Investigation of the specificity of Raman spectroscopy in non-invasive blood glucose measurements
Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of...
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Published in | Analytical and bioanalytical chemistry Vol. 400; no. 9; pp. 2871 - 2880 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Berlin/Heidelberg
Springer-Verlag
01.07.2011
Springer |
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Abstract | Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood–tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to NIR absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions. |
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AbstractList | Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood–tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to NIR absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions. Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared to that of the other analytes in the blood-tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test (OGTT) test. We demonstrate that the spurious concentration profile based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to NIR absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions. Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (N1R) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood--tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to N1R absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions. Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (N1R) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood--tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to N1R absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions. Keywords Raman spectroscopy * Non-invasive glucose monitoring * Chance correlations * Causation * Animal model * Human subject |
Audience | Academic |
Author | Kang, Jeon Woong Dasari, Ramachandra R. Feld, Michael S. Singh, Gajendra P. Barman, Ishan Dingari, Narahara Chari |
Author_xml | – sequence: 1 givenname: Narahara Chari surname: Dingari fullname: Dingari, Narahara Chari organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology – sequence: 2 givenname: Ishan surname: Barman fullname: Barman, Ishan email: ishan@mit.edu organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology – sequence: 3 givenname: Gajendra P. surname: Singh fullname: Singh, Gajendra P. organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology – sequence: 4 givenname: Jeon Woong surname: Kang fullname: Kang, Jeon Woong organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology – sequence: 5 givenname: Ramachandra R. surname: Dasari fullname: Dasari, Ramachandra R. organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology – sequence: 6 givenname: Michael S. surname: Feld fullname: Feld, Michael S. organization: George R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology |
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Keywords | Chance correlations Animal model Raman spectroscopy Causation Non-invasive glucose monitoring Human subject Time Glucose Blood Spectral data Near infrared spectrometry Tissue Signal Specificity Absorption Raman spectrometry Human Prediction Concentration Calibration Clamping In vitro In vivo Non destructive method Absorption spectrometry Technique |
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Snippet | Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman... Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (N1R) absorption and Raman... Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman... |
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SubjectTerms | Analytical Chemistry Animals Biochemistry Biocompatibility Biomedical materials Blood Glucose - analysis Blood sugar Calibration Characterization and Evaluation of Materials Chemistry Chemistry and Materials Science Comparative analysis Dogs Exact sciences and technology Food Science Glucose Glucose metabolism Glucose tolerance tests Humans In vivo testing In vivo tests Laboratory Medicine Mathematical models Measurement Monitoring/Environmental Analysis Raman spectroscopy Sensitivity and Specificity Spectrometric and optical methods Spectrum Analysis, Raman - methods Surgical implants Technical Note |
Title | Investigation of the specificity of Raman spectroscopy in non-invasive blood glucose measurements |
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