ArticleBiophotonics discovery2024
Enhanced peripheral tissue oxygenation and hemoglobin concentration after a high-fat meal measured with spatial frequency domain imaging.
Article in Biophotonics discovery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Review of shortwave infrared imaging and spectroscopy in tissue [Invited].Biomedical optics express · 2025Review
- Frequency domain broadband short-wave infrared spectroscopy for measurement of tissue optical properties from 685 to 1300 nm.Journal of biomedical optics · 2025Article
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Authors and funding
3 authors.
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Abstract
Significance: The magnitude and temporal dynamics of changes in blood nutrient and lipid levels following a high-fat meal have been previously shown to be an important indicator of current and future cardiovascular health and disease. Measurement of circulating nutrients and lipids currently requires invasive blood draws. The development of a non-invasive method for continuous monitoring of postprandial (i.e., after-meal) changes may assist in enhancing cardiovascular health management, dietary monitoring, and identification of disease-promoting factors. Spatial frequency domain imaging (SFDI) is a non-contact, label-free optical technique that can quantify tissue optical properties and hemodynamics in vivo. We hypothesized that SFDI may track the postprandial state in peripheral tissue. Aim: We aim to investigate the relationship between postprandial factors, namely triglycerides and glucose, and the optical properties and oxygenation of peripheral tissue measured with SFDI. Approach: Fifteen healthy volunteers consumed both a low- (2 g) and high- (60 g) fat meal on different days. A custom SFDI device was used to measure the dorsal hand surface of volunteers before the meal and each hour for 5 h after the meal. Measurements were taken at 730, 880, and 1100 nm. Longitudinal postprandial changes in tissue optical properties were correlated with changes in blood triglycerides and glucose levels as well as blood pressure, heart rate, and room temperature. A machine-learning model was trained to estimate triglyceride levels from SFDI metrics. Results: Several SFDI metrics increased and peaked 3 to 4 h following the high-fat meal, including tissue oxygen saturation ( Conclusion: These findings suggest that SFDI could serve as a powerful non-invasive tool to monitor postprandial hemodynamics. In the future, SFDI measurements may help enhance cardiovascular disease prediction and management.
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