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. 2024 Jan 24;15(2):991-1003.
doi: 10.1364/BOE.506092. eCollection 2024 Feb 1.

High-accuracy noninvasive continuous glucose monitoring using OCT angiography-purified blood scattering signals in human skin

Affiliations

High-accuracy noninvasive continuous glucose monitoring using OCT angiography-purified blood scattering signals in human skin

Mengqin Gao et al. Biomed Opt Express. .

Abstract

The accuracy of noninvasive continuous glucose monitoring (CGM) through near-infrared scattering is challenged by mixed scattering signals from different compartments, where glucose has a positive correlation with a blood scattering coefficient but a negative correlation with a tissue scattering coefficient. In this study, we developed a high-accuracy noninvasive CGM based on OCT angiography (OCTA)-purified blood scattering signals. The blood optical scattering coefficient (BOC) was initially extracted from the depth attenuation of backscattered light in OCT and then purified by eliminating the scattering signals from the surrounding tissues under the guidance of a 3D OCTA vascular map in human skin. The purified BOC was used to estimate the optical blood glucose concentration (BGC) through a linear calibration. The optical and reference BGC measurements were highly correlated (R = 0.94) without apparent time delay. The mean absolute relative difference was 6.09%. All optical BGC measurements were within the clinically acceptable Zones A + B, with 96.69% falling in Zone A on Parke's error grids. The blood glucose response during OGTT was mapped with a high spatiotemporal resolution of the single vessel and 5 seconds. This noninvasive OCTA-based CGM shows promising accuracy for clinical use. Future research will involve larger sample sizes and diabetic participants to confirm these preliminary findings.

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Conflict of interest statement

The authors declared no potential conflicts of interest concerning the research, authorship, and publication of this article.

Figures

Fig. 1.
Fig. 1.
(a) Flow diagram of glucose monitoring using OCT angiography in human skin. (i) generating OCT structural image by taking Fourier transform of raw spectral sequence, (ii) extracting depth-resolved scattering coefficient, (iii) computing OCT angiogram, (iv) binarizing using Otsu's method, (v) calculating BGC and IGC. Representative cross-sectional OCT structure (b), optical scattering coefficient (OSC) map (c), OCT angiogram (d) and vascular mask (e). The insert in (b) is a representative depth profile at the location indicated by the white dashed line in (b). (f) Enface OCTA angiogram. The white dashed line in (f) indicates the location of the cross-sections in (b-e). Scale bar in (b) is 500 µm and applies to (b-f). E: epidermis, D: dermis, NM: nail matrix, NR: nail root, NB: nail bed.
Fig. 2.
Fig. 2.
Linear correlation between BOC and BGC. (a) Outcomes of Mie theory (Eq. (1), red line) and simplified representation (Eq. (19), blue line) within the BGC range of 0-1000 mg/dL. (b) Correlation between BOC and BGC in vivo experiment. (c) Times course of percentage changes in BOC during OGTT. In the simulation, it was assumed that Gb0 = 90 mg/dL, H0 = 0.45, and osm0 = 300 mosm/L under isotonic condition. BOC: blood optical scattering coefficient (μsb) , BGC: blood glucose concentration (Gb) , Ref.: reference BGC.
Fig. 3.
Fig. 3.
Linear relation between TOC and IGC. (a) Using numerical simulation, plots of TOC against IGC within 0-1000 mg/dL. (b) Correlation between TOC and IGC through vivo experiment. The solid squares and the solid line represent the correlation between the TOC and IGC after correcting for the delay time. (c) Times course of percentage changes in TOC during OGTT. TOC: tissue optical scattering coefficient (μsi) , IGC: ISF glucose concentration (Gi) , Ref: reference BGC.
Fig. 4.
Fig. 4.
OCTA-based BGC and IGC measurements during OGTT. (a) Representative enface BGC mappings at instants: -10 min, 0 min, 20 min, 50 min. (b) Time courses of optical BGC and reference BGC. (c) Correlation between optical and reference BGC. (d) Time courses of optical IGC and reference BGC. (e) The correlation between the optical IGC and reference BGC. The solid squares and the solid line represent the correlation between the IGC and BGC after correcting for delay time. Opt.: optical BGC (or IGC); Ref.: reference BGC.
Fig. 5.
Fig. 5.
Accuracy of optical BGC measurement. (a) Parke’s error grid. Red and blue circles indicate points within zones A and B, respectively. The five risk zones are: Zone A, clinically accurate; Zone B, benign; Zone C, excessive; Zone D, undetectable; Zone E, faulty. Both zones A and B are clinically acceptable. (b) ISO 15197:2013. The solid line is the relative difference of ±15 mg/dL when BGC < 100 mg/dL and ±15% when BGC ≥ 100 mg/dL. Red and blue circles represent values within or outside the accuracy criteria. A total of 121 pairs of optical and reference BGC are used.
Fig. 6.
Fig. 6.
Diurnal variations in blood analytes. Data is pooled from [–49]. Changes are expressed as a percentage relative to the average value. Meals are taken around 9:00, 13:30, and 18:00, denoting breakfast, lunch, and dinner. The gray region indicates the sleep period. MCV, mean corpuscular volume.

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