Three Dimensional-CTA versus Doppler Ultrasound for Anterolateral Thigh Flap Reconstruction in Limb Defects: A Retrospective Study
Bibliographic record
Abstract
Background: Soft tissue limb defects often require anterolateral thigh (ALT) flap reconstruction, but anatomical variability of perforator vessels poses a challenge. The comparative efficacy of 3-dimensional computed tomographic angiography (3D-CTA) and color Doppler ultrasonography (CDUS) for preoperative planning remains unclear. Methods: This retrospective study analyzed 95 patients who underwent ALT flap limb reconstruction between March 2017 and May 2023, comparing a 3D-CTA–guided group (n=45) with a CDUS-guided group (n=50). Key outcomes included perforator mapping accuracy, surgical efficiency, postoperative complications, functional and aesthetic results, and cost-effectiveness. Results: Use of 3D-CTA demonstrated superior perforator detection sensitivity (98.4% versus 85.8%, P < 0.001) and positional accuracy (deviation: 0.3 versus 1.8 cm, P < 0.001). The 3D-CTA group had significantly shorter flap harvest times (38.5 versus 51.4 min, P < 0.001), fewer vascular complications (4.4% versus 20.0%, P = 0.0489), and higher flap survival (100% versus 92.0%, P = 0.047). The 3D-CTA cohort also achieved better sensory recovery and donor-site outcomes (Vancouver Scar Scale: 2.1 versus 4.3, P < 0.01). Despite higher initial imaging costs, 3D-CTA proved more cost-effective overall. Conclusions: For ALT flap reconstruction in limb defects, 3D-CTA provides superior perforator mapping, enhances surgical efficiency, improves clinical outcomes, and offers greater cost-effectiveness compared with CDUS. These findings support prioritizing 3D-CTA in preoperative planning for complex limb salvage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".