Efficacy of minimally invasive vascular interventions assessed with mobile multispectral near-infrared spectroscopy
Bibliographic record
Abstract
Background The adoption of minimally invasive techniques for treating chronic venous insufficiency has surged. Techniques such as foam sclerotherapy and radiofrequency ablation (RFA) are now widely used to address incompetent great saphenous veins. Duplex ultrasound examination has become the gold standard for diagnosing venous insufficiency and evaluating the effectiveness of these treatments. However, venous reflux ultrasound studies remain some of the most time-consuming tasks to obtain. Objective The objective of this study was to evaluate the effectiveness of minimally invasive vascular interventions, such as foam sclerotherapy and/or RFA, using mobile multispectral near-infrared spectroscopic (NIRS) imaging. By measuring changes in tissue oxygenation (StO 2 ) before and after treatment, this study aims to provide insights into the utility of NIRS imaging as a noninvasive tool for assessing treatment outcomes. Methods This quasi-experimental pre-post-test design study included 14 patients treated for chronic venous insufficiency with either foam sclerotherapy or RFA between November 2022 and February 2024. The patient population presented with significant great saphenous vein insufficiency and normal deep venous pathology, with no evidence of deep vein thrombosis or superficial vein thrombosis, except for one case with partial chronic and deep venous thrombosis. NIRS images of the lower extremities were collected before and immediately after the treatment. The images were acquired from various anatomical locations including the dorsum and plantar aspects of the foot, the medial and lateral leg, and the wound area if present. Results The results demonstrated a statistically significant increase in mean StO 2 in lower extremities after foam sclerotherapy and RFA, indicating an improved microcirculatory function in the treated limb. These improvements in StO 2 in the lower extremities were consistent with the vascular examination results, which confirmed successful vein ablation or closure. Conclusions The study demonstrates that NIRS imaging effectively tracks treatment-related changes, providing a noninvasive and reliable method for the real-time assessment of StO 2 . By visualizing changes in microcirculation, this technology offers clinicians valuable insights, enabling earlier detection of treatment success or failure and facilitating timely interventions. As such, NIRS imaging holds promise as a valuable tool in clinical practice for evaluating the efficacy of minimally invasive vascular treatments. However, the small sample size limits the ability to draw definitive conclusions.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".