Novel Noninvasive Assessment of Microvascular Structure and Function in Humans
Bibliographic record
Abstract
INTRODUCTION: Optical coherence tomography (OCT) is a novel high-resolution imaging technique capable of visualizing in vivo structures at a resolution of ~10 μm. We have developed specialized OCT-based approaches that quantify diameter, speed, and flow rate in human cutaneous microvessels. In this study, we hypothesized that OCT-based microvascular assessments would possess comparable levels of reliability when compared with those derived using conventional laser Doppler flowmetry (LDF). METHODS: Speckle decorrelation images (OCT) and red blood cell flux (LDF) measures were collected from adjacent forearm skin locations on 2 d (48 h apart), at baseline, and after a 30-min rapid local heating protocol (30°C-44°C) in eight healthy young individuals. OCT postprocessing quantified cutaneous microvascular diameter, speed, flow rate, and density (vessel recruitment) within a region of interest, and data were compared between days. RESULTS: Forearm skin LDF (13 ± 4 to 182 ± 31 AU, P < 0.05) and OCT-derived diameter (41.8 ± 6.6 vs 64.5 ± 6.9 μm), speed (68.4 ± 9.5 vs 89.0 ± 7.3 μm·s), flow rate (145.0 ± 60.6 vs 485 ± 132 pL·s), and density (9.9% ± 4.9% vs 45.4% ± 5.9%) increased in response to local heating. The average OCT-derived microvascular flow response (pL·s) to heating (234% increase) was lower (P < 0.05) than the LDF-derived change (AU) (1360% increase). Pearson correlation was significant for between-day local heating responses in terms of OCT flow (r = 0.93, P < 0.01), but not LDF (P = 0.49). Bland-Altman analysis revealed that between-day baseline OCT-derived flow rates were less variable than LDF-derived flux. CONCLUSIONS: Our findings indicate that OCT, which directly visualizes human microvessels, not only allows microvascular quantification of diameter, speed, flow rate, and vessel recruitment but also provides outputs that are highly reproducible. OCT is a promising novel approach that enables a comprehensive assessment of cutaneous microvascular structure and function in humans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".