Feasibility and Efficacy of Fusion Imaging Systems for Immediate Post Ablation Assessment of Liver Neoplasms: Protocol for a Rapid Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Percutaneous thermal ablation is widely adopted as a curative treatment approach for unresectable liver neoplasms. Accurate immediate assessment of therapeutic response post-ablation is critical to achieve favourable outcomes. The conventional technique of side-by-side comparison of pre- and post-ablation scans is challenging and hence there is a need for improved methods, which will accurately evaluate the immediate post-therapeutic response. OBJECTIVES AND SIGNIFICANCE: This review summarizes the findings of studies investigating the feasibility and efficacy of the fusion imaging systems in the immediate post-operative assessment of the therapeutic response to thermal ablation in liver neoplasms. The findings could potentially empower the clinicians with updated knowledge of the state-of-the-art in the assessment of treatment response for unresectable liver neoplasms. METHODS AND ANALYSIS: A rapid review will be performed on publicly available major electronic databases to identify articles reporting the feasibility and efficacy of the fusion imaging systems in the immediate assessment of the therapeutic response to thermal ablation in liver neoplasms. The risk of bias and quality of articles will be assessed using the Cochrane risk of bias tool 2.0 and Newcastle Ottawa tool. ETHICS AND DISSEMINATION: Being a review, we do not anticipate the need for any approval from the Institutional Review Board. The outcomes of this study will be published in a peer-reviewed journal. HIGHLIGHTS: Evaluation of the therapeutic response in liver neoplasms immediately post-ablation is critical to achieve favourable patient outcomes. We will examine the feasibility and technical efficacy of different fusion imaging systems in assessing the immediate treatment response post-ablation. The findings are expected to guide the clinicians with updated knowledge on the state-of-the-art when assessing the immediate treatment response for unresectable liver neoplasms.
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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 | 0.056 | 0.088 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.020 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.005 |
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".