Anatomical & Imaging Measures of the Left Ventricular Apical Thinning
Bibliographic record
Abstract
Doing the heart three-dimensional CT imaging (3DCT), the writers found 3DCT can clearly show the left ventricular apical thinning (LVAT). Purpose: To observe the shape of LVAT and measure related parameters in the end-systolic and end-diastolic phases. Methods: 12 cadaveric heart specimens were observed, and the thickness of LVAT was measured, as well as the thickest myocardium of left ventricle (TMLV). There are 69 cases imaging data of the end-systolic and end-diastolic phases without heart diseases from PACS in our hospital, with multiplanar reconstruction (MPR), Volume rendering (VR), the LVAT was clearly shown and measured. Measuring parameters include the thickness of LVAT, TMLV and the distance between the LVAT and the anterior descending branch of left coronary artery (DBLCA). Statistical comparisons were made. Results: In all cadaveric heart specimens of 12 cases were found the LVAT, the thickness of LVAT, TMLV was 1.74 mm ± 0.32 mm, 13.07 mm ± 1.48 mm. 3DCT clearly showed the LVAT in the 69 cases, whose thickness was 1.17 mm ± 0.43 mm in the diastole phase and 1.19 mm ± 0.48 mm in the systole phase. The thickness of TMLV was 12.02 mm ± 1.66mm, and the distance between the LVAT and DBLCA was 13.70mm ± 3.78 mm in the diastole phase. There were not significant differences in the LVAT thickness between systole and diastole phases (t = 0.366, p > 0.5), but there are significant differences in measuring the thickness of myocardium between the anatomy and 3DCT (t = 2.210, 0.01< P<0.05). Conclusion: The LVAT can be clearly shown by anatomy and 3DCT, and its thickness does not change in the end-systolic and end-diastolic phases.
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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 | 0.001 |
| 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) | 0.001 | 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 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".