Preoperative assessment of vascularity by color Doppler ultrasonography in human rectal carcinoma
Bibliographic record
Abstract
PURPOSE: Although angiogenesis assessed by immunostaining endothelial cells (microvessel density) is a well-known prognostic factor in a wide variety of human solid tumors, preoperative determination of microvessel density seems to be difficult in rectal carcinoma. Thus, we performed transanal color Doppler ultrasonography in 46 patients with rectal carcinoma to assess preoperative angiogenic status and compare it with microvessel density in surgical specimens. METHODS: Time-averaged maximal velocity, peak systolic velocity, number of vascular points, and vascular point index were conducted by color Doppler ultrasonography in 46 patients with rectal carcinoma. Number of vascular points was defined as the number of vessels with pulsation in the section of tumor. Vascular point index was defined as the average number of vascular points divided by the area assessed by color Doppler ultrasonography in the section of tumor. The profiles of number of vascular points were similar to those assessed by microangiography in five rectal carcinomas. RESULTS: Vascular point index significantly correlated with microvessel density (P < 0.0001). No significant correlation was found between microvessel density and time-averaged maximal velocity or peak systolic velocity. Vascular point index was also a better indicator of lymph node metastasis and venous invasion than microvessel density. In addition, 11 of 46 cases with postoperative hematogenous metastasis (23.9 percent) were observed prospectively. Vascular point index may be a best predictor for hematogenous metastasis from rectal carcinoma compared with peak systolic velocity, time-averaged maximal velocity, and microvessel density by receiver operating characteristic analysis. CONCLUSION: These results suggest that preoperative quantification of angiogenesis using color Doppler ultrasonography will provide quick and useful information in the management of rectal carcinoma.
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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".