Non-Invasive Characterization of Lower Extremity Deep Vein Thrombosis via Advanced Ultrasound Elastography: A Prospective Pilot Study
Bibliographic record
Abstract
Duplex ultrasonography is the preferred non-invasive imaging technique for diagnosing lower extremity deep vein thrombosis (DVT), but considered largely unreliable for determining thrombus-specific features. Elastosonography techniques including real-time strain elastography (RT-SE) are widely used in clinical practice to assess tissue elasticity, but its potential remains largely unrealized in DVT, where RT-SE might provide adjunct information on thrombus biomechanical properties potentially aiding clinical decision-making. This single-center prospective pilot study investigates the use of modern RT-SE imaging enhanced with an advanced quantification software for reconstructive tissue elasticity analysis in patients with symptomatic acute lower-extremity DVT objectively diagnosed within 6 months of enrollment. Between-group differences in median thrombus elasticity, assessed via a newly proposed elasticity biomarker, namely thrombus tissue deformation index, were evaluated using Mann-Whitney U or Kruskal-Wallis tests. Relationships between thrombus elasticity and patient-, DVT- and anticoagulation-related factors were assessed through Spearman's rank-order correlation. Thirty-eight deep venous thrombi were analyzed using advanced RT-SE, in addition to standard duplex ultrasonography (i.e., triplex ultrasonography). Median thrombus elasticity was 25.7% (interquartile range [IQR], 22.1-26.1), 20.8% (IQR, 17.1-22.1), and 3.8% (IQR, 1.3-6.6) in acute, sub-acute, and chronic DVT, respectively (p < 0.001). Thrombus elasticity robustly correlated with the period of DVT diagnosis (i.e., lower elasticity with increasing thrombus chronological age; ρ = -0.70, p < 0.0001). Elasticity of chronic thrombi inversely correlated with dynamic changes in residual vein obstruction (i.e., higher elasticity of thrombi undergoing smaller size reduction over time; ρ = 0.85, p < 0.0001). These findings preliminarily identify modern advanced RT-SE imaging as a viable and easily-implementable tool for enhanced non-invasive thrombus characterization, with the potential to inform thrombus-guided management strategies in patients with DVT.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".