Researchers at MIT’s Spectroscopy Laboratory have announced that they are currently working on a Raman spectroscopy machine which can measure blood glucose without a blood sample. The machine sends infrared light through the skin to determine glucose levels in the interstitial fluid. In a paper published in the July 15 issue of Analytical Chemistry, the researchers described their algorithm for determining blood glucose levels based on the interstitial concentration.
From MIT’s press release:
Researchers in the Spectroscopy Lab have been developing this technology for about 15 years. One of the major obstacles they have faced is that near-infrared light penetrates only about half a millimeter below the skin, so it measures the amount of glucose in the fluid that bathes skin cells (known as interstitial fluid), not the amount in the blood. To overcome this, the team came up with an algorithm that relates the two concentrations, allowing them to predict blood glucose levels from the glucose concentration in interstitial fluid.
However, this calibration becomes more difficult immediately after the patient eats or drinks something sugary, because blood glucose soars rapidly, while it takes five to 10 minutes to see a corresponding surge in the interstitial fluid glucose levels. Therefore, interstitial fluid measurements do not give an accurate picture of what’s happening in the bloodstream.
To address that lag time, Barman and Kong developed a new calibration method, called Dynamic Concentration Correction (DCC), which incorporates the rate at which glucose diffuses from the blood into the interstitial fluid. In a study of 10 healthy volunteers, the researchers used DCC-calibrated Raman spectroscopy to significantly boost the accuracy of blood glucose measurements – an average improvement of 15 percent, and up to 30 percent in some subjects.
Press release: Shining a light – literally – on diabetes…
Abstract of the researchers’ paper: Accurate Spectroscopic Calibration for Noninvasive Glucose Monitoring by Modeling the Physiological Glucose Dynamics