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Zhang T, Zhu J, Li Z, Zhao Y, Li Y, Li J, He Q, Geng Y, Lu W, Zhang L, Li Z. The UF-5000 Atyp.C parameter is an independent risk factor for bladder cancer. Sci Rep 2024; 14:12659. [PMID: 38830942 PMCID: PMC11148171 DOI: 10.1038/s41598-024-63572-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 05/30/2024] [Indexed: 06/05/2024] Open
Abstract
Bladder carcinoma (BC) accounts for > 90% of all urothelial cancers. Pathological diagnosis through cytoscopic biopsy is the gold standard, whereas non-invasive diagnostic tools remain lacking. The "Atyp.C" parameter of the Sysmex UF-5000 urine particle analyzer represents the ratio of nucleus to cytoplasm and can be employed to detect urinary atypical cells. The present study examined the association between urinary Atyp.C values and BC risk. This two-center, retrospective case-control study identified clinical primary or newly recurrent BC (study period, 2022-2023; n = 473) cases together with controls with urinary tract infection randomly matched by age and sex (1:1). Urinary sediment differences were compared using non-parametric tests. The correlations between urinary Atyp.C levels and BC grade or infiltration were analyzed using Spearman's rank correlation. The BC risk factor odds ratio of Atyp.C was calculated using conditional logistic regression, and potential confounder effects were adjusted using stepwise logistic regression (LR). Primary risk factors were identified by stratified analysis according to pathological histological diagnosis. The mean value of urinary Atyp.C in BC cases (1.30 ± 3.12) was 8.7 times higher than that in the controls (0.15 ± 0.68; P < 0.001). Urinary Atyp.C values were positively correlated with BC pathological grade and invasion (r = 0.360, P < 0.001; r = 0.367, P < 0.001). Urinary Atyp.C was an independent risk factor for BC and closely related with BC pathological grade and invasion. Elevated urinary Atyp.C values was an independent risk factor for BC. Our findings support the use of Atyp.C as a marker that will potentially aid in the early diagnosis and long-term surveillance of new and recurrent BC cases.
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Affiliation(s)
- Tong Zhang
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Jianhong Zhu
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Zhaoxing Li
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Ya Zhao
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Yan Li
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Jing Li
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Qian He
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Yan Geng
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Wei Lu
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Lei Zhang
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China.
| | - Zhenzhen Li
- Department of Clinical Laboratory, Second Hospital, Xi'an Jiaotong University, Xi'an, 710004, China.
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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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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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4
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Lee YK, Ryu D, Kim S, Park J, Park SY, Ryu D, Lee H, Lim S, Min HS, Park Y, Lee EK. Machine-learning-based diagnosis of thyroid fine-needle aspiration biopsy synergistically by Papanicolaou staining and refractive index distribution. Sci Rep 2023; 13:9847. [PMID: 37330568 PMCID: PMC10276805 DOI: 10.1038/s41598-023-36951-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 06/13/2023] [Indexed: 06/19/2023] Open
Abstract
We developed a machine learning algorithm (MLA) that can classify human thyroid cell clusters by exploiting both Papanicolaou staining and intrinsic refractive index (RI) as correlative imaging contrasts and evaluated the effects of this combination on diagnostic performance. Thyroid fine-needle aspiration biopsy (FNAB) specimens were analyzed using correlative optical diffraction tomography, which can simultaneously measure both, the color brightfield of Papanicolaou staining and three-dimensional RI distribution. The MLA was designed to classify benign and malignant cell clusters using color images, RI images, or both. We included 1535 thyroid cell clusters (benign: malignancy = 1128:407) from 124 patients. Accuracies of MLA classifiers using color images, RI images, and both were 98.0%, 98.0%, and 100%, respectively. As information for classification, the nucleus size was mainly used in the color image; however, detailed morphological information of the nucleus was also used in the RI image. We demonstrate that the present MLA and correlative FNAB imaging approach has the potential for diagnosing thyroid cancer, and complementary information from color and RI images can improve the performance of the MLA.
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Affiliation(s)
- Young Ki Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Cancer Center, Goyang, 10408, South Korea
| | | | - Seungwoo Kim
- Artificial Intelligence Graduate School, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, South Korea
| | - Juyeon Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, South Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, 34141, South Korea
| | - Seog Yun Park
- Deparment of Pathology, National Cancer Center, Goyang, 10408, South Korea
| | - Donghun Ryu
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, South Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, 34141, South Korea
- Department of Electrical Engineering and Computer Science (EECS), MIT, Cambridge, MA, 02139, USA
| | - Hayoung Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Cancer Center, Goyang, 10408, South Korea
| | - Sungbin Lim
- Department of Statistics, Korea University, Seoul, 02841, South Korea
| | | | - YongKeun Park
- Tomocube Inc., Daejeon, 34051, South Korea.
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, South Korea.
- KAIST Institute for Health Science and Technology, KAIST, Daejeon, 34141, South Korea.
| | - Eun Kyung Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Cancer Center, Goyang, 10408, South Korea.
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Malinaric R, Mantica G, Lo Monaco L, Mariano F, Leonardi R, Simonato A, Van der Merwe A, Terrone C. The Role of Novel Bladder Cancer Diagnostic and Surveillance Biomarkers-What Should a Urologist Really Know? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19159648. [PMID: 35955004 PMCID: PMC9368399 DOI: 10.3390/ijerph19159648] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 07/29/2022] [Accepted: 07/31/2022] [Indexed: 05/20/2023]
Abstract
The aim of this review is to analyze and describe the current landscape of bladder cancer diagnostic and surveillance biomarkers. We researched the literature from 2016 to November 2021 to find the most promising new molecules and divided them into seven different subgroups based on their function and location in the cell. Although cystoscopy and cytology are still the gold standard for diagnosis and surveillance when it comes to bladder cancer (BCa), their cost is quite a burden for national health systems worldwide. Currently, the research is focused on finding a biomarker that has high negative predictive value (NPV) and can exclude with a certainty the presence of the tumor, considering missing it could be disastrous for the patient. Every subgroup has its own advantages and disadvantages; for example, protein biomarkers cost less than genomic ones, but on the other hand, they seem to be less precise. We tried to simplify this complicated topic as much as possible in order to make it comprehensible to doctors and urologists that are not as familiar with it, as well as encourage them to actively participate in ongoing research.
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Affiliation(s)
- Rafaela Malinaric
- Department of Urology, IRCCS Policlinic Hospital San Martino, 16132 Genoa, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate (DISC), University of Genoa, 16132 Genoa, Italy
- Correspondence:
| | - Guglielmo Mantica
- Department of Urology, IRCCS Policlinic Hospital San Martino, 16132 Genoa, Italy
| | - Lorenzo Lo Monaco
- Department of Urology, IRCCS Policlinic Hospital San Martino, 16132 Genoa, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate (DISC), University of Genoa, 16132 Genoa, Italy
| | - Federico Mariano
- Department of Urology, IRCCS Policlinic Hospital San Martino, 16132 Genoa, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate (DISC), University of Genoa, 16132 Genoa, Italy
| | - Rosario Leonardi
- Department of Urology, Casa di Cura Musumeci GECAS, 95030 Gravina di Catania, Italy
| | - Alchiede Simonato
- Department of Surgical, Oncological and Stomatological Sciences, University of Palermo, 90133 Palermo, Italy
| | - André Van der Merwe
- Department of Urology, Tygerberg Academic Hospital, Stellenbosch University, Cape Town 7600, South Africa
| | - Carlo Terrone
- Department of Urology, IRCCS Policlinic Hospital San Martino, 16132 Genoa, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate (DISC), University of Genoa, 16132 Genoa, Italy
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6
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Krishnamurthy S, Ban K. Feasibility of using digital confocal microscopy for cytopathological examination in clinical practice. Mod Pathol 2022; 35:319-325. [PMID: 34628480 PMCID: PMC8860740 DOI: 10.1038/s41379-021-00925-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/11/2021] [Accepted: 09/07/2021] [Indexed: 11/17/2022]
Abstract
Optical imaging modalities are emerging as digital microscopy tools for tissue examination. The investigation of these techniques for potential applications in anatomic pathology practice has focused primarily on surgical pathology and has not included cytopathological specimens. We evaluated the feasibility of using digital confocal microscopy (CM) to examine cytopathological specimens. Smears and cell suspensions collected in RPMI solution were prepared from tissue scrapes obtained from surgical resections of breast, lung, liver, and kidney. Air-dried smears and cell pellets obtained from centrifugation of the cell suspensions were stained with 0.6 mM acridine orange and imaged with a CM platform. After completion of imaging, the smears were stained with Diff-Quik (DQ), and cell pellets were routinely processed, embedded in paraffin wax, cut, and stained with hematoxylin and eosin (H&E). We evaluated the mean time to acquire digital CM images; quality of images based on the extent of tissue recognition (0%, grade 0; 1-19%, grade 1; 20-50%, grade 2; >50%, grade 3); comparison of images with DQ- and H&E-stained specimens; and ability to make specific diagnoses. We imaged 91 smears and 52 cell pellets and acquired digital CM images within 2-3 min, with 92% and 88% of images, respectively, from smears and cell pellets showing grade 3 quality. On the basis of CM images, 8 smears (9%) and 7 cell pellets (14%) were categorized as benign, and 83 (91%) and 45 (88%), respectively, as malignant. Specific diagnoses were made by using digital CM images of smears and cell pellets that matched accurately with corresponding DQ- and H&E-stained preparations. The results of our first feasibility study clearly indicated the utility of CM as a next-generation digital microscopy tool for evaluating cytology specimens. Prospective clinical studies are warranted for validating our findings for potential incorporation into cytopathological clinical practice.
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Affiliation(s)
- Savitri Krishnamurthy
- Department of Pathology and Laboratory Medicine, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA.
| | - Kechen Ban
- grid.240145.60000 0001 2291 4776Department of Neurosurgery Research, The University of Texas, MD Anderson Cancer Center Houston, Houston, TX USA
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7
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Lv S, Chu Y, Zhang P, Ma S, Zhao M, Wang Z, Gu Y, Sun X. Improved efficiency of urine cell image segmentation using droplet microfluidics technology. Cytometry A 2020; 99:722-731. [PMID: 33342063 DOI: 10.1002/cyto.a.24296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/25/2020] [Accepted: 12/16/2020] [Indexed: 12/12/2022]
Abstract
Recent advances in the recognition of biological samples using machine vision have made this technology increasingly important in research and detection. Image segmentation is an important step in this process. This study focuses on how to reduce the interference factors such as the overlap between different types (or within the same type) of urine cells according to microfluidics and improve the machine vision segmentation accuracy for cell images. In this study, we demonstrate that the platform can realize this hypothesis using urine cell image segmentation as an example application. We first discuss the reported urine cell droplet microfluidic chip system, which can realize the test conditions in which urine cells are encapsulated in the droplet and isolated from salt crystallization and/or bacteria and other urine-formed elements. Then, based on the analysis conditions set in the aforementioned experiment, the proportions of red blood cells, white blood cells, and squamous epithelial cells covered by various formed elements in the total urine cells in the same urine sample are measured. We simultaneously analyze the percentage of urine cells covered by salt crystallization and the incidence of overlapping between urine cells. Finally, the Otsu algorithm is used to segment the urine cell images encapsulated by the droplet and the urine cell images not encapsulated by the droplet, and the Dice, Jaccard, precision, and recall values are calculated. The results suggest that the method of encapsulating single cells based on droplets can improve the image segmentation effect without optimizing the algorithm.
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Affiliation(s)
- Shuxing Lv
- School of Medical Laboratory, Tianjin Medical University, Tianjin, China
| | - Yuying Chu
- School of Medical Laboratory, Tianjin Medical University, Tianjin, China
| | - Panpan Zhang
- North China University of Science and Technology Affiliated Hospital, Tangshan, China
| | - Sike Ma
- Engineering Research Center of Learning-Based Intelligent System, Ministry of Education of China, Tianjin University of Technology, Tianjin, China
| | - Meng Zhao
- Engineering Research Center of Learning-Based Intelligent System, Ministry of Education of China, Tianjin University of Technology, Tianjin, China
| | - Zhexiang Wang
- School of Medical Laboratory, Tianjin Medical University, Tianjin, China
| | - Yajun Gu
- School of Medical Laboratory, Tianjin Medical University, Tianjin, China
| | - Xuguo Sun
- School of Medical Laboratory, Tianjin Medical University, Tianjin, China
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8
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Jiao Y, Kandel ME, Liu X, Lu W, Popescu G. Real-time Jones phase microscopy for studying transparent and birefringent specimens. OPTICS EXPRESS 2020; 28:34190-34200. [PMID: 33182894 PMCID: PMC7679182 DOI: 10.1364/oe.397062] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Tissue birefringence is an intrinsic marker of potential value for cancer diagnosis. Traditionally, birefringence properties have been studied by using intensity-based formalisms, through the Mueller matrix algebra. On the other hand, the Jones matrix description allows for a direct assessment of the sample's anisotropic response. However, because Jones algebra is based on complex fields, requiring measurements of both phase and amplitude, it is less commonly used. Here we propose a real-time imaging method for measuring Jones matrices by quantitative phase imaging. We combine a broadband phase imaging system with a polarization-sensitive detector to obtain Jones matrices at each point in a megapixel scale image, with near video rate capture speeds. To validate the utility of our approach, we measured standard targets, partially birefringent samples, dynamic specimens, and thinly sliced histopathological tissue.
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Affiliation(s)
- Yuheng Jiao
- Quantitative Light Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, the University of Illinois at Urbana-Champaign, Illinois 61801, USA
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Mikhail E. Kandel
- Quantitative Light Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, the University of Illinois at Urbana-Champaign, Illinois 61801, USA
| | - Xiaojun Liu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wenlong Lu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Gabriel Popescu
- Quantitative Light Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, the University of Illinois at Urbana-Champaign, Illinois 61801, USA
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9
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Piao D. Laparoscopic diffuse reflectance spectroscopy of an underlying tubular inclusion: a phantom study. APPLIED OPTICS 2019; 58:9689-9699. [PMID: 31873570 DOI: 10.1364/ao.58.009689] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 11/04/2019] [Indexed: 06/10/2023]
Abstract
We demonstrate diffuse reflectance spectroscopy (DRS) of a subsurface tubular inclusion by using a fiber probe having a single source-detector pair attached to a laparoscopic bipolar device. A forward model was also developed for DRS sensing of an underlying long absorbing tubular inclusion set in parallel to the tissue surface, normal to the line of sight of the source-detector pair, and equidistant from the source and the detector. The model agreed with measurements performed at 500 nm and using a 10 mm source-detector separation (SDS) on an aqueous tissue phantom embedding a tubing of 2 or 4 mm inner diameter that contained 9.1% to 33.3% red dye at a depth of up to 11.5 mm. When tested on solid phantoms using the 10 mm SDS, a tubular inclusion of $ \ge 3\;{\rm mm}$≥3mm inner diameter containing 0.05% red dye at a background absorption coefficient of $ 0.021\;{\rm mm}^{-1} $0.021mm-1 caused $ \ge 8\% $≥8% change of the signal at 500 nm versus the baseline when the inclusion was shallower than 5 mm. When assessed on avian muscle tissue having a 4 mm tubular inclusion embedded at an edge depth of 2 mm, DRS with the 10 mm SDS differentiated the following contents of the inclusion: 33.3% red dye (mimicking blood), 33.3% green dye, 33.3% yellow dye (mimicking bile), water (mimicking urine), and air.
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10
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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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11
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Takabayashi M, Majeed H, Kajdacsy-Balla A, Popescu G. Tissue spatial correlation as cancer marker. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-6. [PMID: 30666854 PMCID: PMC6985696 DOI: 10.1117/1.jbo.24.1.016502] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 12/28/2018] [Indexed: 05/03/2023]
Abstract
We propose an intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing two-dimensional Fourier transforms over image subregions-requiring long computational times. We propose a more time-efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy.
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Affiliation(s)
- Masanori Takabayashi
- Kyushu Institute of Technology, Department of Systems Design and Informatics, Iizuka, Fukuoka, Japan
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
- Address all correspondence to Masanori Takabayashi, E-mail:
| | - Hassaan Majeed
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Department of Bioengineering, Urbana, Illinois, United States
| | - Andre Kajdacsy-Balla
- 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, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
- University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Department of Bioengineering, Urbana, Illinois, United States
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12
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Eldridge WJ, Hoballah J, Wax A. Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope. JOURNAL OF BIOPHOTONICS 2018; 11:e201800126. [PMID: 29896886 DOI: 10.1002/jbio.201800126] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 06/05/2016] [Accepted: 06/06/2018] [Indexed: 05/19/2023]
Abstract
Apoptotic mechanisms are often dysregulated in cancerous phenotypes. Additionally, many anticancer treatments induce apoptosis and necrosis, and the monitoring of this apoptotic activity can allow researchers to identify therapeutic efficiency. Here, we introduce a microscope which combines quantitative phase imaging (QPI) with the ability to detect molecular events via fluorescence (or Förster) resonance energy transfer (FRET). The system was applied to study cells undergoing apoptosis to correlate the onset of apoptotic enzyme activity as observed using a FRET-based apoptosis sensor with whole cell morphological changes analyzed via QPI. The QPI data showed changes in cell disorder strength during the initiation of apoptotic enzymatic activity.
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Affiliation(s)
- Will J Eldridge
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
| | - Jawad Hoballah
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
| | - Adam Wax
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
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13
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Norazman SHB, Nakamura T, Kimura F, Yamaguchi M. Analysis of quantitative phase obtained by digital holography on H&E-stained pathological samples. ARTIFICIAL LIFE AND ROBOTICS 2018. [DOI: 10.1007/s10015-018-0468-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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14
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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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15
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Pantanowitz L, Preffer F, Wilbur DC. Advanced imaging technology applications in cytology. Diagn Cytopathol 2018; 47:5-14. [DOI: 10.1002/dc.23898] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 01/25/2018] [Indexed: 12/13/2022]
Affiliation(s)
- Liron Pantanowitz
- Department of Pathology; University of Pittsburgh Medical Center; Pittsburgh Pennsylvania
| | - Frederic Preffer
- Department of Pathology. Massachusetts General Hospital; Harvard Medical School; Boston Massachusetts
| | - David C. Wilbur
- Department of Pathology. Massachusetts General Hospital; Harvard Medical School; Boston Massachusetts
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