Quantitative Analysis of 3D Anatomy to Inform Planning of Ductal Arteriosus Stenting

Abstract

Background: Ductus arteriosus stenting (DAS) is used to palliate infants with ductal-dependent pulmonary blood flow (DD-PBF), however patent ductus arteriosus (PDA) anatomy can be complex and heterogenous.

Aims: We developed custom, open-source software to model and quantify PDA anatomy.

Methods: We retrospectively identified 33 neonates with DD-PBF with a CTA before DAS. A novel custom workflow was implemented in 3D Slicer and SlicerHeart to semi-automatically extract centerlines of the course of the PDA and surrounding vessels. 3D ductal length, diameter, curvature and tortuosity were automatically calculated (3D automatic) and compared to manually adjusted 3D measurements (3D semi-automatic), and manual measurements of PDA dimensions in 2D projectional angiograms before and after stent angioplasty.

Results: Ductal anatomy was successfully modeled and quantified in all subjects. 3D automatic and semi-automatic measurements of straight-line aortic to pulmonary artery length were not significantly different than 2D measurements. Semi-automatic 3D measurements were similar to 2D measurements of the total length. Minimum and maximum ductal diameters were not significantly different by 3D automatic and 2D measurements, however semi-automatic 3D diameters were significantly larger. Inter-reader reliability of ductal length and diameter was higher with manual adjustment of 3D centerlines compared to standard measurement of 2D angiograms. These differences were consistent across PGE doses between CTA and DAS.

Conclusions: Automatic PDA modeling is feasible and efficient, enabling reproducible quantification of ductal anatomy for procedural planning of DAS in patients with DD-PBF. Further development is needed as well as investigation of whether 3D modeling-derived measurements influence procedural duration or outcome.

Keywords: 3D modeling; CT angiography; PDA stent; congenital heart disease; quantification.

Figure 1:

Image processing workflow for a patient with tricuspid atresia using a custom PDA quantification module created for 3D Slicer. (Steps 1, 2) CT angiogram obtained and imported to 3D Slicer to generate a whole vasculature segmentation. (Step 3) The segmentation is smoothed and cropped to visualize the PDA, aorta and pulmonary arteries. (Steps 4–5) The segmentation is imported to the SlicerHeart PDA Quantification module and vessel endpoints are selected to automatically extract the vessel centerlines using the vascular modeling toolkit VMTK). (Step 6) The PDA metrics are quantified and exported.

Figure 2.

PDA quantification metrics reported by the custom-built PDA Quantification module of SlicerHeart. A) Torsion. B) PDA total length. C) Curvature. D) Euclidian length (Aortic to pulmonary artery). E) Minimum (1) and maximum (2) diameters.

Figure 3.

I. Patient with left common carotid artery access. (a) All branch angles on PDA model (b) PDA to descending aorta angle (c) PDA to left common carotid artery (d) PDA to right common carotid artery II. Patient with right common carotid artery access. (a) All branch angles on PDA model (b) PDA to descending aorta (c) PDA to left subclavian artery (d) PDA to transverse aorta

Figure 4:

Extracted vessel centerlines in four patients with varying aortic arch anatomy. A) Highlighted PDA region with spheres indicating software-defined boundaries of the PDA for centerline extraction. B) Centerlines of left aortic arch with normal branching. C) Left aortic arch with common brachiocephalic trunk. D) Right aortic arch with mirror image branching.

Figure 5.

PDA lengths measured in three different modalities for one patient. A) 3D segmentation of CT angiogram data. B) Near-sagittal slice of CT angiogram. C) 2D angiogram from DAS procedure. Euclidean (blue arrow) and total (red arrow) PDA lengths are noted.

Figure 6:

Plot of 33 subjects comparing “minimum stented length” (gray) measured by post-DAS 2D angiography to Euclidean (blue) and total PDA lengths (orange) measured by 2D angiography, 3D semi-automatic or 3D automatic method.