In Vivo High-Frequency, Contrast-Enhanced Ultrasonography of Uveal Melanoma in Mice: Imaging Features and Histopathologic Correlations
Bibliographic record
Abstract
PURPOSE: To evaluate the usefulness of in vivo imaging of uveal melanoma in mice using high-frequency contrast-enhanced ultrasound (HF-CE-US) with 2D or 3D modes and to correlate the sonographic findings with histopathologic characteristics. METHODS: Fourteen 12-week-old C57BL6 mice were inoculated into their right eyes with aliquots of 5 × 10(5)/2.5 μL B16LS9 melanoma cells and were randomly assigned to either of two groups. At 7 days after inoculation, tumor-bearing eyes in group 1 (n = 8) were imaged using HF-CE-US to determine the 2D tumor size and relative blood volume; eyes in group 2 (n = 6) were imaged by 3D microbubble contrast-enhanced ultrasound, and the tumor volume was determined. Histologic tumor burden was quantified in enucleated eyes by image processing software, and microvascular density was determined by counting von Willebrand factor-positive vascular channels. Ultrasound images were evaluated and compared with histopathologic findings. RESULTS: Using HF-CE-US, melanomas were visualized as relatively hyperechoic regions. The intraobserver variability of sonographic measurements was 9.65% ± 7.89%, and the coefficient of variation for multiple measurements was 7.33% ± 5.71%. The correlation coefficient of sonographic volume or size and histologic area was 0.71 (P = 0.11) and 0.79 (P = 0.32). The relative blood volume within the tumor demonstrated sonographically correlated significantly with histologic tumor vascularity (r = 0.83; P < 0.001). CONCLUSIONS: There was a positive linear correlation between sonographic tumor measurements and histologic tumor burden in the mouse ocular melanoma model. Contrast-enhanced intensity corresponded with microvascular density and blood volume. HF-CE-US is a real-time, noninvasive, reliable method for in vivo evaluation of experimental intraocular melanoma tumor area and relative blood volume.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| 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".