3d Models Of Pediatric Sinus And Atrioventricular Nodal Regions: A Tool For Guiding Congenital Heart Surgery
Brian Cottle, Masters1, Robert Hitchcock, Ph.D.1, Aditya Kaza, MD, MBA2, Frank Sachse, Ph.D.1, Abhijit Mondal2.
1University of Utah, Salt Lake City, UT, USA, 2Boston Children's Hospital, Boston, MA, USA.
Objective(s): Iatrogenic damage to the cardiac conduction system (CCS) remains a significant risk during congenital heart surgery. Current surgical best practice involves using superficial anatomical landmarks to locate and avoid damaging the CCS. Prior work indicates inherent variability in the anatomy of the CCS and supporting tissues. This study introduces high-resolution, 3D models of the CCS in normal pediatric human hearts to evaluate variability in the nodes and surrounding structures.
Methods: Human pediatric hearts were obtained with an average donor age of 2.7 days. A pipeline was developed to excise, section, stain, and image atrioventricular (AVN) and sinus (SN) nodal tissue regions. A convolutional neural network (CNN) was trained to enable precise multi-class segmentation of whole-slide images, which were subsequently used to generate high-resolution 3D tissue models.
Results: Nodal tissue region models were created (11 AVN, 8 SN). All models contain tissue composition information on cardiac muscle, connective tissue, nuclear density, neural tissue, vasculature, and nodal tissues at micrometer resolution. AVN models also contain information on the individual components including the compact node, His bundle, and left and right bundle branches.
Conclusions: The inclusion of CNNs in the image processing pipeline enabled high-resolution segmentation of finely detailed structures in the nodal regions. Neural, vascular, and nodal structures such as the Bundle of His were accurately represented. These models provide surgeons with insight into the heterogeneity of the nodal regions and the intricate relationships between the CCS and the surrounding vascular and neural structures.
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