Three-dimensional microscopic image reconstruction of prostatic adenocarcinoma.
Bibliographic record
Abstract
CONTEXT: Routine microscopy provides only a 2-dimensional view of the complex 3-dimensional structure that makes up human tissue. Three-dimensional microscopic image reconstruction has not been described previously for prostate cancer. OBJECTIVES: To develop a simple method of computerized 3-dimensional image reconstruction and to demonstrate its applicability to the study of prostatic adenocarcinoma. METHODS: Serial sections were cut from archival paraffin-embedded prostate specimens, immunostained using antikeratin CAM5.2, and digitally imaged. Computer image-rendering software was used to produce 3-dimensional image reconstructions of prostate cancer of varying Gleason grades, normal prostate, and prostatic intraepithelial neoplasia. RESULTS: The rendering system proved easy to use and provided good-quality 3-dimensional images of most specimens. Normal prostate glands formed irregular fusiform structures branching off central tubular ducts. Prostatic intraepithelial neoplasia showed external contours similar to those of normal glands, but with a markedly complex internal arrangement of branching lumens. Gleason grade 3 carcinoma was found to consist of a complex array of interconnecting tubules rather than the apparently separate glands seen in 2 dimensions on routine light microscopy. Gleason grade 4 carcinoma demonstrated a characteristic form of glandular fusion that was readily visualized by optically sectioning and rotating the reconstructed images. CONCLUSIONS: Computerized 3-dimensional microscopic imaging holds great promise as an investigational tool. By revealing the structural relationships of the various Gleason grades of prostate cancer, this method could be used to refine diagnostic and grading criteria for this common tumor.
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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 | 0.000 | 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 | 0.000 | 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".