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Bueno G, Fernández-Carrobles MM, Deniz O, García-Rojo M. New Trends of Emerging Technologies in Digital Pathology. Pathobiology 2017; 83:61-9. [PMID: 27100343 DOI: 10.1159/000443482] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The future paradigm of pathology will be digital. Instead of conventional microscopy, a pathologist will perform a diagnosis through interacting with images on computer screens and performing quantitative analysis. The fourth generation of virtual slide telepathology systems, so-called virtual microscopy and whole-slide imaging (WSI), has allowed for the storage and fast dissemination of image data in pathology and other biomedical areas. These novel digital imaging modalities encompass high-resolution scanning of tissue slides and derived technologies, including automatic digitization and computational processing of whole microscopic slides. Moreover, automated image analysis with WSI can extract specific diagnostic features of diseases and quantify individual components of these features to support diagnoses and provide informative clinical measures of disease. Therefore, the challenge is to apply information technology and image analysis methods to exploit the new and emerging digital pathology technologies effectively in order to process and model all the data and information contained in WSI. The final objective is to support the complex workflow from specimen receipt to anatomic pathology report transmission, that is, to improve diagnosis both in terms of pathologists' efficiency and with new information. This article reviews the main concerns about and novel methods of digital pathology discussed at the latest workshop in the field carried out within the European project AIDPATH (Academia and Industry Collaboration for Digital Pathology).
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Ahmed Raza SE, Langenkämper D, Sirinukunwattana K, Epstein D, Nattkemper TW, Rajpoot NM. Robust normalization protocols for multiplexed fluorescence bioimage analysis. BioData Min 2016; 9:11. [PMID: 26949415 PMCID: PMC4779207 DOI: 10.1186/s13040-016-0088-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 02/02/2016] [Indexed: 12/18/2022] Open
Abstract
study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to use the standard immuno-fluorescence microscopy in a cyclic manner (Nat Biotechnol 24:1270–8, 2006; Proc Natl Acad Sci 110:11982–7, 2013). Unfortunately, these techniques suffer from variability in intensity and positioning of signals from protein markers within a run and across different runs. Therefore, it is necessary to standardize protocols for preprocessing of the multiplexed bioimaging (MBI) data from multiple runs to a comparable scale before any further analysis can be performed on the data. In this paper, we compare various normalization protocols and propose on the basis of the obtained results, a robust normalization technique that produces consistent results on the MBI data collected from different runs using the Toponome Imaging System (TIS). Normalization results produced by the proposed method on a sample TIS data set for colorectal cancer patients were ranked favorably by two pathologists and two biologists. We show that the proposed method produces higher between class Kullback-Leibler (KL) divergence and lower within class KL divergence on a distribution of cell phenotypes from colorectal cancer and histologically normal samples.
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Affiliation(s)
- Shan E Ahmed Raza
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL UK
| | | | | | - David Epstein
- Mathematics Institute, University of Warwick, Coventry, CV4 7AL UK
| | | | - Nasir M Rajpoot
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL UK ; Department of Computer Science and Engineering, Qatar University, Doha, Qatar
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Livingstone SG, Smith MJ, Silva DS, Upshur REG. Much ado about omics: welcome to 'the permutome'. J Eval Clin Pract 2015; 21:1018-21. [PMID: 26149276 DOI: 10.1111/jep.12406] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
| | - Maxwell J Smith
- Dalla Lana School of Public Health and Joint Centre for Bioethics, University of Toronto, Toronto, ON, Canada
| | - Diego S Silva
- Institute for History, Ethics and Philosophy of Medicine, Hannover Medical School, Hannover, Germany
| | - Ross E G Upshur
- Department of Family and Community Medicine, and Joint Centre for Bioethics, University of Toronto, Toronto, ON, Canada
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Theophilou G, Paraskevaidi M, Lima KMG, Kyrgiou M, Martin-Hirsch PL, Martin FL. Extracting biomarkers of commitment to cancer development: potential role of vibrational spectroscopy in systems biology. Expert Rev Mol Diagn 2015; 15:693-713. [DOI: 10.1586/14737159.2015.1028372] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Schubert W. Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems. J Mol Recognit 2014; 27:3-18. [PMID: 24375580 PMCID: PMC4283051 DOI: 10.1002/jmr.2326] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 08/27/2013] [Indexed: 01/27/2023]
Abstract
Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described-a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs.
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Affiliation(s)
- Walter Schubert
- Molecular pattern recognition research group, O-v-G-university MagdeburgGermany
- International faculty, Max-Planck (CAS-MPG) partner institute for computational biologyShanghai, China
- Human toponome project, TNLMunich, Germany
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Kovacheva VN, Khan AM, Khan M, Epstein DBA, Rajpoot NM. DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data. ACTA ACUST UNITED AC 2013; 30:420-7. [PMID: 24273247 DOI: 10.1093/bioinformatics/btt676] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
MOTIVATION New bioimaging techniques have recently been proposed to visualize the colocation or interaction of several proteins within individual cells, displaying the heterogeneity of neighbouring cells within the same tissue specimen. Such techniques could hold the key to understanding complex biological systems such as the protein interactions involved in cancer. However, there is a need for new algorithmic approaches that analyze the large amounts of multi-tag bioimage data from cancerous and normal tissue specimens to begin to infer protein networks and unravel the cellular heterogeneity at a molecular level. RESULTS The proposed approach analyzes cell phenotypes in normal and cancerous colon tissue imaged using the robotically controlled Toponome Imaging System microscope. It involves segmenting the 4',6-diamidino-2-phenylindole-labelled image into cells and determining the cell phenotypes according to their protein-protein dependence profile. These were analyzed using two new measures, Difference in Sums of Weighted cO-dependence/Anti-co-dependence profiles (DiSWOP and DiSWAP) for overall co-expression and anti-co-expression, respectively. These novel quantities were extracted using 11 Toponome Imaging System image stacks from either cancerous or normal human colorectal specimens. This approach enables one to easily identify protein pairs that have significantly higher/lower co-expression levels in cancerous tissue samples when compared with normal colon tissue. AVAILABILITY AND IMPLEMENTATION http://www2.warwick.ac.uk/fac/sci/dcs/research/combi/research/bic/diswop.
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Affiliation(s)
- Violeta N Kovacheva
- Department of Systems Biology, Department of Computer Science, School of Life Science, Mathematics Institute, The University of Warwick, Coventry CV4 7AL, UK and Department of Computer Science and Engineering, Qatar University, Doha, Qatar
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Bunschoten A, Welling MM, Termaat MF, Sathekge M, van Leeuwen FWB. Development and Prospects of Dedicated Tracers for the Molecular Imaging of Bacterial Infections. Bioconjug Chem 2013; 24:1971-89. [DOI: 10.1021/bc4003037] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- A. Bunschoten
- Department
of Radiology, Interventional Molecular Imaging Laboratory, Leiden University Medical Center, Leiden, The Netherlands
| | - M. M. Welling
- Department
of Radiology, Interventional Molecular Imaging Laboratory, Leiden University Medical Center, Leiden, The Netherlands
| | - M. F. Termaat
- Department
of Trauma Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | - M. Sathekge
- Department of Nuclear Medicine, University of Pretoria & Steve Biko Academic Hospital, Pretoria, South Africa
| | - F. W. B. van Leeuwen
- Department
of Radiology, Interventional Molecular Imaging Laboratory, Leiden University Medical Center, Leiden, The Netherlands
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Patel II, Shearer DA, Fogarty SW, Fullwood NJ, Quaroni L, Martin FL, Weisz J. Infrared microspectroscopy identifies biomolecular changes associated with chronic oxidative stress in mammary epithelium and stroma of breast tissues from healthy young women: implications for latent stages of breast carcinogenesis. Cancer Biol Ther 2013; 15:225-35. [PMID: 24107651 DOI: 10.4161/cbt.26748] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Studies of the decades-long latent stages of breast carcinogenesis have been limited to when hyperplastic lesions are already present. Investigations of earlier stages of breast cancer (BC) latency have been stymied by the lack of fiducial biomarkers needed to identify where in histologically normal tissues progression toward a BC might be taking place. Recent evidence suggests that a marker of chronic oxidative stress (OxS), protein adducts of 4-hydroxy-2-nonenal (4HNE), can meet this need. Specifically: (1) 4HNE immunopositive (4HNE+) mammary epithelial (ME) cells were found to be prevalent in normal (reduction mammoplasty) tissues of most women (including many teenagers) studied, representative of those living in the United States' high risk-posing environment and: (2) marked (> 1.5-fold) differences were identified between tissues of healthy young women with many vs. few 4HNE+ ME cells in the relative levels of transcripts for 42 of the 84 OxS-associated genes represented in SABioscience Oxidative-Stress/Oxidative-Defense PCR array. Herein we used synchrotron radiation-based Fourier-transform infrared (SR-FTIR) microspectroscopy to identify molecular changes associated with 4HNE adducts in basal and luminal ME cells in terminal ductal units (TDLU), which are the cells of origin of BC, and associated intralobular and interlobular stroma, known contributors to carcinogenesis. Multivariate analysis-derived wavenumbers differentiated 4HNE+ and 4HNE- cells in each of the anatomical compartments. Specifically, principal component and linear discriminant analyses of mid-infrared spectra obtained from these cells revealed unambiguous, statistically highly significant differences in the "biochemical fingerprint" of 4HNE+ vs. 4HNE- luminal and basal ME cells, as well as between associated intralobular and interlobular stroma. These findings demonstrate further SR-FTIR microspectroscopy's ability to identify molecular changes associated with altered physiological and/or pathophysiological states, in this case with a state of chronic OxS that provides a pro-carcinogenic microenvironment.
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Affiliation(s)
- Imran I Patel
- Center for Biophotonics; Lancaster Environment Centre; Lancaster University; Lancaster, UK
| | - Debra A Shearer
- Department of Obstetrics and Gynecology; College of Medicine; Pennsylvania State University; Hershey, PA USA
| | - Simon W Fogarty
- Division of Biomedical and Life Sciences; Faculty of Health and Medicine; Lancaster University; Lancaster, UK
| | - Nigel J Fullwood
- Division of Biomedical and Life Sciences; Faculty of Health and Medicine; Lancaster University; Lancaster, UK
| | | | - Francis L Martin
- Center for Biophotonics; Lancaster Environment Centre; Lancaster University; Lancaster, UK
| | - Judith Weisz
- Department of Obstetrics and Gynecology; College of Medicine; Pennsylvania State University; Hershey, PA USA; Department of Pathology; College of Medicine; Pennsylvania State University; Hershey, PA USA
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