Discrepancy between regional left ventricular regional circumferential strain assessed by MR-tagging and by speckle tracking echocardiography
Notice bibliographique
Résumé
Background: In recent years, myocardial strain imaging has gained an important place for the evaluation of cardiac patients. Global longitudinal strain assessed by speckle tracking echocardiography (STE) is now commonly used but circumferential strain remains less extensively studied. MR-tagging is recognized as the reference method for circum- ferential strain analysis, however no validation study between regional MR-tagging and regional STE has been performed up to now. Objective: To compare segmental circumferential strain values (Ecc) obtained by speckle tracking and by MR-tagging in patient with normal systolic function in order to define if both methods are interchangeable or not. Patients and methods: patients without significant regional nor global systolic dysfunction (LVEF > 55%) were studied by MR-tagging ( n =82) and by STE ( n =35). Left ventricular mid-level short axis slice was obtained by both methods and paired data were available in 16 patients. Segmental Ecc values were computed in six equidistant sectors using GE EchoPac software for STE and InTag post processing software for MR-tagging. Results: 1) Comparison between regions: Overall results showed that regional peak Ecc magnitude |Eccpeak| was not uniform with both methods but in an opposite way. MR-tagging demonstrated significantly lower septal |Eccpeak| as compared with postero-lateral |Eccpeak| (-16.5±3.6 vs -23.4±4.4, p <10 -4 ). Conversely, STE showed significantly higher septal |Eccpeak| as compared with postero-lateral |Eccpeak| (-22.3±6.4 vs -13.9±6.2, p <10 -4 ). 2) Comparison between both methods: In the subgroup of patients studied by both methods, septal |Eccpeak| was 29% lower by MR-tagging as compared with STE (-14.9±2.4 vs -20.9±6.5, p <.006) and postero-lateral |Eccpeak| was 39% lower by STE as compared with MR-tagging (-12.9±5.9 vs -21.0±2.9, p <.0003). 3) Intra and interobserver coefficients of variation were homogeneous (in the range 10%-14%) for all sectors with MR-tagging but were dramatically variable with STE (15% to 20% in the anterior-septal region but three times higher, in the range 35%-40%, in the postero-lateral territory). Conclusion: Regional distributions of Ecc is not uniform but opposite results are provided by MR-tagging and by STE. This finding demonstrates that both methods cannot be considered as interchangeable. These conflicting results raise the question of the validity of either MR tagging or speckle tracking for the quantification of regional circumferential strain. Some arguments, developed in the discussion would rather let believe that MR-tagging results should be more reliable.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».