Room: Room 207
Purpose: Virtual clinical trials (VCTs) provide a framework that enables quantification and evaluation of imaging systems using computer simulations. In this process, realistic models of scanners and patients are indispensable. We have recently developed a fast, scanner-specific CT simulator and a new generation of computational phantoms (XCAT) that include intra-organ heterogeneities modeled as textures. To further enhance the realism of our simulation platform, this study aimed to incorporate respiratory motion to these high-resolution phantoms for conducting VCTs in the context of free-breathing CT.
Methods: A parameterized respiratory motion model was developed based on respiratory mechanics and sets of respiratory-gated CT data of healthy patients. The new generation of XCAT phantoms, originally modeled in voxels, were converted into polygon meshes. The patient-derived respiratory motion profiles were assigned to these meshes to generate the phantoms at different time points within the respiratory cycle. In the case of sparse motion vectors, a smoothing algorithm was applied to generate motion vectors for all the intra-organ heterogeneities defined within the phantoms. To qualitatively evaluate the process, the resulting phantoms were imaged using our CT simulator (based on Siemens-Flash) under free-breathing and breadth-hold protocols.
Results: Qualitatively, our method was successful in applying realistic respiratory motion to the new generation of phantoms. Since our motion model was parametric, we were able to generate respiratory motion profiles with variable diaphragm movement and chest expansion curves, and respiratory rates. This flexibility enables the generation of phantoms and further simulating CT images with variable respiratory attributes such as lung parenchyma density variations and organ positions under free-breathing conditions.
Conclusion: We developed a framework to incorporate respiratory motion to the new generation of XCAT phantoms that include intra-organ heterogeneities. This toolset, combined with our recently developed CT simulator, facilitates comprehensive image quality-based evaluation and quantification of CT systems in free-breathing conditions.
Funding Support, Disclosures, and Conflict of Interest: Ehsan Samei: Unrelated to this study, active reseach grants with Siemens and GE and advisory board member of medInt Holdings, LLC. Nothing else to disclose.