in biomedical imaging. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:040901. [PMID: 37035031 PMCID: PMC10075274 DOI: 10.1117/1.jbo.28.4.040901] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 02/27/2023] [Indexed: 05/18/2023]
Abstract
Significance Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging. Aim With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications. Approach We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of "compact," we included a table of dimensions and weights for systems that met our definition. Results There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry-Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings. Conclusions Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.
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Affiliation(s)
- Minh H. Tran
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
| | - Baowei Fei
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- University of Texas Southwestern Medical Center, Department of Radiology, Dallas, Texas, United States
- University of Texas at Dallas, Center for Imaging and Surgical Innovation, Richardson, Texas, United States
- Address all correspondence to Baowei Fei,
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Zhou X, Mubarak HK, Ma L, Palsgrove D, Sumer BD, Fei B. Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2023; 12382:1238204. [PMID: 38481487 PMCID: PMC10932728 DOI: 10.1117/12.2655831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
We developed a polarized hyperspectral microscope to collect four types of Stokes vector data cubes (S0, S1, S2, and S3) of the pathologic slides with head and neck squamous cell carcinoma (HNSCC). Our system consists of an optical light microscope with a movable stage, two polarizers, two liquid crystal variable retarders (LCVRs), and a SnapScan hyperspectral camera. The polarizers and LCVRs work in tandem with the hyperspectral camera to acquire polarized hyperspectral images. Synthetic pseudo-RGB images are generated from the four Stokes vector data cubes based on a transformation function similar to the spectral response of human eye for the visualization of hyperspectral images. Collagen is the most abundant extracellular matrix (ECM) protein in the human body. A major focus of studying the ECM in tumor microenvironment is the role of collagen in both normal and abnormal function. Collagen tends to accumulate in and around tumors during cancer development and growth. In this study, we acquired images from normal regions containing normal cells and collagen fibers and from tumor regions containing cancerous squamous cells and collagen fibers on HNSCC pathologic slides. The preliminary results demonstrated that our customized polarized hyperspectral microscope is able to improve the visualization of collagen on HNSCC pathologic slides under different situations, including thick fibers of normal stroma, thin fibers of normal stroma, fibers of normal muscle cells, fibers accumulated in tumors, fibers accumulated around tumors. Our preliminary results also demonstrated that the customized polarized hyperspectral microscope is capable of extracting the spectral signatures of collagen based on Stokes vector parameters and can have various applications in pathology and oncology.
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Affiliation(s)
- Ximing Zhou
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX
- University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Hasan K. Mubarak
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX
- University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Ling Ma
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX
- University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Doreen Palsgrove
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Baran D. Sumer
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Baowei Fei
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX
- University of Texas at Dallas, Department of Bioengineering, Richardson, TX
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX
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Du X, Koronyo Y, Mirzaei N, Yang C, Fuchs DT, Black KL, Koronyo-Hamaoui M, Gao L. Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau. PNAS NEXUS 2022; 1:pgac164. [PMID: 36157597 PMCID: PMC9491695 DOI: 10.1093/pnasnexus/pgac164] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/15/2022] [Indexed: 01/16/2023]
Abstract
Alzheimer's disease (AD) is a major risk for the aging population. The pathological hallmarks of AD-an abnormal deposition of amyloid β-protein (Aβ) and phosphorylated tau (pTau)-have been demonstrated in the retinas of AD patients, including in prodromal patients with mild cognitive impairment (MCI). Aβ pathology, especially the accumulation of the amyloidogenic 42-residue long alloform (Aβ42), is considered an early and specific sign of AD, and together with tauopathy, confirms AD diagnosis. To visualize retinal Aβ and pTau, state-of-the-art methods use fluorescence. However, administering contrast agents complicates the imaging procedure. To address this problem from fundamentals, ex-vivo studies were performed to develop a label-free hyperspectral imaging method to detect the spectral signatures of Aβ42 and pS396-Tau, and predicted their abundance in retinal cross-sections. For the first time, we reported the spectral signature of pTau and demonstrated an accurate prediction of Aβ and pTau distribution powered by deep learning. We expect our finding will lay the groundwork for label-free detection of AD.
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Affiliation(s)
- Xiaoxi Du
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yosef Koronyo
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Nazanin Mirzaei
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Chengshuai Yang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Dieu-Trang Fuchs
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Keith L Black
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Maya Koronyo-Hamaoui
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Biomedical Sciences, Division of Applied Cell Biology and Physiology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Liang Gao
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
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Zhou X, Ma L, Mubarak HK, Little JV, Chen AY, Myers LL, Sumer BD, Fei B. Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and deep learning. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2022; 12039:120390G. [PMID: 36798940 PMCID: PMC9930132 DOI: 10.1117/12.2614624] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The study is to incorporate polarized hyperspectral imaging (PHSI) with deep learning for automatic detection of head and neck squamous cell carcinoma (SCC) on hematoxylin and eosin (H&E) stained tissue slides. A polarized hyperspectral imaging microscope had been developed in our group. In this paper, we firstly collected the Stokes vector data cubes (S0, S1, S2, and S3) of histologic slides from 17 patients with SCC by the PHSI microscope, under the wavelength range from 467 nm to 750 nm. Secondly, we generated the synthetic RGB images from the original Stokes vector data cubes. Thirdly, we cropped the synthetic RGB images into image patches at the image size of 96×96 pixels, and then set up a ResNet50-based convolutional neural network (CNN) to classify the image patches of the four Stokes vector parameters (S0, S1, S2, and S3) by application of transfer learning. To test the performances of the model, each time we trained the model based on the image patches (S0, S1, S2, and S3) of 16 patients out of 17 patients, and used the trained model to calculate the testing accuracy based on the image patches of the rest 1 patient (S0, S1, S2, and S3). We repeated the process for 6 times and obtained 24 testing accuracies (S0, S1, S2, and S3) from 6 different patients out of the 17 patients. The preliminary results showed that the average testing accuracy (84.2%) on S3 outperformed the average testing accuracy (83.5%) on S0. Furthermore, 4 of 6 testing accuracies of S3 (96.0%, 87.3%, 82.8%, and 86.7%) outperformed the testing accuracies of S0 (93.3%, 85.2%, 80.2%, and 79.0%). The study demonstrated the potential of using polarized hyperspectral imaging and deep learning for automatic detection of head and neck SCC on pathologic slides.
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Affiliation(s)
- Ximing Zhou
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Ling Ma
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Hasan K Mubarak
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - James V. Little
- Emory University, Department of Pathology and Laboratory Medicine, Atlanta, GA
| | - Amy Y. Chen
- Emory University, Department of Otolaryngology, Atlanta, GA
| | - Larry L. Myers
- Univ. of Texas Southwestern Medical Center, Dept. of Otolaryngology, Dallas, TX
| | - Baran D. Sumer
- Univ. of Texas Southwestern Medical Center, Dept. of Otolaryngology, Dallas, TX
| | - Baowei Fei
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
- Univ. of Texas Southwestern Medical Center, Advanced Imaging Research Center, Dallas, TX
- Univ. of Texas Southwestern Medical Center, Dept. of Radiology, Dallas, TX
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Murar M, Albertazzi L, Pujals S. Advanced Optical Imaging-Guided Nanotheranostics towards Personalized Cancer Drug Delivery. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:399. [PMID: 35159744 PMCID: PMC8838478 DOI: 10.3390/nano12030399] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/13/2022] [Accepted: 01/20/2022] [Indexed: 12/12/2022]
Abstract
Nanomedicine involves the use of nanotechnology for clinical applications and holds promise to improve treatments. Recent developments offer new hope for cancer detection, prevention and treatment; however, being a heterogenous disorder, cancer calls for a more targeted treatment approach. Personalized Medicine (PM) aims to revolutionize cancer therapy by matching the most effective treatment to individual patients. Nanotheranostics comprise a combination of therapy and diagnostic imaging incorporated in a nanosystem and are developed to fulfill the promise of PM by helping in the selection of treatments, the objective monitoring of response and the planning of follow-up therapy. Although well-established imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET) and Single-Photon Emission Computed Tomography (SPECT), are primarily used in the development of theranostics, Optical Imaging (OI) offers some advantages, such as high sensitivity, spatial and temporal resolution and less invasiveness. Additionally, it allows for multiplexing, using multi-color imaging and DNA barcoding, which further aids in the development of personalized treatments. Recent advances have also given rise to techniques permitting better penetration, opening new doors for OI-guided nanotheranostics. In this review, we describe in detail these recent advances that may be used to design and develop efficient and specific nanotheranostics for personalized cancer drug delivery.
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Affiliation(s)
- Madhura Murar
- Institute of Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain; (M.M.); (L.A.)
| | - Lorenzo Albertazzi
- Institute of Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain; (M.M.); (L.A.)
- Department of Biomedical Engineering, Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
| | - Silvia Pujals
- Institute of Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain; (M.M.); (L.A.)
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12
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Kistler M, Köhler H, Theopold J, Gockel I, Roth A, Hepp P, Osterhoff G. Intraoperative hyperspectral imaging (HSI) as a new diagnostic tool for the detection of cartilage degeneration. Sci Rep 2022; 12:608. [PMID: 35022498 PMCID: PMC8755763 DOI: 10.1038/s41598-021-04642-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 12/17/2021] [Indexed: 11/09/2022] Open
Abstract
To investigate, whether hyperspectral imaging (HSI) is able to reliably differentiate between healthy and damaged cartilage tissue. A prospective diagnostic study was performed including 21 patients undergoing open knee surgery. HSI data were acquired during surgery, and the joint surface's cartilage was assessed according to the ICRS cartilage injury score. The HSI system records light spectra from 500 to 1000 nm and generates several parameters including tissue water index (TWI) and the absorbance at 960 nm and 540 nm. Receiver operating characteristic curves were calculated to assess test parameters for threshold values of HSI. Areas with a cartilage defect ICRS grade ≥ 3 showed a significantly lower TWI (p = 0.026) and higher values for 540 nm (p < 0.001). No difference was seen for 960 nm (p = 0.244). For a threshold of 540 nm > 0.74, a cartilage defect ICRS grade ≥ 3 could be detected with a sensitivity of 0.81 and a specificity of 0.81. TWI was not suitable for cartilage defect detection. HSI can provide reliable parameters to differentiate healthy and damaged cartilage. Our data clearly suggest that the difference in absorbance at 540 nm would be the best parameter to achieve accurate identification of damaged cartilage.
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Affiliation(s)
- Max Kistler
- Department of Orthopaedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Hannes Köhler
- Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, Leipzig, Germany
| | - Jan Theopold
- Department of Orthopaedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Andreas Roth
- Department of Orthopaedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Pierre Hepp
- Department of Orthopaedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Georg Osterhoff
- Department of Orthopaedics, Trauma and Plastic Surgery, University Hospital Leipzig, 04103, Leipzig, Germany.
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13
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Lyu Z, Jiang H, Xiao F, Rong J, Zhang T, Wandell B, Farrell J. Simulations of fluorescence imaging in the oral cavity. BIOMEDICAL OPTICS EXPRESS 2021; 12:4276-4292. [PMID: 34457414 PMCID: PMC8367257 DOI: 10.1364/boe.429995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 05/31/2021] [Accepted: 06/01/2021] [Indexed: 06/13/2023]
Abstract
We describe an end-to-end image systems simulation that models a device capable of measuring fluorescence in the oral cavity. Our software includes a 3D model of the oral cavity and excitation-emission matrices of endogenous fluorophores that predict the spectral radiance of oral mucosal tissue. The predicted radiance is transformed by a model of the optics and image sensor to generate expected sensor image values. We compare simulated and real camera data from tongues in healthy individuals and show that the camera sensor chromaticity values can be used to quantify the fluorescence from porphyrins relative to the bulk fluorescence from multiple fluorophores (elastin, NADH, FAD, and collagen). Validation of the simulations supports the use of soft-prototyping in guiding system design for fluorescence imaging.
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Affiliation(s)
- Zheng Lyu
- Stanford Center for Image Systems Engineering, Stanford, California 94305, USA
- Department of Electrical Engineering, Stanford, California 94305, USA
| | | | - Feng Xiao
- Fengyun Vision Technologies, Beijing 100080, China
| | - Jian Rong
- Fengyun Vision Technologies, Beijing 100080, China
| | | | - Brian Wandell
- Stanford Center for Image Systems Engineering, Stanford, California 94305, USA
- Psychology Department, Stanford, California 94305, USA
| | - Joyce Farrell
- Stanford Center for Image Systems Engineering, Stanford, California 94305, USA
- Department of Electrical Engineering, Stanford, California 94305, USA
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14
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Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection. SENSORS 2021; 21:s21093219. [PMID: 34066507 PMCID: PMC8125388 DOI: 10.3390/s21093219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 05/01/2021] [Accepted: 05/01/2021] [Indexed: 11/26/2022]
Abstract
This aim of this study was to find effective spectral bands for the early detection of oral cancer. The spectral images in different bands were acquired using a self-made portable light-emitting diode (LED)-induced autofluorescence multispectral imager equipped with 365 and 405 nm excitation LEDs, emission filters with center wavelengths of 470, 505, 525, 532, 550, 595, 632, 635, and 695 nm, and a color image sensor. The spectral images of 218 healthy points in 62 healthy participants and 218 tumor points in 62 patients were collected in the ex vivo trials at China Medical University Hospital. These ex vivo trials were similar to in vivo because the spectral images of anatomical specimens were immediately acquired after the on-site tumor resection. The spectral images associated with red, blue, and green filters correlated with and without nine emission filters were quantized by four computing method, including summated intensity, the highest number of the intensity level, entropy, and fractional dimension. The combination of four computing methods, two excitation light sources with two intensities, and 30 spectral bands in three experiments formed 264 classifiers. The quantized data in each classifier was divided into two groups: one was the training group optimizing the threshold of the quantized data, and the other was validating group tested under this optimized threshold. The sensitivity, specificity, and accuracy of each classifier were derived from these tests. To identify the influential spectral bands based on the area under the region and the testing results, a single-layer network learning process was used. This was compared to conventional rules-based approaches to show its superior and faster performance. Consequently, four emission filters with the center wavelengths of 470, 505, 532, and 550 nm were selected by an AI-based method and verified using a rule-based approach. The sensitivities of six classifiers using these emission filters were more significant than 90%. The average sensitivity of these was about 96.15%, the average specificity was approximately 69.55%, and the average accuracy was about 82.85%.
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15
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Guerraty M, Bhargava A, Senarathna J, Mendelson AA, Pathak AP. Advances in translational imaging of the microcirculation. Microcirculation 2021; 28:e12683. [PMID: 33524206 PMCID: PMC8647298 DOI: 10.1111/micc.12683] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/18/2021] [Accepted: 01/26/2021] [Indexed: 12/21/2022]
Abstract
The past few decades have seen an explosion in the development and use of methods for imaging the human microcirculation during health and disease. The confluence of innovative imaging technologies, affordable computing power, and economies of scale have ushered in a new era of "translational" imaging that permit us to peer into blood vessels of various organs in the human body. These imaging techniques include near-infrared spectroscopy (NIRS), positron emission tomography (PET), and magnetic resonance imaging (MRI) that are sensitive to microvascular-derived signals, as well as computed tomography (CT), optical imaging, and ultrasound (US) imaging that are capable of directly acquiring images at, or close to microvascular spatial resolution. Collectively, these imaging modalities enable us to characterize the morphological and functional changes in a tissue's microcirculation that are known to accompany the initiation and progression of numerous pathologies. Although there have been significant advances for imaging the microcirculation in preclinical models, this review focuses on developments in the assessment of the microcirculation in patients with optical imaging, NIRS, PET, US, MRI, and CT, to name a few. The goal of this review is to serve as a springboard for exploring the burgeoning role of translational imaging technologies for interrogating the structural and functional status of the microcirculation in humans, and highlight the breadth of current clinical applications. Making the human microcirculation "visible" in vivo to clinicians and researchers alike will facilitate bench-to-bedside discoveries and enhance the diagnosis and management of disease.
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Affiliation(s)
- Marie Guerraty
- Division of Cardiovascular Medicine, Department of
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA,
USA
| | - Akanksha Bhargava
- Russell H. Morgan Department of Radiology and Radiological
Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Janaka Senarathna
- Russell H. Morgan Department of Radiology and Radiological
Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Asher A. Mendelson
- Department of Medicine, Section of Critical Care, Rady
Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Arvind P. Pathak
- Russell H. Morgan Department of Radiology and Radiological
Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, The Johns Hopkins
University School of Medicine, Baltimore, MD, USA
- Department of Electrical Engineering, Johns Hopkins
University, Baltimore, MD, USA
- Sidney Kimmel Comprehensive Cancer Center, The Johns
Hopkins University School of Medicine, Baltimore, MD, USA
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16
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Zhou X, Ma L, Brown W, Little JV, Chen AY, Myers LL, Sumer BD, Fei B. Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and machine learning. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 11603:116030Q. [PMID: 34955584 PMCID: PMC8699168 DOI: 10.1117/12.2582330] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The aim of this study is to incorporate polarized hyperspectral imaging (PHSI) with machine learning for automatic detection of head and neck squamous cell carcinoma (SCC) on hematoxylin and eosin (H&E) stained tissue slides. A polarized hyperspectral imaging microscope had been developed in our group. In this paper, we imaged 20 H&E stained tissue slides from 10 patients with SCC of the larynx by the PHSI microscope. Several machine learning algorithms, including support vector machine (SVM), random forest, Gaussian naive Bayes, and logistic regression, were applied to the collected image data for the automatic detection of SCC on the H&E stained tissue slides. The performance of these methods was compared among the collected PHSI data, the pseudo-RGB images generated from the PHSI data, and the PHSI data after applying the principal component analysis (PCA) transformation. The results suggest that SVM is a superior classifier for the classification task based on the PHSI data cubes compared to the other three classifiers. The incorporate of four Stokes vector parameters improved the classification accuracy. Finally, the PCA transformed image data did not improve the accuracy as it might lose some important information from the original PHSI data. The preliminary results show that polarized hyperspectral imaging can have many potential applications in digital pathology.
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Affiliation(s)
- Ximing Zhou
- The University of Texas at Dallas, Department of Bioengineering and Center for Imaging and Surgical Innovation, Richardson, TX
| | - Ling Ma
- The University of Texas at Dallas, Department of Bioengineering and Center for Imaging and Surgical Innovation, Richardson, TX
| | - William Brown
- The University of Texas at Dallas, Department of Bioengineering and Center for Imaging and Surgical Innovation, Richardson, TX
| | - James V. Little
- Emory University, Department of Pathology and Laboratory
Medicine, Atlanta, GA
| | - Amy Y. Chen
- Emory University, Department of Otolaryngology, Atlanta,
GA
| | - Larry L. Myers
- Univ. of Texas Southwestern Medical Center, Dept. of
Otolaryngology, Dallas, TX
| | - Baran D. Sumer
- Univ. of Texas Southwestern Medical Center, Dept. of
Otolaryngology, Dallas, TX
| | - Baowei Fei
- The University of Texas at Dallas, Department of Bioengineering and Center for Imaging and Surgical Innovation, Richardson, TX
- Univ. of Texas Southwestern Medical Center, Advanced
Imaging Research Center, Dallas, TX
- Univ. of Texas Southwestern Medical Center, Dept. of
Radiology, Dallas, TX
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17
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Ma L, Fei B. Comprehensive review of surgical microscopes: technology development and medical applications. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-200292VRR. [PMID: 33398948 PMCID: PMC7780882 DOI: 10.1117/1.jbo.26.1.010901] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/04/2020] [Indexed: 05/06/2023]
Abstract
SIGNIFICANCE Surgical microscopes provide adjustable magnification, bright illumination, and clear visualization of the surgical field and have been increasingly used in operating rooms. State-of-the-art surgical microscopes are integrated with various imaging modalities, such as optical coherence tomography (OCT), fluorescence imaging, and augmented reality (AR) for image-guided surgery. AIM This comprehensive review is based on the literature of over 500 papers that cover the technology development and applications of surgical microscopy over the past century. The aim of this review is threefold: (i) providing a comprehensive technical overview of surgical microscopes, (ii) providing critical references for microscope selection and system development, and (iii) providing an overview of various medical applications. APPROACH More than 500 references were collected and reviewed. A timeline of important milestones during the evolution of surgical microscope is provided in this study. An in-depth technical overview of the optical system, mechanical system, illumination, visualization, and integration with advanced imaging modalities is provided. Various medical applications of surgical microscopes in neurosurgery and spine surgery, ophthalmic surgery, ear-nose-throat (ENT) surgery, endodontics, and plastic and reconstructive surgery are described. RESULTS Surgical microscopy has been significantly advanced in the technical aspects of high-end optics, bright and shadow-free illumination, stable and flexible mechanical design, and versatile visualization. New imaging modalities, such as hyperspectral imaging, OCT, fluorescence imaging, photoacoustic microscopy, and laser speckle contrast imaging, are being integrated with surgical microscopes. Advanced visualization and AR are being added to surgical microscopes as new features that are changing clinical practices in the operating room. CONCLUSIONS The combination of new imaging technologies and surgical microscopy will enable surgeons to perform challenging procedures and improve surgical outcomes. With advanced visualization and improved ergonomics, the surgical microscope has become a powerful tool in neurosurgery, spinal, ENT, ophthalmic, plastic and reconstructive surgeries.
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Affiliation(s)
- Ling Ma
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
| | - Baowei Fei
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- University of Texas Southwestern Medical Center, Department of Radiology, Dallas, Texas, United States
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18
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Pal R, Villarreal P, Yu X, Qiu S, Vargas G. Multimodal widefield fluorescence imaging with nonlinear optical microscopy workflow for noninvasive oral epithelial neoplasia detection: a preclinical study. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200213R. [PMID: 33200597 PMCID: PMC7667429 DOI: 10.1117/1.jbo.25.11.116008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/02/2020] [Indexed: 05/06/2023]
Abstract
SIGNIFICANCE Early detection of epithelial cancers and precancers/neoplasia in the presence of benign lesions is challenging due to the lack of robust in vivo imaging and biopsy guidance techniques. Label-free nonlinear optical microscopy (NLOM) has shown promise for optical biopsy through the detection of cellular and extracellular signatures of neoplasia. Although in vivo microscopy techniques continue to be developed, the surface area imaged in microscopy is limited by the field of view. FDA-approved widefield fluorescence (WF) imaging systems that capture autofluorescence signatures of neoplasia provide molecular information at large fields of view, which may complement the cytologic and architectural information provided by NLOM. AIM A multimodal imaging approach with high-sensitivity WF and high-resolution NLOM was investigated to identify and distinguish image-based features of neoplasia from normal and benign lesions. APPROACH In vivo label-free WF imaging and NLOM was performed in preclinical hamster models of oral neoplasia and inflammation. Analyses of WF imaging, NLOM imaging, and dual modality (WF combined with NLOM) were performed. RESULTS WF imaging showed increased red-to-green autofluorescence ratio in neoplasia compared to inflammation and normal oral mucosa (p < 0.01). In vivo assessment of the mucosal tissue with NLOM revealed subsurface cytologic (nuclear pleomorphism) and architectural (remodeling of extracellular matrix) atypia in histologically confirmed neoplastic tissue, which were not observed in inflammation or normal mucosa. Univariate and multivariate statistical analysis of macroscopic and microscopic image-based features indicated improved performance (94% sensitivity and 97% specificity) of a multiscale approach over WF alone, even in the presence of benign lesions (inflammation), a common confounding factor in diagnostics. CONCLUSIONS A multimodal imaging approach integrating strengths from WF and NLOM may be beneficial in identifying oral neoplasia. Our study could guide future studies on human oral neoplasia to further evaluate merits and limitations of multimodal workflows and inform the development of multiscale clinical imaging systems.
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Affiliation(s)
- Rahul Pal
- Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Paula Villarreal
- The University of Texas Medical Branch, Biomedical Engineering and Imaging Sciences Group, Galveston, Texas, United States
- The University of Texas Medical Branch, Department of Neuroscience, Cell Biology, and Anatomy, Galveston, Texas, United States
| | - Xiaoying Yu
- The University of Texas Medical Branch, Department of Preventive Medicine and Population Health, Galveston, Texas, United States
| | - Suimin Qiu
- The University of Texas Medical Branch, Department of Pathology, Galveston, Texas, United States
| | - Gracie Vargas
- The University of Texas Medical Branch, Biomedical Engineering and Imaging Sciences Group, Galveston, Texas, United States
- The University of Texas Medical Branch, Department of Neuroscience, Cell Biology, and Anatomy, Galveston, Texas, United States
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19
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Zhou X, Ma L, Halicek M, Dormer J, Fei B. Development of a new polarized hyperspectral imaging microscope. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2020; 11213:1121308. [PMID: 32577044 PMCID: PMC7309561 DOI: 10.1117/12.2549676] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In this study, we proposed and designed a transmission mode polarized hyperspectral imaging microscope (PHSIM). The hyperspectral imaging (HSI) component is based on the snapscan with a hyperspectral camera. The HSI wavelength range is from 467-700 nm. Polarized light imaging is realized by the integration of two polarizers and two liquid crystal variable retarders (LCVR), which is capable of full Stokes polarimetric imaging. The new imaging device was tested for the detection of squamous cell carcinoma (SCC) in H&E stained oral tissue slides of 8 patients. One normal area and one cancerous area on each slide are selected to make the comparison. The preliminary results indicated that the spectral curves of the Stokes vector parameters (S0, S1, S2, S3) of the normal area on the H&E stained oral tissue slides are different from those of SCC in certain wavelength range. Further work is required to apply the new polarized hyperspectral imaging microscope to a large number of patient samples and to test the PHSIM system in different cancer types.
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Affiliation(s)
- Ximing Zhou
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Ling Ma
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Martin Halicek
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - James Dormer
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
| | - Baowei Fei
- The University of Texas at Dallas, Department of Bioengineering, Richardson, TX
- University of Texas Southwestern Medical Center, Department of Radiology, Dallas, TX
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20
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Lee Y, Kim J, Bae S, Seo JM. Design of Microscope Optics for the Acquisition of Multiple Wavelength Band Image. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:4423-4426. [PMID: 31946847 DOI: 10.1109/embc.2019.8857424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We design combinations of filters that lead to make outputs of multiple wavelength bands simultaneously. These bands are either 1) Infrared, RGB, Ultraviolet-3ranges 2) IR, Red, Green, Blue, UV-5ranges 3) IR+ Red, Green, Blue+UV-3ranges. Each is mostly devised by the arrangement of normal cold mirror, UV cold mirror, Philips(RGB) prism, UV filter and color filter. For the selection 1), UV cold mirror reflects UV and transmit VIS + IR. VIS and IR are sorted by normal cold mirror, which passes IR and reflects VIS. Each sorted light goes to each sensor to capture the images. The sorting of VIS and UV also can be done by UV filter. For the selection 2), have a same process in 1) but make VIS pass Philips(RGB) prism which sorts VIS into R, G, B. For the selection 3), the light passes green color filter first, Green color is only transmitted and the others are reflected. And then reflected light goes through UV cold mirror so that UV and Blue (wavelength <; 500nm) are reflected. And the others(wavelength>550nm, but green color zone was already sorted roughly wavelength>600nm) are transmitted, which is Red and IR. This sorting can be done by another design. After sorting all ranges by the selection 2), we can arrange UV goes a same pass with blue, and IR with red. We need band pass filters (in here, color filters) to revise the passes.
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21
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Yang EC, Vohra IS, Badaoui H, Schwarz RA, Cherry KD, Jacob J, Rodriguez J, Williams MD, Vigneswaran N, Gillenwater AM, Richards-Kortum RR. Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study. Head Neck 2019; 42:171-179. [PMID: 31621979 PMCID: PMC7003735 DOI: 10.1002/hed.25978] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 09/03/2019] [Accepted: 09/17/2019] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Multimodal optical imaging, incorporating reflectance and fluorescence modalities, is a promising tool to detect oral premalignant lesions in real-time. METHODS Images were acquired from 171 sites in 66 patient visits for clinical evaluation of oral lesions. An automated algorithm was used to classify lesions as high- or low-risk for neoplasia. Biopsies were acquired at clinically indicated sites and those classified as high-risk by imaging, at the surgeon's discretion. RESULTS Twenty sites were biopsied based on clinical examination or imaging. Of these, 12 were indicated clinically and by imaging; 58% were moderate dysplasia or worse. Four biopsies were indicated by imaging evaluation only; 75% were moderate dysplasia or worse. Finally, four biopsies were indicated by clinical evaluation only; 75% were moderate dysplasia or worse. CONCLUSION Multimodal imaging identified more cases of high-grade dysplasia than clinical evaluation, and can improve detection of high grade precancer in patients with oral lesions.
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Affiliation(s)
- Eric C Yang
- MD/PhD Medical Scientist Training Program, Baylor College of Medicine, Houston, Texas, USA
| | - Imran S Vohra
- Department of Bioengineering, Rice University, Houston, Texas, USA
| | - Hawraa Badaoui
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
| | | | - Katelin D Cherry
- Department of Bioengineering, Rice University, Houston, Texas, USA
| | - Justin Jacob
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
| | - Jessica Rodriguez
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
| | - Michelle D Williams
- Department of Pathology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
| | - Nadarajah Vigneswaran
- Department of Diagnostic and Biomedical Sciences, The University of Texas Health Science Center at Houston School of Dentistry, Houston, Texas
| | - Ann M Gillenwater
- Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, Texas
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22
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Shapey J, Xie Y, Nabavi E, Bradford R, Saeed SR, Ourselin S, Vercauteren T. Intraoperative multispectral and hyperspectral label-free imaging: A systematic review of in vivo clinical studies. JOURNAL OF BIOPHOTONICS 2019; 12:e201800455. [PMID: 30859757 PMCID: PMC6736677 DOI: 10.1002/jbio.201800455] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/26/2019] [Accepted: 03/08/2019] [Indexed: 05/21/2023]
Abstract
Multispectral and hyperspectral imaging (HSI) are emerging optical imaging techniques with the potential to transform the way surgery is performed but it is not clear whether current systems are capable of delivering real-time tissue characterization and surgical guidance. We conducted a systematic review of surgical in vivo label-free multispectral and HSI systems that have been assessed intraoperatively in adult patients, published over a 10-year period to May 2018. We analysed 14 studies including 8 different HSI systems. Current in-vivo HSI systems generate an intraoperative tissue oxygenation map or enable tumour detection. Intraoperative tissue oxygenation measurements may help to predict those patients at risk of postoperative complications and in-vivo intraoperative tissue characterization may be performed with high specificity and sensitivity. All systems utilized a line-scanning or wavelength-scanning method but the spectral range and number of spectral bands employed varied significantly between studies and according to the system's clinical aim. The time to acquire a hyperspectral cube dataset ranged between 5 and 30 seconds. No safety concerns were reported in any studies. A small number of studies have demonstrated the capabilities of intraoperative in-vivo label-free HSI but further work is needed to fully integrate it into the current surgical workflow.
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Affiliation(s)
- Jonathan Shapey
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Yijing Xie
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Eli Nabavi
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Robert Bradford
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - Shakeel R Saeed
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
- The Ear Institute, University College London, London, UK
- The Royal National Throat, Nose and Ear Hospital, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Tom Vercauteren
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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23
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Johnson A, Baeten J, Patel K, Killian M, Sunny S, Suresh A, Uma K, Birur P, Kuriakose M, Kademani D. Evaluation of a Lectin-Based Imaging System for the Chairside Detection of Oral Dysplasia and Malignancy. J Oral Maxillofac Surg 2019; 77:1941-1951. [PMID: 31004587 DOI: 10.1016/j.joms.2019.03.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 03/14/2019] [Accepted: 03/14/2019] [Indexed: 02/04/2023]
Abstract
PURPOSE Currently available oral cancer screening adjuncts have not enhanced clinical screening methods because of high false positives and negatives, highlighting the need for a molecularly specific technique for accurate screening of suspicious oral lesions. The purpose of this study was to evaluate the in vivo screening accuracy of an oral lesion identification system that evaluates aberrant glycosylation patterns using a fluorescently labeled lectin (wheat germ agglutinin and fluorescein isothiocyanate [WGA-FITC]). MATERIALS AND METHODS The authors designed and implemented a prospective cohort study at 3 institutions composed of patients with and without suspicious oral lesions. Oral cavities were screened by clinical examination and with the oral lesion identification system according to a stepwise procedure that included the topical application and fluorescence visualization of a fluorescent nuclear stain and WGA-FITC. Tissue samples were obtained from all enrolled patients for histopathological diagnosis and were used to calculate sensitivity and specificity metrics (primary outcome variable) irrespective of the oral lesion identification system result. RESULTS The sample was composed of 97 patients; 86 had 100 clinically suspicious lesions and 11 without such lesions were included as a control group. Use of the oral lesion identification system resulted in 100, 100, and 74% sensitivity for cancer, high-grade dysplasia, and low-grade dysplasia, respectively, and a specificity of 80%. Clinical diagnosis yielded similar sensitivity values of 84, 100, and 88% for cancer, high-grade dysplasia, and low-grade dysplasia, respectively, and a specificity of 76%. Use of the oral lesion identification system enhanced the visualization of lesion dimensionality and borders. CONCLUSIONS The results of this study suggest the oral lesion identification system was a beneficial adjunct to standard clinical examination, because the system provided sensitivity and specificity values similar to or greater than clinical diagnosis.
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Affiliation(s)
| | - John Baeten
- Director of Engineering/Research and Development, Inter-Med, Inc, Racine, WI
| | - Ketan Patel
- Attending Surgeon, North Memorial Health Care, Robbinsdale, MN
| | - Molly Killian
- Clinical Research Coordinator, North Memorial Health Care, Robbinsdale, MN
| | - Sumsum Sunny
- Fellow, Mazumdar Shaw Cancer Center, Bangalore, India
| | - Amritha Suresh
- Research Scientist, Mazumdar Shaw Cancer Center, Bangalore, India
| | - K Uma
- Oral Pathologist, KLES Dental College, Bangalore, India
| | - Praveen Birur
- Professor and Department Head, Oral Medicine and Radiology, KLES Dental College, Bangalore, India
| | - Moni Kuriakose
- Professor and Director, Department of Surgical Oncology, Narayana Hrudayalaya Hospital, Bangalore, India; Professor of Oncology and Director of Head and Neck Oncology Research Program, Roswell Park Cancer Institute, Buffalo, NY
| | - Deepak Kademani
- Chief of Surgery, Chief and Fellowship Director, Oral and Maxillofacial Surgery, North Memorial Medical Center, Robbinsdale, MN.
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Halicek M, Little JV, Wang X, Chen AY, Fei B. Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-9. [PMID: 30891966 PMCID: PMC6975184 DOI: 10.1117/1.jbo.24.3.036007] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 01/14/2019] [Indexed: 05/21/2023]
Abstract
For patients undergoing surgical cancer resection of squamous cell carcinoma (SCCa), cancer-free surgical margins are essential for good prognosis. We developed a method to use hyperspectral imaging (HSI), a noncontact optical imaging modality, and convolutional neural networks (CNNs) to perform an optical biopsy of ex-vivo, surgical gross-tissue specimens, collected from 21 patients undergoing surgical cancer resection. Using a cross-validation paradigm with data from different patients, the CNN can distinguish SCCa from normal aerodigestive tract tissues with an area under the receiver operator curve (AUC) of 0.82. Additionally, normal tissue from the upper aerodigestive tract can be subclassified into squamous epithelium, muscle, and gland with an average AUC of 0.94. After separately training on thyroid tissue, the CNN can differentiate between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multinodular goiter (MNG) with an AUC of 0.93. Classical-type papillary thyroid carcinoma is differentiated from MNG with an AUC of 0.91. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multicategory diagnostic information for normal and cancerous head-and-neck tissue, and more patient data are needed to fully investigate the potential and reliability of the proposed technique.
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Affiliation(s)
- Martin Halicek
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- Emory University and Georgia Institute of Technology, Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - James V. Little
- Emory University School of Medicine, Department of Pathology and Laboratory Medicine, Atlanta, Georgia, United States
| | - Xu Wang
- Emory University School of Medicine, Department of Hematology and Medical Oncology, Atlanta, Georgia, United States
| | - Amy Y. Chen
- Emory University School of Medicine, Department of Otolaryngology, Atlanta, Georgia, United States
| | - Baowei Fei
- University of Texas at Dallas, Department of Bioengineering, Richardson, Texas, United States
- Emory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia, United States
- University of Texas Southwestern Medical Center, Advanced Imaging Research Center, Dallas, Texas, United States
- University of Texas Southwestern Medical Center, Department of Radiology, Dallas, Texas, United States
- Address all correspondence to Baowei Fei, E-mail:
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Uthoff RD, Song B, Sunny S, Patrick S, Suresh A, Kolur T, Keerthi G, Spires O, Anbarani A, Wilder-Smith P, Kuriakose MA, Birur P, Liang R. Point-of-care, smartphone-based, dual-modality, dual-view, oral cancer screening device with neural network classification for low-resource communities. PLoS One 2018; 13:e0207493. [PMID: 30517120 PMCID: PMC6281283 DOI: 10.1371/journal.pone.0207493] [Citation(s) in RCA: 94] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 10/30/2018] [Indexed: 01/17/2023] Open
Abstract
Oral cancer is a growing health issue in a number of low- and middle-income countries (LMIC), particularly in South and Southeast Asia. The described dual-modality, dual-view, point-of-care oral cancer screening device, developed for high-risk populations in remote regions with limited infrastructure, implements autofluorescence imaging (AFI) and white light imaging (WLI) on a smartphone platform, enabling early detection of pre-cancerous and cancerous lesions in the oral cavity with the potential to reduce morbidity, mortality, and overall healthcare costs. Using a custom Android application, this device synchronizes external light-emitting diode (LED) illumination and image capture for AFI and WLI. Data is uploaded to a cloud server for diagnosis by a remote specialist through a web app, with the ability to transmit triage instructions back to the device and patient. Finally, with the on-site specialist's diagnosis as the gold-standard, the remote specialist and a convolutional neural network (CNN) were able to classify 170 image pairs into 'suspicious' and 'not suspicious' with sensitivities, specificities, positive predictive values, and negative predictive values ranging from 81.25% to 94.94%.
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Affiliation(s)
- Ross D. Uthoff
- College of Optical Sciences, The University of Arizona, Tucson, Arizona, United States of America
- * E-mail: (RDU); (BS); (RL)
| | - Bofan Song
- College of Optical Sciences, The University of Arizona, Tucson, Arizona, United States of America
- * E-mail: (RDU); (BS); (RL)
| | - Sumsum Sunny
- Mazumdar Shaw Medical Centre, Bangalore, India
- Mazumdar Shaw Medical Foundation, Bangalore, India
| | | | - Amritha Suresh
- Mazumdar Shaw Medical Centre, Bangalore, India
- Mazumdar Shaw Medical Foundation, Bangalore, India
| | | | - G. Keerthi
- KLE Society’s Institute of Dental Sciences, Bangalore, India
| | - Oliver Spires
- College of Optical Sciences, The University of Arizona, Tucson, Arizona, United States of America
| | - Afarin Anbarani
- Beckman Laser Institute, University of California, Irvine, Irvine, California, United States of America
| | - Petra Wilder-Smith
- Beckman Laser Institute, University of California, Irvine, Irvine, California, United States of America
| | - Moni Abraham Kuriakose
- Mazumdar Shaw Medical Centre, Bangalore, India
- Mazumdar Shaw Medical Foundation, Bangalore, India
| | - Praveen Birur
- Biocon Foundation, Bangalore, India
- KLE Society’s Institute of Dental Sciences, Bangalore, India
| | - Rongguang Liang
- College of Optical Sciences, The University of Arizona, Tucson, Arizona, United States of America
- * E-mail: (RDU); (BS); (RL)
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Abdel Gawad AL, El-Sharkawy Y, Ayoub HS, El-Sherif AF, Hassan MF. Classification of dental diseases using hyperspectral imaging and laser induced fluorescence. Photodiagnosis Photodyn Ther 2018; 25:128-135. [PMID: 30500670 DOI: 10.1016/j.pdpdt.2018.11.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 11/15/2018] [Accepted: 11/26/2018] [Indexed: 10/27/2022]
Abstract
PURPOSE Early diagnosis of tooth enamel demineralization, and dentin caries lesions, present a valuable solution to avoid or decrease their deleterious effect. The aim of this study was to design a simple, effective, and non-invasive technique, employing a novel laser wavelength to classify and differentiate between various tooth abnormalities in-vitro, by estimating wavelengths, showing distinctive appearance for each tooth class. METHODS This study implies a fluorescence hyperspectral imaging system employing a 395-nm laser diode source, irradiating a pre-diagnosed 12 molars and premolars teeth. The obtained reconstructed images were displayed and processed by HSAnalysis2XL, accompanied by a custom made digital, and image signal processing algorithms, revealing the exact wavelengths, characterizing the fluorescence of each tooth pre-diagnosed class. RESULTS The proposed hyperspectral imaging system was able to discriminate between normal, and abnormal dental classes for the entire specimens. Furthermore, a series of wavelengths, noting each lesion individually were obtained from the spectroscopic hyperspectral output. The root calculus, white spot, dentin caries, and enamel caries have a bright visual appearance at λ3 = 702 nm, λ5 = 771 nm, and λ6 = 798 nm respectively. Consequently, these abnormalities exhibit a dark appearance at λ1 = 421 nm, λ2 = 462 nm, and λ4 = 734 nm. The wavelength selections were confirmed by the grayscale image outcomes. CONCLUSIONS This study provides a set of wavelengths that can be employed by dentists to diagnose white spot, root calculus, and enamel dentin caries lesions under the irradiation of a new UV-vis laser illumination source without, any hazardous thermal or mechanical effects.
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Affiliation(s)
| | - Yasser El-Sharkawy
- Department of Biomedical Engineering, Military Technical College, Cairo, Egypt
| | - H S Ayoub
- Department of Physics, Faculty of Science, Cairo University, Egypt
| | - Ashraf F El-Sherif
- Laser Photonics Research Center, Engineering Physics Department, Military Technical College, Cairo, Egypt
| | - Mahmoud F Hassan
- Laser Photonics Research Center, Engineering Physics Department, Military Technical College, Cairo, Egypt
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27
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Huang TT, Chen KC, Wong TY, Chen CY, Chen WC, Chen YC, Chang MH, Wu DY, Huang TY, Nioka S, Chung PC, Huang JS. Two-channel autofluorescence analysis for oral cancer. JOURNAL OF BIOMEDICAL OPTICS 2018; 24:1-10. [PMID: 30411551 PMCID: PMC6992899 DOI: 10.1117/1.jbo.24.5.051402] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 08/01/2018] [Indexed: 06/08/2023]
Abstract
We created a two-channel autofluorescence test to detect oral cancer. The wavelengths 375 and 460 nm, with filters of 479 and 525 nm, were designed to excite and detect reduced-form nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) autofluorescence. Patients with oral cancer or with precancerous lesions, and a control group with healthy oral mucosae, were enrolled. The lesion in the autofluorescent image was the region of interest. The average intensity and heterogeneity of the NADH and FAD were calculated. The redox ratio [(NADH)/(NADH + FAD)] was also computed. A quadratic discriminant analysis (QDA) was used to compute boundaries based on sensitivity and specificity. We analyzed 49 oral cancer lesions, 34 precancerous lesions, and 77 healthy oral mucosae. A boundary (sensitivity: 0.974 and specificity: 0.898) between the oral cancer lesions and healthy oral mucosae was validated. Oral cancer and precancerous lesions were also differentiated from healthy oral mucosae (sensitivity: 0.919 and specificity: 0.755). The two-channel autofluorescence detection device and analyses of the intensity and heterogeneity of NADH, and of FAD, and the redox ratio combined with a QDA classifier can differentiate oral cancer and precancerous lesions from healthy oral mucosae.
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Affiliation(s)
- Tze-Ta Huang
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Ken-Chung Chen
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Tung-Yiu Wong
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | | | | | - Yi-Chun Chen
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
| | - Ming-Hsuan Chang
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Dong-Yuan Wu
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Teng-Yi Huang
- National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan, Taiwan
| | - Shoko Nioka
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
| | - Pau-Choo Chung
- National Cheng Kung University, Department of Electrical Engineering, Tainan, Taiwan
| | - Jehn-Shyun Huang
- National Cheng Kung University Hospital, Department of Stomatology, Division of Oral and Maxillofacial Surgery, Tainan, Taiwan
- National Cheng Kung University Medical College and Hospital, Institute of Oral Medicine, Tainan, Taiwan
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Ex Vivo Hyperspectral Autofluorescence Imaging and Localization of Fluorophores in Human Eyes with Age-Related Macular Degeneration. Vision (Basel) 2018; 2:vision2040038. [PMID: 31735901 PMCID: PMC6835627 DOI: 10.3390/vision2040038] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 05/19/2018] [Accepted: 09/12/2018] [Indexed: 12/28/2022] Open
Abstract
To characterize fluorophore signals from drusen and retinal pigment epithelium (RPE) and their changes in age related macular degeneration (AMD), the authors describe advances in ex vivo hyperspectral autofluorescence (AF) imaging of human eye tissue. Ten RPE flatmounts from eyes with AMD and 10 from eyes without AMD underwent 40× hyperspectral AF microscopic imaging. The number of excitation wavelengths tested was initially two (436 nm and 480 nm), then increased to three (436 nm, 480 nm, and 505 nm). Emission spectra were collected at 10 nm intervals from 420 nm to 720 nm. Non-negative matrix factorization (NMF) algorithms decomposed the hyperspectral images into individual emission spectra and their spatial abundances. These include three distinguishable spectra for RPE fluorophores (S1, S2, and S3) in both AMD and non-AMD eyes, a spectrum for drusen (SDr) only in AMD eyes, and a Bruch's membrane spectrum that was detectable in normal eyes. Simultaneous analysis of datacubes excited atthree excitation wavelengths revealed more detailed spatial localization of the RPE spectra and SDr within drusen than exciting only at two wavelengths. Within AMD and non-AMD groups, two different NMF initialization methods were tested on each group and converged to qualitatively similar spectra. In AMD, the peaks of the SDr at ~510 nm (436 nm excitation) were particularly consistent. Between AMD and non-AMD groups, corresponding spectra in common, S1, S2, and S3, also had similar peak locations and shapes, but with some differences and further characterization warranted.
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Optical imaging with a high-resolution microendoscope to identify sinonasal pathology. Am J Otolaryngol 2018; 39:383-387. [PMID: 29622347 DOI: 10.1016/j.amjoto.2018.03.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 03/19/2018] [Indexed: 11/21/2022]
Abstract
OBJECTIVES High-resolution microendoscopy (HRME) is an optical imaging modality that allows real time imaging of epithelial tissue and structural changes within. We hypothesize that HRME, using proflavine, a contrast agent that preferentially stains cell nuclei and allows detection of cellular morphologic changes, can distinguish sinonasal pathology from uninvolved mucosa, potentially enabling real-time surgical margin differentiation. STUDY DESIGN Ex vivo imaging of histopathologically confirmed samples of sinonasal pathology and uninvolved, normal sinus epithelium. SETTING Single tertiary-level institution. SUBJECTS AND METHODS Five inverted papillomas, one oncocytic papilloma, two uninvolved sinus epithelia specimens, and three inflammatory polyps were imaged ex vivo with HRME after surface staining with proflavine. Following imaging, the specimens were submitted for hematoxylin and eosin staining to allow histopathological correlation. RESULTS Results show that sinonasal pathology and normal sinus epithelia have distinct HRME imaging characteristics. Schneiderian papilloma specimens show increased nuclear-to-cytoplasmic ratio, nuclear crowding, and small internuclear separation, whereas normal sinus epithelia specimens show small, bright nuclei with dark cytoplasm and relatively large internuclear separation. Inflammatory polyps, however, have varying imaging characteristics, that resemble both Schneiderian papilloma and normal sinus epithelia. CONCLUSIONS This study demonstrates the feasibility of HRME imaging to discriminate sinonasal pathology from normal sinus epithelia. While the system performed well in the absence of inflammation, discrimination of inflamed tissue was inconsistent, creating a significant limitation for this application. Novel imaging systems such as HRME with alternative contrast agents may assist with real-time surgical margin differentiation, enabling complete surgical resection of inverted papilloma and reducing recurrence rates.
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Tian P, Chen C, Jin J, Hong H, Lu JQ, Hu XH. Quantitative characterization of turbidity by radiative transfer based reflectance imaging. BIOMEDICAL OPTICS EXPRESS 2018; 9:2081-2094. [PMID: 29760971 PMCID: PMC5946772 DOI: 10.1364/boe.9.002081] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 03/20/2018] [Accepted: 03/26/2018] [Indexed: 06/08/2023]
Abstract
A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of μ a , the scattering coefficient of μs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging.
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Affiliation(s)
- Peng Tian
- Institute for Advanced Optics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
- Department of Physics, East Carolina University, Greenville, NC 27858, USA
- School of Physics & Electronics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
| | - Cheng Chen
- Department of Physics, East Carolina University, Greenville, NC 27858, USA
| | - Jiahong Jin
- Institute for Advanced Optics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
- School of Physics & Electronics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
| | - Heng Hong
- Department of Pathology and Laboratory Science, Brody School of Medicine, East Carolina University, Greenville, NC 27858, USA
| | - Jun Q. Lu
- Institute for Advanced Optics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
- Department of Physics, East Carolina University, Greenville, NC 27858, USA
| | - Xin-Hua Hu
- Institute for Advanced Optics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China
- Department of Physics, East Carolina University, Greenville, NC 27858, USA
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31
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Lu G, Wang D, Qin X, Muller S, Wang X, Chen AY, Chen ZG, Fei B. Detection and delineation of squamous neoplasia with hyperspectral imaging in a mouse model of tongue carcinogenesis. JOURNAL OF BIOPHOTONICS 2018; 11:10.1002/jbio.201700078. [PMID: 28921845 PMCID: PMC5839941 DOI: 10.1002/jbio.201700078] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2017] [Revised: 06/16/2017] [Accepted: 09/14/2017] [Indexed: 05/08/2023]
Abstract
Hyperspectral imaging (HSI) holds the potential for the noninvasive detection of cancers. Oral cancers are often diagnosed at a late stage when treatment is less effective and the mortality and morbidity rates are high. Early detection of oral cancer is, therefore, crucial in order to improve the clinical outcomes. To investigate the potential of HSI as a noninvasive diagnostic tool, an animal study was designed to acquire hyperspectral images of in vivo and ex vivo mouse tongues from a chemically induced tongue carcinogenesis model. A variety of machine-learning algorithms, including discriminant analysis, ensemble learning, and support vector machines, were evaluated for tongue neoplasia detection using HSI and were validated by the reconstructed pathological gold-standard maps. The diagnostic performance of HSI, autofluorescence imaging, and fluorescence imaging were compared in this study. Color-coded prediction maps were generated to display the predicted location and distribution of premalignant and malignant lesions. This study suggests that hyperspectral imaging combined with machine-learning techniques can provide a noninvasive tool for the quantitative detection and delineation of squamous neoplasia.
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Affiliation(s)
- Guolan Lu
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia
Institute of Technology and Emory University, Atlanta, GA, USA
| | - Dongsheng Wang
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA, USA
| | - Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University,
Atlanta, GA, USA
| | - Susan Muller
- Department of Otolaryngology, Emory University School of Medicine,
Atlanta, GA, USA
| | - Xu Wang
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA, USA
| | - Amy Y. Chen
- Department of Otolaryngology, Emory University School of Medicine,
Atlanta, GA, USA
| | - Zhuo Georgia Chen
- Department of Hematology and Medical Oncology, Emory University,
Atlanta, GA, USA
| | - Baowei Fei
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia
Institute of Technology and Emory University, Atlanta, GA, USA
- Department of Radiology and Imaging Sciences, Emory University,
Atlanta, GA, USA
- Department of Mathematics & Computer Science, Emory
University, Atlanta, GA, USA
- Winship Cancer Institute of Emory University, Atlanta, GA, USA
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Khouj Y, Dawson J, Coad J, Vona-Davis L. Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma In Situ. Front Oncol 2018; 8:17. [PMID: 29468139 PMCID: PMC5808285 DOI: 10.3389/fonc.2018.00017] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 01/17/2018] [Indexed: 11/13/2022] Open
Abstract
Hyperspectral imaging (HSI) is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues. Tissue samples mounted on slides were identified from 10 different patients. Samples from each patient included both normal and ductal carcinoma tissue, both stained with hematoxylin and eosin stain and unstained. Slides were imaged using a snapshot HSI system, and the spectral reflectance differences were evaluated. Analysis of the spectral reflectance values indicated that wavelengths near 550 nm showed the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. The K-means method was applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with true negative rate of 95.8%, and false positive rate of 4.2%. These results were verified by ground-truth marking of the tissue samples by a pathologist. In the hyperspectral image analysis, the image processing algorithm, K-means, shows the greatest potential for building a semi-automated system that could identify and sort between normal and ductal carcinoma in situ tissues.
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Affiliation(s)
- Yasser Khouj
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, United States
| | - Jeremy Dawson
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, United States
| | - James Coad
- Department of Pathology, West Virginia University, Morgantown, WV, United States.,West Virginia University Cancer Institute, Morgantown, WV, United States
| | - Linda Vona-Davis
- West Virginia University Cancer Institute, Morgantown, WV, United States.,Department of Surgery, West Virginia University, Morgantown, WV, United States
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Angelino K, Shah P, Edlund DA, Mohit M, Yauney G. Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque. BMC Oral Health 2017; 17:162. [PMID: 29284461 PMCID: PMC5745686 DOI: 10.1186/s12903-017-0472-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 12/20/2017] [Indexed: 01/02/2023] Open
Abstract
Background Significant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases. Methods A handheld device equipped with 405 nm light-emitting diodes was constructed to examine the prevalence of red fluorescence signatures associated with dental plaque. This device was used for in vivo imaging of all four incisors and all four canines of twenty-eight consenting human subjects. The same areas were further imaged under white light illumination with a commercial image-processing based plaque-imaging device, and evaluated by a hygienist and dentist. A custom computer vision algorithm using pixel information was developed to calculate plaque coverage ratios ranging from 0 (no plaque) to 1 (complete plaque coverage) for images captured by both devices. Results The algorithm calculated red fluorescence-based plaque coverage ratios ranging from 0.011 to 0.211 for the subjects imaged. Clinical assessment and statistical analyses of associated plaque ratios of the 405 nm device images indicated high sensitivity and specificity in detecting dental plaque by the experimental device compared to the commercial reference device. Conclusions The low-cost and open source 405 nm device and the associated computer vision algorithm successfully captured red fluorescence signatures associated with dental plaque and demonstrated comparable performance to a commercially available device. Therefore, a proof of concept validation was provided for the construction and application of a sensitive cost-effective plaque-detecting device. A miniaturized mobile adaptable version of the device was also provided, together with and a step-by-step guide for device assembly and webhost the associated software, to facilitate open-source access to a cost-effective at-home, in-clinic oral care technology. Trial registration ClinicalTrials.gov NCT03379337, December 19 2017. Retrospectively registered. Electronic supplementary material The online version of this article (doi: 10.1186/s12903-017-0472-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Keith Angelino
- Department of Media Arts and Sciences, Massachusetts Institute of Technology, 75 Amherst Street, E14, Cambridge, MA, 02139, USA
| | - Pratik Shah
- Department of Media Arts and Sciences, Massachusetts Institute of Technology, 75 Amherst Street, E14, Cambridge, MA, 02139, USA.
| | - David A Edlund
- Hampden Dental Care, 7425 West Hampden Avenue, Lakewood, CO, 80227, USA
| | - Mrinal Mohit
- Department of Media Arts and Sciences, Massachusetts Institute of Technology, 75 Amherst Street, E14, Cambridge, MA, 02139, USA
| | - Gregory Yauney
- Department of Media Arts and Sciences, Massachusetts Institute of Technology, 75 Amherst Street, E14, Cambridge, MA, 02139, USA
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Singh S, Fält P, Barman I, Koistinen A, Dasari RR, Kullaa A. Objective identification of dental abnormalities with multispectral fluorescence imaging. JOURNAL OF BIOPHOTONICS 2017; 10:1279-1286. [PMID: 27943658 PMCID: PMC5468489 DOI: 10.1002/jbio.201600218] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Revised: 10/14/2016] [Accepted: 11/18/2016] [Indexed: 06/06/2023]
Abstract
Sensitive methods that can enable early detection of dental diseases (caries and calculus) are desirable in clinical practice. Optical spectroscopic approaches have emerged as promising alternatives owing to their wealth of molecular information and lack of sample preparation requirements. In the present study, using multispectral fluorescence imaging, we have demonstrated that dental caries and calculus can be objectively identified on extracted tooth. Spectral differences among control, carious and calculus conditions were attributed to the porphyrin pigment content, which is a byproduct of bacterial metabolism. Spectral maps generated using different porphyrin bands offer important clues to the spread of bacterial infection. Statistically significant differences utilizing fluorescence intensity ratios were observed among three groups. In contrast to laser induced fluorescence, these methods can provide information about exact spread of the infection and may aid in long term dental monitoring. Successful adoption of this approach for routine clinical usage can assist dentists in implementing timely remedial measures.
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Affiliation(s)
- S.P. Singh
- Institute of Dentistry, Faculty of Health Sciences, Kuopio
- SIB Labs, University of Eastern Finland, Kuopio
- Laser Biomedical Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - P. Fält
- SIB Labs, University of Eastern Finland, Kuopio
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | | | - Ramachandra Rao Dasari
- Laser Biomedical Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - A.M. Kullaa
- Institute of Dentistry, Faculty of Health Sciences, Kuopio
- Dental Education Clinic, Kuopio, University Hospital, Kuopio, Finland
- Research Unit of Oral Health Sciences, Faculty of Medicine, University of Oulu and Medical Research Center, Oulu University Hospital, Oulu, Finland
- Department of Oral and Maxillofacial Surgey, Institute of Dentistry, University of Turku, Turku, Finland
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Quang T, Tran EQ, Schwarz RA, Williams MD, Vigneswaran N, Gillenwater AM, Richards-Kortum R. Prospective Evaluation of Multimodal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo. Cancer Prev Res (Phila) 2017; 10:563-570. [PMID: 28765195 DOI: 10.1158/1940-6207.capr-17-0054] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2017] [Revised: 06/07/2017] [Accepted: 07/26/2017] [Indexed: 12/16/2022]
Abstract
The 5-year survival rate for patients with oral cancer remains low, in part because diagnosis often occurs at a late stage. Early and accurate identification of oral high-grade dysplasia and cancer can help improve patient outcomes. Multimodal optical imaging is an adjunctive diagnostic technique in which autofluorescence imaging is used to identify high-risk regions within the oral cavity, followed by high-resolution microendoscopy to confirm or rule out the presence of neoplasia. Multimodal optical images were obtained from 206 sites in 100 patients. Histologic diagnosis, either from a punch biopsy or an excised surgical specimen, was used as the gold standard for all sites. Histopathologic diagnoses of moderate dysplasia or worse were considered neoplastic. Images from 92 sites in the first 30 patients were used as a training set to develop automated image analysis methods for identification of neoplasia. Diagnostic performance was evaluated prospectively using images from 114 sites in the remaining 70 patients as a test set. In the training set, multimodal optical imaging with automated image analysis correctly classified 95% of nonneoplastic sites and 94% of neoplastic sites. Among the 56 sites in the test set that were biopsied, multimodal optical imaging correctly classified 100% of nonneoplastic sites and 85% of neoplastic sites. Among the 58 sites in the test set that corresponded to a surgical specimen, multimodal imaging correctly classified 100% of nonneoplastic sites and 61% of neoplastic sites. These findings support the potential of multimodal optical imaging to aid in the early detection of oral cancer. Cancer Prev Res; 10(10); 563-70. ©2017 AACR.
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Affiliation(s)
- Timothy Quang
- Department of Bioengineering, Rice University, Houston, Texas
| | - Emily Q Tran
- Department of Bioengineering, Rice University, Houston, Texas
| | | | - Michelle D Williams
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Nadarajah Vigneswaran
- Department of Diagnostic and Biomedical Sciences, University of Texas School of Dentistry, Houston, Texas
| | - Ann M Gillenwater
- Department of Head and Neck Surgery, University of Texas MD Anderson Cancer Center, Houston, Texas
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Yan YJ, Huang TW, Cheng NL, Hsieh YF, Tsai MH, Chiou JC, Duann JR, Lin YJ, Yang CS, Ou-Yang M. Portable LED-induced autofluorescence spectroscopy for oral cancer diagnosis. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:45007. [PMID: 28421226 DOI: 10.1117/1.jbo.22.4.045007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 03/07/2017] [Indexed: 06/07/2023]
Abstract
Oral cancer is a serious and growing problem in many developing and developed countries. To improve the cancer screening procedure, we developed a portable light-emitting-diode (LED)-induced autofluorescence (LIAF) imager that contains two wavelength LED excitation light sources and multiple filters to capture ex vivo oral tissue autofluorescence images. Compared with conventional means of oral cancer diagnosis, the LIAF imager is a handier, faster, and more highly reliable solution. The compact design with a tiny probe allows clinicians to easily observe autofluorescence images of hidden areas located in concave deep oral cavities. The ex vivo trials conducted in Taiwan present the design and prototype of the portable LIAF imager used for analyzing 31 patients with 221 measurement points. Using the normalized factor of normal tissues under the excitation source with 365 nm of the central wavelength and without the bandpass filter, the results revealed that the sensitivity was larger than 84%, the specificity was not smaller than over 76%, the accuracy was about 80%, and the area under curve of the receiver operating characteristic (ROC) was achieved at about 87%, respectively. The fact shows the LIAF spectroscopy has the possibilities of ex vivo diagnosis and noninvasive examinations for oral cancer.
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Affiliation(s)
- Yung-Jhe Yan
- National Chiao-Tung University, Institute of Electrical Control Engineering, Hsinchu City, Taiwan
| | - Ting-Wei Huang
- National Chiao-Tung University, Department of Electrical and Computer Engineering, Hsinchu City, Taiwan
| | - Nai-Lun Cheng
- National Chiao-Tung University, Institute of Biomedical Engineering, Hsinchu City, Taiwan
| | - Yao-Fang Hsieh
- National Central University, Department of Optics and Photonics, Jhongli City, Taoyuan County, Taiwan
| | - Ming-Hsui Tsai
- China Medical University, School of Medicine, Taichung City, Taiwan
| | - Jin-Chern Chiou
- National Chiao-Tung University, Institute of Electrical Control Engineering, Hsinchu City, TaiwanbNational Chiao-Tung University, Department of Electrical and Computer Engineering, Hsinchu City, TaiwaneChina Medical University, School of Medicine, Taichung City, Taiwan
| | - Jeng-Ren Duann
- China Medical University, School of Medicine, Taichung City, Taiwan
| | - Yung-Jiun Lin
- China Medical University, School of Medicine, Taichung City, Taiwan
| | - Chin-Siang Yang
- National Chiao-Tung University, Department of Electrical and Computer Engineering, Hsinchu City, Taiwan
| | - Mang Ou-Yang
- National Chiao-Tung University, Institute of Electrical Control Engineering, Hsinchu City, TaiwanbNational Chiao-Tung University, Department of Electrical and Computer Engineering, Hsinchu City, Taiwan
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HYPERSPECTRAL AUTOFLUORESCENCE IMAGING OF DRUSEN AND RETINAL PIGMENT EPITHELIUM IN DONOR EYES WITH AGE-RELATED MACULAR DEGENERATION. Retina 2017; 36 Suppl 1:S127-S136. [PMID: 28005671 DOI: 10.1097/iae.0000000000001325] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
PURPOSE To elucidate the molecular pathogenesis of age-related macular degeneration (AMD) and interpretation of fundus autofluorescence imaging, the authors identified spectral autofluorescence characteristics of drusen and retinal pigment epithelium (RPE) in donor eyes with AMD. METHODS Macular RPE/Bruch membrane flat mounts were prepared from 5 donor eyes with AMD. In 12 locations (1-3 per eye), hyperspectral autofluorescence images in 10-nm-wavelength steps were acquired at 2 excitation wavelengths (λex 436, 480 nm). A nonnegative tensor factorization algorithm was used to recover 5 abundant emission spectra and their corresponding spatial localizations. RESULTS At λex 436 nm, the authors consistently localized a novel spectrum (SDr) with a peak emission near 510 nm in drusen and sub-RPE deposits. Abundant emission spectra seen previously (S0 in Bruch membrane and S1, S2, and S3 in RPE lipofuscin/melanolipofuscin, respectively) also appeared in AMD eyes, with the same shapes and peak wavelengths as in normal tissue. Lipofuscin/melanolipofuscin spectra localizations in AMD eyes varied widely in their overlap with drusen, ranging from none to complete. CONCLUSION An emission spectrum peaking at ∼510 nm (λex 436 nm) appears to be sensitive and specific for drusen and sub-RPE deposits. One or more abundant spectra from RPE organelles exhibit characteristic relationships with drusen.
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Ma L, Lu G, Wang D, Wang X, Chen ZG, Muller S, Chen A, Fei B. Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2017; 10137. [PMID: 30220770 DOI: 10.1117/12.2255562] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.
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Affiliation(s)
- Ling Ma
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.,School of Computer Science, Beijing Institute of Technology, Beijing
| | - Guolan Lu
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
| | - Dongsheng Wang
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Xu Wang
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Zhuo Georgia Chen
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Susan Muller
- Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA
| | - Amy Chen
- Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA
| | - Baowei Fei
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.,The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.,Department of Mathematics & Computer Science, Emory University, Atlanta, GA.,Winship Cancer Institute of Emory University, Atlanta, GA
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Shadfan A, Darwiche H, Blanco J, Gillenwater A, Richards-Kortum R, Tkaczyk TS. Development of a multimodal foveated endomicroscope for the detection of oral cancer. BIOMEDICAL OPTICS EXPRESS 2017; 8:1525-1535. [PMID: 28663847 PMCID: PMC5480562 DOI: 10.1364/boe.8.001525] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Revised: 02/06/2017] [Accepted: 02/06/2017] [Indexed: 05/11/2023]
Abstract
A multimodal endomicroscope was developed for cancer detection that combines hyperspectral and confocal imaging through a single foveated objective and a vibrating optical fiber bundle. Standard clinical examination has a limited ability to identify early stage oral cancer. Optical detection methods are typically restricted by either achievable resolution or a small field-of-view. By combining high resolution and widefield spectral imaging into a single probe, a device was developed that provides spectral and spatial information over a 5 mm field to locate suspicious lesions that can then be inspected in high resolution mode. The device was evaluated on ex vivo biopsies of human oral tumors.
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Affiliation(s)
- Adam Shadfan
- Rice University, Bioengineering Department, 6100 Main Street, Houston, TX 77005, USA
| | - Hawraa Darwiche
- Department of Head and Neck Surgery, University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
| | - Jesus Blanco
- Department of Head and Neck Surgery, University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
| | - Ann Gillenwater
- Department of Head and Neck Surgery, University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
| | | | - Tomasz S. Tkaczyk
- Rice University, Bioengineering Department, 6100 Main Street, Houston, TX 77005, USA
- Rice University, Electrical and Computer Engineering, 6100 Main Street, Houston, TX 77005, USA
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40
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Pian Q, Yao R, Sinsuebphon N, Intes X. Compressive hyperspectral time-resolved wide-field fluorescence lifetime imaging. NATURE PHOTONICS 2017; 11:411-414. [PMID: 29242714 PMCID: PMC5726531 DOI: 10.1038/nphoton.2017.82] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 05/03/2017] [Indexed: 05/18/2023]
Abstract
Spectrally resolved fluorescence lifetime imaging1-3 and spatial multiplexing1,4,5 have offered information content and collection-efficiency boosts in microscopy, but efficient implementations for macroscopic applications are still lacking. An imaging platform based on time-resolved structured light and hyperspectral single-pixel detection has been developed to perform quantitative macroscopic fluorescence lifetime imaging (MFLI) over a large field of view (FOV) and multiple spectral bands simultaneously. The system makes use of three digital micromirror device (DMD)-based spatial light modulators (SLMs) to generate spatial optical bases and reconstruct N by N images over 16 spectral channels with a time-resolved capability (~40 ps temporal resolution) using fewer than N2 optical measurements. We demonstrate the potential of this new imaging platform by quantitatively imaging near-infrared (NIR) Förster resonance energy transfer (FRET) both in vitro and in vivo. The technique is well suited for quantitative hyperspectral lifetime imaging with a high sensitivity and paves the way for many important biomedical applications.
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Affiliation(s)
| | | | | | - Xavier Intes
- Correspondence and requests for materials should be addressed to X.I.
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41
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Cosci A, Takahama A, Correr WR, Azevedo RS, Fontes KBFDC, Kurachi C. Automated algorithm for actinic cheilitis diagnosis by wide-field fluorescence imaging. J Med Imaging (Bellingham) 2016; 3:044004. [PMID: 27981067 DOI: 10.1117/1.jmi.3.4.044004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Accepted: 11/01/2016] [Indexed: 01/12/2023] Open
Abstract
Actinic cheilitis (AC) is a disease caused by prolonged and cumulative sun exposure that mostly affects the lower lip, which can progress to a lip squamous cell carcinoma. Routine diagnosis relies on clinician experience and training. We investigated the diagnostic efficacy of wide-field fluorescence imaging coupled to an automated algorithm for AC recognition. Fluorescence images were acquired from 57 patients with confirmed AC and 46 normal volunteers. Three different algorithms were employed: two based on the emission characteristics of local heterogeneity, entropy and intensity range, and one based on the number of objects after K-mean clustering. A classification model was obtained using a fivefold cross correlation algorithm. Sensitivity and specificity rates were 86% and 89.1%, respectively.
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Affiliation(s)
- Alessandro Cosci
- Universidade de São Paulo, Instituto de Fisica de São Carlos, Avenida Trabalhador São-carlense, 400-Pq. Arnold Schimidt, São Carlos CEP 13566-590, Brazil; Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Piazza del Viminale 1, Rome 00184, Italy; Consiglio Nazionale delle Ricerche, Istituto di Fisica Applicata "Nello Carrara," Via Madonna del Piano 10, Sesto Fiorentino 50019, Italy
| | - Ademar Takahama
- Universidade Federal Fluminense , Instituto de Saúde de Nova Friburgo, Estomatologia e Patologia Oral, Faculdade de Odontologia de Nova Friburgo, Rua Doutor Silvio Henrique Braune 22, Centro, Nova Friburgo, Rio de Janeiro CEP 28625-650, Brazil
| | - Wagner Rafael Correr
- Universidade de São Paulo , Instituto de Fisica de São Carlos, Avenida Trabalhador São-carlense, 400-Pq. Arnold Schimidt, São Carlos CEP 13566-590, Brazil
| | - Rebeca Souza Azevedo
- Universidade Federal Fluminense , Instituto de Saúde de Nova Friburgo, Estomatologia e Patologia Oral, Faculdade de Odontologia de Nova Friburgo, Rua Doutor Silvio Henrique Braune 22, Centro, Nova Friburgo, Rio de Janeiro CEP 28625-650, Brazil
| | - Karla Bianca Fernandes da Costa Fontes
- Universidade Federal Fluminense , Instituto de Saúde de Nova Friburgo, Estomatologia e Patologia Oral, Faculdade de Odontologia de Nova Friburgo, Rua Doutor Silvio Henrique Braune 22, Centro, Nova Friburgo, Rio de Janeiro CEP 28625-650, Brazil
| | - Cristina Kurachi
- Universidade de São Paulo , Instituto de Fisica de São Carlos, Avenida Trabalhador São-carlense, 400-Pq. Arnold Schimidt, São Carlos CEP 13566-590, Brazil
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Landau MJ, Gould DJ, Patel KM. Advances in fluorescent-image guided surgery. ANNALS OF TRANSLATIONAL MEDICINE 2016; 4:392. [PMID: 27867944 DOI: 10.21037/atm.2016.10.70] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Fluorescence imaging is increasingly gaining intraoperative applications. Here, we highlight a few recent advances in the surgical use of fluorescent probes.
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Affiliation(s)
- Mark J Landau
- Division of Plastic and Reconstructive Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
| | - Daniel J Gould
- Division of Plastic and Reconstructive Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
| | - Ketan M Patel
- Division of Plastic and Reconstructive Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
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Garcia-Sucerquia J. Color digital lensless holographic microscopy: laser versus LED illumination. APPLIED OPTICS 2016; 55:6649-6655. [PMID: 27556985 DOI: 10.1364/ao.55.006649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
A comparison of the performance of color digital lensless holographic microscopy (CDLHM) as utilized for illumination of RGB lasers or a super-bright white-light LED with a set of spectral filters is presented. As the use of lasers in CDLHM conceals the possibility of having a compact, lightweight, portable, and low cost microscope, and additionally the limited available laser radiation wavelengths limit a real multispectral imaging microscope, here we present the use of super-bright white-light LED and spectral filters for illuminating the sample. The performance of RGB laser-CDLHM and LED-CDLHM is evaluated on imaging a section of the head of a Drosophila melanogaster fly. This comparison shows that there is trade-off between the spatial resolution of the microscope and the light sources utilized, which can be understood with regard to the coherence properties of the illuminating light. Despite the smaller spatial coherence features of LED-CDLHM in comparison with laser-CDLHM, the former shows promise as a portable RGB digital lensless holographic microscope that could be extended to other wavelengths by the use of different spectral filters.
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Bailey MJ, Sokolov K. Depth-resolved measurements with elliptically polarized reflectance spectroscopy. BIOMEDICAL OPTICS EXPRESS 2016; 7:2861-76. [PMID: 27446712 PMCID: PMC4948636 DOI: 10.1364/boe.7.002861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 06/09/2016] [Accepted: 06/15/2016] [Indexed: 05/11/2023]
Abstract
The ability of elliptical polarized reflectance spectroscopy (EPRS) to detect spectroscopic alterations in tissue mimicking phantoms and in biological tissue in situ is demonstrated. It is shown that there is a linear relationship between light penetration depth and ellipticity. This dependence is used to demonstrate the feasibility of a depth-resolved spectroscopic imaging using EPRS. The advantages and drawbacks of EPRS in evaluation of biological tissue are analyzed and discussed.
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Affiliation(s)
- Maria J. Bailey
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX 78712, USA
| | - Konstantin Sokolov
- Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX 78712, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
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Lv Y, Zhang J, Zhang D, Cai W, Chen N, Luo J. In vivo simultaneous multispectral fluorescence imaging with spectral multiplexed volume holographic imaging system. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:60502. [PMID: 27258060 DOI: 10.1117/1.jbo.21.6.060502] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Accepted: 05/09/2016] [Indexed: 05/13/2023]
Abstract
A simultaneous multispectral fluorescence imaging system incorporating multiplexed volume holographic grating (VHG) is developed to acquire multispectral images of an object in one shot. With the multiplexed VHG, the imaging system can provide the distribution and spectral characteristics of multiple fluorophores in the scene. The implementation and performance of the simultaneous multispectral imaging system are presented. Further, the system’s capability in simultaneously obtaining multispectral fluorescence measurements is demonstrated with in vivo experiments on a mouse. The demonstrated imaging system has the potential to obtain multispectral images fluorescence simultaneously.
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Affiliation(s)
- Yanlu Lv
- Tsinghua University, Department of Biomedical Engineering, Haidian District, Beijing 100084, China
| | - Jiulou Zhang
- Tsinghua University, Department of Biomedical Engineering, Haidian District, Beijing 100084, China
| | - Dong Zhang
- Tsinghua University, Department of Biomedical Engineering, Haidian District, Beijing 100084, China
| | - Wenjuan Cai
- Tsinghua University, Department of Biomedical Engineering, Haidian District, Beijing 100084, China
| | - Nanguang Chen
- National University of Singapore, Department of Biomedical Engineering, Singapore 117576, Singapore
| | - Jianwen Luo
- Tsinghua University, Department of Biomedical Engineering, Haidian District, Beijing 100084, ChinacTsinghua University, Center for Biomedical Imaging Research, Haidian District, Beijing 100084, China
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Lu G, Qin X, Wang D, Muller S, Zhang H, Chen A, Chen ZG, Fei B. Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2016; 9788. [PMID: 27656034 DOI: 10.1117/12.2216553] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection.
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Affiliation(s)
- Guolan Lu
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
| | - Xulei Qin
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Dongsheng Wang
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Susan Muller
- Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA
| | - Hongzheng Zhang
- Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA
| | - Amy Chen
- Department of Otolaryngology, Emory University School of Medicine, Atlanta, GA
| | - Zhuo Georgia Chen
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA
| | - Baowei Fei
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Mathematics & Computer Science, Emory University, Atlanta, GA; Winship Cancer Institute of Emory University, Atlanta, GA
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47
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Pike R, Lu G, Wang D, Chen ZG, Fei B. A Minimum Spanning Forest-Based Method for Noninvasive Cancer Detection With Hyperspectral Imaging. IEEE Trans Biomed Eng 2016; 63:653-63. [PMID: 26285052 PMCID: PMC4791052 DOI: 10.1109/tbme.2015.2468578] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
GOAL The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. METHODS An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. CONCLUSION The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. SIGNIFICANCE Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection.
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48
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Cha J, Shademan A, Le HND, Decker R, Kim PCW, Kang JU, Krieger A. Multispectral tissue characterization for intestinal anastomosis optimization. JOURNAL OF BIOMEDICAL OPTICS 2015; 20:106001. [PMID: 26440616 PMCID: PMC5996867 DOI: 10.1117/1.jbo.20.10.106001] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 09/11/2015] [Indexed: 05/27/2023]
Abstract
Intestinal anastomosis is a surgical procedure that restores bowel continuity after surgical resection to treat intestinal malignancy, inflammation, or obstruction. Despite the routine nature of intestinal anastomosis procedures, the rate of complications is high. Standard visual inspection cannot distinguish the tissue subsurface and small changes in spectral characteristics of the tissue, so existing tissue anastomosis techniques that rely on human vision to guide suturing could lead to problems such as bleeding and leakage from suturing sites. We present a proof-of-concept study using a portable multispectral imaging (MSI) platform for tissue characterization and preoperative surgical planning in intestinal anastomosis. The platform is composed of a fiber ring light-guided MSI system coupled with polarizers and image analysis software. The system is tested on ex vivo porcine intestine tissue, and we demonstrate the feasibility of identifying optimal regions for suture placement.
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Affiliation(s)
- Jaepyeong Cha
- Johns Hopkins University, Department of Electrical and Computer Engineering, 3400 North Charles Street, Baltimore, Maryland 21218, United States
| | - Azad Shademan
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, 111 Michigan Avenue, Washington, DC 20010, United States
| | - Hanh N. D. Le
- Johns Hopkins University, Department of Electrical and Computer Engineering, 3400 North Charles Street, Baltimore, Maryland 21218, United States
| | - Ryan Decker
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, 111 Michigan Avenue, Washington, DC 20010, United States
| | - Peter C. W. Kim
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, 111 Michigan Avenue, Washington, DC 20010, United States
| | - Jin U. Kang
- Johns Hopkins University, Department of Electrical and Computer Engineering, 3400 North Charles Street, Baltimore, Maryland 21218, United States
| | - Axel Krieger
- Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, 111 Michigan Avenue, Washington, DC 20010, United States
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Sharma G. Diagnostic aids in detection of oral cancer: An update. World J Stomatol 2015; 4:115-120. [DOI: 10.5321/wjs.v4.i3.115] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Revised: 05/07/2015] [Accepted: 08/17/2015] [Indexed: 02/06/2023] Open
Abstract
Oral cancer is the sixth most common malignancy with almost 500000 new cases reported worldwide annually. The diagnosis of oral cancer at an early stage has a good prognosis as the survival rate is high (around 80%). However, the majority of oral cancer cases are diagnosed at a later stage with a considerably poor 5-year survival rate of 50% according to World Health Organization statistics. Thus, an effective management strategy for oral cancer will depend on its early identification and intervention which would pave the way for superior prognosis. Despite the obvious advantage of earlier diagnosis of oral cancer, no approach has yet proven to be a reliably successful in diagnosis of oral cancer at an early stage. Currently; the primary line of screening of oral cancer is performed by visual inspection, which is a subjective examination. Among the screening tests or diagnostic aids now available for oral cancer, few (toluidine blue, brush biopsy, salivary and serum bio-markers) have been utilised and studied for many years while others have recently become commercially available. The authors in the present article review all the modalities of screening aids used in oral cancer detection and provide an update on the latest screening tools used in oral cancer detection.
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Fawzy Y, Lam S, Zeng H. Rapid multispectral endoscopic imaging system for near real-time mapping of the mucosa blood supply in the lung. BIOMEDICAL OPTICS EXPRESS 2015; 6:2980-90. [PMID: 26309761 PMCID: PMC4541525 DOI: 10.1364/boe.6.002980] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 07/15/2015] [Accepted: 07/16/2015] [Indexed: 05/14/2023]
Abstract
We have developed a fast multispectral endoscopic imaging system that is capable of acquiring images in 18 optimized spectral bands spanning 400-760 nm by combining a customized light source with six triple-band filters and a standard color CCD camera. A method is developed to calibrate the spectral response of the CCD camera. Imaging speed of 15 spectral image cubes/second is achieved. A spectral analysis algorithm based on a linear matrix inversion approach is developed and implemented in a graphics processing unit (GPU) to map the mucosa blood supply in the lung in vivo. Clinical measurements on human lung patients are demonstrated.
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Affiliation(s)
- Yasser Fawzy
- Imaging Unit – Integrative Oncology Department, British Columbia Cancer Agency Research Centre, Vancouver, BC, V5Z 1L3, Canada
| | - Stephen Lam
- Imaging Unit – Integrative Oncology Department, British Columbia Cancer Agency Research Centre, Vancouver, BC, V5Z 1L3, Canada
- Respiratory Medicine Division – Department of Medicine, University of British Columbia, Vancouver, BC, V5Z 1M9, Canada
| | - Haishan Zeng
- Imaging Unit – Integrative Oncology Department, British Columbia Cancer Agency Research Centre, Vancouver, BC, V5Z 1L3, Canada
- Photomedicine Institute – Department of Dermatology and Skin Science, University of British Columbia, Vancouver, BC, V5Z 4E8, Canada
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