The visibility of retinal amyloid deposits as a biomarker of Alzheimer’s disease when imaged in polarized light through the cornea
Bibliographic record
Abstract
Abstract Background We previously reported a novel, dye‐free method to image amyloid deposits in the retina. Using polarized light interactions to create deposit contrast, the number of deposits in ex vivo retinas predicted the severity of brain amyloid found in association with Alzheimer’s disease (AD). Here we describe the effect of the potential range of corneal interactions with polarized light on the visibility of these retinal deposits when imaged in vivo . Method 52 retinal amyloid deposits, positive for thioflavin (Fig 1) and with a range of visibility in polarized light were imaged ex vivo in retinas of 12 participants with a moderate (2) or high (10) likelihood of Alzheimer’s disease, based on brain pathology. New images of each deposit were created by combining the polarized light interactions of the deposit and surrounding retina with the known range of interactions of human corneas with polarized light. The varying contrasts of each deposit with 45 different sets of corneal properties (a total of 2340 deposit images) were compared to the initial ex vivo images. Result As a function of the modelled corneal properties, the root mean square (RMS) contrast of each deposit both increased and decreased from that without a cornea (Fig 2). On average, RMS contrast across deposits combined with a cornea decreased 12% from that without a cornea. For 3% of deposit images, there was a corneal property that reduced the deposit contrast by over 50% (Fig 2). However, even in these cases, because of the variation in interaction with polarized light across the deposit (Fig 3), the deposit remained visible against the background retina. Conclusion Although the cornea interaction with polarized light will affect images of amyloid deposits in the retina taken with our non‐invasive method, all cases investigated are predicted to remain visible against the background retina. In addition, during in vivo imaging, an established method of compensating for an individual’s corneal interaction with polarized light, would guarantee 100% visibility. Thus, in vivo , our retinal imaging method is predicted to give a biomarker of the severity of amyloid in the brain found in association with Alzheimer’s disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".