Developing 3D Lung Rendering Algorithms for Computational Modeling of Gene Therapy Drug-Delivery Routes for ARDS and Ventilator-Induced Lung Injury.
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Date
2024-05
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The Ohio State University
Abstract
Acute Respiratory Distress Syndrome (ARDS) is a severe condition defined by oxygen depletion and pulmonary edema. Mechanical ventilation, a common care method, can further exacerbate the damage created by ARDS by increasing inflammation and mechanical stress within the lungs. Thankfully, gene therapy technology has shown promise in mitigating inflammatory responses caused by ventilator-induced lung injury. Gene therapy for ARDS relies on successfully delivering aerosolized microRNA nanoparticles (which include miR-146a) to the injury site. The use of 3D computational models of damaged and healthy CT lung scans can help realize the effective drug-delivery route of miR-146a while minimizing pulmonary fluid occlusion. This project explores the use of three distinct algorithms for developing computationally compatible 3D lung models: active contours segmentation, trained neural network segmentation, and 3D spline lofting.
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Keywords
Acute Respiratory Distress Syndrome, Computational Modeling, Clinical Diagnostics, CT, Lung, Machine Learning, Neural Networks, CAD, FEA