COMPARISON OF OPTICAL POLARIMETRY AND DIFFUSION TENSOR MR IMAGING FOR ASSESSING MYOCARDIAL ANISOTROPY
Bibliographic record
Abstract
We have recently proposed an optical method for assessing heart structure that uses polarized light measurement of birefringence as an indicator of tissue anisotropy. The highly aligned nature of healthy cardiac muscle tissue has a detectable effect on the polarization of light, resulting in a measurable phase shift ("retardance"). When this organized tissue structure is perturbed, for example after cardiac infarction (heart attack), scar tissue containing disorganized collagen is formed, causing a decrease in the measured retardance values. However, these are dependent not only on tissue anisotropy, but also on the angle between the tissue's optical anisotropy direction and the beam interrogating the sample. To remove this experimental ambiguity, we present a method that interrogates the sample at two different incident beam angles, thus yielding enough information to uniquely determine the true magnitude and orientation of the tissue optical anisotropy. We use an infarcted porcine heart model to compare these polarimetry-derived anisotropy metrics with those obtained with diffusion tensor magnetic resonance imaging (DT-MRI). The latter yields the anisotropy and the direction of tissue water diffusivity, providing an independent measure of tissue anisotropy. The optical and MR results are thus directly compared in a common ex vivo biological model of interest, yielding reasonable agreement but also highlighting some technique-specific differences.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".