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Burström G, Amini M, El-Hajj VG, Arfan A, Gharios M, Buwaider A, Losch MS, Manni F, Edström E, Elmi-Terander A. Optical Methods for Brain Tumor Detection: A Systematic Review. J Clin Med 2024; 13:2676. [PMID: 38731204 PMCID: PMC11084501 DOI: 10.3390/jcm13092676] [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: 04/11/2024] [Revised: 04/28/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.
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Affiliation(s)
- Gustav Burström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Misha Amini
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Victor Gabriel El-Hajj
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Arooj Arfan
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Maria Gharios
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Ali Buwaider
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Merle S. Losch
- Department of Biomechanical Engineering, Faculty of Mechanical Engineering, Delft University of Technology, 2627 Delft, The Netherlands
| | - Francesca Manni
- Department of Electrical Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands;
| | - Erik Edström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
| | - Adrian Elmi-Terander
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
- Department of Surgical Sciences, Uppsala University, 751 35 Uppsala, Sweden
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Murugappan S, Tofail SAM, Thorat ND. Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer. ACS OMEGA 2023; 8:27845-27861. [PMID: 37576695 PMCID: PMC10413827 DOI: 10.1021/acsomega.3c01848] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 07/12/2023] [Indexed: 08/15/2023]
Abstract
Brain cancer is one of those few cancers with very high mortality and low five-year survival rate. First and foremost reason for the woes is the difficulty in diagnosing and monitoring the progression of brain tumors both benign and malignant, noninvasively and in real time. This raises a need in this hour for a tool to diagnose the tumors in the earliest possible time frame. On the other hand, Raman spectroscopy which is well-known for its ability to precisely represent the molecular markers available in any sample given, including biological ones, with great sensitivity and specificity. This has led to a number of studies where Raman spectroscopy has been used in brain tumors in various ways. This review article highlights the fundamentals of Raman spectroscopy and its types including conventional Raman, SERS, SORS, SRS, CARS, etc. are used in brain tumors for diagnostics, monitoring, and even theragnostics, collating all the major works in the area. Also, the review explores how Raman spectroscopy can be even more effectively used in theragnostics and the clinical level which would make them a one-stop solution for all brain cancer needs in the future.
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Affiliation(s)
- Sivasubramanian Murugappan
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
| | - Syed A. M. Tofail
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
| | - Nanasaheb D. Thorat
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
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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: 28] [Impact Index Per Article: 9.3] [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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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 2020; 135:469-479. [PMID: 33007757 DOI: 10.3171/2020.5.jns20376] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [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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Jin H, He X, Zhou H, Zhang M, Tang Q, Lin L, Hao J, Zeng R. Efficacy of raman spectroscopy in the diagnosis of kidney cancer: A systematic review and meta-analysis. Medicine (Baltimore) 2020; 99:e20933. [PMID: 32629694 PMCID: PMC7337610 DOI: 10.1097/md.0000000000020933] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Revised: 05/03/2020] [Accepted: 05/25/2020] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE To comprehensively analyze the relative effectiveness of Raman spectroscopy (RS) in the diagnosis of suspected kidney cancer. PATIENTS AND METHODS We performed a complete systematic review based on studies from PubMed/Medline, EMBASE, Web of Science, Ovid, Web of Knowledge, Cochrane Library and China National Knowledge Infrastructure. We identified 2413 spectra with strict criteria in 6 individual studies published between January 2008 and November 2018 in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We summarized the test performance using random effects models. RESULTS General pooled diagnostic sensitivity and specificity of RS to kidney cancer were 0.96 (95% confidence interval [CI] 0.95-0.97) and 0.91 (95% CI 0.89-0.92). The pooled positive likelihood ratio (LR) was 9.57 (95% CI 5.73-15.46) while the negative LR was 0.04 (95% CI 0.02-0.11). The pooled diagnostic odds ratio was 238.06 (95% CI 77.79-728.54). The area under curve of summary receiver operator characteristics was 0.9466. CONCLUSION Through this meta-analysis, we found a promisingly high sensitivity and specificity of RS in the diagnosis of suspected kidney masses and tumors. Other parameters like positive LR, negative LR, diagnostic odds ratio and area under curve of the summary receiver operator characteristics curve all helped to illustrate the high efficacy of RS in the diagnosis of kidney cancer.
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Affiliation(s)
- Hongyu Jin
- Department of Liver Surgery and Liver Transplantation Center, West China Hospital
| | - Xiao He
- West China Clinical Skills Training Center, West China School of Medicine, Sichuan University
| | - Hui Zhou
- Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology
| | | | | | | | | | - Rui Zeng
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China
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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: 17] [Impact Index Per Article: 4.3] [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
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
| | - Daniel C. Côté
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
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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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Bury D, Morais CLM, Martin FL, Lima KMG, Ashton KM, Baker MJ, Dawson TP. Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model. Br J Neurosurg 2019; 34:40-45. [PMID: 31642351 DOI: 10.1080/02688697.2019.1679352] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Introduction: In order for brain tumours to be successfully treated, maximal resection is beneficial. A method to detect infiltrative tumour edges intraoperatively, improving on current methods would be clinically useful. Vibrational spectroscopy offers the potential to provide a handheld, reagent-free method for tumour detection.Purpose: This study was designed to determine the ability of both Raman and Fourier-transform infrared (FTIR) spectroscopy towards differentiating between normal brain tissue, glioma or meningioma.Method: Unfixed brain tissue, which had previously only been frozen, comprising normal, glioma or meningioma tissue was placed onto calcium fluoride slides for analysis using Raman and attenuated total reflection (ATR)-FTIR spectroscopy. Matched haematoxylin and eosin slides were used to confirm tumour areas. Analyses were then conducted to generate a classification model.Results: This study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to discriminate tumour from non-tumour fresh frozen brain tissue with 94% and 97.2% of cases correctly classified, with sensitivities of 98.8% and 100%, respectively. This decreases when spectroscopy is used to determine tumour type.Conclusion: The study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to detect tumour tissue from non-tumour brain tissue with a high degree of accuracy. This demonstrates the ability of spectroscopy when targeted for a cancer diagnosis. However, further improvement would be required for a classification model to determine tumour type using this technology, in order to make this tool clinically viable.
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Affiliation(s)
- Danielle Bury
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Kássio M G Lima
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Katherine M Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Timothy P Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
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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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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: 70] [Impact Index Per Article: 8.8] [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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Henry AI, Sharma B, Cardinal MF, Kurouski D, Van Duyne RP. Surface-Enhanced Raman Spectroscopy Biosensing: In Vivo Diagnostics and Multimodal Imaging. Anal Chem 2016; 88:6638-47. [PMID: 27268724 DOI: 10.1021/acs.analchem.6b01597] [Citation(s) in RCA: 169] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
This perspective presents recent developments in the application of surface-enhanced Raman spectroscopy (SERS) to biosensing, with a focus on in vivo diagnostics. We describe the concepts and methodologies developed to date and the target analytes that can be detected. We also discuss how SERS has evolved from a "point-and-shoot" stand-alone technique in an analytical chemistry laboratory to an integrated quantitative analytical tool for multimodal imaging diagnostics. Finally, we offer a guide to the future of SERS in the context of clinical diagnostics.
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Affiliation(s)
- Anne-Isabelle Henry
- Northwestern University , Department of Chemistry, 2145 Sheridan Road, Evanston, Illinois 60208, United States
| | - Bhavya Sharma
- Northwestern University , Department of Chemistry, 2145 Sheridan Road, Evanston, Illinois 60208, United States
| | - M Fernanda Cardinal
- Northwestern University , Department of Chemistry, 2145 Sheridan Road, Evanston, Illinois 60208, United States
| | - Dmitry Kurouski
- Northwestern University , Department of Chemistry, 2145 Sheridan Road, Evanston, Illinois 60208, United States
| | - Richard P Van Duyne
- Northwestern University , Department of Chemistry, 2145 Sheridan Road, Evanston, Illinois 60208, United States
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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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Kast RE, Tucker SC, Killian K, Trexler M, Honn KV, Auner GW. Emerging technology: applications of Raman spectroscopy for prostate cancer. Cancer Metastasis Rev 2015; 33:673-93. [PMID: 24510129 DOI: 10.1007/s10555-013-9489-6] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.
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Affiliation(s)
- Rachel E Kast
- Smart Sensors and Integrated Microsystems Laboratories, Department of Electrical and Computer Engineering, Wayne State University, 5050 Anthony Wayne Drive, Room 3100, Detroit, MI, 48202, USA
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Huang L, Jing R, Yang Y, Pu X, Li M, Wen Z, Li Y. Characteristic wavenumbers of Raman spectra reveal the molecular mechanisms of oral leukoplakia and can help to improve the performance of diagnostic models. ANALYTICAL METHODS 2015. [DOI: 10.1039/c4ay02318h] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
An effective method for diagnosing various grades of oral leukoplakia with dysplasia.
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Affiliation(s)
- Liqiu Huang
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Runyu Jing
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Yongning Yang
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Xuemei Pu
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Menglong Li
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Zhining Wen
- College of Chemistry
- Sichuan University
- Chengdu 610064
- China
| | - Yi Li
- State Key Laboratory of Oral Disease
- West China Hospital of Stomatology
- Sichuan University
- Chengdu 610041
- China
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Kalkanis SN, Kast RE, Rosenblum ML, Mikkelsen T, Yurgelevic SM, Nelson KM, Raghunathan A, Poisson LM, Auner GW. Raman spectroscopy to distinguish grey matter, necrosis, and glioblastoma multiforme in frozen tissue sections. J Neurooncol 2014; 116:477-85. [PMID: 24390405 DOI: 10.1007/s11060-013-1326-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 12/23/2013] [Indexed: 12/01/2022]
Abstract
The need exists for a highly accurate, efficient and inexpensive tool to distinguish normal brain tissue from glioblastoma multiforme (GBM) and necrosis boundaries rapidly, in real-time, in the operating room. Raman spectroscopy provides a unique biochemical signature of a tissue type, with the potential to provide intraoperative identification of tumor and necrosis boundaries. We aimed to develop a database of Raman spectra from normal brain, GBM, and necrosis, and a methodology for distinguishing these pathologies. Raman spectroscopy was used to measure 95 regions from 40 frozen tissue sections using 785 nm excitation wavelength. Review of adjacent hematoxylin and eosin sections confirmed histology of each region. Three regions each of normal grey matter, necrosis, and GBM were selected as a training set. Ten regions were selected as a validation set, with a secondary validation set of tissue regions containing freeze artifact. Grey matter contained higher lipid (1061, 1081 cm(-1)) content, whereas necrosis revealed increased protein and nucleic acid content (1003, 1206, 1239, 1255-1266, 1552 cm(-1)). GBM fell between these two extremes. Discriminant function analysis showed 99.6, 97.8, and 77.5% accuracy in distinguishing tissue types in the training, validation, and validation with freeze artifact datasets, respectively. Decreased classification in the freeze artifact group was due to tissue preparation damage. This study shows the potential of Raman spectroscopy to accurately identify normal brain, necrosis, and GBM as a tool to augment pathologic diagnosis. Future work will develop mapped images of diffuse glioma and neoplastic margins toward development of an intraoperative surgical tool.
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Affiliation(s)
- Steven N Kalkanis
- Department of Neurosurgery, Hermelin Brain Tumor Center, Henry Ford Health System, 2799 W Grand Blvd, Detroit, MI, 48202, USA,
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Pacheco MT, Moreira LM. Raman Spectroscopy: New Perspectives for Its Clinical Application in Diagnosis. Photomed Laser Surg 2013; 31:463-5. [DOI: 10.1089/pho.2013.9873] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Marcos T.T. Pacheco
- Universidade Camilo Castelo Branco (Unicastelo), São José dos Campos, São Paulo, Brazil
| | - Leonardo M. Moreira
- Universidade Federal de São João Del-Rei (UFSJ), São João Del-Rei, Minas Gerais, Brazil
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