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Arceneaux JS, Brockman AA, Khurana R, Chalkley MBL, Geben LC, Krbanjevic A, Vestal M, Zafar M, Weatherspoon S, Mobley BC, Ess KC, Ihrie RA. Multiparameter quantitative analyses of diagnostic cells in brain tissues from tuberous sclerosis complex. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2024. [PMID: 38953209 DOI: 10.1002/cyto.b.22194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
The advent of high-dimensional imaging offers new opportunities to molecularly characterize diagnostic cells in disorders that have previously relied on histopathological definitions. One example case is found in tuberous sclerosis complex (TSC), a developmental disorder characterized by systemic growth of benign tumors. Within resected brain tissues from patients with TSC, detection of abnormally enlarged balloon cells (BCs) is pathognomonic for this disorder. Though BCs can be identified by an expert neuropathologist, little is known about the specificity and broad applicability of protein markers for these cells, complicating classification of proposed BCs identified in experimental models of this disorder. Here, we report the development of a customized machine learning pipeline (BAlloon IDENtifier; BAIDEN) that was trained to prospectively identify BCs in tissue sections using a histological stain compatible with high-dimensional cytometry. This approach was coupled to a custom 36-antibody panel and imaging mass cytometry (IMC) to explore the expression of multiple previously proposed BC marker proteins and develop a descriptor of BC features conserved across multiple tissue samples from patients with TSC. Here, we present a modular workflow encompassing BAIDEN, a custom antibody panel, a control sample microarray, and analysis pipelines-both open-source and in-house-and apply this workflow to understand the abundance, structure, and signaling activity of BCs as an example case of how high-dimensional imaging can be applied within human tissues.
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Affiliation(s)
- Jerome S Arceneaux
- Department of Biochemistry, Cancer Biology, Neuroscience, and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Asa A Brockman
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Rohit Khurana
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Mary-Bronwen L Chalkley
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Laura C Geben
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee, USA
| | - Aleksandar Krbanjevic
- Department of Pathology, Microbiology, & Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Matthew Vestal
- Duke University Children's Hospital and Health Center, Durham, North Carolina, USA
| | - Muhammad Zafar
- Duke University Children's Hospital and Health Center, Durham, North Carolina, USA
| | - Sarah Weatherspoon
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, Tennessee, USA
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Bret C Mobley
- Department of Pathology, Microbiology, & Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kevin C Ess
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Section of Child Neurology, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA
| | - Rebecca A Ihrie
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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2
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Abuh SO, Barbora A, Minnes R. Metastasis diagnosis using attenuated total reflection-Fourier transform infra-red (ATR-FTIR) spectroscopy. PLoS One 2024; 19:e0304071. [PMID: 38820279 PMCID: PMC11142428 DOI: 10.1371/journal.pone.0304071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 05/06/2024] [Indexed: 06/02/2024] Open
Abstract
The suitability of Fourier transform infrared spectroscopy as a metastasis prognostic tool has not been reported for some cancer types. Our main aim was to show spectroscopic differences between live un-preprocessed cancer cells of different metastatic levels. Spectra of four cancer cell pairs, including colon cancer (SW480, SW620); human melanoma (WM115, WM266.4); murine melanoma (B16F01, B16F10); and breast cancer (MCF7, MDA-MB-231); each pair having the same genetic background, but different metastatic level were analyzed in the regions 1400-1700 cm-1 and 3100-3500 cm-1 using Principal Component Analysis, curve fitting, multifractal dimension and receiver operating characteristic (ROC) curves. The results show spectral markers I1540/I1473, I1652/I1473, [Formula: see text], and multifractal dimension of the spectral images are significantly different for the cells based on their metastatic levels. ROC curve analysis showed good diagnostic performance of the spectral markers in separating cells based on metastatic degree, with areas under the ROC curves having 95% confidence interval lower limits greater than 0.5 for most instances. These spectral features can be important in predicting the probability of metastasis in primary tumors, providing useful guidance for treatment planning. Our markers are effective in differentiating metastatic levels without sample fixation or drying and therefore could be compactible for future use in in-vivo procedures involving spectroscopic cancer diagnosis.
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Affiliation(s)
- Samuel Onuh Abuh
- Faculty of Natural Sciences, Department of Physics, Ariel University, Ariel, Israel
| | - Ayan Barbora
- Faculty of Natural Sciences, Department of Physics, Ariel University, Ariel, Israel
| | - Refael Minnes
- Faculty of Natural Sciences, Department of Physics, Ariel University, Ariel, Israel
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3
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Félix MM, Tavares MV, Santos IP, Batista de Carvalho ALM, Batista de Carvalho LAE, Marques MPM. Cervical Squamous Cell Carcinoma Diagnosis by FTIR Microspectroscopy. Molecules 2024; 29:922. [PMID: 38474435 DOI: 10.3390/molecules29050922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/09/2024] [Accepted: 02/17/2024] [Indexed: 03/14/2024] Open
Abstract
Cervical cancer was considered the fourth most common cancer worldwide in 2020. In order to reduce mortality, an early diagnosis of the tumor is required. Currently, this type of cancer occurs mostly in developing countries due to the lack of vaccination and screening against the Human Papillomavirus. Thus, there is an urgent clinical need for new methods aiming at a reliable screening and an early diagnosis of precancerous and cancerous cervical lesions. Vibrational spectroscopy has provided very good results regarding the diagnosis of various tumors, particularly using Fourier transform infrared microspectroscopy, which has proved to be a promising complement to the currently used histopathological methods of cancer diagnosis. This spectroscopic technique was applied to the analysis of cryopreserved human cervical tissue samples, both squamous cell carcinoma (SCC) and non-cancer samples. A dedicated Support Vector Machine classification model was constructed in order to categorize the samples into either normal or malignant and was subsequently validated by cross-validation, with an accuracy higher than 90%.
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Affiliation(s)
- Maria M Félix
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Mariana V Tavares
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
- Gynaecology Department, Portuguese Oncology Institute of Porto, 4200-072 Porto, Portugal
| | - Inês P Santos
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Ana L M Batista de Carvalho
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Luís A E Batista de Carvalho
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Maria Paula M Marques
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
- Department of Life Sciences, Faculty of Science and Technology, University of Coimbra, 3000-456 Coimbra, Portugal
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4
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Maitra I, Morais CLM, Lima KMG, Ashton KM, Bury D, Date RS, Martin FL. Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma. J Pers Med 2023; 13:1277. [PMID: 37623527 PMCID: PMC10455976 DOI: 10.3390/jpm13081277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023] Open
Abstract
This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Camilo L. M. Morais
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
- Center for Education, Science and Technology of the Inhamuns Region, State University of Ceará, Tauá 63660-000, Brazil
| | - Kássio M. G. Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
| | - Katherine M. Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Danielle Bury
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
| | - Ravindra S. Date
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Francis L. Martin
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
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5
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Stec P, Dudała J, Wandzilak A, Wróbel P, Chmura Ł, Szczerbowska-Boruchowska M. Fourier transform infrared microspectroscopy analysis of ovarian cancerous tissues in paraffin and deparaffinized tissue samples. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 297:122717. [PMID: 37080053 DOI: 10.1016/j.saa.2023.122717] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/30/2023] [Accepted: 04/04/2023] [Indexed: 05/03/2023]
Abstract
Ovarian cancer is one of the deadliest cancers occurring in women. This is typically due to late diagnosis of the disease and difficult treatment. Infrared microspectroscopy is a complementary research method that can be helpful in the diagnosis of this disease, because it allows for the analysis of the tissues biomolecular composition. In this study, archival paraffin-embedded preparations of ovarian tissues, tumours and control, were used. However, the paraffin present in such specimens is a strong absorber of infrared radiation, which makes it impossible to reliably analyse the biomolecular composition of the sample. The solution to this problem is to deparaffinize the tissue before the analysis. However, the extend to which the paraffinization and deparaffinization processes influence the biomolecular composition of the tissues is unclear. Analysed tissues in the form of cores were placed in a paraffin micromatrix and FTIR measurements were performed. Then the samples were deparaffinized and the measurements were taken again. For both sets of samples (embedded in paraffin and deparaffinized) ratios of integrated peaks and massifs within the obtained spectra were calculated. The obtained ratios were compared for different types of diseased and healthy, control tissues. The Kruskal-Wallis test revealed statistically significant differences of the calculated ratios between most of the types of tissues. Random Forest models clearly showed that both samples in paraffin and deparaffinized retain enough information to classify the tissues reliably. The feature analysis revealed the most important feature for distinguishing between different types of samples, i.e. 1080 cm-1/1240 cm-1 ratio and lipid saturation for the samples embedded in paraffin and deparaffinized respectively. The study showed that the deparaffinization process leads to changes in the biomolecular composition of the analysed tissues. Despite this, classification of the tissues based on FTIR measurements remains possible.
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Affiliation(s)
- Patryk Stec
- Department of Medical Physics and Biophysics, AGH University of Science and Technology, Mickiewicza st. 30, 30-059 Cracow, Poland.
| | - Joanna Dudała
- Department of Medical Physics and Biophysics, AGH University of Science and Technology, Mickiewicza st. 30, 30-059 Cracow, Poland
| | - Aleksandra Wandzilak
- Department of Medical Physics and Biophysics, AGH University of Science and Technology, Mickiewicza st. 30, 30-059 Cracow, Poland
| | - Paweł Wróbel
- Department of Medical Physics and Biophysics, AGH University of Science and Technology, Mickiewicza st. 30, 30-059 Cracow, Poland
| | - Łukasz Chmura
- Chair and Department of Pathomorphology, Jagiellonian University Medical College, Grzegorzecka st. 16, 31-531 Cracow, Poland
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6
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Schiemer R, Furniss D, Phang S, Seddon AB, Atiomo W, Gajjar KB. Vibrational Biospectroscopy: An Alternative Approach to Endometrial Cancer Diagnosis and Screening. Int J Mol Sci 2022; 23:ijms23094859. [PMID: 35563249 PMCID: PMC9102412 DOI: 10.3390/ijms23094859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 01/27/2023] Open
Abstract
Endometrial cancer (EC) is the sixth most common cancer and the fourth leading cause of death among women worldwide. Early detection and treatment are associated with a favourable prognosis and reduction in mortality. Unlike other common cancers, however, screening strategies lack the required sensitivity, specificity and accuracy to be successfully implemented in clinical practice and current diagnostic approaches are invasive, costly and time consuming. Such limitations highlight the unmet need to develop diagnostic and screening alternatives for EC, which should be accurate, rapid, minimally invasive and cost-effective. Vibrational spectroscopic techniques, Mid-Infrared Absorption Spectroscopy and Raman, exploit the atomic vibrational absorption induced by interaction of light and a biological sample, to generate a unique spectral response: a “biochemical fingerprint”. These are non-destructive techniques and, combined with multivariate statistical analysis, have been shown over the last decade to provide discrimination between cancerous and healthy samples, demonstrating a promising role in both cancer screening and diagnosis. The aim of this review is to collate available evidence, in order to provide insight into the present status of the application of vibrational biospectroscopy in endometrial cancer diagnosis and screening, and to assess future prospects.
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Affiliation(s)
- Roberta Schiemer
- Division of Child Health, Obstetrics and Gynaecology, University of Nottingham, Nottingham NG5 1PB, UK;
- Correspondence:
| | - David Furniss
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - Sendy Phang
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - Angela B. Seddon
- Mid-Infrared Photonics Group, George Green Institute for Electromagnetics Research, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK; (D.F.); (S.P.); (A.B.S.)
| | - William Atiomo
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai P.O. Box 505055, United Arab Emirates;
| | - Ketankumar B. Gajjar
- Division of Child Health, Obstetrics and Gynaecology, University of Nottingham, Nottingham NG5 1PB, UK;
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7
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Nallala J, Griggs R, Lloyd GR, Stone N, Shepherd NA. Infrared Spectroscopic Analysis in the Differentiation of Epithelial Misplacement From Adenocarcinoma in Sigmoid Colonic Adenomatous Polyps. Clin Med Insights Pathol 2022; 15:2632010X221088960. [PMID: 35509812 PMCID: PMC9058331 DOI: 10.1177/2632010x221088960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/03/2022] [Indexed: 11/15/2022] Open
Abstract
Purpose The differential diagnosis of epithelial misplacement from invasive cancer in the colon is a challenging endeavour, augmented by the introduction of bowel cancer population screening. The main aim of the work is to test, as a proof-of concept study, the ability of the infrared spectroscopic imaging approach to differentiate epithelial misplacement from adenocarcinoma in sigmoid colonic adenomatous polyps. Methods Ten samples from each of the four diagnostic groups, normal colonic mucosa, adenomatous polyps with low grade dysplasia, epithelial misplacement in adenomatous polyps and adenocarcinoma, were analysed using IR spectroscopic imaging and data processing methods. IR spectral images were subjected to data pre-processing and cluster analysis based segmentation to identify epithelial, connective tissue and stromal regions. Statistical analysis was carried out using principal component analysis and linear discriminant analysis based cross validation, to classify spectral features according to the pathology, and the diagnostic attributes were compared. Results The combined 4-group classification model on an average showed a sensitivity of 64%, a specificity of 88% and an accuracy of 76% for prediction based on a 'single spectrum', whilst a 'majority-vote' prediction on an average showed a sensitivity of 73%, a specificity of 90% and an accuracy of 82%. The 2-group model, for the differential diagnosis of epithelial misplacement versus adenocarcinoma, showed an average sensitivity and specificity of 82.5% for prediction based on a 'single spectrum' whilst a 'majority-vote' classification showed an average sensitivity and specificity of 90%. A 92% area under the curve (AUC) value was obtained when evaluating the classifier using the Receiver Operating Characteristics (ROC) curves. Conclusions IR spectroscopy shows promise in its ability to differentiate epithelial misplacement from adenocarcinoma in tissue sections, considered as one of the most challenging endeavours in population-wide diagnostic histopathology. Further studies with larger series, including cases with challenging diagnostic features are required to ascertain the capability of this modern digital pathology approach. In the long-term, IR spectroscopy based pathology which is relatively low-cost and rapid, could be a promising endeavour to consider for integration into the existing histopathology pathway, in particular for population based screening programmes where large number of samples are scrutinised.
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Affiliation(s)
- Jayakrupakar Nallala
- Biomedical Physics, School of Physics and Astronomy, University of Exeter, Exeter, UK
| | - Rebecca Griggs
- Gloucestershire Cellular Pathology Laboratory, Cheltenham General Hospital, Cheltenham, Gloucestershire, UK
| | - Gavin R Lloyd
- Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Nick Stone
- Biomedical Physics, School of Physics and Astronomy, University of Exeter, Exeter, UK
| | - Neil A Shepherd
- Biomedical Physics, School of Physics and Astronomy, University of Exeter, Exeter, UK.,Gloucestershire Cellular Pathology Laboratory, Cheltenham General Hospital, Cheltenham, Gloucestershire, UK
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8
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Oungsakul P, Perez-Guaita D, Shah AK, Duffy D, Wood BR, Bielefeldt-Ohmann H, Hill MM. Addressing Delicate and Variable Cancer Morphology in Spectral Histopathology Using Canine Visceral Hemangiosarcoma. Anal Chem 2021; 93:12187-12194. [PMID: 34459578 DOI: 10.1021/acs.analchem.0c05190] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Spectral histopathology has shown promise for the classification and diagnosis of tumors with defined morphology, but application in tumors with variable or diffuse morphologies is yet to be investigated. To address this gap, we evaluated the application of Fourier transform infrared (FTIR) imaging as an accessory diagnostic tool for canine hemangiosarcoma (HSA), a vascular endothelial cell cancer that is difficult to diagnose. To preserve the delicate vascular tumor tissue structure, and potential classification of single endothelial cells, paraffin removal was not performed, and a partial least square discrimination analysis (PLSDA) and Random Forest (RF) models to classify different tissue types at individual pixel level were established using a calibration set (24 FTIR images from 13 spleen specimens). Next, the prediction capability of the PLSDA model was tested with an independent test set (n = 11), resulting in 74% correct classification of different tissue types at an individual pixel level. Finally, the performance of the FTIR spectropathology and chemometric algorithm for diagnosis of HSA was established in a blinded set of tissue samples (n = 24), with sensitivity and specificity of 80 and 81%, respectively. Taken together, these results show that FTIR imaging without paraffin removal can be applied to tumors with diffuse morphology, and this technique is a promising tool to assist in canine splenic HSA differential diagnosis.
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Affiliation(s)
- Patharee Oungsakul
- School of Veterinary Science, The University of Queensland, Gatton Campus, Gatton, QLD 4343, Australia.,QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
| | - David Perez-Guaita
- FOCAS Research Institute, Technological University Dublin, City Campus, Dublin D02 HW71, Ireland.,Department of Analytical Chemistry, University of Valencia, Burjassot 46000, Spain
| | - Alok K Shah
- QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
| | - David Duffy
- QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia
| | - Bayden R Wood
- Centre for Biospectroscopy, School of Chemistry, Faculty of Science, Monash University, Clayton, VIC 3800, Australia
| | - Helle Bielefeldt-Ohmann
- School of Veterinary Science, The University of Queensland, Gatton Campus, Gatton, QLD 4343, Australia.,School of Chemistry & Molecular Biosciences, The University of Queensland, St Lucia, QLD 4072, Australia
| | - Michelle M Hill
- QIMR Berghofer Medical Research Institute, Herston, QLD 4006, Australia.,The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia
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9
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Boutegrabet W, Guenot D, Bouché O, Boulagnon-Rombi C, Marchal Bressenot A, Piot O, Gobinet C. Automatic Identification of Paraffin Pixels on FTIR Images Acquired on FFPE Human Samples. Anal Chem 2021; 93:3750-3761. [PMID: 33590761 DOI: 10.1021/acs.analchem.0c03910] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The transfer of mid-infrared spectral histopathology to the clinic will be possible provided that its application in clinical practice is simple. Rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue section is thus a prerequisite. The chemical dewaxing of these samples before image acquisition used by the majority of studies is in contradiction with this principle. Fortunately, the in silico analysis of the images acquired on FFPE samples is possible using extended multiplicative signal correction (EMSC). However, the removal of pure paraffin pixels is essential to perform a relevant classification of tissue spectra. So far, this task was possible only if using manual and subjective histogram analysis. In this article, we thus propose a new automatic and multivariate methodology based on the analysis of optimized combinations of EMSC regression coefficients by validity indices and KMeans clustering to separate paraffin and tissue pixels. The validation of our method is performed using simulated infrared spectral images by measuring the Jaccard index between our partitions and the image model, with values always over 0.90 for diverse baseline complexity and signal-to-noise ratio. These encouraging results were also validated on real images by comparing our method with classical ones and by computing the Jaccard index between our partitions and the KMeans partitions obtained on the infrared image acquired on the same samples but after chemical dewaxing, with values always over 0.84.
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Affiliation(s)
- Warda Boutegrabet
- Institut National de la Santé et de la Recherche Médicale, IRFAC Inserm U1113, Université de Strasbourg (Unistra), 3 avenue Molière, 67200 Strasbourg, France.,BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France
| | - Dominique Guenot
- Institut National de la Santé et de la Recherche Médicale, IRFAC Inserm U1113, Université de Strasbourg (Unistra), 3 avenue Molière, 67200 Strasbourg, France
| | - Olivier Bouché
- BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France.,Hepato-Gastroenterology Department, CHU de Reims, rue du Général Koenig, 51092 Reims, France
| | - Camille Boulagnon-Rombi
- MEDyC CNRS UMR 7369, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France.,Biopathology Laboratory, CHU de Reims, rue du Général Koenig, 51092 Reims, France
| | - Aude Marchal Bressenot
- BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France.,Biopathology Laboratory, CHU de Reims, rue du Général Koenig, 51092 Reims, France
| | - Olivier Piot
- BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France.,Platform of Cellular and Tissular Imaging (PICT), 51 rue Cognacq-Jay, 51097 Reims, France
| | - Cyril Gobinet
- BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France
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10
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Kirkby CJ, Gala de Pablo J, Tinkler-Hundal E, Wood HM, Evans SD, West NP. Developing a Raman spectroscopy-based tool to stratify patient response to pre-operative radiotherapy in rectal cancer. Analyst 2021; 146:581-589. [DOI: 10.1039/d0an01803a] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The use of Raman spectroscopy to stratify rectal cancer patient response to pre-operative radiotherapy, using routine pre-treatment biopsy samples.
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Affiliation(s)
- Chloe J. Kirkby
- Pathology & Data Analytics
- Leeds Institute of Medical Research at St James's
- University of Leeds
- Leeds
- UK
| | - Julia Gala de Pablo
- Molecular and Nanoscale Physics Group
- School of Physics and Astronomy
- University of Leeds
- Leeds
- UK
| | - Emma Tinkler-Hundal
- Pathology & Data Analytics
- Leeds Institute of Medical Research at St James's
- University of Leeds
- Leeds
- UK
| | - Henry M. Wood
- Pathology & Data Analytics
- Leeds Institute of Medical Research at St James's
- University of Leeds
- Leeds
- UK
| | - Stephen D. Evans
- Molecular and Nanoscale Physics Group
- School of Physics and Astronomy
- University of Leeds
- Leeds
- UK
| | - Nicholas P. West
- Pathology & Data Analytics
- Leeds Institute of Medical Research at St James's
- University of Leeds
- Leeds
- UK
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11
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Al Jedani S, Smith CI, Gunning P, Ellis BG, Gardner P, Barrett SD, Triantafyllou A, Risk JM, Weightman P. A de-waxing methodology for scanning probe microscopy. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:3397-3403. [PMID: 32930228 DOI: 10.1039/d0ay00965b] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
A de-waxing protocol that successfully removes paraffin from tissue microarray (TMA) cores of fixed tissue obtained from oral cancer is described. The success of the protocol is demonstrated by the comparison of Fourier transform infrared (FTIR) results obtained on paraffin-embedded and de-waxed tissue and the absence of any significant correlations between infrared scanning near-field optical microscopy (SNOM) images of de-waxed tissue obtained at the three main paraffin IR peaks. The success of the protocol in removing paraffin from tissue is also demonstrated by images obtained with scanning electron microscopy (SEM) and by energy dispersive spectra (EDS) of a de-waxed CaF2 disc which shows no significant contribution from carbon. The FTIR spectra of the de-waxed TMA core overlaps that obtained from OE19 oesophageal cancer cells which had never been exposed to paraffin.
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Affiliation(s)
- Safaa Al Jedani
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | | | - Philip Gunning
- Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, L3 9TA, UK
| | - Barnaby G Ellis
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Peter Gardner
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK
| | - Steve D Barrett
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Asterios Triantafyllou
- Department of Pathology, Liverpool Clinical Laboratories, University of Liverpool, Liverpool, UK
| | - Janet M Risk
- Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, L3 9TA, UK
| | - Peter Weightman
- Department of Physics, University of Liverpool, L69 7ZE, UK.
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12
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Gaifulina R, Caruana DJ, Oukrif D, Guppy NJ, Culley S, Brown R, Bell I, Rodriguez-Justo M, Lau K, Thomas GMH. Rapid and complete paraffin removal from human tissue sections delivers enhanced Raman spectroscopic and histopathological analysis. Analyst 2020; 145:1499-1510. [PMID: 31894759 PMCID: PMC7677988 DOI: 10.1039/c9an01030k] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 12/14/2019] [Indexed: 12/29/2022]
Abstract
Incomplete removal of paraffin and organic contaminants from tissues processed for diagnostic histology has been a profound barrier to the introduction of Raman spectroscopic techniques into clinical practice. We report a route to rapid and complete paraffin removal from a range of formalin-fixed paraffin embedded tissues using super mirror stainless steel slides. The method is equally effective on a range of human and animal tissues, performs equally well with archived and new samples and is compatible with standard pathology lab procedures. We describe a general enhancement of the Raman scatter and enhanced staining with antibodies used in immunohistochemistry for clinical diagnosis. We conclude that these novel slide substrates have the power to improve diagnosis through anatomical pathology by facilitating the simultaneous combination of improved, more sensitive immunohistochemical staining and simplified, more reliable Raman spectroscopic imaging, analysis and signal processing.
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Affiliation(s)
- Riana Gaifulina
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
- Department of Chemistry
, University College London
,
UK
| | | | - Dahmane Oukrif
- Research Department of Pathology
, University College London
,
UK
| | - Naomi J. Guppy
- UCL Advanced Diagnostics
, University College Hospital
,
UK
| | - Siân Culley
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
- MRC Laboratory for Molecular Cell Biology
, University College London
,
UK
| | - Robert Brown
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Ian Bell
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Manuel Rodriguez-Justo
- Department of Gastrointestinal Pathology
, University College Hospital and Department of Research Pathology/Cancer Institute
,
UCL
, UK
| | - Katherine Lau
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Geraint M. H. Thomas
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
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13
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Nallala J, Jeynes C, Saunders S, Smart N, Lloyd G, Riley L, Salmon D, Stone N. Characterization of colorectal mucus using infrared spectroscopy: a potential target for bowel cancer screening and diagnosis. J Transl Med 2020; 100:1102-1110. [PMID: 32203151 PMCID: PMC7374084 DOI: 10.1038/s41374-020-0418-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 03/10/2020] [Accepted: 03/10/2020] [Indexed: 12/27/2022] Open
Abstract
Biological materials presenting early signs of cancer would be beneficial for cancer screening/diagnosis. In this respect, the suitability of potentially exploiting mucus in colorectal cancer was tested using infrared spectroscopy in combination with statistical modeling. Twenty-six paraffinized colon tissue biopsy sections containing mucus regions from 20 individuals (10 normal and 16 cancerous) were measured using mid-infrared spectroscopic imaging. A digital de-paraffinization, followed by cluster analysis driven digital color-coded multi-staining segmented the infrared images into various histopathological features such as epithelium, connective tissue, stroma, and mucus regions within the tissue sections. Principal component analysis followed by supervised linear discriminant analysis was carried out on pure mucus and epithelial spectra from normal and cancerous regions of the tissue. For the mucus-based classification, a sensitivity of 96%, a specificity of 83%, and an area under the curve performance of 95% was obtained. For the epithelial tissue-based classification, a sensitivity of 72%, a specificity of 88%, and an area under the curve performance of 89% was obtained. The mucus spectral profiles further showed contributions indicative of glycans including that of sialic acid changes between these pathology groups. The study demonstrates that infrared spectroscopic analysis of mucus discriminates colorectal cancers with high sensitivity. This concept could be exploited to develop screening/diagnostic approaches complementary to histopathology.
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Affiliation(s)
- Jayakrupakar Nallala
- Biomedical Physics, School of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK.
| | - Charles Jeynes
- 0000 0004 1936 8024grid.8391.3Living Systems Institute, University of Exeter, Exeter, EX4 4QD UK
| | - Sarah Saunders
- grid.416118.bCellular Pathology Department, Royal Devon & Exeter Hospital, Exeter, EX2 5AD UK
| | - Neil Smart
- grid.416118.bDepartment of Surgery, Royal Devon and Exeter Hospital, Exeter, EX2 5DW UK
| | - Gavin Lloyd
- 0000 0004 1936 7486grid.6572.6Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT UK
| | - Leah Riley
- grid.416118.bCellular Pathology Department, Royal Devon & Exeter Hospital, Exeter, EX2 5AD UK
| | - Debbie Salmon
- 0000 0004 1936 8024grid.8391.3Biocatalysis Centre, Biosciences, University of Exeter, Exeter, EX4 4QD UK
| | - Nick Stone
- 0000 0004 1936 8024grid.8391.3Biomedical Physics, School of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL UK
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14
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Isabelle M, Dorney J, Lewis A, Lloyd GR, Old O, Shepherd N, Rodriguez-Justo M, Barr H, Lau K, Bell I, Ohrel S, Thomas G, Stone N, Kendall C. Multi-centre Raman spectral mapping of oesophageal cancer tissues: a study to assess system transferability. Faraday Discuss 2018; 187:87-103. [PMID: 27048868 DOI: 10.1039/c5fd00183h] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The potential for Raman spectroscopy to provide early and improved diagnosis on a wide range of tissue and biopsy samples in situ is well documented. The standard histopathology diagnostic methods of reviewing H&E and/or immunohistochemical (IHC) stained tissue sections provides valuable clinical information, but requires both logistics (review, analysis and interpretation by an expert) and costly processing and reagents. Vibrational spectroscopy offers a complimentary diagnostic tool providing specific and multiplexed information relating to molecular structure and composition, but is not yet used to a significant extent in a clinical setting. One of the challenges for clinical implementation is that each Raman spectrometer system will have different characteristics and therefore spectra are not readily compatible between systems. This is essential for clinical implementation where classification models are used to compare measured biochemical or tissue spectra against a library training dataset. In this study, we demonstrate the development and validation of a classification model to discriminate between adenocarcinoma (AC) and non-cancerous intraepithelial metaplasia (IM) oesophageal tissue samples, measured on three different Raman instruments across three different locations. Spectra were corrected using system transfer spectral correction algorithms including wavenumber shift (offset) correction, instrument response correction and baseline removal. The results from this study indicate that the combined correction methods do minimize the instrument and sample quality variations within and between the instrument sites. However, more tissue samples of varying pathology states and greater tissue area coverage (per sample) are needed to properly assess the ability of Raman spectroscopy and system transferability algorithms over multiple instrument sites.
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Affiliation(s)
- M Isabelle
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
| | - J Dorney
- Biomedical Spectroscopy, School of Physics, University of Exeter, UK
| | - A Lewis
- Department of Cell and Developmental Biology, University College London, London, UK
| | - G R Lloyd
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
| | - O Old
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
| | - N Shepherd
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
| | - M Rodriguez-Justo
- Department of Cell and Developmental Biology, University College London, London, UK
| | - H Barr
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
| | - K Lau
- Spectroscopy Products Division, Renishaw plc, Wotton-Under-Edge, Gloucestershire, UK
| | - I Bell
- Spectroscopy Products Division, Renishaw plc, Wotton-Under-Edge, Gloucestershire, UK
| | - S Ohrel
- Spectroscopy Products Division, Renishaw plc, Wotton-Under-Edge, Gloucestershire, UK
| | - G Thomas
- Department of Cell and Developmental Biology, University College London, London, UK
| | - N Stone
- Biomedical Spectroscopy, School of Physics, University of Exeter, UK
| | - C Kendall
- Biophotonics Research Unit and Pathology Department, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, UK.
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15
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Seddon AB, Napier B, Lindsay I, Lamrini S, Moselund PM, Stone N, Bang O, Farries M. Prospective on using fibre mid-infrared supercontinuum laser sources for in vivo spectral discrimination of disease. Analyst 2018; 143:5874-5887. [DOI: 10.1039/c8an01396a] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Mid-infrared (MIR) fibre-optics may play a future role in in vivo diagnosis of disease, including cancer.
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Affiliation(s)
- Angela B. Seddon
- Mid-Infrared Photonics Group
- George Green Institute for Electromagnetics’ Research
- Faculty of Engineering
- University of Nottingham
- UK
| | - Bruce Napier
- Vivid Components Ltd
- German Office
- 33102 Paderborn
- Germany
| | - Ian Lindsay
- Gooch & Housego
- UK
- now at H. H. Wills Physics Laboratory
- Tyndall Ave
- University of Bristol
| | - Samir Lamrini
- LISA laser products OHG
- Fuhrberg & Teichmann
- Albert Einstein Straße
- 1-9 37191 Katlenburg-Lindau
- Germany
| | | | - Nicholas Stone
- Physics and Astronomy
- College of Engineering
- Mathematics and Physical Sciences
- University of Exeter
- UK
| | - Ole Bang
- Fibre Sensors and Supercontinuum Group
- DTU Fotonik
- Technical University of Denmark
- DK-2800 Kongens Lyngby
- Denmark
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16
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Gaifulina R, Maher AT, Kendall C, Nelson J, Rodriguez-Justo M, Lau K, Thomas GM. Label-free Raman spectroscopic imaging to extract morphological and chemical information from a formalin-fixed, paraffin-embedded rat colon tissue section. Int J Exp Pathol 2016; 97:337-350. [PMID: 27581376 PMCID: PMC5061758 DOI: 10.1111/iep.12194] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 05/04/2016] [Indexed: 12/19/2022] Open
Abstract
Animal models and archived human biobank tissues are useful resources for research in disease development, diagnostics and therapeutics. For the preservation of microscopic anatomical features and to facilitate long-term storage, a majority of tissue samples are denatured by the chemical treatments required for fixation, paraffin embedding and subsequent deparaffinization. These aggressive chemical processes are thought to modify the biochemical composition of the sample and potentially compromise reliable spectroscopic examination useful for the diagnosis or biomarking. As a result, spectroscopy is often conducted on fresh/frozen samples. In this study, we provide an extensive characterization of the biochemical signals remaining in processed samples (formalin fixation and paraffin embedding, FFPE) and especially those originating from the anatomical layers of a healthy rat colon. The application of chemometric analytical methods (unsupervised and supervised) was shown to eliminate the need for tissue staining and easily revealed microscopic features consistent with goblet cells and the dense populations of cells within the mucosa, principally via strong nucleic acid signals. We were also able to identify the collagenous submucosa- and serosa- as well as the muscle-associated signals from the muscular regions and blood vessels. Applying linear regression analysis to the data, we were able to corroborate this initial assignment of cell and tissue types by confirming the biological origin of each layer by reference to a subset of authentic biomolecular standards. Our results demonstrate the potential of using label-free Raman microspectroscopy to obtain superior imaging contrast in FFPE sections when compared directly to conventional haematoxylin and eosin (H&E) staining.
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Affiliation(s)
- Riana Gaifulina
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Andrew Thomas Maher
- Department of Cell and Developmental Biology, University College London, London, UK
- CoMPLEX, University College London, London, UK
| | - Catherine Kendall
- Biophotonics Research Unit, Gloucestershire Royal Hospital, Gloucester, UK
| | - James Nelson
- Department of Statistical Science, University College London, London, UK
| | | | - Katherine Lau
- Spectroscopy Products Division, Renishaw Plc, Wotton-under-Edge, UK
| | - Geraint Mark Thomas
- Department of Cell and Developmental Biology, University College London, London, UK.
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17
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Nguyen TNQ, Jeannesson P, Groh A, Piot O, Guenot D, Gobinet C. Fully unsupervised inter-individual IR spectral histology of paraffinized tissue sections of normal colon. JOURNAL OF BIOPHOTONICS 2016; 9:521-532. [PMID: 26872124 DOI: 10.1002/jbio.201500285] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 12/16/2015] [Accepted: 01/04/2016] [Indexed: 06/05/2023]
Abstract
In label-free Fourier-transform infrared histology, spectral images are individually recorded from tissue sections, pre-processed and clustered. Each single resulting color-coded image is annotated by a pathologist to obtain the best possible match with tissue structures revealed after Hematoxylin-Eosin staining. However, the main limitations of this approach are the empirical choice of the number of clusters in unsupervised classification, and the marked color heterogeneity between the clustered spectral images. Here, using normal murine and human colon tissues, we developed an automatic multi-image spectral histology to simultaneously analyze a set of spectral images (8 images mice samples and 72 images human ones). This procedure consisted of a joint Extended Multiplicative Signal Correction (EMSC) to numerically deparaffinize the tissue sections, followed by an automated joint K-Means (KM) clustering using the hierarchical double application of Pakhira-Bandyopadhyay-Maulik (PBM) validity index. Using this procedure, the main murine and human colon histological structures were correctly identified at both the intra- and the inter-individual levels, especially the crypts, secreted mucus, lamina propria and submucosa. Here, we show that batched multi-image spectral histology procedure is insensitive to the reference spectrum but highly sensitive to the paraffin model of joint EMSC. In conclusion, combining joint EMSC and joint KM clustering by double PBM application allows to achieve objective and automated batched multi-image spectral histology.
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Affiliation(s)
- Thi Nguyet Que Nguyen
- Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, Reims, France
- CNRS UMR7369, Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Reims, France
| | - Pierre Jeannesson
- Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, Reims, France
- CNRS UMR7369, Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Reims, France
| | - Audrey Groh
- Progression tumorale et microenvironnement, Approches translationnelles et Epidémiologie, EA 3430, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg (UdS), Strasbourg, France
| | - Olivier Piot
- Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, Reims, France
- CNRS UMR7369, Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Reims, France
| | - Dominique Guenot
- Progression tumorale et microenvironnement, Approches translationnelles et Epidémiologie, EA 3430, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg (UdS), Strasbourg, France
| | - Cyril Gobinet
- Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, Reims, France
- CNRS UMR7369, Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Reims, France
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18
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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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