O-2 | Development of a 3D Modeling Tool for Procedural Planning of Ductal Stenting
Notice bibliographique
Résumé
BackgroundDuctus arteriosus stenting (DAS) is an important palliative option for infants with ductal-dependent pulmonary blood flow (DD-PBF). However, assessment of patient candidacy and pre-procedural planning are complicated by complex PDA anatomy that is difficult to characterize by standard echocardiography. We aimed to develop a novel tool for 3D modeling and quantification of PDA structure using CT angiographic (CTA) images to inform interventional planning.MethodsWe identified 33 infants with DD-PBF who had a CTA followed by DAS. The CTA vascular anatomy was visualized and segmented in 3D Slicer. A custom python-scripted module was built to semi-automatically extract centerlines of the vascular tree of the ductus and surrounding vessels (A). Metrics of ductal length, diameter, curvature, and tortuosity were automatically calculated (B,C), and retrospectively compared to 2D projectional angiograms (D).ResultsThe ductal anatomy was successfully modeled and quantified in all. 3D modeling generated a shorter total ductal length than the 2D measurements [median 14.9mm (IQR 9.8-16.5mm) vs 16.3mm (IQR 11.3-18.4mm), p<0.001] and shorter aortic ampulla to PA length [median 7.2mm (IQR 6.3-9.2mm) vs 9.2mm (IQR 7.5-11.1mm), p<0.002]. Maximum ductal diameters were similar [median 4.6mm (IQR 3.6-5.3mm) vs 4.8mm (IQR 4.0-5.4mm), p=0.76].ConclusionsDisclosuresM. Gupta Nothing to disclose. C. Pinter Nothing to disclose. A. Cianciulli Nothing to disclose. H. Dewey Nothing to disclose. S. Amin Nothing to disclose. A. Lasso Nothing to disclose. M. L. O'Byrne Nothing to disclose. A. C. Glatz Nothing to disclose. M. Jolley Nothing to disclose. BackgroundDuctus arteriosus stenting (DAS) is an important palliative option for infants with ductal-dependent pulmonary blood flow (DD-PBF). However, assessment of patient candidacy and pre-procedural planning are complicated by complex PDA anatomy that is difficult to characterize by standard echocardiography. We aimed to develop a novel tool for 3D modeling and quantification of PDA structure using CT angiographic (CTA) images to inform interventional planning. Ductus arteriosus stenting (DAS) is an important palliative option for infants with ductal-dependent pulmonary blood flow (DD-PBF). However, assessment of patient candidacy and pre-procedural planning are complicated by complex PDA anatomy that is difficult to characterize by standard echocardiography. We aimed to develop a novel tool for 3D modeling and quantification of PDA structure using CT angiographic (CTA) images to inform interventional planning. MethodsWe identified 33 infants with DD-PBF who had a CTA followed by DAS. The CTA vascular anatomy was visualized and segmented in 3D Slicer. A custom python-scripted module was built to semi-automatically extract centerlines of the vascular tree of the ductus and surrounding vessels (A). Metrics of ductal length, diameter, curvature, and tortuosity were automatically calculated (B,C), and retrospectively compared to 2D projectional angiograms (D). We identified 33 infants with DD-PBF who had a CTA followed by DAS. The CTA vascular anatomy was visualized and segmented in 3D Slicer. A custom python-scripted module was built to semi-automatically extract centerlines of the vascular tree of the ductus and surrounding vessels (A). Metrics of ductal length, diameter, curvature, and tortuosity were automatically calculated (B,C), and retrospectively compared to 2D projectional angiograms (D). ResultsThe ductal anatomy was successfully modeled and quantified in all. 3D modeling generated a shorter total ductal length than the 2D measurements [median 14.9mm (IQR 9.8-16.5mm) vs 16.3mm (IQR 11.3-18.4mm), p<0.001] and shorter aortic ampulla to PA length [median 7.2mm (IQR 6.3-9.2mm) vs 9.2mm (IQR 7.5-11.1mm), p<0.002]. Maximum ductal diameters were similar [median 4.6mm (IQR 3.6-5.3mm) vs 4.8mm (IQR 4.0-5.4mm), p=0.76]. The ductal anatomy was successfully modeled and quantified in all. 3D modeling generated a shorter total ductal length than the 2D measurements [median 14.9mm (IQR 9.8-16.5mm) vs 16.3mm (IQR 11.3-18.4mm), p<0.001] and shorter aortic ampulla to PA length [median 7.2mm (IQR 6.3-9.2mm) vs 9.2mm (IQR 7.5-11.1mm), p<0.002]. Maximum ductal diameters were similar [median 4.6mm (IQR 3.6-5.3mm) vs 4.8mm (IQR 4.0-5.4mm), p=0.76]. Conclusions DisclosuresM. Gupta Nothing to disclose. C. Pinter Nothing to disclose. A. Cianciulli Nothing to disclose. H. Dewey Nothing to disclose. S. Amin Nothing to disclose. A. Lasso Nothing to disclose. M. L. O'Byrne Nothing to disclose. A. C. Glatz Nothing to disclose. M. Jolley Nothing to disclose. M. Gupta Nothing to disclose. C. Pinter Nothing to disclose. A. Cianciulli Nothing to disclose. H. Dewey Nothing to disclose. S. Amin Nothing to disclose. A. Lasso Nothing to disclose. M. L. O'Byrne Nothing to disclose. A. C. Glatz Nothing to disclose. M. Jolley Nothing to disclose.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,138 |
| Bibliométrie | 0,000 | 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».