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Huang Z, Cao L. Quantitative phase imaging based on holography: trends and new perspectives. LIGHT, SCIENCE & APPLICATIONS 2024; 13:145. [PMID: 38937443 PMCID: PMC11211409 DOI: 10.1038/s41377-024-01453-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 04/07/2024] [Accepted: 04/10/2024] [Indexed: 06/29/2024]
Abstract
In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.
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Affiliation(s)
- Zhengzhong Huang
- Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Liangcai Cao
- Department of Precision Instrument, Tsinghua University, Beijing, 100084, China.
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2
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Liu Y, Uttam S. Perspective on quantitative phase imaging to improve precision cancer medicine. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S22705. [PMID: 38584967 PMCID: PMC10996848 DOI: 10.1117/1.jbo.29.s2.s22705] [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: 11/29/2023] [Revised: 03/03/2024] [Accepted: 03/15/2024] [Indexed: 04/09/2024]
Abstract
Significance Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states. Aim This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection. Approach We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging. Results QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research. Conclusions QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.
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Affiliation(s)
- Yang Liu
- University of Illinois Urbana-Champaign, Beckman Institute for Advanced Science and Technology, Cancer Center at Illinois, Department of Bioengineering, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
- University of Pittsburgh, Departments of Medicine and Bioengineering, Pittsburgh, Pennsylvania, United States
| | - Shikhar Uttam
- University of Pittsburgh, Department of Computational and Systems Biology, Pittsburgh, Pennsylvania, United States
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Szuniewicz J, Kurdziałek S, Kundu S, Zwolinski W, Chrapkiewicz R, Lahiri M, Lapkiewicz R. Noise-resistant phase imaging with intensity correlation. SCIENCE ADVANCES 2023; 9:eadh5396. [PMID: 37738351 PMCID: PMC10516487 DOI: 10.1126/sciadv.adh5396] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 08/21/2023] [Indexed: 09/24/2023]
Abstract
Interferometric methods form the basis of highly sensitive measurement techniques from astronomy to bioimaging. Interferometry typically requires high stability between the measured and reference beams. The presence of rapid phase fluctuations washes out interference fringes, making phase profile recovery impossible. This challenge can be addressed by shortening the measurement time. However, such an approach reduces photon-counting rates, precluding applications in low-intensity imaging. We introduce a phase imaging technique which is immune to time-dependent phase fluctuations. Our technique, relying on intensity correlation instead of direct intensity measurements, allows one to obtain high interference visibility for arbitrarily long acquisition times. We prove the optimality of our method using the Cramér-Rao bound in the extreme case when no more than two photons are detected within the time window of phase stability. Our technique will broaden prospects in phase measurements, including emerging applications such as in infrared and x-ray imaging and quantum and matter-wave interferometry.
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Affiliation(s)
- Jerzy Szuniewicz
- Institute of Experimental Physics, Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093 Warszawa, Poland
| | - Stanisław Kurdziałek
- Institute of Experimental Physics, Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093 Warszawa, Poland
| | - Sanjukta Kundu
- Institute of Experimental Physics, Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093 Warszawa, Poland
| | - Wojciech Zwolinski
- Institute of Experimental Physics, Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093 Warszawa, Poland
| | | | - Mayukh Lahiri
- Department of Physics, Oklahoma State University, Stillwater, OK 74078, USA
| | - Radek Lapkiewicz
- Institute of Experimental Physics, Faculty of Physics, University of Warsaw, ul. Pasteura 5, 02-093 Warszawa, Poland
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Gigli L, Braidotti N, Lima MADRBF, Ciubotaru CD, Cojoc D. Label-Free Analysis of Urine Samples with In-Flow Digital Holographic Microscopy. BIOSENSORS 2023; 13:789. [PMID: 37622874 PMCID: PMC10452265 DOI: 10.3390/bios13080789] [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: 06/15/2023] [Revised: 07/29/2023] [Accepted: 07/30/2023] [Indexed: 08/26/2023]
Abstract
Urinary tract infections are among the most frequent infectious diseases and require screening a great amount of urine samples from patients. However, a high percentage of samples result as negative after urine culture plate tests (CPTs), demanding a simple and fast preliminary technique to screen out the negative samples. We propose a digital holographic microscopy (DHM) method to inspect fresh urine samples flowing in a glass capillary for 3 min, recording holograms at 2 frames per second. After digital reconstruction, bacteria, white and red blood cells, epithelial cells and crystals were identified and counted, and the samples were classified as negative or positive according to clinical cutoff values. Taking the CPT as reference, we processed 180 urine samples and compared the results with those of urine flow cytometry (UFC). Using standard evaluation metrics for our screening test, we found a similar performance for DHM and UFC, indicating DHM as a suitable and fast screening technique retaining several advantages. As a benefit of DHM, the technique is label-free and does not require sample preparation. Moreover, the phase and amplitude images of the cells and other particles present in urine are digitally recorded and can serve for further investigation afterwards.
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Affiliation(s)
- Lucia Gigli
- Alifax s.r.l. Via Merano, 30, Nimis, 33045 Udine, Italy;
| | - Nicoletta Braidotti
- Consiglio Nazionale Delle Ricerche (CNR), Istituto Officina dei Materiali (IOM), Area Science Park-Basovizza, Strada Statale 14, Km 163,5, 34149 Trieste, Italy; (N.B.); (M.A.d.R.B.F.L.); (C.D.C.)
- Department of Physics, University of Trieste, Via A. Valerio 2, 34127 Trieste, Italy
| | - Maria Augusta do R. B. F. Lima
- Consiglio Nazionale Delle Ricerche (CNR), Istituto Officina dei Materiali (IOM), Area Science Park-Basovizza, Strada Statale 14, Km 163,5, 34149 Trieste, Italy; (N.B.); (M.A.d.R.B.F.L.); (C.D.C.)
- Department of Physics, University of Trieste, Via A. Valerio 2, 34127 Trieste, Italy
| | - Catalin Dacian Ciubotaru
- Consiglio Nazionale Delle Ricerche (CNR), Istituto Officina dei Materiali (IOM), Area Science Park-Basovizza, Strada Statale 14, Km 163,5, 34149 Trieste, Italy; (N.B.); (M.A.d.R.B.F.L.); (C.D.C.)
| | - Dan Cojoc
- Consiglio Nazionale Delle Ricerche (CNR), Istituto Officina dei Materiali (IOM), Area Science Park-Basovizza, Strada Statale 14, Km 163,5, 34149 Trieste, Italy; (N.B.); (M.A.d.R.B.F.L.); (C.D.C.)
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Park J, Shin SJ, Shin J, Lee AJ, Lee M, Lee MJ, Kim G, Heo JE, Suk lee K, Park Y. Quantification of structural heterogeneity in H&E stained clear cell renal cell carcinoma using refractive index tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:1071-1081. [PMID: 36950245 PMCID: PMC10026583 DOI: 10.1364/boe.484092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/16/2023] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
Clear cell renal cell carcinoma (ccRCC) is a common histopathological subtype of renal cancer and is notorious for its poor prognosis. Its accurate diagnosis by histopathology, which relies on manual microscopic inspection of stained slides, is challenging. Here, we present a correlative approach to utilize stained images and refractive index (RI) tomography and demonstrate quantitative assessments of the structural heterogeneities of ccRCC slides obtained from human patients. Machine-learning-assisted segmentation of nuclei and cytoplasm enabled the quantification at the subcellular level. Compared to benign regions, malignant regions exhibited a considerable increase in structural heterogeneities. The results demonstrate that RI tomography provides quantitative information in synergy with stained images on the structural heterogeneities in ccRCC.
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Affiliation(s)
- Juyeon Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Contributed equally
| | - Su-Jin Shin
- Department of Pathology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
- Contributed equally
| | - Jeongwon Shin
- Department of Biological Sciences, KAIST, Daejeon, 34141, Republic of Korea
- Contributed equally
| | - Ariel J. Lee
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Moosung Lee
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Mahn Jae Lee
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, 34141, Republic of Korea
| | - Geon Kim
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Ji Eun Heo
- Department of Urology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - Kwang Suk lee
- Department of Urology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - YongKeun Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Tomocube Inc., Daejeon 34051, Republic of Korea
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Pirone D, Lim J, Merola F, Miccio L, Mugnano M, Bianco V, Cimmino F, Visconte F, Montella A, Capasso M, Iolascon A, Memmolo P, Psaltis D, Ferraro P. Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry. NATURE PHOTONICS 2022; 16:851-859. [PMID: 36451849 PMCID: PMC7613862 DOI: 10.1038/s41566-022-01096-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.
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Affiliation(s)
- Daniele Pirone
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
- DIETI, Department of Electrical Engineering and Information Technologies, University of Naples “Federico II”, Via Claudio 21, 80125 Napoli, Italy
| | - Joowon Lim
- EPFL, Ecole Polytechnique Fédérale de Lausanne, Optics Laboratory, CH-1015 Lausanne, Switzerland
| | - Francesco Merola
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Lisa Miccio
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Martina Mugnano
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Vittorio Bianco
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Flora Cimmino
- CEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy
| | - Feliciano Visconte
- CEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy
| | - Annalaura Montella
- CEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy
- DMMBM, Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, Via Pansini 5, 80131 Napoli, Italy
| | - Mario Capasso
- CEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy
- DMMBM, Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, Via Pansini 5, 80131 Napoli, Italy
| | - Achille Iolascon
- CEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy
- DMMBM, Department of Molecular Medicine and Medical Biotechnology, University of Naples “Federico II”, Via Pansini 5, 80131 Napoli, Italy
| | - Pasquale Memmolo
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
| | - Demetri Psaltis
- EPFL, Ecole Polytechnique Fédérale de Lausanne, Optics Laboratory, CH-1015 Lausanne, Switzerland
| | - Pietro Ferraro
- CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy
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7
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Soltani S, Cheng B, Osunkoya AO, Robles FE. Deep UV Microscopy Identifies Prostatic Basal Cells: An Important Biomarker for Prostate Cancer Diagnostics. BME FRONTIERS 2022; 2022:9847962. [PMID: 37850167 PMCID: PMC10521648 DOI: 10.34133/2022/9847962] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/05/2022] [Indexed: 10/19/2023] Open
Abstract
Objective and Impact Statement. Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge. In this work, we developed an approach based on label-free, high-resolution molecular imaging with multispectral deep ultraviolet (UV) microscopy which identifies important prostate tissue components, including basal cells. This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer. Introduction. One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts. However, identifying basal cells using hematoxylin and eosin (H&E) stains, which is the standard of care, can be difficult in a subset of cases. In such situations, pathologists often resort to immunohistochemical (IHC) stains for a definitive diagnosis. However, IHC is expensive and time-consuming and requires more tissue sections which may not be available. In addition, IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis. Methods. We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells, luminal cells, and inflammatory cells. The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information. Results. Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity, free of any staining procedures, based on the presence or absence of basal cells. We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells, even in cases where IHC stains fail. Conclusion. Our simple, low-cost, and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.
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Affiliation(s)
- Soheil Soltani
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Brian Cheng
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Adeboye O. Osunkoya
- Departments of Pathology and Urology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
| | - Francisco E. Robles
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Departments of Pathology and Urology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
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Naseri Kouzehgarani G, Kandel ME, Sakakura M, Dupaty JS, Popescu G, Gillette MU. Circadian Volume Changes in Hippocampal Glia Studied by Label-Free Interferometric Imaging. Cells 2022; 11:2073. [PMID: 35805157 PMCID: PMC9265588 DOI: 10.3390/cells11132073] [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: 02/11/2022] [Revised: 06/02/2022] [Accepted: 06/17/2022] [Indexed: 12/10/2022] Open
Abstract
Complex brain functions, including learning and memory, arise in part from the modulatory role of astrocytes on neuronal circuits. Functionally, the dentate gyrus (DG) exhibits differences in the acquisition of long-term potentiation (LTP) between day and night. We hypothesize that the dynamic nature of astrocyte morphology plays an important role in the functional circuitry of hippocampal learning and memory, specifically in the DG. Standard microscopy techniques, such as differential interference contrast (DIC), present insufficient contrast for detecting changes in astrocyte structure and function and are unable to inform on the intrinsic structure of the sample in a quantitative manner. Recently, gradient light interference microscopy (GLIM) has been developed to upgrade a DIC microscope with quantitative capabilities such as single-cell dry mass and volume characterization. Here, we present a methodology for combining GLIM and electrophysiology to quantify the astrocyte morphological behavior over the day-night cycle. Colocalized measurements of GLIM and fluorescence allowed us to quantify the dry masses and volumes of hundreds of astrocytes. Our results indicate that, on average, there is a 25% cell volume reduction during the nocturnal cycle. Remarkably, this cell volume change takes place at constant dry mass, which suggests that the volume regulation occurs primarily through aqueous medium exchange with the environment.
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Affiliation(s)
- Ghazal Naseri Kouzehgarani
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA;
- Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; (M.E.K.); (M.S.); (G.P.)
| | - Mikhail E. Kandel
- Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; (M.E.K.); (M.S.); (G.P.)
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
| | - Masayoshi Sakakura
- Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; (M.E.K.); (M.S.); (G.P.)
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
| | - Joshua S. Dupaty
- Department of Biomedical Engineering, Mercer University, Macon, GA 31207, USA;
| | - Gabriel Popescu
- Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; (M.E.K.); (M.S.); (G.P.)
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
| | - Martha U. Gillette
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA;
- Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; (M.E.K.); (M.S.); (G.P.)
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
- Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
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Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data. Cells 2022; 11:cells11040716. [PMID: 35203365 PMCID: PMC8870406 DOI: 10.3390/cells11040716] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 02/11/2022] [Accepted: 02/14/2022] [Indexed: 11/24/2022] Open
Abstract
The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empirical assessment, a certain amount of subjectivity is unavoidable. Furthermore, the reliance on external contrast agents such as hematoxylin and eosin (H&E), albeit being well-established methods, makes it difficult to standardize color balance, staining strength, and imaging conditions, hindering automated computational analysis. In response to these challenges, we applied spatial light interference microscopy (SLIM), a label-free method that generates contrast based on intrinsic tissue refractive index signatures. Thus, we reduce human bias and make imaging data comparable across instruments and clinics. We applied a mask R-CNN deep learning algorithm to the SLIM data to achieve an automated colorectal cancer screening procedure, i.e., classifying normal vs. cancerous specimens. Our results, obtained on a tissue microarray consisting of specimens from 132 patients, resulted in 91% accuracy for gland detection, 99.71% accuracy in gland-level classification, and 97% accuracy in core-level classification. A SLIM tissue scanner accompanied by an application-specific deep learning algorithm may become a valuable clinical tool, enabling faster and more accurate assessments by pathologists.
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Trusiak M. Fringe analysis: single-shot or two-frames? Quantitative phase imaging answers. OPTICS EXPRESS 2021; 29:18192-18211. [PMID: 34154081 DOI: 10.1364/oe.423336] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/28/2021] [Indexed: 06/13/2023]
Abstract
Conditions of the digital recording of the fringe pattern determine the phase reconstruction procedure, which in turn directly shapes the final accuracy and throughput of the full-field (non-scanning) optical measurement technique and defines the system capabilities. In this way, the fringe pattern analysis plays a crucial role in the ubiquitous optical measurements and thus is under constant development focused on high temporal/spatial resolution. It is especially valuable in the quantitative phase imaging technology, which emerged in the high-contrast label-free biomedical microscopy. In this paper, I apply recently blossomed two-frame phase-shifting techniques to the QPI and merge them with advanced adaptive interferogram pre-filtering algorithms. Next, I comprehensively test such frameworks against classical and adaptive single-shot methods applied for phase reconstruction in dynamic QPI enabling highest phase time-space-bandwidth product. The presented study systematically tackles important question: what is the gain, if any, in QPI realized by recording two phase-shifted interferograms? Counterintuitively, the results show that single-shot demodulation exhibited higher phase reconstruction accuracy than two-frame phase-shifting methods in low and medium interferogram signal-to-noise ratio regimes. Thus, the single-shot approach is promoted due to not only high temporal resolution but also larger phase-information throughput. Additionally, in the majority of scenarios, the best option is to shift the paradigm and employ two-frame pre-filtering rather than two-frame phase retrieval. Experimental fringe analysis in QPI of LSEC/RWPE cell lines successfully corroborated all novel numerical findings. Hence, the presented numerical-experimental research advances the important field of fringe analysis solutions for optical full-field measurement methods with widespread bio-engineering applications.
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Costa PC, Guang Z, Ledwig P, Zhang Z, Neill S, Olson JJ, Robles FE. Towards in-vivo label-free detection of brain tumor margins with epi-illumination tomographic quantitative phase imaging. BIOMEDICAL OPTICS EXPRESS 2021; 12:1621-1634. [PMID: 33796377 PMCID: PMC7984798 DOI: 10.1364/boe.416731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 02/11/2021] [Accepted: 02/20/2021] [Indexed: 05/03/2023]
Abstract
Brain tumor surgery involves a delicate balance between maximizing the extent of tumor resection while minimizing damage to healthy brain tissue that is vital for neurological function. However, differentiating between tumor, particularly infiltrative disease, and healthy brain in-vivo remains a significant clinical challenge. Here we demonstrate that quantitative oblique back illumination microscopy (qOBM)-a novel label-free optical imaging technique that achieves tomographic quantitative phase imaging in thick scattering samples-clearly differentiates between healthy brain tissue and tumor, including infiltrative disease. Data from a bulk and infiltrative brain tumor animal model show that qOBM enables quantitative phase imaging of thick fresh brain tissues with remarkable cellular and subcellular detail that closely resembles histopathology using hematoxylin and eosin (H&E) stained fixed tissue sections, the gold standard for cancer detection. Quantitative biophysical features are also extracted from qOBM which yield robust surrogate biomarkers of disease that enable (1) automated tumor and margin detection with high sensitivity and specificity and (2) facile visualization of tumor regions. Finally, we develop a low-cost, flexible, fiber-based handheld qOBM device which brings this technology one step closer to in-vivo clinical use. This work has significant implications for guiding neurosurgery by paving the way for a tool that delivers real-time, label-free, in-vivo brain tumor margin detection.
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Affiliation(s)
- Paloma Casteleiro Costa
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Zhe Guang
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Patrick Ledwig
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Zhaobin Zhang
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Stewart Neill
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
- Department of Pathology & Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jeffrey J. Olson
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Francisco E. Robles
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
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12
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Das N, Alexandrov S, Gilligan KE, Dwyer RM, Saager RB, Ghosh N, Leahy M. Characterization of nanosensitive multifractality in submicron scale tissue morphology and its alteration in tumor progression. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-200223R. [PMID: 33432788 PMCID: PMC7797786 DOI: 10.1117/1.jbo.26.1.016003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 12/09/2020] [Indexed: 05/02/2023]
Abstract
SIGNIFICANCE Assessment of disease using optical coherence tomography is an actively investigated problem, owing to many unresolved challenges in early disease detection, diagnosis, and treatment response monitoring. The early manifestation of disease or precancer is typically associated with subtle alterations in the tissue dielectric and ultrastructural morphology. In addition, biological tissue is known to have ultrastructural multifractality. AIM Detection and characterization of nanosensitive structural morphology and multifractality in the tissue submicron structure. Quantification of nanosensitive multifractality and its alteration in progression of tumor. APPROACH We have developed a label free nanosensitive multifractal detrended fluctuation analysis(nsMFDFA) technique in combination with multifractal analysis and nanosensitive optical coherence tomography (nsOCT). The proposed method deployed for extraction and quantification of nanosensitive multifractal parameters in mammary fat pad (MFP). RESULTS Initially, the nsOCT approach is numerically validated on synthetic submicron axial structures. The nsOCT technique was applied to pathologically characterized MFP of murine breast tissue to extract depth-resolved nanosensitive submicron structures. Subsequently, two-dimensional MFDFA were deployed on submicron structural en face images to extract nanosensitive tissue multifractality. We found that nanosensitive multifractality increases in transition from healthy to tumor. CONCLUSIONS This method for extraction of nanosensitive tissue multifractality promises to provide a noninvasive diagnostic tool for early disease detection and monitoring treatment response. The novel ability to delineate the dominant submicron scale nanosensitive multifractal properties may also prove useful for characterizing a wide variety of complex scattering media of non-biological origin.
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Affiliation(s)
- Nandan Das
- National University of Ireland, Tissue Optics and Microcirculation Imaging, Galway, Ireland
- Linköping University, Biomedical Imaging and Spectroscopy, Clinical Instrument Translation, Linköping, Sweden
- Address all correspondence to Nandan Das,
| | - Sergey Alexandrov
- National University of Ireland, Tissue Optics and Microcirculation Imaging, Galway, Ireland
| | - Katie E. Gilligan
- National University of Ireland Galway, Discipline of Surgery, Lambe Institute for Translational Research, Galway, Ireland
| | - Róisín M. Dwyer
- National University of Ireland Galway, Discipline of Surgery, Lambe Institute for Translational Research, Galway, Ireland
| | - Rolf B. Saager
- Linköping University, Biomedical Imaging and Spectroscopy, Clinical Instrument Translation, Linköping, Sweden
| | - Nirmalya Ghosh
- Indian Institute of Science Education and Research Kolkata, Bio-Optics and Nano-Photonics, Kolkata, India
| | - Martin Leahy
- National University of Ireland, Tissue Optics and Microcirculation Imaging, Galway, Ireland
- Institute of Photonic Sciences, Barcelona, Spain
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13
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Cheng S, Fu S, Kim YM, Song W, Li Y, Xue Y, Yi J, Tian L. Single-cell cytometry via multiplexed fluorescence prediction by label-free reflectance microscopy. SCIENCE ADVANCES 2021; 7:eabe0431. [PMID: 33523908 PMCID: PMC7810377 DOI: 10.1126/sciadv.abe0431] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 11/19/2020] [Indexed: 05/08/2023]
Abstract
Traditional imaging cytometry uses fluorescence markers to identify specific structures but is limited in throughput by the labeling process. We develop a label-free technique that alleviates the physical staining and provides multiplexed readouts via a deep learning-augmented digital labeling method. We leverage the rich structural information and superior sensitivity in reflectance microscopy and show that digital labeling predicts accurate subcellular features after training on immunofluorescence images. We demonstrate up to three times improvement in the prediction accuracy over the state of the art. Beyond fluorescence prediction, we demonstrate that single cell-level structural phenotypes of cell cycles are correctly reproduced by the digital multiplexed images, including Golgi twins, Golgi haze during mitosis, and DNA synthesis. We further show that the multiplexed readouts enable accurate multiparametric single-cell profiling across a large cell population. Our method can markedly improve the throughput for imaging cytometry toward applications for phenotyping, pathology, and high-content screening.
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Affiliation(s)
- Shiyi Cheng
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Sipei Fu
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Yumi Mun Kim
- Department of Philosophy & Neuroscience, Boston University, Boston, MA 02215, USA
| | - Weiye Song
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA 02118, USA
| | - Yunzhe Li
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Yujia Xue
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Ji Yi
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
- Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA 02118, USA
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
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14
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Chen X, Kandel ME, Hu C, Lee YJ, Popescu G. Wolf phase tomography (WPT) of transparent structures using partially coherent illumination. LIGHT, SCIENCE & APPLICATIONS 2020; 9:142. [PMID: 32864117 DOI: 10.1117/12.2582903] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/30/2020] [Accepted: 08/03/2020] [Indexed: 05/27/2023]
Abstract
In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10-5.
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Affiliation(s)
- Xi Chen
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Mikhail E Kandel
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Chenfei Hu
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Young Jae Lee
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Gabriel Popescu
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
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15
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Chen X, Kandel ME, Hu C, Lee YJ, Popescu G. Wolf phase tomography (WPT) of transparent structures using partially coherent illumination. LIGHT, SCIENCE & APPLICATIONS 2020; 9:142. [PMID: 32864117 PMCID: PMC7438521 DOI: 10.1038/s41377-020-00379-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/30/2020] [Accepted: 08/03/2020] [Indexed: 05/03/2023]
Abstract
In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10-5.
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Affiliation(s)
- Xi Chen
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Mikhail E. Kandel
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Chenfei Hu
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Young Jae Lee
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Gabriel Popescu
- Quantitative Light Imaging Laboratory, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
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16
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Trusiak M, Cywińska M, Micó V, Picazo-Bueno JÁ, Zuo C, Zdańkowski P, Patorski K. Variational Hilbert Quantitative Phase Imaging. Sci Rep 2020; 10:13955. [PMID: 32811839 PMCID: PMC7435195 DOI: 10.1038/s41598-020-69717-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 07/15/2020] [Indexed: 11/09/2022] Open
Abstract
Utilizing the refractive index as the endogenous contrast agent to noninvasively study transparent cells is a working principle of emerging quantitative phase imaging (QPI). In this contribution, we propose the Variational Hilbert Quantitative Phase Imaging (VHQPI)-end-to-end purely computational add-on module able to improve performance of a QPI-unit without hardware modifications. The VHQPI, deploying unique merger of tailored variational image decomposition and enhanced Hilbert spiral transform, adaptively provides high quality map of sample-induced phase delay, accepting particularly wide range of input single-shot interferograms (from off-axis to quasi on-axis configurations). It especially promotes high space-bandwidth-product QPI configurations alleviating the spectral overlapping problem. The VHQPI is tailored to deal with cumbersome interference patterns related to detailed locally varying biological objects with possibly high dynamic range of phase and relatively low carrier. In post-processing, the slowly varying phase-term associated with the instrumental optical aberrations is eliminated upon variational analysis to further boost the phase-imaging capabilities. The VHQPI is thoroughly studied employing numerical simulations and successfully validated using static and dynamic cells phase-analysis. It compares favorably with other single-shot phase reconstruction techniques based on the Fourier and Hilbert-Huang transforms, both in terms of visual inspection and quantitative evaluation, potentially opening up new possibilities in QPI.
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Affiliation(s)
- Maciej Trusiak
- Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli St., 02-525, Warsaw, Poland.
| | - Maria Cywińska
- Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli St., 02-525, Warsaw, Poland.
| | - Vicente Micó
- Departamento de Óptica y de Optometría y Ciencias de la Visión, Facultad de Física, Universitat de Valencia, C/Doctor Moliner 50, 46100, Burjassot, Spain
| | - José Ángel Picazo-Bueno
- Departamento de Óptica y de Optometría y Ciencias de la Visión, Facultad de Física, Universitat de Valencia, C/Doctor Moliner 50, 46100, Burjassot, Spain
| | - Chao Zuo
- Jiangsu Key Laboratory of Spectral Imaging and Intelligence Sense, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, China
| | - Piotr Zdańkowski
- Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli St., 02-525, Warsaw, Poland
| | - Krzysztof Patorski
- Institute of Micromechanics and Photonics, Warsaw University of Technology, 8 Sw. A. Boboli St., 02-525, Warsaw, Poland
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17
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Zhang JK, He Y, Sobh N, Popescu G. Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM). APL PHOTONICS 2020; 5:040805. [PMID: 34368439 PMCID: PMC8341383 DOI: 10.1063/5.0004723] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 04/01/2020] [Indexed: 05/11/2023]
Abstract
Current pathology workflow involves staining of thin tissue slices, which otherwise would be transparent, followed by manual investigation under the microscope by a trained pathologist. While the hematoxylin and eosin (H&E) stain is well-established and a cost-effective method for visualizing histology slides, its color variability across preparations and subjectivity across clinicians remain unaddressed challenges. To mitigate these challenges, recently we have demonstrated that spatial light interference microscopy (SLIM) can provide a path to intrinsic, objective markers, that are independent of preparation and human bias. Additionally, the sensitivity of SLIM to collagen fibers yields information relevant to patient outcome, which is not available in H&E. Here, we show that deep learning and SLIM can form a powerful combination for screening applications: training on 1,660 SLIM images of colon glands and validating on 144 glands, we obtained a benign vs. cancer classification accuracy of 99%. We envision that the SLIM whole slide scanner presented here paired with artificial intelligence algorithms may prove valuable as a pre-screening method, economizing the clinician's time and effort.
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Affiliation(s)
- Jingfang Kelly Zhang
- Quantitative Light Imaging Laboratory, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
| | - Yuchen He
- Quantitative Light Imaging Laboratory, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
| | - Nahil Sobh
- Quantitative Light Imaging Laboratory, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
| | - Gabriel Popescu
- Quantitative Light Imaging Laboratory, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, IL 61801, USA
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18
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Kandel ME, Hu C, Naseri Kouzehgarani G, Min E, Sullivan KM, Kong H, Li JM, Robson DN, Gillette MU, Best-Popescu C, Popescu G. Epi-illumination gradient light interference microscopy for imaging opaque structures. Nat Commun 2019; 10:4691. [PMID: 31619681 PMCID: PMC6795907 DOI: 10.1038/s41467-019-12634-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 09/17/2019] [Indexed: 02/06/2023] Open
Abstract
Multiple scattering and absorption limit the depth at which biological tissues can be imaged with light. In thick unlabeled specimens, multiple scattering randomizes the phase of the field and absorption attenuates light that travels long optical paths. These obstacles limit the performance of transmission imaging. To mitigate these challenges, we developed an epi-illumination gradient light interference microscope (epi-GLIM) as a label-free phase imaging modality applicable to bulk or opaque samples. Epi-GLIM enables studying turbid structures that are hundreds of microns thick and otherwise opaque to transmitted light. We demonstrate this approach with a variety of man-made and biological samples that are incompatible with imaging in a transmission geometry: semiconductors wafers, specimens on opaque and birefringent substrates, cells in microplates, and bulk tissues. We demonstrate that the epi-GLIM data can be used to solve the inverse scattering problem and reconstruct the tomography of single cells and model organisms.
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Affiliation(s)
- Mikhail E Kandel
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Chenfei Hu
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ghazal Naseri Kouzehgarani
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Eunjung Min
- Rowland Institute at Harvard University, Cambridge, Cambridge, MA, USA
| | | | - Hyunjoon Kong
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Car R. Woese Institute for Genomic Biology, University of Illinois at Urbana-, Champaign, IL, USA
| | - Jennifer M Li
- Rowland Institute at Harvard University, Cambridge, Cambridge, MA, USA
| | - Drew N Robson
- Rowland Institute at Harvard University, Cambridge, Cambridge, MA, USA
| | - Martha U Gillette
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Catherine Best-Popescu
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Gabriel Popescu
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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19
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Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM). Sci Rep 2019; 9:14679. [PMID: 31604963 PMCID: PMC6789107 DOI: 10.1038/s41598-019-50143-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 08/31/2019] [Indexed: 01/22/2023] Open
Abstract
Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology.
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20
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Nawn D, Chatterjee S, Anura A, Bag S, Chakraborty D, Pal M, Paul RR, Chatterjee J. Elucidation of Differential Nano-Textural Attributes for Normal Oral Mucosa and Pre-Cancer. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2019; 25:1224-1233. [PMID: 31526400 DOI: 10.1017/s1431927619014867] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Computational analysis on altered micro-nano-textural attributes of the oral mucosa may provide precise diagnostic information about oral potentially malignant disorders (OPMDs) instead of an existing handful of qualitative reports. This study evaluated micro-nano-textural features of oral epithelium from scanning electron microscopic (SEM) images and the sub-epithelial connective tissue from light microscopic (LM) and atomic force microscopic (AFM) images for normal and OPMD (namely oral sub-mucous fibrosis, i.e., OSF). Objective textural descriptors, namely discrete wavelet transform, gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP), were extracted and fed to standard classifiers. Best classification accuracy of 87.28 and 93.21%; sensitivity of 93 and 96%; specificity of 80 and 91% were achieved, respectively, for SEM and AFM. In the study groups, SEM analysis showed a significant (p < 0.01) variation for all the considered textural descriptors, while for AFM, a remarkable alteration (p < 0.01) was only found in GLCM and LBP. Interestingly, sub-epithelial collagen nanoscale and microscale textural information from AFM and LM images, respectively, were complementary, namely microlevel contrast was more in normal (0.251) than OSF (0.193), while nanolevel contrast was more in OSF (0.283) than normal (0.204). This work, thus, illustrated differential micro-nano-textural attributes for oral epithelium and sub-epithelium to distinguish OPMD precisely and may be contributory in early cancer diagnostics.
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Affiliation(s)
- Debaleena Nawn
- Advanced Technology Development Centre, Indian Institute of Technology, Kharagpur 721302, West Bengal, India
| | - Saunak Chatterjee
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur 721302, West Bengal, India
| | - Anji Anura
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur 721302, West Bengal, India
| | - Swarnendu Bag
- Tata Medical Center, Kolkata 700160, West Bengal, India
| | - Debjani Chakraborty
- Department of Mathematics, Indian Institute of Technology, Kharagpur 721302, West Bengal, India
| | - Mousumi Pal
- Guru Nanak Institute of Dental Sciences and Research, Kolkata 700114, West Bengal, India
| | - Ranjan Rashmi Paul
- Guru Nanak Institute of Dental Sciences and Research, Kolkata 700114, West Bengal, India
| | - Jyotirmoy Chatterjee
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur 721302, West Bengal, India
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21
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Trusiak M, Picazo-Bueno JA, Patorski K, Zdańkowski P, Mico V. Single-shot two-frame π-shifted spatially multiplexed interference phase microscopy. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-8. [PMID: 31522487 PMCID: PMC6997581 DOI: 10.1117/1.jbo.24.9.096004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 07/30/2019] [Indexed: 05/05/2023]
Abstract
Single-shot, two-frame, π-shifted spatially multiplexed interference microscopy (π-SMIM) is presented as an improvement to previous SMIM implementations, introducing a versatile, robust, fast, and accurate method for cumbersome, noisy, and low-contrast phase object analysis. The proposed π-SMIM equips a commercially available nonholographic microscope with a high-speed (video frame rate) enhanced quantitative phase imaging (QPI) capability by properly placing a beam-splitter in the microscope embodiment to simultaneously (in a single shot) record two holograms mutually phase shifted by π radians at the expense of reducing the field of view. Upon subsequent subtractive superimposition of holograms, a π-hologram is generated with reduced background and improved modulation of interference fringes. These features determine superior phase retrieval quality, obtained by employing the Hilbert spiral transform on the π-hologram, as compared with a single low-quality (low signal-to-noise ratio) hologram analysis. In addition, π-SMIM enables accurate in-vivo analysis of high dynamic range phase objects, otherwise measurable only in static regime using time-consuming phase-shifting. The technique has been validated utilizing a 20 × / 0.46 NA objective in a regular Olympus BX-60 upright microscope for QPI of different lines of prostate cancer cells and flowing microbeads.
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Affiliation(s)
- Maciej Trusiak
- Warsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland
- Address all correspondence to Maciej Trusiak, E-mail: ; Vicente Mico, E-mail:
| | - Jose-Angel Picazo-Bueno
- Universitat de Valencia, Departamento de Óptica y Optometría y Ciencias de la Visión, Burjassot, Spain
| | - Krzysztof Patorski
- Warsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland
| | - Piotr Zdańkowski
- Warsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland
| | - Vicente Mico
- Universitat de Valencia, Departamento de Óptica y Optometría y Ciencias de la Visión, Burjassot, Spain
- Address all correspondence to Maciej Trusiak, E-mail: ; Vicente Mico, E-mail:
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22
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Ge X, Tang H, Wang X, Liu X, Chen S, Wang N, Ni G, Yu X, Chen S, Liang H, Bo E, Wang L, Braganza CS, Xu C, Rowe SM, Tearney GJ, Liu L. Geometry-Dependent Spectroscopic Contrast in Deep Tissues. iScience 2019; 19:965-975. [PMID: 31522119 PMCID: PMC6745491 DOI: 10.1016/j.isci.2019.08.046] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 07/10/2019] [Accepted: 08/22/2019] [Indexed: 12/19/2022] Open
Abstract
Nano-structures of biological systems can produce diverse spectroscopic effects through interactions with broadband light. Although structured coloration at the surface has been extensively studied, natural spectroscopic contrasts in deep tissues are poorly understood, which may carry valuable information for evaluating the anatomy and function of biological systems. Here we investigated the spectroscopic characteristics of an important geometry in deep tissues at the nanometer scale: packed nano-cylinders, in the near-infrared window, numerically predicted and experimentally proved that transversely oriented and regularly arranged nano-cylinders could selectively backscatter light of the long wavelengths. Notably, we found that the spectroscopic contrast of nanoscale fibrous structures was sensitive to the pressure load, possibly owing to the changes in the orientation, the degree of alignment, and the spacing. To explore the underlying physical basis, we further developed an analytical model based on the radial distribution function in terms of their radius, refractive index, and spatial distribution.
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Affiliation(s)
- Xin Ge
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Hongying Tang
- College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
| | - Xianghong Wang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Xinyu Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Si Chen
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Nanshuo Wang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Guangming Ni
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xiaojun Yu
- School of Automation, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China
| | - Shufen Chen
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Haitao Liang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - En Bo
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Lulu Wang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Cilwyn Shalitha Braganza
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore
| | - Chenjie Xu
- School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 637459, Republic of Singapore
| | - Steven M Rowe
- Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA; Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
| | - Guillermo J Tearney
- Wellman Center for Photomedicine, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02114, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA 02139, USA; Department of Pathology, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02114, USA.
| | - Linbo Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore; School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 637459, Republic of Singapore.
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23
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Liu Y, Xu J. High-resolution microscopy for imaging cancer pathobiology. CURRENT PATHOBIOLOGY REPORTS 2019; 7:85-96. [PMID: 32953251 PMCID: PMC7500261 DOI: 10.1007/s40139-019-00201-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW Light microscopy plays an essential role in clinical diagnosis and understanding the pathogenesis of cancer. Conventional bright-field microscope is used to visualize abnormality in tissue architecture and nuclear morphology, but often suffers from many limitations. This review focuses on the potential of new imaging techniques to improve basic and clinical research in pathobiology. RECENT FINDINGS Light microscopy has significantly expanded its ability in resolution, imaging volume, speed and contrast. It now allows 3D high-resolution volumetric imaging of tissue architecture from large tissue and molecular structures at nanometer resolution. SUMMARY Pathologists and researchers now have access to various imaging tools to study cancer pathobiology in both breadth and depth. Although clinical adoption of a new technique is slow, the new imaging tools will provide significant new insights and open new avenues for improving early cancer detection, personalized risk assessment and identifying the best treatment strategies.
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Affiliation(s)
- Yang Liu
- Biomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jianquan Xu
- Biomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
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24
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Uttam S, Hashash JG, LaFace J, Binion D, Regueiro M, Hartman DJ, Brand RE, Liu Y. Three-Dimensional Nanoscale Nuclear Architecture Mapping of Rectal Biopsies Detects Colorectal Neoplasia in Patients with Inflammatory Bowel Disease. Cancer Prev Res (Phila) 2019; 12:527-538. [PMID: 31164345 DOI: 10.1158/1940-6207.capr-19-0024] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/19/2019] [Accepted: 05/29/2019] [Indexed: 12/25/2022]
Abstract
Patients with inflammatory bowel disease (IBD) colitis are at an increased risk of developing colorectal cancer and are currently recommended to undergo extensive annual or biennial colonoscopy, a costly and invasive procedure. Most surveillance colonoscopies are negative with no existing objective measures for assessing their risk of developing cancer. We have recently developed a less invasive, cost-effective and objective method to assess cancer risk by detecting the presence of colonic neoplasia via 3-dimensional (3D) nanoscale nuclear architecture mapping (nanoNAM) of normal-appearing rectal biopsies. To establish its translational relevance, we prospectively recruited 103 patients with IBD colitis undergoing surveillance colonoscopy and measured submicroscopic alterations in aberrant intrinsic nuclear architecture of epithelial cells from normal-appearing rectal biopsies with nanoNAM. The results were correlated with the histologic diagnoses from all random biopsies obtained during initial and follow-up colonoscopy within 3 years. Using nanoNAM-based structural characterization as input features into a soft margin-based ν-SVM risk classifier, we show that nanoNAM detects colonic neoplasia with AUC of 0.87 ± 0.04, sensitivity of 0.81 ± 0.09, and specificity of 0.82 ± 0.07 in the independent validation set. In addition, projecting nanoNAM features onto a 2-sphere reveals patients with low-risk and high-risk IBD colitis existing on separate hemispheres. Finally, we show that this ability to assess cancer risk translates to clinically-relevant estimation of individual-patient likelihood of being truly at risk. We demonstrate the potential of nanoNAM to identify patients with IBD at higher risk of developing cancer from normal-appearing rectum tissue, which may aid clinicians in patients with personalized IBD colitis surveillance.
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Affiliation(s)
- Shikhar Uttam
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.
| | - Jana G Hashash
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Justin LaFace
- Biomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David Binion
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Miguel Regueiro
- Department of Gastroenterology, Hepatology and Nutrition, Cleveland Clinic, Cleveland, Ohio
| | - Douglas J Hartman
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Randall E Brand
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.,University of Pittsburgh Hillman Cancer Center, Pittsburgh, Pennsylvania
| | - Yang Liu
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania. .,Biomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania.,University of Pittsburgh Hillman Cancer Center, Pittsburgh, Pennsylvania
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25
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Majeed H, Nguyen TH, Kandel ME, Kajdacsy-Balla A, Popescu G. Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM). Sci Rep 2018; 8:6875. [PMID: 29720678 PMCID: PMC5932029 DOI: 10.1038/s41598-018-25261-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 04/03/2018] [Indexed: 11/16/2022] Open
Abstract
Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis, a need that can potentially be met by novel microscopy methods. We present a quantitative method for label-free breast tissue evaluation using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective, label-free and potentially automatable method for breast histopathology. We demonstrated our method by imaging a tissue microarray consisting of 68 different subjects −34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. Our disease signatures represent intrinsic physical attributes of the sample, independent of staining quality, facilitating classification through machine learning packages since our images do not vary from scan to scan or instrument to instrument.
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Affiliation(s)
- Hassaan Majeed
- Quantitative Light Imaging (QLI) Lab, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N Matthews, Urbana, IL 61801, USA
| | - Tan Huu Nguyen
- Quantitative Light Imaging (QLI) Lab, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N Matthews, Urbana, IL 61801, USA
| | - Mikhail Eugene Kandel
- Quantitative Light Imaging (QLI) Lab, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N Matthews, Urbana, IL 61801, USA
| | - Andre Kajdacsy-Balla
- Department of Pathology, University of Illinois at Chicago, 840 South Wood Street, Suite 130 CSN, Chicago, IL 60612, USA
| | - Gabriel Popescu
- Quantitative Light Imaging (QLI) Lab, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N Matthews, Urbana, IL 61801, USA.
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26
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Takabayashi M, Majeed H, Kajdacsy-Balla A, Popescu G. Disorder strength measured by quantitative phase imaging as intrinsic cancer marker in fixed tissue biopsies. PLoS One 2018; 13:e0194320. [PMID: 29561905 PMCID: PMC5862460 DOI: 10.1371/journal.pone.0194320] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 02/28/2018] [Indexed: 12/15/2022] Open
Abstract
Tissue refractive index provides important information about morphology at the nanoscale. Since the malignant transformation involves both intra- and inter-cellular changes in the refractive index map, the tissue disorder measurement can be used to extract important diagnosis information. Quantitative phase imaging (QPI) provides a practical means of extracting this information as it maps the optical path-length difference (OPD) across a tissue sample with sub-wavelength sensitivity. In this work, we employ QPI to compare the tissue disorder strength between benign and malignant breast tissue histology samples. Our results show that disease progression is marked by a significant increase in the disorder strength. Since our imaging system can be added as an upgrading module to an existing microscope, we anticipate that it can be integrated easily in the pathology work flow.
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Affiliation(s)
- Masanori Takabayashi
- Department of Systems Design and Informatics, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan
- Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- * E-mail:
| | - Hassaan Majeed
- Department of Bioengineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Andre Kajdacsy-Balla
- Department of Pathology, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Gabriel Popescu
- Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
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27
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Uttam S, Liu Y. Fourier phase based depth-resolved nanoscale nuclear architecture mapping for cancer detection. Methods 2017; 136:134-151. [PMID: 29127043 DOI: 10.1016/j.ymeth.2017.10.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 10/29/2017] [Accepted: 10/31/2017] [Indexed: 10/18/2022] Open
Abstract
Quantitative phase imaging (QPI) modality has been widely adopted in a variety of applications ranging from identifying photomask defects in lithography to characterizing cell structure and tissue morphology in cancer. Traditional QPI utilizes the electromagnetic phase of transmitted light to measure, with nanometer scale sensitivity, alterations in the optical thickness of a sample of interest. In our work, the QPI paradigm is generalized to study depth-resolved properties of phase objects with slowly varying refractive index without a strong interface by utilizing the Fourier phase associated with Fourier-domain optical coherence tomography (FD-OCT). Specifically, based on computing the Fourier phase of light back-scattered by cell nuclei, we have developed nanoscale nuclear architecture mapping (nanoNAM) method that quantifies, with nanoscale sensitivity, (a) the depth-resolved alterations in mean nuclear optical density, and (b) depth-resolved localized heterogeneity in optical density of the cell nuclei. We have used nanoNAM to detect malignant transformation in colon carcinogenesis, even in tissue that appears histologically normal according to pathologists, thereby showing its potential as a pathology aid in cases where pathology examination remains inconclusive, and for screening patient populations at risk of developing cancer. In this paper, we integrate all aspects of nanoNAM, from principle through instrumentation and analysis, to show that nanoNAM is a promising, low-cost, and label-free method for identifying pathologically indeterminate pre-cancerous and cancerous cells. Importantly, it can seamlessly integrate into the clinical pipeline by utilizing clinically prepared formalin-fixed, paraffin-embedded tissue sections.
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Affiliation(s)
- Shikhar Uttam
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Yang Liu
- Biomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States.
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28
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Kandel ME, Sridharan S, Liang J, Luo Z, Han K, Macias V, Shah A, Patel R, Tangella K, Kajdacsy-Balla A, Guzman G, Popescu G. Label-free tissue scanner for colorectal cancer screening. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:66016. [PMID: 28655054 DOI: 10.1117/1.jbo.22.6.066016] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 05/22/2017] [Indexed: 05/20/2023]
Abstract
The current practice of surgical pathology relies on external contrast agents to reveal tissue architecture, which is then qualitatively examined by a trained pathologist. The diagnosis is based on the comparison with standardized empirical, qualitative assessments of limited objectivity. We propose an approach to pathology based on interferometric imaging of “unstained” biopsies, which provides unique capabilities for quantitative diagnosis and automation. We developed a label-free tissue scanner based on “quantitative phase imaging,” which maps out optical path length at each point in the field of view and, thus, yields images that are sensitive to the “nanoscale” tissue architecture. Unlike analysis of stained tissue, which is qualitative in nature and affected by color balance, staining strength and imaging conditions, optical path length measurements are intrinsically quantitative, i.e., images can be compared across different instruments and clinical sites. These critical features allow us to automate the diagnosis process. We paired our interferometric optical system with highly parallelized, dedicated software algorithms for data acquisition, allowing us to image at a throughput comparable to that of commercial tissue scanners while maintaining the nanoscale sensitivity to morphology. Based on the measured phase information, we implemented software tools for autofocusing during imaging, as well as image archiving and data access. To illustrate the potential of our technology for large volume pathology screening, we established an “intrinsic marker” for colorectal disease that detects tissue with dysplasia or colorectal cancer and flags specific areas for further examination, potentially improving the efficiency of existing pathology workflows.
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Affiliation(s)
- Mikhail E Kandel
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United StatesbUniversity of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
| | - Shamira Sridharan
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United StatescUniversity of Illinois at Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United StatesdUniversity of California, Biomedical Engineering Department, Davis, California, United States
| | - Jon Liang
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States
| | - Zelun Luo
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States
| | - Kevin Han
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States
| | - Virgilia Macias
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | - Anish Shah
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | - Roshan Patel
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | | | - Andre Kajdacsy-Balla
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | - Grace Guzman
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | - Gabriel Popescu
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United StatesbUniversity of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United StatescUniversity of Illinois at Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
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29
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The transformation of the nuclear nanoarchitecture in human field carcinogenesis. Future Sci OA 2017; 3:FSO206. [PMID: 28884003 PMCID: PMC5583697 DOI: 10.4155/fsoa-2017-0027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Accepted: 04/07/2017] [Indexed: 12/23/2022] Open
Abstract
Morphological alterations of the nuclear texture are a hallmark of carcinogenesis. At later stages of disease, these changes are well characterized and detectable by light microscopy. Evidence suggests that similar albeit nanoscopic alterations develop at the predysplastic stages of carcinogenesis. Using the novel optical technique partial wave spectroscopic microscopy, we identified profound changes in the nanoscale chromatin topology in microscopically normal tissue as a common event in the field carcinogenesis of many cancers. In particular, higher-order chromatin structure at supranucleosomal length scales (20-200 nm) becomes exceedingly heterogeneous, a measure we quantify using the disorder strength (Ld ) of the spatial arrangement of chromatin density. Here, we review partial wave spectroscopic nanocytology clinical studies and the technology's promise as an early cancer screening technology.
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30
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Majeed H, Okoro C, Kajdacsy-Balla A, Toussaint KC, Popescu G. Quantifying collagen fiber orientation in breast cancer using quantitative phase imaging. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:46004. [PMID: 28388706 DOI: 10.1117/1.jbo.22.4.046004] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 03/16/2017] [Indexed: 05/20/2023]
Abstract
Tumor progression in breast cancer is significantly influenced by its interaction with the surrounding stromal tissue. Specifically, the composition, orientation, and alignment of collagen fibers in tumor-adjacent stroma affect tumor growth and metastasis. Most of the work done on measuring this prognostic marker has involved imaging of collagen fibers using second-harmonic generation microscopy (SHGM), which provides label-free specificity. Here, we show that spatial light interference microscopy (SLIM), a label-free quantitative phase imaging technique, is able to provide information on collagen-fiber orientation that is comparable to that provided by SHGM. Due to its wide-field geometry, the throughput of the SLIM system is much higher than that of SHGM and, because of the linear imaging, the equipment is simpler and significantly less expensive. Our results indicate that SLIM images can be used to extract important prognostic information from collagen fibers in breast tissue, potentially providing a convenient high throughput clinical tool for assessing patient prognosis.
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Affiliation(s)
- Hassaan Majeed
- University of Illinois at Urbana Champaign, Quantitative Light Imaging (QLI) Lab, Department of Bioengineering, Beckman Institute of Advanced Science and Technology, Urbana, Illinois, United States
| | - Chukwuemeka Okoro
- University of Illinois at Urbana Champaign, Photonics Research of Bio/Nano Environments (PROBE) Lab, Department of Electrical and Computer Engineering, Mechanical Engineering Lab, Urbana, Illinois, United States
| | - André Kajdacsy-Balla
- University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States
| | - Kimani C Toussaint
- University of Illinois at Urbana Champaign, Photonics Research of Bio/Nano Environments (PROBE) Lab, Department of Mechanical Science and Engineering, Mechanical Engineering Lab, Urbana, Illinois, United States
| | - Gabriel Popescu
- University of Illinois at Urbana Champaign, Quantitative Light Imaging (QLI) Lab, Department of Electrical and Computer Engineering, Beckman Institute of Advanced Science and Technology, Urbana, Illinois, United States
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31
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Nguyen TH, Sridharan S, Macias V, Kajdacsy-Balla A, Melamed J, Do MN, Popescu G. Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:36015. [PMID: 28358941 DOI: 10.1117/1.jbo.22.3.036015] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 03/13/2017] [Indexed: 05/20/2023]
Abstract
We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of the unlabeled specimen. We use these data to train a random forest classifier to learn textural behaviors of prostate samples and classify each pixel in the image into different classes. Automatic diagnosis results were computed from the segmented regions. By combining morphological features with quantitative information from the glands and stroma, logistic regression was used to discriminate regions with Gleason grade 3 versus grade 4 cancer in prostatectomy tissue. The overall accuracy of this classification derived from a receiver operating curve was 82%, which is in the range of human error when interobserver variability is considered. We anticipate that our approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.
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Affiliation(s)
- Tan H Nguyen
- University of Illinois, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, Quantitative Light Imaging Laboratory, Urbana-Champaign, Illinois, United States
| | - Shamira Sridharan
- University of Illinois, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, Quantitative Light Imaging Laboratory, Urbana-Champaign, Illinois, United States
| | - Virgilia Macias
- University of Illinois, Department of Pathology, Chicago, Illinois, United States
| | - Andre Kajdacsy-Balla
- University of Illinois, Department of Pathology, Chicago, Illinois, United States
| | - Jonathan Melamed
- New York University, School of Medicine, Department of Pathology, New York, New York, United States
| | - Minh N Do
- University of Illinois, Department of Electrical and Computer Engineering, Computational Imaging Group, Coordinated Science Laboratory, Urbana-Champaign, Illinois, United States
| | - Gabriel Popescu
- University of Illinois, Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering, Quantitative Light Imaging Laboratory, Urbana-Champaign, Illinois, United States
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32
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Cherkezyan L, Zhang D, Subramanian H, Capoglu I, Taflove A, Backman V. Review of interferometric spectroscopy of scattered light for the quantification of subdiffractional structure of biomaterials. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:30901. [PMID: 28290596 PMCID: PMC5348632 DOI: 10.1117/1.jbo.22.3.030901] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Accepted: 02/20/2017] [Indexed: 05/19/2023]
Abstract
Optical microscopy is the staple technique in the examination of microscale material structure in basic science and applied research. Of particular importance to biology and medical research is the visualization and analysis of the weakly scattering biological cells and tissues. However, the resolution of optical microscopy is limited to ? 200 ?? nm due to the fundamental diffraction limit of light. We review one distinct form of the spectroscopic microscopy (SM) method, which is founded in the analysis of the second-order spectral statistic of a wavelength-dependent bright-field far-zone reflected-light microscope image. This technique offers clear advantages for biomedical research by alleviating two notorious challenges of the optical evaluation of biomaterials: the diffraction limit of light and the lack of sensitivity to biological, optically transparent structures. Addressing the first issue, it has been shown that the spectroscopic content of a bright-field microscope image quantifies structural composition of samples at arbitrarily small length scales, limited by the signal-to-noise ratio of the detector, without necessarily resolving them. Addressing the second issue, SM utilizes a reference arm, sample arm interference scheme, which allows us to elevate the weak scattering signal from biomaterials above the instrument noise floor.
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Affiliation(s)
- Lusik Cherkezyan
- Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States
| | - Di Zhang
- Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States
| | - Hariharan Subramanian
- Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States
| | - Ilker Capoglu
- Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States
| | - Allen Taflove
- Northwestern University, Department of Electrical Engineering, Evanston, Illinois, United States
| | - Vadim Backman
- Northwestern University, Department of Biomedical Engineering, Evanston, Illinois, United States
- Address all correspondence to: Vadim Backman, E-mail:
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Majeed H, Sridharan S, Mir M, Ma L, Min E, Jung W, Popescu G. Quantitative phase imaging for medical diagnosis. JOURNAL OF BIOPHOTONICS 2017; 10:177-205. [PMID: 27539534 DOI: 10.1002/jbio.201600113] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2016] [Revised: 07/06/2016] [Accepted: 07/13/2016] [Indexed: 05/19/2023]
Abstract
Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter- and intra-observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label-free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date. [Image adapted from Y. Park, M. Diez-Silva, G. Popescu, G. Lykotrafitis, W. Choi, M. S. Feld, and S. Suresh, Proc. Natl. Acad. Sci. 105, 13730-13735 (2008).].
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Affiliation(s)
- Hassaan Majeed
- Quantitative Light Imaging Lab, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N. Mathews Ave., Urbana, IL, 61801, USA
| | - Shamira Sridharan
- Biomedical Engineering Department, University of California Davis, Genome and Biomedical Sciences Facility #2603B, 451 Health Science Dr., Davis, CA, 95616, USA
| | - Mustafa Mir
- Molecular and Cell Biology, University of California, Berkeley, 485 Li Ka Shing Center, 94720, Berkeley, CA, USA
| | - Lihong Ma
- Institute of Information Optics, Zhejiang Normal University, Jinhua, 321004, China
| | - Eunjung Min
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, Republic of Korea
| | - Woonggyu Jung
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, Republic of Korea
- Center for Soft and Living Matter, Institute for Basic Science (IBS), 50 UNIST-gil, Ulsan, 44919, Republic of Korea
| | - Gabriel Popescu
- Quantitative Light Imaging Lab, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, 405 N. Mathews Ave., Urbana, IL, 61801, USA
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Shan M, Kandel ME, Popescu G. Refractive index variance of cells and tissues measured by quantitative phase imaging. OPTICS EXPRESS 2017; 25:1573-1581. [PMID: 28158039 DOI: 10.1364/oe.25.001573] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The refractive index distribution of cells and tissues governs their interaction with light and can report on morphological modifications associated with disease. Through intensity-based measurements, refractive index information can be extracted only via scattering models that approximate light propagation. As a result, current knowledge of refractive index distributions across various tissues and cell types remains limited. Here we use quantitative phase imaging and the statistical dispersion relation (SDR) to extract information about the refractive index variance in a variety of specimens. Due to the phase-resolved measurement in three-dimensions, our approach yields refractive index results without prior knowledge about the tissue thickness. With the recent progress in quantitative phase imaging systems, we anticipate that using SDR will become routine in assessing tissue optical properties.
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Shan M, Kandel ME, Majeed H, Nastasa V, Popescu G. White-light diffraction phase microscopy at doubled space-bandwidth product. OPTICS EXPRESS 2016; 24:29033-29039. [PMID: 27958568 DOI: 10.1364/oe.24.029033] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
White light diffraction microscopy (wDPM) is a quantitative phase imaging method that benefits from both temporal and spatial phase sensitivity, granted, respectively, by the common-path geometry and white light illumination. However, like all off-axis quantitative phase imaging methods, wDPM is characterized by a reduced space-bandwidth product compared to phase shifting approaches. This happens essentially because the ultimate resolution of the image is governed by the period of the interferogram and not just the diffraction limit. As a result, off-axis techniques generates single-shot, i.e., high time-bandwidth, phase measurements, at the expense of either spatial resolution or field of view. Here, we show that combining phase-shifting and off-axis, the original space-bandwidth is preserved. Specifically, we developed phase-shifting diffraction phase microscopy with white light, in which we measure and combine two phase shifted interferograms. Due to the white light illumination, the phase images are characterized by low spatial noise, i.e., <1nm pathlength. We illustrate the operation of the instrument with test samples, blood cells, and unlabeled prostate tissue biopsy.
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Uttam S, Liu Y. Fourier phase in Fourier-domain optical coherence tomography. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2015; 32:2286-306. [PMID: 26831383 PMCID: PMC4741112 DOI: 10.1364/josaa.32.002286] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Phase of an electromagnetic wave propagating through a sample-of-interest is well understood in the context of quantitative phase imaging in transmission-mode microscopy. In the past decade, Fourier-domain optical coherence tomography has been used to extend quantitative phase imaging to the reflection-mode. Unlike transmission-mode electromagnetic phase, however, the origin and characteristics of reflection-mode Fourier phase are poorly understood, especially in samples with a slowly varying refractive index. In this paper, the general theory of Fourier phase from first principles is presented, and it is shown that Fourier phase is a joint estimate of subresolution offset and mean spatial frequency of the coherence-gated sample refractive index. It is also shown that both spectral-domain phase microscopy and depth-resolved spatial-domain low-coherence quantitative phase microscopy are special cases of this general theory. Analytical expressions are provided for both, and simulations are presented to explain and support the theoretical results. These results are further used to show how Fourier phase allows the estimation of an axial mean spatial frequency profile of the sample, along with depth-resolved characterization of localized optical density change and sample heterogeneity. Finally, a Fourier phase-based explanation of Doppler optical coherence tomography is also provided.
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