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Tiwari S, Raman J, Reddy V, Ghetler A, Tella RP, Han Y, Moon CR, Hoke CD, Bhargava R. Towards Translation of Discrete Frequency Infrared Spectroscopic Imaging for Digital Histopathology of Clinical Biopsy Samples. Anal Chem 2016; 88:10183-10190. [PMID: 27626947 DOI: 10.1021/acs.analchem.6b02754] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Fourier transform infrared (FT-IR) spectroscopic imaging has been widely tested as a tool for stainless digital histology of biomedical specimens, including for the identification of infiltration and fibrosis in endomyocardial biopsy samples to assess transplant rejection. A major barrier in clinical translation has been the slow speed of imaging. To address this need, we tested and report here the viability of using high speed discrete frequency infrared (DFIR) imaging to obtain stain-free biochemical imaging in cardiovascular samples collected from patients. Images obtained by this method were classified with high accuracy by a Bayesian classification algorithm trained on FT-IR imaging data as well as on DFIR data. A single spectral feature correlated with instances of fibrosis, as identified by the pathologist, highlights the advantage of the DFIR imaging approach for rapid detection. The speed of digital pathologic recognition was at least 16 times faster than the fastest FT-IR imaging instrument. These results indicate that a fast, on-site identification of fibrosis using IR imaging has potential for real time assistance during surgeries. Further, the work describes development and applications of supervised classifiers on DFIR imaging data, comparing classifiers developed on FT-IR and DFIR imaging modalities and identifying specific spectral features for accurate identification of fibrosis. This addresses a topic of much debate on the use of training data and cross-modality validity of IR measurements. Together, the work is a step toward addressing a clinical diagnostic need at acquisition time scales that make IR imaging technology practical for medical use.
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Affiliation(s)
- Saumya Tiwari
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States
| | - Jai Raman
- Knight Cardiovascular Institute, Oregon Health & Science University , 3181 SW Sam Jackson Park Road, Portland, Oregon 97201, United States
| | - Vijaya Reddy
- Department of Pathology, Rush University Medical Center , 1725 West Harrison Street, Chicago, Illinois 60612, United States
| | - Andrew Ghetler
- California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States
| | - Richard P Tella
- California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States
| | - Yang Han
- California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States
| | - Christopher R Moon
- California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States
| | - Charles D Hoke
- California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States
| | - Rohit Bhargava
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.,Departments of Chemistry, Mechanical Science and Engineering, Chemical and Biomolecular Engineering, Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States
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Krafft C, Shapoval L, Sobottka SB, Schackert G, Salzer R. Identification of Primary Tumors of Brain Metastases by Infrared Spectroscopic Imaging and Linear Discriminant Analysis. Technol Cancer Res Treat 2016; 5:291-8. [PMID: 16700626 DOI: 10.1177/153303460600500311] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
This study applies infrared (IR) spectroscopy to distinguish normal brain tissue from brain metastases and to determine the primary tumor of four frequent brain metastases such as lung cancer, colorectal cancer, breast cancer, and renal cell carcinoma. Standard methods sometimes fail to identify the origin of brain metastases. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the primary tumor of a brain metastasis. IR spectroscopic images were recorded by a FTIR spectrometer equipped with a macro sample chamber and coupled to a focal plane array detector. Unsupervised cluster analysis of IR images revealed variances within each sample and between samples of the same tissue type. Cluster averaged IR spectra of tissue classes with known diagnoses were selected to develop a metric with eight variables. These data trained a supervised classification model based on linear discriminant analysis that was used to identify the origin of 20 cryosections including one brain metastasis with an unknown primary tumor.
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Affiliation(s)
- Christoph Krafft
- Institute for Analytical Chemistry, Dresden University of Technology, 01062 Dresden, Germany.
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3
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Wald N, Bordry N, Foukas PG, Speiser DE, Goormaghtigh E. Identification of melanoma cells and lymphocyte subpopulations in lymph node metastases by FTIR imaging histopathology. BIOCHIMICA ET BIOPHYSICA ACTA 2016; 1862:202-12. [PMID: 26612718 DOI: 10.1016/j.bbadis.2015.11.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2015] [Revised: 10/28/2015] [Accepted: 11/17/2015] [Indexed: 12/31/2022]
Abstract
While early stages of melanoma are usually cured by surgery, metastatic melanomas are difficult to treat because the widely available options have low response rates. Careful and precise diagnosis and staging are essential to determine patient's risk and to select appropriate treatments. Fortunately, the recent progress in immunotherapy is very encouraging. In this context, it is important to characterize the intratumoral infiltration of immune cells in each patient, which is however not done routinely due to the lack of standardized methods. In this study, we used Fourier transform infrared (FTIR) imaging combined with multivariate statistical analyses to investigate non-metastatic and metastatic lymph nodes from melanoma patients. Our results show that the different cell types have different infrared spectral features allowing automated identification of these cell types. High recognition rates were obtained using a supervised partial least square discriminant analysis (PLS-DA) model. Melanoma cells were recognized with 87.1% sensitivity and 85.7% specificity, showing that FTIR spectroscopy has similar detection power as immunohistochemistry. Besides, FTIR imaging could also distinguish lymphocyte subpopulations (B and T cells). Finally, we investigated the changes in lymphocytes due to the presence of metastases. Interestingly, specific features of spectra of lymphocytes present in metastatic or tumor-free lymph nodes could be evidenced by PCA. A PLS-DA model was capable of predicting whether lymphocytes originated from invaded or non-invaded lymph nodes. These data demonstrate that FTIR imaging is capable to distinguish known and also novel biological features in human tissues, with potential practical relevance for histopathological diagnosis and biomarker assessment.
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Affiliation(s)
- N Wald
- Laboratory for the Structure and Function of Biological Membranes, Center for Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.
| | - N Bordry
- Ludwig Center for Cancer Research, Department of Oncology CHUV, University of Lausanne, Lausanne, Switzerland
| | - P G Foukas
- Ludwig Center for Cancer Research, Department of Oncology CHUV, University of Lausanne, Lausanne, Switzerland
| | - D E Speiser
- Ludwig Center for Cancer Research, Department of Oncology CHUV, University of Lausanne, Lausanne, Switzerland
| | - E Goormaghtigh
- Laboratory for the Structure and Function of Biological Membranes, Center for Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
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Staniszewska-Slezak E, Fedorowicz A, Kramkowski K, Leszczynska A, Chlopicki S, Baranska M, Malek K. Plasma biomarkers of pulmonary hypertension identified by Fourier transform infrared spectroscopy and principal component analysis. Analyst 2015; 140:2273-9. [PMID: 25599976 DOI: 10.1039/c4an01864h] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The main goal of this study was to find specific plasma spectral markers associated with pulmonary arterial hypertension (PAH) induced by monocrotaline injection in rats. FTIR was used to monitor biochemical changes in plasma caused by PAH as compared with the systemic hypertension induced by partial ligation on the left artery and with the control group. Both pathologies, systemic and pulmonary hypertension, induced a unique response in the biochemical content of plasma, mainly related to the composition and secondary structure of plasma proteins. For PAH, β-pleated sheet components of plasma proteins were identified whereas the protein composition in systemic hypertension was dominated by unordered structures. In addition, a higher concentration of tyrosine-rich proteins was found in plasma in PAH than in systemic hypertension. The differences between both pathologies were identified also in terms of lipid composition/metabolism as well as in the content of RNA and glucose, suggesting that lipid peroxidation appears upon pulmonary hypertension development. In summary, this work demonstrates that FTIR spectroscopy supported by principal component analysis (PCA) has the potential to become a fast and non-destructive method for biochemical characterization of plasma that consequently could have a diagnostic significance in pulmonary hypertension.
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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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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: 42] [Impact Index Per Article: 4.7] [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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7
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Combining multiset resolution and segmentation for hyperspectral image analysis of biological tissues. Anal Chim Acta 2015; 881:24-36. [DOI: 10.1016/j.aca.2015.04.053] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Revised: 04/24/2015] [Accepted: 04/28/2015] [Indexed: 11/19/2022]
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Tiwari S, Reddy VB, Bhargava R, Raman J. Computational chemical imaging for cardiovascular pathology: chemical microscopic imaging accurately determines cardiac transplant rejection. PLoS One 2015; 10:e0125183. [PMID: 25932912 PMCID: PMC4416885 DOI: 10.1371/journal.pone.0125183] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Accepted: 03/10/2015] [Indexed: 02/06/2023] Open
Abstract
Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR) spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients’ biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.
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Affiliation(s)
- Saumya Tiwari
- Department of Bioengineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, Urbana, Illinois, 61801, United States of America
| | - Vijaya B. Reddy
- Department of Pathology, Rush University Medical Center, 1725 West Harrison St, Chicago, Illinois, 60612, United States of America
| | - Rohit Bhargava
- Department of Bioengineering, Chemistry, Mechanical Science and Engineering, Chemical and Biomolecular Engineering, Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology and University of Illinois Cancer Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801, United States of America
| | - Jaishankar Raman
- Cardiac Surgery, Advanced Heart Failure Transplantation & Mechanical Circulatory Support, Rush University Medical Center, 1725 West Harrison St, Chicago, Illinois, 60612, United States of America
- * E-mail:
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Wald N, Legat A, Meyer C, Speiser DE, Goormaghtigh E. An infrared spectral signature of human lymphocyte subpopulations from peripheral blood. Analyst 2015; 140:2257-65. [PMID: 25553786 DOI: 10.1039/c4an02247e] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Metastatic melanomas are frequently refractory to most adjuvant therapies such as chemotherapies and radiotherapies. Recently, immunotherapies have shown good results in the treatment of some metastatic melanomas. Immune cell infiltration in the tumor has been associated with successful immunotherapy. More generally, tumor infiltrating lymphocytes (TILs) in the primary tumor and in metastases of melanoma patients have been demonstrated to correlate positively with favorable clinical outcomes. Altogether, these findings suggest the importance of being able to identify, quantify and characterize immune infiltration at the tumor site for a better diagnostic and treatment choice. In this paper, we used Fourier Transform Infrared (FTIR) imaging to identify and quantify different subpopulations of T cells: the cytotoxic T cells (CD8+), the helper T cells (CD4+) and the regulatory T cells (T reg). As a proof of concept, we investigated pure populations isolated from human peripheral blood from 6 healthy donors. These subpopulations were isolated from blood samples by magnetic labeling and purities were assessed by Fluorescence Activated Cell Sorting (FACS). The results presented here show that Fourier Transform Infrared (FTIR) imaging followed by supervised Partial Least Square Discriminant Analysis (PLS-DA) allows an accurate identification of CD4+ T cells and CD8+ T cells (>86%). We then developed a PLS regression allowing the quantification of T reg in a different mix of immune cells (e.g. Peripheral Blood Mononuclear Cells (PBMCs)). Altogether, these results demonstrate the sensitivity of infrared imaging to detect the low biological variability observed in T cell subpopulations.
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Affiliation(s)
- N Wald
- Center for Structural Biology and Bioinformatics, Laboratory for the Structure and Function of Biological Membranes; Université Libre de Bruxelles, Campus Plaine, Bld du Triomphe 2, CP206/2, B1050 Brussels, Belgium.
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10
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Benard A, Desmedt C, Smolina M, Szternfeld P, Verdonck M, Rouas G, Kheddoumi N, Rothé F, Larsimont D, Sotiriou C, Goormaghtigh E. Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment. Analyst 2014; 139:1044-56. [PMID: 24418921 DOI: 10.1039/c3an01454a] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Current evaluation of histological sections of breast cancer samples remains unsatisfactory. The search for new predictive and prognostic factors is ongoing. Infrared spectroscopy and its potential to probe tissues and cells at the molecular level without requirement for contrast agents could be an attractive tool for clinical and diagnostic analysis of breast cancer. In this study, we report the successful application of FTIR (Fourier transform infrared) imaging for breast tissue component characterization. We show that specific FTIR spectral signatures can be assigned to the major tissue components of breast tumor samples. We demonstrate that a tissue component classifier can be built based on a spectral database of well-annotated tissues and successfully validated on independent breast samples. We also demonstrate that spectral features can reveal subtle differences within a tissue component, capturing for instance lymphocytic and stromal activation. By investigating in parallel lymph nodes, tonsils and wound healing tissues, we prove the uniqueness of the signature of both lymphocytic infiltrate and tumor microenvironment in the breast disease context. Finally, we demonstrate that the biochemical information reflected in the epithelial spectra might be clinically relevant for the grading purpose, suggesting potential to improve breast cancer management in the future.
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Affiliation(s)
- Audrey Benard
- Laboratory for the Structure and Function of Biological Membranes, Center for Structural Biology and Bioinformatics, Université Libre de Bruxelles (ULB), Bld du Triomphe 2, CP206/2, B1050 Brussels, Belgium.
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11
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Hackett MJ, McQuillan JA, El-Assaad F, Aitken JB, Levina A, Cohen DD, Siegele R, Carter EA, Grau GE, Hunt NH, Lay PA. Chemical alterations to murine brain tissue induced by formalin fixation: implications for biospectroscopic imaging and mapping studies of disease pathogenesis. Analyst 2011; 136:2941-52. [DOI: 10.1039/c0an00269k] [Citation(s) in RCA: 143] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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12
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Vahlsing T, Damm U, Kondepati VR, Leonhardt S, Brendel MD, Wood BR, Heise HM. Transmission infrared spectroscopy of whole blood--complications for quantitative analysis from leucocyte adhesion during continuous monitoring. JOURNAL OF BIOPHOTONICS 2010; 3:567-578. [PMID: 20449832 DOI: 10.1002/jbio.201000021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Infrared spectroscopy has been applied to analyse glucose and cellular components in whole blood with the aim of developing an online clinical diagnostic and monitoring modality. Leucocyte adsorption onto the CaF(2) windows was observed over a period of several hours under continuous blood flow using a transmission cell of 30 mum path length. This build-up of cellular material on the windows is responsible for diminishing the sample path length under the flow conditions chosen. The adsorption dynamics have been characterised and their impact on glucose monitoring is reported. For short-term monitoring (<2 hours) a standard error of prediction of 11 mg/dL with human citrated blood samples from three different subjects was achieved. Furthermore, the leucocyte build-up was also reported for porcine EDTA blood monitoring. Consequences and testing opportunities with regard to the first stages in the immune cell reaction to the exposure of body-foreign materials to anticoagulated whole blood are discussed.
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Affiliation(s)
- Thorsten Vahlsing
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
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Raman Spectroscopy: A Tool for Tissue Engineering. EMERGING RAMAN APPLICATIONS AND TECHNIQUES IN BIOMEDICAL AND PHARMACEUTICAL FIELDS 2010. [DOI: 10.1007/978-3-642-02649-2_18] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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14
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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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15
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Steiner G, Küchler S, Hermann A, Koch E, Salzer R, Schackert G, Kirsch M. Rapid and label-free classification of human glioma cells by infrared spectroscopic imaging. Cytometry A 2008; 73A:1158-64. [DOI: 10.1002/cyto.a.20639] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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16
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Wang L, Mizaikoff B. Application of multivariate data-analysis techniques to biomedical diagnostics based on mid-infrared spectroscopy. Anal Bioanal Chem 2008; 391:1641-54. [PMID: 18379763 DOI: 10.1007/s00216-008-1989-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2008] [Revised: 02/14/2008] [Accepted: 02/18/2008] [Indexed: 10/22/2022]
Abstract
The objective of this contribution is to review the application of advanced multivariate data-analysis techniques in the field of mid-infrared (MIR) spectroscopic biomedical diagnosis. MIR spectroscopy is a powerful chemical analysis tool for detecting biomedically relevant constituents such as DNA/RNA, proteins, carbohydrates, lipids, etc., and even diseases or disease progression that may induce changes in the chemical composition or structure of biological systems including cells, tissues, and bio-fluids. However, MIR spectra of multiple constituents are usually characterized by strongly overlapping spectral features reflecting the complexity of biological samples. Consequently, MIR spectra of biological samples are frequently difficult to interpret by simple data-analysis techniques. Hence, with increasing complexity of the sample matrix more sophisticated mathematical and statistical data analysis routines are required for deconvoluting spectroscopic data and for providing useful results from information-rich spectroscopic signals. A large body of work relates to the combination of multivariate data-analysis techniques with MIR spectroscopy, and has been applied by a variety of research groups to biomedically relevant areas such as cancer detection and analysis, artery diseases, biomarkers, and other pathologies. The reported results indeed reveal a promising perspective for more widespread application of multivariate data analysis in assisting MIR spectroscopy as a screening or diagnostic tool in biomedical research and clinical studies. While the authors do not mean to ignore any relevant contributions to biomedical analysis across the entire electromagnetic spectrum, they confine the discussion in this contribution to the mid-infrared spectral range as a potentially very useful, yet underutilized frequency region. Selected representative examples without claiming completeness will demonstrate a range of biomedical diagnostic applications with particular emphasis on the advantageous interaction between multivariate data analysis and MIR spectroscopy.
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Affiliation(s)
- Liqun Wang
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332-0400, USA
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17
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Microimaging FT-IR of oral cavity tumours. Part III: Cells, inoculated tissues and human tissues. J Mol Struct 2007. [DOI: 10.1016/j.molstruc.2006.10.060] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Abstract
Over the last 15 years, infrared (IR) spectroscopy has developed into a novel and powerful biomedical tool that has multiple applications in the field of haematology. By revealing subtle alterations in both the conformation and concentration of key macromolecules, such as DNA, protein and lipids, IR spectroscopy has been employed to investigate multiple aspects of leucocyte physiology. IR spectroscopy has been used, for example, to diagnose and prognose leukaemia; to characterise differentiation and apoptotic processes; to predict drug sensitivity and resistance in leukaemic patients undergoing chemotherapy; to monitor the response of leucocytes to chemotherapy and to perform human leucocyte antigen matching for bone marrow transplant patients. Such studies have provided insight into pathogenic mechanisms underlying specific leucocyte disorders, especially leukaemia. While it is likely to be some considerable time before IR spectroscopy is sufficiently developed to displace the established technologies, IR spectroscopy has the potential to become a valuable analytic tool in basic and clinical haematology.
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Affiliation(s)
- Kan-Zhi Liu
- Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, MB, Canada.
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20
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Wessel E, Heinsohn G, Schmidt-Lewerkuehne H, Wittern KP, Rapp C, Siesler HW. Observation of a penetration depth gradient in attenuated total reflection fourier transform infrared spectroscopic imaging applications. APPLIED SPECTROSCOPY 2006; 60:1488-92. [PMID: 17217601 DOI: 10.1366/000370206779321391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Affiliation(s)
- Elke Wessel
- Beiersdorf AG, Research and Development, Unnastrasse 48, D-20253 Hamburg, Germany.
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Krafft C, Sobottka SB, Geiger KD, Schackert G, Salzer R. Classification of malignant gliomas by infrared spectroscopic imaging and linear discriminant analysis. Anal Bioanal Chem 2006; 387:1669-77. [PMID: 17103151 DOI: 10.1007/s00216-006-0892-5] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2006] [Revised: 09/25/2006] [Accepted: 10/02/2006] [Indexed: 10/23/2022]
Abstract
Infrared (IR) spectroscopy provides a sensitive molecular fingerprint for tissue without external markers. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. Infrared imaging spectrometers equipped with multi-channel detectors combine the spectral and spatial information. Tissue areas of 4 x 4 mm(2) can be analyzed within a few minutes in the macroscopic imaging mode. An approach is described to apply this methodology to human astrocytic gliomas, which are graded according to their malignancy from one to four. Multiple IR images of three tissue sections from one patient with a malignant glioma are acquired and assigned to the six classes normal brain tissue, astrocytoma grade II, astrocytoma grade III, glioblastoma multiforme grade IV, hemorrhage, and other tissue by a linear discriminant analysis model which was trained by data from a single-channel detector. Before the model is applied here, the spectra are shown to be virtually identical. The first specimen contained approximately 95% malignant glioma regions, that means astrocytoma grade III or glioblastoma. The smaller percentage of 12-34% malignant glioma in the second specimen is consistent with its location at the tumor periphery. The detection of less than 0.2% malignant glioma in the third specimen points to a location outside the tumor. The results were correlated with the cellularity of the tissue which was obtained from the histopathologic gold standard. Potential applications of IR spectroscopic imaging as a rapid tool to complement established diagnostic methods are discussed.
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Affiliation(s)
- Christoph Krafft
- Institute for Analytical Chemistry, Dresden University of Technology, 01062 Dresden, Germany.
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Krafft C, Shapoval L, Sobottka SB, Geiger KD, Schackert G, Salzer R. Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2006; 1758:883-91. [PMID: 16787638 DOI: 10.1016/j.bbamem.2006.05.001] [Citation(s) in RCA: 80] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2005] [Revised: 03/24/2006] [Accepted: 05/01/2006] [Indexed: 11/16/2022]
Abstract
Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.
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Affiliation(s)
- Christoph Krafft
- Institute for Analytical Chemistry, Dresden University of Technology, 01062 Dresden, Germany.
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Steller W, Einenkel J, Horn LC, Braumann UD, Binder H, Salzer R, Krafft C. Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging. Anal Bioanal Chem 2005; 384:145-54. [PMID: 16328253 DOI: 10.1007/s00216-005-0124-4] [Citation(s) in RCA: 53] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2005] [Revised: 08/18/2005] [Accepted: 09/19/2005] [Indexed: 10/25/2022]
Abstract
Infrared (IR) spectroscopic imaging coupled with microscopy has been used to investigate thin sections of cervix uteri encompassing normal tissue, precancerous structures, and squamous cell carcinoma. Methods for unsupervised distinction of tissue types based on IR spectroscopy were developed. One-hundred and twenty-two images of cervical tissue were recorded by an FTIR spectrometer with a 64x64 focal plane array detector. The 499,712 IR spectra obtained were grouped by an approach which used fuzzy C-means clustering followed by hierarchical cluster analysis. The resulting false color maps were correlated with the morphological characteristics of an adjacent section of hematoxylin and eosin-stained tissue. In the first step, cervical stroma, epithelium, inflammation, blood vessels, and mucus could be distinguished in IR images by analysis of the spectral fingerprint region (950-1480 cm(-1)). In the second step, analysis in the spectral window 1420-1480 cm(-1) enables, for the first time, IR spectroscopic distinction between the basal layer, dysplastic lesions and squamous cell carcinoma within a particular sample. The joint application of IR microspectroscopic imaging and multivariate spectral processing combines diffraction-limited lateral optical resolution on the single cell level with highly specific and sensitive spectral classification on the molecular level. Compared with previous reports our approach constitutes a significant progress in the development of optical molecular spectroscopic techniques toward an additional diagnostic tool for the early histopathological characterization of cervical cancer.
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Affiliation(s)
- Wolfram Steller
- Institute for Analytical Chemistry, Dresden University of Technology, 01062, Dresden, Germany
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