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Akalin A, Ergin A, Remiszewski S, Mu X, Raz D, Diem M. Resolving Interobserver Discrepancies in Lung Cancer Diagnoses by Spectral Histopathology. Arch Pathol Lab Med 2019; 143:157-173. [PMID: 30141697 PMCID: PMC8817896 DOI: 10.5858/arpa.2017-0476-sa] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
This paper reports the results of a collaborative lung cancer study between City of Hope Cancer Center (Duarte, California) and CIRECA, LLC (Cambridge, Massachusetts), comprising 328 samples from 249 patients, that used an optical technique known as spectral histopathology (SHP) for tissue classification. Because SHP is based on a physical measurement, it renders diagnoses on a more objective and reproducible basis than methods based on assessing cell morphology and tissue architecture. This report demonstrates that SHP provides distinction of adenocarcinomas from squamous cell carcinomas of the lung with an accuracy comparable to that of immunohistochemistry and highly reliable classification of adenosquamous carcinoma. Furthermore, this report shows that SHP can be used to resolve interobserver differences in lung pathology. Spectral histopathology is based on the detection of changes in biochemical composition, rather than morphologic features, and is therefore more akin to methods such as matrix-assisted laser desorption ionization time-of-flight mass spectrometry imaging. Both matrix-assisted laser desorption ionization time-of-flight mass spectrometry and SHP imaging modalities demonstrate that changes in tissue morphologic features observed in classical pathology are accompanied by, and may be correlated to, changes in the biochemical composition at the cellular level. Thus, these imaging methods provide novel insight into biochemical changes due to disease.
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Affiliation(s)
- Ali Akalin
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
| | - Ayşegül Ergin
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
| | - Stanley Remiszewski
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
| | - Xinying Mu
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
| | - Dan Raz
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
| | - Max Diem
- From the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem)
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2
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Chrabaszcz K, Jasztal A, Smęda M, Zieliński B, Blat A, Diem M, Chlopicki S, Malek K, Marzec KM. Label-free FTIR spectroscopy detects and visualizes the early stage of pulmonary micrometastasis seeded from breast carcinoma. Biochim Biophys Acta Mol Basis Dis 2018; 1864:3574-3584. [DOI: 10.1016/j.bbadis.2018.08.022] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 08/06/2018] [Accepted: 08/17/2018] [Indexed: 12/18/2022]
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3
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Kucuk Baloglu F, Baloglu O, Heise S, Brockmann G, Severcan F. Triglyceride dependent differentiation of obesity in adipose tissues by FTIR spectroscopy coupled with chemometrics. JOURNAL OF BIOPHOTONICS 2017; 10:1345-1355. [PMID: 28128535 DOI: 10.1002/jbio.201600223] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 10/28/2016] [Accepted: 12/23/2016] [Indexed: 06/06/2023]
Abstract
The excess deposition of triglycerides in adipose tissue is the main reason of obesity and causes excess release of fatty acids to the circulatory system resulting in obesity and insulin resistance. Body mass index and waist circumference are not precise measure of obesity and obesity related metabolic diseases. Therefore, in the current study, it was aimed to propose triglyceride bands located at 1770-1720 cm-1 spectral region as a more sensitive obesity related biomarker using the diagnostic potential of Fourier Transform Infrared (FTIR) spectroscopy in subcutaneous (SCAT) and visceral (VAT) adipose tissues. The adipose tissue samples were obtained from 10 weeks old male control (DBA/2J) (n = 6) and four different obese BFMI mice lines (n = 6 per group). FTIR spectroscopy coupled with hierarchical cluster analysis (HCA) and principal component analysis (PCA) was applied to the spectra of triglyceride bands as a diagnostic tool in the discrimination of the samples. Successful discrimination of the obese, obesity related insulin resistant and control groups were achieved with high sensitivity and specificity. The results revealed the power of FTIR spectroscopy coupled with chemometric approaches in internal diagnosis of abdominal obesity based on the spectral differences in the triglyceride region that can be used as a spectral marker.
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Affiliation(s)
- Fatma Kucuk Baloglu
- Department of Biological Sciences, Middle East Technical University, 06531, Ankara, Turkey
| | - Onur Baloglu
- Department of Biological Sciences, Middle East Technical University, 06531, Ankara, Turkey
| | - Sebastian Heise
- Department of Breeding Biology and Molecular Genetics, Humboldt Universitatzu Berlin, Berlin, Germany
| | - Gudrun Brockmann
- Department of Breeding Biology and Molecular Genetics, Humboldt Universitatzu Berlin, Berlin, Germany
| | - Feride Severcan
- Department of Biological Sciences, Middle East Technical University, 06531, Ankara, Turkey
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4
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Pounder FN, Reddy RK, Bhargava R. Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging. Faraday Discuss 2016; 187:43-68. [PMID: 27095431 PMCID: PMC5515302 DOI: 10.1039/c5fd00199d] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Breast cancer screening provides sensitive tumor identification, but low specificity implies that a vast majority of biopsies are not ultimately diagnosed as cancer. Automated techniques to evaluate biopsies can prevent errors, reduce pathologist workload and provide objective analysis. Fourier transform infrared (FT-IR) spectroscopic imaging provides both molecular signatures and spatial information that may be applicable for pathology. Here, we utilize both the spectral and spatial information to develop a combined classifier that provides rapid tissue assessment. First, we evaluated the potential of IR imaging to provide a diagnosis using spectral data alone. While highly accurate histologic [epithelium, stroma] recognition could be achieved, the same was not possible for disease [cancer, no-cancer] due to the diversity of spectral signals. Hence, we employed spatial data, developing and evaluating increasingly complex models, to detect cancers. Sub-mm tumors could be very confidently predicted as indicated by the quantitative measurement of accuracy via receiver operating characteristic (ROC) curve analyses. The developed protocol was validated with a small set and statistical performance used to develop a model that predicts study design for a large scale, definitive validation. The results of evaluation on different instruments, at higher noise levels, under a coarser spectral resolution and two sampling modes [transmission and transflection], indicate that the protocol is highly accurate under a variety of conditions. The study paves the way to validating IR imaging for rapid breast tumor detection, its statistical validation and potential directions for optimization of the speed and sampling for clinical deployment.
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Affiliation(s)
- F Nell Pounder
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
| | - Rohith K Reddy
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
| | - Rohit Bhargava
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. and Departments of Chemical & Biomolecular Engineering, Electrical & Computer Engineering, Mechanical Science & Engineering and Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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5
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Nallala J, Lloyd GR, Shepherd N, Stone N. High-resolution FTIR imaging of colon tissues for elucidation of individual cellular and histopathological features. Analyst 2016; 141:630-9. [DOI: 10.1039/c5an01871d] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Comparison of spectral-histopathological features of a colon tissue measured using a conventional (5.5 μm × 5.5 μm, left) and a high-magnification (1.1 μm × 1.1 μm, right) FTIR imaging system with respect to HE stained tissue (middle).
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Affiliation(s)
| | - Gavin Rhys Lloyd
- Biophotonics Research Unit
- Gloucestershire Royal Hospital
- Gloucester
- UK
| | - Neil Shepherd
- Department of Pathology
- Gloucestershire Hospitals NHS Foundation Trust
- Gloucester
- UK
| | - Nick Stone
- Biomedical Physics
- School of Physics
- University of Exeter
- UK
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6
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Verdonck M, Garaud S, Duvillier H, Willard-Gallo K, Goormaghtigh E. Label-free phenotyping of peripheral blood lymphocytes by infrared imaging. Analyst 2015; 140:2247-56. [PMID: 25516910 DOI: 10.1039/c4an01855a] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
It is now widely accepted that the immune microenvironment of tumors and more precisely Tumor Infiltrating Lymphocytes (TIL) play an important role in cancer development and outcome. TILs are considered to be important prognostic and predictive factors based on a growing body of clinical evidence; however, their presence at the tumor site is not currently assessed routinely. FTIR (Fourier transform infrared) imaging has proven it has value in studying a range of tumors, particularly for characterizing tumor cells. Currently, very little is known about the potential for FTIR imaging to characterize TIL. The present proof of concept study investigates the ability of FTIR imaging to identify the principal lymphocyte subpopulations present in human peripheral blood (PB). A negative cell isolation method was employed to select pure, label-free, helper T cells (CD4(+)), cytotoxic T cells (CD8(+)) and B cells (CD19(+)) from six healthy donors PB by Fluorescence Activated Cell Sorting (FACS). Cells were centrifuged onto Barium Fluoride windows and ten infrared images were recorded for each lymphocyte subpopulation from all six donors. After spectral pre-treatment, statistical analyses were performed. Unsupervised Principal Component Analyses (PCA) revealed that in the absence of donor variability, CD4(+) T cells, CD8(+) T cells and B cells each display distinct IR spectral features. Supervised Partial Least Square Discriminant Analyses (PLS-DA) demonstrated that the differences between the three lymphocyte subpopulations are reflected in their IR spectra, permitting their individual identification even when significant donor variability is present. Our results also show that a distinct spectral signature is associated with antibody binding. To our knowledge this is the first study reporting that FTIR imaging can effectively identify T and B lymphocytes and differentiate helper T cells from cytotoxic T cells. This proof of concept study demonstrates that FTIR imaging is a reliable tool for the identification of lymphocyte subpopulations and has the potential for use in characterizing TIL.
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Affiliation(s)
- M Verdonck
- Laboratory for the Structure and Function of Biological Membranes, Center for Structural Biology and Bioinformatics, Université Libre de Bruxelles, Campus Plaine, Bd du Triomphe 2, CP206/02, B1050 Brussels, Belgium.
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7
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Leslie LS, Wrobel TP, Mayerich D, Bindra S, Emmadi R, Bhargava R. High definition infrared spectroscopic imaging for lymph node histopathology. PLoS One 2015; 10:e0127238. [PMID: 26039216 PMCID: PMC4454651 DOI: 10.1371/journal.pone.0127238] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 04/14/2015] [Indexed: 11/19/2022] Open
Abstract
Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.
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Affiliation(s)
- L. Suzanne Leslie
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Tomasz P. Wrobel
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - David Mayerich
- Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, United States America
| | - Snehal Bindra
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Rajyasree Emmadi
- Department of Pathology, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Rohit Bhargava
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Chemistry, University of Illinois at Urbana-Champaign, Illinois, United States of America
- * E-mail:
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8
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Smolina M, Goormaghtigh E. Infrared imaging of MDA-MB-231 breast cancer cell line phenotypes in 2D and 3D cultures. Analyst 2015; 140:2336-43. [DOI: 10.1039/c4an01833h] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Breast cancer cell lines in 2D (top) and 3D (bottom) culture: H&H, unstained bright field, and IR images.
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Affiliation(s)
- Margarita Smolina
- Laboratory for the Structure and Function of Biological Membranes
- Center for Structural Biology and Bioinformatics
- Université Libre de Bruxelles (ULB)
- B-1050 Brussels
- Belgium
| | - Erik Goormaghtigh
- Laboratory for the Structure and Function of Biological Membranes
- Center for Structural Biology and Bioinformatics
- Université Libre de Bruxelles (ULB)
- B-1050 Brussels
- Belgium
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9
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Diem M, Mazur A, Lenau K, Schubert J, Bird B, Miljković M, Krafft C, Popp J. Molecular pathology via IR and Raman spectral imaging. JOURNAL OF BIOPHOTONICS 2013; 6:855-86. [PMID: 24311233 DOI: 10.1002/jbio.201300131] [Citation(s) in RCA: 126] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Accepted: 09/03/2013] [Indexed: 05/21/2023]
Abstract
During the last 15 years, vibrational spectroscopic methods have been developed that can be viewed as molecular pathology methods that depend on sampling the entire genome, proteome and metabolome of cells and tissues, rather than probing for the presence of selected markers. First, this review introduces the background and fundamentals of the spectroscopies underlying the new methodologies, namely infrared and Raman spectroscopy. Then, results are presented in the context of spectral histopathology of tissues for detection of metastases in lymph nodes, squamous cell carcinoma, adenocarcinomas, brain tumors and brain metastases. Results from spectral cytopathology of cells are discussed for screening of oral and cervical mucosa, and circulating tumor cells. It is concluded that infrared and Raman spectroscopy can complement histopathology and reveal information that is available in classical methods only by costly and time-consuming steps such as immunohistochemistry, polymerase chain reaction or gene arrays. Due to the inherent sensitivity toward changes in the bio-molecular composition of different cell and tissue types, vibrational spectroscopy can even provide information that is in some cases superior to that of any one of the conventional techniques.
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Affiliation(s)
- Max Diem
- Laboratory for Spectral Diagnosis LSpD, Department of Chemistry & Chemical Biology, Northeastern University, Boston, MA 02115, USA
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10
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Hughes C, Iqbal-Wahid J, Brown M, Shanks JH, Eustace A, Denley H, Hoskin PJ, West C, Clarke NW, Gardner P. FTIR microspectroscopy of selected rare diverse sub-variants of carcinoma of the urinary bladder. JOURNAL OF BIOPHOTONICS 2013; 6:73-87. [PMID: 23125109 DOI: 10.1002/jbio.201200126] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2012] [Revised: 10/01/2012] [Accepted: 10/01/2012] [Indexed: 06/01/2023]
Abstract
Urothelial carcinomas of the bladder are a heterogeneous group of tumours, although some histological sub-variants are rare and sparsely reported in the literature. Diagnosis of sub-variants from conventional urothelial carcinoma can be challenging, as they may mimic the morphology of other malignancies or benign tumours and therefore their distinction is important. For the first time, the spectral pathology of some of these sub-variants has been documented by infrared microspectroscopy and an attempt made to profile their biochemistry. It is important not only to identify and separate the cancer-associated epithelial tissue spectra from common tissue features such as stroma or blood, but also to detect the signatures of tumour sub-variants. As shown, their spectroscopic signals can change dramatically as a consequence of differentiation. Example cases are discussed and compared with histological evaluations.
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Affiliation(s)
- Caryn Hughes
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
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11
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Pereira TM, Zezell DM, Bird B, Miljković M, Diem M. The characterization of normal thyroid tissue by micro-FTIR spectroscopy. Analyst 2013; 138:7094-100. [DOI: 10.1039/c3an00296a] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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12
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Bird B, Miljković MS, Remiszewski S, Akalin A, Kon M, Diem M. Infrared spectral histopathology (SHP): a novel diagnostic tool for the accurate classification of lung cancer. J Transl Med 2012; 92:1358-73. [PMID: 22751349 DOI: 10.1038/labinvest.2012.101] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
We report results of a study utilizing a recently developed tissue diagnostic method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples from a tissue microarray. The spectral diagnostic method allows reproducible and objective diagnosis of unstained tissue sections. This is accomplished by acquiring infrared hyperspectral data sets containing thousands of spectra, each collected from tissue pixels about 6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis, which reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology (SHP) is presented, which suggests SHP can achieve levels of diagnostic accuracy that is comparable to that of multi-panel immunohistochemistry.
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Affiliation(s)
- Benjamin Bird
- Laboratory for Spectral Diagnosis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
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13
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Einenkel J, Braumann UD, Steller W, Binder H, Horn LC. Suitability of infrared microspectroscopic imaging for histopathology of the uterine cervix. Histopathology 2012; 60:1084-98. [DOI: 10.1111/j.1365-2559.2011.04140.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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14
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Applications of Infrared and Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics: Present Status and Future Promises. ACTA ACUST UNITED AC 2012. [DOI: 10.1155/2012/848360] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This paper summarizes the progress achieved over the past fifteen years in applying vibrational (Raman and IR) spectroscopy to problems of medical diagnostics and cellular biology. During this time, a number of research groups have verified the enormous information content of vibrational spectra; in fact, genomic, proteomic, and metabolomic information can be deduced by decoding the observed vibrational spectra. This decoding process is aided enormously by the availability of high-power computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared microspectral data has rendered practical the collection of images based solely on spectral data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational biological and biomedical arenas.
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15
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Riber-Hansen R, Vainer B, Steiniche T. Digital image analysis: a review of reproducibility, stability and basic requirements for optimal results. APMIS 2011; 120:276-89. [PMID: 22429210 DOI: 10.1111/j.1600-0463.2011.02854.x] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides optimized for light microscopy and the human eye. With improved technical methods and the acknowledgement that computerized readings are different from analysis by human eye, recognition has been achieved that to really empower DIA, histological slides must be optimized for the digital 'eye', with reproducible results correlating with clinical findings. In this review, we focus on the basic expectations and requirements for DIA to gain wider use in histopathological research and diagnostics. With a reference to studies that specifically compare DIA with conventional methods, this review discusses reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques.
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16
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Bird B, Miljković M, Laver N, Diem M. Spectral Detection of Micro-Metastases and Individual Metastatic Cells in Lymph Node Histology. Technol Cancer Res Treat 2011; 10:135-44. [DOI: 10.7785/tcrt.2012.500188] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The detection of micro-metastases and individual metastatic cells in lymph node tissue by spectral methods is summarized. These methods are based on instrument-based acquisition of thousands of infrared spectra of individual tissue pixels from the tissue section, and analysis of the resulting spectral hypercube by multivariate algorithms. The method of infrared image acquisition, followed by multivariate analysis, is henceforth referred to as Spectral Histopathology (SHP). SHP produces pseudo-color images of tissue sections which reveal details that compare very favorably with images collected from hematoxylin/eosin (H & E) stained tissues in that the same tissue structures are detected. However, the infrared results are based on objective and reproducible measurements and do not depend on subjective interpretation. One of the major topics of this paper is the comparison of spectral patterns observed for the same cancer type from different patients. While this is easy in some tissue types, we found it to be difficult in tissues of very different cellularity, or tissue sections that exhibit high levels of inflammatory response. In both cases, spectral quality will be compromised due to confounding effects resulting from scattering effects. The correction of these effects now permits the direct comparison of different patient samples, and paves the way for diagnostic algorithms for cancer detection to be developed.
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Affiliation(s)
- B. Bird
- Laboratory for Spectral Diagnosis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115 USA
| | - M. Miljković
- Laboratory for Spectral Diagnosis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115 USA
| | - N. Laver
- Department of Pathology, Tufts Medical Center, Boston, MA 02111 USA
| | - M. Diem
- Laboratory for Spectral Diagnosis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115 USA
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17
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Severcan F, Bozkurt O, Gurbanov R, Gorgulu G. FT-IR spectroscopy in diagnosis of diabetes in rat animal model. JOURNAL OF BIOPHOTONICS 2010; 3:621-631. [PMID: 20575104 DOI: 10.1002/jbio.201000016] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
In recent years, Fourier Transform Infrared (FT-IR) spectroscopy has had an increasingly important role in the field of pathology and diagnosis of disease states. In the current study, FT-IR spectroscopy together with cluster analysis were used as a diagnostic tool in the discrimination of diabetic samples from control ones in rat kidney plasma membrane apical sides (brush-border membranes), liver microsomal membranes and Extensor digitorum longus (EDL) and Soleus (SOL) skeletal muscle tissues. A variety of alterations in the spectral parameters, such as frequency and signal intensity/area was observed in diabetic tissues and membranes compared to the control samples. Based on these spectral variations, using cluster analysis successful differentiation between diabetic and control groups was obtained in different spectral regions. The results of this current study further revealed the power and sensitivity of FT-IR spectroscopy in precise and automated diagnosis of diabetes.
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Affiliation(s)
- Feride Severcan
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey.
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18
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Bird B, Miljković M, Diem M. Two step resonant Mie scattering correction of infrared micro-spectral data: human lymph node tissue. JOURNAL OF BIOPHOTONICS 2010; 3:597-608. [PMID: 20437419 DOI: 10.1002/jbio.201000024] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
In this manuscript, we report the application of EMSC to correct infrared micro-spectral data recorded from tissue that describe resonant Mie scattering contributions. Small breast micro-metastases previously undetectable using the raw measured spectra were provided clear contrast from the surrounding tissue after signal correction. The technique also proved transferrable, successfully correcting imaging data sets recorded from multiple patients. It is envisaged more robust methods of supervised analysis can now be constructed to automatically classify and diagnose tissue spectra.
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Affiliation(s)
- Benjamin Bird
- Chemical Biology Department, Northeastern University, Boston, MA 02115, USA.
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Diem M, Papamarkakis K, Schubert J, Bird B, Romeo MJ, Miljković M. The infrared spectral signatures of disease: extracting the distinguishing spectral features between normal and diseased states. APPLIED SPECTROSCOPY 2009; 63:307A-318A. [PMID: 19891826 DOI: 10.1366/000370209789806894] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Affiliation(s)
- Max Diem
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
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Bird B, Bedrossian K, Laver N, Miljković M, Romeo MJ, Diem M. Detection of breast micro-metastases in axillary lymph nodes by infrared micro-spectral imaging. Analyst 2009; 134:1067-76. [PMID: 19475131 DOI: 10.1039/b821166c] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We report the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes and detect metastatic breast cancer cells. The acquisition of spectral data from tissue embedded in paraffin provided spectra free of dispersive artefacts that may be observed for infrared microscopic measurements using a 'reflection/absorption' methodology. As a consequence, superior tissue classification and identification of cellular abnormality unattainable for deparaffinised tissue was achieved.
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Affiliation(s)
- Benjamin Bird
- Laboratory for Spectral Diagnosis (LSpD), Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, USA.
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