TY - JOUR
T1 - Investigation of the specificity of Raman spectroscopy in non-invasive blood glucose measurements
AU - Dingari, Narahara Chari
AU - Barman, Ishan
AU - Singh, Gajendra P.
AU - Kang, Jeon Woong
AU - Dasari, Ramachandra R.
AU - Feld, Michael S.
N1 - Funding Information:
This work was supported by the NIH National Center for Research Resources (Grant No. P41-RR02594) and a grant from Bayer HealthCare, LLC. The animal model study was performed at the Indiana University-Purdue University Fort Wayne facility in collaboration with the Bayer HealthCare, Diabetes Care division. Specifically, the animal model dataset used in this article was acquired by Dr. Mihailo V. Rebec and his clinical team. One of the authors, IB, acknowledges the support of Lester Wolfe Fellowship from the Laser Biomedical Research Center.
PY - 2011/7
Y1 - 2011/7
N2 - 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.
AB - 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.
KW - Animal model
KW - Causation
KW - Chance correlations
KW - Human subject
KW - Non-invasive glucose monitoring
KW - Raman spectroscopy
UR - https://www.scopus.com/pages/publications/85027952068
UR - https://www.scopus.com/pages/publications/85027952068#tab=citedBy
U2 - 10.1007/s00216-011-5004-5
DO - 10.1007/s00216-011-5004-5
M3 - Article
AN - SCOPUS:85027952068
SN - 1618-2642
VL - 400
SP - 2871
EP - 2880
JO - Analytical and Bioanalytical Chemistry
JF - Analytical and Bioanalytical Chemistry
IS - 9
ER -