Use of ultrasound biomicroscopy to image human ovaries <i>in vitro</i>
Bibliographic record
Abstract
OBJECTIVES: To test the hypothesis that ultrasound biomicroscopy is an effective tool for imaging human ovaries in vitro. METHODS: This was a prospective, observational study of 11 women (mean age, 48.9 +/- 2.3 years; range, 40-65 years) undergoing unilateral or bilateral oophorectomy. Ovaries were obtained in the operating room and imaged in a cooled saline bath using conventional two-dimensional (2D) ultrasound. Follicles identified using conventional 2D ultrasound were then imaged in a cooled saline bath using ultrasound biomicroscopy. Ovaries were then placed in 10% neutral-buffered formaldehyde and transported to the Pathology Department for histological evaluation. Digital images of individually identified ovarian follicles using conventional ultrasound, ultrasound biomicroscopy and histology were obtained (n = 22). Thicknesses of the follicle wall, granulosa layer and theca interna layer were measured using standardized techniques. RESULTS: The imaging sensitivity, defined as the smallest follicle visualized, was greater using ultrasound biomicroscopy (0.33 +/- 0.07 mm) than it was using conventional ultrasound (1.5 +/- 0.21 mm; P < 0.0001). The mean follicle wall thickness was greater using conventional ultrasound (0.675 +/- 0.039 mm) compared with ultrasound biomicroscopy (0.254 +/- 0.017 mm), which in turn, was greater than that measured by histology (0.160 +/- 0.009 mm) (P < 0.0001). The mean granulosa and theca layer thickness measurements, respectively, were greater using ultrasound biomicroscopy (0.067 +/- 0.004 mm; 0.186 +/- 0.014 mm) compared with histology (0.034 +/- 0.002 mm; 0.126 +/- 0.008 mm) (P < or = 0.001). Protrusions from the follicle wall into the antrum, believed to represent cumulus-oocyte complexes, were visualized in five of 22 follicles using ultrasound biomicroscopy. CONCLUSIONS: The ultrasound biomicroscope was an effective tool to image human ovaries in vitro. Ultrasound biomicroscopy provided greater sensitivity and resolution for imaging ovarian follicles compared with conventional 2D ultrasonographic techniques.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".