Dense concentric circle scanning protocol for measuring pulsatile retinal blood flow in rats with Doppler optical coherence tomography
Bibliographic record
Abstract
The variability in the spatial orientation of retinal blood vessels near the optic nerve head (ONH) results in imprecision of the measured Doppler angle and therefore the pulsatile blood flow (BF), when those parameters are evaluated using Doppler OCT imaging protocols based on dual-concentric circular scans. Here, we utilized a dense concentric circle scanning protocol and evaluated its precision for measuring pulsatile retinal BF in rats for different numbers of the circular scans. An spectral domain optical coherence tomography (SD-OCT) system operating in the 1060-nm spectral range with image acquisition rate of 47,000 A-scans/s was used to acquire concentric circular scans centered at the rat's ONH, with diameters ranging from 0.8 to 1.0 mm. A custom, automatic blood vessel segmentation algorithm was used to track the spatial orientation of the retinal blood vessels in three dimensions, evaluate the spatially dependent Doppler angle and calculate more accurately the axial BF for each major retinal blood vessel. Metrics such as retinal BF, pulsatility index, and resistance index were evaluated for each and all of the major retinal blood vessels. The performance of the proposed dense concentric circle scanning protocols was compared with that of the dual-circle scanning protocol. Results showed a 3.8±2.2 deg difference in the Doppler angle calculation between the two approaches, which resulted in ∼7% difference in the calculated retinal BF.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".