1
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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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2
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Kopeć M, Beton-Mysur K, Abramczyk H. Biochemical changes in lipid and protein metabolism caused by mannose-Raman spectroscopy studies. Analyst 2024; 149:2942-2955. [PMID: 38597575 DOI: 10.1039/d4an00128a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Biochemical analysis of human normal bronchial cells (BEpiC) and human cancer lung cells (A549) has been performed by using Raman spectroscopy and Raman imaging. Our approach provides a biochemical compositional mapping of the main cell components: nucleus, mitochondria, lipid droplets, endoplasmic reticulum, cytoplasm and cell membrane. We proved that Raman spectroscopy and Raman imaging can distinguish successfully BEpiC and A549 cells. In this study, we have focused on the role of mannose in cancer development. It has been shown that changes in the concentration of mannose can regulate some metabolic processes in cells. Presented results suggest lipids and proteins can be considered as Raman biomarkers during lung cancer progression. Analysis obtained for bands 1444 cm-1, and 2854 cm-1 characteristic for lipids and derivatives proved that the addition of mannose reduced levels of these compounds. Results obtained for protein compounds based on bands 858 cm-1, 1004 cm-1 and 1584 cm-1 proved that the addition of mannose increases the values of protein in BEpiC cells and blocks protein glycolisation in A549 cells. Noticing Raman spectral changes in BEpiC and A549 cells supplemented with mannose can help to understand the mechanism of sugar metabolism during cancer development and could play in the future an important role in clinical treatment.
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Affiliation(s)
- Monika Kopeć
- Lodz University of Technology, Institute of Applied Radiation Chemistry, Laboratory of Laser Molecular Spectroscopy, Wroblewskiego 15, 93-590 Lodz, Poland.
| | - Karolina Beton-Mysur
- Lodz University of Technology, Institute of Applied Radiation Chemistry, Laboratory of Laser Molecular Spectroscopy, Wroblewskiego 15, 93-590 Lodz, Poland.
| | - Halina Abramczyk
- Lodz University of Technology, Institute of Applied Radiation Chemistry, Laboratory of Laser Molecular Spectroscopy, Wroblewskiego 15, 93-590 Lodz, Poland.
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3
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Zhang X, Fan A, Shu Z, Ma W, Zhang X. Surface-enhanced Raman database of 24 metabolites: Stable measurement of spectra, extraction and analysis of the main features. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 306:123587. [PMID: 37918093 DOI: 10.1016/j.saa.2023.123587] [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: 04/06/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/04/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has been used in Raman-based metabolomics to provide abundant molecular fingerprint information in situ with extremely high sensitivity, without damaging the sample. However, poor reproducibility, caused by the randomness of the adsorption sites, and the short-range effect of SERS have hindered the development of SERS in metabolomics, resulting in very few SERS reference databases for small-molecule metabolites. In this work, our previously proposed large laser spot-swift mapping SERS method was adopted for the measurement of 24 commercially available metabolite standards, to provide reproducible and reliable references for Raman-based metabolomics study. Among these 24 metabolites, 22 contained no Raman data in PubChem. Other than the SERS spectra data, we extracted and explained the molecular vibration information of these metabolites, and combined with the density functional theory (DFT) calculations, we provided a new possibility for the fast Raman recognition of small-molecule metabolites. Accordingly, a large laser spot-swift mapping SERS database of metabolites in human serum was initially established, which contained not only the original spectral data but also other detailed feature information regarding the Raman peaks. With continuous accumulation, this database could play a promising role in Raman-based metabolomics and other Raman-related research.
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Affiliation(s)
- Xiaoyu Zhang
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China
| | - Aoran Fan
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China
| | - Zixin Shu
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China
| | - Weigang Ma
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China
| | - Xing Zhang
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China.
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4
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Yang E, Kim JH, Tressler CM, Shen XE, Brown DR, Johnson CC, Hahm TH, Barman I, Glunde K. RaMALDI: Enabling simultaneous Raman and MALDI imaging of the same tissue section. Biosens Bioelectron 2023; 239:115597. [PMID: 37597501 PMCID: PMC10544780 DOI: 10.1016/j.bios.2023.115597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/02/2023] [Accepted: 08/11/2023] [Indexed: 08/21/2023]
Abstract
Multimodal tissue imaging techniques that integrate two complementary modalities are powerful discovery tools for unraveling biological processes and identifying biomarkers of disease. Combining Raman spectroscopic imaging (RSI) and matrix-assisted laser-desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain fused images with the advantages of both modalities has the potential of providing spatially resolved, sensitive, specific biomolecular information, but has so far involved two separate sample preparations, or even consecutive tissue sections for RSI and MALDI MSI, resulting in images with inherent disparities. We have developed RaMALDI, a streamlined, integrated, multimodal imaging workflow of RSI and MALDI MSI, performed on a single tissue section with one sample preparation protocol. We show that RaMALDI imaging of various tissues effectively integrates molecular information acquired from both RSI and MALDI MSI of the same sample, which will drive discoveries in cell biology, biomedicine, and pathology, and advance tissue diagnostics.
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Affiliation(s)
- Ethan Yang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Caitlin M Tressler
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Xinyi Elaine Shen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Dalton R Brown
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Cole C Johnson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Tae-Hun Hahm
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ishan Barman
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Kristine Glunde
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Departments of Oncology and Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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5
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Kordić A, Šarolić A. Dielectric Spectroscopy Shows a Permittivity Contrast between Meningioma Tissue and Brain White and Gray Matter-A Potential Physical Biomarker for Meningioma Discrimination. Cancers (Basel) 2023; 15:4153. [PMID: 37627181 PMCID: PMC10452737 DOI: 10.3390/cancers15164153] [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: 07/08/2023] [Revised: 07/22/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
The effectiveness of surgical resection of meningioma, the most common primary CNS tumor, depends on the capability to intraoperatively discriminate between the meningioma tissue and the surrounding brain white and gray matter tissues. Aiming to find a potential biomarker based on tissue permittivity, dielectric spectroscopy of meningioma, white matter, and gray matter ex vivo tissues was performed using the open-ended coaxial probe method in the microwave frequency range from 0.5 to 18 GHz. The averages and the 95% confidence intervals of the measured permittivity for each tissue were compared. The results showed the absence of overlap between the 95% confidence intervals for meningioma tissue and for brain white and gray matter, indicating a significant difference in average permittivity (p ≤ 0.05) throughout almost the entire measured frequency range, with the most pronounced contrast found between 2 GHz and 5 GHz. The discovered contrast is relevant as a potential physical biomarker to discriminate meningioma tissue from the surrounding brain tissues by means of permittivity measurement, e.g., for intraoperative meningioma margin assessment. The permittivity models for each tissue, developed in this study as its byproducts, will allow more accurate electromagnetic modeling of brain tumor and healthy tissues, facilitating the development of new microwave-based medical devices and tools.
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Affiliation(s)
- Anton Kordić
- Department of Neurosurgery, University Hospital Centre Zagreb, 10000 Zagreb, Croatia
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6
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Zhang L, Zhou Y, Wu B, Zhang S, Zhu K, Liu CH, Yu X, Alfano RR. A Handheld Visible Resonance Raman Analyzer Used in Intraoperative Detection of Human Glioma. Cancers (Basel) 2023; 15:cancers15061752. [PMID: 36980638 PMCID: PMC10046110 DOI: 10.3390/cancers15061752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/08/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
There is still a lack of reliable intraoperative tools for glioma diagnosis and to guide the maximal safe resection of glioma. We report continuing work on the optical biopsy method to detect glioma grades and assess glioma boundaries intraoperatively using the VRR-LRRTM Raman analyzer, which is based on the visible resonance Raman spectroscopy (VRR) technique. A total of 2220 VRR spectra were collected during surgeries from 63 unprocessed fresh glioma tissues using the VRR-LRRTM Raman analyzer. After the VRR spectral analysis, we found differences in the native molecules in the fingerprint region and in the high-wavenumber region, and differences between normal (control) and different grades of glioma tissues. A principal component analysis–support vector machine (PCA-SVM) machine learning method was used to distinguish glioma tissues from normal tissues and different glioma grades. The accuracy in identifying glioma from normal tissue was over 80%, compared with the gold standard of histopathology reports of glioma. The VRR-LRRTM Raman analyzer may be a new label-free, real-time optical molecular pathology tool aiding in the intraoperative detection of glioma and identification of tumor boundaries, thus helping to guide maximal safe glioma removal and adjacent healthy tissue preservation.
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Affiliation(s)
- Liang Zhang
- Department of Neurosurgery, Medical School of Nankai University, Tianjin 300071, China
- Department of Neurosurgery, PLA General Hospital, Beijing 100853, China
| | - Yan Zhou
- Department of Neurosurgery, Air Force Medical Center, Beijing 100142, China
- Correspondence: (Y.Z.); (X.Y.)
| | - Binlin Wu
- Physics Department and CSCU Center for Nanotechnology, Southern Connecticut State University, New Haven, CT 06515, USA
| | | | - Ke Zhu
- Institute of Physics, Chinese Academy of Sciences (CAS), Beijing 100190, China
| | - Cheng-Hui Liu
- Institute for Ultrafast Spectroscopy and Lasers, Department of Physics, The City College of the City University of New York, New York, NY 10031, USA
| | - Xinguang Yu
- Department of Neurosurgery, Medical School of Nankai University, Tianjin 300071, China
- Department of Neurosurgery, PLA General Hospital, Beijing 100853, China
- Correspondence: (Y.Z.); (X.Y.)
| | - Robert R. Alfano
- Institute for Ultrafast Spectroscopy and Lasers, Department of Physics, The City College of the City University of New York, New York, NY 10031, USA
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7
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Skyrman S, Burström G, Lai M, Manni F, Hendriks B, Frostell A, Edström E, Persson O, Elmi-Terander A. Diffuse reflectance spectroscopy sensor to differentiate between glial tumor and healthy brain tissue: a proof-of-concept study. BIOMEDICAL OPTICS EXPRESS 2022; 13:6470-6483. [PMID: 36589562 PMCID: PMC9774850 DOI: 10.1364/boe.474344] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/03/2022] [Accepted: 11/06/2022] [Indexed: 06/17/2023]
Abstract
Glial tumors grow diffusely in the brain. Survival is correlated to the extent of tumor removal, but tumor borders are often invisible. Resection beyond the borders as defined by conventional methods may further improve prognosis. In this proof-of-concept study, we evaluate diffuse reflectance spectroscopy (DRS) for discrimination between glial tumors and normal brain ex vivo. DRS spectra and histology were acquired from 22 tumor samples and nine brain tissue samples retrieved from 30 patients. The content of biological chromophores and scattering features were estimated by fitting a model derived from diffusion theory to the DRS spectra. DRS parameters differed significantly between tumor and normal brain tissue. Classification using random forest yielded a sensitivity and specificity for the detection of low-grade gliomas of 82.0% and 82.7%, respectively, and the area under curve (AUC) was 0.91. Applied in a hand-held probe or biopsy needle, DRS has the potential to provide intra-operative tissue analysis.
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Affiliation(s)
- Simon Skyrman
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Gustav Burström
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Marco Lai
- Philips Research, 5656 AE, Eindhoven, The Netherlands
- Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
| | - Francesca Manni
- Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
| | - Benno Hendriks
- Philips Research, 5656 AE, Eindhoven, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, 2628 CD, Delft, The Netherlands
| | - Arvid Frostell
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Erik Edström
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
| | - Oscar Persson
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Adrian Elmi-Terander
- Department of Neurosurgery, Karolinska University Hospital, 171 64 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
- Stockholm Spine Center, 194 45 Upplands-Väsby, Sweden
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8
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Romanishkin I, Savelieva T, Kosyrkova A, Okhlopkov V, Shugai S, Orlov A, Kravchuk A, Goryaynov S, Golbin D, Pavlova G, Pronin I, Loschenov V. Differentiation of glioblastoma tissues using spontaneous Raman scattering with dimensionality reduction and data classification. Front Oncol 2022; 12:944210. [PMID: 36185245 PMCID: PMC9520479 DOI: 10.3389/fonc.2022.944210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
The neurosurgery of intracranial tumors is often complicated by the difficulty of distinguishing tumor center, infiltration area, and normal tissue. The current standard for intraoperative navigation is fluorescent diagnostics with a fluorescent agent. This approach can be further enhanced by measuring the Raman spectrum of the tissue, which would provide additional information on its composition even in the absence of fluorescence. However, for the Raman spectra to be immediately helpful for a neurosurgeon, they must be additionally processed. In this work, we analyzed the Raman spectra of human brain glioblastoma multiforme tissue samples obtained during the surgery and investigated several approaches to dimensionality reduction and data classificatin to distinguish different types of tissues. In our study two approaches to Raman spectra dimensionality reduction were approbated and as a result we formulated new technique combining both of them: feature filtering based on the selection of those shifts which correspond to the biochemical components providing the statistically significant differences between groups of examined tissues (center of glioblastoma multiforme, tissues from infiltration area and normally appeared white matter) and principal component analysis. We applied the support vector machine to classify tissues after dimensionality reduction of registered Raman spectra. The accuracy of the classification of malignant tissues (tumor edge and center) and normal ones using the principal component analysis alone was 83% with sensitivity of 96% and specificity of 44%. With a combined technique of dimensionality reduction we obtained 83% accuracy with 77% sensitivity and 92% specificity of tumor tissues classification.
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Affiliation(s)
- Igor Romanishkin
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
- *Correspondence: Igor Romanishkin,
| | - Tatiana Savelieva
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
- National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russia
| | - Alexandra Kosyrkova
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Vladimir Okhlopkov
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Svetlana Shugai
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Arseniy Orlov
- National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russia
| | - Alexander Kravchuk
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Sergey Goryaynov
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Denis Golbin
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Galina Pavlova
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
- Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia
| | - Igor Pronin
- N.N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russia
| | - Victor Loschenov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow, Russia
- National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russia
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9
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Pekov SI, Zhvansky ES, Eliferov VA, Sorokin AA, Ivanov DG, Nikolaev EN, Popov IA. Determination of Brain Tissue Samples Storage Conditions for Reproducible Intraoperative Lipid Profiling. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27082587. [PMID: 35458785 PMCID: PMC9029908 DOI: 10.3390/molecules27082587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 11/16/2022]
Abstract
Ex-vivo molecular profiling has recently emerged as a promising method for intraoperative tissue identification, especially in neurosurgery. The short-term storage of resected samples at room temperature is proposed to have negligible influence on the lipid molecular profiles. However, a detailed investigation of short-term molecular profile stability is required to implement molecular profiling in a clinic. This study evaluates the effect of storage media, temperature, and washing solution to determine conditions that provide stable and reproducible molecular profiles, with the help of ambient ionization mass spectrometry using rat cerebral cortex as model brain tissue samples. Utilizing normal saline for sample storage and washing media shows a positive effect on the reproducibility of the spectra; however, the refrigeration shows a negligible effect on the spectral similarity. Thus, it was demonstrated that up to hour-long storage in normal saline, even at room temperature, ensures the acquisition of representative molecular profiles using ambient ionization mass spectrometry.
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Affiliation(s)
- Stanislav I. Pekov
- Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- Siberian State Medical University, 634050 Tomsk, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
| | - Evgeny S. Zhvansky
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Vasily A. Eliferov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Anatoly A. Sorokin
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- Department of Biochemistry and Systems Biology, Faculty of Health and Life Sciences, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3BX, UK
| | - Daniil G. Ivanov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
| | - Eugene N. Nikolaev
- Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
| | - Igor A. Popov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (E.S.Z.); (V.A.E.); (A.A.S.); (D.G.I.)
- National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov, 117997 Moscow, Russia
- Correspondence: (S.I.P.); (E.N.N); (I.A.P.)
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10
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Iturrioz-Rodríguez N, De Pasquale D, Fiaschi P, Ciofani G. Discrimination of glioma patient-derived cells from healthy astrocytes by exploiting Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 269:120773. [PMID: 34952436 DOI: 10.1016/j.saa.2021.120773] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 11/29/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. It presents a very bad prognosis with a patients' overall survival of 12-15 months; treatment failure is mainly ascribable to tumor recurrence. The development of new tools, that could help the precise detection of the tumor border, is thus an urgent need. During the last decades, different vibrational spectroscopy techniques have been developed to distinguish cancer tissue from heathy tissue; in the present work, we compared GBM cells deriving from four patients with healthy human astrocytes using Raman spectroscopy. We have shown that the region between 1000 and 1300 cm-1 is enough informative for this discrimination, indeed highlighting that peaks related to DNA/RNA and cytochrome c are increased in cancer cells. Finally, our model has been able to discriminate cancer cells from healthy cells with an average accuracy of 92.5%. We believe that this study might help to further understand which are the essential Raman peaks exploitable in the detection of cancer cells, with important perspectives under a diagnostic point of view.
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Affiliation(s)
- Nerea Iturrioz-Rodríguez
- Istituto Italiano di Tecnologia, Smart Bio-Interfaces, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.
| | - Daniele De Pasquale
- Istituto Italiano di Tecnologia, Smart Bio-Interfaces, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy
| | - Pietro Fiaschi
- San Martino Policlinico Hospital, Department of Neurosurgery, IRCCS for Oncology and Neurosciences, Largo Rosanna Benzi 10, 16132 Genova, Italy; University of Genoa, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI), Largo Paolo Daneo 3, 16132 Genova, Italy
| | - Gianni Ciofani
- Istituto Italiano di Tecnologia, Smart Bio-Interfaces, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.
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11
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Adams WR, Gautam R, Locke A, Masson LE, Borrachero-Conejo AI, Dollinger B, Throckmorton GA, Duvall C, Jansen ED, Mahadevan-Jansen A. Visualizing Lipid Dynamics Role in Infrared Neural Stimulation using Stimulated Raman Scattering. Biophys J 2022; 121:1525-1540. [PMID: 35276133 PMCID: PMC9072573 DOI: 10.1016/j.bpj.2022.03.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/14/2021] [Accepted: 03/04/2022] [Indexed: 11/02/2022] Open
Abstract
Infrared neural stimulation, or INS, uses pulsed infrared light to yield label-free neural stimulation with broad experimental and translational utility. Despite its robust demonstration, INS's mechanistic and biophysical underpinnings have been the subject of debate for more than a decade. The role of lipid membrane thermodynamics appears to play an important role in how fast IR-mediated heating nonspecifically drives action potential generation. Direct observation of lipid membrane dynamics during INS remains to be shown in a live neural model system. We used hyperspectral stimulated Raman scattering (hsSRS) microscopy to study biochemical signatures of high-speed vibrational dynamics underlying INS in a live neural cell culture model. Findings suggest that lipid bilayer structural changes are occurring during INS in vitro in NG108-15 neuroglioma cells. Lipid-specific signatures of cell SRS spectra varied with stimulation energy and radiant exposure. Spectroscopic observations agree with high-speed ratiometric fluorescence imaging of a conventional lipophilic membrane structure reporter, di-4-ANNEPS. Overall, the presented findings support the hypothesis that INS causes changes in the lipid membrane of neural cells by changing lipid membrane packing order. Furthermore, this work highlights the potential of hsSRS as a method to study biophysical and biochemical dynamics safely in live cells.
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Affiliation(s)
- Wilson R Adams
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Rekha Gautam
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Andrea Locke
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Laura E Masson
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | | | - Bryan Dollinger
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | | | - Craig Duvall
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - E Duco Jansen
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Dept. of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anita Mahadevan-Jansen
- Dept. of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Dept. of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA.
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Davies DJ, Hadis M, Di Pietro V, Lazzarino G, Forcione M, Harris G, Stevens AR, Soon WC, Goldberg Oppenheimer P, Milward M, Belli A, Palin WM. Photobiomodulation reduces hippocampal apoptotic cell death and produces a Raman spectroscopic “signature”. PLoS One 2022; 17:e0264533. [PMID: 35239693 PMCID: PMC8893683 DOI: 10.1371/journal.pone.0264533] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 02/11/2022] [Indexed: 11/18/2022] Open
Abstract
Apoptotic cell death within the brain represents a significant contributing factor to impaired post-traumatic tissue function and poor clinical outcome after traumatic brain injury. After irradiation with light in the wavelength range of 600–1200 nm (photobiomodulation), previous investigations have reported a reduction in apoptosis in various tissues. This study investigates the effect of 660 nm photobiomodulation on organotypic slice cultured hippocampal tissue of rats, examining the effect on apoptotic cell loss. Tissue optical Raman spectroscopic changes were evaluated. A significantly higher proportion of apoptotic cells 62.8±12.2% vs 48.6±13.7% (P<0.0001) per region were observed in the control group compared with the photobiomodulation group. After photobiomodulation, Raman spectroscopic observations demonstrated 1440/1660 cm-1 spectral shift. Photobiomodulation has the potential for therapeutic utility, reducing cell loss to apoptosis in injured neurological tissue, as demonstrated in this in vitro model. A clear Raman spectroscopic signal was observed after apparent optimal irradiation, potentially integrable into therapeutic light delivery apparatus for real-time dose metering.
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Affiliation(s)
- David J. Davies
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
- National Institute of Health Research Surgical Reconstruction and Microbiology Research Centre, University Hospitals Birmingham’ Edgbaston, Birmingham, United Kingdom
- * E-mail:
| | - Mohammed Hadis
- Photobiology Research Group, School of Dentistry, College of Medical and Dental Science, Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Valentina Di Pietro
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
| | - Giuseppe Lazzarino
- Department of Chemical Sciences, Laboratory of Biochemistry, University of Catania, Catania, Italy
| | - Mario Forcione
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
- National Institute of Health Research Surgical Reconstruction and Microbiology Research Centre, University Hospitals Birmingham’ Edgbaston, Birmingham, United Kingdom
| | - Georgia Harris
- Faculty of Chemical and Biological Engineering, University of Birmingham, Birmingham, United Kingdom
| | - Andrew R. Stevens
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
- National Institute of Health Research Surgical Reconstruction and Microbiology Research Centre, University Hospitals Birmingham’ Edgbaston, Birmingham, United Kingdom
| | - Wai Cheong Soon
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
| | - Pola Goldberg Oppenheimer
- Faculty of Chemical and Biological Engineering, University of Birmingham, Birmingham, United Kingdom
| | - Michael Milward
- Photobiology Research Group, School of Dentistry, College of Medical and Dental Science, Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Antonio Belli
- Department of Neuroscience and Ophthalmology, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
- National Institute of Health Research Surgical Reconstruction and Microbiology Research Centre, University Hospitals Birmingham’ Edgbaston, Birmingham, United Kingdom
| | - William M. Palin
- Photobiology Research Group, School of Dentistry, College of Medical and Dental Science, Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
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Willenbacher E, Brunner A, Zelger B, Unterberger SH, Stalder R, Huck CW, Willenbacher W, Pallua JD. Application of mid-infrared microscopic imaging for the diagnosis and classification of human lymphomas. JOURNAL OF BIOPHOTONICS 2021; 14:e202100079. [PMID: 34159739 DOI: 10.1002/jbio.202100079] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 06/15/2021] [Accepted: 06/15/2021] [Indexed: 06/13/2023]
Abstract
Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis.
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Affiliation(s)
- Ella Willenbacher
- Internal Medicine V: Hematology & Oncology, Medical University of Innsbruck, Innsbruck, Austria
| | - Andrea Brunner
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - Bettina Zelger
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Roland Stalder
- Institute of Mineralogy and Petrography, Leopold-Franzens University Innsbruck, Innsbruck, Austria
| | - Christian W Huck
- Institute of Analytical Chemistry and Radiochemistry, Innsbruck, Austria
| | - Wolfgang Willenbacher
- Internal Medicine V: Hematology & Oncology, Medical University of Innsbruck, Innsbruck, Austria
- Oncotyrol, Center for personalized Cancer Medicine, Innsbruck, Austria
| | - Johannes D Pallua
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
- University Hospital for Orthopedics and Traumatology, Medical University of Innsbruck, Innsbruck, Austria
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Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies. Cancers (Basel) 2021; 13:cancers13164196. [PMID: 34439355 PMCID: PMC8392399 DOI: 10.3390/cancers13164196] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/12/2021] [Accepted: 08/16/2021] [Indexed: 11/26/2022] Open
Abstract
Simple Summary Isocitrate dehydrogenase (IDH) mutation is one of the most important prognostic markers in glioma tumors. Raman spectroscopy (RS) is an optical technique with great potential in intraoperative molecular diagnosis and surgical guidance. We analyzed RS’s ability to detect the IDH mutation onto unprocessed glioma biopsies. A total of 2073 Raman spectra were extracted from 38 tumor specimens. From the 103 Raman shifts screened, we identified 52 shifts (related to lipids, collagen, DNA and cholesterol/phospholipids) with the highest performance in the distinction of the two groups. We described 18 shifts never used before for IDH detection with RS in fresh or frozen samples. We were able to distinguish between IDH-mutated and IDH-wild-type tumors with an accuracy and precision of 87%. RS showed optimal accuracy and precision in discriminating IDH-mutated glioma from IDH-wild-type tumors ex-vivo onto fresh surgical specimens. Abstract Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.
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Livermore LJ, Isabelle M, Bell IM, Edgar O, Voets NL, Stacey R, Ansorge O, Vallance C, Plaha P. Raman spectroscopy to differentiate between fresh tissue samples of glioma and normal brain: a comparison with 5-ALA-induced fluorescence-guided surgery. J Neurosurg 2021; 135:469-479. [PMID: 33007757 DOI: 10.3171/2020.5.jns20376] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/22/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Raman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)-induced fluorescence. METHODS A principal component analysis (PCA)-fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA-induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor. RESULTS The PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA-induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA-induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009). CONCLUSIONS Raman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA-induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA-induced fluorescence to guide extent of resection in glioma surgery.
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Affiliation(s)
- Laurent J Livermore
- 1Nuffield Department of Clinical Neurosciences, and
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
| | - Martin Isabelle
- 4Renishaw plc, Spectroscopy Products Division, Gloucestershire
| | - Ian M Bell
- 4Renishaw plc, Spectroscopy Products Division, Gloucestershire
| | - Oliver Edgar
- 1Nuffield Department of Clinical Neurosciences, and
| | - Natalie L Voets
- 2Nuffield Department of Surgery, University of Oxford, John Radcliffe Hospital, Oxford
- 6FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Richard Stacey
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
| | - Olaf Ansorge
- 1Nuffield Department of Clinical Neurosciences, and
| | | | - Puneet Plaha
- 2Nuffield Department of Surgery, University of Oxford, John Radcliffe Hospital, Oxford
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
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16
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Kostrikov S, Johnsen KB, Braunstein TH, Gudbergsson JM, Fliedner FP, Obara EAA, Hamerlik P, Hansen AE, Kjaer A, Hempel C, Andresen TL. Optical tissue clearing and machine learning can precisely characterize extravasation and blood vessel architecture in brain tumors. Commun Biol 2021; 4:815. [PMID: 34211069 PMCID: PMC8249617 DOI: 10.1038/s42003-021-02275-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/25/2021] [Indexed: 02/06/2023] Open
Abstract
Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challenging the development of new therapeutics for brain disorders. Transcardial perfusion is instrumental for removing the intravascular fraction of an injected compound, thereby allowing for ex vivo assessment of extravasation into the brain. However, pathological remodeling of tissue microenvironment can affect the efficiency of transcardial perfusion, which has been largely overlooked. We show that, in contrast to healthy vasculature, transcardial perfusion cannot remove an injected compound from the tumor vasculature to a sufficient extent leading to considerable overestimation of compound extravasation. We demonstrate that 3D deep imaging of optically cleared tumor samples overcomes this limitation. We developed two machine learning-based semi-automated image analysis workflows, which provide detailed quantitative characterization of compound extravasation patterns as well as tumor angioarchitecture in large three-dimensional datasets from optically cleared samples. This methodology provides a precise and comprehensive analysis of extravasation in brain tumors and allows for correlation of extravasation patterns with specific features of the heterogeneous brain tumor vasculature.
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Affiliation(s)
- Serhii Kostrikov
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Kasper B Johnsen
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Thomas H Braunstein
- Core Facility for Integrated Microscopy, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Johann M Gudbergsson
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
- Laboratory for Neurobiology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Frederikke P Fliedner
- Department of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Department of Biomedical Sciences, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark
- Department of Biomedical Sciences, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark
| | - Elisabeth A A Obara
- Brain Tumor Biology, Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Clinical Biochemistry, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Bispebjerg, Denmark
| | - Petra Hamerlik
- Brain Tumor Biology, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anders E Hansen
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Andreas Kjaer
- Department of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Department of Biomedical Sciences, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark
- Department of Biomedical Sciences, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark
| | - Casper Hempel
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
| | - Thomas L Andresen
- Section for Biotherapeutic Engineering and Drug Targeting, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.
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Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples. Cancers (Basel) 2021; 13:cancers13051073. [PMID: 33802369 PMCID: PMC7959285 DOI: 10.3390/cancers13051073] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/17/2021] [Accepted: 02/25/2021] [Indexed: 12/14/2022] Open
Abstract
Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.
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Hollon T, Orringer DA. Label-free brain tumor imaging using Raman-based methods. J Neurooncol 2021; 151:393-402. [PMID: 33611706 DOI: 10.1007/s11060-019-03380-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 12/20/2019] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes. METHODS Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH). RESULTS Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of -CH2 bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the development of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively. CONCLUSIONS These results demonstrate how label-free Raman-based imaging methods can be used to improve the management of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.
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Abstract
This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.
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Chaichi A, Hasan SMA, Mehta N, Donnarumma F, Ebenezer P, Murray KK, Francis J, Gartia MR. Label-free lipidome study of paraventricular thalamic nucleus (PVT) of rat brain with post-traumatic stress injury by Raman imaging. Analyst 2021; 146:170-183. [PMID: 33135036 DOI: 10.1039/d0an01615b] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Post-traumatic stress disorder (PTSD) is a widespread psychiatric injury that develops serious life-threatening symptoms like substance abuse, severe depression, cognitive impairments, and persistent anxiety. However, the mechanisms of post-traumatic stress injury in brain are poorly understood due to the lack of practical methods to reveal biochemical alterations in various brain regions affected by this type of injury. Here, we introduce a novel method that provides quantitative results from Raman maps in the paraventricular nucleus of the thalamus (PVT) region. By means of this approach, we have shown a lipidome comparison in PVT regions of control and PTSD rat brains. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry was also employed for validation of the Raman results. Lipid alterations can reveal invaluable information regarding the PTSD mechanisms in affected regions of brain. We have showed that the concentration of cholesterol, cholesteryl palmitate, phosphatidylinositol, phosphatidylserine, phosphatidylethanolamine, sphingomyelin, ganglioside, glyceryl tripalmitate and sulfatide changes in the PVT region of PTSD compared to control rats. A higher concentration of cholesterol suggests a higher level of corticosterone in the brain. Moreover, concentration changes of phospholipids and sphingolipids suggest the alteration of phospholipase A2 (PLA2) which is associated with inflammatory processes in the brain. Our results have broadened the understanding of biomolecular mechanisms for PTSD in the PVT region of the brain. This is the first report regarding the application of Raman spectroscopy for PTSD studies. This method has a wide spectrum of applications and can be applied to various other brain related disorders or other regions of the brain.
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Affiliation(s)
- Ardalan Chaichi
- Department of Mechanical and Industrial Engineering, Louisiana State University, Baton Rouge, LA 70803, USA.
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Bik E, Mateuszuk L, Stojak M, Chlopicki S, Baranska M, Majzner K. Menadione-induced endothelial inflammation detected by Raman spectroscopy. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2020; 1868:118911. [PMID: 33227312 DOI: 10.1016/j.bbamcr.2020.118911] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 11/13/2020] [Accepted: 11/18/2020] [Indexed: 12/24/2022]
Abstract
In this work, the effect of an early oxidative stress on human endothelial cells induced by menadione was studied using a combined methodology of label-free Raman imaging and fluorescence staining. Menadione-induced ROS-dependent endothelial inflammation in human aorta endothelial cells (HAEC) was studied with focus on changes in cytochrome, proteins, nucleic acids and lipids content and their distribution in cells. Fluorescence staining (ICAM-1, VCAM-1, vWF, LipidTox, MitoRos and DCF) was used to confirm endothelial inflammation and ROS generation. The results showed that short time, exposure to menadione did not cause their apoptosis or necrosis (Annexin V Apoptosis Detection Kit) within the 3 h timescale of measurement. On the other hand, 3 h of incubation, did result in endothelial inflammation (ICAM-1, VCAM-1, vWF) that was associated with an increased ROS formation (MitoRos and DCF) suggesting the oxidative stress-mediated inflammation. Chemometric analysis of spectral data enabled the determination of spectroscopic markers of menadione-induced oxidative stress-mediated endothelial inflammation including a decrease of the bands intensity of cytochrome (604, 750, 1128, 1315 and 1585 cm-1), nucleic acids bands (785 cm-1), proteins (1005 cm-1) and increased intensity of lipid bands (722, 1085, 1265, 1303, 1445 and 1660 cm-1), without changes in the spectroscopic signature of the cell nucleus. In conclusion, oxidative stress resulting in endothelial inflammation was featured by significant alterations in the number of biochemical changes in mitochondria and other cellular compartments detected by Raman spectroscopy. Most of these, coexisted with results from fluorescence imaging, and most importantly occurred earlier than the detection of increased ROS or markers of endothelial inflammation.
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Affiliation(s)
- Ewelina Bik
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland; Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland
| | - Lukasz Mateuszuk
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland
| | - Marta Stojak
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland
| | - Stefan Chlopicki
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland; Chair of Pharmacology, Jagiellonian University, Medical College 16 Grzegorzecka Str., 31-531 Krakow, Poland
| | - Malgorzata Baranska
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland; Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland
| | - Katarzyna Majzner
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland; Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland.
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Abstract
Neurosurgery of intracranial tumors, especially of glial origin, is a non-trivial task due to their infiltrative growth. In recent years, optical methods of intraoperative navigation have been actively used in neurosurgery. However, one of the most widely used approaches based on the selective accumulation of fluorescent contrast medium (5-ALA-induced protoporphyrin IX) by the tumor cannot be applied to a significant number of tumors due to its low accumulation. On the contrary, Raman spectroscopy, which allows analyzing the molecular composition of tissues while preserving all the advantages of the method of fluorescence spectroscopy, does not require the use of an exogenous dye and may become a method of choice when composing a system for intraoperative navigation or optical biopsy. This work presents the first results of using the principal component method to classify Raman spectra of human glioblastoma with intermediate processing of spectra to minimize possible errors from the fluorescence of both endogenous fluorophores and photosensitizers used in fluorescence navigation. As a result, differences were found in the principal component space, corresponding to tissue samples with microcystic components, extensive areas of necrosis, and foci of fresh hemorrhages. It is shown that this approach can serve as the basis for constructing a system for automatic intraoperative tissue classification based on the analysis of Raman spectra.
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Abstract
In neurosurgery, the extent of resection plays a critical role, especially in the management of malignant gliomas. These tumors are characterized through a diffuse infiltration into the surrounding brain parenchyma. Delineation between tumor and normal brain parenchyma can therefore often be challenging. During the recent years, several techniques, aiming at better intraoperative tumor visualization, have been developed and implemented in the field of brain tumor surgery. In this chapter, we discuss current strategies for intraoperative imaging in brain tumor surgery, comprising conventional techniques such as neuronavigation, techniques using fluorescence-guided surgery, and further highly precise developments such as targeted fluorescence spectroscopy or Raman spectroscopy.
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Affiliation(s)
- Stephanie Schipmann-Miletić
- Department of Neurosurgery, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, 48149, Münster, Germany.
| | - Walter Stummer
- Department of Neurosurgery, University Hospital Münster, Albert-Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
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24
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DePaoli D, Lemoine É, Ember K, Parent M, Prud’homme M, Cantin L, Petrecca K, Leblond F, Côté DC. Rise of Raman spectroscopy in neurosurgery: a review. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-36. [PMID: 32358930 PMCID: PMC7195442 DOI: 10.1117/1.jbo.25.5.050901] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/10/2020] [Indexed: 05/21/2023]
Abstract
SIGNIFICANCE Although the clinical potential for Raman spectroscopy (RS) has been anticipated for decades, it has only recently been used in neurosurgery. Still, few devices have succeeded in making their way into the operating room. With recent technological advancements, however, vibrational sensing is poised to be a revolutionary tool for neurosurgeons. AIM We give a summary of neurosurgical workflows and key translational milestones of RS in clinical use and provide the optics and data science background required to implement such devices. APPROACH We performed an extensive review of the literature, with a specific emphasis on research that aims to build Raman systems suited for a neurosurgical setting. RESULTS The main translatable interest in Raman sensing rests in its capacity to yield label-free molecular information from tissue intraoperatively. Systems that have proven usable in the clinical setting are ergonomic, have a short integration time, and can acquire high-quality signal even in suboptimal conditions. Moreover, because of the complex microenvironment of brain tissue, data analysis is now recognized as a critical step in achieving high performance Raman-based sensing. CONCLUSIONS The next generation of Raman-based devices are making their way into operating rooms and their clinical translation requires close collaboration between physicians, engineers, and data scientists.
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Affiliation(s)
- Damon DePaoli
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
| | - Émile Lemoine
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Katherine Ember
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Martin Parent
- Université Laval, CERVO Brain Research Center, Québec, Canada
| | - Michel Prud’homme
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Léo Cantin
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, Montreal, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Daniel C. Côté
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
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25
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Lemoine É, Dallaire F, Yadav R, Agarwal R, Kadoury S, Trudel D, Guiot MC, Petrecca K, Leblond F. Feature engineering applied to intraoperative in vivo Raman spectroscopy sheds light on molecular processes in brain cancer: a retrospective study of 65 patients. Analyst 2020; 144:6517-6532. [PMID: 31647061 DOI: 10.1039/c9an01144g] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Raman spectroscopy is a promising tool for neurosurgical guidance and cancer research. Quantitative analysis of the Raman signal from living tissues is, however, limited. Their molecular composition is convoluted and influenced by clinical factors, and access to data is limited. To ensure acceptance of this technology by clinicians and cancer scientists, we need to adapt the analytical methods to more closely model the Raman-generating process. Our objective is to use feature engineering to develop a new representation for spectral data specifically tailored for brain diagnosis that improves interpretability of the Raman signal while retaining enough information to accurately predict tissue content. The method consists of band fitting of Raman bands which consistently appear in the brain Raman literature, and the generation of new features representing the pairwise interaction between bands and the interaction between bands and patient age. Our technique was applied to a dataset of 547 in situ Raman spectra from 65 patients undergoing glioma resection. It showed superior predictive capacities to a principal component analysis dimensionality reduction. After analysis through a Bayesian framework, we were able to identify the oncogenic processes that characterize glioma: increased nucleic acid content, overexpression of type IV collagen and shift in the primary metabolic engine. Our results demonstrate how this mathematical transformation of the Raman signal allows the first biological, statistically robust analysis of in vivo Raman spectra from brain tissue.
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Affiliation(s)
- Émile Lemoine
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Quebec, Canada.
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26
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Wöss C, Unterberger SH, Degenhart G, Akolkar A, Traxl R, Kuhn V, Schirmer M, Pallua AK, Tappert R, Pallua JD. Comparison of structure and composition of a fossil Champsosaurus vertebra with modern Crocodylidae vertebrae: A multi-instrumental approach. J Mech Behav Biomed Mater 2020; 104:103668. [PMID: 32174426 DOI: 10.1016/j.jmbbm.2020.103668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/29/2020] [Accepted: 02/01/2020] [Indexed: 11/30/2022]
Abstract
Information on the adaptation of bone structures during evolution is rare since histological data are limited. Micro- and nano-computed tomography of a fossilized vertebra from Champsosaurus sp., which has an estimated age of 70-73 million years, revealed lower porosity and higher bone density compared to modern Crocodylidae vertebrae. Mid-infrared reflectance and energy dispersive X-ray mapping excluded a petrification process, and demonstrated a typical carbonate apatite distribution, confirming histology in light- and electron microscopy of the preserved vertebra. As a consequence of this evolutionary process, the two vertebrae of modern Crocodylidae show reduced overall stiffness in the finite element analysis simulation compared to the fossilized Champsosaurus sp. vertebra, with predominant stiffness along the longitudinal z-axes.
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Affiliation(s)
- C Wöss
- Institute of Legal Medicine, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria
| | - S H Unterberger
- Unit for Material Technology, University of Innsbruck, Technikerstraße 13, 6020, Innsbruck, Austria
| | - G Degenhart
- Department of Radiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - A Akolkar
- Illwerke vkw Professorship for Energy Efficiency, Vorarlberg University of Applied Sciences, Hochschulstraße 1, 6850, Dornbirn, Austria; Josef Ressel Center for Applied Computational Science in Energy, Finance, and Logistics, Hochschulstraße 1, 6850, Dornbirn, Austria
| | - R Traxl
- Unit for Material Technology, University of Innsbruck, Technikerstraße 13, 6020, Innsbruck, Austria
| | - V Kuhn
- Department of Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - M Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - A K Pallua
- Former Institute for Computed Tomography-Neuro CT, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria
| | - R Tappert
- Hyperspectral Intelligence Inc., Box 851, Gibsons, British Columbia, V0N 1V0, Canada
| | - J D Pallua
- Institute of Legal Medicine, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria; Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria.
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27
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Galli R, Meinhardt M, Koch E, Schackert G, Steiner G, Kirsch M, Uckermann O. Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy-A Study of 209 Patients. Front Oncol 2019; 9:1165. [PMID: 31750251 PMCID: PMC6848276 DOI: 10.3389/fonc.2019.01165] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 10/17/2019] [Indexed: 01/09/2023] Open
Abstract
In brain surgery, novel technologies are continuously developed to achieve better tumor delineation and maximize the extent of resection. Raman spectroscopy is an optical method that enables to retrieve a molecular signature of tissue biochemical composition in order to identify tumor and normal tissue. Here, the translation of Raman spectroscopy to the surgical practice for discerning a variety of different tumor entities from non-neoplastic brain parenchyma was investigated. Fresh unprocessed biopsies obtained from brain tumor surgery were analyzed over 1.5 years including all patients that gave consent. Measurements were performed with a Raman microscope by medical personnel as routine activity. The Raman and fluorescence signals of the acquired spectra were analyzed by principal component analysis, followed by supervised classification to discriminate non-tumor tissue vs. tumor and distinguish tumor entities. Histopathology of the measured biopsies was performed as reference. Classification led to the correct recognition of all non-neoplastic biopsies (7/7) and of 97% of the investigated tumor biopsies (195/202). For instance, GBM was recognized as tumor with a correct rate of 94% if primary, and of 100% if recurrent. Astrocytoma and oligodendroglioma were recognized as tumor with correct rates of 86 and 90%, respectively. All brain metastases, meningioma and schwannoma were correctly recognized as tumor and distinguished from non-neoplastic brain tissue. Furthermore, metastases were discerned from glioma with correct rate of 90%. Oligodendroglioma and astrocytoma IDH1-mutant, which differ in the presence of 1p/19q codeletion, were discerned with a correct rate of 81%. These results demonstrate the feasibility of rapid brain tumors recognition and extraction of diagnostic information by Raman spectroscopy, using a protocol that can be easily included in the routine surgical workflow.
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Affiliation(s)
- Roberta Galli
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Matthias Meinhardt
- Neuropathology, Institute of Pathology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Edmund Koch
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Gabriele Schackert
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Gerald Steiner
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Matthias Kirsch
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Ortrud Uckermann
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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28
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Zhou Y, Liu CH, Wu B, Yu X, Cheng G, Zhu K, Wang K, Zhang C, Zhao M, Zong R, Zhang L, Shi L, Alfano RR. Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-12. [PMID: 31512439 PMCID: PMC6997631 DOI: 10.1117/1.jbo.24.9.095001] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 07/26/2019] [Indexed: 05/06/2023]
Abstract
Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.
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Affiliation(s)
- Yan Zhou
- PLA Air Force Medical Center, Department of Neurosurgery, Beijing, China
| | - Cheng-Hui Liu
- City University of New York, Institute for Ultrafast Spectroscopy and Lasers, Department of Physics of the City College, New York, United States
| | - Binlin Wu
- Southern Connecticut State University, CSCU Center for Nanotechnology, Physics Department, New Haven, Connecticut, United States
| | - Xinguang Yu
- PLA General Hospital, Department of Neurosurgery, Beijing, China
| | - Gangge Cheng
- PLA Air Force Medical Center, Department of Neurosurgery, Beijing, China
| | - Ke Zhu
- Chinese Academy of Sciences, Institute of Physics, Beijing, China
| | - Kai Wang
- Jilin University, State Key Laboratory of Superhard Materials, Changchun, China
| | - Chunyuan Zhang
- City University of New York, Institute for Ultrafast Spectroscopy and Lasers, Department of Physics of the City College, New York, United States
| | - Mingyue Zhao
- PLA Air Force Medical Center, Department of Neurosurgery, Beijing, China
| | - Rui Zong
- PLA General Hospital, Department of Neurosurgery, Beijing, China
| | - Lin Zhang
- City University of New York, Institute for Ultrafast Spectroscopy and Lasers, Department of Physics of the City College, New York, United States
| | - Lingyan Shi
- University of California San Diego, Department of Bioengineering, La Jolla, California, United States
| | - Robert R. Alfano
- City University of New York, Institute for Ultrafast Spectroscopy and Lasers, Department of Physics of the City College, New York, United States
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29
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Petrokilidou C, Pavlou E, Gaitanis G, Bassukas ID, Saridomichelakis MN, Velegraki A, Kourkoumelis N. The lipid profile of three Malassezia species assessed by Raman spectroscopy and discriminant analysis. Mol Cell Probes 2019; 46:101416. [PMID: 31247316 DOI: 10.1016/j.mcp.2019.06.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 06/21/2019] [Accepted: 06/24/2019] [Indexed: 11/27/2022]
Abstract
Malassezia yeasts constitute the major eukaryotic cutaneous flora of homoeothermic vertebrates. These lipophilic yeasts are able to cause, trigger, or aggravate common skin diseases under favorable conditions. Species identification and subspecies differentiation is currently based on morphological characteristics, lipid assimilation profile, and molecular tests. Mass spectrometry has been also reported as a reliable, yet costly and labor-intensive, method to classify Malassezia yeasts. Here, we introduce Raman spectroscopy as a new molecular technique able to differentiate three phylogenetically close Malassezia species (M.globosa, M.pachydermatis, and M.sympodialis) by examining their lipid metabolic profile. Using Raman spectroscopy, lipid fingerprints of Malassezia cultures on Leeming-Notman agar, were analyzed by spectral bands assignment and partial least squares discriminant analysis. Our results demonstrate differential utilization of lipid supplements among these three species and the ability of Raman spectroscopy to rapidly and accurately discriminate them by predictive modelling.
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Affiliation(s)
- Chrysoula Petrokilidou
- Faculty of Medicine, Department Medical Physics, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Eleftherios Pavlou
- Faculty of Medicine, Department Medical Physics, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Georgios Gaitanis
- Faculty of Medicine, Department of Skin and Venereal Diseases, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Ioannis D Bassukas
- Faculty of Medicine, Department of Skin and Venereal Diseases, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Manolis N Saridomichelakis
- Clinic of Medicine, Faculty of Veterinary Science, School of Health Sciences, University of Thessaly, Karditsa, Greece
| | - Aristea Velegraki
- Microbiology Department, Mycology Research Laboratory & UOA/HCPF Culture Collection, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikolaos Kourkoumelis
- Faculty of Medicine, Department Medical Physics, School of Health Sciences, University of Ioannina, Ioannina, Greece.
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30
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Desroches J, Lemoine É, Pinto M, Marple E, Urmey K, Diaz R, Guiot MC, Wilson BC, Petrecca K, Leblond F. Development and first in-human use of a Raman spectroscopy guidance system integrated with a brain biopsy needle. JOURNAL OF BIOPHOTONICS 2019; 12:e201800396. [PMID: 30636032 DOI: 10.1002/jbio.201800396] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 12/10/2018] [Accepted: 01/09/2019] [Indexed: 05/22/2023]
Abstract
Navigation-guided brain biopsies are the standard of care for diagnosis of several brain pathologies. However, imprecise targeting and tissue heterogeneity often hinder obtaining high-quality tissue samples, resulting in poor diagnostic yield. We report the development and first clinical testing of a navigation-guided fiberoptic Raman probe that allows surgeons to interrogate brain tissue in situ at the tip of the biopsy needle prior to tissue removal. The 900 μm diameter probe can detect high spectral quality Raman signals in both the fingerprint and high wavenumber spectral regions with minimal disruption to the neurosurgical workflow. The probe was tested in three brain tumor patients, and the acquired spectra in both normal brain and tumor tissue demonstrated the expected spectral features, indicating the quality of the data. As a proof-of-concept, we also demonstrate the consistency of the acquired Raman signal with different systems and experimental settings. Additional clinical development is planned to further evaluate the performance of the system and develop a statistical model for real-time tissue classification during the biopsy procedure.
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Affiliation(s)
- Joannie Desroches
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Québec, Canada
- Laboratory of Radiological Optics, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Québec, Canada
| | - Émile Lemoine
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Québec, Canada
- Laboratory of Radiological Optics, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Québec, Canada
| | - Michael Pinto
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Québec, Canada
| | - Eric Marple
- Research and development, EMVision LLC, Loxahatchee, Florida
| | - Kirk Urmey
- Research and development, EMVision LLC, Loxahatchee, Florida
| | - Roberto Diaz
- Brain Tumour Research Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Marie-Christine Guiot
- Division of Neuropathology, Department of Pathology, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
| | - Brian C Wilson
- Laser Biophysics group, Princess Margaret Cancer Centre-University Health Network/University of Toronto, Toronto, Ontario, Canada
| | - Kevin Petrecca
- Brain Tumour Research Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Frédéric Leblond
- Department of Engineering Physics, Polytechnique Montreal, Montreal, Québec, Canada
- Laboratory of Radiological Optics, Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montreal, Québec, Canada
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31
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Pallua JD, Brunner A, Zelger B, Stalder R, Unterberger SH, Schirmer M, Tappert MC. Clinical infrared microscopic imaging: An overview. Pathol Res Pract 2018; 214:1532-1538. [PMID: 30220435 DOI: 10.1016/j.prp.2018.08.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 08/22/2018] [Accepted: 08/26/2018] [Indexed: 11/16/2022]
Abstract
New developments in Mid-infrared microscopic imaging instrumentation and data analysis have turned this method into a conventional technique. This imaging method offers a global analysis of samples, with a resolution close to the cellular level enabling the acquisition of local molecular expression profiles. It is possible to get chemo-morphological information about the tissue status, which represents an essential benefit for future analytical interpretation of pathological changes of tissue. In this review, we give an overview of Mid-infrared microscopic imaging and its applications in clinical research.
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Affiliation(s)
- J D Pallua
- Department of Pathology, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria; Institute of Legal Medicine, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria.
| | - A Brunner
- Department of Pathology, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria
| | - B Zelger
- Department of Pathology, Medical University of Innsbruck, Müllerstraße 44, 6020, Innsbruck, Austria
| | - R Stalder
- Institute of Mineralogy and Petrography, Leopold-Franzens University Innsbruck, Innrain 52, 6020, Innsbruck, Austria
| | - S H Unterberger
- Material-Technology, Leopold-Franzens University Innsbruck, Technikerstraße 13, 6020, Innsbruck, Austria
| | - M Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria
| | - M C Tappert
- Hyperspectral Intelligence Inc., Box 851, V0N 1V0, Gibsons, Canada
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32
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Ryabchykov O, Popp J, Bocklitz T. Fusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples. Front Chem 2018; 6:257. [PMID: 30062092 PMCID: PMC6055053 DOI: 10.3389/fchem.2018.00257] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 06/08/2018] [Indexed: 01/03/2023] Open
Abstract
Despite of a large number of imaging techniques for the characterization of biological samples, no universal one has been reported yet. In this work, a data fusion approach was investigated for combining Raman spectroscopic data with matrix-assisted laser desorption/ionization (MALDI) mass spectrometric data. It betters the image analysis of biological samples because Raman and MALDI information can be complementary to each other. While MALDI spectrometry yields detailed information regarding the lipid content, Raman spectroscopy provides valuable information about the overall chemical composition of the sample. The combination of Raman spectroscopic and MALDI spectrometric imaging data helps distinguishing different regions within the sample with a higher precision than would be possible by using either technique. We demonstrate that a data weighting step within the data fusion is necessary to reveal additional spectral features. The selected weighting approach was evaluated by examining the proportions of variance within the data explained by the first principal components of a principal component analysis (PCA) and visualizing the PCA results for each data type and combined data. In summary, the presented data fusion approach provides a concrete guideline on how to combine Raman spectroscopic and MALDI spectrometric imaging data for biological analysis.
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Affiliation(s)
- Oleg Ryabchykov
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
| | - Juergen Popp
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
| | - Thomas Bocklitz
- Spectroscopy and Imaging Research Department, Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
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33
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Wiercigroch E, Szafraniec E, Czamara K, Pacia MZ, Majzner K, Kochan K, Kaczor A, Baranska M, Malek K. Raman and infrared spectroscopy of carbohydrates: A review. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2017. [PMID: 28599236 DOI: 10.1002/jrs.4607] [Citation(s) in RCA: 582] [Impact Index Per Article: 83.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Carbohydrates are widespread and naturally occurring compounds, and essential constituents for living organisms. They are quite often reported when biological systems are studied and their role is discussed. However surprisingly, up till now there is no database collecting vibrational spectra of carbohydrates and their assignment, as has been done already for other biomolecules. So, this paper serves as a comprehensive review, where for selected 14 carbohydrates in the solid state both FT-Raman and ATR FT-IR spectra were collected and assigned. Carbohydrates can be divided into four chemical groups and in the same way is organized this review. First, the smallest molecules are discussed, i.e. monosaccharides (d-(-)-ribose, 2-deoxy-d-ribose, l-(-)-arabinose, d-(+)-xylose, d-(+)-glucose, d-(+)-galactose and d-(-)-fructose) and disaccharides (d-(+)-sucrose, d-(+)-maltose and d-(+)-lactose), and then more complex ones, i.e. trisaccharides (d-(+)-raffinose) and polysaccharides (amylopectin, amylose, glycogen). Both Raman and IR spectra were collected in the whole spectral range and discussed looking at the specific regions, i.e. region V (3600-3050cm-1), IV (3050-2800cm-1) and II (1200-800cm-1) assigned to the stretching vibrations of the OH, CH/CH2 and C-O/C-C groups, respectively, and region III (1500-1200cm-1) and I (800-100cm-1) dominated by deformational modes of the CH/CH2 and CCO groups, respectively. In spite of the fact that vibrational spectra of saccharides are significantly less specific than spectra of other biomolecules (e.g. lipids or proteins), marker bands of the studied molecules can be identified and correlated with their structure.
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Affiliation(s)
- Ewelina Wiercigroch
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Ewelina Szafraniec
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Krzysztof Czamara
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Marta Z Pacia
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Katarzyna Majzner
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Kamila Kochan
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Agnieszka Kaczor
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland
| | - Malgorzata Baranska
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland.
| | - Kamilla Malek
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland.
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Elastic and inelastic light scattering spectroscopy and its possible use for label-free brain tumor typing. Anal Bioanal Chem 2017; 409:6613-6623. [PMID: 28918486 DOI: 10.1007/s00216-017-0614-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Revised: 07/21/2017] [Accepted: 08/30/2017] [Indexed: 10/18/2022]
Abstract
This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated. Graphical Abstract Bimodal approach for label-free brain tumor typing. Elastic and inelastic light scattering spectra are collected laterally resolved in one measurement setup. The spectra are investigated by multivariate data analysis for assigning the tissues to specific WHO grades according to their malignancy.
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Brusatori M, Auner G, Noh T, Scarpace L, Broadbent B, Kalkanis SN. Intraoperative Raman Spectroscopy. Neurosurg Clin N Am 2017; 28:633-652. [PMID: 28917291 DOI: 10.1016/j.nec.2017.05.014] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Surgical excision of brain tumors provides a means of cytoreduction and diagnosis while minimizing neurologic deficit and improving overall survival. Despite advances in functional and three-dimensional stereotactic navigation and intraoperative MRI, delineating tissue in real time with physiologic confirmation is challenging. Raman spectroscopy has potential to be an important modality in the intraoperative evaluation of tissue during surgical resection. In vitro experimental studies have shown that this technique can be used to differentiate normal brain tissue from tissue with infiltrating cancer cells and dense cancerous masses with high specificity, indicating the feasibility of this method for in vivo application.
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Affiliation(s)
- Michelle Brusatori
- Department of Surgery, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Biomedical Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Smart Sensors and Integrated Microsystems, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA
| | - Gregory Auner
- Department of Surgery, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Biomedical Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Smart Sensors and Integrated Microsystems, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; The Detroit Institute of Ophthalmology, Henry Ford Health System, 15415 E. Jefferson Avenue, Grosse Pointe Park, MI 48230, USA
| | - Thomas Noh
- Department of Neurosurgery, Hermelin Brain Tumor Center, Henry Ford Health System, 2799 West Grand Boulevard, Detroit, MI 48202, USA; Josephine Ford Cancer Center, Henry Ford Health System, 2799 West Grand Boulevard, Detroit, MI 48202, USA
| | - Lisa Scarpace
- Department of Neurosurgery, Hermelin Brain Tumor Center, Henry Ford Health System, 2799 West Grand Boulevard, Detroit, MI 48202, USA
| | - Brandy Broadbent
- Department of Surgery, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Biomedical Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA; Department of Smart Sensors and Integrated Microsystems, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA
| | - Steven N Kalkanis
- Department of Neurosurgery, Hermelin Brain Tumor Center, Henry Ford Health System, 2799 West Grand Boulevard, Detroit, MI 48202, USA; Josephine Ford Cancer Center, Henry Ford Health System, 2799 West Grand Boulevard, Detroit, MI 48202, USA.
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Jurowski K, Kochan K, Walczak J, Barańska M, Piekoszewski W, Buszewski B. Analytical Techniques in Lipidomics: State of the Art. Crit Rev Anal Chem 2017; 47:418-437. [PMID: 28340309 DOI: 10.1080/10408347.2017.1310613] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.
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Affiliation(s)
- Kamil Jurowski
- a Kraków Higher School of Health Promotion , Krakow , Poland
| | - Kamila Kochan
- b Jagiellonian Centre for Experimental Therapeutics (JCET) , Jagiellonian University in Cracow , Cracow , Poland.,c Centre for Biospectroscopy and School of Chemistry , Monash University , Clayton , Victoria , Australia
| | - Justyna Walczak
- d Department of Environmental Chemistry and Bioanalytics , Faculty of Chemistry, Nicolaus Copernicus University , Torun , Poland
| | - Małgorzata Barańska
- b Jagiellonian Centre for Experimental Therapeutics (JCET) , Jagiellonian University in Cracow , Cracow , Poland.,e Department of Chemical Physics, Faculty of Chemistry , Jagiellonian University in Cracow , Cracow , Poland
| | - Wojciech Piekoszewski
- f Department of Analytical Chemistry, Faculty of Chemistry , Jagiellonian University in Cracow , Cracow , Poland.,g School of Biomedicine , Far Eastern Federal University , Vladivostok , Russia
| | - Bogusław Buszewski
- d Department of Environmental Chemistry and Bioanalytics , Faculty of Chemistry, Nicolaus Copernicus University , Torun , Poland
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Woess C, Unterberger SH, Roider C, Ritsch-Marte M, Pemberger N, Cemper-Kiesslich J, Hatzer-Grubwieser P, Parson W, Pallua JD. Assessing various Infrared (IR) microscopic imaging techniques for post-mortem interval evaluation of human skeletal remains. PLoS One 2017; 12:e0174552. [PMID: 28334006 PMCID: PMC5363948 DOI: 10.1371/journal.pone.0174552] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 03/11/2017] [Indexed: 11/18/2022] Open
Abstract
Due to the influence of many environmental processes, a precise determination of the post-mortem interval (PMI) of skeletal remains is known to be very complicated. Although methods for the investigation of the PMI exist, there still remains much room for improvement. In this study the applicability of infrared (IR) microscopic imaging techniques such as reflection-, ATR- and Raman- microscopic imaging for the estimation of the PMI of human skeletal remains was tested. PMI specific features were identified and visualized by overlaying IR imaging data with morphological tissue structures obtained using light microscopy to differentiate between forensic and archaeological bone samples. ATR and reflection spectra revealed that a more prominent peak at 1042 cm-1 (an indicator for bone mineralization) was observable in archeological bone material when compared with forensic samples. Moreover, in the case of the archaeological bone material, a reduction in the levels of phospholipids, proteins, nucleic acid sugars, complex carbohydrates as well as amorphous or fully hydrated sugars was detectable at (reciprocal wavelengths/energies) between 3000 cm-1 to 2800 cm-1. Raman spectra illustrated a similar picture with less ν2PO43-at 450 cm-1 and ν4PO43- from 590 cm-1 to 584 cm-1, amide III at 1272 cm-1 and protein CH2 deformation at 1446 cm-1 in archeological bone material/samples/sources. A semi-quantitative determination of various distributions of biomolecules by chemi-maps of reflection- and ATR- methods revealed that there were less carbohydrates and complex carbohydrates as well as amorphous or fully hydrated sugars in archaeological samples compared with forensic bone samples. Raman- microscopic imaging data showed a reduction in B-type carbonate and protein α-helices after a PMI of 3 years. The calculated mineral content ratio and the organic to mineral ratio displayed that the mineral content ratio increases, while the organic to mineral ratio decreases with time. Cluster-analyses of data from Raman microscopic imaging reconstructed histo-anatomical features in comparison to the light microscopic image and finally, by application of principal component analyses (PCA), it was possible to see a clear distinction between forensic and archaeological bone samples. Hence, the spectral characterization of inorganic and organic compounds by the afore mentioned techniques, followed by analyses such as multivariate imaging analysis (MIAs) and principal component analyses (PCA), appear to be suitable for the post mortem interval (PMI) estimation of human skeletal remains.
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Affiliation(s)
- Claudia Woess
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Clemens Roider
- Division for Biomedical Physics, Medical University of Innsbruck, Innsbruck, Austria
| | - Monika Ritsch-Marte
- Division for Biomedical Physics, Medical University of Innsbruck, Innsbruck, Austria
| | - Nadin Pemberger
- Department of Pharmaceutical Technology, Institute of Pharmacy, Leopold Franzens University of Innsbruck, Innsbruck, Austria
| | - Jan Cemper-Kiesslich
- Interfaculty Department of Legal Medicine, University of Salzburg, Salzburg, Austria
| | | | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Johannes Dominikus Pallua
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
- Department of Pathology, Medical University of Innsbruck, Innsbruck, Austria
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Salerno M, Shayganpour A, Salis B, Dante S. Surface-enhanced Raman scattering of self-assembled thiol monolayers and supported lipid membranes on thin anodic porous alumina. BEILSTEIN JOURNAL OF NANOTECHNOLOGY 2017; 8:74-81. [PMID: 28144566 PMCID: PMC5238693 DOI: 10.3762/bjnano.8.8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 12/12/2016] [Indexed: 05/24/2023]
Abstract
Thin anodic porous alumina (tAPA) was fabricated from a 500 nm thick aluminum (Al) layer coated on silicon wafers, through single-step anodization performed in a Teflon electrochemical cell in 0.4 M aqueous phosphoric acid at 110 V. Post-fabrication etching in the same acid allowed obtaining tAPA surfaces with ≈160 nm pore diameter and ≈80 nm corresponding wall thickness to be prepared. The tAPA surfaces were made SERS-active by coating with a thin (≈25 nm) gold (Au) layer. The as obtained tAPA-Au substrates were incubated first with different thiols, namely mercaptobenzoic acid (MbA) and aminothiol (AT), and then with phospholipid vesicles of different composition to form a supported lipid bilayer (SLB). At each step, the SERS substrate functionality was assessed, demonstrating acceptable enhancement (≥100×). The chemisorption of thiols during the first step and the formation of SLB from the vesicles during the second step, were independently monitored by using a quartz crystal microbalance with dissipation monitoring (QCM-D) technique. The SLB membranes represent a simplified model system of the living cells membranes, which makes the successful observation of SERS on these films promising in view of the use of tAPA-Au substrates as a platform for the development of surface-enhanced Raman spectroscopy (SERS) biosensors on living cells. In the future, these tAPA-Au-SLB substrates will be investigated also for drug delivery of bioactive agents from the APA pores.
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Affiliation(s)
- Marco Salerno
- Department of Nanophysics, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
| | - Amirreza Shayganpour
- Department of Nanophysics, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
- Department of Bioengineering and Robotics, University of Genova, viale Causa 13, I-16145 Genova, Italy
| | - Barbara Salis
- Department of Nanophysics, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
- Department of Bioengineering and Robotics, University of Genova, viale Causa 13, I-16145 Genova, Italy
| | - Silvia Dante
- Department of Nanophysics, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
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Abstract
Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.
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Affiliation(s)
- Lauren A Austin
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown, Massachusetts 02129, USA.
| | - Sam Osseiran
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown, Massachusetts 02129, USA. and Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Avenue E25-519, Cambridge, Massachusetts 02139, USA
| | - Conor L Evans
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown, Massachusetts 02129, USA.
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Desroches J, Laurence A, Jermyn M, Pinto M, Tremblay MA, Petrecca K, Leblond F. Raman spectroscopy in microsurgery: impact of operating microscope illumination sources on data quality and tissue classification. Analyst 2017; 142:1185-1191. [DOI: 10.1039/c6an02061e] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
A filter system to performin vivoRaman spectroscopy measurements under microscope lighting for seamless integration into the surgical workflow.
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Affiliation(s)
| | - Audrey Laurence
- Dept. of Engineering Physics
- Polytechnique Montreal
- Montreal
- Canada
| | - Michael Jermyn
- Montreal Neurological Institute and Hospital
- Dept. of Neurology and Neurosurgery
- McGill University
- Montreal
- Canada
| | - Michael Pinto
- Dept. of Engineering Physics
- Polytechnique Montreal
- Montreal
- Canada
| | | | - Kevin Petrecca
- Montreal Neurological Institute and Hospital
- Dept. of Neurology and Neurosurgery
- McGill University
- Montreal
- Canada
| | - Frédéric Leblond
- Dept. of Engineering Physics
- Polytechnique Montreal
- Montreal
- Canada
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Hollon T, Lewis S, Freudiger CW, Sunney Xie X, Orringer DA. Improving the accuracy of brain tumor surgery via Raman-based technology. Neurosurg Focus 2016; 40:E9. [PMID: 26926067 DOI: 10.3171/2015.12.focus15557] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Despite advances in the surgical management of brain tumors, achieving optimal surgical results and identification of tumor remains a challenge. Raman spectroscopy, a laser-based technique that can be used to nondestructively differentiate molecules based on the inelastic scattering of light, is being applied toward improving the accuracy of brain tumor surgery. Here, the authors systematically review the application of Raman spectroscopy for guidance during brain tumor surgery. Raman spectroscopy can differentiate normal brain from necrotic and vital glioma tissue in human specimens based on chemical differences, and has recently been shown to differentiate tumor-infiltrated tissues from noninfiltrated tissues during surgery. Raman spectroscopy also forms the basis for coherent Raman scattering (CRS) microscopy, a technique that amplifies spontaneous Raman signals by 10,000-fold, enabling real-time histological imaging without the need for tissue processing, sectioning, or staining. The authors review the relevant basic and translational studies on CRS microscopy as a means of providing real-time intraoperative guidance. Recent studies have demonstrated how CRS can be used to differentiate tumor-infiltrated tissues from noninfiltrated tissues and that it has excellent agreement with traditional histology. Under simulated operative conditions, CRS has been shown to identify tumor margins that would be undetectable using standard bright-field microscopy. In addition, CRS microscopy has been shown to detect tumor in human surgical specimens with near-perfect agreement to standard H & E microscopy. The authors suggest that as the intraoperative application and instrumentation for Raman spectroscopy and imaging matures, it will become an essential component in the neurosurgical armamentarium for identifying residual tumor and improving the surgical management of brain tumors.
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Affiliation(s)
- Todd Hollon
- Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan
| | - Spencer Lewis
- Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan
| | | | - X Sunney Xie
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Daniel A Orringer
- Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan
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Mandair GS, Han AL, Keller ET, Morris MD. Raman microscopy of bladder cancer cells expressing green fluorescent protein. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:115001. [PMID: 27805248 PMCID: PMC8357324 DOI: 10.1117/1.jbo.21.11.115001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Accepted: 10/14/2016] [Indexed: 05/06/2023]
Abstract
Gene engineering is a commonly used tool in cellular biology to determine changes in function or expression of downstream targets. However, the impact of genetic modulation on biochemical effects is less frequently evaluated. The aim of this study is to use Raman microscopy to assess the biochemical effects of gene silencing on T24 and UMUC-13 bladder cancer cell lines. Cellular biochemical information related to nucleic acid and lipogenic components was obtained from deconvolved Raman spectra. We show that the green fluorescence protein (GFP), the chromophore that served as a fluorescent reporter for gene silencing, could also be detected by Raman microscopy. Only the gene-silenced UMUC-13 cell lines exhibited low-to-moderate GFP fluorescence as determined by fluorescence imaging and Raman spectroscopic studies. Moreover, we show that gene silencing and cell phenotype had a greater effect on nucleic acid and lipogenic components with minimal interference from GFP expression. Gene silencing was also found to perturb cellular protein secondary structure in which the amount of disorderd protein increased at the expense of more ordered protein. Overall, our study identified the spectral signature for cellular GFP expression and elucidated the effects of gene silencing on cancer cell biochemistry and protein secondary structure.
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Affiliation(s)
- Gurjit S. Mandair
- University of Michigan, School of Dentistry, Department of Biologic and Materials Sciences, 1011 North University Avenue, Ann Arbor, Michigan 48109-1078, United States
- Address all correspondence to: Gurjit S. Mandair, E-mail:
| | - Amy L. Han
- University of Michigan, Department of Urology and Biointerfaces Institute, NCRC Building 20, 2800 Plymouth Road, Ann Arbor, Michigan 48109-2800, United States
| | - Evan T. Keller
- University of Michigan, Department of Urology and Biointerfaces Institute, NCRC Building 20, 2800 Plymouth Road, Ann Arbor, Michigan 48109-2800, United States
| | - Michael D. Morris
- University of Michigan, Department of Chemistry, 930 North University Avenue, Ann Arbor, Michigan 48109-1055, United States
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43
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Ji YB, Oh SJ, Kang SG, Heo J, Kim SH, Choi Y, Song S, Son HY, Kim SH, Lee JH, Haam SJ, Huh YM, Chang JH, Joo C, Suh JS. Terahertz reflectometry imaging for low and high grade gliomas. Sci Rep 2016; 6:36040. [PMID: 27782153 PMCID: PMC5080552 DOI: 10.1038/srep36040] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 10/10/2016] [Indexed: 01/02/2023] Open
Abstract
Gross total resection (GTR) of glioma is critical for improving the survival rate of glioma patients. One of the greatest challenges for achieving GTR is the difficulty in discriminating low grade tumor or peritumor regions that have an intact blood brain barrier (BBB) from normal brain tissues and delineating glioma margins during surgery. Here we present a highly sensitive, label-free terahertz reflectometry imaging (TRI) that overcomes current key limitations for intraoperative detection of World Health Organization (WHO) grade II (low grade), and grade III and IV (high grade) gliomas. We demonstrate that TRI provides tumor discrimination and delineation of tumor margins in brain tissues with high sensitivity on the basis of Hematoxylin and eosin (H&E) stained image. TRI may help neurosurgeons to remove gliomas completely by providing visualization of tumor margins in WHO grade II, III, and IV gliomas without contrast agents, and hence, improve patient outcomes.
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Affiliation(s)
- Young Bin Ji
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seung Jae Oh
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Brain Tumor Center, Brain Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jung Heo
- Department of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea
| | - Sang-Hoon Kim
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
- Applied Electromagnetic Wave Research Center, Korea Electrotechnology Research Institute, Ansan, Republic of Korea
| | - Yuna Choi
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seungri Song
- Department of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hye Young Son
- Severance Biomedical Science Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Se Hoon Kim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ji Hyun Lee
- Department of Neurosurgery, Brain Tumor Center, Brain Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seung Joo Haam
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul, Republic of Korea
| | - Yong Min Huh
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Brain Tumor Center, Brain Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Chulmin Joo
- Department of Mechanical Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jin-Suck Suh
- YUHS-KRIBB Medical Convergence Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
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Woess C, Drach M, Villunger A, Tappert R, Stalder R, Pallua JD. Application of mid-infrared (MIR) microscopy imaging for discrimination between follicular hyperplasia and follicular lymphoma in transgenic mice. Analyst 2015; 140:6363-72. [PMID: 26236782 PMCID: PMC4562367 DOI: 10.1039/c5an01072a] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Mid-infrared (MIR) microscopy imaging is a vibrational spectroscopic technique that uses infrared radiation to image molecules of interest in thin tissue sections. A major advantage of this technology is the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue. Therefore, this technology has become an essential tool for the detection and characterization of the molecular components of many biological processes. Using this method, it is possible to investigate the spatial distribution of proteins and small molecules within biological systems by in situ analysis. In this study, we have evaluated the potential of mid-infrared microscopy imaging to study biochemical changes which distinguish between reactive lymphadenopathy and cancer in genetically modified mice with different phenotypes. We were able to demonstrate that MIR microscopy imaging and multivariate image analyses of different mouse genotypes correlated well with the morphological tissue features derived from HE staining. Using principal component analyses, we were also able to distinguish spectral clusters from different phenotype samples, particularly from reactive lymphadenopathy (follicular hyperplasia) and cancer (follicular lymphoma).
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Affiliation(s)
- C Woess
- Institute of Legal Medicine, Medical University of Innsbruck, Müllerstraße 44, 6020 Innsbruck, Austria.
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45
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A novel direct spray-from-tissue ionization method for mass spectrometric analysis of human brain tumors. Anal Bioanal Chem 2015; 407:7797-805. [PMID: 26277186 DOI: 10.1007/s00216-015-8947-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 07/28/2015] [Accepted: 07/30/2015] [Indexed: 12/20/2022]
Abstract
Real-time feedback about dissected tissue during the neurosurgical procedure is strongly requested. A novel direct ionization mass spectrometric method for identifying pathological differences in tissues is proposed. The method is based on simultaneous extraction of tissue lipids and electrospray ionization which allows mass spectrometric data to be obtained directly from soft tissues. The advantage of this method is the stable flow of solvent, which leads to stable time-dependent spectra. The tissues included necrotized tissues and tumor tissues in different combinations. Capability for direct analysis of samples of dissected tissues during the neurosurgical procedure is demonstrated. Data validation is conducted by compound identification using precise masses from the MS profile, MS/MS, and isotopic distribution structure analysis. The method can be upgraded and applied for real-time identification of tissues during surgery. This paper describes the technique and its application perspective. For these purposes, other methods were compared with the investigated one and the results were shown to be reproducible. Differences in lipid profiles were observed even in tissues from one patient where distinctions between different samples could be poor. The paper presents a proof of concept for the method to be applied in neurosurgery particularly and in tissue analysis generically. The paper also contains preliminary results proving the possibility of observing differences in mass spectra of different tumors.
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46
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Staniszewska-Slezak E, Malek K, Baranska M. Complementary analysis of tissue homogenates composition obtained by Vis and NIR laser excitations and Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2015; 147:245-256. [PMID: 25847786 DOI: 10.1016/j.saa.2015.03.086] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Revised: 03/05/2015] [Accepted: 03/11/2015] [Indexed: 06/04/2023]
Abstract
Raman spectroscopy and four excitation lines in the visible (Vis: 488, 532, 633 nm) and near infrared (NIR: 785 nm) were used for biochemical analysis of rat tissue homogenates, i.e. myocardium, brain, liver, lung, intestine, and kidney. The Vis Raman spectra are very similar for some organs (brain/intestines and kidney/liver) and dominated by heme signals when tissues of lung and myocardium were investigated (especially with 532 nm excitation). On the other hand, the NIR Raman spectra are specific for each tissue and more informative than the corresponding ones collected with the Vis excitations. The spectra analyzed without any special pre-processing clearly illustrate different chemical composition of each tissue and give information about main components e.g. lipids or proteins, but also about the content of some specific compounds such as amino acid residues, nucleotides and nucleobases. However, in order to obtain the whole spectral information about tissues complex composition the spectra of Vis and NIR excitations should be collected and analyzed together. A good agreement of data gathered from Raman spectra of the homogenates and those obtained previously from Raman imaging of the tissue cross-sections indicates that the presented here approach can be a method of choice for an investigation of biochemical variation in animal tissues. Moreover, the Raman spectral profile of tissue homogenates is specific enough to be used for an investigation of potential pathological changes the organism undergoes, in particular when supported by the complementary FTIR spectroscopy.
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Affiliation(s)
- Emilia Staniszewska-Slezak
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland; Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348 Krakow, Poland
| | - Kamilla Malek
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland; Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348 Krakow, Poland.
| | - Malgorzata Baranska
- Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Krakow, Poland; Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Bobrzynskiego 14, 30-348 Krakow, Poland
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Longato S, Wöss C, Hatzer-Grubwieser P, Bauer C, Parson W, Unterberger SH, Kuhn V, Pemberger N, Pallua AK, Recheis W, Lackner R, Stalder R, Pallua JD. Post-mortem interval estimation of human skeletal remains by micro-computed tomography, mid-infrared microscopic imaging and energy dispersive X-ray mapping. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2015; 7:2917-2927. [PMID: 25878731 PMCID: PMC4383336 DOI: 10.1039/c4ay02943g] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Accepted: 02/04/2015] [Indexed: 06/04/2023]
Abstract
In this study different state-of-the-art visualization methods such as micro-computed tomography (micro-CT), mid-infrared (MIR) microscopic imaging and energy dispersive X-ray (EDS) mapping were evaluated to study human skeletal remains for the determination of the post-mortem interval (PMI). PMI specific features were identified and visualized by overlaying molecular imaging data and morphological tissue structures generated by radiological techniques and microscopic images gained from confocal microscopy (Infinite Focus (IFM)). In this way, a more distinct picture concerning processes during the PMI as well as a more realistic approximation of the PMI were achieved. It could be demonstrated that the gained result in combination with multivariate data analysis can be used to predict the Ca/C ratio and bone volume (BV) over total volume (TV) for PMI estimation. Statistical limitation of this study is the small sample size, and future work will be based on more specimens to develop a screening tool for PMI based on the outcome of this multidimensional approach.
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Affiliation(s)
- S Longato
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria .
| | - C Wöss
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria .
| | - P Hatzer-Grubwieser
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria .
| | - C Bauer
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria . ; Department of Internal Medicine IV (Nephrology and Hypertension) , Medical University of Innsbruck , Anichstraße 35 , 6020 Innsbruck , Austria
| | - W Parson
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria . ; Penn State Eberly College of Science , University Park , PA , USA
| | - S H Unterberger
- Material-Technology , Leopold-Franzens University Innsbruck , Technikerstraße 13 , 6020 Innsbruck , Austria
| | - V Kuhn
- Department of Traumatology , Medical University of Innsbruck , Anichstraße 35 , 6020 Innsbruck , Austria
| | - N Pemberger
- Department of Pharmaceutical Technology , Institute of Pharmacy , Leopold Franzens University of Innsbruck , Innrain 52c , 6020 Innsbruck , Austria
| | - Anton K Pallua
- Former Institute for Computed Tomography-Neuro CT , Medical University of Innsbruck , Anichstraße 35 , 6020 Innsbruck , Austria
| | - W Recheis
- Department of Radiology , Medical University of Innsbruck , Anichstraße 35 , 6020 Innsbruck , Austria
| | - R Lackner
- Material-Technology , Leopold-Franzens University Innsbruck , Technikerstraße 13 , 6020 Innsbruck , Austria
| | - R Stalder
- Institute of Mineralogy and Petrography , Leopold-Franzens University Innsbruck , Innrain 52 , 6020 Innsbruck , Austria
| | - J D Pallua
- Institute of Legal Medicine , Medical University of Innsbruck , Müllerstraße 44 , 6020 Innsbruck , Austria .
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48
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Classification and prediction of HCC tissues by Raman imaging with identification of fatty acids as potential lipid biomarkers. J Cancer Res Clin Oncol 2014; 141:407-18. [PMID: 25238702 DOI: 10.1007/s00432-014-1818-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Accepted: 08/27/2014] [Indexed: 12/22/2022]
Abstract
PURPOSE Patients with hepatocellular carcinoma (HCC) can only be treated curatively at early stages and then have a favorable prognosis of this often fatal disease. For this reason, an early detection and diagnostic confirmation are crucial. Raman imaging spectroscopy is a promising technology for high-resolution visualization of the spatial distribution of molecular composition in tissue sections. The aim of this study was to investigate molecular information of liver tissue by Raman imaging for classification and diagnostic prediction. METHODS Unstained cryosections of human hepatic tissues (23 patients) were measured by Raman spectroscope in the regions of HCC (n = 12) and fibrosis (n = 17). The acquired data set was used to generate a random forest classification model with 101 iterations of sevenfold cross-validation. The models obtained during cross-validation were also used to predict regions of tumor margin (n = 8) aside from independent testing. RESULTS Raman spectra differed between malignant and non-malignant tissue regions. Based on these spectral data, a random forest classification model calculated a prediction accuracy of 86 % (76 % sensitivity and 93 % specificity). The ten most important variables were identified at 2895, 2856, 1439, 1298, 1080, 1063, 1023, 937, 920, and 719 cm(-1). CONCLUSIONS In this study, Raman imaging spectroscopy was applied successfully for liver tissue to differentiate, classify, and predict with high accuracy malignant and non-malignant tissue regions. Furthermore, the most important differences were identified as the Raman signature of fatty acids. The demonstrated results highlight the enormous potential which vibrational spectroscopy techniques have for the future diagnostics and prognosis estimation of HCC.
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Assessment of tumor cells in a mouse model of diffuse infiltrative glioma by Raman spectroscopy. BIOMED RESEARCH INTERNATIONAL 2014; 2014:860241. [PMID: 25247190 PMCID: PMC4163456 DOI: 10.1155/2014/860241] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Revised: 06/30/2014] [Accepted: 07/04/2014] [Indexed: 12/13/2022]
Abstract
Glioma of infiltrative nature is challenging for surgeons to achieve tumor-specific and maximal resection. Raman spectroscopy provides structural information on the targeted materials as vibrational shifts. We utilized Raman spectroscopy to distinguish invasive tumors from normal tissues. Spectra obtained from replication-competent avian sarcoma-(RCAS-) based infiltrative glioma cells and glioma tissues (resembling low-grade human glioma) were compared with those obtained from normal mouse astrocytes and normal tissues. In cell analysis, the spectra at 950-1000, 1030, 1050-1100, 1120-1130, 1120-1200, 1200-1300, 1300-1350, and 1450 cm(-1) were significantly higher in infiltrative glioma cells than in normal astrocytes. In brain tissue analysis, the spectra at 1030, 1050-1100, and 1200-1300 cm(-1) were significantly higher in infiltrative glioma tissues than in normal brain tissues. These spectra reflect the structures of proteins, lipids, and DNA content. The sensitivity and specificity to predict glioma cells by distinguishing normal cells were 98.3% and 75.0%, respectively. Principal component analysis elucidated the significance of spectral difference between tumor tissues and normal tissues. It is possible to distinguish invasive tumors from normal tissues by using Raman spectroscopy.
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50
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Kast RE, Auner GW, Rosenblum ML, Mikkelsen T, Yurgelevic SM, Raghunathan A, Poisson LM, Kalkanis SN. Raman molecular imaging of brain frozen tissue sections. J Neurooncol 2014; 120:55-62. [PMID: 25038847 DOI: 10.1007/s11060-014-1536-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Accepted: 07/06/2014] [Indexed: 02/03/2023]
Abstract
Raman spectroscopy provides a molecular signature of the region being studied. It is ideal for neurosurgical applications because it is non-destructive, label-free, not impacted by water concentration, and can map an entire region of tissue. The objective of this paper is to demonstrate the meaningful spatial molecular information provided by Raman spectroscopy for identification of regions of normal brain, necrosis, diffusely infiltrating glioma and solid glioblastoma (GBM). Five frozen section tissues (1 normal, 1 necrotic, 1 GBM, and 2 infiltrating glioma) were mapped in their entirety using a 300-µm-square step size. Smaller regions of interest were also mapped using a 25-µm step size. The relative concentrations of relevant biomolecules were mapped across all tissues and compared with adjacent hematoxylin and eosin-stained sections, allowing identification of normal, GBM, and necrotic regions. Raman peaks and peak ratios mapped included 1003, 1313, 1431, 1585, and 1659 cm(-1). Tissue maps identified boundaries of grey and white matter, necrosis, GBM, and infiltrating tumor. Complementary information, including relative concentration of lipids, protein, nucleic acid, and hemoglobin, was presented in a manner which can be easily adapted for in vivo tissue mapping. Raman spectroscopy can successfully provide label-free imaging of tissue characteristics with high accuracy. It can be translated to a surgical or laboratory tool for rapid, non-destructive imaging of tumor margins.
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Affiliation(s)
- Rachel E Kast
- Electrical and Computer Engineering, Wayne State University, Detroit, MI, 48202, USA
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