Author: Christopher A. Aguilera, Hunter Tillery, Cheyann Windsor 👨🔬
Affiliation: Oregon Health & Science University, Northwest Medical Physics Center 🌍
Purpose: To demonstrate a method of acquiring 4DCT commissioning datasets for deviceless 4DCT which relies on an image-based algorithm instead of an external breathing signal for 4D image binning. The deviceless algorithm is designed for human anatomy and as such commercially available dynamic phantoms that would typically be used for 4DCT commissioning are incompatible.
Methods: A dynamic thorax phantom was slightly modified to be compatible with the deviceless 4D algorithm by cantilevering a 3D printed external rind from the surrogate platform to extend over the thorax. With these modifications 4DCT commissioning datasets were acquired with 3, 5, and 7 second Cos6 regular breathing patterns. Additionally, 3 irregular breathing patterns with: irregular amplitude, irregular frequency, and a combination of both irregular frequency and amplitude were also acquired. These same commissioning datasets were also acquired using device based 4DCT means for further comparison. Dosimetric end to end measurements were conducted with an ionization chamber using both regular and irregular breathing patterns.
Results: Deviceless 4DCT binning methods proved to be on par with published commissioning recommendations for both regular and irregular datasets. As datasets became more irregular, the datasets binned with the deviceless algorithm showed improvements over those binned with conventional device based 4DCTs.
Conclusion: Commissioning datasets were acquired for deviceless 4DCT with a modified commercially available dynamic thorax phantom. These acquired datasets were compared with published commissioning guidelines for 4DCT. Device based 4DCT datasets were compared to the deviceless datasets. Differences in binning methods highlighted situations where deviceless datasets may be more favorable in patients with highly irregular breathing patterns.