Quantitative Assessment of Abdominal Aortic Aneurysm Geometry and Rupture Potential
Bibliographic record
Abstract
Recent biomechanics studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) and its expansion rate are not reliable indicators of rupture potential. We hypothesize that geometrical shape and size, as well as wall thickness may be related to rupture risk and can therefore be deciding factors in the clinical management of the disease. A non-invasive, image-based evaluation of AAA size and geometry was implemented on a retrospective study of twenty subjects. The contrast enhanced, computed tomography (CT) scans of 10 patients who suffered AAA rupture within 1 month of the scan were compared to those of 10 patients who received elective repair. The images were segmented and three-dimensional models were generated. Twenty-eight geometry-based indices were calculated to characterize the size and shape of each AAA and regional variations in wall thickness were estimated. A multivariate analysis of variance was performed for all indices comparing the ruptured and non-ruptured data sets to determine which indices are statistically significant. Receiving Operating Characteristic (ROC) curves were generated to determine the indices’ potential as predictors of rupture risk. In addition to maximum diameter, five other geometry-based indices were found to be statistically significant, with the minimum wall thickness being the best discriminator between ruptures and non-ruptured AAAs.
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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".