O-2 | Development of a 3D Modeling Tool for Procedural Planning of Ductal Stenting
Bibliographic record
Abstract
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.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.138 |
| 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) | 0.000 | 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".