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Vanna R, Masella A, Bazzarelli M, Ronchi P, Lenferink A, Tresoldi C, Morasso C, Bedoni M, Cerullo G, Polli D, Ciceri F, De Poli G, Bregonzio M, Otto C. High-Resolution Raman Imaging of >300 Patient-Derived Cells from Nine Different Leukemia Subtypes: A Global Clustering Approach. Anal Chem 2024; 96:9468-9477. [PMID: 38821490 PMCID: PMC11170555 DOI: 10.1021/acs.analchem.4c00787] [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: 02/08/2024] [Revised: 05/17/2024] [Accepted: 05/17/2024] [Indexed: 06/02/2024]
Abstract
Leukemia comprises a diverse group of bone marrow tumors marked by cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, by conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated preprocessing pipeline followed by a single-step global clustering approach performed over the entire data set identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO), and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudostained images at the single-cell level. Furthermore, this approach provided a semiquantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.
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Affiliation(s)
- Renzo Vanna
- Istituto
di Fotonica e Nanotecnologie − Consiglio Nazionale delle Ricerche
(IFN-CNR), c/o Politecnico di Milano, Milan 20133, Italy
| | | | | | - Paola Ronchi
- IRCCS
Ospedale San Raffaele, University Vita-Salute
San Raffaele, Milan 20132, Italy
| | - Aufried Lenferink
- Medical
Cell BioPhysics, Department of Science and Technology, TechMed Center, University of Twente, Enschede, NL 7500
AE, The Netherlands
| | - Cristina Tresoldi
- IRCCS
Ospedale San Raffaele, University Vita-Salute
San Raffaele, Milan 20132, Italy
| | - Carlo Morasso
- Istituti
Clinici Scientifici Maugeri IRCCS, Via Maugeri 4, Pavia 27100, Italy
| | - Marzia Bedoni
- IRCCS, Fondazione Don Carlo
Gnocchi, Milan 20148, Italy
| | - Giulio Cerullo
- Istituto
di Fotonica e Nanotecnologie − Consiglio Nazionale delle Ricerche
(IFN-CNR), c/o Politecnico di Milano, Milan 20133, Italy
- Dipartimento
di Fisica, Politecnico di Milano, Milan 20133, Italy
| | - Dario Polli
- Istituto
di Fotonica e Nanotecnologie − Consiglio Nazionale delle Ricerche
(IFN-CNR), c/o Politecnico di Milano, Milan 20133, Italy
- Dipartimento
di Fisica, Politecnico di Milano, Milan 20133, Italy
| | - Fabio Ciceri
- IRCCS
Ospedale San Raffaele, University Vita-Salute
San Raffaele, Milan 20132, Italy
| | | | | | - Cees Otto
- Medical
Cell BioPhysics, Department of Science and Technology, TechMed Center, University of Twente, Enschede, NL 7500
AE, The Netherlands
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Brunner A, Unterberger SH, Auer H, Hautz T, Schneeberger S, Stalder R, Badzoka J, Kappacher C, Huck CW, Zelger B, Pallua JD. Suitability of Fourier transform infrared microscopy for the diagnosis of cystic echinococcosis in human tissue sections. JOURNAL OF BIOPHOTONICS 2024; 17:e202300513. [PMID: 38531615 DOI: 10.1002/jbio.202300513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/14/2024] [Accepted: 03/17/2024] [Indexed: 03/28/2024]
Abstract
Cystic echinococcosis (CE) is a global health concern caused by cestodes, posing diagnostic challenges due to nonspecific symptoms and inconclusive radiographic results. Diagnosis relies on histopathological evaluation of affected tissue, demanding comprehensive tools. In this retrospective case study, Fourier transform infrared microscopy was explored for detecting and identifying CE through biochemical changes in human tissue sections. Tissue samples from 11 confirmed CE patients were analyzed. Archived FFPE blocks were cut and stained, and then CE-positive unstained sections were examined using Fourier transform infrared microscopy post-deparaffinization. Results revealed the method's ability to distinguish echinococcus elements from human tissue, irrespective of organ type. This research showcases the potential of mid-infrared microscopy as a valuable diagnostic tool for CE, offering promise in enhancing diagnostic precision in the face of the disease's complexities.
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Affiliation(s)
- A Brunner
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - S H Unterberger
- Department of Material-Technology, Leopold-Franzens University Innsbruck, Innsbruck, Austria
| | - H Auer
- Department of Medical Parasitology, Clinical Institute of Hygiene and Medical Microbiology, Medical University of Vienna, Vienna, Austria
| | - T Hautz
- OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - S Schneeberger
- OrganLifeTM, Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - R Stalder
- Institute of Mineralogy and Petrography, Leopold-Franzens University Innsbruck, Innsbruck, Austria
| | - J Badzoka
- Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innsbruck, Austria
| | - C Kappacher
- Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innsbruck, Austria
| | - C W Huck
- Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innsbruck, Austria
| | - B Zelger
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - J D Pallua
- Department of Hospital for Orthopedics and Traumatology, Medical University of Innsbruck, Innsbruck, Austria
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Sharma VJ, Singh A, Grant JL, Raman J. Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning. Pathology 2024; 56:313-321. [PMID: 38341306 DOI: 10.1016/j.pathol.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/24/2023] [Accepted: 11/01/2023] [Indexed: 02/12/2024]
Abstract
Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and resources. Vibrational spectroscopy is a novel technique that offers an alternative atraumatic approach, with short scan times, while providing metabolic and morphological data. This review evaluates vibrational spectroscopy for the assessment of fibrosis, with a focus on point-of-care capabilities. OVID Medline, Embase and Cochrane databases were systematically searched using PRISMA guidelines for search terms including vibrational spectroscopy, human tissue and fibrosis. Studies were stratified based on imaging modality and tissue type. Outcomes recorded included tissue type, machine learning technique, metrics for accuracy and author conclusions. Systematic review yielded 420 articles, of which 14 were relevant. Ten of these articles considered mid-infrared spectroscopy, three dealt with Raman spectroscopy and one with near-infrared spectroscopy. The metrics for detecting fibrosis were Pearson correlation coefficients ranging from 0.65-0.98; sensitivity from 76-100%; specificity from 90-99%; area under receiver operator curves from 0.83-0.98; and accuracy of 86-99%. Vibrational spectroscopy identified fibrosis in myeloproliferative neoplasms in bone, cirrhotic and hepatocellular carcinoma in liver, end-stage heart failure in cardiac tissue and following laser ablation for acne in skin. It also identified interstitial fibrosis as a predictor of early renal transplant rejection in renal tissue. Vibrational spectroscopic techniques can therefore accurately identify fibrosis in a range of human tissues. Emerging data show that it can be used to quantify, classify and provide data about the nature of fibrosis with a high degree of accuracy with potential scope for point-of-care use.
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Affiliation(s)
- Varun J Sharma
- Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Health, Heidelberg, Melbourne, Vic, Australia; Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Spectromix Laboratory, Melbourne, Vic, Australia
| | - Aashima Singh
- Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Melbourne Medical School, The University of Melbourne, Vic, Australia
| | | | - Jaishankar Raman
- Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Health, Heidelberg, Melbourne, Vic, Australia; Department of Surgery (Austin Health), Melbourne Medical School, The University of Melbourne, Vic, Australia; Spectromix Laboratory, Melbourne, Vic, Australia; Department of Cardiac Surgery, St Vincent's Hospital, Fitzroy, Melbourne, Vic, Australia.
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Sharma VJ, Adegoke JA, Fasulakis M, Green A, Goh SK, Peng X, Liu Y, Jackett L, Vago A, Poon EKW, Starkey G, Moshfegh S, Muthya A, D'Costa R, James F, Gordon CL, Jones R, Afara IO, Wood BR, Raman J. Point-of-care detection of fibrosis in liver transplant surgery using near-infrared spectroscopy and machine learning. Health Sci Rep 2023; 6:e1652. [PMID: 37920655 PMCID: PMC10618569 DOI: 10.1002/hsr2.1652] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/27/2023] [Accepted: 10/11/2023] [Indexed: 11/04/2023] Open
Abstract
Introduction Visual assessment and imaging of the donor liver are inaccurate in predicting fibrosis and remain surrogates for histopathology. We demonstrate that 3-s scans using a handheld near-infrared-spectroscopy (NIRS) instrument can identify and quantify fibrosis in fresh human liver samples. Methods We undertook NIRS scans on 107 samples from 27 patients, 88 from 23 patients with liver disease, and 19 from four organ donors. Results Liver disease patients had a median immature fibrosis of 40% (interquartile range [IQR] 20-60) and mature fibrosis of 30% (10%-50%) on histopathology. The organ donor livers had a median fibrosis (both mature and immature) of 10% (IQR 5%-15%). Using machine learning, this study detected presence of cirrhosis and METAVIR grade of fibrosis with a classification accuracy of 96.3% and 97.2%, precision of 96.3% and 97.0%, recall of 96.3% and 97.2%, specificity of 95.4% and 98.0% and area under receiver operator curve of 0.977 and 0.999, respectively. Using partial-least square regression machine learning, this study predicted the percentage of both immature (R 2 = 0.842) and mature (R 2 = 0.837) with a low margin of error (root mean square of error of 9.76% and 7.96%, respectively). Conclusion This study demonstrates that a point-of-care NIRS instrument can accurately detect, quantify and classify liver fibrosis using machine learning.
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Affiliation(s)
- Varun J. Sharma
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Brian F. Buxton Department of Cardiac and Thoracic Aortic SurgeryAustin HospitalMelbourneVictoriaAustralia
| | - John A. Adegoke
- Centre for BiospectroscopyMonash UniversityMelbourneVictoriaAustralia
| | - Michael Fasulakis
- Department of EngineeringUniversity of MelbourneMelbourneVictoriaAustralia
| | - Alexander Green
- Centre for BiospectroscopyMonash UniversityMelbourneVictoriaAustralia
| | - Su K. Goh
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Liver & Intestinal Transplant UnitAustin HealthMelbourneVictoriaAustralia
| | - Xiuwen Peng
- Department of EngineeringUniversity of MelbourneMelbourneVictoriaAustralia
| | - Yifan Liu
- Department of EngineeringUniversity of MelbourneMelbourneVictoriaAustralia
| | - Louise Jackett
- Department of Anatomical PathologyAustin HealthMelbourneVictoriaAustralia
| | - Angela Vago
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Liver & Intestinal Transplant UnitAustin HealthMelbourneVictoriaAustralia
| | - Eric K. W. Poon
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and ImmunityUniversity of MelbourneMelbourneVictoriaAustralia
| | - Graham Starkey
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Liver & Intestinal Transplant UnitAustin HealthMelbourneVictoriaAustralia
| | - Sarina Moshfegh
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
| | - Ankita Muthya
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
| | - Rohit D'Costa
- DonateLife VictoriaCarltonVictoriaAustralia
- Department of Intensive Care MedicineMelbourne HealthMelbourneVictoriaAustralia
| | - Fiona James
- Department of Infectious DiseasesAustin HealthMelbourneVictoriaAustralia
| | - Claire L. Gordon
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and ImmunityUniversity of MelbourneMelbourneVictoriaAustralia
- Department of Infectious DiseasesAustin HealthMelbourneVictoriaAustralia
| | - Robert Jones
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Liver & Intestinal Transplant UnitAustin HealthMelbourneVictoriaAustralia
| | - Isaac O. Afara
- School of Information Technology and Electrical EngineeringFaculty of Engineering, Architecture, and Information TechnologyBrisbaneQueenslandAustralia
- Biomedical Spectroscopy Laboratory, Department of Applied PhysicsUniversity of Eastern FinlandKuopioFinland
| | - Bayden R. Wood
- Centre for BiospectroscopyMonash UniversityMelbourneVictoriaAustralia
| | - Jaishankar Raman
- Department of Surgery, Melbourne Medical SchoolUniversity of MelbourneMelbourneVictoriaAustralia
- Brian F. Buxton Department of Cardiac and Thoracic Aortic SurgeryAustin HospitalMelbourneVictoriaAustralia
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Guillard J, Untereiner V, Garnotel R, Boulagnon-Rombi C, Gobinet C, Proult I, Sockalingum GD, Thiéfin G. Longitudinal Study of Cirrhosis Development in STAM and carbon tetrachloride Mouse Models Using Fourier Transform Infrared Spectral Imaging. J Transl Med 2023; 103:100231. [PMID: 37544611 DOI: 10.1016/j.labinv.2023.100231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 07/31/2023] [Accepted: 07/31/2023] [Indexed: 08/08/2023] Open
Abstract
Animal models of cirrhosis are of great interest to investigate the pathological process leading to the final stage of cirrhosis. The aim of this study was to analyze the different steps involved in the progressive development of cirrhosis using Fourier transform infrared spectral histology in 2 mouse models of cirrhosis, the STAM model of metabolic cirrhosis, and the carbon tetrachloride-induced cirrhosis model. Formalin-fixed, paraffin-embedded liver samples were obtained from 3 mice at 5 time points in each model to analyze the course of hepatic lesions up to the formation of cirrhosis. For each time point, adjacent 3-μm-thick liver sections were obtained for histologic stains and spectral histology. Fourier transform infrared acquisitions of liver sections were performed at projected pixel sizes of 25 μm × 25 μm and 6.25 μm × 6.25 μm. Spectral images were then preprocessed with an extended multiplicative signal correction and analyzed with common k-means clustering, including all stages in each model. In both models, the 2- and 4-class common k-means clustering in the 1000 to 1350 cm-1 range showed that spectral classes characterized by higher absorbance peaks of glycogen were predominant at baseline, then decreased markedly in early stages of hepatic damage, and almost disappeared in cirrhotic tissues. Concomitantly, spectral classes characterized by higher absorbance peaks of nucleic acids became progressively predominant during the course of hepatic lesions. These results were confirmed using k-means clustering on the peaks of interest identified for glycogen and nucleic acid content. Our study showed that the glycogen depletion previously described at the stage of cirrhosis is an early event in the pathological process, independently of the cause of cirrhosis. In addition, there was a progressive increase in the nucleic acid content, which may be linked to increased proliferation and polyploidy in response to cellular lesions.
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Affiliation(s)
- Julien Guillard
- Université de Reims Champagne-Ardenne, BioSpecT, Reims, France
| | - Valérie Untereiner
- Université de Reims Champagne-Ardenne, Plateforme en Imagerie Cellulaire et Tissulaire, Reims, France
| | - Roselyne Garnotel
- Université de Reims Champagne-Ardenne, BioSpecT, Reims, France; Laboratoire de Biochimie-Pharmacologie-Toxicologie, Pôle de Biologie Territoriale, Centre Hospitalo-Universitaire de Reims, Reims, France
| | - Camille Boulagnon-Rombi
- Laboratoire de Biopathologie, Pôle de Biologie Territoriale, Centre Hospitalo-Universitaire de Reims, Reims, France
| | - Cyril Gobinet
- Université de Reims Champagne-Ardenne, BioSpecT, Reims, France
| | - Isabelle Proult
- Université de Reims Champagne-Ardenne, Centre National de la Recherche Scientifique, MEDyC, Reims, France
| | | | - Gérard Thiéfin
- Université de Reims Champagne-Ardenne, BioSpecT, Reims, France; Service d'Hépato-Gastroentérologie et de Cancérologie Digestive, Centre Hospitalo-Universitaire de Reims, Reims, France.
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Goines S, Deng M, Glasscott MW, Leung JWC, Dick JE. Enhancing scanning electrochemical microscopy's potential to probe dynamic co-culture systems via hyperspectral assisted-imaging. Analyst 2022; 147:2396-2404. [PMID: 35579029 PMCID: PMC9287841 DOI: 10.1039/d2an00319h] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Precise determination of boundaries in co-culture systems is difficult to achieve with scanning electrochemical microscopy alone. Thus, biological scanning electrochemical microscope platforms generally consist of a scanning electrochemical microscope positioner mounted on the stage of an inverted microscope for correlated electrochemical and optical imaging. Use of a fluorescence microscope allows for site-specific fluorescence labeling to obtain more clearly resolved spatial and electrochemical data. Here, we construct a unique hyperspectral assisted-biological scanning electrochemical microscope platform to widen the scope of biological imaging. Specifically, we incorporate a variable fluorescence bandpass source into a biological scanning electrochemical microscope platform for simultaneous optical, spectral, and electrochemical imaging. Not only does this platform serve as a cost-effective alternative to white light laser imaging, but additionally it provides multi-functional analysis of biological samples. Here, we demonstrate the efficacy of our platform to discern the electrochemical contribution of site-specific cells by optically and spectroscopically resolving boundaries as well as cell types within a complex biological system.
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Affiliation(s)
- Sondrica Goines
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Mingchu Deng
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Matthew W Glasscott
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Justin W C Leung
- Department of Radiation Oncology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Jeffrey E Dick
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Infrared Spectral Microscopy: A Primer for the Interventional Radiologist. J Vasc Interv Radiol 2021; 32:878-881.e1. [PMID: 33771714 DOI: 10.1016/j.jvir.2021.03.524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/03/2021] [Accepted: 03/14/2021] [Indexed: 11/20/2022] Open
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