Accuracy of Endorectal Ultrasound for Measurement of the Closest Predicted Radial Mesorectal Margin for Rectal Cancer
Bibliographic record
Abstract
BACKGROUND: At present, pelvic phased array-coil MR is used as the validated imaging modality for measurement of the closest predicted radial mesorectal margin for rectal cancer. Endorectal ultrasound is also used to assess the clinical stage of the cancer that will determine the recommendation for neoadjuvant chemoradiation, but it has not been used to assess the closest predicted radial margin. OBJECTIVE: We propose to assess endorectal ultrasound identification of mesorectal margins and the measurement of the closest predicted radial tumor-mesorectal margin. PATIENTS AND METHODS: Patients included were those having MRI and endorectal ultrasound for evaluation of primary rectal cancer in 2010 at a tertiary cancer referral colorectal clinic. Clinical data, MRI, and endorectal ultrasound images were assessed. Two independent retrospective measurements of mesorectal dimensions were correlated to evaluate the reproducibility of identifying mesorectal margins. MRI and endorectal ultrasound images were compared for independent measurements of mesorectal dimensions and of the closest predicted radial mesorectal margin. MRI and endorectal ultrasound determination of margin involvement were assessed for agreement. RESULTS: Fifty-two patients were studied with an average rectal cancer distance to the anal verge of 6.8 cm. Interobserver correlation coefficients of endorectal ultrasound mesorectal dimensions ranged from 0.47 to 0.53 (p < 0.01). MR and endorectal ultrasound measurements of the closest predicted radial mesorectal margin were correlated r = 0.56 (p < 0.0001). MR and endorectal ultrasound determination of margin involvement agreed in 81% of cases. CONCLUSION: Endorectal ultrasound has substantial agreement with MR to measure the closest predicted radial tumor-mesorectal margin. Correlations between observers and modalities for identification of mesorectal dimensions are modest. Further assessment is indicated to confirm endorectal ultrasound mesorectal measurements in a larger sample and to understand the advantages and disadvantages relative to MR.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".