Purpose: Free-Breathing Fast Helical CT (FBFHCT) has enabled physical modeling of the lungs, such as ventilation mapping and elastography, to guide radiation treatment planning. However, the nature of FBFHCT provides information useful for applications outside of radiation oncology, such as downstream modeling to guide surgery. To realize these applications, the dose must be reduced to the diagnostic range. The aim of this project is to assess the feasibility of diagnostic dose FHFBCT for ventilation measurements by quantifying the difference in measured ventilation between CT protocols matching radiation oncology and diagnostic dose levels.
Methods: In this study, noise was injected into six 40mAs FBFHCT scans to simulate 20mAs images, correlating to total doses of 3.6mSv. The first image was arbitrarily selected to be the reference, and the other five were chosen based on simultaneous respiratory bellows signals that sufficiently sampled the range of breathing amplitudes, simulating prospective scanning. The images were registered to the reference image with the pTVreg algorithm. To assess the effect of the dose reduction on registration accuracy, the Jacobians and their fit to the breathing amplitudes (dJ/dA) were calculated for each voxel and compared between doses.
Results: Among the patient datasets, the mean absolute difference in the voxel-specific Jacobians between 40mAs and 20mAs scan sets was 0.031. 86.8% of voxels had an absolute Jacobian difference of 0.05 or less. The mean difference in dJ/dA between doses was 0.04 Jacobian per breath, and 80.3% of voxels were within 0.05.
Conclusion: We have measured the change in the Jacobians when reducing the image protocol dose to be acceptable, thus demonstrating that CTs in the diagnostic dose range can be used to correctly measure ventilation. This work opens the door to motion modeling, biomechanical modeling, and regional ventilation mapping outside of the radiotherapy domain.
Low-dose CT, Ventilation/perfusion, Lung
IM/TH- Image Analysis (Single Modality or Multi-Modality): Image registration