Type II Endoleak after Endoaortic Graft Implantation: Diagnosis with Helical CT Arteriography
Bibliographic record
Abstract
PURPOSE: To retrospectively assess endoleak shapes and locations within aneurysms to differentiate type II from type I and type III endoleaks. MATERIALS AND METHODS: The institutional review board granted an exemption for this HIPAA-compliant study; patient informed consent was not required. A retrospective review of arterial phase helical computed tomographic (CT) studies and medical records was performed for 39 patients (29 men, 10 women; age range, 60-89 years; mean, 78.5 years) who had an endoleak after endoaortic graft implantation for treatment of abdominal aortic aneurysm and who subsequently underwent angiography (n = 25), surgery (n = 8), or long-term follow-up (n = 6) to classify their endoleak into a specific type. At CT, endoleak shape (tubular or nontubular) and location (central or peripheral) were recorded. An endoleak was classified as type II if it contained a peripheral tubular component (PTC) near the aortic wall, with or without an identifiable feeding vessel. Endoleaks without these features were classified as type I or III. The Fisher exact test was used to assess associations between CT findings and endoleak type. RESULTS: There were 22 type II and 17 type I or III endoleaks. CT enabled correct identification of 22 (100%) of 22 type II endoleaks, all of which contained a PTC. Of 17 type I or III endoleaks, only two (12%) contained a PTC and were misclassified as type II endoleaks; the remaining 15 (88%) were correctly classified. Overall, CT enabled correct identification of endoleaks as type II or type I or III in 37 (95%) of 39 patients. PTCs were significantly more common (P < .001) in type II than in type I or III endoleaks, with a sensitivity, specificity, accuracy, negative predictive value, and positive predictive value of 100%, 88.2%, 94.9%, 100%, and 91.7%, respectively. CONCLUSION: A PTC is a statistically significant predictor of type II endoleak in most patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".