Segmental Approach to Imaging of Congenital Heart Disease
Bibliographic record
Abstract
The segmental approach, which is widely used in the imaging work-up of congenital heart disease, consists of a three-step evaluation of the cardiac anatomy. In step 1, the visceroatrial situs is determined. Visceroatrial situs refers to the position of the atria in relation to the nearby anatomy (including the stomach, liver, spleen, and bronchi). Three different anatomic configurations may be observed: situs solitus (normal), situs inversus (inverted), or situs ambiguus (ambiguous). In step 2, the left- or rightward orientation of the ventricular loop is evaluated, and the positions of the ventricles are identified on the basis of their internal morphologic features. In step 3, the position of the great vessels is determined first, and any abnormalities are noted. Abnormalities in the origin of the great vessels, or conotruncal anomalies, are predominantly of three types: D-transposition (dextrotransposition), L-transposition (levotransposition), and D-malposition with double outlet right ventricle. Next, the relationships between the atria and ventricles and the ventricles and great vessels are determined at two levels: atrioventricular (concordant, discordant, ambiguous, double inlet, absence of right or left connection) and ventriculoarterial (concordant, discordant, double outlet). Last, a search is performed for any associated abnormalities of the cardiac chambers, septa, outflow tract, and great vessels. By executing these steps sequentially during image review, the radiologist can achieve a more accurate interpretation. Multiplanar reconstructions of cross-sectional image data obtained with computed tomography or magnetic resonance imaging are particularly useful for evaluating congenital heart disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".