Cardiac computed tomography based analysis of mitral annulus, coronary sinus and left circumflex artery in patients with mitral regurgitation: Implications for transcatheter mitral annuloplasty techniques
Bibliographic record
Abstract
INTRODUCTION: CT imaging analysis of mitral annulus (MA), coronary sinus (CS) and left circumflex artery (LCX) is critical to transcatheter mitral annuloplasty (TMA), which, however, is scantly reported. We aimed to comprehensively assess MA, CS and LCX anatomy and geometry in mitral regurgitation (MR) based on 3-D reconstruction of cardiac CT images. METHODS: Patients with primary or secondary MR and patients without MR were recruited and underwent cardiac CT examination. MR severity was evaluated by echocardiography. 3-D reconstruction of cardiac CT images was done by the Mimics Research 21.0 software. A MA-centered two dimensional coordinate system, a CS plane, a MA plane and a series of auxiliary planes along the posterior MA were created for the measurement of parameters defining MA, CS and LCX anatomy and geometry during the cardiac cycle. RESULTS: The secondary MR group had a significantly higher MA perimeter index than the other two groups during the cardiac cycle. The CS diameters at most sites, and the posterior MA radian were substantially greater in the two MR groups. Distances between the CS and MA at some locations were significant different among the three groups. The secondary MR group had a significantly smaller CS-MA plane angle than the other two groups during systole, and than control group during diastole. The site where the CS crossed LCX was pinpointed. CONCLUSION: The comprehensive information from this study may help improve the results of TMA and enhance the design of devices for a better annuloplasty effect.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".