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Yang SW, Xie Y, Liu JZ, Zhang D, Huang J, Liang P. A novel method for quantitative determination of multiple substances using Raman spectroscopy combined with CWT. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 317:124427. [PMID: 38754205 DOI: 10.1016/j.saa.2024.124427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 04/21/2024] [Accepted: 05/07/2024] [Indexed: 05/18/2024]
Abstract
The identification of mixed solutions is a challenging and important subject in chemical analysis. In this paper, we propose a novel workflow that enables rapid qualitative and quantitative detection of mixed solutions. We use a methanol-ethanol mixed solution as an example to demonstrate the superiority of this workflow. The workflow includes the following steps: (1) converting Raman spectra into Raman images through CWT; (2) using MobileNetV3 as the backbone network, improved multi-label and multi-channel synchronization enables simultaneous prediction of multiple mixture concentrations; and (3) using transfer learning and multi-stage training strategies for training to achieve accurate quantitative analysis. We compare six traditional machine learning algorithms and two deep learning models to evaluate the performance of our new method. The experimental results show that our model has achieved good prediction results when predicting the concentration of methanol and ethanol, and the coefficient of determination R2 is greater than 0.999. At different concentrations, both MAPE and RSD outperform other models, which demonstrates that our workflow has outstanding analytical capabilities. Importantly, we have solved the problem that current quantitative analysis algorithms for Raman spectroscopy are almost unable to accurately predict the concentration of multiple substances simultaneously. In conclusion, it is foreseeable that this non-destructive, automated, and highly accurate workflow can further advance Raman spectroscopy.
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Affiliation(s)
- Si-Wei Yang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China
| | - Yuhao Xie
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China
| | - Jia-Zhen Liu
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China
| | - De Zhang
- College of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Jie Huang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China
| | - Pei Liang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China.
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Müller DH, Börger M, Thien J, Koß HJ. Bioprocess in-line monitoring and control using Raman spectroscopy and Indirect Hard Modeling (IHM). Biotechnol Bioeng 2024; 121:2225-2233. [PMID: 38678541 DOI: 10.1002/bit.28724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/27/2024] [Accepted: 04/12/2024] [Indexed: 05/01/2024]
Abstract
Process in-line monitoring and control are crucial to optimize the productivity of bioprocesses. A frequently applied Process Analytical Technology (PAT) tool for bioprocess in-line monitoring is Raman spectroscopy. However, evaluating bioprocess Raman spectra is complex and calibrating state-of-the-art statistical evaluation models is effortful. To overcome this challenge, we developed an Indirect Hard Modeling (IHM) prediction model in a previous study. The combination of Raman spectroscopy and the IHM prediction model enables non-invasive in-line monitoring of glucose and ethanol mass fractions during yeast fermentations with significantly less calibration effort than comparable approaches based on statistical models. In this study, we advance this IHM-based approach and successfully demonstrate that the combination of Raman spectroscopy and IHM is capable of not only bioprocess monitoring but also bioprocess control. For this purpose, we used this combination's in-line information as input of a simple on-off glucose controller to control the glucose mass fraction in Saccharomyces cerevisiae fermentations. When we performed two of these fermentations with different predefined glucose set points, we achieved similar process control quality as approaches using statistical models, despite considerably smaller calibration effort. Therefore, this study reaffirms that the combination of Raman spectroscopy and IHM is a powerful PAT tool for bioprocesses.
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Affiliation(s)
| | - Marieke Börger
- Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
| | - Julia Thien
- Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
| | - Hans-Jürgen Koß
- Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
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3
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Vazquez-Osorio N, Castro-Ramos J, Sánchez-Escobar JJ. Matching Pursuit for Denoising Raman Spectra, Based on Genetic Algorithm and Hermite Atoms. APPLIED SPECTROSCOPY 2023; 77:1009-1024. [PMID: 37448352 DOI: 10.1177/00037028231179744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/15/2023]
Abstract
Due to its various advantages, Raman spectroscopy has become a powerful tool in different fields of science and engineering; however, in specific applications, this technique's limiting factor is closely related to the inherent noise of the Raman spectra. To eliminate the noise of a Raman spectrum, preserving its position, intensity, and width characteristic, we propose using a genetic matching pursuit-Hermite atoms (GMP-HAs) algorithm in this work. This algorithm helps recover Raman spectra immersed in Gaussian noise with the least number of atoms. The noise-free Raman signal is reconstructed with the GMP-HAs algorithm, transforming the typical best-matching atom search into an optimization problem. Specifically, we maximize the fitness function, defined as the correlation between current residual and Hermite atoms, with the genetic algorithm MI-LXPM encoded in a real domain and avoiding local maxima, by adding a stopping criterion based on an exponential adjustment according to the algorithm's behavior in the presence of noise. Simulated and biological Raman spectra are used to evaluate the proposed algorithm and compare its performance with typically known methods for denoising, such as the Savitzky- Golay filter (SG) and basis pursuit denoising. Using the signal-to-noise ratio (S/N)metric resulted in a 0.31 dB advantage in the S/N product for the proposed algorithm with respect to SG. Additionally, it is shown that the algorithm uses only 25.3% of the number of atoms needed by the matching pursuit algorithm. The results indicate that the GMP-HAs algorithm has better denoising capabilities, and at the same time, the Raman spectra are decomposed with fewer atoms compared to known sparse algorithms.
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Affiliation(s)
- Noe Vazquez-Osorio
- Coordinación de Óptica, Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico
| | - J Castro-Ramos
- Coordinación de Óptica, Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, Mexico
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Fitzgerald S, Marple E, Mahadevan-Jansen A. Performance assessment of probe-based Raman spectroscopy systems for biomedical analysis. BIOMEDICAL OPTICS EXPRESS 2023; 14:3597-3609. [PMID: 37497480 PMCID: PMC10368060 DOI: 10.1364/boe.494289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 07/28/2023]
Abstract
We present a methodology for evaluating the performance of probe-based Raman spectroscopy systems for biomedical analysis. This procedure uses a biological standard sample and data analysis approach to circumvent many of the issues related to accurately measuring and comparing the signal quality of Raman spectra between systems. Dairy milk is selected as the biological standard due to its similarity to tissue spectral properties and because its homogeneity eliminates the dependence of probe orientation on the measured spectrum. A spectral dataset is first collected from milk for each system configuration, followed by a model-based correction step to remove photobleaching artifacts and accurately calculate SNR. Results demonstrate that the proposed strategy, unlike current methods, produces an experimental SNR that agrees with the theoretical value. Four preconfigured imaging spectrographs that share similar manufacturer specifications were compared, showing that their capabilities to detect biological Raman spectra widely differ in terms of throughput and stray light rejection. While the methodology is used to compare spectrographs in this case, it can be adapted for other purposes, such as optimizing the design of a custom-built Raman spectrometer, evaluating inter-probe variability, or examining how altering system subcomponents affects signal quality.
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Affiliation(s)
- Sean Fitzgerald
- Vanderbilt Biophotonics Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - Eric Marple
- EmVision LCC, 1471 F Road, Loxahatchee, FL 33470, USA
| | - Anita Mahadevan-Jansen
- Vanderbilt Biophotonics Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
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Krishna R, Colak I. Advances in Biomedical Applications of Raman Microscopy and Data Processing: A Mini Review. ANAL LETT 2022. [DOI: 10.1080/00032719.2022.2094391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Ram Krishna
- Department of Mechanical Engineering, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh, India
- Electrical and Electronics Engineering, Nisantasi University, Istanbul, Turkey
- Ohm Janki Biotech Research Private Limited, India
| | - Ilhami Colak
- Electrical and Electronics Engineering, Nisantasi University, Istanbul, Turkey
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Ma X, Wang K, Chou KC, Li Q, Lu X. Conditional Generative Adversarial Network for Spectral Recovery to Accelerate Single-Cell Raman Spectroscopic Analysis. Anal Chem 2022; 94:577-582. [DOI: 10.1021/acs.analchem.1c04263] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Xiangyun Ma
- School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada
| | - Kaidi Wang
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec H9X 3V9, Canada
| | - Keng C. Chou
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada
| | - Qifeng Li
- School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Xiaonan Lu
- Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec H9X 3V9, Canada
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Fosca M, Basoli V, Della Bella E, Russo F, Vadala G, Alini M, Rau JV, Verrier S. Raman spectroscopy in skeletal tissue disorders and tissue engineering: present and prospective. TISSUE ENGINEERING PART B-REVIEWS 2021; 28:949-965. [PMID: 34579558 DOI: 10.1089/ten.teb.2021.0139] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Musculoskeletal disorders are the most common reason of chronic pain and disability representing worldwide an enormous socio-economic burden. In this review, new biomedical application fields for Raman spectroscopy (RS) technique related to skeletal tissues are discussed showing that it can provide a comprehensive profile of tissue composition in situ, in a rapid, label-free, and non-destructive manner. RS can be used as a tool to study tissue alterations associated to aging, pathologies, and disease treatments. The main advantage with respect to currently applied methods in clinics is its ability to provide specific information on molecular composition, which goes beyond other diagnostic tools. Being compatible with water, RS can be performed without pre-treatment on unfixed, hydrated tissue samples, without any labelling and chemical fixation used in histochemical methods. This review provides first the description of basic principles of RS as a biotechnology tool and introduces into the field of currently available RS based techniques, developed to enhance Raman signal. The main spectral processing statistical tools, fingerprint identification and available databases are mentioned. The recent literature has been analysed for such applications of RS as tendon and ligaments, cartilage, bone, and tissue engineered constructs for regenerative medicine. Several cases of proof-of-concept preclinical studies have been described. Finally, advantages, limitations, future perspectives, and challenges for translation of RS into clinical practice have been also discussed.
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Affiliation(s)
- Marco Fosca
- Istituto di Struttura della Materia Consiglio Nazionale delle Ricerche, 204549, Roma, Lazio, Italy;
| | - Valentina Basoli
- AO Research Institute Davos, 161930, Regenerative Orthopaedics, Davos, Graubünden, Switzerland;
| | - Elena Della Bella
- AO Research Institute Davos, 161930, Regenerative Orthopaedics, Davos, Graubünden, Switzerland;
| | - Fabrizio Russo
- Campus Bio-Medico University Hospital, 220431, Roma, Lazio, Italy;
| | - Gianluca Vadala
- Campus Bio-Medico University Hospital, 220431, Roma, Lazio, Italy;
| | - Mauro Alini
- AO Research Institute Davos, 161930, Regenerative Orthopaedics, Davos, Graubünden, Switzerland;
| | - Julietta V Rau
- Istituto di Struttura della Materia Consiglio Nazionale delle Ricerche, 204549, Roma, Lazio, Italy.,I M Sechenov First Moscow State Medical University, 68477, Moskva, Moskva, Russian Federation;
| | - Sophie Verrier
- AO Research Institute Davos, 161930, Regenerative Orthopaedics, Davos, Graubünden, Switzerland;
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Sadura F, Wróbel MS, Karpienko K. Colored Tattoo Ink Screening Method with Optical Tissue Phantoms and Raman Spectroscopy. MATERIALS 2021; 14:ma14123147. [PMID: 34201157 PMCID: PMC8227768 DOI: 10.3390/ma14123147] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 12/30/2022]
Abstract
Due to the increasing popularity of tattoos among the general population, to ensure their safety and quality, there is a need to develop reliable and rapid methods for the analysis of the composition of tattoo inks, both in the ink itself and in already existing tattoos. This paper presents the possibility of using Raman spectroscopy to examine tattoo inks in biological materials. We have developed optical tissue phantoms mimicking the optical scattering coefficient typical for human dermis as a substitute for an in vivo study. The material employed herein allows for mimicking the tattoo-making procedure. We investigated the effect of the scattering coefficient of the matrix in which the ink is located, as well as its chemical compositions on the spectra. Raman surface line scanning has been carried out for each ink in the skin phantom to establish the spatial gradient of ink concentration distribution. This ensures the ability to detect miniature concentrations for a tattoo margin assessment. An analysis and comparison of the spectra of the inks and the tattooed inks in the phantoms are presented. We recommend the utilization of Raman spectroscopy as a screening method to enforce the tattoo ink safety legislations as well as an early medical diagnostic screening tool.
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Utilizing pulse dynamics for non-invasive Raman spectroscopy of blood analytes. Biosens Bioelectron 2021; 180:113115. [PMID: 33677359 DOI: 10.1016/j.bios.2021.113115] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/23/2022]
Abstract
Non-invasive measurement methods offer great benefits in the field of medical diagnostics with molecular-specific techniques such as Raman spectroscopy which is increasingly being used for quantitative measurements of tissue biochemistry in vivo. However, some important challenges still remain for label-free optical spectroscopy to be incorporated into the clinical laboratory for routine testing. In particular, non-analyte-specific variations in tissue properties introduce significant variability of the spectra, thereby preventing reliable calibration. For measurements of blood analytes such as glucose, we propose to decrease the interference from individual tissue characteristics by exploiting the known dynamics of the blood-tissue matrix. We reason that by leveraging the natural blood pulse rhythm, the signals from the blood analytes can be enhanced while those from the static components can be effectively suppressed. Here, time-resolved measurements with subsequent pulse frequency estimation and phase-sensitive detection are proposed to recover the Raman spectra correlated with the dynamic changes at blood-pulse frequency. Pilot in vivo study results are presented to establish the benefits as well as outline the challenges of the proposed method in terms of instrumentation and signal processing.
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González-Viveros N, Castro-Ramos J, Gómez-Gil P, Cerecedo-Núñez HH. Characterization of glycated hemoglobin based on Raman spectroscopy and artificial neural networks. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 247:119077. [PMID: 33137627 DOI: 10.1016/j.saa.2020.119077] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 10/01/2020] [Accepted: 10/09/2020] [Indexed: 06/11/2023]
Abstract
The World Health Organization has declared the glycated hemoglobin (HbA1c) as a gold standard biomarker for diabetes diagnosis; this has led to relevant research on the spectral behavior and characterization of HbA1c. This paper presents an analysis of Raman peaks of commercial lyophilized HbA1c, diluted in distilled water, using concentrations of 4.76% and 9.09%, as well as pure powder (100% concentration). Vibrational Raman peak positions of HbA1c powder were found at 1578, 1571, 1536, 1436, 1311, 1308, 1230, 1222, 1114, 1106, 969, 799 and 665 cm-1; these values are consistent with results reported in other works. Besides, a nonlinear regression model based on a Feed-Forward Neural Network (FFNN) was built to quantify percentages of HbA1c for unknown concentrations. Using the Raman spectra as independent variables, the regression provided a Root Mean Square Error in Cross-Validation (RMSECV) of 0.08% ± 0.04. We also include a detailed molecular assignment of the average spectra of lyophilized powder of HbA1c.
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Affiliation(s)
- N González-Viveros
- National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Santa María Tonantzintla, San Andrés Cholula, C.P. 72840 Puebla, México.
| | - J Castro-Ramos
- National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Santa María Tonantzintla, San Andrés Cholula, C.P. 72840 Puebla, México
| | - P Gómez-Gil
- National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Santa María Tonantzintla, San Andrés Cholula, C.P. 72840 Puebla, México
| | - H H Cerecedo-Núñez
- Faculty of Physics, Veracruzan University, Zona Universitaria, C.P. 91090 Xalapa, Veracruz, México
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Pleus S, Schauer S, Jendrike N, Zschornack E, Link M, Hepp KD, Haug C, Freckmann G. Proof of Concept for a New Raman-Based Prototype for Noninvasive Glucose Monitoring. J Diabetes Sci Technol 2021; 15:11-18. [PMID: 32783466 PMCID: PMC7783007 DOI: 10.1177/1932296820947112] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Noninvasive glucose monitoring (NIGM) in diabetes is a long-sought-for technology. Among the many attempts Raman spectroscopy was considered as the most promising because of its glucose specificity. In this study, a recently developed prototype (GlucoBeam, RSP Systems A/S, Denmark) was tested in patients with type 1 diabetes to establish calibration models and to demonstrate proof of concept for this device in real use. METHODS The NIGM table-top prototype was used by 15 adult subjects with type 1 diabetes for up to 25 days at home and in an in-clinic setting. On each day, the subjects performed at least six measurement units throughout the day. Each measurement unit comprised two capillary blood glucose measurements, two scans with an intermittent scanning continuous glucose monitoring (CGM) system, and two NIGM measurements using the thenar of the subject's right hand. RESULTS Calibration models were established using data from 19 to 24 days. The remaining 3-8 days were used for independent validation. The mean absolute relative difference of the NIGM prototype was 23.6% ± 13.1% for the outpatient days, 28.2% ± 9.9% for the in-clinic day, and 26.3% ± 10.8% for the complete study. Consensus error grid analysis of the NIGM prototype for the complete study showed 93.6% of values in clinically acceptable zones A and B. CONCLUSIONS This proof of concept study demonstrated a practical realization of a Raman-based NIGM device, with performance on par with early-generation CGM systems. The findings will assist in further performance improvements of the device.
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Affiliation(s)
- Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Sebastian Schauer
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Nina Jendrike
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Eva Zschornack
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Manuela Link
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Karl Dietrich Hepp
- Independent Scientific Advisor for RSP Systems A/S, RSP Systems A/S, Denmark
| | - Cornelia Haug
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
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Jermyn M, Desroches J, Aubertin K, St-Arnaud K, Madore WJ, De Montigny E, Guiot MC, Trudel D, Wilson BC, Petrecca K, Leblond F. A review of Raman spectroscopy advances with an emphasis on clinical translation challenges in oncology. Phys Med Biol 2016; 61:R370-R400. [DOI: 10.1088/0031-9155/61/23/r370] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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13
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Marshall S, Cooper JB. Quantitative Raman Spectroscopy when the Signal-to-Noise is Below the Limit of Quantitation due to Fluorescence Interference: Advantages of a Moving Window Sequentially Shifted Excitation Approach. APPLIED SPECTROSCOPY 2016; 70:1489-1501. [PMID: 27613308 DOI: 10.1177/0003702816662621] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 02/03/2016] [Indexed: 06/06/2023]
Abstract
Raman spectroscopy is a useful analytical tool. However, its application is often limited because shot noise from fluorescence obscures the Raman signal. In such cases, quantitative analysis is not possible when the signal-to-noise ratio (SNR) drops below two. A method is described for performing quantitative Raman spectroscopy that not only removes fluorescence backgrounds, but also results in a significant improvement in the SNR. The Raman data is extracted using a moving window sequentially shifted excitation algorithm. To demonstrate the capabilities of the method, a binary mixture of two analytes at varying concentrations is quantified in the presence of a highly fluorescent dye. Linear calibration plots were constructed and validated for the binary model using individual Raman peaks with SNR ranging from 0.073-12.6; r(2) values are greater than 0.96 in all cases, with all but the weakest peaks yielding values greater than 0.997. The presented method demonstrates a universal and autonomous approach for the quantitative analysis of highly fluorescent samples via Raman spectroscopy. The lower limit on the SNR ratio for quantitative Raman analysis with the described method is 0.1. In order to assess the effectiveness of the presented method, the entire set of experiments was also processed using the more common shifted excitation Raman difference spectroscopy (SERDS) approach. The advantages of the proposed method over SERDS are demonstrated for both the detection limit and the SNR of the processed spectra.
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Affiliation(s)
- Sarah Marshall
- Department of Chemistry and Biochemistry, Old Dominion University, USA
| | - John B Cooper
- Department of Chemistry and Biochemistry, Old Dominion University, USA
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Desroches J, Jermyn M, Mok K, Lemieux-Leduc C, Mercier J, St-Arnaud K, Urmey K, Guiot MC, Marple E, Petrecca K, Leblond F. Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification. BIOMEDICAL OPTICS EXPRESS 2015; 6. [PMID: 26203368 PMCID: PMC4505696 DOI: 10.1364/boe.6.002380] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%.
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Affiliation(s)
- Joannie Desroches
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
| | - Michael Jermyn
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
- Brain Tumour Research Centre, Montreal Neurological Institute and Hospital, Dept. of Neurology and Neurosurgery, McGill University, 3801 University St., Montreal, QC, H3A 2B4, Canada
| | - Kelvin Mok
- Neuronavigation Unit, Montreal Neurological Institute and Hospital, McGill University, 3801 University St., Montreal, QC, H3A 2B4, Canada
| | - Cédric Lemieux-Leduc
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
| | - Jeanne Mercier
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
| | - Karl St-Arnaud
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
| | - Kirk Urmey
- EMVision LLC, 1471 F Road, Loxahatchee, Florida, 33470, USA
| | - Marie-Christine Guiot
- Division of Neuropathology, Department of Pathology, McGill University, 3801 University St., Montreal, QC, H3A 2B4, Canada
| | - Eric Marple
- EMVision LLC, 1471 F Road, Loxahatchee, Florida, 33470, USA
| | - Kevin Petrecca
- Brain Tumour Research Centre, Montreal Neurological Institute and Hospital, Dept. of Neurology and Neurosurgery, McGill University, 3801 University St., Montreal, QC, H3A 2B4, Canada
| | - Frédéric Leblond
- Dept. of Engineering Physics, Polytechnique Montreal, CP 6079, Succ. Centre-Ville, Montreal, QC, H3C 3A7, Canada
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