Dynamic Microbubble Contrast-enhanced US to Measure Tumor Response to Targeted Therapy: A Proposed Clinical Protocol with Results from Renal Cell Carcinoma Patients Receiving Antiangiogenic Therapy
Bibliographic record
Abstract
PURPOSE: To develop and implement an evidence-based protocol for characterizing vascular response of renal cell carcinoma (RCC) to targeted therapy by using dynamic contrast material-enhanced (DCE) ultrasonography (US). MATERIALS AND METHODS: The study was approved by the institutional research ethics board; written informed consent was obtained from all patients. Seventeen patients (four women; median age, 58 years; range, 42-72 years; 13 men, median age, 62 years; range, 45-81 years) with metastatic RCC were examined by using DCE US before and after 2 weeks of treatment with sunitinib (May 2007 to October 2009). Two contrast agent techniques--bolus injection and disruption-replenishment infusion of microbubbles--were compared. Changes in tumor blood velocity and fractional blood volume were measured with both methods, together with reproducibility and effect of compensation for respiratory motion. Tumor changes were assessed with computed tomography, by using the best response with the Response Evaluation Criteria in Solid Tumors (RECIST) and progression-free survival (PFS). Follow-up RECIST measurements were performed at 6-week intervals until progressive disease was detected. RESULTS: In response to treatment, median tumor fractional blood volume measured with the disruption-replenishment infusion method decreased by 73.2% (interquartile range, 46%-87%) (P < .002), with repeated-measure reproducibility of 9%-15%. Significant decreases were also seen with the bolus method, but with poor correlation of changes in bolus peak (r = 0.46, P = .066) and area under the curve (r = 0.47, P = .058), compared with infusion measurements. Changes in DCE US parameters over 2 weeks did not correlate with PFS and could not be used to predict long-term assessment of best response by using RECIST. Follow-up times ranged 28-501 days; the median was 164 days. CONCLUSION: DCE US provides reproducible and sensitive assessment of vascular changes in response to antiangiogenic therapy. The disruption-replenishment infusion protocol is a flexible method suitable for many tumor types, but further studies are needed to assess whether this protocol may be predictive of patient outcome.
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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 | 0.041 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".