The Use of Contrast-Enhanced Sonography for Therapy Monitoring of Metastatic Lymph Nodes: A Systematic Review
Bibliographic record
Abstract
Metastatic cervical lymph nodes are a frequent finding in head and neck squamous cell carcinoma (HNSCC). If a non-surgical approach is primarily chosen, a therapy response evaluation of the primary tumor and the affected lymph nodes is necessary in the follow-up. Supplementary contrast-enhanced ultrasound (CEUS) can be used to precisely visualize the microcirculation of the target lesion in the neck, whereby malignant and benign findings differ in their uptake behavior. The same applies to many other solid tumors. For various tumor entities, it has already been shown that therapy monitoring is possible through regular contrast-enhanced sonography of the primary tumor or the affected lymph nodes. Thus, in some cases, maybe in the future, a change in therapy strategy can be achieved at an early stage in the case of non-response or, in the case of therapy success, a de-escalation of subsequent (surgical) measures can be achieved. In this paper, a systematic review of the available studies and a discussion of the potential of therapy monitoring by means of CEUS in HNSCC are presented.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".