Novel Approach in the Evaluation of Flap Failure Using near Infrared Spectroscopy and Imaging
Bibliographic record
Abstract
Methods of tissue viability assessment should be classified into those that measure blood flow and those that monitor tissue metabolism. The problem with measuring blood flow is that it can be misleading due to the phenomenon of arteriovenous shunting. Near infrared (NIR) spectroscopy is capable of identifying certain molecules in the tissues. In this study, using the reverse McFarlane rat skin flap as a model, oxygen delivery to the tissue along the flap was demonstrated in the form of a spectrum. This was achieved by using the differential absorption of oxy- and deoxyhemoglobin between wavelengths of 650 nm and 900 nm. NIR imaging works on a similar principle, but an oxygen saturation image is obtained, with the darkest area indicating the most deoxygenated area of the flap and vice versa. There were two types of studies done. In the chronic study (n=10), NIR spectroscopy was done on the intact skin preoperatively for three days and then after elevation of the flap at various sites for three days. Preoperative measurements showed excellent reproducibility, and postoperative measurements showed progressive deoxygenation toward the distal aspect of the flap. NIR imaging at 1 h after flap elevation showed a zone of demarcation that corresponded with that noted clinically at 72 h. In the acute study (n=3), NIR spectroscopy, imaging and laser Doppler flowmetry were acquired before, immediately following and 1 h after raising the flap, and then measurements were taken after applying a vascular clamp across the base of the flap; reperfusion was evaluated after clamp release. Spectroscopy immediately following flap elevation indicated deoxygenation of the most distant part of the flap. Clamping the base of the flap caused deoxygenation of the whole flap; this was immediately evident on both spectroscopy and imaging. These changes recovered after releasing the clamp in the areas that were expected to survive. Laser Doppler flowmetry results generally correlated well with the NIR spectroscopy and imaging results. However, the method was very sensitive to fine movements during monitoring. The main advantage of NIR monitoring is that it looks directly at oxygen consumption rather than measuring blood flow. In addition, the NIR imaging gives a global picture of the eventual fate of the flap. These properties make these devices much more practical when the flap's well-being is concerned.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".