Multimodality Imaging of Aortic Dimensions: Comparison of Transthoracic Echocardiography with Multidetector Row Computed Tomography
Bibliographic record
Abstract
BACKGROUND: With recent advances in multimodality cardiac imaging, a number of methods exist for the noninvasive assessment of aortic disease. Although multidetector row computed tomography (MDCT) remains the gold standard for aortic measurements, there are a number of limitations including radiation and contrast-induced nephropathy. Transthoracic echocardiography (TTE) is an alternative to MDCT for providing accurate anatomic assessment of aortic root and ascending aorta dimensions. OBJECTIVES AND METHODS: To determine the accuracy of two-dimensional (2D) TTE for determining aortic measurements in comparison to MDCT, a retrospective study of individuals with varying aortic root and ascending aorta dimensions was performed. RESULTS: There were 116 patients (77 males, mean age 49 ± 12 years) in total. The maximum aortic diameters by 2D TTE were 26.1 ± 4.3 mm (annulus), 32.4 ± 5.6 mm (sinuses), 30.1 ± 5.9 mm (sinotubular [ST] junction), and 33.4 ± 7.3 mm (ascending aorta). The maximum aortic diameters by MDCT were 30.1 ± 4.1 mm (annulus), 35.8 ± 5.8 mm (sinuses), 33.2 ± 5.9 mm (ST junction), and 37.4 ± 7.6 mm (ascending aorta). There was good to excellent correlation between 2D TTE and MDCT at all four levels of the aorta (annulus: r = 0.84; sinuses: r = 0.93; ST junction: r = 0.93; ascending aorta: r = 0.88). There was a consistent underestimation of aortic measurements obtained by 2D TTE when compared to MDCT. CONCLUSION: 2DTTE is a feasible, accurate, and reproducible method for the noninvasive assessment of thoracic aortic diameters as compared to MDCT.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".