All-optical label-free human breast tissue block histology using photoacoustic remote sensing
Bibliographic record
Abstract
The direct imaging of tissue preserved in formalin-fixed paraffin-embedded (FFPE) blocks remains a challenge. There are presently millions of tissues preserved as FFPE blocks whose assessment via bright-field microscopes requires them to be sectioned and subsequently stained. These processes are laborious, resource-intensive, and time consuming. In this Letter, we utilize an ultraviolet laser with photoacoustic remote sensing to provide a novel method that enables direct label-free pathological assessment of FFPE blocks. We demonstrate the efficacy of this technique by imaging human breast tissue, highlighting salient features such as ducts, adipocytes, and ductal hyperplasia. This direct imaging of FFPE blocks facilitates pathological assessment much earlier in the histopathological workflow, saving valuable time in clinical and research settings. The presented non-contact label-free reflection-mode device enables augmentation of existing histopathological workflows and aims to expand the arsenal of imaging technologies available to clinicians.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".